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Doing good by doing bad
(2022)
This study investigates how tone at the top, implemented by top management, and tone at the bottom, in an employee's immediate work environment, determine noncompliance. We focus on the disallowed actions of employees that improve their own and, in turn, the company's performance, referred to as performance-improving noncompliant behavior (PINC behavior). We conduct a survey of German sales employees to investigate specifically how, on the one hand, (1) corporate rules and (2) performance pressure, both implemented by top management, and, on the other hand, (3) others' PINC expectations and (4) others' PINC behavior, both arising from the employee's immediate work environment, influence PINC behavior. When considered in isolation, we find that corporate rules, as top management's main instrument to guide employee behavior, decrease employee PINC behavior. However, this effect is negatively influenced by the employees' immediate work environment when employees are expected to engage in PINC or when others engage in PINC. In contrast, even though top management places great performance pressure on employees, that by itself does not increase PINC behavior. Overall, our study informs practitioners and researchers about whether and how the four determinants increase or decrease employees' PINC behavior, which is important to comprehend triggers and to counteract such misconduct.
Sharing marketplaces emerged as the new Holy Grail of value creation by enabling exchanges between strangers. Identity reveal, encouraged by platforms, cuts both ways: While inducing pre-transaction confidence, it is suspected of backfiring on the information senders with its discriminative potential. This study employs a discrete choice experiment to explore the role of names as signifiers of discriminative peculiarities and the importance of accompanying cues in peer choices of a ridesharing offer. We quantify users' preferences for quality signals in monetary terms and evidence comparative disadvantage of Middle Eastern descent male names for drivers and co-travelers. It translates into a lower willingness to accept and pay for an offer. Market simulations confirm the robustness of the findings. Further, we discover that females are choosier and include more signifiers of involuntary personal attributes in their decision-making. Price discounts and positive information only partly compensate for the initial disadvantage, and identity concealment is perceived negatively.
Nowadays, production planning and control must cope with mass customization, increased fluctuations in demand, and high competition pressures. Despite prevailing market risks, planning accuracy and increased adaptability in the event of disruptions or failures must be ensured, while simultaneously optimizing key process indicators. To manage that complex task, neural networks that can process large quantities of high-dimensional data in real time have been widely adopted in recent years. Although these are already extensively deployed in production systems, a systematic review of applications and implemented agent embeddings and architectures has not yet been conducted. The main contribution of this paper is to provide researchers and practitioners with an overview of applications and applied embeddings and to motivate further research in neural agent-based production. Findings indicate that neural agents are not only deployed in diverse applications, but are also increasingly implemented in multi-agent environments or in combination with conventional methods — leveraging performances compared to benchmarks and reducing dependence on human experience. This not only implies a more sophisticated focus on distributed production resources, but also broadening the perspective from a local to a global scale. Nevertheless, future research must further increase scalability and reproducibility to guarantee a simplified transfer of results to reality.
Algorithmic management
(2022)
Entrepreneurial failure
(2022)
Although entrepreneurial failure (EF) is a fairly recent topic in entrepreneurship literature, the number of publications has been growing dynamically and particularly rapidly. Our systematic review maps and integrates the research on EF based on a multi-method approach to give structure and consistency to this fragmented field of research. The results reveal that the field revolves around six thematic clusters of EF: 1) Soft underpinnings of EF, 2) Contextuality of EF, 3) Perception of EF, 4) Two-sided effects of EF, 5) Multi-stage EF effects, and 6) Institutional drivers of EF. An integrative framework of the positive and negative effects of entrepreneurial failure is proposed, and a research agenda is suggested.
Long-term value creation is expected not only to be concerned with maximizing shareholder value but also includes the impact on other stakeholders and the environment. Environmental, social, and governance (ESG) issues are therefore gaining increasing importance, in line with the growing demand for corporate sustainability. ESG ratings foster the comparison of companies with respect to their sustainable practices. This study aims to investigate how ESG ratings impact financial performance in the European food industry. Ordinary least squares regression is applied to analyze the relation between ESG ratings and financial performance over a 4-year period from 2017 to 2020. The profitability measures Return on Assets (ROA) and Return on Equity (ROE) are employed as financial performance measures, while ESG ratings are obtained from the database CSRHub. Results show that higher ESG ratings are associated with better financial performance. Although the effect is modest in the present study, the findings support previous results that ESG ratings are positively related to financial performance. Nonetheless, they also highlight that ESG ratings strongly converge to the mean, which depicts the need to reassess whether ESG ratings are able to measure actual ESG behavior.
The organisation of legislative chambers and the consequences of parliamentary procedures have been among the most prominent research questions in legislative studies. Even though democratic elections not only lead to the formation of a government but also result in an opposition, the literature has mostly neglected oppositions and their role in legislative chambers. This paper proposes to fill this gap by looking at the legislative organisation from the perspective of opposition players. The paper focuses on the potential influence of opposition players in the policy-making process and presents data on more than 50 legislative chambers. The paper shows considerable variance of the formal power granted to opposition players. Furthermore, the degree of institutionalisation of opposition rights is connected to electoral systems and not necessarily correlated with other institutional characteristics such as regime type or the size of legislative chambers.
Enterprise systems have long played an important role in businesses of various sizes. With the increasing complexity of today’s business relationships, pecialized application systems are being used more and more. Moreover, emerging technologies such as artificial intelligence are becoming accessible for enterprise systems. This raises the question of the future role of enterprise systems. This minitrack covers novel ideas that contribute to and shape the future role of enterprise systems with five contributions.
Findings in the extant literature are mixed concerning when and how gender diversity benefits team performance. We develop and test a model that posits that gender-diverse teams outperform gender-homogeneous teams when perceived time pressure is low, whereas the opposite is the case when perceived time pressure is high. Drawing on the categorization-elaboration model (CEM; van Knippenberg, De Dreu, & Homan, 2004), we begin with the assumption that information elaboration is the process whereby gender diversity fosters positive effects on team performance. However, also in line with the CEM, we argue that this process can be disrupted by adverse team dynamics. Specifically, we argue that as time pressure increases, higher gender diversity leads to more team withdrawal, which, in turn, moderates the positive indirect effect of gender diversity on team performance via information elaboration such that this effect becomes weaker as team withdrawal increases. In an experimental study of 142 four-person teams, we found support for this model that explains why perceived time pressure affects the performance of gender-diverse teams more negatively than that of gender-homogeneous teams. Our study sheds new light on when and how gender diversity can become either an asset or a liability for team performance.
Entrepreneurship education (EE) has attracted much scholarly attention, showing exponential growth in publication and citation numbers. The research field has become broad, complex, and fragmented, making it increasingly difficult to oversee. Our research goal is to organise and integrate the previous literature. To this end, we use bibliometric analyses, differing from prior analyses, which are outdated or have a different focus. Our results show an immense growth in publications and citations over the last decade and an almost equal involvement of business and educational research. We identify the most productive and influential journals and authors. Our co-citation analysis reveals two research clusters, one focusing on psychological constructs relating to EE, and the other on entrepreneurial behaviour and new venture creation. Based on a review of the 25 most-cited articles on an annual basis, we identify and quantify the most relevant research themes and integrate them into a research framework that we propose for future research. A major finding is that extant research centres around the outcomes of entrepreneurship education, whereas its pedagogy is still mainly a black box.
Real options are widely applied in strategic and operational decision-making, allowing for managerial flexibility in uncertaincontexts. Increased scholarly interest has led to an extensive but fragmented research landscape. We aim to measure andsystematize the research field quantitatively. To achieve this goal, we conduct bibliometric performance analyses and bibliographiccoupling analyses with an in-depth content review. The results of the performance analyses show an increasing interest in realoptions since the beginning of the 2000s and identify the most influential journals and authors. The science mappings reveal sixand seven research clusters over the last two decades. Based on an in-depth analysis of their themes, we develop a researchframework comprising antecedents, application areas, internal and external contingencies, and uncertainty resolution throughreal option valuation or reasoning. We identify several gaps in that framework, which we propose to tackle in future research.
Diet analysis of bats killed at wind turbines suggests large-scale losses of trophic interactions
(2022)
Agricultural practice has led to landscape simplification and biodiversity decline, yet recently, energy-producing infrastructures, such as wind turbines, have been added to these simplified agroecosystems, turning them into multi-functional energy-agroecosystems. Here, we studied the trophic interactions of bats killed at wind turbines using a DNA metabarcoding approach to shed light on how turbine-related bat fatalities may possibly affect local habitats. Specifically, we identified insect DNA in the stomachs of common noctule bats (Nyctalus noctula) killed by wind turbines in Germany to infer in which habitats these bats hunted. Common noctule bats consumed a wide variety of insects from different habitats, ranging from aquatic to terrestrial ecosystems (e.g., wetlands, farmland, forests, and grasslands). Agricultural and silvicultural pest insects made up about 20% of insect species consumed by the studied bats. Our study suggests that the potential damage of wind energy production goes beyond the loss of bats and the decline of bat populations. Bat fatalities at wind turbines may lead to the loss of trophic interactions and ecosystem services provided by bats, which may add to the functional simplification and impaired crop production, respectively, in multi-functional ecosystems.
The development of speaking competence is widely regarded as a central aspect of second language (L2) learning. It may be questioned, however, if the currently predominant ways of conceptualising the term fully satisfy the complexity of the construct: Although there is growing recognition that language primarily constitutes a tool for communication and participation in social life, as yet it is rare for conceptualisations of speaking competence to incorporate the ability to inter-act and co-construct meaning with co-participants. Accordingly, skills allowing for the successful accomplishment of interactional tasks (such as orderly speaker change, and resolving hearing and understanding trouble) also remain largely unrepresented in language teaching and assessment. As fostering the ability to successfully use the L2 within social interaction should arguably be a main objective of language teaching, it appears pertinent to broaden the construct of speaking competence by incorporating interactional competence (IC). Despite there being a growing research interest in the conceptualisation and development of (L2) IC, much of the materials and instruments required for its teaching and assessment, and thus for fostering a broader understanding of speaking competence in the L2 classroom, still await development. This book introduces an approach to the identification of candidate criterial features for the assessment of EFL learners’ L2 repair skills. Based on a corpus of video-recorded interaction between EFL learners, and following conversation-analytic and interactional-linguistic methodology as well as drawing on basic premises of research in the framework of Conversation Analysis for Second Language Acquisition, differences between (groups of) learners in terms of their L2 repair conduct are investigated through qualitative and inductive analyses. Candidate criterial features are derived from the analysis results. This book does not only contribute to the operationalisation of L2 IC (and of L2 repair skills in particular), but also lays groundwork for the construction of assessment scales and rubrics geared towards the evaluation of EFL learners’ L2 interactional skills.
Knowledge graphs are structured repositories of knowledge that store facts
about the general world or a particular domain in terms of entities and
their relationships. Owing to the heterogeneity of use cases that are served
by them, there arises a need for the automated construction of domain-
specific knowledge graphs from texts. While there have been many research
efforts towards open information extraction for automated knowledge graph
construction, these techniques do not perform well in domain-specific settings.
Furthermore, regardless of whether they are constructed automatically from
specific texts or based on real-world facts that are constantly evolving, all
knowledge graphs inherently suffer from incompleteness as well as errors in
the information they hold.
This thesis investigates the challenges encountered during knowledge graph
construction and proposes techniques for their curation (a.k.a. refinement)
including the correction of semantic ambiguities and the completion of missing
facts. Firstly, we leverage existing approaches for the automatic construction
of a knowledge graph in the art domain with open information extraction
techniques and analyse their limitations. In particular, we focus on the
challenging task of named entity recognition for artwork titles and show
empirical evidence of performance improvement with our proposed solution
for the generation of annotated training data.
Towards the curation of existing knowledge graphs, we identify the issue of
polysemous relations that represent different semantics based on the context.
Having concrete semantics for relations is important for downstream appli-
cations (e.g. question answering) that are supported by knowledge graphs.
Therefore, we define the novel task of finding fine-grained relation semantics
in knowledge graphs and propose FineGReS, a data-driven technique that
discovers potential sub-relations with fine-grained meaning from existing pol-
ysemous relations. We leverage knowledge representation learning methods
that generate low-dimensional vectors (or embeddings) for knowledge graphs
to capture their semantics and structure. The efficacy and utility of the
proposed technique are demonstrated by comparing it with several baselines
on the entity classification use case.
Further, we explore the semantic representations in knowledge graph embed-
ding models. In the past decade, these models have shown state-of-the-art
results for the task of link prediction in the context of knowledge graph comple-
tion. In view of the popularity and widespread application of the embedding
techniques not only for link prediction but also for different semantic tasks,
this thesis presents a critical analysis of the embeddings by quantitatively
measuring their semantic capabilities. We investigate and discuss the reasons
for the shortcomings of embeddings in terms of the characteristics of the
underlying knowledge graph datasets and the training techniques used by
popular models.
Following up on this, we propose ReasonKGE, a novel method for generating
semantically enriched knowledge graph embeddings by taking into account the
semantics of the facts that are encapsulated by an ontology accompanying the
knowledge graph. With a targeted, reasoning-based method for generating
negative samples during the training of the models, ReasonKGE is able to
not only enhance the link prediction performance, but also reduce the number
of semantically inconsistent predictions made by the resultant embeddings,
thus improving the quality of knowledge graphs.
The “HPI Future SOC Lab” is a cooperation of the Hasso Plattner Institute (HPI) and industry partners. Its mission is to enable and promote exchange and interaction between the research community and the industry partners.
The HPI Future SOC Lab provides researchers with free of charge access to a complete infrastructure of state of the art hard and software. This infrastructure includes components, which might be too expensive for an ordinary research environment, such as servers with up to 64 cores and 2 TB main memory. The offerings address researchers particularly from but not limited to the areas of computer science and business information systems. Main areas of research include cloud computing, parallelization, and In-Memory technologies.
This technical report presents results of research projects executed in 2018. Selected projects have presented their results on April 17th and November 14th 2017 at the Future SOC Lab Day events.
During his trip to New Spain in 1803, Alexander von Humboldt visited large tracts of New Spanish territory, which includes modern Mexico and part of the United States. This trip provided the data for his geographical Atlas of the region, as well as information about the ancient Mexican cultures that he would later include in the general Atlas and in other major works, such as Vues des Cordillères. Likewise, Humboldt’s Political Essay on the Kingdom of New Spain displayed a comprehensive physical, natural, economic, and social description of Mexico in the colonial period, which will also be analysed. With these works, Humboldt presented a new geographical and cultural image of New Spain to the European audiences. In addition to this, his work made important contributions to cartographic knowledge.
Distances affect economic decision-making in numerous situations. The time at which we make a decision about future consumption has an impact on our consumption behavior. The spatial distance to employer, school or university impacts the place where we live and vice versa. The emotional closeness to other individuals influences our willingness to give money to them. This cumulative thesis aims to enrich the literature on the role of distance for economic decision-making. Thereby, each of my research projects sheds light on the impact of one kind of distance for efficient decision-making.
The Antarctic ice sheet is the largest freshwater reservoir worldwide. If it were to melt completely, global sea levels would rise by about 58 m. Calculation of projections of the Antarctic contribution to sea level rise under global warming conditions is an ongoing effort which
yields large ranges in predictions. Among the reasons for this are uncertainties related to the physics of ice sheet modeling. These
uncertainties include two processes that could lead to runaway ice retreat: the Marine Ice Sheet Instability (MISI), which causes rapid grounding line retreat on retrograde bedrock, and the Marine Ice Cliff Instability (MICI), in which tall ice cliffs become unstable and calve off, exposing even taller ice cliffs.
In my thesis, I investigated both marine instabilities (MISI and MICI) using the Parallel Ice Sheet Model (PISM), with a focus on MICI.
An important goal in biotechnology and (bio-) medical research is the isolation of single cells from a heterogeneous cell population. These specialised cells are of great interest for bioproduction, diagnostics, drug development, (cancer) therapy and research. To tackle emerging questions, an ever finer differentiation between target cells and non-target cells is required. This precise differentiation is a challenge for a growing number of available methods.
Since the physiological properties of the cells are closely linked to their morphology, it is beneficial to include their appearance in the sorting decision. For established methods, this represents a non addressable parameter, requiring new methods for the identification and isolation of target cells. Consequently, a variety of new flow-based methods have been developed and presented in recent years utilising 2D imaging data to identify target cells within a sample. As these methods aim for high throughput, the devices developed typically require highly complex fluid handling techniques, making them expensive while offering limited image quality.
In this work, a new continuous flow system for image-based cell sorting was developed that uses dielectrophoresis to precisely handle cells in a microchannel. Dielectrophoretic forces are exerted by inhomogeneous alternating electric fields on polarisable particles (here: cells). In the present system, the electric fields can be switched on and off precisely and quickly by a signal generator. In addition to the resulting simple and effective cell handling, the system is characterised by the outstanding quality of the image data generated and its compatibility with standard microscopes. These aspects result in low complexity, making it both affordable and user-friendly.
With the developed cell sorting system, cells could be sorted reliably and efficiently according to their cytosolic staining as well as morphological properties at different optical magnifications. The achieved purity of the target cell population was up to 95% and about 85% of the sorted cells could be recovered from the system. Good agreement was achieved between the results obtained and theoretical considerations. The achieved throughput of the system was up to 12,000 cells per hour. Cell viability studies indicated a high biocompatibility of the system.
The results presented demonstrate the potential of image-based cell sorting using dielectrophoresis. The outstanding image quality and highly precise yet gentle handling of the cells set the system apart from other technologies. This results in enormous potential for processing valuable and sensitive cell samples.
Pictures are a medium that helps make the past tangible and preserve memories. Without context, they are not able to do so. Pictures are brought to life by their associated stories. However, the older pictures become, the fewer contemporary witnesses can tell these stories.
Especially for large, analog picture archives, knowledge and memories are spread over many people. This creates several challenges: First, the pictures must be digitized to save them from decaying and make them available to the public. Since a simple listing of all the pictures is confusing, the pictures should be structured accessibly. Second, known information that makes the stories vivid needs to be added to the pictures. Users should get the opportunity to contribute their knowledge and memories. To make this usable for all interested parties, even for older, less technophile generations, the interface should be intuitive and error-tolerant.
The resulting requirements are not covered in their entirety by any existing software solution without losing the intuitive interface or the scalability of the system.
Therefore, we have developed our digital picture archive within the scope of a bachelor project in cooperation with the Bad Harzburg-Stiftung. For the implementation of this web application, we use the UI framework React in the frontend, which communicates via a GraphQL interface with the Content Management System Strapi in the backend. The use of this system enables our project partner to create an efficient process from scanning analog pictures to presenting them to visitors in an organized and annotated way. To customize the solution for both picture delivery and information contribution for our target group, we designed prototypes and evaluated them with people from Bad Harzburg. This helped us gain valuable insights into our system’s usability and future challenges as well as requirements.
Our web application is already being used daily by our project partner. During the project, we still came up with numerous ideas for additional features to further support the exchange of knowledge.
Many participants in Massive Open Online Courses are full-time employees seeking greater flexibility in their time commitment and the available learning paths. We recently addressed these requirements by splitting up our 6-week courses into three 2-week modules followed by a separate exam. Modularizing courses offers many advantages: Shorter modules are more sustainable and can be combined, reused, and incorporated into learning paths more easily. Time flexibility for learners is also improved as exams can now be offered multiple times per year, while the learning content is available independently. In this article, we answer the question of which impact this modularization has on key learning metrics, such as course completion rates, learning success, and no-show rates. Furthermore, we investigate the influence of longer breaks between modules on these metrics. According to our analysis, course modules facilitate more selective learning behaviors that encourage learners to focus on topics they are the most interested in. At the same time, participation in overarching exams across all modules seems to be less appealing compared to an integrated exam of a 6-week course. While breaks between the modules increase the distinctive appearance of individual modules, a break before the final exam further reduces initial interest in the exams. We further reveal that participation in self-paced courses as a preparation for the final exam is unlikely to attract new learners to the course offerings, even though learners' performance is comparable to instructor-paced courses. The results of our long-term study on course modularization provide a solid foundation for future research and enable educators to make informed decisions about the design of their courses.
Accurately solving classification problems nowadays is likely to be the most relevant machine learning task. Binary classification separating two classes only is algorithmically simpler but has fewer potential applications as many real-world problems are multi-class. On the reverse, separating only a subset of classes simplifies the classification task. Even though existing multi-class machine learning algorithms are very flexible regarding the number of classes, they assume that the target set Y is fixed and cannot be restricted once the training is finished. On the other hand, existing state-of-the-art production environments are becoming increasingly interconnected with the advance of Industry 4.0 and related technologies such that additional information can simplify the respective classification problems. In light of this, the main aim of this thesis is to introduce dynamic classification that generalizes multi-class classification such that the target class set can be restricted arbitrarily to a non-empty class subset M of Y at any time between two consecutive predictions.
This task is solved by a combination of two algorithmic approaches. First, classifier calibration, which transforms predictions into posterior probability estimates that are intended to be well calibrated. The analysis provided focuses on monotonic calibration and in particular corrects wrong statements that appeared in the literature. It also reveals that bin-based evaluation metrics, which became popular in recent years, are unjustified and should not be used at all. Next, the validity of Platt scaling, which is the most relevant parametric calibration approach, is analyzed in depth. In particular, its optimality for classifier predictions distributed according to four different families of probability distributions as well its equivalence with Beta calibration up to a sigmoidal preprocessing are proven. For non-monotonic calibration, extended variants on kernel density estimation and the ensemble method EKDE are introduced. Finally, the calibration techniques are evaluated using a simulation study with complete information as well as on a selection of 46 real-world data sets.
Building on this, classifier calibration is applied as part of decomposition-based classification that aims to reduce multi-class problems to simpler (usually binary) prediction tasks. For the involved fusing step performed at prediction time, a new approach based on evidence theory is presented that uses classifier calibration to model mass functions. This allows the analysis of decomposition-based classification against a strictly formal background and to prove closed-form equations for the overall combinations. Furthermore, the same formalism leads to a consistent integration of dynamic class information, yielding a theoretically justified and computationally tractable dynamic classification model. The insights gained from this modeling are combined with pairwise coupling, which is one of the most relevant reduction-based classification approaches, such that all individual predictions are combined with a weight. This not only generalizes existing works on pairwise coupling but also enables the integration of dynamic class information.
Lastly, a thorough empirical study is performed that compares all newly introduced approaches to existing state-of-the-art techniques. For this, evaluation metrics for dynamic classification are introduced that depend on corresponding sampling strategies. Thereafter, these are applied during a three-part evaluation. First, support vector machines and random forests are applied on 26 data sets from the UCI Machine Learning Repository. Second, two state-of-the-art deep neural networks are evaluated on five benchmark data sets from a relatively recent reference work. Here, computationally feasible strategies to apply the presented algorithms in combination with large-scale models are particularly relevant because a naive application is computationally intractable. Finally, reference data from a real-world process allowing the inclusion of dynamic class information are collected and evaluated. The results show that in combination with support vector machines and random forests, pairwise coupling approaches yield the best results, while in combination with deep neural networks, differences between the different approaches are mostly small to negligible. Most importantly, all results empirically confirm that dynamic classification succeeds in improving the respective prediction accuracies. Therefore, it is crucial to pass dynamic class information in respective applications, which requires an appropriate digital infrastructure.
StudyMe
(2022)
N-of-1 trials are multi-crossover self-experiments that allow individuals to systematically evaluate the effect of interventions on their personal health goals. Although several tools for N-of-1 trials exist, there is a gap in supporting non-experts in conducting their own user-centric trials. In this study, we present StudyMe, an open-source mobile application that is freely available from https://play.google.com/store/apps/details?id=health.studyu.me and offers users flexibility and guidance in configuring every component of their trials. We also present research that informed the development of StudyMe, focusing on trial creation. Through an initial survey with 272 participants, we learned that individuals are interested in a variety of personal health aspects and have unique ideas on how to improve them. In an iterative, user-centered development process with intermediate user tests, we developed StudyMe that features an educational part to communicate N-of-1 trial concepts. A final empirical evaluation of StudyMe showed that all participants were able to create their own trials successfully using StudyMe and the app achieved a very good usability rating. Our findings suggest that StudyMe provides a significant step towards enabling individuals to apply a systematic science-oriented approach to personalize health-related interventions and behavior modifications in their everyday lives.
Muscle quality defined as the ratio of muscle strength to muscle mass disregards underlying factors which influence muscle strength. The aim of this review was to investigate the relationship of phase angle (PhA), echo intensity (EI), muscular adipose tissue (MAT), muscle fiber type, fascicle pennation angle (θf), fascicle length (lf), muscle oxidative capacity, insulin sensitivity (IS), neuromuscular activation, and motor unit to muscle strength. PubMed search was performed in 2021. The inclusion criteria were: (i) original research, (ii) human participants, (iii) adults (≥18 years). Exclusion criteria were: (i) no full-text, (ii) non-English or -German language, (iii) pathologies. Forty-one studies were identified. Nine studies found a weak–moderate negative (range r: [−0.26]–[−0.656], p < 0.05) correlation between muscle strength and EI. Four studies found a weak–moderate positive correlation (range r: 0.177–0.696, p < 0.05) between muscle strength and PhA. Two studies found a moderate-strong negative correlation (range r: [−0.446]–[−0.87], p < 0.05) between muscle strength and MAT. Two studies found a weak-strong positive correlation (range r: 0.28–0.907, p < 0.05) between θf and muscle strength. Muscle oxidative capacity was found to be a predictor of muscle strength. This review highlights that the current definition of muscle quality should be expanded upon as to encompass all possible factors of muscle quality.
Teaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In this way, a comparative analysis between AI usage in administration and teaching and learning processes, a systematization of the state of research, an identification of research gaps as well as further research path on AI in higher education institutions are contributed to research.
OBJECTIVE: For an effective control of the SARS-CoV-2 pandemic with vaccines, most people in a population need to be vaccinated. It is thus important to know how to inform the public with reference to individual preferences–while also acknowledging the societal preference to encourage vaccinations. According to the health care standard of informed decision-making, a comparison of the benefits and harms of (not) having the vaccination would be required to inform undecided and skeptical people. To test evidence-based fact boxes, an established risk communication format, and to inform their development, we investigated their contribution to knowledge and evaluations of COVID-19 vaccines.
METHODS: We conducted four studies (1, 2, and 4 were population-wide surveys with N = 1,942 to N = 6,056): Study 1 assessed the relationship between vaccination knowledge and intentions in Germany over three months. Study 2 assessed respective information gaps and needs of the population in Germany. In parallel, an experiment (Study 3) with a mixed design (presentation formats; pre-post-comparison) assessed the effect of fact boxes on risk perceptions and fear, using a convenience sample (N = 719). Study 4 examined how effective two fact box formats are for informing vaccination intentions, with a mixed experimental design: between-subjects (presentation formats) and within-subjects (pre-post-comparison).
RESULTS: Study 1 showed that vaccination knowledge and vaccination intentions increased between November 2020 and February 2021. Study 2 revealed objective information requirements and subjective information needs. Study 3 showed that the fact box format is effective in adjusting risk perceptions concerning COVID-19. Based on those results, fact boxes were revised and implemented with the help of a national health authority in Germany. Study 4 showed that simple fact boxes increase vaccination knowledge and positive evaluations in skeptics and undecideds.
CONCLUSION: Fact boxes can inform COVID-19 vaccination intentions of undecided and skeptical people without threatening societal vaccination goals of the population.
Background
The association between bivariate variables may not necessarily be homogeneous throughout the whole range of the variables. We present a new technique to describe inhomogeneity in the association of bivariate variables.
Methods
We consider the correlation of two normally distributed random variables. The 45° diagonal through the origin of coordinates represents the line on which all points would lie if the two variables completely agreed. If the two variables do not completely agree, the points will scatter on both sides of the diagonal and form a cloud. In case of a high association between the variables, the band width of this cloud will be narrow, in case of a low association, the band width will be wide. The band width directly relates to the magnitude of the correlation coefficient. We then determine the Euclidean distances between the diagonal and each point of the bivariate correlation, and rotate the coordinate system clockwise by 45°. The standard deviation of all Euclidean distances, named “global standard deviation”, reflects the band width of all points along the former diagonal. Calculating moving averages of the standard deviation along the former diagonal results in “locally structured standard deviations” and reflect patterns of “locally structured correlations (LSC)”. LSC highlight inhomogeneity of bivariate correlations. We exemplify this technique by analyzing the association between body mass index (BMI) and hip circumference (HC) in 6313 healthy East German adults aged 18 to 70 years.
Results
The correlation between BMI and HC in healthy adults is not homogeneous. LSC is able to identify regions where the predictive power of the bivariate correlation between BMI and HC increases or decreases, and highlights in our example that slim people have a higher association between BMI and HC than obese people.
Conclusion
Locally structured correlations (LSC) identify regions of higher or lower than average correlation between two normally distributed variables.
There is broad agreement among researchers to view mind wandering as an obstacle to learning because it draws attention away from learning tasks. Accordingly, empirical findings revealed negative correlations between the frequency of mind wandering during learning and various kinds of learning outcomes (e.g., text retention). However, a few studies have indicated positive effects of mind wandering on creativity in real-world learning environments. The present article reviews these studies and highlights potential benefits of mind wandering for learning mediated through creative processes. Furthermore, we propose various ways to promote useful mind wandering and, at the same time, minimize its negative impact on learning.
Stress and pain
(2022)
Introduction: Low back pain (LBP) leads to considerable impairment of quality of life worldwide and is often accompanied by psychosomatic symptoms.
Objectives: First, to assess the association between stress and chronic low back pain (CLBP) and its simultaneous appearance with fatigue and depression as a symptom triad. Second, to identify the most predictive stress-related pattern set for CLBP for a 1-year diagnosis.
Methods: In a 1-year observational study with four measurement points, a total of 140 volunteers (aged 18–45 years with intermittent pain) were recruited. The primary outcomes were pain [characteristic pain intensity (CPI), subjective pain disability (DISS)], fatigue, and depressive mood. Stress was assessed as chronic stress, perceived stress, effort reward imbalance, life events, and physiological markers [allostatic load index (ALI), hair cortisol concentration (HCC)]. Multiple linear regression models and selection procedures for model shrinkage and variable selection (least absolute shrinkage and selection operator) were applied. Prediction accuracy was calculated by root mean squared error (RMSE) and receiver-operating characteristic curves.
Results: There were 110 participants completed the baseline assessments (28.2 7.5 years, 38.1% female), including HCC, and a further of 46 participants agreed to ALI laboratory measurements. Different stress types were associated with LBP, CLBP, fatigue, and depressive mood and its joint occurrence as a symptom triad at baseline; mainly social-related stress types were of relevance. Work-related stress, such as “excessive demands at work”[b = 0.51 (95%CI -0.23, 1.25), p = 0.18] played a role for upcoming chronic pain disability. “Social overload” [b = 0.45 (95%CI -0.06, 0.96), p = 0.080] and “over-commitment at work” [b = 0.28 (95%CI -0.39, 0.95), p = 0.42] were associated with an upcoming depressive mood within 1-year. Finally, seven psychometric (CPI: RMSE = 12.63; DISS: RMSE = 9.81) and five biomarkers (CPI: RMSE = 12.21; DISS: RMSE = 8.94) could be derived as the most predictive pattern set for a 1-year prediction of CLBP. The biomarker set showed an apparent area under the curve of 0.88 for CPI and 0.99 for DISS.
Conclusion: Stress disrupts allostasis and favors the development of chronic pain, fatigue, and depression and the emergence of a “hypocortisolemic symptom triad,” whereby the social-related stressors play a significant role. For translational medicine, a predictive pattern set could be derived which enables to diagnose the individuals at higher risk for the upcoming pain disorders and can be used in practice.
Physical activity and exercise are effective approaches in prevention and therapy of multiple diseases. Although the specific characteristics of lengthening contractions have the potential to be beneficial in many clinical conditions, eccentric training is not commonly used in clinical populations with metabolic, orthopaedic, or neurologic conditions. The purpose of this pilot study is to investigate the feasibility, functional benefits, and systemic responses of an eccentric exercise program focused on the trunk and lower extremities in people with low back pain (LBP) and multiple sclerosis (MS). A six-week eccentric training program with three weekly sessions is performed by people with LBP and MS. The program consists of ten exercises addressing strength of the trunk and lower extremities. The study follows a four-group design (N = 12 per group) in two study centers (Israel and Germany): three groups perform the eccentric training program: A) control group (healthy, asymptomatic); B) people with LBP; C) people with MS; group D (people with MS) receives standard care physiotherapy. Baseline measurements are conducted before first training, post-measurement takes place after the last session both comprise blood sampling, self-reported questionnaires, mobility, balance, and strength testing. The feasibility of the eccentric training program will be evaluated using quantitative and qualitative measures related to the study process, compliance and adherence, safety, and overall program assessment. For preliminary assessment of potential intervention effects, surrogate parameters related to mobility, postural control, muscle strength and systemic effects are assessed. The presented study will add knowledge regarding safety, feasibility, and initial effects of eccentric training in people with orthopaedic and neurological conditions. The simple exercises, that are easily modifiable in complexity and intensity, are likely beneficial to other populations. Thus, multiple applications and implementation pathways for the herein presented training program are conceivable.
Inverted perovskite solar cells still suffer from significant non-radiative recombination losses at the perovskite surface and across the perovskite/C₆₀ interface, limiting the future development of perovskite-based single- and multi-junction photovoltaics. Therefore, more effective inter- or transport layers are urgently required. To tackle these recombination losses, we introduce ortho-carborane as an interlayer material that has a spherical molecular structure and a three-dimensional aromaticity. Based on a variety of experimental techniques, we show that ortho-carborane decorated with phenylamino groups effectively passivates the perovskite surface and essentially eliminates the non-radiative recombination loss across the perovskite/C₆₀ interface with high thermal stability. We further demonstrate the potential of carborane as an electron transport material, facilitating electron extraction while blocking holes from the interface. The resulting inverted perovskite solar cells deliver a power conversion efficiency of over 23% with a low non-radiative voltage loss of 110 mV, and retain >97% of the initial efficiency after 400 h of maximum power point tracking. Overall, the designed carborane based interlayer simultaneously enables passivation, electron-transport and hole-blocking and paves the way toward more efficient and stable perovskite solar cells.
Studies from several countries suggest that COVID-19 vaccination rates are lower among migrants compared to the general population. Urgent calls have been made to improve vaccine outreach to migrants, however, there is limited evidence on effective approaches, especially using social media. We assessed a targeted, low-cost, Facebook campaign disseminating COVID-19 vaccine information among Arabic, Turkish and Russian speakers in Germany (N = 888,994). As part of the campaign, we conducted two randomized, online experiments to assess the impact of the advertisement (1) language and (2) depicted messenger (government authority, religious leader, doctor or family). Key outcomes included reach, click-through rates, conversion rates and cost-effectiveness. Within 29 days, the campaign reached 890 thousand Facebook users. On average, 2.3 individuals accessed the advertised COVID-19 vaccination appointment tool for every euro spent on the campaign. Migrants were 2.4 (Arabic), 1.8 (Russian) and 1.2 (Turkish) times more likely to click on advertisements translated to their native language compared to German-language advertisements. Furthermore, findings showed that government representatives can be more successful in engaging migrants online compared to other messengers, despite common claims of lower trust in government institutions among migrants. This study highlights the potential of tailored, and translated, vaccination campaigns on social media for reaching migrants who may be left out by traditional media campaigns.
A multidimensional and analytical perspective on Open Educational Practices in the 21st century
(2022)
Participatory approaches to teaching and learning are experiencing a new lease on life in the 21st century as a result of the rapid technology development. Knowledge, practices, and tools can be shared across spatial and temporal boundaries in higher education by means of Open Educational Resources, Massive Open Online Courses, and open-source technologies. In this context, the Open Education Movement calls for new didactic approaches that encourage greater learner participation in formal higher education. Based on a representative literature review and focus group research, in this study an analytical framework was developed that enables researchers and practitioners to assess the form of participation in formal, collaborative teaching and learning practices. The analytical framework is focused on the micro-level of higher education, in particular on the interaction between students and lecturers when organizing the curriculum. For this purpose, the research reflects anew on the concept of participation, taking into account existing stage models for participation in the educational context. These are then brought together with the dimensions of teaching and learning processes, such as methods, objectives and content, etc. This paper aims to make a valuable contribution to the opening up of learning and teaching, and expands the discourse around possibilities for interpreting Open Educational Practices.
The present dissertation conducts empirical research on the relationship between urban life and its economic costs, especially for the environment. On the one hand, existing gaps in research on the influence of population density on air quality are closed and, on the other hand, innovative policy measures in the transport sector are examined that are intended to make metropolitan areas more sustainable. The focus is on air pollution, congestion and traffic accidents, which are important for general welfare issues and represent significant cost factors for urban life. They affect a significant proportion of the world's population. While 55% of the world's people already lived in cities in 2018, this share is expected to reach approximately 68% by 2050.
The four self-contained chapters of this thesis can be divided into two sections: Chapters 2 and 3 provide new causal insights into the complex interplay between urban structures and air pollution. Chapters 4 and 5 then examine policy measures to promote non-motorised transport and their influence on air quality as well as congestion and traffic accidents.
Intuitively, strongly constraining contexts should lead to stronger probabilistic representations of sentences in memory. Encountering unexpected words could therefore be expected to trigger costlier shifts in these representations than expected words. However, psycholinguistic measures commonly used to study probabilistic processing, such as the N400 event-related potential (ERP) component, are sensitive to word predictability but not to contextual constraint. Some research suggests that constraint-related processing cost may be measurable via an ERP positivity following the N400, known as the anterior post-N400 positivity (PNP). The PNP is argued to reflect update of a sentence representation and to be distinct from the posterior P600, which reflects conflict detection and reanalysis. However, constraint-related PNP findings are inconsistent. We sought to conceptually replicate Federmeier et al. (2007) and Kuperberg et al. (2020), who observed that the PNP, but not the N400 or the P600, was affected by constraint at unexpected but plausible words. Using a pre-registered design and statistical approach maximising power, we demonstrated a dissociated effect of predictability and constraint: strong evidence for predictability but not constraint in the N400 window, and strong evidence for constraint but not predictability in the later window. However, the constraint effect was consistent with a P600 and not a PNP, suggesting increased conflict between a strong representation and unexpected input rather than greater update of the representation. We conclude that either a simple strong/weak constraint design is not always sufficient to elicit the PNP, or that previous PNP constraint findings could be an artifact of smaller sample size.
Introduction: The body-specificity hypothesis states that in right-handers, positive concepts should be associated with the right side and negative concepts with the left side of the body. Following this hypothesis, our study postulated that negative out-group ethnic stereotypes would be associated with the left side, and positive in-group stereotypes would be associated with the right side.
Methods: The experiment consisted of two parts. First, we measured the spatial mapping of ethnic stereotypes by using a sensibility judgment task, in which participants had to decide whether a sentence was sensible or not by pressing either a left or a right key. The sentences included German vs. Arabic proper names. Second, we measured implicit ethnic stereotypes in the same participants using the Go/No-go Association Task (GNAT), in which Arabic vs. German proper names were presented in combination with positive vs. negative adjectives. Right-handed German native speakers (N = 92) participated in an online study.
Results: As predicted, in the GNAT, participants reacted faster to German names combined with positive adjectives and to Arabic names combined with negative adjectives, which is diagnostic of existing valenced in-and outgroup ethnic stereotypes. However, we failed to find any reliable effects in the sensibility judgment task, i.e., there was no evidence of spatial mapping of positive and negative ethnic stereotypes. There was no correlation between the results of the two tasks at the individual level. Further Bayesian analysis and exploratory analysis in the left-handed subsample (N = 9) corroborated the evidence in favor of null results.
Discussion: Our study suggests that ethnic stereotypes are not automatically mapped in a body-specific manner.
Eight d-metal-containing N-butylpyridinium ionic liquids (ILs) with the nominal composition (C4Py)2[Ni0.5M0.5Cl4] or (C4Py)2[Zn0.5M0.5Cl4] (M = Cu, Co, Mn, Ni, Zn; C4Py = N-butylpyridinium) were synthesized, characterized, and investigated for their optical properties. Single crystal and powder X-ray analysis shows that the compounds are isostructural to existing examples based on other d-metal ions. Inductively coupled plasma optical emission spectroscopy measurements confirm that the metal/metal ratio is around 50 : 50. UV-Vis spectroscopy shows that the optical absorption can be tuned by selection of the constituent metals. Moreover, the compounds can act as an optical sensor for the detection of gases such as ammonia as demonstrated via a simple prototype setup.
Balkan varieties of Turkic, particularly those on the periphery of the Turkic spread area in the region, such as Gagauz and West Rumelian Turkish, are commonly observed to have head-initial verb phrases. Based on a wide survey, this paper attempts a more precise description of the pattern of VP directionality across Balkan Turkic and shows that there is considerable variation in how prevalent VX order is, a pattern that turns out to be more complex than the previous descriptions suggest: Two spectrums of directionality can be discerned between XV and VX orders, contingent upon type of the dependent of the verb and dialect locale. The paper also explores the grammatical causes underlying this shift in constituent order. First, VX order seems to be dependent upon whether a clause is nominal or not. Nonfinite clauses of the nominal type have XV order across Balkan Turkic, while finite clauses and nonfinite clauses of the converbial type show differing degrees of VX order depending on type of dependent and geographical location. Second, VX order appears to be an outcome of verb movement to the left of the dependent in finite clauses and nonfinite clauses of the converbial type, rather than head parameter shift.
The process of number symbolization is assumed to be critically influenced by the acquisition of so-called verbal number skills (e.g., verbally reciting the number chain and naming Arabic numerals). For the acquisition of these verbal number skills, verbal and visuospatial skills are discussed as contributing factors. In this context, children’s verbal number skills have been found to be associated with their concurrent spatial language skills such as mastery of verbal descriptions of spatial position (e.g., in front of, behind). In a longitudinal study with three measurement times (T1, T2, T3) at an interval of about 6 months, we evaluated the predictive role of preschool children’s (mean age at T1: 3 years and 10 months) spatial language skills for the acquisition of verbal number skills. Children’s spatial language skills at T2 significantly predicted their verbal number skills at T3, when controlling for influences of important covariates such as vocabulary knowledge. In addition, further analyses replicated previous results indicating that children’s spatial language skills at T2 were associated with their verbal number skills at T2. Exploratory analyses further revealed that children’s verbal number skills at T1 predict their spatial language at T2. Results suggests that better spatial language skills at the age of 4 years facilitate the future acquisition of verbal number skills.
Sprache
Englisch
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusionmodel and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a wellcalibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output.
High-throughput proteomics approaches have resulted in large-scale protein–protein interaction (PPI) networks that have been employed for the prediction of protein complexes. However, PPI networks contain false-positive as well as false-negative PPIs that affect the protein complex prediction algorithms. To address this issue, here we propose an algorithm called CUBCO+ that: (1) employs GO semantic similarity to retain only biologically relevant interactions with a high similarity score, (2) based on link prediction approaches, scores the false-negative edges, and (3) incorporates the resulting scores to predict protein complexes. Through comprehensive analyses with PPIs from Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens, we show that CUBCO+ performs as well as the approaches that predict protein complexes based on recently introduced graph partitions into biclique spanned subgraphs and outperforms the other state-of-the-art approaches. Moreover, we illustrate that in combination with GO semantic similarity, CUBCO+ enables us to predict more accurate protein complexes in 36% of the cases in comparison to CUBCO as its predecessor.
Background
Eating in absence of hunger is quite common and often associated with an increased energy intake co-existent with a poorer food choice. Intuitive eating (IE), i.e., eating in accordance with internal hunger and satiety cues, may protect from overeating. IE, however, requires accurate perception and processing of one’s own bodily signals, also referred to as interoceptive sensitivity. Training interoceptive sensitivity might therefore be an effective method to promote IE and prevent overeating. As most studies on eating behavior are conducted in younger adults and close social relationships influence health-related behavior, this study focuses on middle-aged and older couples.
Methods
The present pilot randomized intervention study aims at investigating the feasibility and effectiveness of a 21-day mindfulness-based training program designed to increase interoceptive sensitivity. A total of N = 60 couples participating in the NutriAct Family Study, aged 50–80 years, will be recruited. This randomized-controlled intervention study comprises three measurement points (pre-intervention, post-intervention, 4-week follow-up) and a 21-day training that consists of daily mindfulness-based guided audio exercises (e.g., body scan). A three-arm intervention study design is applied to compare two intervention groups (training together as a couple vs. training alone) with a control group (no training). Each measurement point includes the assessment of self-reported and objective indicators of interoceptive sensitivity (primary outcome), self-reported indicators of intuitive and maladaptive eating (secondary outcomes), and additional variables. A training evaluation applying focus group discussions will be conducted to assess participants’ overall acceptance of the training and its feasibility.
Discussion
By investigating the feasibility and effectiveness of a mindfulness-based training program to increase interoceptive sensitivity, the present study will contribute to a deeper understanding of how to promote healthy eating in older age.
Here we present an exome-wide rare genetic variant association study for 30 blood biomarkers in 191,971 individuals in the UK Biobank. We compare gene- based association tests for separate functional variant categories to increase interpretability and identify 193 significant gene-biomarker associations. Genes associated with biomarkers were ~ 4.5-fold enriched for conferring Mendelian disorders. In addition to performing weighted gene-based variant collapsing tests, we design and apply variant-category-specific kernel-based tests that integrate quantitative functional variant effect predictions for mis- sense variants, splicing and the binding of RNA-binding proteins. For these tests, we present a computationally efficient combination of the likelihood- ratio and score tests that found 36% more associations than the score test alone while also controlling the type-1 error. Kernel-based tests identified 13% more associations than their gene-based collapsing counterparts and had advantages in the presence of gain of function missense variants. We introduce local collapsing by amino acid position for missense variants and use it to interpret associations and identify potential novel gain of function variants in PIEZO1. Our results show the benefits of investigating different functional mechanisms when performing rare-variant association tests, and demonstrate pervasive rare-variant contribution to biomarker variability.
Refugee youth in protracted humanitarian contexts are faced with limited access to quality education. They may sustain traumatic experiences from conflicts and discrimination yet have limited psychosocial support access. Comprehending the magnitude and effects of these challenges is vital for designing and executing educational interventions in such contexts. This study evaluates the implementation quality of the Youth Education Pack intervention through the lens of the Inter-agency Network for Education in Emergencies minimum standards framework. It explores the types of discrimination experienced by refugee youth in the Dadaab refugee camp in Kenya. Nine participants comprising refugee students (N = 2), former refugee students (N = 2), teachers (N = 3), and project supervisors (N = 2) participated in the study. The first author conducted interviews and observations in the camp. The data were qualitatively coded deductively and analysed in Nvivo 12. We found that the YEP intervention faced contextual challenges that hindered the achievement of the implementation quality standards outlined in the INEE minimum standards for education. Refugee youth and refugee teachers experienced various forms of discrimination, including at individual, institutional, and structural levels. We conclude that providing refugee youth with an inclusive and high-quality education is central to providing secure and long-term solutions to their challenges and adversities and may promote their psychosocial wellbeing.
Anomalous-diffusion, the departure of the spreading dynamics of diffusing particles from the traditional law of Brownian-motion, is a signature feature of a large number of complex soft-matter and biological systems. Anomalous-diffusion emerges due to a variety of physical mechanisms, e.g., trapping interactions or the viscoelasticity of the environment. However, sometimes systems dynamics are erroneously claimed to be anomalous, despite the fact that the true motion is Brownian—or vice versa. This ambiguity in establishing whether the dynamics as normal or anomalous can have far-reaching consequences, e.g., in predictions for reaction- or relaxation-laws. Demonstrating that a system exhibits normal- or anomalous-diffusion is highly desirable for a vast host of applications. Here, we present a criterion for anomalous-diffusion based on the method of power-spectral analysis of single trajectories. The robustness of this criterion is studied for trajectories of fractional-Brownian-motion, a ubiquitous stochastic process for the description of anomalous-diffusion, in the presence of two types of measurement errors. In particular, we find that our criterion is very robust for subdiffusion. Various tests on surrogate data in absence or presence of additional positional noise demonstrate the efficacy of this method in practical contexts. Finally, we provide a proof-of-concept based on diverse experiments exhibiting both normal and anomalous-diffusion.
Following excited-state chemical shifts in molecular ultrafast x-ray photoelectron spectroscopy
(2022)
The conversion of photon energy into other energetic forms in molecules is accompanied by charge moving on ultrafast timescales. We directly observe the charge motion at a specific site in an electronically excited molecule using time-resolved x-ray photoelectron spectroscopy (TR-XPS). We extend the concept of static chemical shift from conventional XPS by the excited-state chemical shift (ESCS), which is connected to the charge in the framework of a potential model. This allows us to invert TR-XPS spectra to the dynamic charge at a specific atom. We demonstrate the power of TR-XPS by using sulphur 2p-core-electron-emission probing to study the UV-excited dynamics of 2-thiouracil. The method allows us to discover that a major part of the population relaxes to the molecular ground state within 220–250 fs. In addition, a 250-fs oscillation, visible in the kinetic energy of the TR-XPS, reveals a coherent exchange of population among electronic states.
Perceived predation risk varies in space and time. Foraging in this landscape of fear alters forager-resource interactions via cascading nonconsumptive effects. Estimating these indirect effects is difficult in natural systems. Here, we applied a novel measure to quantify the diversity at giving-up density that allows to test how spatial variation in perceived predation risk modifies the diversity of multispecies resources at local and regional spatial levels. Furthermore, we evaluated whether the nonconsumptive effects on resource species diversity can be explained by the preferences of foragers for specific functional traits and by the forager species richness. We exposed rodents of a natural community to artificial food patches, each containing an initial multispecies resource community of eight species (10 items each) mixed in sand. We sampled 35 landscapes, each containing seven patches in a spatial array, to disentangle effects at local (patch) and landscape levels. We used vegetation height as a proxy for perceived predation risk. After a period of three nights, we counted how many and which resource species were left in each patch to measure giving-up density and resource diversity at the local level (alpha diversity) and the regional level (gamma diversity and beta diversity). Furthermore, we used wildlife cameras to identify foragers and assess their species richness. With increasing vegetation height, i.e., decreasing perceived predation risk, giving-up density, and local alpha and regional gamma diversity decreased, and patches became less similar within a landscape (beta diversity increased). Foragers consumed more of the bigger and most caloric resources. The higher the forager species richness, the lower the giving-up density, and alpha and gamma diversity. Overall, spatial variation of perceived predation risk of foragers had measurable cascading effects on local and regional resource species biodiversity, independent of the forager species. Thus, nonconsumptive predation effects modify forager-resource interactions and might act as an equalizing mechanism for species coexistence.
Neural conversation models aim to predict appropriate contributions to a (given) conversation by using neural networks trained on dialogue data. A specific strand focuses on non-goal driven dialogues, first proposed by Ritter et al. (2011): They investigated the task of transforming an utterance into an appropriate reply. Then, this strand evolved into dialogue system approaches using long dialogue histories and additional background context. Contributing meaningful and appropriate to a conversation is a complex task, and therefore research in this area has been very diverse: Serban et al. (2016), for example, looked into utilizing variable length dialogue histories, Zhang et al. (2018) added additional context to the dialogue history, Wolf et al. (2019) proposed a model based on pre-trained Self-Attention neural networks (Vasvani et al., 2017), and Dinan et al. (2021) investigated safety issues of these approaches. This trend can be seen as a transformation from trying to somehow carry on a conversation to generating appropriate replies in a controlled and reliable way.
In this thesis, we first elaborate the meaning of appropriateness in the context of neural conversation models by drawing inspiration from the Cooperative Principle (Grice, 1975). We first define what an appropriate contribution has to be by operationalizing these maxims as demands on conversation models: being fluent, informative, consistent towards given context, coherent and following a social norm. Then, we identify different targets (or intervention points) to achieve the conversational appropriateness by investigating recent research in that field.
In this thesis, we investigate the aspect of consistency towards context in greater detail, being one aspect of our interpretation of appropriateness.
During the research, we developed a new context-based dialogue dataset (KOMODIS) that combines factual and opinionated context to dialogues. The KOMODIS
dataset is publicly available and we use the data in this thesis to gather new insights in context-augmented dialogue generation.
We further introduced a new way of encoding context within Self-Attention based neural networks. For that, we elaborate the issue of space complexity from knowledge graphs,
and propose a concise encoding strategy for structured context inspired from graph neural networks (Gilmer et al., 2017) to reduce the space complexity of the additional context. We discuss limitations of context-augmentation for neural conversation models, explore the characteristics of knowledge graphs, and explain how we create and augment knowledge graphs for our experiments.
Lastly, we analyzed the potential of reinforcement and transfer learning to improve context-consistency for neural conversation models. We find that current reward functions need to be more precise to enable the potential of reinforcement learning, and that sequential transfer learning can improve the subjective quality of generated dialogues.
This dissertation aimed to determine differential expressed miRNAs in the context of chronic pain in polyneuropathy. For this purpose, patients with chronic painful polyneuropathy were compared with age matched healthy patients. Taken together, all miRNA pre library preparation quality controls were successful and none of the samples was identified as an outlier or excluded for library preparation. Pre sequencing quality control showed that library preparation worked for all samples as well as that all samples were free of adapter dimers after BluePippin size selection and reached the minimum molarity for further processing. Thus, all samples were subjected to sequencing. The sequencing control parameters were in their optimal range and resulted in valid sequencing results with strong sample to sample correlation for all samples. The resulting FASTQ file of each miRNA library was analyzed and used to perform a differential expression analysis. The differentially expressed and filtered miRNAs were subjected to miRDB to perform a target prediction. Three of those four miRNAs were downregulated: hsa-miR-3135b, hsa-miR-584-5p and hsa-miR-12136, while one was upregulated: hsa-miR-550a-3p. miRNA target prediction showed that chronic pain in polyneuropathy might be the result of a combination of miRNA mediated high blood flow/pressure and neural activity dysregulations/disbalances. Thus, leading to the promising conclusion that these four miRNAs could serve as potential biomarkers for the diagnosis of chronic pain in polyneuropathy.
Since TRPV1 seems to be one of the major contributors of nociception and is associated with neuropathic pain, the influence of PKA phosphorylated ARMS on the sensitivity of TRPV1 as well as the part of AKAP79 during PKA phosphorylation of ARMS was characterized. Therefore, possible PKA-sites in the sequence of ARMS were identified. This revealed five canonical PKA-sites: S882, T903, S1251/52, S1439/40 and S1526/27. The single PKA-site mutants of ARMS revealed that PKA-mediated ARMS phosphorylation seems not to influence the interaction rate of TRPV1/ARMS. While phosphorylation of ARMST903 does not increase the interaction rate with TRPV1, ARMSS1526/27 is probably not phosphorylated and leads to an increased interaction rate. The calcium flux measurements indicated that the higher the interaction rate of TRPV1/ARMS, the lower the EC50 for capsaicin of TRPV1, independent of the PKA phosphorylation status of ARMS. In addition, the western blot analysis confirmed the previously observed TRPV1/ARMS interaction. More importantly, AKAP79 seems to be involved in the TRPV1/ARMS/PKA signaling complex. To overcome the problem of ARMS-mediated TRPV1 sensitization by interaction, ARMS was silenced by shRNA. ARMS silencing resulted in a restored TRPV1 desensitization without affecting the TRPV1 expression and therefore could be used as new topical therapeutic analgesic alternative to stop ARMS mediated TRPV1 sensitization.
Efficiency is central to understanding the communicative and cognitive underpinnings of language. However, efficiency management is a complex mechanism in which different efficiency effects-such as articulatory, processing and planning ease, mental accessibility, and informativity, online and offline efficiency effects-conspire to yield the coding of linguistic signs. While we do not yet exactly understand the interactional mechanism of these different effects, we argue that universal attractors are an important component of any dynamic theory of efficiency that would be aimed at predicting efficiency effects across languages. Attractors are defined as universal states around which language evolution revolves. Methodologically, we approach efficiency from a cross-linguistic perspective on the basis of a world-wide sample of 383 languages from 53 families, balancing all six macro-areas (Eurasia, North and South America, Australia, Africa, and Oceania). We explore the grammatical domain of verbal person-number subject indexes. We claim that there is an attractor state in this domain to which languages tend to develop and tend not to leave if they happen to comply with the attractor in their earlier stages of evolution. The attractor is characterized by different lengths for each person and number combination, structured along Zipf's predictions. Moreover, the attractor strongly prefers non-compositional, cumulative coding of person and number. On the basis of these and other properties of the attractor, we conclude that there are two domains in which efficiency pressures are most powerful: strive towards less processing and articulatory effort. The latter, however, is overridden by constant information flow. Strive towards lower lexicon complexity and memory costs are weaker efficiency pressures for this grammatical category due to its order of frequency.
The starting point of this article is the occurrence of determiner-less and bare que relative complementizers like (en) que, ‘(in) that’, instead of (en) el que, ‘(in) which’, in Yucatecan Spanish (southeast Mexico). While reference grammars treat complementizers with a determiner as the standard option, previous diachronic research has shown that determiner-less complementizers actually predate relative complementizers with a determiner. Additionally, Yucatecan Spanish has been in long-standing contact with Yucatec Maya. Relative complementation in Yucatec Maya differs from that in Spanish (at least) in that the non-complex complementizer tu’ux (‘where’) is generally the only option for locative complementation. The paper explores monolingual and bilingual data from Yucatecan Spanish to discuss the question whether the determiner-less and bare que relative complementizers in our data constitute a historic remnant or a dialectal recast, possibly (but not necessarily) due to language contact. Although our pilot study may not answer these far-reaching questions, it does reveal two separate, but intertwined developments: (i) a generally increased rate of bare que relative complementation, across both monolingual speakers of Spanish and Spanish Maya bilinguals, compared to other Spanish varieties, and (ii) a preference for donde at the cost of other locative complementizer constructions in the bilingual group. Our analysis thus reveals intriguing differences between the complementizer preferences of monolingual and bilingual speakers, suggesting that different variational patterns caused by different (socio-)linguistic factors can co-develop in parallel in one and the [same] region.
The highly structured nature of the educational sector demands effective policy mechanisms close to the needs of the field. That is why evidence-based policy making, endorsed by the European Commission under Erasmus+ Key Action 3, aims to make an alignment between the domains of policy and practice. Against this background, this article addresses two issues: First, that there is a vertical gap in the translation of higher-level policies to local strategies and regulations. Second, that there is a horizontal gap between educational domains regarding the policy awareness of individual players. This was analyzed in quantitative and qualitative studies with domain experts from the fields of virtual mobility and teacher training. From our findings, we argue that the combination of both gaps puts the academic bridge from secondary to tertiary education at risk, including the associated knowledge proficiency levels. We discuss the role of digitalization in the academic bridge by asking the question: which value does the involved stakeholders expect from educational policies? As a theoretical basis, we rely on the model of value co-creation for and by stakeholders. We describe the used instruments along with the obtained results and proposed benefits. Moreover, we reflect on the methodology applied, and we finally derive recommendations for future academic bridge policies.
In its practical outlook, the interdisciplinary-driven colonial discourse theory is often criticized for its totalizing tendencies regarding the structure of the exam-ined discourse and the power relations prevailing in this framework. As a result of this structural totalization, the concerned subjects got disempowered and de-graded to mere passive objects incapable of raising their voices within the dis-course. Based on this justified criticism, this thesis investigates the role colonial subjects played in the emergence, the distribution, as well as in questioning and critiquing of the colonial discourse during the initial phase of British colonialism in West Africa. The focal point lies on three themes relevant to the period be-tween 1874 and 1914: The Ashanti-Wars, the creation of an educational system, and the issue of the so-called "Europeanized Africans." Newspapers published by the colonial elite serve as the central source material in order to reconstruct Afri-can perspectives on these subjects. First, the discursive trajectory of the first two themes will be reconstructed and then shown why the initial support of the elite gradually declined towards the end of the century. Eventually, the analyzed tendencies culminated in the emergence of the "African Regeneration" discourse, which was able to reverse the colonial discourse's basic assumptions, at least on a theoretical level. Consequently, the Africans were displayed as the "civilizer" of Europe. On the structural level, however, this discourse likewise employed a to-talizing picture of African and European societies, respectively.
Learning from failure
(2022)
Regression testing is a widespread practice in today's software industry to ensure software product quality. Developers derive a set of test cases, and execute them frequently to ensure that their change did not adversely affect existing functionality. As the software product and its test suite grow, the time to feedback during regression test sessions increases, and impedes programmer productivity: developers wait longer for tests to complete, and delays in fault detection render fault removal increasingly difficult.
Test case prioritization addresses the problem of long feedback loops by reordering test cases, such that test cases of high failure probability run first, and test case failures become actionable early in the testing process. We ask, given test execution schedules reconstructed from publicly available data, to which extent can their fault detection efficiency improved, and which technique yields the most efficient test schedules with respect to APFD?
To this end, we recover regression 6200 test sessions from the build log files of Travis CI, a popular continuous integration service, and gather 62000 accompanying changelists. We evaluate the efficiency of current test schedules, and examine the prioritization results of state-of-the-art lightweight, history-based heuristics. We propose and evaluate a novel set of prioritization algorithms, which connect software changes and test failures in a matrix-like data structure.
Our studies indicate that the optimization potential is substantial, because the existing test plans score only 30% APFD. The predictive power of past test failures proves to be outstanding: simple heuristics, such as repeating tests with failures in recent sessions, result in efficiency scores of 95% APFD. The best-performing matrix-based heuristic achieves a similar score of 92.5% APFD. In contrast to prior approaches, we argue that matrix-based techniques are useful beyond the scope of effective prioritization, and enable a number of use cases involving software maintenance.
We validate our findings from continuous integration processes by extending a continuous testing tool within development environments with means of test prioritization, and pose further research questions. We think that our findings are suited to propel adoption of (continuous) testing practices, and that programmers' toolboxes should contain test prioritization as an existential productivity tool.
Background
Maximal isokinetic strength ratios of joint flexors and extensors are important parameters to indicate the level of muscular balance at the joint. Further, in combat sports athletes, upper and lower limb muscle strength is affected by the type of sport. Thus, this study aimed to examine the differences in maximal isokinetic strength of the flexors and extensors and the corresponding flexor–extensor strength ratios of the elbows and knees in combat sports athletes.
Method
Forty male participants (age = 22.3 ± 2.5 years) from four different combat sports (amateur boxing, taekwondo, karate, and judo; n = 10 per sport) were tested for eccentric peak torque of the elbow/knee flexors (EF/KF) and concentric peak torque of the elbow/knee extensors (EE/KE) at three different angular velocities (60, 120, and 180°/s) on the dominant and non-dominant side using an isokinetic device.
Results
Analyses revealed significant, large-sized group × velocity × limb interactions for EF, EE, and EF–EE ratio, KF, KE, and KF–KE ratio (p ≤ 0.03; 0.91 ≤ d ≤ 1.75). Post-hoc analyses indicated that amateur boxers displayed the largest EE strength values on the non-dominant side at ≤ 120°/s and the dominant side at ≥ 120°/s (p < 0.03; 1.21 ≤ d ≤ 1.59). The largest EF–EE strength ratios were observed on amateur boxers’ and judokas’ non-dominant side at ≥ 120°/s (p < 0.04; 1.36 ≤ d ≤ 2.44). Further, we found lower KF–KE strength measures in karate (p < 0.04; 1.12 ≤ d ≤ 6.22) and judo athletes (p ≤ 0.03; 1.60 ≤ d ≤ 5.31) particularly on the non-dominant side.
Conclusions
The present findings indicated combat sport-specific differences in maximal isokinetic strength measures of EF, EE, KF, and KE particularly in favor of amateur boxers on the non-dominant side.
This study examined the spoken narrative skills of a group of bilingual Mandarin–English speaking 3–6-year-olds (N = 25) in Australia, using a remote online story-retell task. Bilingual preschoolers are an understudied population, especially those who are speaking typologically distinct languages such as Mandarin and English which have fewer structural overlaps compared to language pairs that are typologically closer, reducing cross-linguistic positive transfer. We examined these preschoolers’ spoken narrative skills as measured by macrostructures (the global organization of a story) and microstructures (linguistic structures, e.g., total number of utterances, nouns, verbs, phrases, and modifiers) across and within each language, and how various factors such as age and language experiences contribute to individual variability. The results indicate that our bilingual preschoolers acquired spoken narrative skills similarly across their two languages, i.e., showing similar patterns of productivity for macrostructure and microstructure elements in both of their two languages. While chronological age was positively correlated with macrostructures in both languages (showing developmental effects), there were no significant correlations between measures of language experiences and the measures of spoken narrative skills (no effects for language input/output). The findings suggest that although these preschoolers acquire two typologically diverse languages in different learning environments, Mandarin at home with highly educated parents, and English at preschool, they displayed similar levels of oral narrative skills as far as these macro−/micro-structure measures are concerned. This study provides further evidence for the feasibility of remote online assessment of preschoolers’ narrative skills.
The Permo-Triassic period marks the time interval between Hercynian (Variscan) orogenic events in the Tien Shan and the North Pamir, and the Cimmerian accretion of the Gondwana-derived Central and South Pamir to the southern margin of the Paleo-Asian continent. A well-preserved Permo-Triassic volcano-sedimentary sequence from the Chinese North Pamir yields important information on the geodynamic evolution of Asia’s pre-Cimmerian southern margin. The oldest volcanic rocks from that section are dated to the late Guadalupian epoch by a rhyolite and a dacitic dike that gave zircon U-Pb ages of ~260 Ma. Permian volcanism was largely pyroclastic and mafic to intermediate. Upsection, a massive ignimbritic crystal tuff in the Chinese Qimgan valley was dated to 244.1 +/- 1.1 Ma, a similar unit in the nearby Gez valley to 245 +/- 11 Ma, and an associated rhyolite to 233.4 +/- 1.1 Ma. Deposition of the locally ~200 m thick crystal tuff unit follows an unconformity and marks the onset of intense, mainly mafic to intermediate, calc-alkaline magmatic activity. Triassic volcanic activity in the North Pamir was coeval with the major phase of Cimmerian intrusive activity in the Karakul-Mazar arc-accretionary complex to the south, caused by northward subduction of the Paleo-Tethys. It also coincided with the emplacement of basanitic and carbonatitic dikes and a thermal event in the South Tien Shan, to the north of our study area. Evidence for arc-related magmatic activity in a back-arc position provides strong arguments for back-arc extension or transtension and basin formation. This puts the Qimgan succession in line with a more than 1000 km long realm of extensional Triassic back-arc basins known from the North Pamir in the Kyrgyz Altyn Darya valley (Myntekin formation), the North Pamir of Tajikistan and Afghanistan, and the Afghan Hindukush (Doab formation) and further west from the Paropamisus and Kopet Dag (Aghdarband, NE Iran).
Piloting a Survey-Based Assessment of Transparency and Trustworthiness with Three Medical AI Tools
(2022)
Artificial intelligence (AI) offers the potential to support healthcare delivery, but poorly trained or validated algorithms bear risks of harm. Ethical guidelines stated transparency about model development and validation as a requirement for trustworthy AI. Abundant guidance exists to provide transparency through reporting, but poorly reported medical AI tools are common. To close this transparency gap, we developed and piloted a framework to quantify the transparency of medical AI tools with three use cases. Our framework comprises a survey to report on the intended use, training and validation data and processes, ethical considerations, and deployment recommendations. The transparency of each response was scored with either 0, 0.5, or 1 to reflect if the requested information was not, partially, or fully provided. Additionally, we assessed on an analogous three-point scale if the provided responses fulfilled the transparency requirement for a set of trustworthiness criteria from ethical guidelines. The degree of transparency and trustworthiness was calculated on a scale from 0% to 100%. Our assessment of three medical AI use cases pin-pointed reporting gaps and resulted in transparency scores of 67% for two use cases and one with 59%. We report anecdotal evidence that business constraints and limited information from external datasets were major obstacles to providing transparency for the three use cases. The observed transparency gaps also lowered the degree of trustworthiness, indicating compliance gaps with ethical guidelines. All three pilot use cases faced challenges to provide transparency about medical AI tools, but more studies are needed to investigate those in the wider medical AI sector. Applying this framework for an external assessment of transparency may be infeasible if business constraints prevent the disclosure of information. New strategies may be necessary to enable audits of medical AI tools while preserving business secrets.
Effects of fences and fence gaps on the movement behavior of three southern African antelope species
(2022)
Globally, migratory ungulates are affected by fences. While field observational studies reveal the amount of animal–fence interactions across taxa, GPS tracking-based studies uncover fence effects on movement patterns and habitat selection. However, studies on the direct effects of fences and fence gaps on movement behavior, especially based on high-frequency tracking data, are scarce. We used GPS tracking on three common African antelopes (Tragelaphus strepsiceros, Antidorcas marsupialis, and T. oryx) with movement strategies ranging from range residency to nomadism in a semi-arid, Namibian savanna traversed by wildlife-proof fences that elephants have regularly breached. We classified major forms of ungulate–fence interaction types on a seasonal and a daily scale. Furthermore, we recorded the distances and times spent at fences regarding the total individual space use. Based on this, we analyzed the direct effects of fences and fence gaps on the animals’ movement behavior for the previously defined types of animal–fence interactions. Antelope-fence interactions peaked during the early hours of the day and during seasonal transitions when the limiting resource changed between water and forage. Major types of ungulate–fence interactions were quick, trace-like, or marked by halts. We found that the amount of time spent at fences was highest for nomadic eland. Migratory springbok adjusted their space use concerning fence gap positions. If the small home ranges of sedentary kudu included a fence, they frequently interacted with this fence. For springbok and eland, distance traveled along a fence declined with increasing utilization of a fence gap. All species reduced their speed in the proximity of a fence but often increased their speed when encountering the fence. Crossing a fence led to increased speeds for all species. We demonstrate that fence effects mainly occur during crucial foraging times (seasonal scale) and during times of directed movements (daily scale). Importantly, we provide evidence that fences directly alter antelope movement behaviors with negative implications for energy budgets and that persistent fence gaps can reduce the intensity of such alterations. Our findings help to guide future animal–fence studies and provide insights for wildlife fencing and fence gap planning.
Objective: There is a lack of brief rating scales for the reliable assessment of psychotherapeutic skills, which do not require intensive rater training and/or a high level of expertise. Thus, the objective is to validate a 14-item version of the Clinical Communication Skills Scale (CCSS-S).
Methods: Using a sample of N = 690 video-based ratings of role-plays with simulated patients, we calculated a confirmatory factor analysis and an exploratory structural equation modeling (ESEM), assessed convergent validities, determined inter-rater reliabilities and compared these with those who were either psychology students, advanced psychotherapy trainees, or experts.
Results: Correlations with other competence rating scales were high (rs > 0.86–0.89). The intraclass correlations ranged between moderate and good [ICC(2,2) = 0.65–0.80], with student raters yielding the lowest scores. The one-factor model only marginally replicated the data, but the internal consistencies were excellent (α = 0.91–95). The ESEM yielded a two-factor solution (Collaboration and Structuring and Exploration Skills).
Conclusion: The CCSS-S is a brief and valid rating scale that reliably assesses basic communication skills, which is particularly useful for psychotherapy training using standardized role-plays. To ensure good inter-rater reliabilities, it is still advisable to employ raters with at least some clinical experience. Future studies should further investigate the one- or two-factor structure of the instrument.
For life-long learning, an effective learning strategy repertoire is particularly important during acquisition of knowledge in lower secondary school—an educational level characterized with transition into more autonomous learning environments with increased complex academic demands. Using latent profile analysis, we explored the occurrence of different secondary school learner profiles depending on their various combinations of cognitive and metacognitive learning strategy use, as well as their differences in perceived autonomy support, intrinsic motivation, and gender. Data were collected from 576 ninth grade students in Uganda using self-report questionnaires. Four learner profiles were identified: competent strategy user, struggling user, surface-level learner, and deep-level learner profiles. Gender differences were noted in students’ use of elaboration and organization strategies to learn Physics, in favor of girls. In terms of profile memberships, significant differences in gender, intrinsic motivation and perceived autonomy support were also noted. Girls were 2.4–2.7 times more likely than boys to be members of the competent strategy user and surface-level learner profiles. Additionally, higher levels of intrinsic motivation predicted an increased likelihood membership into the deep-level learner profile, while higher levels of perceived teacher autonomy predicted an increased likelihood membership into the competent strategy user profile as compared to other profiles. Further, implications of the findings were discussed.
There is an ongoing debate about how to test and operationalize self-control. This limited understanding is in large part due to a variety of different tests and measures used to assess self-control, as well as the lack of empirical studies examining the temporal dynamics during the exertion of self-control. In order to track changes that occur over the course of exposure to a self-control task, we investigate and compare behavioral, subjective, and physiological indicators during the exertion of self-control. Participants completed both a task requiring inhibitory control (Go/No-Go task) and a control task (two-choice task). Behavioral performance and pupil size were measured during the tasks. Subjective vitality was measured before and after the tasks. While pupil size and subjective vitality showed similar trajectories in the two tasks, behavioral performance decreased in the inhibitory control-demanding task, but not in the control task. However, behavioral, subjective, and physiological measures were not significantly correlated. These results suggest that there is a disconnect between different measures of self-control with high intra- and interindividual variability. Theoretical and methodological implications for self-control theory and future empirical work are discussed.
The link between emotions and motor function has been known for decades but is still not clarified. The Adaptive Force (AF) describes the neuromuscular capability to adapt to increasing forces and was suggested to be especially vulnerable to interfering inputs. This study investigated the influence of pleasant an unpleasant food imagery on the manually assessed AF of elbow and hip flexors objectified by a handheld device in 12 healthy women. The maximal isometric AF was significantly reduced during unpleasant vs. pleasant imagery and baseline (p < 0.001, dz = 0.98–1.61). During unpleasant imagery, muscle lengthening started at 59.00 ± 22.50% of maximal AF, in contrast to baseline and pleasant imagery, during which the isometric position could be maintained mostly during the entire force increase up to ~97.90 ± 5.00% of maximal AF. Healthy participants showed an immediately impaired holding function triggered by unpleasant imagery, presumably related to negative emotions. Hence, AF seems to be suitable to test instantaneously the effect of emotions on motor function. Since musculoskeletal complaints can result from muscular instability, the findings provide insights into the understanding of the causal chain of linked musculoskeletal pain and mental stress. A case example (current stress vs. positive imagery) suggests that the approach presented in this study might have future implications for psychomotor diagnostics and therapeutics.
Basic psychological needs theory postulates that a social environment that satisfies individuals’ three basic psychological needs of autonomy, competence, and relatedness leads to optimal growth and well-being. On the other hand, the frustration of these needs is associated with ill-being and depressive symptoms foremost investigated in non-clinical samples; yet, there is a paucity of research on need frustration in clinical samples. Survey data were compared between adult individuals with major depressive disorder (MDD; n = 115; 48.69% female; 38.46 years, SD = 10.46) with those of a non-depressed comparison sample (n = 201; 53.23% female; 30.16 years, SD = 12.81). Need profiles were examined with a linear mixed model (LMM). Individuals with depression reported higher levels of frustration and lower levels of satisfaction in relation to the three basic psychological needs when compared to non-depressed adults. The difference between depressed and non-depressed groups was significantly larger for frustration than satisfaction regarding the needs for relatedness and competence. LMM correlation parameters confirmed the expected positive correlation between the three needs. This is the first study showing substantial differences in need-based experiences between depressed and non-depressed adults. The results confirm basic assumptions of the self-determination theory and have preliminary implications in tailoring therapy for depression.
Dementia as one of the most prevalent diseases urges for a better understanding of the central mechanisms responsible for clinical symptoms, and necessitates improvement of actual diagnostic capabilities. The brainstem nucleus locus coeruleus (LC) is a promising target for early diagnosis because of its early structural alterations and its relationship to the functional disturbances in the patients. In this study, we applied our improved method of localisation-based LC resting-state fMRI to investigate the differences in central sensory signal processing when comparing functional connectivity (fc) of a patient group with mild cognitive impairment (MCI, n = 28) and an age-matched healthy control group (n = 29). MCI and control participants could be differentiated in their Mini-Mental-State-Examination (MMSE) scores (p < .001) and LC intensity ratio (p = .010). In the fMRI, LC fc to anterior cingulate cortex (FDR p < .001) and left anterior insula (FDR p = .012) was elevated, and LC fc to right temporoparietal junction (rTPJ, FDR p = .012) and posterior cingulate cortex (PCC, FDR p = .021) was decreased in the patient group. Importantly, LC to rTPJ connectivity was also positively correlated to MMSE scores in MCI patients (p = .017). Furthermore, we found a hyperactivation of the left-insula salience network in the MCI patients. Our results and our proposed disease model shed new light on the functional pathogenesis of MCI by directing to attentional network disturbances, which could aid new therapeutic strategies and provide a marker for diagnosis and prediction of disease progression.
Association of primary allostatic load mediators and metabolic syndrome (MetS): A systematic review
(2022)
Allostatic load (AL) exposure may cause detrimental effects on the neuroendocrine system, leading to metabolic syndrome (MetS). The primary mediators of AL involve serum dehydroepiandrosterone sulfate (DHEAS; a functional HPA axis antagonist); further, cortisol, urinary norepinephrine (NE), and epinephrine (EPI) excretion levels (assessed within 12-h urine as a golden standard for the evaluation of the HPA axis activity and sympathetic nervous system activity). However, the evidence of an association between the primary mediators of AL and MetS is limited. This systematic review aimed to critically examine the association between the primary mediators of AL and MetS. PubMed and Web of Science were searched for articles from January 2010 to December 2021, published in English. The search strategy focused on cross-sectional and case–control studies comprising adult participants with MetS, obesity, overweight, and without chronic diseases. The STROBE checklist was used to assess study quality control. Of 770 studies, twenty-one studies with a total sample size (n = 10,666) met the eligibility criteria. Eighteen studies were cross-sectional, and three were case–control studies. The included studies had a completeness of reporting score of COR % = 87.0 ± 6.4%. It is to be noted, that cortisol as a primary mediator of AL showed an association with MetS in 50% (urinary cortisol), 40% (serum cortisol), 60% (salivary cortisol), and 100% (hair cortisol) of the studies. For DHEAS, it is to conclude that 60% of the studies showed an association with MetS. In contrast, urinary EPI and urinary NE had 100% no association with MetS. In summary, there is a tendency for the association between higher serum cortisol, salivary cortisol, urinary cortisol, hair cortisol, and lower levels of DHEAS with MetS. Future studies focusing on longitudinal data are warranted for clarification and understanding of the association between the primary mediators of AL and MetS.
Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical context. This paper evaluates the feasibility of differentially private federated learning for chest X-ray classification as a defense against data privacy attacks. To the best of our knowledge, we are the first to directly compare the impact of differentially private training on two different neural network architectures, DenseNet121 and ResNet50. Extending the federated learning environments previously analyzed in terms of privacy, we simulated a heterogeneous and imbalanced federated setting by distributing images from the public CheXpert and Mendeley chest X-ray datasets unevenly among 36 clients. Both non-private baseline models achieved an area under the receiver operating characteristic curve (AUC) of 0.940.94 on the binary classification task of detecting the presence of a medical finding. We demonstrate that both model architectures are vulnerable to privacy violation by applying image reconstruction attacks to local model updates from individual clients. The attack was particularly successful during later training stages. To mitigate the risk of a privacy breach, we integrated Rényi differential privacy with a Gaussian noise mechanism into local model training. We evaluate model performance and attack vulnerability for privacy budgets ε∈{1,3,6,10}�∈{1,3,6,10}. The DenseNet121 achieved the best utility-privacy trade-off with an AUC of 0.940.94 for ε=6�=6. Model performance deteriorated slightly for individual clients compared to the non-private baseline. The ResNet50 only reached an AUC of 0.760.76 in the same privacy setting. Its performance was inferior to that of the DenseNet121 for all considered privacy constraints, suggesting that the DenseNet121 architecture is more robust to differentially private training.
In recent years digital technologies have become a major means for providing health-related services and this trend was strongly reinforced by the current Coronavirus disease 2019 (COVID-19) pandemic. As it is well-known that regular physical activity has positive effects on individual physical and mental health and thus is an important prerequisite for healthy aging, digital technologies are also increasingly used to promote unstructured and structured forms of physical activity. However, in the course of this development, several terms (e.g., Digital Health, Electronic Health, Mobile Health, Telehealth, Telemedicine, and Telerehabilitation) have been introduced to refer to the application of digital technologies to provide health-related services such as physical interventions. Unfortunately, the above-mentioned terms are often used in several different ways, but also relatively interchangeably. Given that ambiguous terminology is a major source of difficulty in scientific communication which can impede the progress of theoretical and empirical research, this article aims to make the reader aware of the subtle differences between the relevant terms which are applied at the intersection of physical activity and Digital Health and to provide state-of-art definitions for them.
Numerical magnitude information is assumed to be spatially represented in the form of a mental number line defined with respect to a body-centred, egocentric frame of reference. In this context, spatial language skills such as mastery of verbal descriptions of spatial position (e.g., in front of, behind, to the right/left) have been proposed to be relevant for grasping spatial relations between numerical magnitudes on the mental number line. We examined 4- to 5-year-old’s spatial language skills in tasks that allow responses in egocentric and allocentric frames of reference, as well as their relative understanding of numerical magnitude (assessed by a number word comparison task). In addition, we evaluated influences of children’s absolute understanding of numerical magnitude assessed by their number word comprehension (montring different numbers using their fingers) and of their knowledge on numerical sequences (determining predecessors and successors as well as identifying missing dice patterns of a series). Results indicated that when considering responses that corresponded to the egocentric perspective, children’s spatial language was associated significantly with their relative numerical magnitude understanding, even after controlling for covariates, such as children’s SES, mental rotation skills, and also absolute magnitude understanding or knowledge on numerical sequences. This suggests that the use of egocentric reference frames in spatial language may facilitate spatial representation of numbers along a mental number line and thus seem important for preschoolers’ relative understanding of numerical magnitude.
In intervention research, single-case experimental designs are an important way to gain insights into the causes of individual changes that yield high internal validity. They are commonly applied to examine the effectiveness of classroom-based interventions to reduce problem behavior in schools. At the same time, there is no consensus on good design characteristics of single-case experimental designs when dealing with behavioral problems in schools. Moreover, specific challenges arise concerning appropriate approaches to analyzing behavioral data. Our study addresses the interplay between the test power of piecewise regression analysis and important design specifications of single-case research designs. Here, we focus on the influence of the following specifications of single-case research designs: number of measurement times, the initial frequency of the behavior, intervention effect, and data trend. We conducted a Monte-Carlo study. First, simulated datasets were created with specific design conditions based on reviews of published single-case intervention studies. Following, data were analyzed using piecewise Poisson-regression models, and the influence of specific design specifications on the test power was investigated. Our results indicate that piecewise regressions have a high potential of adequately identifying the effects of interventions for single-case studies. At the same time, test power is strongly related to the specific design specifications of the single-case study: Few measurement times, especially in phase A, and low initial frequencies of the behavior make it impossible to detect even large intervention effects. Research designs with a high number of measurement times show robust power. The insights gained are highly relevant for researchers in the field, as decisions during the early stage of conceptualizing and planning single-case experimental design studies may impact the chance to identify an existing intervention effect during the research process correctly.
The aim of this review was to describe and summarize the scientific literature on programming parameters related to jump or plyometric training in male and female soccer players of different ages and fitness levels. A literature search was conducted in the electronic databases PubMed, Web of Science and Scopus using keywords related to the main topic of this study (e.g., “ballistic” and “plyometric”). According to the PICOS framework, the population for the review was restricted to soccer players, involved in jump or plyometric training. Among 7556 identified studies, 90 were eligible for inclusion. Only 12 studies were found for females. Most studies (n = 52) were conducted with youth male players. Moreover, only 35 studies determined the effectiveness of a given jump training programming factor. Based on the limited available research, it seems that a dose of 7 weeks (1–2 sessions per week), with ~80 jumps (specific of combined types) per session, using near-maximal or maximal intensity, with adequate recovery between repetitions (<15 s), sets (≥30 s) and sessions (≥24–48 h), using progressive overload and taper strategies, using appropriate surfaces (e.g., grass), and applied in a well-rested state, when combined with other training methods, would increase the outcome of effective and safe plyometric-jump training interventions aimed at improving soccer players physical fitness. In conclusion, jump training is an effective and easy-to-administer training approach for youth, adult, male and female soccer players. However, optimal programming for plyometric-jump training in soccer is yet to be determined in future research.
Quantifying neurological disorders from voice is a rapidly growing field of research and holds promise for unobtrusive and large-scale disorder monitoring. The data recording setup and data analysis pipelines are both crucial aspects to effectively obtain relevant information from participants. Therefore, we performed a systematic review to provide a high-level overview of practices across various neurological disorders and highlight emerging trends. PRISMA-based literature searches were conducted through PubMed, Web of Science, and IEEE Xplore to identify publications in which original (i.e., newly recorded) datasets were collected. Disorders of interest were psychiatric as well as neurodegenerative disorders, such as bipolar disorder, depression, and stress, as well as amyotrophic lateral sclerosis amyotrophic lateral sclerosis, Alzheimer's, and Parkinson's disease, and speech impairments (aphasia, dysarthria, and dysphonia). Of the 43 retrieved studies, Parkinson's disease is represented most prominently with 19 discovered datasets. Free speech and read speech tasks are most commonly used across disorders. Besides popular feature extraction toolkits, many studies utilise custom-built feature sets. Correlations of acoustic features with psychiatric and neurodegenerative disorders are presented. In terms of analysis, statistical analysis for significance of individual features is commonly used, as well as predictive modeling approaches, especially with support vector machines and a small number of artificial neural networks. An emerging trend and recommendation for future studies is to collect data in everyday life to facilitate longitudinal data collection and to capture the behavior of participants more naturally. Another emerging trend is to record additional modalities to voice, which can potentially increase analytical performance.
Training intervention effects on cognitive performance and neuronal plasticity — A pilot study
(2022)
Studies suggest that people suffering from chronic pain may have altered brain plasticity, along with altered functional connectivity between pain-processing brain regions. These may be related to decreased mood and cognitive performance. There is some debate as to whether physical activity combined with behavioral therapy (e.g. cognitive distraction, body scan) may counteract these changes. However, underlying neuronal mechanisms are unclear. The aim of the current pilot study with a 3-armed randomized controlled trial design was to examine the effects of sensorimotor training for nonspecific chronic low back pain on (1) cognitive performance; (2) fMRI activity co-fluctuations (functional connectivity) between pain-related brain regions; and (3) the relationship between functional connectivity and subjective variables (pain and depression). Six hundred and sixty two volunteers with non-specific chronic low back pain were randomly allocated to a unimodal (sensorimotor training), multidisciplinary (sensorimotor training and behavioral therapy) intervention, or to a control group within a multicenter study. A subsample of patients (n = 21) from one study center participated in the pilot study presented here. Measurements were at baseline, during (3 weeks, M2) and after intervention (12 weeks, M4 and 24 weeks, M5). Cognitive performance was measured by the Trail Making Test and functional connectivity by MRI. Pain perception and depression were assessed by the Von Korff questionnaire and the Hospital and Anxiety. Group differences were calculated by univariate and repeated ANOVA measures and Bayesian statistics; correlations by Pearson's r. Change and correlation of functional connection were analyzed within a pooled intervention group (uni-, multidisciplinary group). Results revealed that participants with increased pain intensity at baseline showed higher functional connectivity between pain-related brain areas used as ROIs in this study. Though small sample sizes limit generalization, cognitive performance increased in the multimodal group. Increased functional connectivity was observed in participants with increased pain ratings. Pain ratings and connectivity in pain-related brain regions decreased after the intervention. The results provide preliminary indication that intervention effects can potentially be achieved on the cognitive and neuronal level. The intervention may be suitable for therapy and prevention of non-specific chronic low back pain.
Genetic divergence and the frequency of hybridization are central for defining species delimitations, especially among cryptic species where morphological differences are merely absent. Rotifers are known for their high cryptic diversity and therefore are ideal model organisms to investigate such patterns. Here, we used the recently resolved Brachionus calyciflorus species complex to investigate whether previously observed between species differences in thermotolerance and gene expression are also reflected in their genomic footprint. We identified a Heat Shock Protein gene (HSP 40 kDa) which exhibits cross species pronounced sequence variation. This gene exhibits species-specific fixed sites, alleles, and sites putatively under positive selection. These sites are located in protein binding regions involved in chaperoning and may therefore reflect adaptive diversification. By comparing three genetic markers (ITS, COI, HSP 40 kDa), we revealed hybridization events between the cryptic species. The low frequency of introgressive haplotypes/alleles suggest a tight, but not fully impermeable boundary between the cryptic species.
In this thesis, I present my contributions to the field of ultrafast molecular spectroscopy. Using the molecule 2-thiouracil as an example, I use ultrashort x-ray pulses from free- electron lasers to study the relaxation dynamics of gas-phase molecular samples. Taking advantage of the x-ray typical element- and site-selectivity, I investigate the charge flow and geometrical changes in the excited states of 2-thiouracil.
In order to understand the photoinduced dynamics of molecules, knowledge about the ground-state structure and the relaxation after photoexcitation is crucial. Therefore, a part of this thesis covers the electronic ground-state spectroscopy of mainly 2-thiouracil to provide the basis for the time-resolved experiments. Many of the previously published studies that focused on the gas-phase time-resolved dynamics of thionated uracils after UV excitation relied on information from solution phase spectroscopy to determine the excitation energies. This is not an optimal strategy as solvents alter the absorption spec- trum and, hence, there is no guarantee that liquid-phase spectra resemble the gas-phase spectra. Therefore, I measured the UV-absorption spectra of all three thionated uracils to provide a gas-phase reference and, in combination with calculations, we determined the excited states involved in the transitions.
In contrast to the UV absorption, the literature on the x-ray spectroscopy of thionated uracil is sparse. Thus, we measured static photoelectron, Auger-Meitner and x-ray absorption spectra on the sulfur L edge before or parallel to the time-resolved experiments we performed at FLASH (DESY, Hamburg). In addition, (so far unpublished) measurements were performed at the synchrotron SOLEIL (France) which have been included in this thesis and show the spin-orbit splitting of the S 2p photoline and its satellite which was not observed at the free-electron laser.
The relaxation of 2-thiouracil has been studied extensively in recent years with ultrafast visible and ultraviolet methods showing the ultrafast nature of the molecular process after photoexcitation. Ultrafast spectroscopy probing the core-level electrons provides a complementary approach to common optical ultrafast techniques. The method inherits its local sensitivity from the strongly localised core electrons. The core energies and core-valence transitions are strongly affected by local valence charge and geometry changes, and past studies have utilised this sensitivity to investigate the molecular process reflected by the ultrafast dynamics. We have built an apparatus that provides the requirements to perform time-resolved x-ray spectroscopy on molecules in the gas phase. With the apparatus, we performed UV-pump x-ray-probe electron spectroscopy on the S 2p edge of 2-thiouracil using the free-electron laser FLASH2. While the UV triggers the relaxation dynamics, the x-ray probes the single sulfur atom inside the molecule. I implemented photoline self-referencing for the photoelectron spectral analysis. This minimises the spectral jitter of the FEL, which is due to the underlying self-amplified spontaneous emission (SASE) process. With this approach, we were not only able to study dynamical changes in the binding energy of the electrons but also to detect an oscillatory behaviour in the shift of the observed photoline, which we associate with non-adiabatic dynamics involving several electronic states. Moreover, we were able to link the UV-induced shift in binding energy to the local charge flow at the sulfur which is directly connected to the electronic state. Furthermore, the analysis of the Auger-Meitner electrons shows that energy shifts observed at early stages of the photoinduced relaxation are related to the geometry change in the molecule. More specifically, the observed increase in kinetic energy of the Auger-Meitner electrons correlates with a previously predicted C=S bond stretch.
This study examines the access to healthcare for children and adolescents with three common chronic diseases (type-1 diabetes (T1D), obesity, or juvenile idiopathic arthritis (JIA)) within the 4th (Delta), 5th (Omicron), and beginning of the 6th (Omicron) wave (June 2021 until July 2022) of the COVID-19 pandemic in Germany in a cross-sectional study using three national patient registries. A paper-and-pencil questionnaire was given to parents of pediatric patients (<21 years) during the routine check-ups. The questionnaire contains self-constructed items assessing the frequency of healthcare appointments and cancellations, remote healthcare, and satisfaction with healthcare. In total, 905 parents participated in the T1D-sample, 175 in the obesity-sample, and 786 in the JIA-sample. In general, satisfaction with healthcare (scale: 0–10; 10 reflecting the highest satisfaction) was quite high (median values: T1D 10, JIA 10, obesity 8.5). The proportion of children and adolescents with canceled appointments was relatively small (T1D 14.1%, JIA 11.1%, obesity 20%), with a median of 1 missed appointment, respectively. Only a few parents (T1D 8.6%; obesity 13.1%; JIA 5%) reported obstacles regarding health services during the pandemic. To conclude, it seems that access to healthcare was largely preserved for children and adolescents with chronic health conditions during the COVID-19 pandemic in Germany.
Why do exercises in collaborative governance often witness more impasse than advantage? This cumulative dissertation undertakes a micro-level analysis of collaborative governance to tackle this research puzzle. It situates micropolitics at the very center of analysis: a wide range of activities, interventions, and tactics used by actors – be they conveners, facilitators, or participants – to shape the collaborative exercise. It is by focusing on these daily minutiae, and on the consequences that they bring along, the study argues, that we can better understand why and how collaboration can become stuck or unproductive. To do so, the foundational part of this dissertation (Article 1) uses power as a sensitizing concept to investigate the micro-dynamics that shape collaboration. It develops an analytical approach to advance the study of collaborative governance at the empirical level under a power-sensitive and process-oriented perspective. The subsequent articles follow the dissertation's red thread of investigating the micropolitics of collaborative governance by showing facilitation artefacts' interrelatedness and contribution to the potential success or failure of collaborative arrangements (Article 2); and by examining the specialized knowledge, skills and practices mobilized when designing a collaborative process (Article 3). The work is based on an abductive research approach, tacking back and forth between empirical data and theory, and offers a repertoire of concepts – from analytical terms (designed and emerging interaction orders, flows of power, arenas for power), to facilitation practices (scripting, situating, and supervising) and types of knowledge (process expertise) – to illustrate and study the detailed and constant work (and rework) that surrounds collaborative arrangements. These concepts sharpen the way researchers can look at, observe, and understand collaborative processes at a micro level. The thesis thereby elucidates the subtleties of power, which may be overlooked if we focus only on outcomes rather than the processes that engender them, and supports efforts to identify potential sources of impasse.
The Arctic nearshore zone plays a key role in the carbon cycle. Organic-rich sediments get eroded off permafrost affected coastlines and can be directly transferred to the nearshore zone. Permafrost in the Arctic stores a high amount of organic matter and is vulnerable to thermo-erosion, which is expected to increase due to climate change. This will likely result in higher sediment loads in nearshore waters and has the potential to alter local ecosystems by limiting light transmission into the water column, thus limiting primary production to the top-most part of it, and increasing nutrient export from coastal erosion. Greater organic matter input could result in the release of greenhouse gases to the atmosphere. Climate change also acts upon the fluvial system, leading to greater discharge to the nearshore zone. It leads to decreasing sea-ice cover as well, which will both increase wave energy and lengthen the open-water season. Yet, knowledge on these processes and the resulting impact on the nearshore zone is scarce, because access to and instrument deployment in the nearshore zone is challenging.
Remote sensing can alleviate these issues in providing rapid data delivery in otherwise non-accessible areas. However, the waters in the Arctic nearshore zone are optically complex, with multiple influencing factors, such as organic rich suspended sediments, colored dissolved organic matter (cDOM), and phytoplankton. The goal of this dissertation was to use remotely sensed imagery to monitor processes related to turbidity caused by suspended sediments in the Arctic nearshore zone. In-situ measurements of water-leaving reflectance and surface water turbidity were used to calibrate a semi-empirical algorithm which relates turbidity from satellite imagery. Based on this algorithm and ancillary ocean and climate variables, the mechanisms underpinning nearshore turbidity in the Arctic were identified at a resolution not achieved before.
The calibration of the Arctic Nearshore Turbidity Algorithm (ANTA) was based on in-situ measurements from the coastal and inner-shelf waters around Herschel Island Qikiqtaruk (HIQ) in the western Canadian Arctic from the summer seasons 2018 and 2019. It performed better than existing algorithms, developed for global applications, in relating turbidity from remotely sensed imagery. These existing algorithms were lacking validation data from permafrost affected waters, and were thus not able to reflect the complexity of Arctic nearshore waters. The ANTA has a higher sensitivity towards the lowest turbidity values, which is an asset for identifying sediment pathways in the nearshore zone. Its transferability to areas beyond HIQ was successfully demonstrated using turbidity measurements matching satellite image recordings from Adventfjorden, Svalbard. The ANTA is a powerful tool that provides robust turbidity estimations in a variety of Arctic nearshore environments.
Drivers of nearshore turbidity in the Arctic were analyzed by combining ANTA results from the summer season 2019 from HIQ with ocean and climate variables obtained from the weather station at HIQ, the ERA5 reanalysis database, and the Mackenzie River discharge. ERA5 reanalysis data were obtained as domain averages over the Canadian Beaufort Shelf. Nearshore turbidity was linearly correlated to wind speed, significant wave height and wave period. Interestingly, nearshore turbidity was only correlated to wind speed at the shelf, but not to the in-situ measurements from the weather station at HIQ. This shows that nearshore turbidity, albeit being of limited spatial extent, gets influenced by the weather conditions multiple kilometers away, rather than in its direct vicinity. The large influence of wave energy on nearshore turbidity indicates that freshly eroded material off the coast is a major contributor to the nearshore sediment load. This contrasts results from the temperate and tropical oceans, where tides and currents are the major drivers of nearshore turbidity. The Mackenzie River discharge was not identified as a driver of nearshore turbidity in 2019, however, the analysis of 30 years of Landsat archive imagery from 1986 to 2016 suggests a direct link between the prevailing wind direction, which heavily influences the Mackenzie River plume extent, and nearshore turbidity around HIQ. This discrepancy could be caused by the abnormal discharge behavior of the Mackenzie River in 2019.
This dissertation has substantially advanced the understanding of suspended sediment processes in the Arctic nearshore zone and provided new monitoring tools for future studies. The presented results will help to understand the role of the Arctic nearshore zone in the carbon cycle under a changing climate.
Land-use intensification is the main factor for the catastrophic decline of insect pollinators. However, land-use intensification includes multiple processes that act across various scales and should affect pollinator guilds differently depending on their ecology. We aimed to reveal how two main pollinator guilds, wild bees and hoverflies, respond to different land-use intensification measures, that is, arable field cover (AFC), landscape heterogeneity (LH), and functional flower composition of local plant communities as a measure of habitat quality. We sampled wild bees and hoverflies on 22 dry grassland sites within a highly intensified landscape (NE Germany) within three campaigns using pan traps. We estimated AFC and LH on consecutive radii (60–3000 m) around the dry grassland sites and estimated the local functional flower composition. Wild bee species richness and abundance was positively affected by LH and negatively by AFC at small scales (140–400 m). In contrast, hoverflies were positively affected by AFC and negatively by LH at larger scales (500–3000 m), where both landscape parameters were negatively correlated to each other. At small spatial scales, though, LH had a positive effect on hoverfly abundance. Functional flower diversity had no positive effect on pollinators, but conspicuous flowers seem to attract abundance of hoverflies. In conclusion, landscape parameters contrarily affect two pollinator guilds at different scales. The correlation of landscape parameters may influence the observed relationships between landscape parameters and pollinators. Hence, effects of land-use intensification seem to be highly landscape-specific.
In numerical processing, the functional role of Spatial-Numerical Associations (SNAs, such as the association of smaller numbers with left space and larger numbers with right space, the Mental Number Line hypothesis) is debated. Most studies demonstrate SNAs with lateralized responses, and there is little evidence that SNAs appear when no response is required. We recorded passive holding grip forces in no-go trials during number processing. In Experiment 1, participants performed a surface numerical decision task (“Is it a number or a letter?”). In Experiment 2, we used a deeper semantic task (“Is this number larger or smaller than five?”). Despite instruction to keep their grip force constant, participants' spontaneous grip force changed in both experiments: Smaller numbers led to larger force increase in the left than in the right hand in the numerical decision task (500–700 ms after stimulus onset). In the semantic task, smaller numbers again led to larger force increase in the left hand, and larger numbers increased the right-hand holding force. This effect appeared earlier (180 ms) and lasted longer (until 580 ms after stimulus onset). This is the first demonstration of SNAs with passive holding force. Our result suggests that (1) explicit motor response is not a prerequisite for SNAs to appear, and (2) the timing and strength of SNAs are task-dependent. (216 words).
Background and Aims Wearable inertial sensors may offer additional kinematic parameters of the shoulder compared to traditional instruments such as goniometers when elaborate and time-consuming data processing procedures are undertaken. However, in clinical practice simple-real time motion analysis is required to improve clinical reasoning. Therefore, the aim was to assess the criterion validity between a portable "off-the-shelf" sensor-software system (IMU) and optical motion (Mocap) for measuring kinematic parameters during active shoulder movements. Methods 24 healthy participants (9 female, 15 male, age 29 +/- 4 years, height 177 +/- 11 cm, weight 73 +/- 14 kg) were included. Range of motion (ROM), total range of motion (TROM), peak and mean angular velocity of both systems were assessed during simple (abduction/adduction, horizontal flexion/horizontal extension, vertical flexion/extension, and external/internal rotation) and complex shoulder movements. Criterion validity was determined using intraclass-correlation coefficients (ICC), root mean square error (RMSE) and Bland and Altmann analysis (bias; upper and lower limits of agreement). Results ROM and TROM analysis revealed inconsistent validity during simple (ICC: 0.040-0.733, RMSE: 9.7 degrees-20.3 degrees, bias: 1.2 degrees-50.7 degrees) and insufficient agreement during complex shoulder movements (ICC: 0.104-0.453, RMSE: 10.1 degrees-23.3 degrees, bias: 1.0 degrees-55.9 degrees). Peak angular velocity (ICC: 0.202-0.865, RMSE: 14.6 degrees/s-26.7 degrees/s, bias: 10.2 degrees/s-29.9 degrees/s) and mean angular velocity (ICC: 0.019-0.786, RMSE:6.1 degrees/s-34.2 degrees/s, bias: 1.6 degrees/s-27.8 degrees/s) were inconsistent. Conclusions The "off-the-shelf" sensor-software system showed overall insufficient agreement with the gold standard. Further development of commercial IMU-software-solutions may increase measurement accuracy and permit their integration into everyday clinical practice.
Anomalous diffusion or, more generally, anomalous transport, with nonlinear dependence of the mean-squared displacement on the measurement time, is ubiquitous in nature. It has been observed in processes ranging from microscopic movement of molecules to macroscopic, large-scale paths of migrating birds. Using data from multiple empirical systems, spanning 12 orders of magnitude in length and 8 orders of magnitude in time, we employ a method to detect the individual underlying origins of anomalous diffusion and transport in the data. This method decomposes anomalous transport into three primary effects: long-range correlations (“Joseph effect”), fat-tailed probability density of increments (“Noah effect”), and nonstationarity (“Moses effect”). We show that such a decomposition of real-life data allows us to infer nontrivial behavioral predictions and to resolve open questions in the fields of single-particle tracking in living cells and movement ecology.
Background
Non-invasive transcutaneous auricular vagus nerve stimulation (taVNS) has received tremendous attention as a potential neuromodulator of cognitive and affective functions, which likely exerts its effects via activation of the locus coeruleus-noradrenaline (LC-NA) system. Reliable effects of taVNS on markers of LC-NA system activity, however, have not been demonstrated yet.
Methods
The aim of the present study was to overcome previous limitations by pooling raw data from a large sample of ten taVNS studies (371 healthy participants) that collected salivary alpha-amylase (sAA) as a potential marker of central NA release.
Results
While a meta-analytic approach using summary statistics did not yield any significant effects, linear mixed model analyses showed that afferent stimulation of the vagus nerve via taVNS increased sAA levels compared to sham stimulation (b = 0.16, SE = 0.05, p = 0.001). When considering potential confounders of sAA, we further replicated previous findings on the diurnal trajectory of sAA activity.
Conclusion(s)
Vagal activation via taVNS increases sAA release compared to sham stimulation, which likely substantiates the assumption that taVNS triggers NA release. Moreover, our results highlight the benefits of data pooling and data sharing in order to allow stronger conclusions in research.
Flood risk management in Germany follows an integrative approach in which both private households and businesses can make an important contribution to reducing flood damage by implementing property-level adaptation measures. While the flood adaptation behavior of private households has already been widely researched, comparatively less attention has been paid to the adaptation strategies of businesses. However, their ability to cope with flood risk plays an important role in the social and economic development of a flood-prone region. Therefore, using quantitative survey data, this study aims to identify different strategies and adaptation drivers of 557 businesses damaged by a riverine flood in 2013 and 104 businesses damaged by pluvial or flash floods between 2014 and 2017. Our results indicate that a low perceived self-efficacy may be an important factor that can reduce the motivation of businesses to adapt to flood risk. Furthermore, property-owners tended to act more proactively than tenants. In addition, high experience with previous flood events and low perceived response costs could strengthen proactive adaptation behavior. These findings should be considered in business-tailored risk communication.
Predation is a strong species interaction causing severe harm or death to prey. Thus, prey species have evolved various defence strategies to minimize predation risk, which may be immediate (e.g., a change in behaviour) or transgenerational (morphological defence structures). We studied the behaviour of two strains of a rotiferan prey (Brachionus calyciflorus) that differ in their ability to develop morphological defences in response to their predator Asplanchna brightwellii. Using video analysis, we tested: (a) if two strains differ in their response to predator presence and predator cues when both are undefended; (b) whether defended individuals respond to live predators or their cues; and (c) if the morphological defence (large spines) per se has an effect on the swimming behaviour. We found a clear increase in swimming speed for both undefended strains in predator presence. However, the defended specimens responded neither to the predator presence nor to their cues, showing that they behave indifferently to their predator when they are defended. We did not detect an effect of the spines on the swimming behaviour. Our study demonstrates a complex plastic behaviour of the prey, not only in the presence of their predator, but also with respect to their defence status.
The Pamir Frontal Thrust (PFT) located in the Trans Alai range in Central Asia is the principal active fault of the intracontinental India-Eurasia convergence zone and constitutes the northernmost boundary of the Pamir orogen at the NW edge of this collision zone. Frequent seismic activity and ongoing crustal shortening reflect the northward propagation of the Pamir into the intermontane Alai Valley. Quaternary deposits are being deformed and uplifted by the advancing thrust front of the Trans Alai range. The Alai Valley separates the Pamir range front from the Tien Shan mountains in the north; the Alai Valley is the vestige of a formerly contiguous basin that linked the Tadjik Depression in the west with the Tarim Basin in the east. GNSS measurements across the Central Pamir document a shortening rate of ~25 mm/yr, with a dramatic decrease of ~10-15 mm over a short distance across the northernmost Trans Alai range. This suggests that almost half of the shortening in the greater Pamir – Tien Shan collision zone is absorbed along the PFT. The short-term (geodetic) and long-term (geologic) shortening rates across the northern Pamir appear to be at odds with an apparent slip-rate discrepancy along the frontal fault system of the Pamir. Moreover, the present-day seismicity and historical records have not revealed great Mw > 7 earthquakes that might be expected with such a significant slip accommodation. In contrast, recent and historic earthquakes exhibit complex rupture patterns within and across seismotectonic segments bounding the Pamir mountain front, challenging our understanding of fault interaction and the seismogenic potential of this area, and leaving the relationships between seismicity and the geometry of the thrust front not well understood.
In this dissertation I employ different approaches to assess the seismogenic behavior along the PFT. Firstly, I provide paleoseismic data from five trenches across the central PFT segment (cPFT) and compute a segment-wide earthquake chronology over the past 16 kyr. This novel dataset provides important insights into the recurrence, magnitude, and rupture extent of past earthquakes along the cPFT. I interpret five, possibly six paleoearthquakes that have ruptured the Pamir mountain front since ∼7 ka and 16 ka, respectively. My results indicate that at least three major earthquakes ruptured the full-segment length and possibly crossed segment boundaries with a recurrence interval of ∼1.9 kyr and potential magnitudes of up to Mw 7.4. Importantly, I did not find evidence for great (i.e., Mw ≥8) earthquakes.
Secondly, I combine my paleoseimic results with morphometric analyses to establish a segment-wide distribution of the cumulative vertical separation along offset fluvial terraces and I model a long-term slip rate for the cPFT. My investigations reveal discrepancies between the extents of slip and rupture during apparent partial segment ruptures in the western half of the cPFT. Combined with significantly higher fault scarp offsets in this sector of the cPFT, the observations indicate a more mature fault section with a potential for future fault linkage. I estimate an average rate of horizontal motion for the cPFT of 4.1 ± 1.5 mm/yr during the past ∼5 kyr, which does not fully match the GNSS-derived present-day shortening rate of ∼10 mm/yr. This suggests a complex distribution of strain accumulation and potential slip partitioning between the cPFT and additional faults and folds within the Pamir that may be associated with a partially locked regional décollement.
The third part of the thesis provides new insights regarding the surface rupture of the 2008 Mw 6.6 Nura earthquake that ruptured along the eastern PFT sector. I explore this rupture in the context of its structural complexity by combining extensive field observations with high-resolution digital surface models. I provide a map of the rupture extent, net slip measurements, and updated regional geological observations. Based on this data I propose a tectonic model in this area associated with secondary flexural-slip faulting along steeply dipping bedding of folded Paleogene sedimentary strata that is related to deformation along a deeper blind thrust. Here, the strain release seems to be transferred from the PFT towards older inherited basement structures within the area of advanced Pamir-Tien Shan collision zone.
The extensive research of my dissertation results in a paleoseismic database of the past 16 ~kyr, which contributes to the understanding of the seismogenic behavior of the PFT, but also to that of segmented thrust-fault systems in active collisional settings. My observations underscore the importance of combining different methodological approaches in the geosciences, especially in structurally complex tectonic settings like the northern Pamir. Discrepancy between GNSS-derived present-day deformation rates and those from different geological archives in the central part, as well as the widespread distribution of the deformation due to earthquake triggered strain transfer in the eastern part reveals the complexity of this collision zone and calls for future studies involving multi-temporal and interdisciplinary approaches.
Identifying urban pluvial flood-prone areas is necessary but the application of two-dimensional hydrodynamic models is limited to small areas. Data-driven models have been showing their ability to map flood susceptibility but their application in urban pluvial flooding is still rare. A flood inventory (4333 flooded locations) and 11 factors which potentially indicate an increased hazard for pluvial flooding were used to implement convolutional neural network (CNN), artificial neural network (ANN), random forest (RF) and support vector machine (SVM) to: (1) Map flood susceptibility in Berlin at 30, 10, 5, and 2 m spatial resolutions. (2) Evaluate the trained models' transferability in space. (3) Estimate the most useful factors for flood susceptibility mapping. The models' performance was validated using the Kappa, and the area under the receiver operating characteristic curve (AUC). The results indicated that all models perform very well (minimum AUC = 0.87 for the testing dataset). The RF models outperformed all other models at all spatial resolutions and the RF model at 2 m spatial resolution was superior for the present flood inventory and predictor variables. The majority of the models had a moderate performance for predictions outside the training area based on Kappa evaluation (minimum AUC = 0.8). Aspect and altitude were the most influencing factors on the image-based and point-based models respectively. Data-driven models can be a reliable tool for urban pluvial flood susceptibility mapping wherever a reliable flood inventory is available.
Large-scale databases that report the inhibitory capacities of many combinations of candidate drug compounds and cultivated cancer cell lines have driven the development of preclinical drug-sensitivity models based on machine learning. However, cultivated cell lines have devolved from human cancer cells over years or even decades under selective pressure in culture conditions. Moreover, models that have been trained on in vitro data cannot account for interactions with other types of cells. Drug-response data that are based on patient-derived cell cultures, xenografts, and organoids, on the other hand, are not available in the quantities that are needed to train high-capacity machine-learning models. We found that pre-training deep neural network models of drug sensitivity on in vitro drug-sensitivity databases before fine-tuning the model parameters on patient-derived data improves the models’ accuracy and improves the biological plausibility of the features, compared to training only on patient-derived data. From our experiments, we can conclude that pre-trained models outperform models that have been trained on the target domains in the vast majority of cases.
Background
Animal personality has emerged as a key concept in behavioral ecology. While many studies have demonstrated the influence of personality traits on behavioral patterns, its quantification, especially in wild animal populations, remains a challenge. Only a few studies have established a link between personality and recurring movements within home ranges, although these small-scale movements are of key importance for identifying ecological interactions and forming individual niches. In this regard, differences in space use among individuals might reflect different exploration styles between behavioral types along the shy-bold continuum.
Methods
We assessed among-individual differences in behavior in the European hare (Lepus europaeus), a characteristic mammalian herbivore in agricultural landscapes using a standardized box emergence test for captive and wild hares. We determined an individuals’ degree of boldness by measuring the latencies of behavioral responses in repeated emergence tests in captivity. During capture events of wild hares, we conducted a single emergence test and recorded behavioral responses proven to be stable over time in captive hares. Applying repeated novel environment tests in a near-natural enclosure, we further quantified aspects of exploration and activity in captive hares. Finally, we investigated whether and how this among-individual behavioral variation is related to general activity and space use in a wild hare population. Wild and captive hares were treated similarly and GPS-collared with internal accelerometers prior to release to the wild or the outdoor enclosure, respectively. General activity was quantified as overall dynamic body acceleration (ODBA) obtained from accelerometers. Finally, we tested whether boldness explained variation in (i) ODBA in both settings and (ii) variation in home ranges and core areas across different time scales of GPS-collared hares in a wild population.
Results
We found three behavioral responses to be consistent over time in captive hares. ODBA was positively related to boldness (i.e., short latencies to make first contact with the new environment) in both captive and wild hares. Space use in wild hares also varied with boldness, with shy individuals having smaller core areas and larger home ranges than bold conspecifics (yet in some of the parameter space, this association was just marginally significant).
Conclusions
Against our prediction, shy individuals occupied relatively large home ranges but with small core areas. We suggest that this space use pattern is due to them avoiding risky, and energy-demanding competition for valuable resources. Carefully validated, activity measurements (ODBA) from accelerometers provide a valuable tool to quantify aspects of animal personality along the shy-bold continuum remotely. Without directly observing—and possibly disturbing—focal individuals, this approach allows measuring variability in animal personality, especially in species that are difficult to assess with experiments. Considering that accelerometers are often already built into GPS units, we recommend activating them at least during the initial days of tracking to estimate individual variation in general activity and, if possible, match them with a simple novelty experiment. Furthermore, information on individual behavioral types will help to facilitate mechanistic understanding of processes that drive spatial and ecological dynamics in heterogeneous landscapes.
The importance of carbohydrate structures is enormous due to their ubiquitousness in our lives. The development of so-called glycomaterials is the result of this tremendous significance. These are not exclusively used for research into fundamental biological processes, but also, among other things, as inhibitors of pathogens or as drug delivery systems. This work describes the development of glycomaterials involving the synthesis of glycoderivatives, -monomers and -polymers. Glycosylamines were synthesized as precursors in a single synthesis step under microwave irradiation to significantly shorten the usual reaction time. Derivatization at the anomeric position was carried out according to the methods developed by Kochetkov and Likhorshetov, which do not require the introduction of protecting groups. Aminated saccharide structures formed the basis for the synthesis of glycomonomers in β-configuration by methacrylation. In order to obtain α-Man-based monomers for interactions with certain α-Man-binding lectins, a monomer synthesis by Staudinger ligation was developed in this work, which also does not require protective groups. Modification of the primary hydroxyl group of a saccharide was accomplished by enzyme-catalyzed synthesis. Ribose-containing cytidine was transesterified using the lipase Novozym 435 and microwave irradiation. The resulting monomer synthesis was optimized by varying the reaction partners. To create an amide bond instead of an ester bond, protected cytidine was modified by oxidation followed by amide coupling to form the monomer. This synthetic route was also used to isolate the monomer from its counterpart guanosine. After obtaining the nucleoside-based monomers, they were block copolymerized using the RAFT method. Pre-synthesized pHPMA served as macroCTA to yield cytidine- or guanosine-containing block copolymer. These isolated block copolymers were then investigated for their self-assembly behavior using UV-Vis, DLS and SEM to serve as a potential thermoresponsive drug delivery system.
Diabetes is hallmarked by high blood glucose levels, which cause progressive generalised vascular damage, leading to microvascular and macrovascular complications. Diabetes-related complications cause severe and prolonged morbidity and are a major cause of mortality among people with diabetes. Despite increasing attention to risk factors of type 2 diabetes, existing evidence is scarce or inconclusive regarding vascular complications and research investigating both micro- and macrovascular complications is lacking. This thesis aims to contribute to current knowledge by identifying risk factors – mainly related to lifestyle – of vascular complications, addressing methodological limitations of previous literature and providing comparative data between micro- and macrovascular complications.
To address this overall aim, three specific objectives were set. The first was to investigate the effects of diabetes complication burden and lifestyle-related risk factors on the incidence of (further) complications. Studies suggest that diabetes complications are interrelated. However, they have been studied mainly independently of individuals’ complication burden. A five-state time-to-event model was constructed to examine the longitudinal patterns of micro- (kidney disease, neuropathy and retinopathy) and macrovascular complications (myocardial infarction and stroke) and their association with the occurrence of subsequent complications. Applying the same model, the effect of modifiable lifestyle factors, assessed alone and in combination with complication load, on the incidence of diabetes complications was studied. The selected lifestyle factors were body mass index (BMI), waist circumference, smoking status, physical activity, and intake of coffee, red meat, whole grains, and alcohol. Analyses were conducted in a cohort of 1199 participants with incident type 2 diabetes from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam, who were free of vascular complications at diabetes diagnosis. During a median follow-up time of 11.6 years, 96 cases of macrovascular complications (myocardial infarction and stroke) and 383 microvascular complications (kidney disease, neuropathy and retinopathy) were identified. In multivariable-adjusted models, the occurrence of a microvascular complication was associated with a higher incidence of further micro- (Hazard ratio [HR] 1.90; 95% Confidence interval [CI] 0.90, 3.98) and macrovascular complications (HR 4.72; 95% CI 1.25, 17.68), compared with persons without a complication burden. In addition, participants who developed a macrovascular event had a twofold higher risk of future microvascular complications (HR 2.26; 95% CI 1.05, 4.86). The models were adjusted for age, sex, state duration, education, lifestyle, glucose-lowering medication, and pre-existing conditions of hypertension and dyslipidaemia. Smoking was positively associated with macrovascular disease, while an inverse association was observed with higher coffee intake. Whole grain and alcohol intake were inversely associated with microvascular complications, and a U-shaped association was observed for red meat intake. BMI and waist circumference were positively associated with microvascular events. The associations between lifestyle factors and incidence of complications were not modified by concurrent complication burden, except for red meat intake and smoking status, where the associations were attenuated among individuals with a previous complication.
The second objective was to perform an in-depth investigation of the association between BMI and BMI change and risk of micro- and macrovascular complications. There is an ongoing debate on the association between obesity and risk of macrovascular and microvascular outcomes in type 2 diabetes, with studies suggesting a protective effect among people with overweight or obesity. These findings, however, might be limited due to suboptimal control for smoking, pre-existing chronic disease, or short-follow-up. After additional exclusion of persons with cancer history at diabetes onset, the associations between pre-diagnosis BMI and relative annual change between pre- and post-diagnosis BMI and incidence of complications were evaluated in multivariable-adjusted Cox models. The analyses were adjusted for age, sex, education, smoking status and duration, physical activity, alcohol consumption, adherence to the Mediterranean diet, and family history of diabetes and cardiovascular disease (CVD). Among 1083 EPIC-Potsdam participants, 85 macrovascular and 347 microvascular complications were identified during a median follow-up period of 10.8 years. Higher pre-diagnosis BMI was associated with an increased risk of total microvascular complications (HR per 5 kg/m2 1.21; 95% CI 1.07, 1.36), kidney disease (HR 1.39; 95% CI 1.21, 1.60) and neuropathy (HR 1.12; 95% CI 0.96, 1.31); but no association was observed for macrovascular complications (HR 1.05; 95% CI 0.81, 1.36). Effect modification was not evident by sex, smoking status, or age groups. In analyses according to BMI change categories, BMI loss of more than 1% indicated a decreased risk of total microvascular complications (HR 0.62; 95% CI 0.47, 0.80), kidney disease (HR 0.57; 95% CI 0.40, 0.81) and neuropathy (HR 0.73; 95% CI 0.52, 1.03), compared with participants with a stable BMI. No clear association was observed for macrovascular complications (HR 1.04; 95% CI 0.62, 1.74). The impact of BMI gain on diabetes-related vascular disease was less evident. Associations were consistent across strata of age, sex, pre-diagnosis BMI, or medication but appeared stronger among never-smokers than current or former smokers.
The last objective was to evaluate whether individuals with a high-risk profile for diabetes and cardiovascular disease (CVD) also have a greater risk of complications. Within the EPIC-Potsdam study, two accurate prognostic tools were developed, the German Diabetes Risk Score (GDRS) and the CVD Risk Score (CVDRS), which predict the 5-year type 2 diabetes risk and 10-year CVD risk, respectively. Both scores provide a non-clinical and clinical version. Components of the risk scores include age, sex, waist circumference, prevalence of hypertension, family history of diabetes or CVD, lifestyle factors, and clinical factors (only in clinical versions). The association of the risk scores with diabetes complications and their discriminatory performance for complications were assessed. In crude Cox models, both versions of GDRS and CVDRS were positively associated with macrovascular complications and total microvascular complications, kidney disease and neuropathy. Higher GDRS was also associated with an elevated risk of retinopathy. The discrimination of the scores (clinical and non-clinical) was poor for all complications, with the C-index ranging from 0.58 to 0.66 for macrovascular complications and from 0.60 to 0.62 for microvascular complications.
In conclusion, this work illustrates that the risk of complication development among individuals with type 2 diabetes is related to the existing complication load, and attention should be given to regular monitoring for future complications. It underlines the importance of weight management and adherence to healthy lifestyle behaviours, including high intake of whole grains, moderation in red meat and alcohol consumption and avoidance of smoking to prevent major diabetes-associated complications, regardless of complication burden. Risk scores predictive for type 2 diabetes and CVD were related to elevated risks of complications. By optimising several lifestyle and clinical factors, the risk score can be improved and may assist in lowering complication risk.
Among the multitude of geomorphological processes, aeolian shaping processes are of special character, Pedogenic dust is one of the most important sources of atmospheric aerosols and therefore regarded as a key player for atmospheric processes. Soil dust emissions, being complex in composition and properties, influence atmospheric processes and air quality and has impacts on other ecosystems. In this because even though their immediate impact can be considered low (exceptions exist), their constant and large-scale force makes them a powerful player in the earth system. dissertation, we unravel a novel scientific understanding of this complex system based on a holistic dataset acquired during a series of field experiments on arable land in La Pampa, Argentina. The field experiments as well as the generated data provide information about topography, various soil parameters, the atmospheric dynamics in the very lower atmosphere (4m height) as well as measurements regarding aeolian particle movement across a wide range of particle size classes between 0.2μm up to the coarse sand.
The investigations focus on three topics: (a) the effects of low-scale landscape structures on aeolian transport processes of the coarse particle fraction, (b) the horizontal and vertical fluxes of the very fine particles and (c) the impact of wind gusts on particle emissions.
Among other considerations presented in this thesis, it could in particular be shown, that even though the small-scale topology does have a clear impact on erosion and deposition patterns, also physical soil parameters need to be taken into account for a robust statistical modelling of the latter. Furthermore, specifically the vertical fluxes of particulate matter have different characteristics for the particle size classes. Finally, a novel statistical measure was introduced to quantify the impact of wind gusts on the particle uptake and its application on the provided data set. The aforementioned measure shows significantly increased particle concentrations during points in time defined as gust event.
With its holistic approach, this thesis further contributes to the fundamental understanding of how atmosphere and pedosphere are intertwined and affect each other.
The increasing demand for energy in the current technological era and the recent political decisions about giving up on nuclear energy diverted humanity to focus on alternative environmentally friendly energy sources like solar energy. Although silicon solar cells are the product of a matured technology, the search for highly efficient and easily applicable materials is still ongoing. These properties made the efficiency of halide perovskites comparable with silicon solar cells for single junctions within a decade of research. However, the downside of halide perovskites are poor stability and lead toxicity for the most stable ones.
On the other hand, chalcogenide perovskites are one of the most promising absorber materials for the photovoltaic market, due to their elemental abundance and chemical stability against moisture and oxygen. In the search of the ultimate solar absorber material, combining the good optoelectronic properties of halide perovskites with the stability of chalcogenides could be the promising candidate.
Thus, this work investigates new techniques for the synthesis and design of these novel chalcogenide perovskites, that contain transition metals as cations, e.g., BaZrS3, BaHfS3, EuZrS3, EuHfS3 and SrHfS3. There are two stages in the deposition techniques of this study: In the first stage, the binary compounds are deposited via a solution processing method. In the second stage, the deposited materials are annealed in a chalcogenide atmosphere to form the perovskite structure by using solid-state reactions.
The research also focuses on the optimization of a generalized recipe for a molecular ink to deposit precursors of chalcogenide perovskites with different binaries. The implementation of the precursor sulfurization resulted in either binaries without perovskite formation or distorted perovskite structures, whereas some of these materials are reported in the literature as they are more favorable in the needle-like non-perovskite configuration.
Lastly, there are two categories for the evaluation of the produced materials: The first category is about the determination of the physical properties of the deposited layer, e.g., crystal structure, secondary phase formation, impurities, etc. For the second category, optoelectronic properties are measured and compared to an ideal absorber layer, e.g., band gap, conductivity, surface photovoltage, etc.
Glaciated high-alpine areas are fundamentally altered by climate change, with well-known implications for hydrology, e.g., due to glacier retreat, longer snow-free periods, and more frequent and intense summer rainstorms. While knowledge on how these hydrological changes will propagate to suspended sediment dynamics is still scarce, it is needed to inform mitigation and adaptation strategies. To understand the processes and source areas most relevant to sediment dynamics, we analyzed discharge and sediment dynamics in high temporal resolution as well as their patterns on several spatial scales, which to date few studies have done.
We used a nested catchment setup in the Upper Ötztal in Tyrol, Austria, where high-resolution (15 min) time series of discharge and suspended sediment concentrations are available for up to 15 years (2006–2020). The catchments of the gauges in Vent, Sölden and Tumpen range from 100 to almost 800 km2 with 10 % to 30 % glacier cover and span an elevation range of 930 to 3772 m a.s.l. We analyzed discharge and suspended sediment yields (SSY), their distribution in space, their seasonality and spatial differences therein, and the relative importance of short-term events. We complemented our analysis by linking the observations to satellite-based snow cover maps, glacier inventories, mass balances and precipitation data.
Our results indicate that the areas above 2500 m a.s.l., characterized by glacier tongues and the most recently deglaciated areas, are crucial for sediment generation in all sub-catchments. This notion is supported by the synchronous spring onset of sediment export at the three gauges, which coincides with snowmelt above 2500 m but lags behind spring discharge onsets. This points at a limitation of suspended sediment supply as long as the areas above 2500 m are snow-covered. The positive correlation of annual SSY with glacier cover (among catchments) and glacier mass balances (within a catchment) further supports the importance of the glacier-dominated areas. The analysis of short-term events showed that summer precipitation events were associated with peak sediment concentrations and yields but on average accounted for only 21 % of the annual SSY in the headwaters. These results indicate that under current conditions, thermally induced sediment export (through snow and glacier melt) is dominant in the study area.
Our results extend the scientific knowledge on current hydro-sedimentological conditions in glaciated high-alpine areas and provide a baseline for studies on projected future changes in hydro-sedimentological system dynamics.
Mammalian arachidonic acid lipoxygenases (ALOXs) have been implicated in cell differentiation and in the pathogenesis of inflammation. The mouse genome involves seven functional Alox genes and the encoded enzymes share a high degree of amino acid conservation with their human orthologs. There are, however, functional differences between mouse and human ALOX orthologs. Human ALOX15B oxygenates arachidonic acid exclusively to its 15-hydroperoxy derivative (15S-HpETE), whereas 8S-HpETE is dominantly formed by mouse Alox15b. The structural basis for this functional difference has been explored and in vitro mutagenesis humanized the reaction specificity of the mouse enzyme. To explore whether this mutagenesis strategy may also humanize the reaction specificity of mouse Alox15b in vivo, we created Alox15b knock-in mice expressing the arachidonic acid 15-lipoxygenating Tyr603Asp+His604Val double mutant instead of the 8-lipoxygenating wildtype enzyme. These mice are fertile, display slightly modified plasma oxylipidomes and develop normally up to an age of 24 weeks. At later developmental stages, male Alox15b-KI mice gain significantly less body weight than outbred wildtype controls, but this effect was not observed for female individuals. To explore the possible reasons for the observed gender-specific growth arrest, we determined the basic hematological parameters and found that aged male Alox15b-KI mice exhibited significantly attenuated red blood cell parameters (erythrocyte counts, hematocrit, hemoglobin). Here again, these differences were not observed in female individuals. These data suggest that humanization of the reaction specificity of mouse Alox15b impairs the functionality of the hematopoietic system in males, which is paralleled by a premature growth arrest.
Current business organizations want to be more efficient and constantly evolving to find ways to retain talent. It is well established that visionary leadership plays a vital role in organizational success and contributes to a better working environment. This study aims to determine the effect of visionary leadership on employees' perceived job satisfaction. Specifically, it investigates whether the mediators meaningfulness at work and commitment to the leader impact the relationship. I take support from job demand resource theory to explain the overarching model used in this study and broaden-and-build theory to leverage the use of mediators.
To test the hypotheses, evidence was collected in a multi-source, time-lagged design field study of 95 leader-follower dyads. The data was collected in a three-wave study, each survey appearing after one month. Data on employee perception of visionary leadership was collected in T1, data for both mediators were collected in T2, and employee perception of job satisfaction was collected in T3. The findings display that meaningfulness at work and commitment to the leader play positive intervening roles (in the form of a chain) in the indirect influence of visionary leadership on employee perceptions regarding job satisfaction.
This research offers contributions to literature and theory by first broadening the existing knowledge on the effects of visionary leadership on employees. Second, it contributes to the literature on constructs meaningfulness at work, commitment to the leader, and job satisfaction. Third, it sheds light on the mediation mechanism dealing with study variables in line with the proposed model. Fourth, it integrates two theories, job demand resource theory and broaden-and-build theory providing further evidence. Additionally, the study provides practical implications for business leaders and HR practitioners.
Overall, my study discusses the potential of visionary leadership behavior to elevate employee outcomes. The study aligns with previous research and answers several calls for further research on visionary leadership, job satisfaction, and mediation mechanism with meaningfulness at work and commitment to the leader.
Microplastics in the environments are estimated to increase in the near future due to increasing consumption of plastic product and also due to further fragmentation in small pieces. The fate and effects of MP once released into the freshwater environment are still scarcely studied, compared to the marine environment. In order to understand possible effect and interaction of MPs in freshwater environment, planktonic zooplankton organisms are very useful for their crucial trophic role. In particular freshwater rotifers are one of the most abundant organisms and they are the interface between primary producers and secondary consumers. The aim of my thesis was to investigate the ingestion and the effect of MPs in rotifers from a more natural scenario and to individuate processes such as the aggregation of MPs, the food dilution effect and the increasing concentrations of MPs that could influence the final outcome of MPs in the environment. In fact, in a near natural scenario MPs interaction with bacteria and algae, aggregations together with the size and concentration are considered drivers of ingestion and effect. The aggregation of MPs makes smaller MPs more available for rotifers and larger MPs less ingested. The negative effect caused by the ingestion of MPs was modulated by their size but also by the quantity and the quality of food that cause variable responses. In fact, rotifers in the environment are subjected to food limitation and the presence of MPs could exacerbate this condition and decrease the population and the reproduction input. Finally, in a scenario incorporating an entire zooplanktonic community, MPs were ingested by most individuals taking into account their feeding mode but also the concentration of MPs, which was found to be essential for the availability of MPs. This study highlights the importance to investigate MPs from a more environmental perspective, this in fact could provide an alternative and realistic view of effect of MPs in the ecosystem.
The first step towards assessing hazards in seismically active regions involves mapping capable faults and estimating their recurrence times. While the mapping of active faults is commonly based on distinct geologic and geomorphic features evident at the surface, mapping blind seismogenic faults is complicated by the absence of on-fault diagnostic features. Here we investigated the Pichilemu Fault in coastal Chile, unknown until it generated a Mw 7.0 earthquake in 2010. The lack of evident surface faulting suggests activity along a partly-hidden blind fault. We used off-fault deformed marine terraces to estimate a fault-slip rate of 0.52 ± 0.04 m/ka, which, when integrated with satellite geodesy suggests a 2.12 ± 0.2 ka recurrence time for Mw~7.0 normal-faulting earthquakes. We propose that extension in the Pichilemu region is associated with stress changes during megathrust earthquakes and accommodated by sporadic slip during upper-plate earthquakes, which has implications for assessing the seismic potential of cryptic faults along convergent margins and elsewhere.
Simultaneous Barcode Sequencing of Diverse Museum Collection Specimens Using a Mixed RNA Bait Set
(2022)
A growing number of publications presenting results from sequencing natural history collection specimens reflect the importance of DNA sequence information from such samples. Ancient DNA extraction and library preparation methods in combination with target gene capture are a way of unlocking archival DNA, including from formalin-fixed wet-collection material. Here we report on an experiment, in which we used an RNA bait set containing baits from a wide taxonomic range of species for DNA hybridisation capture of nuclear and mitochondrial targets for analysing natural history collection specimens. The bait set used consists of 2,492 mitochondrial and 530 nuclear RNA baits and comprises specific barcode loci of diverse animal groups including both invertebrates and vertebrates. The baits allowed to capture DNA sequence information of target barcode loci from 84% of the 37 samples tested, with nuclear markers being captured more frequently and consensus sequences of these being more complete compared to mitochondrial markers. Samples from dry material had a higher rate of success than wet-collection specimens, although target sequence information could be captured from 50% of formalin-fixed samples. Our study illustrates how efforts to obtain barcode sequence information from natural history collection specimens may be combined and are a way of implementing barcoding inventories of scientific collection material.
Isoflux tension propagation (IFTP) theory and Langevin dynamics (LD) simulations are employed to study the dynamics of channel-driven polymer translocation in which a polymer translocates into a narrow channel and the monomers in the channel experience a driving force fc. In the high driving force limit, regardless of the channel width, IFTP theory predicts τ ∝ f βc for the translocation time, where β = −1 is the force scaling exponent. Moreover, LD data show that for a very narrow channel fitting only a single file of monomers, the entropic force due to the subchain inside the channel does not play a significant role in the translocation dynamics and the force exponent β = −1 regardless of the force magnitude. As the channel width increases the number of possible spatial configurations of the subchain inside the channel becomes significant and the resulting entropic force causes the force exponent to drop below unity.