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Kim et al. recently measured the structure factor of deeply supercooled water droplets (Reports, 22 December 2017, p. 1589). We raise several concerns about their data analysis and interpretation. In our opinion, the reported data do not lead to clear conclusions about the origins of water’s anomalies.
In their comment on our paper (Caesar et al 2020 Environ. Res. Lett. 15 024003), Chen and Tung (hereafter C&T) argue that our analysis, showing that over the last decades Atlantic meridional overturning circulation (AMOC) strength and global mean surface temperature (GMST) were positively correlated, is incorrect. Their claim is mainly based on two arguments, neither of which is justified: first, C&T claim that our analysis is based on 'established evidence' that was only true for preindustrial conditions-this is not the case. Using data from the modern period (1947-2012), we show that the established understanding (i.e. deep-water formation in the North Atlantic cools the deep ocean and warms the surface) is correct, but our analysis is not based on this fact. Secondly, C&T claim that our results are based on a statistical analysis of only one cycle of data which was furthermore incorrectly detrended. This, too, is not true. Our conclusion that a weaker AMOC delays the current surface warming rather than enhances it, is based on several independent lines of evidence. The data we show to support this covers more than one cycle and the detrending (which was performed to avoid spurious correlations due to a common trend) does not affect our conclusion: the correlation between AMOC strength and GMST is positive. We do not claim that this is strong evidence that the two time series are in phase, but rather that this means that the two time series are not anti-correlated.
A distinguishing feature of Answer Set Programming is that all atoms belonging to a stable model must be founded. That is, an atom must not only be true but provably true. This can be made precise by means of the constructive logic of Here-and-There, whose equilibrium models correspond to stable models. One way of looking at foundedness is to regard Boolean truth values as ordered by letting true be greater than false. Then, each Boolean variable takes the smallest truth value that can be proven for it. This idea was generalized by Aziz to ordered domains and applied to constraint satisfaction problems. As before, the idea is that a, say integer, variable gets only assigned to the smallest integer that can be justified. In this paper, we present a logical reconstruction of Aziz’ idea in the setting of the logic of Here-and-There. More precisely, we start by defining the logic of Here-and-There with lower bound founded variables along with its equilibrium models and elaborate upon its formal properties. Finally, we compare our approach with related ones and sketch future work.
Several overlapping crises which affected the EU during the past ten years have recently aggravated. Especially the progressing refugee crisis, the persisting financial crisis and geopolitical turmoil in the EU's neighbourhood contributed to the rise of anti-EU movements and diverse articulations of Euroscepticism. Although public opinion and mainstream political analysis have easily identified right-wing populism as one of the most important drivers, it is still doubtful if it can be equated with Euroscepticism without further ado. To date it is by no means clear how and where Euroscepticism exactly originates.
Adsorption of amino acids on the magnetite-(111)-surface: a force field study (vol 19, 851, 2013)
(2016)
Learning how to prove
(2018)
We have developed an alternative approach to teaching computer science students how to prove. First, students are taught how to prove theorems with the Coq proof assistant. In a second, more difficult, step students will transfer their acquired skills to the area of textbook proofs. In this article we present a realisation of the second step. Proofs in Coq have a high degree of formality while textbook proofs have only a medium one. Therefore our key idea is to reduce the degree of formality from the level of Coq to textbook proofs in several small steps. For that purpose we introduce three proof styles between Coq and textbook proofs, called line by line comments, weakened line by line comments, and structure faithful proofs. While this article is mostly conceptional we also report on experiences with putting our approach into practise.
We present a project combining lidar, photometer and particle counter data with a regularization software tool for a closure study of aerosol microphysical property retrieval. In a first step only lidar data are used to retrieve the particle size distribution (PSD). Secondly, photometer data are added, which results in a good consistency of the retrieved PSDs. Finally, those retrieved PSDs may be compared with the measured PSD from a particle counter. The data here were taken in Ny Alesund, Svalbard, as an example.
For a singularly perturbed parabolic - ODE system we construct the asymptotic expansion in the small parameter in the case, when the degenerate equation has a double root. Such systems, which are called partly dissipative reaction-diffusion systems, are used to model various natural processes, including the signal transmission along axons, solid combustion and the kinetics of some chemical reactions. It turns out that the algorithm of the construction of the boundary layer functions and the behavior of the solution in the boundary layers essentially differ from that ones in case of a simple root. The multizonal initial and boundary layers behaviour was stated.
We investigate how the technology acceptance and learning experience of the digital education platform HPI Schul-Cloud (HPI School Cloud) for German secondary school teachers can be improved by proposing a user-centered research and development framework. We highlight the importance of developing digital learning technologies in a user-centered way to take differences in the requirements of educators and students into account. We suggest applying qualitative and quantitative methods to build a solid understanding of a learning platform's users, their needs, requirements, and their context of use. After concept development and idea generation of features and areas of opportunity based on the user research, we emphasize on the application of a multi-attribute utility analysis decision-making framework to prioritize ideas rationally, taking results of user research into account. Afterward, we recommend applying the principle build-learn-iterate to build prototypes in different resolutions while learning from user tests and improving the selected opportunities. Last but not least, we propose an approach for continuous short- and long-term user experience controlling and monitoring, extending existing web- and learning analytics metrics.
Tailed bacteriophages specific for Gram‐negative bacteria encounter lipopolysaccharide (LPS) during the first infection steps. Yet, it is not well understood how biochemistry of these initial interactions relates to subsequent events that orchestrate phage adsorption and tail rearrangements to initiate cell entry. For many phages, long O‐antigen chains found on the LPS of smooth bacterial strains serve as essential receptor recognized by their tailspike proteins (TSP). Many TSP are depolymerases and O‐antigen cleavage was described as necessary step for subsequent orientation towards a secondary receptor. However, O‐antigen specific host attachment must not always come along with O‐antigen degradation. In this issue of Molecular Microbiology Prokhorov et al. report that coliphage G7C carries a TSP that deacetylates O‐antigen but does not degrade it, whereas rough strains or strains lacking O‐antigen acetylation remain unaffected. Bacteriophage G7C specifically functionalizes its tail by attaching the deacetylase TSP directly to a second TSP that is nonfunctional on the host's O‐antigen. This challenges the view that bacteriophages use their TSP only to clear their way to a secondary receptor. Rather, O‐antigen specific phages may employ enzymatically active TSP as a tool for irreversible LPS membrane binding to initiate subsequent infection steps.
New Public Governance (NPG) as a paradigm for collaborative forms of public service delivery and Blockchain governance are trending topics for researchers and practitioners alike. Thus far, each topic has, on the whole, been discussed separately. This paper presents the preliminary results of ongoing research which aims to shed light on the more concrete benefits of Blockchain for the purpose of NPG. For the first time, a conceptual analysis is conducted on process level to spot benefits and limitations of Blockchain-based governance. Per process element, Blockchain key characteristics are mapped to functional aspects of NPG from a governance perspective. The preliminary results show that Blockchain offers valuable support for governments seeking methods to effectively coordinate co-producing networks. However, the extent of benefits of Blockchain varies across the process elements. It becomes evident that there is a need for off-chain processes. It is, therefore, argued in favour of intensifying research on off-chain governance processes to better understand the implications for and influences on on-chain governance.
Monte-Carlo calculations are carried out to simulate the light transport in dense materials. Focus lies on the calculation of diffuse light transmission through films of scattering and absorbing media considering additionally the effect of dependent scattering. Different influences like interaction type between particles, particle size, composition etc. can be studied by this program. Simulations in this study show major influences on the diffuse transmission. Further simulations are carried out to model a sunscreen film and study best compositions of this film and will be presented.
Peace orders of modern times
(2019)
Monitoring is a key prerequisite for self-adaptive software and many other forms of operating software. Monitoring relevant lower level phenomena like the occurrences of exceptions and diagnosis data requires to carefully examine which detailed information is really necessary and feasible to monitor. Adaptive monitoring permits observing a greater variety of details with less overhead, if most of the time the MAPE-K loop can operate using only a small subset of all those details. However, engineering such an adaptive monitoring is a major engineering effort on its own that further complicates the development of self-adaptive software. The proposed approach overcomes the outlined problems by providing generic adaptive monitoring via runtime models. It reduces the effort to introduce and apply adaptive monitoring by avoiding additional development effort for controlling the monitoring adaptation. Although the generic approach is independent from the monitoring purpose, it still allows for substantial savings regarding the monitoring resource consumption as demonstrated by an example.
Monitoring is a key functionality for automated decision making as it is performed by self-adaptive systems, too. Effective monitoring provides the relevant information on time. This can be achieved with exhaustive monitoring causing a high overhead consumption of economical and ecological resources. In contrast, our generic adaptive monitoring approach supports effectiveness with increased efficiency. Also, it adapts to changes regarding the information demand and the monitored system without additional configuration and software implementation effort. The approach observes the executions of runtime model queries and processes change events to determine the currently required monitoring configuration. In this paper we explicate different possibilities to use the approach and evaluate their characteristics regarding the phenomenon detection time and the monitoring effort. Our approach allows balancing between those two characteristics. This makes it an interesting option for the monitoring function of self-adaptive systems because for them usually very short-lived phenomena are not relevant.
I can see it in your face
(2018)
The US perennially has a far higher poverty rate than peer-rich democracies.1 This high poverty rate in the US presents an enormous challenge to population health given that considerable research demonstrates that being in poverty is bad for one’s health.2 Despite valuable contributions of prior research on income and mortality, the quantity of mortality associated with poverty in the US remains uknown. In this cohort study, we estimated the association between poverty and mortality and quantified the proportion and number of deaths associated with poverty.
Foreword
(2018)
We propose a new temporal extension of the logic of Here-and-There (HT) and its equilibria obtained by combining it with dynamic logic over (linear) traces. Unlike previous temporal extensions of HT based on linear temporal logic, the dynamic logic features allow us to reason about the composition of actions. For instance, this can be used to exercise fine grained control when planning in robotics, as exemplified by GOLOG. In this paper, we lay the foundations of our approach, and refer to it as Linear Dynamic Equilibrium Logic, or simply DEL. We start by developing the formal framework of DEL and provide relevant characteristic results. Among them, we elaborate upon the relationships to traditional linear dynamic logic and previous temporal extensions of HT.
This special issue, "Concrete constraints of abstract concepts", addresses the role of concrete determinants, both external and internal to the human body, in acquisition, processing and use of abstract concepts while at the same time presenting to the readers an overview of methods used to assess their representation.
We consider chimera states in a one-dimensional medium of nonlinear nonlocally coupled phase oscillators. Stationary inhomogeneous solutions of the Ott-Antonsen equation for a complex order parameter that correspond to fundamental chimeras have been constructed. Stability calculations reveal that only some of these states are stable. The direct numerical simulation has shown that these structures under certain conditions are transformed to breathing chimera regimes because of the development of instability. Further development of instability leads to turbulent chimeras.
We investigated online electrophysiological components of distributional learning, specifically of tones by listeners of a non tonal language. German listeners were presented with a bimodal distribution of syllables with lexical tones from a synthesized continuum based on Cantonese level tones. Tones were presented in sets of four standards (within-category tokens) followed by a deviant (across-category token). Mismatch negativity (MMN) was measured. Earlier behavioral data showed that exposure to this bimodal distribution improved both categorical perception and perceptual acuity for level tones [I]. In the present study we present analyses of the electrophysiological response recorded during this exposure, i.e., the development of the MMN response during distributional learning. This development over time is analyzed using Generalized Additive Mixed Models and results showed that the MMN amplitude increased for both within and across-category tokens, reflecting higher perceptual acuity accompanying category formation. This is evidence that learners zooming in on phonological categories undergo neural changes associated with more accurate phonetic perception.
Modern server systems with large NUMA architectures necessitate (i) data being distributed over the available computing nodes and (ii) NUMA-aware query processing to enable effective parallel processing in database systems. As these architectures incur significant latency and throughout penalties for accessing non-local data, queries should be executed as close as possible to the data. To further increase both performance and efficiency, data that is not relevant for the query result should be skipped as early as possible. One way to achieve this goal is horizontal partitioning to improve static partition pruning. As part of our ongoing work on workload-driven partitioning, we have implemented a recent approach called aggressive data skipping and extended it to handle both analytical as well as transactional access patterns. In this paper, we evaluate this approach with the workload and data of a production enterprise system of a Global 2000 company. The results show that over 80% of all tuples can be skipped in average while the resulting partitioning schemata are surprisingly stable over time.
While the IEEE 802.15.4 radio standard has many features that meet the requirements of Internet of things applications, IEEE 802.15.4 leaves the whole issue of key management unstandardized. To address this gap, Krentz et al. proposed the Adaptive Key Establishment Scheme (AKES), which establishes session keys for use in IEEE 802.15.4 security. Yet, AKES does not cover all aspects of key management. In particular, AKES comprises no means for key revocation and rekeying. Moreover, existing protocols for key revocation and rekeying seem limited in various ways. In this paper, we hence propose a key revocation and rekeying protocol, which is designed to overcome various limitations of current protocols for key revocation and rekeying. For example, our protocol seems unique in that it routes around IEEE 802.15.4 nodes whose keys are being revoked. We successfully implemented and evaluated our protocol using the Contiki-NG operating system and aiocoap.
Secondary mica minerals collected from the Santa Helena (W- (Cu) mineralization) and Venise (W-Mo mineralization) endogenic breccia structures were Ar-40/Ar-39 dated. The muscovite Ar-40/Ar-39 data yielded 286.8 +/- 1.2 (+/- 1 sigma) Ma (samples 6Ha and 11Ha) which reflect the age of secondary muscovite formation probably from magmatic biotite or feldspar alteration. Sericite Ar-40/Ar-39 data yielded 280.9 +/- 1.2 (+/- 1 sigma) Ma to 279.0 +/- 1.1 (+/- 1 sigma) Ma (samples 6Hb and 11Hb) reflecting the age of greisen alteration (T similar to 300 degrees C) where the W- disseminated mineralization occurs. The muscovite 40Ar/39Ar data of 277.3 +/- 1.3 (+/- 1 sigma) Ma and 281.3 +/- 1.2 (+/- 1 sigma) Ma (samples 5 and 6) also reflect the age of muscovite (selvage) crystallized adjacent to molybdenite veins within the Venise breccia. Geochronological data obtained confirmed that the W mineralization at Santa Helena breccia is older than Mo-mineralization at Venise breccia. Also, the timing of hydrothermal circulation and the cooling history for the W-stage deposition was no longer than 7 Ma and 4 Ma for Mo-deposition.
Modern routing algorithms reduce query time by depending heavily on preprocessed data. The recently developed Navigation Data Standard (NDS) enforces a separation between algorithms and map data, rendering preprocessing inapplicable. Furthermore, map data is partitioned into tiles with respect to their geographic coordinates. With the limited memory found in portable devices, the number of tiles loaded becomes the major factor for run time. We study routing under these restrictions and present new algorithms as well as empirical evaluations. Our results show that, on average, the most efficient algorithm presented uses more than 20 times fewer tile loads than a normal A*.
Editorial
(2018)
"Never doubt that a small group of thoughtful, committed citizens can change the world; indeed, it's the only thing that ever has. - Margaret Mead."
With the last issue of this year we want to point out directions towards what will come and what challenges and opportunities lie ahead of us. More needed than ever are joint creative efforts to find ways to collaborate and innovate in order to secure the wellbeing of our earth for the next generation to come. We have found ourselves puzzled that we could assemble a sustainability issue without having a call for papers or a special issue. In fact, many of the submissions we currently receive, deal with sustainable, ecological or novel approaches to management and organizations. As creativity and innovation are undisputable necessary ingredients for reaching the sustainable development goals, empirical proof and research in this area are still in their infancy. While the role of design and design thinking has been highlighted before for solving wicked societal problems, a lot more research is needed which creative and innovative ways organisations and societies can take to find solutions to climate change, poverty, hunger and education. We would therefore like to call to you, our readers and writers to tackle these problems with your research.
The first article in this issue addresses one of the above named challenges - the role of innovation for achieving the transition to a low-carbon energy world. In “Innovating for low-carbon energy through hydropower: Enabling a conservation charity's transition to a low-carbon community”, the authors John Gallagher, Paul Coughlan, A. Prysor Williams and Aonghus McNabola look at how an eco-design approach has supported a community transition to low-carbon. They highlight the importance of effective management as well as external collaboration and how the key for success lay in fostering an open environment for creativity and idea sharing. The second article addresses another of the grand challenges, the future of mobility and uses a design-driven approach to develop scenarios for mobility in cities. In “Designing radical innovations of meanings for society: envisioning new scenarios for smart mobility”, the authors Claudio Dell'Era, Naiara Altuna and Roberto Verganti investigate how new meanings can be designed and proposed to society rather than to individuals in the particular context of smart mobility. Through two case studies the authors argue for a multi-level perspective, taking the perspective of the society to solve societal challenges while considering the needs of the individual. The latter is needed because we will not change if our needs are not addressed. Furthermore, the authors find that both, meaning and technology need to be considered to create radical innovation for society. The role of meaning continues in the third article in this issue. The authors Marta Gasparin and William Green show in their article “Reconstructing meaning without redesigning products: The case of the Serie7 chair” how meaning changes over time even though the product remains the same. Through an in-depth retrospective study of the Serie 7 chair the authors investigate the relationship between meaning and the materiality of the object, and show the importance of materiality in constructing product meaning over long periods. Translating this meaning over the course of the innovation process is an important task of management in order to gain buy-in from all involved stakeholders. In the following article “A systematic approach for new technology development by using a biomimicry-based TRIZ contradiction matrix” the authors Byungun Yoon, Chaeguk Lim, Inchae Park and Dooseob Yoon develop a systematic process combining biomimicry and technology-based TRIZ in order to solve technological problems or develop new technologies based on completely new sources or combinations from technology and biology.
In the fifth article in this issue “Innovating via Building Absorptive Capacity: Interactive Effects of Top Management Support of Learning, Employee Learning Orientation, and Decentralization Structure” the authors Li-Yun Sun, Chenwei Li and Yuntao Dong examine the effect of learning-related personal and contextual factors on organizational absorptive capability and subsequent innovative performance. The authors find positive effects as well as a moderation influence of decentralized organizational decision-making structures. In the sixth article “Creativity within boundaries: social identity and the development of new ideas in franchise systems” the authors Fanny Simon, Catherine Allix-Desfautaux, Nabil Khelil and Anne-Laure Le Nadant address the paradox of balancing novelty and conformity for creativity in a franchise system. This research is one of the first we know to explicitly address creativity and innovation in such a rigid and pre-determined system. Using a social identity perspective, they can show that social control, which may be exerted by manipulating group identity, is an efficient lever to increase both the creation and the diffusion of the idea. Furthermore, they show that franchisees who do not conform to the norm of the group are stigmatized and must face pressure from the group to adapt their behaviors. This has important implications for future research. In the following article “Exploring employee interactions and quality of contributions in intra-organisational innovation platforms” the authors Dimitra Chasanidou, Njål Sivertstol and Jarle Hildrum examine the user interactions in an intra-organisational innovation platform, and also address the influence of user interactions for idea development. The authors find that employees communicate through the innovation platform with different interaction, contribution and collaboration types and propose three types of contribution qualities—passive, efficient and balanced contribution. In the eighth article “Ready for Take-off”: How Open Innovation influences startup success” Cristina Marullo, Elena Casprini, Alberto di Minin and Andrea Piccaluga seek to predict new venture success based on factors that can be observed in the pre-startup phase. The authors introduce different variables of founding teams and how these relate to startup success. Building on large-scale dataset of submitted business plans at UC Berkeley, they can show that teams with high skills diversity and past joint experience are a lot better able to prevent the risk of business failure at entry and to adapt the internal resources to market conditions. Furthermore, it is crucial for the team to integrate many external knowledge sources into their process (openness) in order to be successful. The crucial role of knowledge and how it is communicated and shared is the focal point of Natalya Sergeeva's and Anna Trifilova's article on “The role of storytelling in the innovation process”. They authors can show how storytelling has an important role to play when it comes to motivating employees to innovate and promoting innovation success stories inside and outside the organization. The deep human desire to hear and experience stories is also addressed in the last article in this issue “Gamification Approaches to the Early Stage of Innovation” by Rui Patricio, Antonio Moreira and Francesco Zurlo. Using gamification approaches at the early stage of innovation promises to create better team coherence, let employees experience fun and engagement, improve communication and foster knowledge exchange. Using an analytical framework, the authors analyze 15 articles that have looked at gamification in the context of innovation management before. They find that gamification indeed supports firms in becoming better at performing complex innovation tasks and managing innovation challenges. Furthermore, gamification in innovation creates a space for inspiration, improves creativity and the generation of high potential ideas.
Editorial
(2019)
Background:
The overall goal of the project ‘StiEL’ is to contribute to the professional development of teachers and other educational staff working at German secondary schools. The aim is to develop an evidence-based training concept for the inclusion of students with diverse abilities. The project is organized as a collaborative research effort of three partnering institutions and funded by the German Federal Ministry of Education and Research from 2018-2021.
Methods:
To support the on-going transition towards inclusive school practices, a multi-stage approach is envisaged. The first phase aims at a scoping review of existing literature and programmes on inclusion. The overview is supplemented by interviews with school staff members. Training modules are developed in the second project phase. The third phase of StiEL puts the newly developed training program into practice. The knowledge and skills acquired by the participants through the training as well as the teaching and management of inclusive classrooms after the training are evaluated through longitudinal and ethnographic approaches. The final project phase creates a best practice manual and makes the modules available via open access databases.
Results:
The presentation will focus on the first phase and try to explore the health-related consequences of the transition towards an inclusive school system in Germany for different participants. We will present preliminary results of expert interviews as well as some results from the literature screening. Due to our findings the current practice on German schools towards the road to inclusion is very stressful for all participants. We will explore recommendations for health promoting schools under conditions of inclusion.
Conclusions:
In terms of health-related consequences for all participants, the road to inclusion is very ambitious but also very stressful. Regarding the development of an inclusive school system, we need to focus much more on health and health promotion.
User-generated content on social media platforms is a rich source of latent information about individual variables. Crawling and analyzing this content provides a new approach for enterprises to personalize services and put forward product recommendations. In the past few years, brands made a gradual appearance on social media platforms for advertisement, customers support and public relation purposes and by now it became a necessity throughout all branches. This online identity can be represented as a brand personality that reflects how a brand is perceived by its customers. We exploited recent research in text analysis and personality detection to build an automatic brand personality prediction model on top of the (Five-Factor Model) and (Linguistic Inquiry and Word Count) features extracted from publicly available benchmarks. The proposed model reported significant accuracy in predicting specific personality traits form brands. For evaluating our prediction results on actual brands, we crawled the Facebook API for 100k posts from the most valuable brands' pages in the USA and we visualize exemplars of comparison results and present suggestions for future directions.
ASEDS
(2018)
The Massive adoption of social media has provided new ways for individuals to express their opinion and emotion online. In 2016, Facebook introduced a new reactions feature that allows users to express their psychological emotions regarding published contents using so-called Facebook reactions. In this paper, a framework for predicting the distribution of Facebook post reactions is presented. For this purpose, we collected an enormous amount of Facebook posts associated with their reactions labels using the proposed scalable Facebook crawler. The training process utilizes 3 million labeled posts for more than 64,000 unique Facebook pages from diverse categories. The evaluation on standard benchmarks using the proposed features shows promising results compared to previous research. The final model is able to predict the reaction distribution on Facebook posts with a recall score of 0.90 for "Joy" emotion.
Network Creation Games are a well-known approach for explaining and analyzing the structure, quality and dynamics of real-world networks like the Internet and other infrastructure networks which evolved via the interaction of selfish agents without a central authority. In these games selfish agents which correspond to nodes in a network strategically buy incident edges to improve their centrality. However, past research on these games has only considered the creation of networks with unit-weight edges. In practice, e.g. when constructing a fiber-optic network, the choice of which nodes to connect and also the induced price for a link crucially depends on the distance between the involved nodes and such settings can be modeled via edge-weighted graphs. We incorporate arbitrary edge weights by generalizing the well-known model by Fabrikant et al. [PODC'03] to edge-weighted host graphs and focus on the geometric setting where the weights are induced by the distances in some metric space. In stark contrast to the state-of-the-art for the unit-weight version, where the Price of Anarchy is conjectured to be constant and where resolving this is a major open problem, we prove a tight non-constant bound on the Price of Anarchy for the metric version and a slightly weaker upper bound for the non-metric case. Moreover, we analyze the existence of equilibria, the computational hardness and the game dynamics for several natural metrics. The model we propose can be seen as the game-theoretic analogue of a variant of the classical Network Design Problem. Thus, low-cost equilibria of our game correspond to decentralized and stable approximations of the optimum network design.
Our dignity in your hands
(2024)
Riback et al. (Reports, 13 October 2017, p. 238) used small-angle x-ray scattering (SAXS) experiments to infer a degree of compaction for unfolded proteins in water versus chemical denaturant that is highly consistent with the results from Forster resonance energy transfer (FRET) experiments. There is thus no "contradiction" between the two methods, nor evidence to support their claim that commonly used FRET fluorophores cause protein compaction.
In this Comment, we review the results of pattern formation in a reaction-diffusion-advection system following the kinetics of the Gray-Scott model. A recent paper by Das [Phys. Rev. E 92, 052914 (2015)] shows that spatiotemporal chaos of the intermittency type can disappear as the advective flow is increased. This study, however, refers to a single point in the space of kinetic parameters of the original Gray-Scott model. Here we show that the wealth of patterns increases substantially as some of these parameters are changed. In addition to spatiotemporal intermittency, defect-mediated turbulence can also be found. In all cases, however, the chaotic behavior is seen to disappear as the advective flow is increased, following a scenario similar to what was reported in our earlier work [I. Berenstein and C. Beta, Phys. Rev. E 86, 056205 (2012)] as well as by Das. We also point out that a similar phenomenon can be found in other reaction-diffusion-advection models, such as the Oregonator model for the Belousov-Zhabotinsky reaction under flow conditions.
Modern production infrastructures of globally operating companies usually consist of multiple distributed production sites. While the organization of individual sites consisting of Industry 4.0 components itself is demanding, new questions regarding the organization and allocation of resources emerge considering the total production network. In an attempt to face the challenge of efficient distribution and processing both within and across sites, we aim to provide a hybrid simulation approach as a first step towards optimization. Using hybrid simulation allows us to include real and simulated concepts and thereby benchmark different approaches with reasonable effort. A simulation concept is conceptualized and demonstrated qualitatively using a global multi-site example.
In the comment on "Varves of the Dead Sea sedimentary record." Quaternary Science Reviews 215 (Ben Dor et al., 2019): 173-184. by R. Bookman, two recently published papers are suggested to prove that the interpretation of the laminated sedimentary sequence of the Dead Sea, deposited mostly during MIS2 and Holocene pluvials, as annual deposits (i.e., varves) is wrong. In the following response, we delineate several lines of evidence which coalesce to demonstrate that based on the vast majority of evidence, including some of the evidence provided in the comment itself, the interpretation of these sediments as varves is the more likely scientific conclusion. We further discuss the evidence brought up in the comment and its irrelevance and lack of robustness for addressing the question under discussion.
Operational decisions in business processes can be modeled by using the Decision Model and Notation (DMN). The complementary use of DMN for decision modeling and of the Business Process Model and Notation (BPMN) for process design realizes the separation of concerns principle. For supporting separation of concerns during the design phase, it is crucial to understand which aspects of decision-making enclosed in a process model should be captured by a dedicated decision model. Whereas existing work focuses on the extraction of decision models from process control flow, the connection of process-related data and decision models is still unexplored. In this paper, we investigate how process-related data used for making decisions can be represented in process models and we distinguish a set of BPMN patterns capturing such information. Then, we provide a formal mapping of the identified BPMN patterns to corresponding DMN models and apply our approach to a real-world healthcare process.
In university teaching today, it is common practice to record regular lectures and special events such as conferences and speeches. With these recordings, a large fundus of video teaching material can be created quickly and easily. Typically, lectures have a length of about one and a half hours and usually take place once or twice a week based on the credit hours. Depending on the number of lectures and other events recorded, the number of recordings available is increasing rapidly, which means that an appropriate form of provisioning is essential for the students. This is usually done in the form of lecture video platforms. In this work, we have investigated how lecture video platforms and the contained knowledge can be improved and accessed more easily by an increasing number of students. We came up with a multistep process we have applied to our own lecture video web portal that can be applied to other solutions as well.
Traditional economic theory could not explain, much less predict, the near collapse of the financial system and its long-lasting effects on the global economy. Since the 2008 crisis, there has been increasing interest in using ideas from complexity theory to make sense of economic and financial markets. Concepts, such as tipping points, networks, contagion, feedback, and resilience have entered the financial and regulatory lexicon, but actual use of complexity models and results remains at an early stage. Recent insights and techniques offer potential for better monitoring and management of highly interconnected economic and financial systems and, thus, may help anticipate and manage future crises.
Detecting and recognizing text in natural scene images is a challenging, yet not completely solved task. In recent years several new systems that try to solve at least one of the two sub-tasks (text detection and text recognition) have been proposed. In this paper we present SEE, a step towards semi-supervised neural networks for scene text detection and recognition, that can be optimized end-to-end. Most existing works consist of multiple deep neural networks and several pre-processing steps. In contrast to this, we propose to use a single deep neural network, that learns to detect and recognize text from natural images, in a semi-supervised way. SEE is a network that integrates and jointly learns a spatial transformer network, which can learn to detect text regions in an image, and a text recognition network that takes the identified text regions and recognizes their textual content. We introduce the idea behind our novel approach and show its feasibility, by performing a range of experiments on standard benchmark datasets, where we achieve competitive results.
LoANs
(2019)
Recently, deep neural networks have achieved remarkable performance on the task of object detection and recognition. The reason for this success is mainly grounded in the availability of large scale, fully annotated datasets, but the creation of such a dataset is a complicated and costly task. In this paper, we propose a novel method for weakly supervised object detection that simplifies the process of gathering data for training an object detector. We train an ensemble of two models that work together in a student-teacher fashion. Our student (localizer) is a model that learns to localize an object, the teacher (assessor) assesses the quality of the localization and provides feedback to the student. The student uses this feedback to learn how to localize objects and is thus entirely supervised by the teacher, as we are using no labels for training the localizer. In our experiments, we show that our model is very robust to noise and reaches competitive performance compared to a state-of-the-art fully supervised approach. We also show the simplicity of creating a new dataset, based on a few videos (e.g. downloaded from YouTube) and artificially generated data.
In self-incompatible plants the female style rejects self pollen, yet the extent to which the female style in the many self-compatible species can still select between different pollen genotypes and thus bias fertilization success is unclear. A new study identifies the molecular basis for how styles of the self-compatible coyote tobacco bias the fertilization success of pollen genotypes using matching gene expression patterns in a manner analogous to cryptic female choice in animals.
A balance to death
(2018)
Leaf senescence plays a crucial role in nutrient recovery in late-stage plant development and requires vast transcriptional reprogramming by transcription factors such as ORESARA1 (ORE1). A proteolytic mechanism is now found to control ORE1 degradation, and thus senescence, during nitrogen starvation.
The Aral Sea desiccation and related changes in hydroclimatic conditions on a regional level is a hot topic for past decades. The key problem of scientific research projects devoted to an investigation of modern Aral Sea basin hydrological regime is its discontinuous nature - the only limited amount of papers takes into account the complex runoff formation system entirely. Addressing this challenge we have developed a continuous prediction system for assessing freshwater inflow into the Small Aral Sea based on coupling stack of hydrological and data-driven models. Results show a good prediction skill and approve the possibility to develop a valuable water assessment tool which utilizes the power of classical physically based and modern machine learning models both for territories with complex water management system and strong water-related data scarcity. The source code and data of the proposed system is available on a Github page (https://github.com/SMASHIproject/IWRM2018).
General intelligence has a substantial genetic background in children, adolescents, and adults, but environmental factors also strongly correlate with cognitive performance as evidenced by a strong (up to one SD) increase in average intelligence test results in the second half of the previous century. This change occurred in a period apparently too short to accommodate radical genetic changes. It is highly suggestive that environmental factors interact with genotype by possible modification of epigenetic factors that regulate gene expression and thus contribute to individual malleability. This modification might as well be reflected in recent observations of an association between dopamine-dependent encoding of reward prediction errors and cognitive capacity, which was modulated by adverse life events.
The globally distributed sperm whale (Physeter macrocephalus) has a partly matrilineal social structure with predominant male dispersal. At the beginning of 2016, a total of 30 male sperm whales stranded in five different countries bordering the southern North Sea. It has been postulated that these individuals were on a migration route from the north to warmer temperate and tropical waters where females live in social groups. By including samples from four countries (n = 27), this event provided a unique chance to genetically investigate the maternal relatedness and the putative origin of these temporally and spatially co-occuring male sperm whales. To utilize existing genetic resources, we sequenced 422 bp of the mitochondrial control region, a molecular marker for which sperm whale data are readily available from the entire distribution range. Based on four single nucleotide polymorphisms (SNPs) within the mitochondrial control region, five matrilines could be distinguished within the stranded specimens, four of which matched published haplotypes previously described in the Atlantic. Among these male sperm whales, multiple matrilineal lineages co-occur. We analyzed the population differentiation and could show that the genetic diversity of these male sperm whales is comparable to the genetic diversity in sperm whales from the entire Atlantic Ocean. We confirm that within this stranding event, males do not comprise maternally related individuals and apparently include assemblages of individuals from different geographic regions. (c) 2017 Deutsche Gesellschaft fur Saugetierkunde. Published by Elsevier GmbH. All rights reserved.
An energy consumption model for multiModal wireless sensor networks based on wake-up radio receivers
(2018)
Energy consumption is a major concern in Wireless Sensor Networks. A significant waste of energy occurs due to the idle listening and overhearing problems, which are typically avoided by turning off the radio, while no transmission is ongoing. The classical approach for allowing the reception of messages in such situations is to use a low-duty-cycle protocol, and to turn on the radio periodically, which reduces the idle listening problem, but requires timers and usually unnecessary wakeups. A better solution is to turn on the radio only on demand by using a Wake-up Radio Receiver (WuRx). In this paper, an energy model is presented to estimate the energy saving in various multi-hop network topologies under several use cases, when a WuRx is used instead of a classical low-duty-cycling protocol. The presented model also allows for estimating the benefit of various WuRx properties like using addressing or not.
HESS J1826-130
(2017)
HESS J1826-130 is an unidentified hard spectrum source discovered by H.E.S.S. along the Galactic plane, the spectral index being Gamma = 1.6 with an exponential cut-off at about 12 TeV. While the source does not have a clear counterpart at longer wavelengths, the very hard spectrum emission at TeV energies implies that electrons or protons accelerated up to several hundreds of TeV are responsible for the emission. In the hadronic case, the VHE emission can be produced by runaway cosmic-rays colliding with the dense molecular clouds spatially coincident with the H.E.S.S. source.
Moving Forces
(2017)
Throughout a large part of the twentieth century, the body was interpreted as a field of signs, the meaning of which pointed to an unconscious dimension. At the height of the popularity of structuralism, Jacques Lacan deemed the unconscious to be “structured like a language.” Starting in the early 1990s, however, a deep shift occurred in the way the body was interpreted. A new movement cast tremendous doubt on the hegemony of language and instead advocated a performative, pictorial, and affective approach — the so-called material turn — which encompassed all of these. In the words of Karen Barad, this turn inquired as to why meaning, history, and truth are assigned to language only, whereas the movements of materiality are given less prominence: “How did language come to be more trustworthy than matter? Why are language and culture granted their own agency and historicity while matter is figured as passive and immutable?” With this shift toward the material, bodies began to be seen in a different light and their materiality understood as something that follows its own laws and movements, which cannot be understood exclusively in terms of social-cultural codes. Instead, these laws and movements call into question the very dichotomies of nature/culture and body/spirit.
This paper investigates the applicability of CMOS decoupling cells for mitigating the Single Event Transient (SET) effects in standard combinational gates. The concept is based on the insertion of two decoupling cells between the gate's output and the power/ground terminals. To verify the proposed hardening approach, extensive SPICE simulations have been performed with standard combinational cells designed in IHP's 130 nm bulk CMOS technology. Obtained simulation results have shown that the insertion of decoupling cells results in the increase of the gate's critical charge, thus reducing the gate's soft error rate (SER). Moreover, the decoupling cells facilitate the suppression of SET pulses propagating through the gate. It has been shown that the decoupling cells may be a competitive alternative to gate upsizing and gate duplication for hardening the gates with lower critical charge and multiple (3 or 4) inputs, as well as for filtering the short SET pulses induced by low-LET particles.
Gilbert et al. conclude that evidence from the Open Science Collaboration’s Reproducibility Project: Psychology indicates high reproducibility, given the study methodology. Their very optimistic assessment is limited by statistical misconceptions and by causal inferences from selectively interpreted, correlational data. Using the Reproducibility Project: Psychology data, both optimistic and pessimistic conclusions about reproducibility are possible, and neither are yet warranted.
Without fear or favour
(2024)
Declarative languages for knowledge representation and reasoning provide constructs to define preference relations over the set of possible interpretations, so that preferred models represent optimal solutions of the encoded problem. We introduce the notion of approximation for replacing preference relations with stronger preference relations, that is, relations comparing more pairs of interpretations. Our aim is to accelerate the computation of a non-empty subset of the optimal solutions by means of highly specialized algorithms. We implement our approach in Answer Set Programming (ASP), where problems involving quantitative and qualitative preference relations can be addressed by ASPRIN, implementing a generic optimization algorithm. Unlike this, chains of approximations allow us to reduce several preference relations to the preference relations associated with ASP’s native weak constraints and heuristic directives. In this way, ASPRIN can now take advantage of several highly optimized algorithms implemented by ASP solvers for computing optimal solutions
Selection of initial points, the number of clusters and finding proper clusters centers are still the main challenge in clustering processes. In this paper, we suggest genetic algorithm based method which searches several solution spaces simultaneously. The solution spaces are population groups consisting of elements with similar structure. Elements in a group have the same size, while elements in different groups are of different sizes. The proposed algorithm processes the population in groups of chromosomes with one gene, two genes to k genes. These genes hold corresponding information about the cluster centers. In the proposed method, the crossover and mutation operators can accept parents with different sizes; this can lead to versatility in population and information transfer among sub-populations. We implemented the proposed method and evaluated its performance against some random datasets and the Ruspini dataset as well. The experimental results show that the proposed method could effectively determine the appropriate number of clusters and recognize their centers. Overall this research implies that using heterogeneous population in the genetic algorithm can lead to better results.
Detect me if you can
(2019)
Spam Bots have become a threat to online social networks with their malicious behavior, posting misinformation messages and influencing online platforms to fulfill their motives. As spam bots have become more advanced over time, creating algorithms to identify bots remains an open challenge. Learning low-dimensional embeddings for nodes in graph structured data has proven to be useful in various domains. In this paper, we propose a model based on graph convolutional neural networks (GCNN) for spam bot detection. Our hypothesis is that to better detect spam bots, in addition to defining a features set, the social graph must also be taken into consideration. GCNNs are able to leverage both the features of a node and aggregate the features of a node’s neighborhood. We compare our approach, with two methods that work solely on a features set and on the structure of the graph. To our knowledge, this work is the first attempt of using graph convolutional neural networks in spam bot detection.
The plant pathogen Pseudomonas syringae is a gram-negative bacterium which infects a wide range of plant species including important crops plants. To suppress plant immunity and cause disease P.syringae injects type-III effector proteins (T3Es) into the plant cell cytosol. In this study, we identified a novel target of the well characterized bacterial T3E HopZ1a. HopZ1a is an acetyltransferase that was shown to disrupt vesicle transport during innate immunity by acetylating tubulin. Using a yeast-two-hybrid screen approach, we identified a REMORIN (REM) protein from tobacco as a novel HopZ1a target. HopZ1a interacts with REM at the plasma membrane (PM) as shown by split-YFP experiments. Interestingly, we found that PBS1, a well-known kinase involved in plant immunity also interacts with REM in pull-down assays, and at the PM as shown by BiFC. Furthermore, we confirmed that REM is phosphorylated by PBS1 in vitro. Overexpression of REM provokes the upregulation of defense genes and leads to disease-like phenotypes pointing to a role of REM in plant immune signaling. Further protein-protein interaction studies reveal novel REM binding partners with a possible role in plant immune signaling. Thus, REM might act as an assembly hub for an immune signaling complex targeted by HopZ1a. Taken together, this is the first report describing that a REM protein is targeted by a bacterial effector. How HopZ1a might mechanistically manipulate the plant immune system through interfering with REM function will be discussed.
The German Enlightenment
(2017)
The term Enlightenment (or Aufklärung) remains heavily contested. Even when historians delimit the remit of the concept, assigning it to a particular historical period rather than to an intellectual or moral programme, the public resonance of the Enlightenment remains high and problematic—especially when equated in an essentialist manner with modernity or some core values of ‘the West’. This Forum has been convened to discuss recent research on the Enlightenment in Germany, different views of the term and its ideological use in public discourse outside academia (and sometimes within it).
Over the past few years, studying abroad and other educational international experiences have become increasingly highly regarded. Nevertheless, research shows that only a minority of students actually take part in
academic mobility programs. But what is it that distinguishes those students who take up these international opportunities from those who do not? In this
study we reviewed recent quantitative studies on why (primarily German) students choose to travel abroad or not. This revealed a pattern of predictive factors. These indicate the key role played by students’ personal and social background, as well as previous international travel and the course of studies they are enrolled in. The study then focuses on teaching students. Both facilitating and debilitating factors are discussed and included in a model illustrating the decision-making process these students use. Finally, we discuss the practical implications for ways in which international, studyrelated travel might be increased in the future. We suggest that higher education institutions analyze individual student characteristics, offering differentiated programs to better meet the needs of different groups, thus raising the likelihood of disadvantaged students participating in academic international travel.