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Digital transformation fundamentally changes the way individuals conduct work in organisations. In accordance with this statement, prevalent literature understands digital workplace transformation as a second-order effect of implementing new information technology to increase organisational effectiveness or reach other strategic goals. This paper, in contrast, provides empirical evidence from two remote-first organisations that undergo a proactive rather than reactive digital workplace transformation. The analysis of these cases suggests that new ways of working can be the consequence of an identity change that is a precondition for introducing new information technology rather than its outcome. The resulting process model contributes a competing argument to the existing debate in digital transformation literature. Instead of issuing digital workplace transformation as a deliverable of technological progress and strategic goals, this paper supports a notion of digital workplace transformation that serves a desired identity based on work preferences.
The massive growth of MOOCs in 2011 laid the groundwork for the achievement of SDG 4. With the various benefits of MOOCs, there is also anticipation that online education should focus on more interactivity and global collaboration. In this context, the Global MOOC and Online Education Alliance (GMA) established a diverse group of 17 world-leading universities and three online education platforms from across 14 countries on all six continents in 2020. Through nearly three years of exploration, GMA has gained experience and achieved progress in fostering global cooperation in higher education. First, in joint teaching, GMA has promoted in-depth cooperation between members inside and outside the alliance. Examples include promoting the exchange of high-quality MOOCs, encouraging the creation of Global Hybrid Classroom, and launching Global Hybrid Classroom Certificate Programs. Second, in capacity building and knowledge sharing, GMA has launched Online Education Dialogues and the Global MOOC and Online Education Conference, inviting global experts to share best practices and attracting more than 10 million viewers around the world. Moreover, GMA is collaborating with international organizations to support teachers’ professional growth, create an online learning community, and serve as a resource for further development. Third, in public advocacy, GMA has launched the SDG Hackathon and Global Massive Open Online Challenge (GMOOC) and attracted global learners to acquire knowledge and incubate their innovative ideas within a cross-cultural community to solve real-world problems that all humans face and jointly create a better future. Based on past experiences and challenges, GMA will explore more diverse cooperation models with more partners utilizing advanced technology, provide more support for digital transformation in higher education, and further promote global cooperation towards building a human community with a shared future.
Metabolic engineering of microalgae offers a promising solution for sustainable biofuel production, and rational design of engineering strategies can be improved by employing metabolic models that integrate enzyme turnover numbers. However, the coverage of turnover numbers for Chlamydomonas reinhardtii, a model eukaryotic microalga accessible to metabolic engineering, is 17-fold smaller compared to the heterotrophic cell factory Saccharomyces cerevisiae. Here we generate quantitative protein abundance data of Chlamydomonas covering 2337 to 3708 proteins in various growth conditions to estimate in vivo maximum apparent turnover numbers. Using constrained-based modeling we provide proxies for in vivo turnover numbers of 568 reactions, representing a 10-fold increase over the in vitro data for Chlamydomonas. Integration of the in vivo estimates instead of in vitro values in a metabolic model of Chlamydomonas improved the accuracy of enzyme usage predictions. Our results help in extending the knowledge on uncharacterized enzymes and improve biotechnological applications of Chlamydomonas.
PyFin-sentiment
(2023)
Responding to the poor performance of generic automated sentiment analysis solutions on domain-specific texts, we collect a dataset of 10,000 tweets discussing the topics of finance and investing. We manually assign each tweet its market sentiment, i.e., the investor’s anticipation of a stock’s future return. Using this data, we show that all existing sentiment models trained on adjacent domains struggle with accurate market sentiment analysis due to the task’s specialized vocabulary. Consequently, we design, train, and deploy our own sentiment model. It outperforms all previous models (VADER, NTUSD-Fin, FinBERT, TwitterRoBERTa) when evaluated on Twitter posts. On posts from a different platform, our model performs on par with BERT-based large language models. We achieve this result at a fraction of the training and inference costs due to the model’s simple design. We publish the artifact as a python library to facilitate its use by future researchers and practitioners.
Knowledge on the response of sediment export to recent climate change in glacierized areas in the European Alps is limited, primarily because long-term records of suspended sediment concentrations (SSCs) are scarce. Here we tested the estimation of sediment export of the past five decades using quantile regression forest (QRF), a nonparametric, multivariate regression based on random forest. The regression builds on short-term records of SSCs and long records of the most important hydroclimatic drivers (discharge, precipitation and air temperature - QPT). We trained independent models for two nested and partially glacier-covered catchments, Vent (98 km(2)) and Vernagt (11.4 km(2)), in the upper otztal in Tyrol, Austria (1891 to 3772 m a.s.l.), where available QPT records start in 1967 and 1975. To assess temporal extrapolation ability, we used two 2-year SSC datasets at gauge Vernagt, which are almost 20 years apart, for a validation. For Vent, we performed a five-fold cross-validation on the 15 years of SSC measurements. Further, we quantified the number of days where predictors exceeded the range represented in the training dataset, as the inability to extrapolate beyond this range is a known limitation of QRF. Finally, we compared QRF performance to sediment rating curves (SRCs). We analyzed the modeled sediment export time series, the predictors and glacier mass balance data for trends (Mann-Kendall test and Sen's slope estimator) and step-like changes (using the widely applied Pettitt test and a complementary Bayesian approach).Our validation at gauge Vernagt demonstrated that QRF performs well in estimating past daily sediment export (Nash-Sutcliffe efficiency (NSE) of 0.73) and satisfactorily for SSCs (NSE of 0.51), despite the small training dataset. The temporal extrapolation ability of QRF was superior to SRCs, especially in periods with high-SSC events, which demonstrated the ability of QRF to model threshold effects. Days with high SSCs tended to be underestimated, but the effect on annual yields was small. Days with predictor exceedances were rare, indicating a good representativity of the training dataset. Finally, the QRF reconstruction models outperformed SRCs by about 20 percent points of the explained variance.Significant positive trends in the reconstructed annual suspended sediment yields were found at both gauges, with distinct step-like increases around 1981. This was linked to increased glacier melt, which became apparent through step-like increases in discharge at both gauges as well as change points in mass balances of the two largest glaciers in the Vent catchment. We identified exceptionally high July temperatures in 1982 and 1983 as a likely cause. In contrast, we did not find coinciding change points in precipitation. Opposing trends at the two gauges after 1981 suggest different timings of "peak sediment". We conclude that, given large-enough training datasets, the presented QRF approach is a promising tool with the ability to deepen our understanding of the response of high-alpine areas to decadal climate change.
Progressive habitat fragmentation threatens plant species with narrow habitat requirements. While local environmental conditions define population growth rates and recruitment success at the patch level, dispersal is critical for population viability at the landscape scale. Identifying the dynamics of plant meta-populations is often confounded by the uncertainty about soil-stored population compartments. We combined a landscape-scale assessment of an amphibious plant's population structure with measurements of dispersal complexity in time to track dispersal and putative shifts in functional connectivity. Using 13 microsatellite markers, we analyzed the genetic structure of extant Oenanthe aquatica populations and their soil seed banks in a kettle hole system to uncover hidden connectivity among populations in time and space. Considerable spatial genetic structure and isolation-by-distance suggest limited gene flow between sites. Spatial isolation and patch size showed minor effects on genetic diversity. Genetic similarity found among extant populations and their seed banks suggests increased local recruitment, despite some evidence of migration and recent colonization. Results indicate stepping-stone dispersal across adjacent populations. Among permanent and ephemeral demes the resulting meta-population demography could be determined by source-sink dynamics. Overall, these spatiotemporal connectivity patterns support mainland-island dynamics in our system, highlighting the importance of persistent seed banks as enduring sources of genetic diversity.
Background: Following the rapid increase of asylum seekers arriving in the European Union in 2015/16, policymakers have invested heavily in improving their foresight and forecasting capabilities. A common method to elicit expert predictions are Delphi surveys. This approach has attracted concern in the literature, given the high uncertainty in experts’ predictions. However, there exists limited guidance on specific design choices for future-related Delphi surveys.
Objective: We test whether or not small adjustments to the Delphi survey can increase certainty (i.e., reduce variation) in expert predictions on immigration to the EU in 2030.
Methods: Based on a two-round Delphi survey with 178 migration experts, we compare variation and subjective confidence in expert predictions and assess whether additional context information (type of migration flow, sociopolitical context) promotes convergence among experts (i.e., less variation) and confidence in their own estimates.
Results: We find that additional context information does not reduce variation and does not increase confidence in expert predictions on migration.
Conclusions: The results reaffirm recent concerns regarding the limited scope for reducing uncertainty by manipulating the survey setup. Persistent uncertainty may be a result of the complexity of migration processes and limited agreement among migration experts regarding key drivers.
Contribution: We caution policymakers and academics on the use of Delphi surveys for eliciting expert predictions on immigration, even when conducted based on a large pool of experts and using specific scenarios. The potential of alternative approaches such as prediction markets should be further explored.
Perception of peripersonal space (PPS) and interpersonal distance (IPD) has been shown to be modified by external factors such as perceived danger, the use of tools, and social factors. Especially in times of social distancing in the context of the COVID-19 pandemic, it is vital to study factors that modify PPS and IPD. The present work addresses the question of whether wearing a face mask as a protection tool and social interaction impact the perception of IPD. We tested estimated IPD in pictures at three distances: 50 cm, 90 cm, and 150 cm in both social interaction (shaking hands) and without interaction and when the two people in the pictures wore a face mask or not. Data from 60 subjects were analyzed in a linear mixed model (on both difference in distance estimation to the depicted distance and in absolute distance estimation) and in a 3 (distance: 50, 90, 150) x 2 (interaction: no interaction, shake hands), x 2 face mask (no mask, mask) rmANOVA on distance estimation difference. All analyses showed that at a distance of 50 and 90 cm, participants generally underestimated the IPD while at an IPD of 150 cm, participants overestimated the distance. This could be grounded in perceived danger and avoidance behavior at closer distances, while the wider distance between persons was not perceived as dangerous. Our findings at an IPD of 90 cm show that social interaction has the largest effect at the border of our PPS, while the face mask did not affect social interaction at either distance. In addition, the ANOVA results indicate that when no social interaction was displayed, participants felt less unsafe when depicted persons wore a face mask at distances of 90 and 150 cm. This shows that participants are on the one hand aware of the given safety measures and internalized them; on the other hand, that refraining from physical social interaction helps to get close to other persons.
Many widely used observational data sets are comprised of several overlapping instrument records. While data inter-calibration techniques often yield continuous and reliable data for trend analysis, less attention is generally paid to maintaining higher-order statistics such as variance and autocorrelation. A growing body of work uses these metrics to quantify the stability or resilience of a system under study and potentially to anticipate an approaching critical transition in the system. Exploring the degree to which changes in resilience indicators such as the variance or autocorrelation can be attributed to non-stationary characteristics of the measurement process – rather than actual changes in the dynamical properties of the system – is important in this context. In this work we use both synthetic and empirical data to explore how changes in the noise structure of a data set are propagated into the commonly used resilience metrics lag-one autocorrelation and variance. We focus on examples from remotely sensed vegetation indicators such as vegetation optical depth and the normalized difference vegetation index from different satellite sources. We find that time series resulting from mixing signals from sensors with varied uncertainties and covering overlapping time spans can lead to biases in inferred resilience changes. These biases are typically more pronounced when resilience metrics are aggregated (for example, by land-cover type or region), whereas estimates for individual time series remain reliable at reasonable sensor signal-to-noise ratios. Our work provides guidelines for the treatment and aggregation of multi-instrument data in studies of critical transitions and resilience.
Reliability of the active knee joint position sense test and influence of limb dominance and sex
(2023)
The output of a sensorimotor performance can be measured with the joint position sense (JPS) test. However, investigations of leg dominance, sex and quality measures on this test are limited. Therefore, these potential influencing factors as well as reliability and consistency measures were evaluated for angular reproduction performance and neuromuscular activity during the active knee JPS test in healthy participants. Twenty healthy participants (10 males; 10 females; age 29 +/- 8 years; height 165 +/- 39 cm; body mass 69 +/- 13 kg) performed a seated knee JPS test with a target angle of 50 degrees. Measurements were conducted in two sessions separated by two weeks and consisted of two blocks of continuous angular reproduction (three minutes each block). The difference between reproduced and target angle was identified as angular error measured by an electrogoniometer. During reproduction, the neuromuscular activity of the quadriceps muscle was assessed by surface electromyography. Neuromuscular activity was normalized to submaximal voluntary contraction (subMVC) and displayed per muscle and movement phase. Differences between leg dominance and sex were calculated using Friedman-test (alpha = 0.05). Reliability measures including intraclass correlation coefficient (ICC), Bland-Altman analysis (bias +/- limits of agreement (LoA)) and minimal detectable change (MDC) were analysed. No significant differences between leg dominance and sex were found in angular error and neuromuscular activity. Angular error demonstrated inter-session ICC scores of 0.424 with a bias of 2.4 degrees (+/- 2.4 degrees LoA) as well as MDC of 6.8 degrees and moderate intra-session ICC (0.723) with a bias of 1.4 degrees (+/- 1.65 degrees LoA) as well as MDC of 4.7 degrees. Neuromuscular activity for all muscles and movement phases illustrated inter-session ICC ranging from 0.432 to 0.809 with biases between - 2.5 and 13.6% subMVC and MDC from 13.4 to 63.9% subMVC. Intra-session ICC ranged from 0.705 to 0.987 with biases of - 7.7 to 2.4% subMVC and MDC of 2.7 to 46.5% subMVC. Leg dominance and sex seem not to influence angular reproduction performance and neuromuscular activity. Poor to excellent relative reliability paired with an acceptable consistency confirm findings of previous studies. Comparisons to pathological populations should be conducted with caution.
The Adaptive Force (AF) reflects the neuromuscular capacity to adapt to external loads during holding muscle actions and is similar to motions in real life and sports. The maximal isometric AF (AFisoₘₐₓ) was considered to be the most relevant parameter and was assumed to have major importance regarding injury mechanisms and the development of musculoskeletal pain. The aim of this study was to investigate the behavior of different torque parameters over the course of 30 repeated maximal AF trials. In addition, maximal holding vs. maximal pushing isometric muscle actions were compared. A side consideration was the behavior of torques in the course of repeated AF actions when comparing strength and endurance athletes. The elbow flexors of n = 12 males (six strength/six endurance athletes, non-professionals) were measured 30 times (120 s rest) using a pneumatic device. Maximal voluntary isometric contraction (MVIC) was measured pre and post. MVIC, AFisoₘₐₓ, and AFₘₐₓ (maximal torque of one AF measurement) were evaluated regarding different considerations and statistical tests. AFₘₐₓ and AFisoₘₐₓ declined in the course of 30 trials [slope regression (mean ± standard deviation): AFₘₐₓ = −0.323 ± 0.263; AFisoₘₐₓ = −0.45 ± 0.45]. The decline from start to end amounted to −12.8% ± 8.3% (p < 0.001) for AFₘₐₓ and −25.41% ± 26.40% (p < 0.001) for AFisoₘₐₓ. AF parameters declined more in strength vs. endurance athletes. Thereby, strength athletes showed a rather stable decline for AFmax and a plateau formation for AFisoₘₐₓ after 15 trials. In contrast, endurance athletes reduced their AFₘₐₓ, especially after the first five trials, and remained on a rather similar level for AFisomax. The maximum of AFisoₘₐₓ of all 30 trials amounted 67.67% ± 13.60% of MVIC (p < 0.001, n = 12), supporting the hypothesis of two types of isometric muscle action (holding vs. pushing). The findings provided the first data on the behavior of torque parameters after repeated isometric–eccentric actions and revealed further insights into neuromuscular control strategies. Additionally, they highlight the importance of investigating AF parameters in athletes based on the different behaviors compared to MVIC. This is assumed to be especially relevant regarding injury mechanisms.
Reply and Counter-Reply
(2023)
Resurrecting the Argo
(2023)
This paper analyses the relationship between the figure of the Argo (ship and character) and the supernatural in the mythic fantasy of Robert Holdstock’s Merlin Codex. It shows how Holdstock’s re-writing of the Argonautica draws on various versions from the Argonautic tradition, including Euripides’ Medea, Apollonius, Valerius Flaccus, Nathaniel Hawthorne, Henry Treece and the 1963 film Jason and the Argonauts. It sets Holdstock’s Argo alongside other representations, as divine herself, possessed by divinity, and a channel of communication with the divine, and in the context of Holdstock’s previous work, particularly Mythago Wood, Lavondyss and Merlin’s Wood. The paper argues that Holdstock uses the Argo as a reflection of myth itself, a version of the forest in Mythago Wood, as well as a metapoetic image for the challenges and complexities of adapting a well-known story, bringing multiple mythological traditions (Arthurian, Finnish and Argonautic) together. It reflects on Holdstock’s relationship to the ancient genres of epic and tragedy, as well as Argo as plot facilitator and mechanism of transformation and transition. Holdstock’s relationship with ancient literature is richer and deeper than previously acknowledged; his self-conscious plays reveal a deep understanding of the polymorphous nature of mythical traditions.
Review symposium
(2023)
Steffen Ganghof’s Beyond Presidentialism and Parliamentarism: Democratic Design and the Separation of Powers (Oxford University Press, 2021) posits that “in a democracy, a constitutional separation of powers between the executive and the assembly may be desirable, but the constitutional concentration of executive power in a single human being is not” (Ganghof, 2021). To consider, examine and theorise about this, Ganghof urges engagement with semi-parliamentarism. As explained by Ganghof, legislative power is shared between two democratically legitimate sections of parliament in a semi-parliamentary system, but only one of those sections selects the government and can remove it in a no-confidence vote. Consequently, power is dispersed and not concentrated in the hands of any one person, which, Ganghof argues, can lead to an enhanced form of parliamentary democracy. In this book review symposium, George Tsebelis, Michael Thies, José Antonio Cheibub, Rosalind Dixon and Daniel Bogéa review Steffen Ganghof’s book and engage with the author about aspects of research design, case selection and theoretical argument. This symposium arose from an engaging and constructive discussion of the book at a seminar hosted by Texas A&M University in 2022. We thank Prof José Cheibub (Texas A&M) for organising that seminar and Dr Anna Fruhstorfer (University of Potsdam) for initiating this book review symposium.
Risk perceptions of individuals living in single-parent households during the COVID-19 crisis
(2023)
The COVID-19 crisis had severe social and economic impact on the life of most citizens around the globe. Individuals living in single-parent households were particularly at risk, revealing detrimental labour market outcomes and assessments of future perspectives marked by worries. As it has not been investigated yet, in this paper we study, how their perception about the future and their outlook on how the pandemic will affect them is related to their objective economic resources. Against this background, we examine the subjective risk perception of worsening living standards of individuals living in single-parent households compared to other household types, their objective economic situation based on the logarithmised equivalised disposable household incomes and analyse the relationship between those indicators. Using the German SOEP, including the SOEP-CoV survey from 2020, our findings based on regression modelling reveal that individuals living in single-parent households have been worse off during the pandemic, facing high economic insecurity. Path and interaction models support our assumption that the association between those indicators may not be that straightforward, as there are underlying mechanisms–such as mediation and moderation–of income affecting its direction and strength. With respect to our central hypotheses, our empirical findings point toward (1) a mediation effect, by demonstrating that the subjective risk perception of single-parent households can be partly explained by economic conditions. (2) The moderating effect suggests that the concrete position at the income distribution of households matters as well. While at the lower end of the income distribution, single-parent households reveal particularly worse risk perceptions during the pandemic, at the high end of the income spectrum, risk perceptions are similar for all household types. Thus, individuals living in single-parent households do not perceive higher risks of worsening living standards due to their household situation per se, but rather because they are worse off in terms of their economic situation compared to individuals living in other household types.
This research paper provides an overview of the current state of MOOCs (massive open online courses) and universities in Austria, focusing on the national MOOC platform iMooX.at. The study begins by presenting the results of an analysis of the performance agreements of 22 Austrian public universities for the period 2022–2024, with a specific focus on the mention of MOOC activities and iMooX. The authors find that 12 of 22 (55 %) Austrian public universities use at least one of these terms, indicating a growing interest in MOOCs and online learning. Additionally, the authors analyze internal documentation data to share insights into how many universities in Austria have produced and/or used a MOOC on the iMooX platform since its launch in 2014. These findings provide a valuable measure of the current usage and monitoring of MOOCs and iMooX among Austrian higher education institutions. Overall, this research contributes to a better understanding of the current state of MOOCs and their integration within Austrian higher education.
State- and private-led search-and-rescue are hypothesized to foster irregular migration (and thereby migrant fatalities) by altering the decision calculus associated with the journey. We here investigate this ‘pull factor’ claim by focusing on the Central Mediterranean route, the most frequented and deadly irregular migration route towards Europe during the past decade. Based on three intervention periods—(1) state-led Mare Nostrum, (2) private-led search-and-rescue, and (3) coordinated pushbacks by the Libyan Coast Guard—which correspond to substantial changes in laws, policies, and practices of search-and-rescue in the Mediterranean, we are able to test the ‘pull factor’ claim by employing an innovative machine learning method in combination with causal inference. We employ a Bayesian structural time-series model to estimate the effects of these three intervention periods on the migration flow as measured by crossing attempts (i.e., time-series aggregate counts of arrivals, pushbacks, and deaths), adjusting for various known drivers of irregular migration. We combine multiple sources of traditional and non-traditional data to build a synthetic, predicted counterfactual flow. Results show that our predictive modeling approach accurately captures the behavior of the target time-series during the various pre-intervention periods of interest. A comparison of the observed and predicted counterfactual time-series in the post-intervention periods suggest that pushback policies did affect the migration flow, but that the search-and-rescue periods did not yield a discernible difference between the observed and the predicted counterfactual number of crossing attempts. Hence we do not find support for search-and-rescue as a driver of irregular migration. In general, this modeling approach lends itself to forecasting migration flows with the goal of answering causal queries in migration research.
The Gutenberg-Richter (GR) and the Omori-Utsu (OU) law describe the earthquakes' energy release and temporal clustering and are thus of great importance for seismic hazard assessment. Motivated by experimental results, which indicate stress-dependent parameters, we consider a combined global data set of 127 main shock-aftershock sequences and perform a systematic study of the relationship between main shock-induced stress changes and associated seismicity patterns. For this purpose, we calculate space-dependent Coulomb Stress (& UDelta;CFS) and alternative receiver-independent stress metrics in the surrounding of the main shocks. Our results indicate a clear positive correlation between the GR b-value and the induced stress, contrasting expectations from laboratory experiments and suggesting a crucial role of structural heterogeneity and strength variations. Furthermore, we demonstrate that the aftershock productivity increases nonlinearly with stress, while the OU parameters c and p systematically decrease for increasing stress changes. Our partly unexpected findings can have an important impact on future estimations of the aftershock hazard.
Self-efficacy reflects the self-belief that one can persistently perform difficult and novel tasks while coping with adversity. As such beliefs reflect how individuals behave, think, and act, they are key for successful entrepreneurial activities. While existing literature mainly analyzes the influence of the task-related construct of entrepreneurial self-efficacy, we take a different perspective and investigate, based on a representative sample of 1,405 German business founders, how the personality characteristic of generalized self-efficacy influences start-up performance as measured by a broad set of business outcomes up to 19 months after business creation. Outcomes include start-up survival and entrepreneurial income, as well as growth-oriented outcomes such as job creation and innovation. We find statistically significant and economically important positive effects of high scores of self-efficacy on start-up survival and entrepreneurial income, which become even stronger when focusing on the growth-oriented outcome of innovation. Furthermore, we observe that generalized self-efficacy is similarly distributed between female and male business founders, with effects being partly stronger for female entrepreneurs. Our findings are important for policy instruments that are meant to support firm growth by facilitating the design of more target-oriented offers for training, coaching, and entrepreneurial incubators.
Background
Self-regulation (SR) as the ability to regulate one's own physical state, emotions, cognitions, and behavior, is considered to play a pivotal role in the concurrent and subsequent mental and physical health of an individual. Although SR skills encompass numerous sub-facets, previous research has often focused on only one or a few of these sub-facets, and only rarely on adolescence. Therefore, little is known about the development of the sub-facets, their interplay, and their specific contributions to future developmental outcomes, particularly in adolescence. To fill these research gaps, this study aims to prospectively examine (1) the development of SR and (2) their influence on adolescent-specific developmental outcomes in a large community sample.
Methods/design
Based on previously collected data from the Potsdam Intrapersonal Developmental Risk (PIER) study with three measurement points, the present prospective, longitudinal study aims to add a fourth measurement point (PIERYOUTH). We aim to retain at least 1074 participants now between 16 and 23 years of the initially 1657 participants (6-11 years of age at the first measurement point in 2012/2013; 52.2% female). The study will continue to follow a multi-method (questionnaires, physiological assessments, performance-based computer tasks), multi-facet (assessing various domains of SR), and multi-rater (self-, parent-, and teacher-report) approach. In addition, a broad range of adolescent-specific developmental outcomes is considered. In doing so, we will cover the development of SR and relevant outcomes over the period of 10 years. In addition, we intend to conduct a fifth measurement point (given prolonged funding) to investigate development up to young adulthood.
Discussion
With its broad and multimethodological approach, PIERYOUTH aims to contribute to a deeper understanding of the development and role of various SR sub-facets from middle childhood to adolescence. The large sample size and low drop-out rates in the first three measurements points form a sound database for our present prospective research.Trial registration German Clinical Trials Register, registration number DRKS00030847.
Purpose
Given inconsistent results in prior studies, this paper applies the dual process theory to investigate what social media messages yield audience engagement during a political event. It tests how affective cues (emotional valence, intensity and collective self-representation) and cognitive cues (insight, causation, certainty and discrepancy) contribute to public engagement.
Design/methodology/approach
The authors created a dataset of more than three million tweets during the 2020 United States (US) presidential elections. Affective and cognitive cues were assessed via sentiment analysis. The hypotheses were tested in negative binomial regressions. The authors also scrutinized a subsample of far-famed Twitter users. The final dataset, scraping code, preprocessing and analysis are available in an open repository.
Findings
The authors found the prominence of both affective and cognitive cues. For the overall sample, negativity bias was registered, and the tweet’s emotionality was negatively related to engagement. In contrast, in the sub-sample of tweets from famous users, emotionally charged content produced higher engagement. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with many followers. Collective self-representation (“we-talk”) is consistently associated with more likes, comments and retweets in the overall sample and subsamples.
Originality/value
The authors expand the dominating one-sided perspective to social media message processing focused on the peripheral route and hence affective cues. Leaning on the dual process theory, the authors shed light on the effectiveness of both affective (peripheral route) and cognitive (central route) cues on information appeal and dissemination on Twitter during a political event. The popularity of the tweet’s author moderates these relationships.
Public opinion polls have become vital and increasingly visible parts of election campaigns. Previous research has frequently demonstrated that polls can influence both citizens' voting intentions and political parties' campaign strategies. However, they are also fraught with uncertainty. Margins of error can reflect (parts of) this uncertainty. This paper investigates how citizens' voting intentions change due to whether polling estimates are presented with or without margins of error.
Using a vignette experiment (N=3224), we examine this question based on a real-world example in which different election polls were shown to nationally representative respondents ahead of the 2021 federal election in Germany. We manipulated the display of the margins of error, the interpretation of polls and the closeness of the electoral race.
The results indicate that margins of error can influence citizens' voting intentions. This effect is dependent on the actual closeness of the race and additional interpretative guidance provided to voters. More concretely, the results consistently show that margins of error increase citizens' inclination to vote for one of the two largest contesting parties if the polling gap between these parties is small, and an interpretation underlines this closeness.
The findings of this study are important for three reasons. First, they help to determine whether margins of error can assist citizens in making more informed (strategic) vote decisions. They shed light on whether depicting opinion-poll uncertainty affects the key features of representative democracy, such as democratic accountability. Second, the results stress the responsibility of the media. The way polls are interpreted and contextualized influences the effect of margins of error on voting behaviour. Third, the findings of this paper underscore the significance of including methodological details when communicating scientific research findings to the broader public.
Spatial and temporal variation in perceived predation risk is an important determinant of movement and foraging activity of animals. Foraging in this landscape of fear, individuals need to decide where and when to move, and what resources to choose. Foraging theory predicts the outcome of these decisions based on energetic trade-offs, but complex interactions between perceived predation risk and preferences of foragers for certain functional traits of their resources are rarely considered. Here, we studied the interactive effects of perceived predation risk on food trait preferences and foraging behavior in bank voles (Myodes glareolus) in experimental landscapes. Individuals (n = 19) were subjected for periods of 24 h to two extreme, risk-uniform landscapes (either risky or safe), containing 25 discrete food patches, filled with seeds of four plant species in even amounts. Seeds varied in functional traits: size, nutrients, and shape. We evaluated whether and how risk modifies forager preference for functional traits. We also investigated whether perceived risk and distance from shelter affected giving-up density (GUD), time in patches, and number of patch visits. In safe landscapes, individuals increased time spent in patches, lowered GUD and visited distant patches more often compared to risky landscapes. Individuals preferred bigger seeds independent of risk, but in the safe treatment they preferred fat-rich over carb-rich seeds. Thus, higher densities of resource levels remained in risky landscapes, while in safe landscapes resource density was lower and less diverse due to selective foraging. Our results suggest that the interaction of perceived risk and dietary preference adds an additional layer to the cascading effects of a landscape of fear which affects biodiversity at resource level.
Strategic social media use positively influences organizational goals such as the long-term accrual of social capital, and thus social media information governance has become an increasingly important organizational objective. It is particularly important for humanitarian nongovernmental organizations (HNGOs), whose work relies on accurate and timely information regarding socially altruistic behavior (donations, volunteerism, etc.). Despite the potential of social media for increasing social capital, tensions in governing social media information across an organization's different operational levels (regional, intermediate, and national) pose a difficult challenge. Prominent governance frameworks offer little guidance, as their focus on control and incremental policymaking is largely incompatible with the processes, roles, standards, and metrics needed for managing self-governing social media. This study offers a notion of dynamic and co-evolutionary process management of multi-level organizations as a means of conceptualizing social media information governance for the accrual of organizational social capital. Based on interviews with members of HNGOs, this study reveals tensions that emerge within eight focus areas of accruing social capital in multi-level organizations, explains how dynamic process management can ease those tensions, and proposes corresponding strategy recommendations.
SOEP-LEE2
(2023)
This article presents the new linked employee-employer study of the Socio-Economic Panel (SOEP-LEE2), which offers new research opportunities for various academic fields. In particular, the study contains two waves of an employer survey for persons in dependent work that is also linkable to the SOEP, a large representative German annual household panel (SOEP-LEE2-Core). Moreover, SOEP-LEE2 includes two waves of self-employed surveys based on self-employed in the SOEP-Core (SOEP-LEE2-Self-employed) and three additional representative employer surveys, independent of the SOEP in terms of sampling employers (SOEP-LEE2-Compare). Survey topics include digitalisation and cybersecurity, human capital formation, COVID-19, and human resource management. Here, we describe the content, survey design, and comparability of the different datasets in the SOEP-LEE2 to potential users in different disciplines of research.
This paper deals with the long-term behavior of positive operator semigroups on spaces of bounded functions and of signed measures, which have applications to parabolic equations with unbounded coefficients and to stochas-tic analysis. The main results are a Tauberian type theorem characterizing the convergence to equilibrium of strongly Feller semigroups and a generalization of a classical convergence theorem of Doob. None of these results requires any kind of time regularity of the semigroup.
Under current land-use regulation, carbon dioxide emissions from biofuel production exceed those from fossil diesel combustion. Therefore, international agreements need to ensure the effective and globally comprehensive protection of natural land before modern bioenergy can effectively contribute to achieving carbon neutrality.
Many geophysical inverse problems are known to be ill-posed and, thus, requiring some kind of regularization in order to provide a unique and stable solution. A possible approach to overcome the inversion ill-posedness consists in constraining the position of the model interfaces. For a grid-based parameterization, such a structurally constrained inversion can be implemented by adopting the usual smooth regularization scheme in which the local weight of the regularization is reduced where an interface is expected. By doing so, sharp contrasts are promoted at interface locations while standard smoothness constraints keep affecting the other regions of the model. In this work, we present a structurally constrained approach and test it on the inversion of frequency-domain electromagnetic induction (FD-EMI) data using a regularization approach based on the Minimum Gradient Support stabilizer, which is capable to promote sharp transitions everywhere in the model, i.e., also in areas where no structural a prioriinformation is available. Using 1D and 2D synthetic data examples, we compare the proposed approach to a structurally constrained smooth inversion as well as to more standard (i.e., not structurally constrained) smooth and sharp inversions. Our results demonstrate that the proposed approach helps in finding a better and more reliable reconstruction of the subsurface electrical conductivity distribution, including its structural characteristics. Furthermore, we demonstrate that it allows to promote sharp parameter variations in areas where no structural information are available. Lastly, we apply our structurally constrained scheme to FD-EMI field data collected at a field site in Eastern Germany to image the thickness of peat deposits along two selected profiles. In this field example, we use collocated constant offset ground-penetrating radar (GPR) data to derive structural a priori information to constrain the inversion of the FD-EMI data. The results of this case study demonstrate the effectiveness and flexibility of the proposed approach.
“How can a course structure be redesigned based on empirical data to enhance the learning effectiveness through a student-centered approach using objective criteria?”, was the research question we asked. “Digital Twins for Virtual Commissioning of Production Machines” is a course using several innovative concepts including an in-depth practical part with online experiments, called virtual labs. The teaching-learning concept is continuously evaluated. Card Sorting is a popular method for designing information architectures (IA), “a practice of effectively organizing, structuring, and labeling the content of a website or application into a structuref that enables efficient navigation” [11]. In the presented higher education context, a so-called hybrid card sort was used, in which each participants had to sort 70 cards into seven predefined categories or create new categories themselves. Twelve out of 28 students voluntarily participated in the process and short interviews were conducted after the activity. The analysis of the category mapping creates a quantitative measure of the (dis-)similarity of the keywords in specific categories using hierarchical clustering (HCA). The learning designer could then interpret the results to make decisions about the number, labeling and order of sections in the course.
Pavlovian cues can influence ongoing instrumental behaviour via Pavlovian-to-instrumental transfer (PIT) processes. While appetitive Pavlovian cues tend to promote instrumental approach, they are detrimental when avoidance behaviour is required, and vice versa for aversive cues. We recently reported that susceptibility to interference between Pavlovian and instrumental control assessed via a PIT task was associated with risky alcohol use at age 18. We now investigated whether such susceptibility also predicts drinking trajectories until age 24, based on AUDIT (Alcohol Use Disorders Identification Test) consumption and binge drinking (gramme alcohol/drinking occasion) scores. The interference PIT effect, assessed at ages 18 and 21 during fMRI, was characterized by increased error rates (ER) and enhanced neural responses in the ventral striatum (VS), the lateral and dorsomedial prefrontal cortices (dmPFC) during conflict, that is, when an instrumental approach was required in the presence of an aversive Pavlovian cue or vice versa. We found that a stronger VS response during conflict at age 18 was associated with a higher starting point of both drinking trajectories but predicted a decrease in binge drinking. At age 21, high ER and enhanced neural responses in the dmPFC were associated with increasing AUDIT-C scores over the next 3 years until age 24. Overall, susceptibility to interference between Pavlovian and instrumental control might be viewed as a predisposing mechanism towards hazardous alcohol use during young adulthood, and the identified high-risk group may profit from targeted interventions.
The 2022 Kunming-Montreal Global Biodiversity Framework (GBF) and Paris Agreement (PA) are highly complementary agreements where each depends on the other’s success to be effective. The GBF offers a very specific framework of interim goals and targets that break down the objective of the Convention on Biodiversity (CBD) into a decade-spanning work plan. Comprised of 10 sections – including a 2050 vision and a 2030 mission, four overarching goals and 23 specific targets – the GBF is expected to guide biodiversity policy around the world in the coming years to decades. A similar set of global interim climate policy targets could translate the global temperature goal into concrete policy milestones that would provide policy makers and civil society with reference points for policy making and efforts to hold governments accountable. Beyond inspiring climate policy experts to convert temperature goals into policy milestones, GBF has the potential to strengthen the implementation of the PA at the nexus of biodiversity and climate (adaptation and mitigation) action. For example, the GBF can help to ensure that nature-based climate solutions are implemented with full consideration of biodiversity concerns, of the rights and interests of Indigenous Peoples and local communities, and with fair and transparent benefit sharing arrangements. In sum, the GBF should be mandatory reading for all climate policy makers.
FicucariconeD (1) and its 4 '-demethyl congener 2 are isoflavones isolated from fruits of Ficus carica that share a 5,7-dimethoxy-6-prenyl-substituted A-ring. Both naturalproducts were, for the first time, obtained by chemical synthesisin six steps, starting from 2,4,6-trihydroxyacetophenone. Key stepsare a microwave-promoted tandem sequence of Claisen- and Cope-rearrangementsto install the 6-prenyl substituent and a Suzuki-Miyaura crosscoupling for installing the B-ring. By using various boronic acids,non-natural analogues become conveniently available. All compoundswere tested for cytotoxicity against drug-sensitive and drug-resistanthuman leukemia cell lines, but were found to be inactive. The compoundswere also tested for antimicrobial activities against a panel of eightGram-negative and two Gram-positive bacterial strains. Addition ofthe efflux pump inhibitor phenylalanine-arginine-beta-naphthylamide(PA beta N) significantly improved the antibiotic activity in mostcases, with MIC values as low as 2.5 mu M and activity improvementfactors as high as 128-fold.
Taxed fairly?
(2023)
Empirically, the poor are more likely to support increases in the level of tax progressivity than the rich. Such income-stratified tax preferences can result from differences in preferences of what should be taxed as argued by previous literature. However, it may also result from income-stratified perceptions of what is taxed. This paper argues that the rich perceive higher levels of tax progressivity than the poor and that tax perceptions affect individuals’ support for progressive taxation. Using data from an Austrian survey experiment, we test this argument in three steps: First, in line with past research, we show that individuals’ income positions are connected to individuals’ tax preferences as a self-interest rationale would predict. However, second, we show that this variation is mainly driven by income-stratified tax perceptions. Third, randomly informing a subset of the sample about actual tax rates, we find that changing tax perceptions causally affects support for redistributive taxation among those who initially overestimated the level of tax progressivity. Our results indicate that tax perceptions are relevant for forming tax preferences and suggest that individuals are more polarized in their perceptions of who pays how much taxes than in their support for who should pay how much tax.
Thai MOOC academy
(2023)
Thai MOOC Academy is a national digital learning platform that has been serving as a mechanism for promoting lifelong learning in Thailand since 2017. It has recently undergone significant improvements and upgrades, including the implementation of a credit bank system and a learner’s eportfolio system interconnected with the platform. Thai MOOC Academy is introducing a national credit bank system for accreditation and management, which allows for the transfer of expected learning outcomes and educational qualifications between formal education, non-formal education, and informal education. The credit bank system has five distinct features, including issuing forgery-prevented certificates, recording learning results, transferring external credits within the same wallet, accumulating learning results, and creating a QR code for verification purposes. The paper discusses the features and future potential of Thai MOOC Academy, as it is extended towards a sandbox for the national credit bank system in Thailand.
The abrahamic religions
(2023)
Long COVID patients show symptoms, such as fatigue, muscle weakness and pain. Adequate diagnostics are still lacking. Investigating muscle function might be a beneficial approach. The holding capacity (maximal isometric Adaptive Force; AFisomax) was previously suggested to be especially sensitive for impairments. This longitudinal, non-clinical study aimed to investigate the AF in long COVID patients and their recovery process. AF parameters of elbow and hip flexors were assessed in 17 patients at three time points (pre: long COVID state, post: immediately after first treatment, end: recovery) by an objectified manual muscle test. The tester applied an increasing force on the limb of the patient, who had to resist isometrically for as long as possible. The intensity of 13 common symptoms were queried. At pre, patients started to lengthen their muscles at ~50% of the maximal AF (AFmax), which was then reached during eccentric motion, indicating unstable adaptation. At post and end, AFisomax increased significantly to ~99% and 100% of AFmax, respectively, reflecting stable adaptation. AFmax was statistically similar for all three time points. Symptom intensity decreased significantly from pre to end. The findings revealed a substantially impaired maximal holding capacity in long COVID patients, which returned to normal function with substantial health improvement. AFisomax might be a suitable sensitive functional parameter to assess long COVID patients and to support therapy process
Background Anxiety and depressive disorders share common features of mood dysfunctions. This has stimulated interest in transdiagnostic dimensional research as proposed by the Research Domain Criteria (RDoC) approach by the National Institute of Mental Health (NIMH) aiming to improve the understanding of underlying disease mechanisms. The purpose of this study was to investigate the processing of RDoC domains in relation to disease severity in order to identify latent disorder-specific as well as transdiagnostic indicators of disease severity in patients with anxiety and depressive disorders.
Methods Within the German research network for mental disorders, 895 participants (n = 476 female, n = 602 anxiety disorder, n = 257 depressive disorder) were recruited for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) and included in this cross-sectional study. We performed incremental regression models to investigate the association of four RDoC domains on disease severity in patients with affective disorders: Positive (PVS) and Negative Valance System (NVS), Cognitive Systems (CS) and Social Processes (SP).
Results The results confirmed a transdiagnostic relationship for all four domains, as we found significant main effects on disease severity within domain-specific models (PVS: & beta; = -0.35; NVS: & beta; = 0.39; CS: & beta; = -0.12; SP: & beta; = -0.32). We also found three significant interaction effects with main diagnosis showing a disease-specific association.
Limitations The cross-sectional study design prevents causal conclusions. Further limitations include possible outliers and heteroskedasticity in all regression models which we appropriately controlled for.
Conclusion Our key results show that symptom burden in anxiety and depressive disorders is associated with latent RDoC indicators in transdiagnostic and disease-specific ways.
This paper presents a new design for MOOCs for professional development of skills needed to meet the UN Sustainable Development Goals – the CoMOOC or Co-designed Massive Open Online Collaboration. The CoMOOC model is based on co-design with multiple stakeholders including end-users within the professional communities the CoMOOC aims to reach. This paper shows how the CoMOOC model could help the tertiary sector deliver on the UN Sustainable Development Goals (UNSDGs) – including but not limited to SDG 4 Education – by providing a more effective vehicle for professional development at a scale that the UNSDGs require. Interviews with professionals using MOOCs, and design-based research with professionals have informed the development of the Co-MOOC model. This research shows that open, online, collaborative learning experiences are highly effective for building professional community knowledge. Moreover, this research shows that the collaborative learning design at the heart of the CoMOOC model is feasible cross-platform Research with teachers working in crisis contexts in Lebanon, many of whom were refugees, will be presented to show how this form of large scale, co-designed, online learning can support professionals, even in the most challenging contexts, such as mass displacement, where expertise is urgently required.
Intrinsic motivation is widely considered essential to creativity because it facilitates more divergent thinking during problem solving. However, we argue that intrinsic motivation has been theorized too heavily as a unitary construct, overlooking various internal factors of a task that can shape the baseline level of intrinsic motivation people have for working on the task. Drawing on theories of cognitive styles, we develop a new scale that measures individual preferences for three different creative thinking styles that we call divergent thinking, bricoleurgent thinking, and emergent thinking. Through a multi-study approach consisting of exploratory factor analysis, confirmatory factor analysis, and convergent validity, we provide psychometric evidence showing that people can have distinct preferences for each cognitive process when generating ideas. Furthermore, when validating this scale through an experiment, we find that each style becomes more dominant in predicting overall enjoyment, engagement, and creativity based on different underlying structures of a task. Therefore, this paper makes both theoretical and empirical contributions to literature by unpacking intrinsic motivation, showing how the alignment between different creative thinking styles and task can be essential to predicting intrinsic motivation, thus reversing the direction of causality between the motivational and cognitive components of creativity typically assumed in literature.
The synthesis and the crystal structure of the double cluster compound [Nb6Cl14(MeCN)(4)][Nb6Cl14(pyz)(4)]middot6CH(3)CN are described. The synthesis is based on a partial ligand exchange reaction, which proceeds upon dissolving [Nb6Cl14(pyz)(4)]middot2CH(2)Cl(2) in acetonitrile. The compound is built up of two discrete neutral cluster units, which consist of octahedra of Nb-6 atoms coordinated by 12 edge-bridging chlorido and two terminal chlorido ligands, and four acetonitrile ligands on one and four pyrazine ligands on the other cluster unit. Co-crystallized acetonitrile molecules are also present. The single-crystal structure determination has revealed a cluster arrangement in which the [Nb6Cl14(pyz)(4)] units are connected by (halogen) lone-pair-(pyrazine) pi interactions. These lead to chains of [Nb6Cl14(pyz)(4)] clusters. These chains are further connected to cluster layers by (nitrile-halogen) dipole-dipole interactions, in which the [Nb6Cl14(MeCN)(4)] and co-crystallized MeCN molecules are also involved. These cluster layers are arranged parallel to the crystallographic {011} plane.
Consume-less appeals in social marketing can help reduce the lavish consumption in wealthy countries, which poses a major threat to the climate. This study experimentally examines the effectiveness of three different types of consume-less appeals (informative, social normative, and emotional appeals) on participants’ actual spending levels during a real shopping trip compared to a control group (no appeal). In addition, the study tests whether these appeals evoke negative rebounds (in terms of post-purchase climate donation) or positive rebounds (in terms of accepting post-purchase material giveaways). A field experiment in a grocery store in Germany with 170 participants shows that social normative and the emotional appeals reduce actual shopping spending. Informative and social normative appeals increase donations, and emotional appeals reduce the items of taken giveaways. The findings further support certain indirect impacts of the consume-less appeals on rebounds in terms of spending levels.
Online businesses are increasingly relying on targeted advertisements as a revenue stream, which might lead to privacy concerns and hinder product adoption. Therefore, it is crucial for online companies to understand which types of targeted advertisements consumers will accept. In recent years, users have been increasingly targeted by political advertisements, which has caused adverse reactions in media and society. Nonetheless, few studies experimentally investigate user privacy concerns and their role in acceptance decisions in response to targeted political advertisements. To fill this gap, we explore the magnitude of privacy concerns towards targeted political ads compared to “traditional” targeting in the product context. Surprisingly, we find no notable differences in privacy concerns between these data use purposes. In the next step, user preferences over ad types are elicited with the help of a discrete choice experiment in the mobile app adoption context. Our findings suggest that while targeted political advertising is somewhat less desirable than targeted product advertising, the odds of choosing an app are statistically insignificant between two data use purposes. Together, these results contribute to a better understanding of users’ privacy concerns and preferences in the context of targeted political advertising online.
Megatrends, affecting multiple aspects of future society, economy, and technology, drive today's business world. They are expected to impact all areas in companies and will, therefore, most likely occur in business negotiations. Although several studies address future developments of different business divisions, the megatrends' impact on negotiations has, thus far, not been analyzed. We designed a model including the three megatrends, i.e., globalization and economic shift, digitalization and new technologies, and demographic and social change, which have main effects on specific negotiation aspects. Our study combined an online survey and expert interviews with negotiation practitioners to provide a first broad view of how megatrends affect future business negotiations. The results confirm our model and reveal a close connection of megatrends and single negotiation aspects. Among others, we examine an orientation toward global partners, an increased interconnection through various electronic systems, as well as two opposite relationship directions - long-term and integrative through strategic cooperation vs. short-term and distributive through competition and new technologies.
The COVID-19 pandemic and related closures of day care centres and schools significantly increased the amount of care work done by parents. There has been much speculation over whether the pandemic increased or decreased gender equality in parental care work. Based on representative data for Germany from spring 2020 and winter 2021 we present an empirical analysis that shows that although gender inequality in the division of care work increased to some extent in the beginning of the pandemic, it returned to the pre-pandemic level in the second lockdown almost nine months later. These results suggest that the COVID-19 pandemic neither aggravated nor lessened inequality in the division of unpaid care work among mothers and fathers in any persistent way in Germany.
The heat is on
(2023)
Climate conditions severely impact the activity and, consequently, the fitness of wildlife species across the globe. Wildlife can respond to new climatic conditions, but the pace of human-induced change limits opportunities for adaptation or migration. Thus, how these changes affect behavior, movement patterns, and activity levels remains unclear. In this study, we investigate how extreme weather conditions affect the activity of European hares (Lepus europaeus) during their peak reproduction period. When hares must additionally invest energy in mating, prevailing against competitors, or lactating, we investigated their sensitivities to rising temperatures, wind speed, and humidity. To quantify their activity, we used the overall dynamic body acceleration (ODBA) calculated from tri-axial acceleration measurements of 33 GPS-collared hares. Our analysis revealed that temperature, humidity, and wind speed are important in explaining changes in activity, with a strong response for high temperatures above 25 & DEG;C and the highest change in activity during temperature extremes of over 35 & DEG;C during their inactive period. Further, we found a non-linear relationship between temperature and activity and an interaction of activity changes between day and night. Activity increased at higher temperatures during the inactive period (day) and decreased during the active period (night). This decrease was strongest during hot tropical nights. At a stage of life when mammals such as hares must substantially invest in reproduction, the sensitivity of females to extreme temperatures was particularly pronounced. Similarly, both sexes increased their activity at high humidity levels during the day and low wind speeds, irrespective of the time of day, while the effect of humidity was stronger for males. Our findings highlight the importance of understanding the complex relationships between extreme weather conditions and mammal behavior, critical for conservation and management. With ongoing climate change, extreme weather events such as heat waves and heavy rainfall are predicted to occur more often and last longer. These events will directly impact the fitness of hares and other wildlife species and hence the population dynamics of already declining populations across Europe.
Sulfur is an important element that is incorporated into many biomolecules in humans. The incorporation and transfer of sulfur into biomolecules is, however, facilitated by a series of different sulfurtransferases. Among these sulfurtransferases is the human mercaptopyruvate sulfurtransferase (MPST) also designated as tRNA thiouridine modification protein (TUM1). The role of the human TUM1 protein has been suggested in a wide range of physiological processes in the cell among which are but not limited to involvement in Molybdenum cofactor (Moco) biosynthesis, cytosolic tRNA thiolation and generation of H2S as signaling molecule both in mitochondria and the cytosol. Previous interaction studies showed that TUM1 interacts with the L-cysteine desulfurase NFS1 and the Molybdenum cofactor biosynthesis protein 3 (MOCS3). Here, we show the roles of TUM1 in human cells using CRISPR/Cas9 genetically modified Human Embryonic Kidney cells. Here, we show that TUM1 is involved in the sulfur transfer for Molybdenum cofactor synthesis and tRNA thiomodification by spectrophotometric measurement of the activity of sulfite oxidase and liquid chromatography quantification of the level of sulfur-modified tRNA. Further, we show that TUM1 has a role in hydrogen sulfide production and cellular bioenergetics.
Development of self-concept and task interest has been shown to be affected by social comparison processes in a variety of cross-sectional studies. A potential explanation for these effects is an effect of social comparative performance feedback on an individual’s self-evaluation of performance, which in turn influences development of self-concept and task interest. There are, however, only few studies addressing this topic with experimental designs. This study was aimed at closing this research gap by experimentally manipulating social comparative performance. Feedback given was based on 2 × 2 experimental conditions: social position (high vs. low) and average performance of the reference group (high vs. low). Results show a strong effect of social position on self-evaluation of performance and smaller effects on self-concept and task interest.
Predicting entrepreneurial development based on individual and business-related characteristics is a key objective of entrepreneurship research. In this context, we investigate whether the motives of becoming an entrepreneur influence the subsequent entrepreneurial development. In our analysis, we examine a broad range of business outcomes including survival and income, as well as job creation, and expansion and innovation activities for up to 40 months after business formation. Using the self-determination theory as conceptual background, we aggregate the start-up motives into a continuous motivational index. We show – based on a unique dataset of German start-ups from unemployment and non-unemployment – that the later business performance is better, the higher they score on this index. Effects are particularly strong for growth-oriented outcomes like innovation and expansion activities. In a next step, we examine three underlying motivational categories that we term opportunity, career ambition, and necessity. We show that individuals driven by opportunity motives perform better in terms of innovation and business expansion activities, while career ambition is positively associated with survival, income, and the probability of hiring employees. All effects are robust to the inclusion of a large battery of covariates that are proven to be important determinants of entrepreneurial performance.
The long term relationship between Medicaid expansion and adult life-threatening chronic conditions
(2023)
We test whether the expansions of children's Medicaid eligibility in the 1980s–1990s resulted in long-term health benefits in terms of severe chronic conditions. Still relatively rare in the field, we use prospective individual-level panel data from the Panel Study of Income Dynamics (PSID) along with the higher quality income measures from the Cross-National Equivalent File (adjusting for taxes, transfers and household size). We observe severe chronic conditions (high blood pressure/heart disease, cancer, diabetes, or lung disease) at ages 30–56 (average age 43.1) for 4670 respondents who were also prospectively observed during childhood (i.e., at ages 0–17). Our analysis exploits within-region temporal variation in childhood Medicaid eligibility and adjusts for state- and individual-level controls. We uniquely concentrate attention on adjusting for childhood income. A standard deviation greater childhood Medicaid eligibility significantly reduces the probability of severe chronic conditions in adulthood by 0.05 to 0.12 (16%–37.5% reduction from mean 0.32). Across the range of observed childhood Medicaid eligibility, the probability is approximately cut in half. Greater childhood Medicaid eligibility also substantially reduces childhood income disparities in severe chronic conditions. At higher levels of childhood Medicaid eligibility, we find no significant childhood income disparities in adult severe chronic conditions.
Atwood analyzes the effects of the 1963 U.S. measles vaccination on long-run labor market outcomes, using a generalized difference-in-differences approach. We reproduce the results of this paper and perform a battery of robustness checks. Overall, we confirm that the measles vaccination had positive labor market effects. While the negative effect on the likelihood of living in poverty and the positive effect on the probability of being employed are very robust across the different specifications, the headline estimate—the effect on earnings—is more sensitive to the exclusion of certain regions and survey years.