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How biased are our models?
(2021)
Geophysical process simulations play a crucial role in the understanding of the subsurface. This understanding is required to provide, for instance, clean energy sources such as geothermal energy. However, the calibration and validation of the physical models heavily rely on state measurements such as temperature. In this work, we demonstrate that focusing analyses purely on measurements introduces a high bias. This is illustrated through global sensitivity studies. The extensive exploration of the parameter space becomes feasible through the construction of suitable surrogate models via the reduced basis method, where the bias is found to result from very unequal data distribution. We propose schemes to compensate for parts of this bias. However, the bias cannot be entirely compensated. Therefore, we demonstrate the consequences of this bias with the example of a model calibration.
Urban air pollution is a substantial threat to human health. Traffic emissions remain a large contributor to air pollution in urban areas. The mobility restrictions put in place in response to the COVID-19 pandemic provided a large-scale real-world experiment that allows for the evaluation of changes in traffic emissions and the corresponding changes in air quality. Here we use observational data, as well as modelling, to analyse changes in nitrogen dioxide, ozone, and particulate matter resulting from the COVID-19 restrictions at the height of the lockdown period in Spring of 2020. Accounting for the influence of meteorology on air quality, we found that reduction of ca. 30-50 % in traffic counts, dominated by changes in passenger cars, corresponded to reductions in median observed nitrogen dioxide concentrations of ca. 40 % (traffic and urban background locations) and a ca. 22 % increase in ozone (urban background locations) during weekdays. Lesser reductions in nitrogen dioxide concentrations were observed at urban background stations at weekends, and no change in ozone was observed. The modelled reductions in median nitrogen dioxide at urban background locations were smaller than the observed reductions and the change was not significant. The model results showed no significant change in ozone on weekdays or weekends. The lack of a simulated weekday/weekend effect is consistent with previous work suggesting that NOx emissions from traffic could be significantly underestimated in European cities by models. These results indicate the potential for improvements in air quality due to policies for reducing traffic, along with the scale of reductions that would be needed to result in meaningful changes in air quality if a transition to sustainable mobility is to be seriously considered. They also confirm once more the highly relevant role of traffic for air quality in urban areas.
The understanding of bidimensional materials dynamics and its electrolyte interface equilibrium, such as graphene oxide (GO), is critical for the development of a capacitive biosensing platform. The interfacial capacitance (C-i) of graphene-based materials may be tuned by experimental conditions such as pH optimization and cation size playing key roles at the enhancement of their capacitive properties allowing their application as novel capacitive biosensors. Here we reported a systematic study of C-i of multilayer GO films in different aqueous electrolytes employing electrochemical impedance spectroscopy for the application in a capacitive detection system. We demonstrated that the presence of ionizable oxygen-containing functional groups within multilayer GO film favors the interactions and the accumulation of cations in the structure of the electrodes enhancing the GO C-i in aqueous solutions, where at pH 7.0 (the best condition) the C-i was 340 mu F mg(-1) at -0.01 V vs Ag/AgCl. We also established that the hydrated cation radius affects the mobility and interaction with GO functional groups and it plays a critical role in the Ci, as demonstrated in the presence of different cations Na+=640 mu F mg(-1), Li+=575 mu F mg(-1) and TMA(+)=477 mu F mg(-1). As a proof-of-concept, the capacitive behaviour of GO was explored as biosensing platform for standard streptavidin-biotin systems. For this system, the C-i varied linearly with the log of the concentration of the targeting analyte in the range from 10 pg mL(-1) to 100 ng mL(-1), showing the promising applicability of capacitive GO based sensors for label-free biosensing.
Design thinking is a well-established practical and educational approach to fostering high-level creativity and innovation, which has been refined since the 1950s with the participation of experts like Joy Paul Guilford and Abraham Maslow. Through real-world projects, trainees learn to optimize their creative outcomes by developing and practicing creative cognition and metacognition. This paper provides a holistic perspective on creativity, enabling the formulation of a comprehensive theoretical framework of creative metacognition. It focuses on the design thinking approach to creativity and explores the role of metacognition in four areas of creativity expertise: Products, Processes, People, and Places. The analysis includes task-outcome relationships (product metacognition), the monitoring of strategy effectiveness (process metacognition), an understanding of individual or group strengths and weaknesses (people metacognition), and an examination of the mutual impact between environments and creativity (place metacognition). It also reviews measures taken in design thinking education, including a distribution of cognition and metacognition, to support students in their development of creative mastery. On these grounds, we propose extended methods for measuring creative metacognition with the goal of enhancing comprehensive assessments of the phenomenon. Proposed methodological advancements include accuracy sub-scales, experimental tasks where examinees explore problem and solution spaces, combinations of naturalistic observations with capability testing, as well as physiological assessments as indirect measures of creative metacognition.
Case report
(2023)
The increasing prevalence of Long COVID is an imminent public health disaster, and established approaches have not provided adequate diagnostics or treatments. Recently, anesthetic blockade of the stellate ganglion was reported to improve Long COVID symptoms in a small case series, purportedly by "rebooting" the autonomic nervous system. Here, we present a novel diagnostic approach based on the Adaptive Force (AF), and report sustained positive outcome for one severely affected Long COVID patient using individualized pulsed electromagnetic field (PEMF) at the area C7/T1. AF reflects the capacity of the neuromuscular system to adapt adequately to external forces in an isometric holding manner. In case, maximal isometric AF (AFiso(max)) is exceeded, the muscle merges into eccentric muscle action. Thereby, the force usually increases further until maximal AF (AFmax) is reached. In case adaptation is optimal, AFiso(max) is similar to 99-100% of AFmax. This holding capacity (AFiso(max)) was found to be vulnerable to disruption by unpleasant stimulus and, hence, was regarded as functional parameter. AF was assessed by an objectified manual muscle test using a handheld device. Prior to treatment, AFiso(max) was considerably lower than AFmax for hip flexors (62 N = similar to 28% AFmax) and elbow flexors (71 N = similar to 44% AFmax); i.e., maximal holding capacity was significantly reduced, indicating dysfunctional motor control. We tested PEMF at C7/T1, identified a frequency that improved neuromuscular function, and applied it for similar to 15 min. Immediately post-treatment, AFiso(max) increased to similar to 210 N (similar to 100% AFmax) at hip and 184 N (similar to 100% AFmax) at elbow. Subjective Long COVID symptoms resolved the following day. At 4 weeks post-treatment, maximal holding capacity was still on a similarly high level as for immediately post-treatment (similar to 100% AFmax) and patient was symptom-free. At 6 months the patient's Long COVID symptoms have not returned. This case report suggests (1) AF could be a promising diagnostic for post-infectious illness, (2) AF can be used to test effective treatments for post-infectious illness, and (3) individualized PEMF may resolve post-infectious symptoms.
Alcohol intoxication is known to affect many aspects of human behavior and cognition; one of such affected systems is articulation during speech production. Although much research has revealed that alcohol negatively impacts pronunciation in a first language (L1), there is only initial evidence suggesting a potential beneficial effect of inebriation on articulation in a non-native language (L2). The aim of this study was thus to compare the effect of alcohol consumption on pronunciation in an L1 and an L2. Participants who had ingested different amounts of alcohol provided speech samples in their L1 (Dutch) and L2 (English), and native speakers of each language subsequently rated the pronunciation of these samples on their intelligibility (for the L1) and accent nativelikeness (for the L2). These data were analyzed with generalized additive mixed modeling. Participants' blood alcohol concentration indeed negatively affected pronunciation in L1, but it produced no significant effect on the L2 accent ratings. The expected negative impact of alcohol on L1 articulation can be explained by reduction in fine motor control. We present two hypotheses to account for the absence of any effects of intoxication on L2 pronunciation: (1) there may be a reduction in L1 interference on L2 speech due to decreased motor control or (2) alcohol may produce a differential effect on each of the two linguistic subsystems.
Objective:
Depression and coronary heart disease (CHD) are highly comorbid conditions. Brain-derived neurotrophic factor (BDNF) plays an important role in cardiovascular processes. Depressed patients typically show decreased BDNF concentrations. We analysed the relationship between BDNF and depression in a sample of patients with CHD and additionally distinguished between cognitive-affective and somatic depression symptoms. We also investigated whether BDNF was associated with somatic comorbidity burden, acute coronary syndrome (ACS) or congestive heart failure (CHF).
Methods:
The following variables were assessed for 225 hospitalised patients with CHD: BDNF concentrations, depression [Patient Health Questionnaire-9 (PHQ-9)], somatic comorbidity (Charlson Comorbidity Index), CHF, ACS, platelet count, smoking status and antidepressant treatment.
Results:
Regression models revealed that BDNF was not associated with severity of depression. Although depressed patients (PHQ-9 score >7) had significantly lower BDNF concentrations compared to non-depressed patients (p = 0.04), this was not statistically significant after controlling for confounders (p = 0.15). Cognitive-affective symptoms and somatic comorbidity burden each closely missed a statistically significant association with BDNF concentrations (p = 0.08, p = 0.06, respectively). BDNF was reduced in patients with CHF (p = 0.02). There was no covariate-adjusted, significant association between BDNF and ACS.
Conclusion:
Serum BDNF concentrations are associated with cardiovascular dysfunction. Somatic comorbidities should be considered when investigating the relationship between depression and BDNF.
With the surging reliance on videoconferencing tools, users may find themselves staring at their reflections for hours a day. We refer to this phenomenon as self-referential information (SRI) consumption and examine its consequences and the mechanism behind them. Building on self-awareness research and the strength model of self-control, we argue that SRI consumption heightens the state of self-awareness and thereby depletes participants’ mental resources, eventually undermining virtual meeting (VM) outcomes. Our findings from a European employee sample revealed contrary effects of SRI consumption across speaker vs listener roles. Engagement with self-view is positively associated with self-awareness, which, in turn, is negatively related to satisfaction with VM process, perceived productivity, and enjoyment. Looking at the self while listening to others exhibits adverse direct and indirect (via self-awareness) effects on VM outcomes. However, looking at the self when speaking exhibits positive direct effects on satisfaction with VM process and enjoyment.
We use the prolonged Greek crisis as a case study to understand how a lasting economic shock affects the innovation strategies of firms in economies with moderate innovation activities. Adopting the 3-stage CDM model, we explore the link between R&D, innovation, and productivity for different size groups of Greek manufacturing firms during the prolonged crisis. At the first stage, we find that the continuation of the crisis is harmful for the R&D engagement of smaller firms while it increased the willingness for R&D activities among the larger ones. At the second stage, among smaller firms the knowledge production remains unaffected by R&D investments, while among larger firms the R&D decision is positively correlated with the probability of producing innovation, albeit the relationship is weakened as the crisis continues. At the third stage, innovation output benefits only larger firms in terms of labor productivity, while the innovation-productivity nexus is insignificant for smaller firms during the lasting crisis.
Paid parental leave schemes have been shown to increase women’s employment rates but to decrease their wages in case of extended leave duration. In view of these potential trade-offs, many countries are discussing the optimal design of parental leave policies. We analyze the impact of a major parental leave reform on mothers’ long-term earnings. The 2007 German parental leave reform replaced a means-tested benefit with a more generous earnings-related benefit that is granted for a shorter period of time. Additionally, a ”daddy quota” of two months was introduced. To identify the causal effect of this policy mix on long-run earnings of mothers, we use a difference-in-differences approach that compares labor market outcomes of mothers who gave birth just before and right after the reform and nets out seasonal effects by including the year before. Using administrative social security data, we confirm previous findings and show that the average duration of employment interruptions increased for mothers with high pre-birth earnings. Nevertheless, we find a positive long-run effect on earnings for mothers in this group. This effect cannot be explained by changes in the selection of working mothers, working hours or changes in employer stability. Descriptive evidence suggests that the stronger involvement of fathers, incentivized by the ”daddy months”, could have facilitated mothers’ re-entry into the labor market and thereby increased earnings. For mothers with low pre-birth earnings, however, we do not find beneficial long-run effects of this parental leave reform.
Gender stereotypes influence subjective beliefs about the world, and this is reflected in our use of language. But do gender biases in language transparently reflect subjective beliefs? Or is the process of translating thought to language itself biased? During the 2016 United States (N = 24,863) and 2017 United Kingdom (N = 2,609) electoral campaigns, we compared participants' beliefs about the gender of the next head of government with their use and interpretation of pronouns referring to the next head of government. In the United States, even when the female candidate was expected to win, she pronouns were rarely produced and induced substantial comprehension disruption. In the United Kingdom, where the incumbent female candidate was heavily favored, she pronouns were preferred in production but yielded no comprehension advantage. These and other findings suggest that the language system itself is a source of implicit biases above and beyond previously known biases, such as those measured by the Implicit Association Test.
Due to their ability to capture attention, emotional stimuli tend to benefit from enhanced perceptual processing, which can be helpful when such stimuli are task-relevant but hindering when they are task-irrelevant. Altered emotion-attention interactions have been associated with symptoms of affective disturbances, and emerging research focuses on improving emotion-attention interactions to prevent or treat affective disorders. In line with the Human Affectome Project's emphasis on linguistic components, we also analyzed the language used to describe attention-related aspects of emotion, and highlighted terms related to domains such as conscious awareness, motivational effects of attention, social attention, and emotion regulation. These terms were discussed within a broader review of available evidence regarding the neural correlates of (1) Emotion-Attention Interactions in Perception, (2) Emotion-Attention Interactions in Learning and Memory, (3) Individual Differences in Emotion-Attention Interactions, and (4) Training and Interventions to Optimize Emotion-Attention Interactions. This comprehensive approach enabled an integrative overview of the current knowledge regarding the mechanisms of emotion-attention interactions at multiple levels of analysis, and identification of emerging directions for future investigations.
In contrast to the common conception that the interfacial energy-level alignment is affixed once the interface is formed, we demonstrate that heterojunctions between organic semiconductors and metal-halide perovskites exhibit huge energy-level realignment during photoexcitation. Importantly, the photoinduced level shifts occur in the organic component, including the first molecular layer in direct contact with the perovskite. This is caused by charge-carrier accumulation within the organic semiconductor under illumination and the weak electronic coupling between the junction components.
This study is trying to understand the pre-eruptive magma storage and crystallization conditions of the Middle Miocene aged, silica-saturated trachytic rocks of the Afyon Volcanic Complex (AVC) in Western Anatolia, Turkey. Those rocks can be divided by their high K2O, K2O/Na2O ratio and Mg# into two groups, namely the intermediate-potassic (IPG) and the ultrapotassic (UPG). Here we are comparing calculated pressure (P) - temperature (T) conditions derived from geothermobarometric calculations of natural samples with results of high-pressure, high-temperature phase equilibria experiments. IPG samples are richer in silica (57-64 wt% SiO2), whereas UPG samples show intermediate SiO2 contents of 56-58 wt%. UPG are having high K2O contents ((>)9 wt %), K2O/Na2O ratios ((>)10 wt%) and Mg# values (75-77). IPG phenocrysts comprise plagioclase + biotite + amphibole + clinopyroxene +/- orthopyroxene +/- sanidine +/- phlogopite and oxides, while UPG mineralogical assemblage consists of amphibole + phlogopite + clinopyroxene + olivine + sanidine and oxides. IPG and UPG are enriched in Large-Ion Lithophile Elements (LILE), and both have negative anomalies in Nb, Sr, Zr and Ti elements. Additionally, IPG shows positive anomalies in Pb. Both IPG and UPG display enrichment in Light Rare Earth Elements (LREE), while IPG shows a more significant negative anomaly in Eu when compared to UPG. Plagioclase fractionation may play a role in magma generation. In IPG samples Ni and Cr values range between (3.3-18.8 ppm) and (2.6-27.8 ppm), respectively; whereas UPG samples have (119.1-120.7 ppm) Ni and (212.1-219.9 ppm) Cr. Dy/Yb ratios of IPG and UPG are higher than 2 and may indicate that garnet was present in the source. Geothermobarometric calculations for natural IPG clinopyroxene-melt pairs imply higher PT conditions (Dogan-Kulahci et al., 2015), while in this study high-pressure/high-temperature (HP/HT) phase equilibria experiments recreated the natural mineral assemblage at 2-4 kbar, 6-9 km and c. 900 degrees C. New plagioclase-melt calculations have confirmed lower mean magma storage temperatures, which are closer to the experimental results but still slightly elevated. Thus, trace element results of the natural rocks and experimental data may imply that a deep garnet-bearing magma source mixed with shallower magmas (IPG) was feeding the volcanic eruption.
We traced diatom composition and diversity through time using diatom-derived sedimentary ancient DNA (sedaDNA) from eastern continental slope sediments off Kamchatka (North Pacific) by applying a short, diatom-specific marker on 63 samples in a DNA metabarcoding approach. The sequences were assigned to diatoms that are common in the area and characteristic of cold water. SedaDNA allowed us to observe shifts of potential lineages from species of the genus Chaetoceros that can be related to different climatic phases, suggesting that pre-adapted ecotypes might have played a role in the long-term success of species in areas of changing environmental conditions. These sedaDNA results complement our understanding of the long-term history of diatom assemblages and their general relationship to environmental conditions of the past. Sea-ice diatoms (Pauliella taeniata [Grunow] Round & Basson, Attheya septentrionalis [ostrup] R. M. Crawford and Nitzschia frigida [Grunow]) detected during the late glacial and Younger Dryas are in agreement with previous sea-ice reconstructions. A positive correlation between pennate diatom richness and the sea-ice proxy IP25 suggests that sea ice fosters pennate diatom richness, whereas a negative correlation with June insolation and temperature points to unfavorable conditions during the Holocene. A sharp increase in proportions of freshwater diatoms at similar to 11.1 cal kyr BP implies the influence of terrestrial runoff and coincides with the loss of 42% of diatom sequence variants. We assume that reduced salinity at this time stabilized vertical stratification which limited the replenishment of nutrients in the euphotic zone.
Prior research suggests that teachers with higher levels of empathy are more willing to intervene in bullying among students. However, these findings are based on hypothetical bullying situations and teachers' self-reports. In this study with 2,071 German students and their 556 teachers, we analysed reactions to hypothetical relational bullying situations as well as retrospectively reported bullying situations both from the teachers' as well as the students' perspectives. Results showed that teachers with higher levels of empathy reported stronger intentions to intervene in hypothetical relational bullying situations but were not more likely to intervene in retrospectively reported bullying situations. From the students' perspective, teachers' empathy was neither connected to the teachers' intention to intervene nor to the likelihood of intervention in the retrospectively reported situations. These different results could be taken as an opportunity to investigate whether existing findings could be influenced by methodological aspects such as teachers' self-reports. Implications for future research are discussed.
Cyanobacteria are important primary producers in temperate freshwater ecosystems. However, studies on the seasonal and spatial distribution of cyanobacteria in deep lakes based on high-throughput DNA sequencing are still rare. In this study, we combined monthly water sampling and monitoring in 2019, amplicon sequence variants analysis (ASVs; a proxy for different species) and quantitative PCR targeting overall cyanobacteria abundance to describe the seasonal and spatial dynamics of cyanobacteria in the deep hard-water oligo-mesotrophic Lake Tiefer See, NE Germany. We observed significant seasonal variation in the cyanobacterial community composition (p < 0.05) in the epi- and metalimnion layers, but not in the hypolimnion. In winter-when the water column is mixed-picocyanobacteria (Synechococcus and Cyanobium) were dominant. With the onset of stratification in late spring, we observed potential niche specialization and coexistence among the cyanobacteria taxa driven mainly by light and nutrient dynamics. Specifically, ASVs assigned to picocyanobacteria and the genus Planktothrix were the main contributors to the formation of deep chlorophyll maxima along a light gradient. While Synechococcus and different Cyanobium ASVs were abundant in the epilimnion up to the base of the euphotic zone from spring to fall, Planktothrix mainly occurred in the metalimnetic layer below the euphotic zone where also overall cyanobacteria abundance was highest in summer. Our data revealed two potentially psychrotolerant (cold-adapted) Cyanobium species that appear to cope well under conditions of lower hypolimnetic water temperature and light as well as increasing sediment-released phosphate in the deeper waters in summer. The potential cold-adapted Cyanobium species were also dominant throughout the water column in fall and winter. Furthermore, Snowella and Microcystis-related ASVs were abundant in the water column during the onset of fall turnover. Altogether, these findings suggest previously unascertained and considerable spatiotemporal changes in the community of cyanobacteria on the species level especially within the genus Cyanobium in deep hard-water temperate lakes.
Many animals form aggregations with individuals of the same species (single-species aggregations, SSA). Less frequently, individuals may also aggregate with individuals of other species (mixed-species aggregations, MSA). Although the benefits and costs of SSA have been intensively studied, the same is not true for MSA. Here, we first review the cases of MSA in harvestmen, an arachnid order in which the records of MSA are more frequent than other arthropod orders. We then propose several benefits and costs of MSA in harvestmen, and contrast them with those of SSA. Second, using field-gathered data we describe gregariousness in seven species of Prionostemma harvestmen from Costa Rica. These species form MSA, but individuals are also found solitarily or in SSA. We tested one possible benefit and one possible cost of gregariousness in Prionostemma harvestmen. Regarding the benefit, we hypothesized that individuals missing legs would be more exposed to predation than eight-legged individuals and thus they should be found preferentially in aggregations, where they would be more protected from predators. Our data, however, do not support this hypothesis. Regarding the cost, we hypothesized that gregariousness increases the chances of parasitism. We found no support for this hypothesis either because both mite prevalence and infestation intensity did not differ between solitary or aggregated individuals. Additionally, the type of aggregation (SSA or MSA) was not associated with the benefit or the cost we explored. This lack of effect may be explained by the fluid membership of the aggregations, as we found high turnover over time in the number of individuals and species composition of the aggregations. In conclusion, we hope our review and empirical data stimulate further studies on MSA, which remains one of the most elusive forms of group living in animals.
The purpose of this study was to examine the longitudinal relationship between problematic online gaming and subjective health complaints and depressive symptoms, and the moderation of console-gaming aggression (i.e. verbal aggression, camping, trolling) in this relationship. Participants were 202 adolescents (86% boys; M age = 12.99 years) in the 7(th) or 8(th) grade who played first-person shooter games. They completed questionnaires on problematic online gaming, console-gaming aggression, subjective health complaints, and depressive symptoms. Six months later (Time 2), they completed questionnaires on subjective health complaints and depressive symptoms again. Findings revealed that problematic online gaming and console-gaming aggression were positive predictors of Time 2 subjective health complaints and depressive symptoms, while controlling for Time 1 levels and gender. Moderating effects were found as well, indicating that high levels of console-gaming aggression increased the positive relationship between problematic online gaming and depressive symptoms. These effects were also replicated for verbal aggression, problematic online gaming, and subjective health complaints. These findings suggest the importance of considering the implications of console-gaming aggression and problematic online gaming for the physical and mental health of adolescents.
IMPACT SUMMARY
Prior State of Knowledge. Problematic online gaming and aggressive behaviors are linked to negative outcomes, including depression and subjective health complaints. Longitudinal research further supports this connection for depression, but not for subjective health complaints or various types of aggression via console games.
Novel Contributions. Few studies have focused on various types of aggression and the longitudinal associations among problematic online gaming, depression, and subjective health complaints, while controlling for previous levels of depression and subjective health complaints. The present research addresses these gaps.
Practical Implications. Findings of the present research has implications for clinicians and researchers concerned with identifying adolescents who might be at risk for negative outcomes.
Hidden semi-Markov models generalise hidden Markov models by explicitly modelling the time spent in a given state, the so-called dwell time, using some distribution defined on the natural numbers. While the (shifted) Poisson and negative binomial distribution provide natural choices for such distributions, in practice, parametric distributions can lack the flexibility to adequately model the dwell times. To overcome this problem, a penalised maximum likelihood approach is proposed that allows for a flexible and data-driven estimation of the dwell-time distributions without the need to make any distributional assumption. This approach is suitable for direct modelling purposes or as an exploratory tool to investigate the latent state dynamics. The feasibility and potential of the suggested approach is illustrated in a simulation study and by modelling muskox movements in northeast Greenland using GPS tracking data. The proposed method is implemented in the R-package PHSMM which is available on CRAN.
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.
Seed dispersal plays an important role in population dynamics in agricultural ecosystems, but the effects of surrounding vegetation height on seed dispersal and population connectivity on the landscape scale have rarely been studied. Understanding the effects of surrounding vegetation height on seed dispersal will provide important information for land-use management in agricultural landscapes to prevent the spread of undesired weeds or enhance functional connectivity. We used two model species, Phragmites australis and Typha latifolia, growing in small natural ponds known as kettle holes, in an agricultural landscape to evaluate the effects of surrounding vegetation height on wind dispersal and population connectivity between kettle holes. Seed dispersal distance and the probability of long-distance dispersal (LDD) were simulated with the mechanistic WALD model under three scenarios of "low", "dynamic" and "high" surrounding vegetation height. Connectivity between the origin and target kettle holes was quantified with a connectivity index adapted from Hanski and Thomas (1994). Our results show that mean seed dispersal distance decreases with the height of surrounding matrix vegetation, but the probability of long-distance dispersal (LDD) increases with vegetation height. This indicates an important vegetation-based trade-off between mean dispersal distance and LDD, which has an impact on connectivity. Matrix vegetation height has a negative effect on mean seed dispersal distance but a positive effect on the probability of LDD. This positive effect and its impact on connectivity provide novel insights into landscape level (meta-)population and community dynamics - a change in matrix vegetation height by land-use or climatic changes could strongly affect the spread and connectivity of wind-dispersed plants. The opposite effect of vegetation height on mean seed dispersal distance and the probability of LDD should therefore be considered in management and analyses of future land-use and climate change effects.
Ranking local climate policy
(2021)
Climate mitigation and climate adaptation are crucial tasks for urban areas and can involve synergies as well as trade-offs. However, few studies have examined how mitigation and adaptation efforts relate to each other in a large number of differently sized cities, and therefore we know little about whether forerunners in mitigation are also leading in adaptation or if cities tend to focus on just one policy field. This article develops an internationally applicable approach to rank cities on climate policy that incorporates multiple indicators related to (1) local commitments on mitigation and adaptation, (2) urban mitigation and adaptation plans and (3) climate adaptation and mitigation ambitions. We apply this method to rank 104 differently sized German cities and identify six clusters: climate policy leaders, climate adaptation leaders, climate mitigation leaders, climate policy followers, climate policy latecomers and climate policy laggards. The article seeks explanations for particular cities' positions and shows that coping with climate change in a balanced way on a high level depends on structural factors, in particular city size, the pathways of local climate policies since the 1990s and funding programmes for both climate mitigation and adaptation.
Objective:
Following a life course perspective, this study examines the link between partnership trajectories and three dimensions of psychological well-being: psychological health, overall sense of self-worth and quality of life.
Background:
Assuming that life outcomes are the result of prior decisions, experiences and events, partnership histories can be seen as a resource for psychological well-being. Furthermore, advantages or disadvantages from living with or without a partner should accumulate over time. While previous cross-sectional research has mainly focused on the influence of partnership status or a status change on well-being, prior longitudinal studies could not control for reverse causality of well-being and partnership trajectories. This research addresses the question of how different patterns of partnership biographies are related to a person's well-being in middle adulthood. Selection effects of pre-trajectory well-being as well as current life conditions are also taken into account.
Method:
Using data from the German LifE Study, the partnership trajectories between ages of 16 and 45 are classified by sequence and cluster analysis. OLS regression is then used to examine the link between types of partnership trajectories and depression, self-esteem and overall life satisfaction at age 45.
Results:
For women, well-being declined when experiencing unstable non-cohabitational union trajectories or divorce followed by unpartnered post-marital trajectories. Men suffered most from being long-term single. The results could not be explained by selection effects of pre-trajectory well-being.
Conclusion:
While women seem to 'recover' from most of the negative effects of unstable partnership trajectories through a new partnership, for men it was shown that being mainly unpartnered has long-lasting effects on their psychological well-being.
This eye-tracking study establishes basic benchmarks of eye movements during reading in heritage language (HL) by Russian-speaking adults and adolescents of high (n = 21) and low proficiency (n = 27). Heritage speakers (HSs) read sentences in Cyrillic, and their eye movements were compared to those of Russian monolingual skilled adult readers, 8-year-old children and L2 learners. Reading patterns of HSs revealed longer mean fixation durations, lower skipping probabilities, and higher regressive saccade rates than in monolingual adults. High-proficient HSs were more similar to monolingual children, while low-proficient HSs performed on par with L2 learners. Low-proficient HSs differed from high-proficient HSs in exhibiting lower skipping probabilities, higher fixation counts, and larger frequency effects. Taken together, our findings are consistent with the weaker links account of bilingual language processing as well as the divergent attainment theory of HL.
This study examined the effect of 6 weeks of progressed and nonprogressed volume-based overload plyometric training (PT) on components of physical fitness and body composition measures in young male basketball players, compared with an active control group. Subjects were randomly assigned to a progressed PT (PPT, n = 7; age = 14.6 +/- 1.1 years), a non-PPT (NPPT, n = 8, age = 13.8 +/- 2.0 years), or a control group (CG, n = 7, age = 14.0 +/- 2.0 years). Before and after training, body composition measures (muscle mass and fat mass), countermovement jump with arms (CMJA) and countermovement jump without arms (CMJ), horizontal bilateral (HCMJ) and unilateral jump with right leg (RJ) and left leg (LJ), 20-cm drop jump (DJ20), sprint speed (10 m sprint), and change of direction speed (CODS [i.e., T-test]) were tested. Significant effects of time were observed for muscle and fat mass, all jump measures, and CODS (all p < 0.01; d = 0.37-0.83). Significant training group x time interactions were observed for all jump measures (all p < 0.05; d = 0.24-0.41). Post hoc analyses revealed significant pre-post performance improvements for the PPT (RJ and LJ: increment 18.6%, d = 0.8 and increment 22.7%, d = 0.9, respectively; HCMJ: increment 16.4%, d = 0.8; CMJ: increment 22.4%, d = 0.7; CMJA: increment 23.3%, d = 0.7; and DJ20: increment 39.7%, d = 1.1) and for the NPPT group (LJ: increment 14.1%, d = 0.4; DJ20: increment 32.9%, d = 0.8) with greater changes after PPT compared with NPPT for all jump measures (all p < 0.05; d = 0.21-0.81). The training efficiency was greater (p < 0.05; d = 0.22) after PPT (0.015% per jump) compared with NPPT (0.0053% per-jump). The PPT induced larger performance improvements on measures of physical fitness as compared to NPPT. Therefore, in-season progressive volume-based overload PT in young male basketball players is recommended.
Do stereotypes strike twice?
(2019)
Stereotypes influence teachers' perception of and behaviour towards students, thus shaping students' learning opportunities. The present study investigated how 315 Australian pre-service teachers' stereotypes about giftedness and gender are related to their perception of students' intellectual ability, adjustment, and social-emotional ability, using an experimental vignette approach and controlling for social desirability in pre-service teachers' responses. Repeated-measures ANOVA showed that pre-service teachers associated giftedness with higher intellectual ability, but with less adjustment compared to average-ability students. Furthermore, pre-service teachers perceived male students as less socially and emotionally competent and less adjusted than female students. Additionally, pre-service teachers seemed to perceive female average-ability students' adjustment as most favourable compared to male average-ability students and gifted students. Findings point to discrepancies between actual characteristics of gifted female and male students and stereotypes in teachers' beliefs. Consequences of stereotyping and implications for teacher education are discussed.
Making sense of the world
(2020)
For human infants, the first years after birth are a period of intense exploration-getting to understand their own competencies in interaction with a complex physical and social environment. In contemporary neuroscience, the predictive-processing framework has been proposed as a general working principle of the human brain, the optimization of predictions about the consequences of one's own actions, and sensory inputs from the environment. However, the predictive-processing framework has rarely been applied to infancy research. We argue that a predictive-processing framework may provide a unifying perspective on several phenomena of infant development and learning that may seem unrelated at first sight. These phenomena include statistical learning principles, infants' motor and proprioceptive learning, and infants' basic understanding of their physical and social environment. We discuss how a predictive-processing perspective can advance the understanding of infants' early learning processes in theory, research, and application.
We are glad to introduce the Second Journal Club of Volume Five, Second Issue. This edition is focused on relevant studies published in the last few years in the field of resistance training, chosen by our Editorial Board members and their colleagues. We hope to stimulate your curiosity in this field and to share with you the passion for the sport, seen also from the scientific point of view. The Editorial Board members wish you an inspiring lecture.
The Kohat fold and thrust belt in Pakistan shows a significantly different structural style due to the structural evolution on the double décollement compared to the rest of the Subhimalaya. In order to better understand the spatio-temporal structural evolution of the Kohat fold and thrust belt, we combine balanced cross sections with apatite (U?Th-Sm)/He (AHe) and apatite fission track (AFT) dating. The AHe and AFT ages appear to be totally reset, allowing us to date exhumation above structural ramps. The results suggest that deformation began on the frontal Surghar thrust at-15 Ma, predating or coeval with the development of the Main Boundary thrust at-12 Ma. Deformation propagated southward from the Main Boundary thrust on double de?collements between 10 Ma and 2 Ma, resulting in a disharmonic structural style inside the Kohat fold and thrust belt. Thermal modeling of the thermochronologic data suggest that samples inside Kohat fold and thrust belt experienced cooling due to formation of the duplexes; this deformation facilitated tectonic thickening of the wedge and erosion of the Miocene to Pliocene foreland strata. The spatial distribution of AHe and AFT ages in combination with the structural forward model suggest that, in the Kohat fold and thrust belt, the wedge deformed in-sequence as a supercritical wedge (-15-12 Ma), then readjusted by out-sequence deformation (-12-0 Ma) within the Kohat fold and thrust belt into a sub-critical wedge.
CrashNet
(2021)
Destructive car crash tests are an elaborate, time-consuming, and expensive necessity of the automotive development process. Today, finite element method (FEM) simulations are used to reduce costs by simulating car crashes computationally. We propose CrashNet, an encoder-decoder deep neural network architecture that reduces costs further and models specific outcomes of car crashes very accurately. We achieve this by formulating car crash events as time series prediction enriched with a set of scalar features. Traditional sequence-to-sequence models are usually composed of convolutional neural network (CNN) and CNN transpose layers. We propose to concatenate those with an MLP capable of learning how to inject the given scalars into the output time series. In addition, we replace the CNN transpose with 2D CNN transpose layers in order to force the model to process the hidden state of the set of scalars as one time series. The proposed CrashNet model can be trained efficiently and is able to process scalars and time series as input in order to infer the results of crash tests. CrashNet produces results faster and at a lower cost compared to destructive tests and FEM simulations. Moreover, it represents a novel approach in the car safety management domain.
Online hate speech has become a widespread problem in the daily life of adolescents. Despite growing societal and academic interest in this online risk, not much is known about the relationship between online hate speech victimization (OHSV) and adolescents' mental well-being.
In addition, potential factors influencing the magnitude of this relationship remain unclear. To address these gaps in the literature, this study investigated the relationship between OHSV and depressive symptoms and the buffering effects of resilience in this relationship. The sample consists of 1,632 adolescents (49.1% girls) between 12 and 18 years old (M-age = 13.83, SDage = 1.23), recruited from nine schools across Spain.
Self-report questionnaires were administered to assess OHSV, depressive symptoms, and resilience. Regression analyses revealed that OHSV was positively linked to depressive symptoms.
In addition, victims of online hate speech were less likely to report depressive symptoms when they reported average or high levels of resilience (i.e., social competence, personal competence, structured style, social resources, and family cohesion) compared with those with low levels of resilience.
Our findings highlight the need for the development of intervention programs and the relevance of focusing on internal and external developmental assets to mitigate negative outcomes for victims of online hate speech.
Deciphering chemical mediators regulating specialized metabolism in a symbiotic cyanobacterium
(2022)
Genomes of cyanobacteria feature a variety of cryptic biosynthetic pathways for complex natural products, but the peculiarities limiting the discovery and exploitation of the metabolic dark matter are not well understood. Here we describe the discovery of two cell density-dependent chemical mediators, nostoclide and nostovalerolactone, in the symbiotic model strain Nostoc punctiforme, and demonstrate their pronounced impact on the regulation of specialized metabolism. Through transcriptional, bioinformatic and labeling studies we assigned two adjacent biosynthetic gene clusters to the biosynthesis of the two polyketide mediators. Our findings provide insight into the orchestration of specialized metabolite production and give lessons for the genomic mining and high-titer production of cyanobacterial bioactive compounds.
Surface melting of the Greenland Ice Sheet contributes a large amount to current and future sea level rise. Increased surface melt may lower the reflectivity of the ice sheet surface and thereby increase melt rates: the so-called melt-albedo feedback describes this self-sustaining increase in surface melting. In order to test the effect of the melt-albedo feedback in a prognostic ice sheet model, we implement dEBM-simple, a simplified version of the diurnal Energy Balance Model dEBM, in the Parallel Ice Sheet Model (PISM). The implementation includes a simple representation of the melt-albedo feedback and can thereby replace the positive-degree-day melt scheme. Using PISM-dEBM-simple, we find that this feedback increases ice loss through surface warming by 60 % until 2300 for the high-emission scenario RCP8.5 when compared to a scenario in which the albedo remains constant at its present-day values. With an increase of 90 % compared to a fixed-albedo scenario, the effect is more pronounced for lower surface warming under RCP2.6. Furthermore, assuming an immediate darkening of the ice surface over all summer months, we estimate an upper bound for this effect to be 70 % in the RCP8.5 scenario and a more than 4-fold increase under RCP2.6. With dEBM-simple implemented in PISM, we find that the melt-albedo feedback is an essential contributor to mass loss in dynamic simulations of the Greenland Ice Sheet under future warming.
Knowing the source and runout of debris flows can help in planning strategies aimed at mitigating these hazards. Our research in this paper focuses on developing a novel approach for optimizing runout models for regional susceptibility modelling, with a case study in the upper Maipo River basin in the Andes of Santiago, Chile. We propose a two-stage optimization approach for automatically selecting parameters for estimating runout path and distance. This approach optimizes the random-walk and Perla et al.'s (PCM) two-parameter friction model components of the open-source Gravitational Process Path (GPP) modelling framework. To validate model performance, we assess the spatial transferability of the optimized runout model using spatial crossvalidation, including exploring the model's sensitivity to sample size. We also present diagnostic tools for visualizing uncertainties in parameter selection and model performance. Although there was considerable variation in optimal parameters for individual events, we found our runout modelling approach performed well at regional prediction of potential runout areas. We also found that although a relatively small sample size was sufficient to achieve generally good runout modelling performance, larger samples sizes (i.e. >= 80) had higher model performance and lower uncertainties for estimating runout distances at unknown locations. We anticipate that this automated approach using the open-source R software and the System for Automated Geoscientific Analyses geographic information system (SAGA-GIS) will make process-based debris-flow models more readily accessible and thus enable researchers and spatial planners to improve regional-scale hazard assessments.
Only the right noise?
(2020)
Seminal work by Werker and colleagues (Stager & Werker [1997]Nature, 388, 381-382) has found that 14-month-old infants do not show evidence for learning minimal pairs in the habituation-switch paradigm. However, when multiple speakers produce the minimal pair in acoustically variable ways, infants' performance improves in comparison to a single speaker condition (Rost & McMurray [2009]Developmental Science, 12, 339-349). The current study further extends these results and assesses how different kinds of input variability affect 14-month-olds' minimal pair learning in the habituation-switch paradigm testing German learning infants. The first two experiments investigated word learning when the labels were spoken by a single speaker versus when the labels were spoken by multiple speakers. In the third experiment we studied whether non-acoustic variability, implemented by visual variability of the objects presented together with the labels, would also affect minimal pair learning. We found enhanced learning in the multiple speakers compared to the single speaker condition, confirming previous findings with English-learning infants. In contrast, visual variability of the presented objects did not support learning. These findings both confirm and better delimit the beneficial role of speech-specific variability in minimal pair learning. Finally, we review different proposals on the mechanisms via which variability confers benefits to learning and outline what may be likely principles that underlie this benefit. We highlight among these the multiplicity of acoustic cues signalling phonemic contrasts and the presence of relations among these cues. It is in these relations where we trace part of the source for the apparent paradoxical benefit of variability in learning.
In this article, I give an overview on nativist street protests in Germany from the early nineteenth century to the present from an historical perspective. In a preliminary re-mark, I will reflect on some recent developments in Germany, where nativist protest campaigns against immigration took place in the streets when voters were turning towards the populist radical right party Alternative für Deutschland (AfD). In the first section, I will outline an older tradition of anti-immigration protest in nineteenth and early twentieth century Germany, which is closely connected to modern antisemitism. In sections two and three, I will retrace how, from the late 1960s onward, the far right in the Federal Republic of Germany (FRG) discovered concerns about immigra-tion in the German population, addressed them in protest campaigns and developed narratives to integrate such sentiments into a broader right-wing extremist ideology, itself deeply rooted in antisemitism. Studying nativism and the radical right from an actor-oriented perspective, I will focus on traditionalist movements, including the Nationaldemokratische Partei Deutschlands (NPD) and neo-Nazi groups.
This study addresses the question of whether and how growing up with more than one language shapes a child's language impairment. Our focus is on Specific Language Impairment (SLI) in bilingual (Turkish-German) children. We specifically investigated a range of phenomena related to the so-called CP (Complementizer Phrase) in German, the hierarchically highest layer of syntactic clause structure, which has been argued to be particularly affected in children with SLI. Spontaneous speech data were examined from bilingual children with SLI in comparison to two comparison groups: (i) typically-developing bilingual children, (ii) monolingual children with SLI. We found that despite persistent difficulty with subject-verb agreement, the two groups of children with SLI did not show any impairment of the CP-domain. We conclude that while subject-verb agreement is a suitable linguistic marker of SLI in German-speaking children, for both monolingual and bilingual ones, 'vulnerability of the CP-domain' is not.
In his essay, Mel Ainscow looks at inclusion and equity from an international perspective and makes suggestions on how to develop inclusive education in a ‘whole-system approach’. After discussing different conceptions of inclusion and equity, he describes international policies which address them. From this international macro-level, Ainscow zooms in to the meso-level of the school and its immediate environment, defining dimensions to be considered for an inclusive school development. One of these dimensions is the ‘use of evidence’. In my comment, I want to focus on this dimension and discuss its scope and the potential to apply it in inclusive education development. As a first and important precondition, Ainscow explains that different circumstances lead to different linguistic uses of the term ‘inclusive education’. Thus, the term ‘inclusive education’ does not refer to an identical set of objectives across countries, and neither does the term ‘equity’.
Rats are a reservoir of human- and livestock-associated methicillin-resistant Staphylococcus aureus (MRSA). However, the composition of the natural S. aureus population in wild and laboratory rats is largely unknown. Here, 144 nasal S. aureus isolates from free-living wild rats, captive wild rats and laboratory rats were genotyped and profiled for antibiotic resistances and human-specific virulence genes. The nasal S. aureus carriage rate was higher among wild rats (23.4%) than laboratory rats (12.3%). Free-living wild rats were primarily colonized with isolates of clonal complex (CC) 49 and CC130 and maintained these strains even in husbandry. Moreover, upon livestock contact, CC398 isolates were acquired. In contrast, laboratory rats were colonized with many different S. aureus lineages—many of which are commonly found in humans. Five captive wild rats were colonized with CC398-MRSA. Moreover, a single CC30-MRSA and two CC130-MRSA were detected in free-living or captive wild rats. Rat-derived S. aureus isolates rarely harbored the phage-carried immune evasion gene cluster or superantigen genes, suggesting long-term adaptation to their host. Taken together, our study revealed a natural S. aureus population in wild rats, as well as a colonization pressure on wild and laboratory rats by exposure to livestock- and human-associated S. aureus, respectively.
Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe
(2020)
Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that similar to 75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least onethird of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.
Objective:
Stunting (height-for-age < −2 SD) is one of the forms of undernutrition and is frequent among children of low- and middle-income countries. But stunting perSe is not a synonym of undernutrition. We investigated association between body height and indicators of energetic undernutrition at three critical thresholds for thinness used in public health: (1) BMI SDS < −2; (2) mid-upper arm circumference divided by height (MUAC (mm) × 10/height (cm) < 1·36) and (3) mean skinfold thickness (SF) < 7 mm and to question the reliability of thresholds as indicators of undernutrition.
Design:
Cross-sectional study; breakpoint analysis.
Setting:
Rural and urban regions of Indonesia and Guatemala – different socio-economic status (SES).
Participants:
1716 Indonesian children (6·0–13·2 years) and 3838 Guatemalan children (4·0–18·9 years) with up to 50 % stunted children.
Results:
When separating the regression of BMI, MUAC or SF, on height into distinguishable segments (breakpoint analysis), we failed to detect relevant associations between height, and BMI, MUAC or SF, even in the thinnest and shortest children. For BMI and SF, the breakpoint analysis either failed to reach statistical significance or distinguished at breakpoints above critical thresholds. For MUAC, the breakpoint analysis yielded negative associations between MUAC/h and height in thin individuals. Only in high SES Guatemalan children, SF and height appeared mildly associated with R2 = 0·017.
Conclusions:
Currently used lower thresholds of height-for-age (stunting) do not show relevant associations with anthropometric indicators of energetic undernutrition. We recommend using the catch-up growth spurt during early re-feeding instead as immediate and sensitive indicator of past undernourishment. We discuss the primacy of education and social-economic-political-emotional circumstances as responsible factors for stunting.
Forage availability has been suggested as one driver of the observed decline in honey bees. However, little is known about the effects of its spatiotemporal variation on colony success. We present a modeling framework for assessing honey bee colony viability in cropping systems. Based on two real farmland structures, we developed a landscape generator to design cropping systems varying in crop species identity, diversity, and relative abundance. The landscape scenarios generated were evaluated using the existing honey bee colony model BEEHAVE, which links foraging to in-hive dynamics. We thereby explored how different cropping systems determine spatiotemporal forage availability and, in turn, honey bee colony viability (e.g., time to extinction, TTE) and resilience (indicated by, e.g., brood mortality). To assess overall colony viability, we developed metrics,P(H)andP(P,)which quantified how much nectar and pollen provided by a cropping system per year was converted into a colony's adult worker population. Both crop species identity and diversity determined the temporal continuity in nectar and pollen supply and thus colony viability. Overall farmland structure and relative crop abundance were less important, but details mattered. For monocultures and for four-crop species systems composed of cereals, oilseed rape, maize, and sunflower,P(H)andP(P)were below the viability threshold. Such cropping systems showed frequent, badly timed, and prolonged forage gaps leading to detrimental cascading effects on life stages and in-hive work force, which critically reduced colony resilience. Four-crop systems composed of rye-grass-dandelion pasture, trefoil-grass pasture, sunflower, and phacelia ensured continuous nectar and pollen supply resulting in TTE > 5 yr, andP(H)(269.5 kg) andP(P)(108 kg) being above viability thresholds for 5 yr. Overall, trefoil-grass pasture, oilseed rape, buckwheat, and phacelia improved the temporal continuity in forage supply and colony's viability. Our results are hypothetical as they are obtained from simplified landscape settings, but they nevertheless match empirical observations, in particular the viability threshold. Our framework can be used to assess the effects of cropping systems on honey bee viability and to develop land-use strategies that help maintain pollination services by avoiding prolonged and badly timed forage gaps.
The aim of this study was to assess the ability of the FFQ to describe reliable and valid dietary pattern (DP) scores. In a total of 134 participants of the European Prospective Investigation into Cancer and Nutrition-Potsdam study aged 35-67 years, the FFQ was applied twice (baseline and after 1 year) to assess its reliability. Between November 1995 and March 1997, twelve 24-h dietary recalls (24HDR) as reference instrument were applied to assess the validity of the FFQ. Exploratory DP were derived by principal component analyses. Investigated predefined DP were the Alternative Healthy Eating Index (AHEI) and two Mediterranean diet indices. From dietary data of each FFQ, two exploratory DP were retained, but differed in highly loading food groups, resulting in moderate correlations (r 0 center dot 45-0 center dot 58). The predefined indices showed higher correlations between the FFQ (r(AHEI) 0 center dot 62, r(Mediterranean Diet Pyramid Index (MedPyr)) 0 center dot 62 and r(traditional Mediterranean Diet Score (tMDS)) 0 center dot 51). From 24HDR dietary data, one exploratory DP retained differed in composition to the first FFQ-based DP, but showed similarities to the second DP, reflected by a good correlation (r 0 center dot 70). The predefined DP correlated moderately (r 0 center dot 40-0 center dot 60). To conclude, long-term analyses on exploratory DP should be interpreted with caution, due to only moderate reliability. The validity differed extensively for the two exploratory DP. The investigated predefined DP showed a better reliability and a moderate validity, comparable to other studies. Within the two Mediterranean diet indices, the MedPyr performed better than the tMDs in this middle-aged, semi-urban German study population.
Across continental Europe, educational research samples are often divided by 'migrant background', a binary variable criticized for masking participant heterogeneity and reinforcing exclusionary norms of belonging.
This study endorses more meaningful, representative, and precise research by offering four guiding questions for selecting relevant, social justice oriented, and feasible social categories for collecting and analysing data in psychological and educational research. Using a preregistered empirical example, we first compare selected social categories ('migrant background', family heritage, religion, citizenship, cultural identification, and generation status) in their potential to reveal participant heterogeneity.
Second, we investigate differences in means and relations between variables (discrimination experiences, perceived societal Islamophobia, and national identity) and academic motivation among 1335 adolescents in Germany (48% female, M-age = 14.69). Regression analyses and multigroup SEM revealed differential experiences with and implications of discrimination for academic motivation.
Results highlight the need for a deliberate, transparent use of social categories to make discrimination visible and centre participants' subjective experiences.
Despite public discourses highlighting the negative consequences of time spent online (TSO) for children's well-being, Norwegian children (aged 9-16 years) use the Internet more than other European children and score higher on self-reported life satisfaction (SRLS).
To explore the possibility that TSO might contribute to high life satisfaction or other underlying explanatory factors, we investigate the relationship between TSO and SRLS in Norway while also accounting for how individual, family, school, and broader social circumstances influence this relationship.
Countering prevailing discourses, we find a positive relationship between TSO and SRLS, which remains positive and significant even after a wider range of variables are accounted for.
By explaining the circumstances under which TSO has a positive effect on SRLS, this article provides evidence of the complex role that digital technology plays in the lives of children.
It also provides a critique of the often simplistic arguments found in public discourses around children's digital media use.
States, in their conflicts with militant groups embedded in civilian populations, often resort to policies of collective punishment to erode civilian support for the militants. We attempt to evaluate the efficacy of such policies in the context of the Gaza Strip, where Israel's blockade and military interventions, purportedly intended to erode support for Hamas, have inflicted hardship on the civilian population.
We combine Palestinian public opinion data, Palestinian labor force surveys, and Palestinian fatalities data, to understand the relationship between exposure to Israeli policies and Palestinian support for militant factions.
Our baseline strategy is a difference-in-differences specification that compares the gap in public opinion between the Gaza Strip and the West Bank during periods of intense punishment with the gap during periods when punishment is eased. Consistent with previous research, we find that Palestinian fatalities are associated with Palestinian support for more militant political factions. The effect is short-lived, however, dissipating after merely one quarter.
Moreover, the blockade of Gaza itself appears to be only weakly associated with support for militant factions. Overall, we find little evidence to suggest that Israeli security policies toward the Gaza Strip have any substantial lasting effect on Gazan support for militant factions, neither deterring nor provoking them relative to their West Bank counterparts.
Our findings therefore call into question the logic of Israel's continued security policies toward Gaza, while prompting a wider re-examination of the efficacy of deterrence strategies in other asymmetric conflicts.
Sporadic E or Es is a transient phenomenon where thin layers of enhanced electron density appear in the ionospheric E region (90-120 km altitude). The neutral wind shear caused by atmospheric tides can lead ions to converge vertically at E-region heights and form the Es layer. This research aims to determine the role of atmospheric solar and lunar tides in Es occurrence. For this purpose, radio occultation data of FORMOSAT-3/COSMIC have been used, which provide complete global coverage of Es events. Moreover, GAIA model simulations have been employed to evaluate the vertical ion convergence induced by solar tides. The results show both migrating and non-migrating solar tidal signatures and the semidiurnal migrating lunar tidal signature mainly in low and mid-latitude Es occurrence. The seasonal variation of the migrating solar tidal components of Es is in good agreement with those in the vertical ion convergence derived from GAIA at higher altitudes. Furthermore, some non-migrating components of solar tides, including semidiurnal westward wavenumbers 1 and 3 and diurnal eastward wavenumbers 2 and 3, also significantly affect the Es occurrence rate.
We present a chronology framework named LegacyAge 1.0 containing harmonized chronologies for 2831 pollen records (downloaded from the Neotoma Paleoecology Database and the supplementary Asian datasets) together with their age control points and metadata in machine-readable data formats.
All chronologies use the Bayesian framework implemented in Bacon version 2.5.3. Optimal parameter settings of priors (accumulation.shape, memory.strength, memory.mean, accumulation.rate, and thickness) were identified based on information in the original publication or iteratively after preliminary model inspection.
The most common control points for the chronologies are radiocarbon dates (86.1 %), calibrated by the latest calibration curves (IntCal20 and SHCal20 for the terrestrial radiocarbon dates in the Northern Hemisphere and Southern Hemisphere and Marine20 for marine materials).
The original publications were consulted when dealing with outliers and inconsistencies. Several major challenges when setting up the chronologies included the waterline issue (18.8% of records), reservoir effect (4.9 %), and sediment deposition discontinuity (4.4 %).
Finally, we numerically compare the LegacyAge 1.0 chronologies to those published in the original publications and show that the reliability of the chronologies of 95.4% of records could be improved according to our assessment.
Our chronology framework and revised chronologies provide the opportunity to make use of the ages and age uncertainties in synthesis studies of, for example, pollen-based vegetation and climate change.
The LegacyAge 1.0 dataset, including metadata, datings, harmonized chronologies, and R code used, is openaccess and available at PANGAEA (https://doi.org/10.1594/PANGAEA.933132; Li et al., 2021) and Zenodo (https://doi.org/10.5281/zenodo.5815192; Li et al., 2022), respectively.
Predicting the electron population of Earth's ring current during geomagnetic storms still remains a challenging task.
In this work, we investigate the sensitivity of 10 keV ring current electrons to different driving processes, parameterised by the Kp index, during several moderate and intense storms.
Results are validated against measurements from the Van Allen Probes satellites. Perturbing the Kp index allows us to identify the most dominant processes for moderate and intense storms respectively.
We find that during moderate storms (Kp < 6) the drift velocities mostly control the behaviour of low energy electrons, while loss from wave-particle interactions is the most critical parameter for quantifying the evolution of intense storms (Kp > 6). Perturbations of the Kp index used to drive the boundary conditions at GEO and set the plasmapause location only show a minimal effect on simulation results over a limited L range.
It is further shown that the flux at L & SIM; 3 is more sensitive to changes in the Kp index compared to higher L shells, making it a good proxy for validating the source-loss balance of a ring current model.
Motivated by recent epidemic outbreaks, including those of COVID-19, we solve the canonical problem of calculating the dynamics and likelihood of extensive outbreaks in a population within a large class of stochastic epidemic models with demographic noise, including the susceptible-infected-recovered (SIR) model and its general extensions.
In the limit of large populations, we compute the probability distribution for all extensive outbreaks, including those that entail unusually large or small (extreme) proportions of the population infected.
Our approach reveals that, unlike other well-known examples of rare events occurring in discrete-state stochastic systems, the statistics of extreme outbreaks emanate from a full continuum of Hamiltonian paths, each satisfying unique boundary conditions with a conserved probability flux.
The water swelling and subsequent solvent exchange including co-nonsolvency behavior of thin films of a doubly thermo-responsive diblock copolymer (DBC) are studied viaspectral reflectance, time-of-flight neutron reflectometry, and Fourier transform infrared spectroscopy.
The DBC consists of a thermo-responsive zwitterionic (poly(4-((3-methacrylamidopropyl) dimethylammonio) butane-1-sulfonate)) (PSBP) block, featuring an upper critical solution temperature transition in aqueous media but being insoluble in acetone, and a nonionic poly(N-isopropylmethacrylamide) (PNIPMAM) block, featuring a lower critical solution temperature transition in water, while being soluble in acetone.
Homogeneous DBC films of 50-100 nm thickness are first swollen in saturated water vapor (H2OorD2O), before they are subjected to a contraction process by exposure to mixed saturated water/acetone vapor (H2OorD2O/acetone-d6 = 9:1 v/v).
The affinity of the DBC film toward H2O is stronger than for D2O, as inferred from the higher film thickness in the swollen state and the higher absorbed water content, thus revealing a pronounced isotope sensitivity.
During the co-solvent-induced switching by mixed water/acetone vapor, a two-step film contraction is observed, which is attributed to the delayed expulsion of water molecules and uptake of acetone molecules.
The swelling kinetics are compared for both mixed vapors (H2O/acetone-d6 and D2O/acetone-d6) and with those of the related homopolymer films.
Moreover, the concomitant variations of the local environment around the hydrophilic groups located in the PSBP and PNIPMAM blocks are followed.
The first contraction step turns out to be dominated by the behavior of the PSBP block, where as the second one is dominated by the PNIPMAM block.
The unusual swelling and contraction behavior of the latter block is attributed to its co-nonsolvency behavior.
Furthermore, we observe cooperative hydration effects in the DBC films, that is, both polymer blocks influence each other's solvation behavior.
The Caenorhabditis elegans (C. elegans) is a model organism that has been increasingly used in health and environmental toxicity assessments. The quantification of such elements in vivo can assist in studies that seek to relate the exposure concentration to possible biological effects.
Therefore, this study is the first to propose a method of quantitative analysis of 21 ions by ion chromatography (IC), which can be applied in different toxicity studies in C. elegans.
The developed method was validated for 12 anionic species (fluoride, acetate, chloride, nitrite, bromide, nitrate, sulfate, oxalate, molybdate, dichromate, phosphate, and perchlorate), and 9 cationic species (lithium, sodium, ammonium, thallium, potassium, magnesium, manganese, calcium, and barium).
The method did not present the presence of interfering species, with R2 varying between 0.9991 and 0.9999, with a linear range from 1 to 100 mu g L-1.
Limits of detection (LOD) and limits of quantification (LOQ) values ranged from 0.2319 mu g L-1 to 1.7160 mu g L-1 and 0.7028 mu g L-1 to 5.1999 mu g L-1, respectively.
The intraday and interday precision tests showed an Relative Standard Deviation (RSD) below 10.0 % and recovery ranging from 71.0 % to 118.0 % with a maximum RSD of 5.5 %.
The method was applied to real samples of C. elegans treated with 200 uM of thallium acetate solution, determining the uptake and bioaccumulated Tl+ content during acute exposure.
Since 2013, the Committee on Economic, Social and Cultural Rights can examine individual communications under the Optional Protocol to the International Covenant on Economic, Social and Cultural Rights (ICESCR). This opens up the possibility to interpret Covenant provisions in a thorough manner. With regard to forced evictions and the right to housing under Article 11 ICESCR, one can discern a fast-developing approach concerning the proportionality analysis of evictions, entailing the establishment of specific criteria that may guide such analysis. This paper seeks to delineate these developments and will also shed light on possible general trends on the topic of limitations within the Committee’s emerging jurisprudence. In doing so, the paper will address if, and how, the developing proportionality analysis under the individual complaints procedure takes into consideration multi-discriminatory dimensions of State measures and how it specifically relates to or incorporates other ICESCR-concepts, such as minimum core obligations or the reasonableness review under Article 8(4) OP ICESCR.
The art of second nature
(2022)
Symbiotic X-ray binaries are systems hosting a neutron star accreting form the wind of a late-type companion. These are rare objects and so far only a handful of them are known. One of the most puzzling aspects of the symbiotic X-ray binaries is the possibility that they contain strongly magnetized neutron stars. These are expected to be evolutionary much younger compared to their evolved companions and could thus be formed through the (yet poorly known) accretion induced collapse of a white dwarf. In this paper, we perform a broad-band X-ray and soft gamma-ray spectroscopy of two known symbiotic binaries, Sct X-1 and 4U 1700+24, looking for the presence of cyclotron scattering features that could confirm the presence of strongly magnetized NSs. We exploited available Chandra, Swift, and NuSTAR data. We find no evidence of cyclotron resonant scattering features (CRSFs) in the case of Sct X-1 but in the case of 4U 1700+24 we suggest the presence of a possible CRSF at similar to 16 keV and its first harmonic at similar to 31 keV, although we could not exclude alternative spectral models for the broad-band fit. If confirmed by future observations, 4U 1700+24 could be the second symbiotic X-ray binary with a highly magnetized accretor. We also report about our long-term monitoring of the last discovered symbiotic X-ray binary IGR J17329-2731 performed with Swift/XRT. The monitoring revealed that, as predicted, in 2017 this object became a persistent and variable source, showing X-ray flares lasting for a few days and intriguing obscuration events that are interpreted in the context of clumpy wind accretion.
Drought and the availability of mineable phosphorus minerals used for fertilization are two of the important issues agriculture is facing in the future. High phosphorus availability in soils is necessary to maintain high agricultural yields. Drought is one of the major threats for terrestrial ecosystem performance and crop production in future. Among the measures proposed to cope with the upcoming challenges of intensifying drought stress and to decrease the need for phosphorus fertilizer application is the fertilization with silica (Si). Here we tested the importance of soil Si fertilization on wheat phosphorus concentration as well as wheat performance during drought at the field scale. Our data clearly showed a higher soil moisture for the Si fertilized plots. This higher soil moisture contributes to a better plant performance in terms of higher photosynthetic activity and later senescence as well as faster stomata responses ensuring higher productivity during drought periods. The plant phosphorus concentration was also higher in Si fertilized compared to control plots. Overall, Si fertilization or management of the soil Si pools seem to be a promising tool to maintain crop production under predicted longer and more serve droughts in the future and reduces phosphorus fertilizer requirements.
Non-fullerene acceptors (NFAs) are far more emissive than their fullerene-based counterparts. Here, we study the spectral properties of photocurrent generation and recombination of the blend of the donor polymer PM6 with the NFA Y6. We find that the radiative recombination of free charges is almost entirely due to the re-occupation and decay of Y6 singlet excitons, but that this pathway contributes less than 1% to the total recombination. As such, the open-circuit voltage of the PM6:Y6 blend is determined by the energetics and kinetics of the charge-transfer (CT) state. Moreover, we find that no information on the energetics of the CT state manifold can be gained from the low-energy tail of the photovoltaic external quantum efficiency spectrum, which is dominated by the excitation spectrum of the Y6 exciton. We, finally, estimate the charge-separated state to lie only 120 meV below the Y6 singlet exciton energy, meaning that this blend indeed represents a high-efficiency system with a low energetic offset.
Identification of protein complexes from protein-protein interaction (PPI) networks is a key problem in PPI mining, solved by parameter-dependent approaches that suffer from small recall rates. Here we introduce GCC-v, a family of efficient, parameter-free algorithms to accurately predict protein complexes using the (weighted) clustering coefficient of proteins in PPI networks. Through comparative analyses with gold standards and PPI networks from Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens, we demonstrate that GCC-v outperforms twelve state-of-the-art approaches for identification of protein complexes with respect to twelve performance measures in at least 85.71% of scenarios. We also show that GCC-v results in the exact recovery of similar to 35% of protein complexes in a pan-plant PPI network and discover 144 new protein complexes in Arabidopsis thaliana, with high support from GO semantic similarity. Our results indicate that findings from GCC-v are robust to network perturbations, which has direct implications to assess the impact of the PPI network quality on the predicted protein complexes. (C) 2021 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
Deliberative and paternalistic interaction styles for conversational agents in digital health
(2021)
Background:
Recent years have witnessed a constant increase in the number of people with chronic conditions requiring ongoing medical support in their everyday lives. However, global health systems are not adequately equipped for this extraordinarily time-consuming and cost-intensive development. Here, conversational agents (CAs) can offer easily scalable and ubiquitous support. Moreover, different aspects of CAs have not yet been sufficiently investigated to fully exploit their potential. One such trait is the interaction style between patients and CAs. In human-to-human settings, the interaction style is an imperative part of the interaction between patients and physicians. Patient-physician interaction is recognized as a critical success factor for patient satisfaction, treatment adherence, and subsequent treatment outcomes. However, so far, it remains effectively unknown how different interaction styles can be implemented into CA interactions and whether these styles are recognizable by users.
Objective:
The objective of this study was to develop an approach to reproducibly induce 2 specific interaction styles into CA-patient dialogs and subsequently test and validate them in a chronic health care context.
Methods:
On the basis of the Roter Interaction Analysis System and iterative evaluations by scientific experts and medical health care professionals, we identified 10 communication components that characterize the 2 developed interaction styles: deliberative and paternalistic interaction styles. These communication components were used to develop 2 CA variations, each representing one of the 2 interaction styles. We assessed them in a web-based between-subject experiment. The participants were asked to put themselves in the position of a patient with chronic obstructive pulmonary disease. These participants were randomly assigned to interact with one of the 2 CAs and subsequently asked to identify the respective interaction style. Chi-square test was used to assess the correct identification of the CA-patient interaction style.
Results:
A total of 88 individuals (42/88, 48% female; mean age 31.5 years, SD 10.1 years) fulfilled the inclusion criteria and participated in the web-based experiment. The participants in both the paternalistic and deliberative conditions correctly identified the underlying interaction styles of the CAs in more than 80% of the assessments (X-1(,8)8(2)=38.2; P<.001; phi coefficient r(phi)=0.68). The validation of the procedure was hence successful.
Conclusions:
We developed an approach that is tailored for a medical context to induce a paternalistic and deliberative interaction style into a written interaction between a patient and a CA. We successfully tested and validated the procedure in a web-based experiment involving 88 participants. Future research should implement and test this approach among actual patients with chronic diseases and compare the results in different medical conditions. This approach can further be used as a starting point to develop dynamic CAs that adapt their interaction styles to their users.
Pathogens and animal pests (P&A) are a major threat to global food security as they directly affect the quantity and quality of food. The Southern Amazon, Brazil's largest domestic region for soybean, maize and cotton production, is particularly vulnerable to the outbreak of P&A due to its (sub)tropical climate and intensive farming systems. However, little is known about the spatial distribution of P&A and the related yield losses. Machine learning approaches for the automated recognition of plant diseases can help to overcome this research gap. The main objectives of this study are to (1) evaluate the performance of Convolutional Neural Networks (ConvNets) in classifying P&A, (2) map the spatial distribution of P&A in the Southern Amazon, and (3) quantify perceived yield and economic losses for the main soybean and maize P&A. The objectives were addressed by making use of data collected with the smartphone application Plantix. The core of the app's functioning is the automated recognition of plant diseases via ConvNets. Data on expected yield losses were gathered through a short survey included in an "expert" version of the application, which was distributed among agronomists. Between 2016 and 2020, Plantix users collected approximately 78,000 georeferenced P&A images in the Southern Amazon. The study results indicate a high performance of the trained ConvNets in classifying 420 different crop-disease combinations. Spatial distribution maps and expert-based yield loss estimates indicate that maize rust, bacterial stalk rot and the fall armyworm are among the most severe maize P&A, whereas soybean is mainly affected by P&A like anthracnose, downy mildew, frogeye leaf spot, stink bugs and brown spot. Perceived soybean and maize yield losses amount to 12 and 16%, respectively, resulting in annual yield losses of approximately 3.75 million tonnes for each crop and economic losses of US$2 billion for both crops together. The high level of accuracy of the trained ConvNets, when paired with widespread use from following a citizen-science approach, results in a data source that will shed new light on yield loss estimates, e.g., for the analysis of yield gaps and the development of measures to minimise them.
The correct orientation of seismic sensors is critical for studies such as full moment tensor inversion, receiver function analysis, and shear-wave splitting. Therefore, the orientation of horizontal components needs to be checked and verified systematically. This study relies on two different waveform-based approaches, to assess the sensor orientations of the broadband network of the Kandilli Observatory and Earthquake Research Institute (KOERI). The network is an important backbone for seismological research in the Eastern Mediterranean Region and provides a comprehensive seismic data set for the North Anatolian fault. In recent years, this region became a worldwide field laboratory for continental transform faults. A systematic survey of the sensor orientations of the entire network, as presented here, facilitates related seismic studies. We apply two independent orientation tests, based on the polarization of P waves and Rayleigh waves to 123 broadband seismic stations, covering a period of 15 yr (2004-2018). For 114 stations, we obtain stable results with both methods. Approximately, 80% of the results agree with each other within 10 degrees. Both methods indicate that about 40% of the stations are misoriented by more than 10 degrees. Among these, 20 stations are misoriented by more than 20 degrees. We observe temporal changes of sensor orientation that coincide with maintenance work or instrument replacement. We provide time-dependent sensor misorientation correction values for the KOERI network in the supplemental material.
The first detections of black hole-neutron star mergers (GW200105 and GW200115) by the LIGO-Virgo-Kagra Collaboration mark a significant scientific breakthrough. The physical interpretation of pre- and postmerger signals requires careful cross-examination between observational and theoretical modelling results. Here we present the first set of black hole-neutron star simulations that were obtained with the numerical-relativity code BAM. Our initial data are constructed using the public LORENE spectral library, which employs an excision of the black hole interior. BAM, in contrast, uses the moving-puncture gauge for the evolution. Therefore, we need to "stuff" the black hole interior with smooth initial data to evolve the binary system in time. This procedure introduces constraint violations such that the constraint damping properties of the evolution system are essential to increase the accuracy of the simulation and in particular to reduce spurious center-of-mass drifts. Within BAM we evolve the Z4c equations and we compare our gravitational-wave results with those of the SXS collaboration and results obtained with the SACRA code. While we find generally good agreement with the reference solutions and phase differences less than or similar to 0.5 rad at the moment of merger, the absence of a clean convergence order in our simulations does not allow for a proper error quantification. We finally present a set of different initial conditions to explore how the merger of black hole neutron star systems depends on the involved masses, spins, and equations of state.
Water bodies are a highly abundant feature of Arctic permafrost ecosystems and strongly influence their hydrology, ecology and biogeochemical cycling. While very high resolution satellite images enable detailed mapping of these water bodies, the increasing availability and abundance of this imagery calls for fast, reliable and automatized monitoring. This technical work presents a largely automated and scalable workflow that removes image noise, detects water bodies, removes potential misclassifications from infrastructural features, derives lake shoreline geometries and retrieves their movement rate and direction on the basis of ortho-ready very high resolution satellite imagery from Arctic permafrost lowlands. We applied this workflow to typical Arctic lake areas on the Alaska North Slope and achieved a successful and fast detection of water bodies. We derived representative values for shoreline movement rates ranging from 0.40-0.56 m yr(-1) for lake sizes of 0.10 ha-23.04 ha. The approach also gives an insight into seasonal water level changes. Based on an extensive quantification of error sources, we discuss how the results of the automated workflow can be further enhanced by incorporating additional information on weather conditions and image metadata and by improving the input database. The workflow is suitable for the seasonal to annual monitoring of lake changes on a sub-meter scale in the study areas in northern Alaska and can readily be scaled for application across larger regions within certain accuracy limitations.
This paper sheds new light on the role of communication for cartel formation. Using machine learning to evaluate free-form chat communication among firms in a laboratory experiment, we identify typical communication patterns for both explicit cartel formation and indirect attempts to collude tacitly. We document that firms are less likely to communicate explicitly about price fixing and more likely to use indirect messages when sanctioning institutions are present. This effect of sanctions on communication reinforces the direct cartel-deterring effect of sanctions as collusion is more difficult to reach and sustain without an explicit agreement. Indirect messages have no, or even a negative, effect on prices.
The leniency rule revisited
(2021)
The experimental literature on antitrust enforcement provides robust evidence that communication plays an important role for the formation and stability of cartels. We extend these studies through a design that distinguishes between innocuous communication and communication about a cartel, sanctioning only the latter. To this aim, we introduce a participant in the role of the competition authority, who is properly incentivized to judge the communication content and price setting behavior of the firms. Using this novel design, we revisit the question whether a leniency rule successfully destabilizes cartels. In contrast to existing experimental studies, we find that a leniency rule does not affect cartelization. We discuss potential explanations for this contrasting result.
COVID-19
(2021)
We investigate how the economic consequences of the pandemic and the government-mandated measures to contain its spread affect the self-employed — particularly women — in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are about one-third more likely to experience income losses than their male counterparts. We do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, e.g., the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.
Detrimental effects of adverse family conditions for children's wellbeing are well-documented, but little is known about the impact of specific risk factors, or about potential protective factors that buffer the effects of family risk factors on negative development.
We investigated the impact of five important family risk factors (e.g., parental conflict) on internalizing and externalizing problems and the potential buffering effects of peer acceptance and academic skills at two measurement points two years apart in 1195 7-to 10-year-olds (T1: M-Age = 8.54).
Latent change models showed that increases in risk factors over the two years predicted increasing internalizing and externalizing problems. Parental conflict was the most impactful risk factor, although peer acceptance and academic skills showed some buffering effects.
The results highlight the necessity of investigating cumulative and single risk factors, specifically interparental conflict, and emphasize the need to strengthen children's internal and social resources to buffer the effects of adverse family conditions.
Previous literature has shown that task-based goal-setting and distributed learning is beneficial to university-level course performance. We investigate the effects of making these insights salient to students by sending out goal-setting prompts in a blended learning environment with bi-weekly quizzes. The randomized field experiment in a large mandatory economics course shows promising results: the treated students outperform the control group. They are 18.8% (0.20 SD) more likely to pass the exam and earn 6.7% (0.19 SD) more points on the exam. While we cannot causally disentangle the effects of goal-setting from the prompt sent, we observe that treated students use the online learning platform earlier in the semester and attempt more online exercises compared to the control group. The heterogeneity analysis suggests that higher treatment effects are associated with low performance at the beginning of the course.
This study deals with the East Beni Suef Basin (Eastern Desert, Egypt) and aims to evaluate the source-generative potential, reconstruct the burial and thermal history, examine the most influential parameters on thermal maturity modeling, and improve on the models already published for the West Beni Suef to ultimately formulate a complete picture of the whole basin evolution.
Source rock evaluation was carried out based on TOC, Rock-Eval pyrolysis, and visual kerogen petrography analyses. Three kerogen types (II, II/III, and III) are distinguished in the East Beni Suef Basin, where the Abu Roash "F" Member acts as the main source rock with good to excellent source potential, oil-prone mainly type II kerogen, and immature to marginal maturity levels.
The burial history shows four depositional and erosional phases linked with the tectonic evolution of the basin. A hiatus (due to erosion or non-deposition) has occurred during the Late Eocene-Oligocene in the East Beni Suef Basin, while the West Beni Suef Basin has continued subsiding.
Sedimentation began later (Middle to Late Albian) with lower rates in the East Beni Suef Basin compared with the West Beni Suef Basin (Early Albian). The Abu Roash "F" source rock exists in the early oil window with a present-day transformation ratio of about 19% and 21% in the East and West Beni Suef Basin, respectively, while the Lower Kharita source rock, which is only recorded in the West Beni Suef Basin, has reached the late oil window with a present-day transformation ratio of about 70%.
The magnitude of erosion and heat flow have proportional and mutual effects on thermal maturity.
We present three possible scenarios of basin modeling in the East Beni Suef Basin concerning the erosion from the Apollonia and Dabaa formations.
Results of this work can serve as a basis for subsequent 2D and/or 3D basin modeling, which are highly recommended to further investigate the petroleum system evolution of the Beni Suef Basin.
The subsurface is a temporally dynamic and spatially heterogeneous compartment of the Earth's critical zone, and biogeochemical transformations taking place in this compartment are crucial for the cycling of nutrients.
The impact of spatial heterogeneity on such microbially mediated nutrient cycling is not well known, which imposes a severe challenge in the prediction of in situ biogeochemical transformation rates and further of nutrient loading contributed by the groundwater to the surface water bodies.
Therefore, we used a numerical modelling approach to evaluate the sensitivity of groundwater microbial biomass distribution and nutrient cycling to spatial heterogeneity in different scenarios accounting for various residence times.
The model results gave us an insight into domain characteristics with respect to the presence of oxic niches in predominantly anoxic zones and vice versa depending on the extent of spatial heterogeneity and the flow regime.
The obtained results show that microbial abundance, distribution, and activity are sensitive to the applied flow regime and that the mobile (i.e. observable by groundwater sampling) fraction of microbial biomass is a varying, yet only a small, fraction of the total biomass in a domain. Furthermore, spatial heterogeneity resulted in anaerobic niches in the domain and shifts in microbial biomass between active and inactive states. The lack of consideration of spatial heterogeneity, thus, can result in inaccurate estimation of microbial activity. In most cases this leads to an overestimation of nutrient removal (up to twice the actual amount) along a flow path.
We conclude that the governing factors for evaluating this are the residence time of solutes and the Damkohler number (Da) of the biogeochemical reactions in the domain. We propose a relationship to scale the impact of spatial heterogeneity on nutrient removal governed by the logioDa.
This relationship may be applied in upscaled descriptions of microbially mediated nutrient cycling dynamics in the subsurface thereby resulting in more accurate predictions of, for example, carbon and nitrogen cycling in groundwater over long periods at the catchment scale.
Epidemiological data suggest that consuming diets rich in carotenoids can reduce the risk of developing several non-communicable diseases. Thus, we investigated the extent to which carotenoid contents of foods can be increased by the choice of food matrices with naturally high carotenoid contents and thermal processing methods that maintain their stability. For this purpose, carotenoids of 15 carrot (Daucus carota L.) cultivars of different colors were assessed with UHPLC-DAD-ToF-MS. Additionally, the processing effects of air drying, air frying, and deep frying on carotenoid stability were applied. Cultivar selection accounted for up to 12.9-fold differences in total carotenoid content in differently colored carrots and a 2.2-fold difference between orange carrot cultivars. Air frying for 18 and 25 min and deep frying for 10 min led to a significant decrease in total carotenoid contents. TEAC assay of lipophilic extracts showed a correlation between carotenoid content and antioxidant capacity in untreated carrots.
Thermally stable photoswitches that are driven with low-energy light are rare, yet crucial for extending the applicability of photoresponsive molecules and materials towards, e.g., living systems. Combined ortho-fluorination and -amination couples high visible light absorptivity of o-aminoazobenzenes with the extraordinary bistability of o-fluoroazobenzenes. Herein, we report a library of easily accessible o-aminofluoroazobenzenes and establish structure-property relationships regarding spectral qualities, visible light isomerization efficiency and thermal stability of the cis-isomer with respect to the degree of o-substitution and choice of amino substituent. We rationalize the experimental results with quantum chemical calculations, revealing the nature of low-lying excited states and providing insight into thermal isomerization. The synthesized azobenzenes absorb at up to 600 nm and their thermal cis-lifetimes range from milliseconds to months. The most unique example can be driven from trans to cis with any wavelength from UV up to 595 nm, while still exhibiting a thermal cis-lifetime of 81 days. <br /> [GRAPHICS] <br /> .
Poly(ionic liquid)s (PIL) are common precursors for heteroatom-doped carbon materials. Despite a relatively higher carbonization yield, the PIL-to-carbon conversion process faces challenges in preserving morphological and structural motifs on the nanoscale. Assisted by a thin polydopamine coating route and ion exchange, imidazoliumbased PIL nanovesicles were successfully applied in morphology-maintaining carbonization to prepare carbon composite nanocapsules. Extending this strategy further to their composites, we demonstrate the synthesis of carbon composite nanocapsules functionalized with iron nitride nanoparticles of an ultrafine, uniform size of 3-5 nm (termed "FexN@C "). Due to its unique nanostructure, the sulfur-loaded FexN@C electrode was tested to efficiently mitigate the notorious shuttle effect of lithium polysulfides (LiPSs) in Li-S batteries. The cavity of the carbon nanocapsules was spotted to better the loading content of sulfur. The well-dispersed iron nitride nanoparticles effectively catalyze the conversion of LiPSs to Li2S, owing to their high electronic conductivity and strong binding power to LiPSs. Benefiting from this well-crafted composite nanostructure, the constructed FexN@C/S cathode demonstrated a fairly high discharge capacity of 1085 mAh g(-1) at 0.5 C initially, and a remaining value of 930 mAh g(-1 )after 200 cycles. In addition, it exhibits an excellent rate capability with a high initial discharge capacity of 889.8 mAh g(-1) at 2 C. This facile PIL-to-nanocarbon synthetic approach is applicable for the exquisite design of complex hybrid carbon nanostructures with potential use in electrochemical energy storage and conversion.
The study of perceptual flexibility in speech depends on a variety of tasks that feature a large degree of variability between participants. Of critical interest is whether measures are consistent within an individual or across stimulus contexts. This is particularly key for individual difference designs that are deployed to examine the neural basis or clinical consequences of perceptual flexibility. In the present set of experiments, we assess the split-half reliability and construct validity of five measures of perceptual flexibility: three of learning in a native language context (e.g., understanding someone with a foreign accent) and two of learning in a non-native context (e.g., learning to categorize non-native speech sounds). We find that most of these tasks show an appreciable level of split-half reliability, although construct validity was sometimes weak. This provides good evidence for reliability for these tasks, while highlighting possible upper limits on expected effect sizes involving each measure.
Changing climatic conditions and unsustainable land use are major threats to savannas worldwide. Historically, many African savannas were used intensively for livestock grazing, which contributed to widespread patterns of bush encroachment across savanna systems. To reverse bush encroachment, it has been proposed to change the cattle-dominated land use to one dominated by comparatively specialized browsers and usually native herbivores. However, the consequences for ecosystem properties and processes remain largely unclear. We used the ecohydrological, spatially explicit model EcoHyD to assess the impacts of two contrasting, herbivore land-use strategies on a Namibian savanna: grazer- versus browser-dominated herbivore communities. We varied the densities of grazers and browsers and determined the resulting composition and diversity of the plant community, total vegetation cover, soil moisture, and water use by plants. Our results showed that plant types that are less palatable to herbivores were best adapted to grazing or browsing animals in all simulated densities. Also, plant types that had a competitive advantage under limited water availability were among the dominant ones irrespective of land-use scenario. Overall, the results were in line with our expectations: under high grazer densities, we found heavy bush encroachment and the loss of the perennial grass matrix. Importantly, regardless of the density of browsers, grass cover and plant functional diversity were significantly higher in browsing scenarios. Browsing herbivores increased grass cover, and the higher total cover in turn improved water uptake by plants overall. We concluded that, in contrast to grazing-dominated land-use strategies, land-use strategies dominated by browsing herbivores, even at high herbivore densities, sustain diverse vegetation communities with high cover of perennial grasses, resulting in lower erosion risk and bolstering ecosystem services.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
ABSTRACT: Structural evolution of cesium triiodide at high pressures has been revealed by synchrotron single-crystal X-ray diffraction. Cesium triiodide undergoes a first-order phase transition above 1.24(3) GPa from an orthorhombic to a trigonal system. This transition is coupled with severe reorganization of the polyiodide network from a layered to three-dimensional architecture. Quantum chemical calculations show that even though the two polymorphic phases are nearly isoenergetic under ambient conditions, the PV term is decisive in stabilizing the trigonal polymorph above the transition point. Phonon calculations using a non-local correlation functional that accounts for dispersion interactions confirm that this polymorph is dynamically unstable under ambient conditions. The high-pressure behavior of crystalline CsI3 can be correlated with other alkali metal trihalides, which undergo a similar sequence of structural changes upon load.
The intensity of cosmic radiation may differ over five orders of magnitude within a few hours or days during the Solar Particle Events (SPEs), thus increasing for several orders of magnitude the probability of Single Event Upsets (SEUs) in space-borne electronic systems. Therefore, it is vital to enable the early detection of the SEU rate changes in order to ensure timely activation of dynamic radiation hardening measures. In this paper, an embedded approach for the prediction of SPEs and SRAM SEU rate is presented. The proposed solution combines the real-time SRAM-based SEU monitor, the offline-trained machine learning model and online learning algorithm for the prediction. With respect to the state-of-the-art, our solution brings the following benefits: (1) Use of existing on-chip data storage SRAM as a particle detector, thus minimizing the hardware and power overhead, (2) Prediction of SRAM SEU rate one hour in advance, with the fine-grained hourly tracking of SEU variations during SPEs as well as under normal conditions, (3) Online optimization of the prediction model for enhancing the prediction accuracy during run-time, (4) Negligible cost of hardware accelerator design for the implementation of selected machine learning model and online learning algorithm. The proposed design is intended for a highly dependable and self-adaptive multiprocessing system employed in space applications, allowing to trigger the radiation mitigation mechanisms before the onset of high radiation levels.
Studies have evaluated the effectiveness of dual career (DC) support services among student-athletes by examining scholastic performances.
These studies investigated self-reported grades student-athletes or focused on career choices student-athletes made after leaving school. Most of these studies examined scholastic performances cross-sectionally among lower secondary school student-athletes or student-athletes in higher education.
The present longitudinal field study in a quasi-experimental design aims to evaluate the development of scholastic performances among upper secondary school students aged 16-19 by using standardized scholastic assessments and grade points in the subject English over a course of 3-4 years.
A sample of 159 students (54.4% females) at three German Elite Sport Schools (ESS) and three comprehensive schools participated in the study. The sample was split into six groups according to three criteria: (1) students' athletic engagement, (2) school type attendance, and (3) usage of DC support services in secondary school.
Repeated-measurement analyses of variance were conducted in order to evaluate the impact of the three previously mentioned criteria as well as their interaction on the development of scholastic performances.
Findings indicated that the development of English performance levels differ among the six groups.
Current attempts to prevent and manage type 2 diabetes have been moderately effective, and a better understanding of the molecular roots of this complex disease is important to develop more successful and precise treatment options.
Recently, we initiated the collective diabetes cross, where four mouse inbred strains differing in their diabetes susceptibility were crossed with the obese and diabetes-prone NZO strain and identified the quantitative trait loci (QTL) Nidd13/NZO, a genomic region on chromosome 13 that correlates with hyperglycemia in NZO allele carriers compared to B6 controls.
Subsequent analysis of the critical region, harboring 644 genes, included expression studies in pancreatic islets of congenic Nidd13/NZO mice, integration of single-cell data from parental NZO and B6 islets as well as haplotype analysis.
Finally, of the five genes (Acot12, S100z, Ankrd55, Rnf180, and Iqgap2) within the polymorphic haplotype block that are differently expressed in islets of B6 compared to NZO mice, we identified the calcium-binding protein S100z gene to affect islet cell proliferation as well as apoptosis when overexpressed in MINE cells. In summary, we define S100z as the most striking gene to be causal for the diabetes QTL Nidd13/NZO by affecting beta-cell proliferation and apoptosis. Thus, S100z is an entirely novel diabetes gene regulating islet cell function.
Model uncertainty quantification is an essential component of effective data assimilation. Model errors associated with sub-grid scale processes are often represented through stochastic parameterizations of the unresolved process. Many existing Stochastic Parameterization schemes are only applicable when knowledge of the true sub-grid scale process or full observations of the coarse scale process are available, which is typically not the case in real applications. We present a methodology for estimating the statistics of sub-grid scale processes for the more realistic case that only partial observations of the coarse scale process are available. Model error realizations are estimated over a training period by minimizing their conditional sum of squared deviations given some informative covariates (e.g., state of the system), constrained by available observations and assuming that the observation errors are smaller than the model errors. From these realizations a conditional probability distribution of additive model errors given these covariates is obtained, allowing for complex non-Gaussian error structures. Random draws from this density are then used in actual ensemble data assimilation experiments. We demonstrate the efficacy of the approach through numerical experiments with the multi-scale Lorenz 96 system using both small and large time scale separations between slow (coarse scale) and fast (fine scale) variables. The resulting error estimates and forecasts obtained with this new method are superior to those from two existing methods.
The nature of the sources powering nebular He II emission in star-forming galaxies remains debated, and various types of objects have been considered, including Wolf-Rayet stars, X-ray binaries, and Population III stars.
Modern X-ray observations show the ubiquitous presence of hot gas filling star-forming galaxies. We use a collisional ionization plasma code to compute the specific He II ionizing flux produced by hot gas and show that if its temperature is not too high (less than or similar to 2.5 MK), then the observed levels of soft diffuse X-ray radiation could explain He II ionization in galaxies.
To gain a physical understanding of this result, we propose a model that combines the hydrodynamics of cluster winds and hot superbubbles with observed populations of young massive clusters in galaxies. We find that in low-metallicity galaxies, the temperature of hot gas is lower and the production rate of He II ionizing photons is higher compared to high-metallicity galaxies. The reason is that the slower stellar winds of massive stars in lower-metallicity galaxies input less mechanical energy in the ambient medium.
Furthermore, we show that ensembles of star clusters up to similar to 10-20 Myr old in galaxies can produce enough soft X-rays to induce nebular He II emission. We discuss observations of the template low-metallicity galaxy I Zw 18 and suggest that the He II nebula in this galaxy is powered by a hot superbubble.
Finally, appreciating the complex nature of stellar feedback, we suggest that soft X-rays from hot superbubbles are among the dominant sources of He II ionizing flux in low-metallicity star-forming galaxies.
It has been highlighted many times how difficult it is to draw a boundary between gift and bribe, and how the same transfer can be interpreted in different ways according to the position of the observer and the narrative frame into which it is inserted. This also applied of course to Ancient Rome; in both the Republic and Principate lawgivers tried to define the limits of acceptable transfers and thus also to identify what we might call ‘corruption’. Yet, such definitions remained to a large extent blurred, and what was constructed was mostly a ‘code of conduct’, allowing Roman politicians to perform their own ‘honesty’ in public duty – while being aware at all times that their involvement in different kinds of transfer might be used by their opponents against them and presented as a case of ‘corrupt’ behaviour.
Widespread on social networking sites (SNSs), envy has been linked to an array of detrimental outcomes for users’ well-being. While envy has been considered a status-related emotion and is likely to be experienced in response to perceiving another’s higher status, there is a lack of research exploring how status perceptions influence the emergence of envy on SNSs. This is important because SNSs typically quantify social interactions and reach with metrics that indicate users’ relative rank and status in the network. To understand how status perceptions impact SNS users, we introduce a new form of metric-based digital status rooted in SNS metrics that are available and visible on a platform. Drawing on social comparison theory and status literature, we conducted an online experiment to investigate how different forms of status contribute to the proliferation of envy on SNSs. Our findings shed light on how metric-based digital status influences feelings of envy on SNSs. Specifically, we could show that metric-based digital status impacts envy through increasing perceptions of others’ socioeconomic and sociometric statuses. Our study contributes to the growing discourse on the negative outcomes associated with SNS use and its consequences for users and society.
Who has the future in mind?
(2022)
An individual's relation to time may be an important driver of pro-environmental behaviour. We studied whether young individual's gender and time-orientation are associated with pro-environmental behaviour. In a controlled laboratory environment with students in Germany, participants earned money by performing a real-effort task and were then offered the opportunity to invest their money into an environmental project that supports climate protection. Afterwards, we controlled for their time-orientation. In this consequential behavioural setting, we find that males who scored higher on future-negative orientation showed significantly more pro-environmental behaviour compared to females who scored higher on future-negative orientation and males who scored lower on future-negative orientation. Interestingly, our results are completely reversed when it comes to past-positive orientation. These findings have practical implications regarding the most appropriate way to address individuals in order to achieve more pro-environmental behaviour.
This paper studies how individuals discount the utility they derive from their provision of goods over spatial distance. In a controlled laboratory experiment in Germany, we elicit preferences for the provision of the same good at different locations. To isolate spatial preferences from any other direct value of the goods being close to the individual, we focus on goods with “existence value.” We find that individuals put special weight on the provision of these goods in their immediate vicinity. This “vicinity bias” represents a spatial analogy to the “present bias” in the time dimension.
Enhancing economic efficiency in modular production systems through deep reinforcement learning
(2024)
In times of increasingly complex production processes and volatile customer demands, the production adaptability is crucial for a company's profitability and competitiveness. The ability to cope with rapidly changing customer requirements and unexpected internal and external events guarantees robust and efficient production processes, requiring a dedicated control concept at the shop floor level. Yet in today's practice, conventional control approaches remain in use, which may not keep up with the dynamic behaviour due to their scenario-specific and rigid properties. To address this challenge, deep learning methods were increasingly deployed due to their optimization and scalability properties. However, these approaches were often tested in specific operational applications and focused on technical performance indicators such as order tardiness or total throughput. In this paper, we propose a deep reinforcement learning based production control to optimize combined techno-financial performance measures. Based on pre-defined manufacturing modules that are supplied and operated by multiple agents, positive effects were observed in terms of increased revenue and reduced penalties due to lower throughput times and fewer delayed products. The combined modular and multi-staged approach as well as the distributed decision-making further leverage scalability and transferability to other scenarios.
Shape-memory hydrogels (SMH) are multifunctional, actively-moving polymers of interest in biomedicine. In loosely crosslinked polymer networks, gelatin chains may form triple helices, which can act as temporary net points in SMH, depending on the presence of salts. Here, we show programming and initiation of the shape-memory effect of such networks based on a thermomechanical process compatible with the physiological environment. The SMH were synthesized by reaction of glycidylmethacrylated gelatin with oligo(ethylene glycol) (OEG) alpha,omega-dithiols of varying crosslinker length and amount. Triple helicalization of gelatin chains is shown directly by wide-angle X-ray scattering and indirectly via the mechanical behavior at different temperatures. The ability to form triple helices increased with the molar mass of the crosslinker. Hydrogels had storage moduli of 0.27-23 kPa and Young's moduli of 215-360 kPa at 4 degrees C. The hydrogels were hydrolytically degradable, with full degradation to water-soluble products within one week at 37 degrees C and pH = 7.4. A thermally-induced shape-memory effect is demonstrated in bending as well as in compression tests, in which shape recovery with excellent shape-recovery rates R-r close to 100% were observed. In the future, the material presented here could be applied, e.g., as self-anchoring devices mechanically resembling the extracellular matrix.
Starting from the observation that the reduced state of a system strongly coupled to a bath is, in general, an athermal state, we introduce and study a cyclic battery-charger quantum device that is in thermal equilibrium, or in a ground state, during the charge storing stage. The cycle has four stages: the equilibrium storage stage is interrupted by disconnecting the battery from the charger, then work is extracted from the battery, and then the battery is reconnected with the charger; finally, the system is brought back to equilibrium. At no point during the cycle are the battery-charger correlations artificially erased. We study the case where the battery and charger together comprise a spin-1/2 Ising chain, and show that the main characteristics-the extracted energy and the thermodynamic efficiency-can be enhanced by operating the cycle close to the quantum phase transition point. When the battery is just a single spin, we find that the output work and efficiency show a scaling behavior at criticality and derive the corresponding critical exponents. Due to always present correlations between the battery and the charger, operations that are equivalent from the perspective of the battery can entail different energetic costs for switching the battery-charger coupling. This happens only when the coupling term does not commute with the battery's bare Hamiltonian, and we use this purely quantum leverage to further optimize the performance of the device.
Charitable giving
(2023)
We investigate how different levels of information influence the allocation decisions of donors who are entitled to freely distribute a fixed monetary endowment between themselves and a charitable organization in both giving and taking frames. Participants donate significantly higher amounts, when the decision is described as taking rather than giving. This framing effect becomes smaller if more information about the charity is provided.
The influence of the process gas, laser scan speed, and sample thickness on the build-up of residual stresses and porosity in Ti-6Al-4V produced by laser powder bed fusion was studied. Pure argon and helium, as well as a mixture of those (30% helium), were employed to establish process atmospheres with a low residual oxygen content of 100 ppm O-2. The results highlight that the subsurface residual stresses measured by X-ray diffraction were significantly lower in the thin samples (220 MPa) than in the cuboid samples (645 MPa). This difference was attributed to the shorter laser vector length, resulting in heat accumulation and thus in-situ stress relief. The addition of helium to the process gas did not introduce additional subsurface residual stresses in the simple geometries, even for the increased scanning speed. Finally, larger deflection was found in the cantilever built under helium (after removal from the baseplate), than in those produced under argon and an argon-helium mixture. This result demonstrates that complex designs involving large scanned areas could be subjected to higher residual stress when manufactured under helium due to the gas's high thermal conductivity, heat capacity, and thermal diffusivity.
In control theory, to solve a finite-horizon sequential decision problem (SDP) commonly means to find a list of decision rules that result in an optimal expected total reward (or cost) when taking a given number of decision steps. SDPs are routinely solved using Bellman's backward induction. Textbook authors (e.g. Bertsekas or Puterman) typically give more or less formal proofs to show that the backward induction algorithm is correct as solution method for deterministic and stochastic SDPs. Botta, Jansson and Ionescu propose a generic framework for finite horizon, monadic SDPs together with a monadic version of backward induction for solving such SDPs. In monadic SDPs, the monad captures a generic notion of uncertainty, while a generic measure function aggregates rewards. In the present paper, we define a notion of correctness for monadic SDPs and identify three conditions that allow us to prove a correctness result for monadic backward induction that is comparable to textbook correctness proofs for ordinary backward induction. The conditions that we impose are fairly general and can be cast in category-theoretical terms using the notion of Eilenberg-Moore algebra. They hold in familiar settings like those of deterministic or stochastic SDPs, but we also give examples in which they fail. Our results show that backward induction can safely be employed for a broader class of SDPs than usually treated in textbooks. However, they also rule out certain instances that were considered admissible in the context of Botta et al. 's generic framework. Our development is formalised in Idris as an extension of the Botta et al. framework and the sources are available as supplementary material.
Scaling agriculture to the globally rising population demands new approaches for future crop production such as multilayer and multitrophic indoor farming. Moreover, there is a current trend towards sustainable local solutions for aquaculture and saline agriculture. In this context, halophytes are becoming increasingly important for research and the food industry. As Salicornia europaea is a highly salt-tolerant obligate halophyte that can be used as a food crop, indoor cultivation with saline water is of particular interest. Therefore, finding a sustainable alternative to the use of seawater in non-coastal regions is crucial. Our goal was to determine whether natural brines, which are widely distributed and often available in inland areas, provide an alternative water source for the cultivation of saline organisms. This case study investigated the potential use of natural brines for the production of S. europaea. In the control group, which reflects the optimal growth conditions, fresh weight was increased, but there was no significant difference between the treatment groups comparing natural brines with artificial sea water. A similar pattern was observed for carotenoids and chlorophylls. Individual components showed significant differences. However, within treatments, there were mostly no changes. In summary, we showed that the influence of the different chloride concentrations was higher than the salt composition. Moreover, nutrient-enriched natural brine was demonstrated to be a suitable alternative for cultivation of S. europaea in terms of yield and nutritional quality. Thus, the present study provides the first evidence for the future potential of natural brine waters for the further development of aquaculture systems and saline agriculture in inland regions.
Sarcopenic obesity is increasingly found in youth, but its health consequences remain unclear.
Therefore, we studied the prevalence of sarcopenia and its association with cardiometabolic risk factors as well as muscular and cardiorespiratory fitness using data from the German Children's Health InterventionaL Trial (CHILT III) programme.
In addition to anthropometric data and blood pressure, muscle and fat mass were determined with bioelectrical impedance analysis.
Sarcopenia was classified via muscle-to-fat ratio. A fasting blood sample was taken, muscular fitness was determined using the standing long jump, and cardiorespiratory fitness was determined using bicycle ergometry. Of the 119 obese participants included in the analysis (47.1% female, mean age 12.2 years), 83 (69.7%) had sarcopenia. Affected individuals had higher gamma-glutamyl transferase, higher glutamate pyruvate transaminase, higher high-sensitivity C-reactive protein, higher diastolic blood pressure, and lower muscular and cardiorespiratory fitness (each p < 0.05) compared to participants who were 'only' obese.
No differences were found in other parameters. In our study, sarcopenic obesity was associated with various disorders in children and adolescents.
However, the clinical value must be tested with larger samples and reference populations to develop a unique definition and appropriate methods in terms of identification but also related preventive or therapeutic approaches.
Forest microclimate can buffer biotic responses to summer heat waves, which are expected to become more extreme under climate warming. Prediction of forest microclimate is limited because meteorological observation standards seldom include situations inside forests.
We use eXtreme Gradient Boosting - a Machine Learning technique - to predict the microclimate of forest sites in Brandenburg, Germany, using seasonal data comprising weather features.
The analysis was amended by applying a SHapley Additive explanation to show the interaction effect of variables and individualised feature attributions.
We evaluate model performance in comparison to artificial neural networks, random forest, support vector machine, and multi-linear regression.
After implementing a feature selection, an ensemble approach was applied to combine individual models for each forest and improve robustness over a given single prediction model.
The resulting model can be applied to translate climate change scenarios into temperatures inside forests to assess temperature-related ecosystem services provided by forests.
Insights in electrosynthesis, target binding, and stability of peptide-imprinted polymer nanofilms
(2021)
Molecularly imprinted polymer (MIP) nanofilms have been successfully implemented for the recognition of different target molecules: however, the underlying mechanistic details remained vague.
This paper provides new insights in the preparation and binding mechanism of electrosynthesized peptide-imprinted polymer nanofilms for selective recognition of the terminal pentapeptides of the beta-chains of human adult hemoglobin, HbA, and its glycated form HbA1c.
To differentiate between peptides differing solely in a glucose adduct MIP nanofilms were prepared by a two-step hierarchical electrosynthesis that involves first the chemisorption of a cysteinyl derivative of the pentapeptide followed by electropolymerization of scopoletin.
This approach was compared with a random single-step electrosynthesis using scopo-letin/pentapeptide mixtures. Electrochemical monitoring of the peptide binding to the MIP nanofilms by means of redox probe gating revealed a superior affinity of the hierarchical approach with a Kd value of 64.6 nM towards the related target.
Changes in the electrosynthesized non-imprinted polymer and MIP nanofilms during chemical, electrochemical template removal and rebinding were substantiated in situ by monitoring the characteristic bands of both target peptides and polymer with surface enhanced infrared absorption spectroscopy.
This rational approach led to MIPs with excellent selectivity and provided key mechanistic insights with respect to electrosynthesis, rebinding and stability of the formed MIPs.
Enhanced charge selectivity via anodic-C60 layer reduces nonradiative losses in organic solar cells
(2021)
Interfacial layers in conjunction with suitable charge-transport layers can significantly improve the performance of optoelectronic devices by facilitating efficient charge carrier injection and extraction.
This work uses a neat C-60 interlayer on the anode to experimentally reveal that surface recombination is a significant contributor to nonradiative recombination losses in organic solar cells.
These losses are shown to proportionally increase with the extent of contact between donor molecules in the photoactive layer and a molybdenum oxide (MoO3) hole extraction layer, proven by calculating voltage losses in low- and high-donor-content bulk heterojunction device architectures.
Using a novel in-device determination of the built-in voltage, the suppression of surface recombination, due to the insertion of a thin anodic-C-60 interlayer on MoO3, is attributed to an enhanced built-in potential.
The increased built-in voltage reduces the presence of minority charge carriers at the electrodes-a new perspective on the principle of selective charge extraction layers.
The benefit to device efficiency is limited by a critical interlayer thickness, which depends on the donor material in bilayer devices.
Given the high popularity of MoO3 as an efficient hole extraction and injection layer and the increasingly popular discussion on interfacial phenomena in organic optoelectronic devices, these findings are relevant to and address different branches of organic electronics, providing insights for future device design.