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Analysis of electrochemical and liver microsomal transformation products of lasalocid by LC/HRMS
(2022)
Rationale:
Lasalocid (LAS), an ionophore, is used in cattle and poultry farming as feed additive for its antibiotic and growth-promoting properties. Literature on transformation products (TP) resulting from LAS degradation is limited. So far, only hydroxylation is found to occur as the metabolic reaction during the LAS degradation. To investigate potential TPs of LAS, we used electrochemistry (EC) and liver microsome (LM) assays to synthesize TPs, which were identified using liquid chromatography high-resolution mass spectrometry (LC/HRMS).
Methods:
Electrochemically produced TPs were analyzed online by direct coupling of the electrochemical cell to the electrospray ionization (ESI) source of a Sciex Triple-TOF high resolution mass spectrometer. Then, EC-treated LAS solution was collected and analyzed offline using LC/HRMS to confirm stable TPs and improve their annotation with a chemical structure due to informative MS/MS spectra. In a complementary approach, TPs formed by rat and human microsomal incubation were investigated using LC/HRMS. The resulting data were used to investigate LAS modification reactions and elucidate the chemical structure of obtained TPs.
Results:
The online measurements identified a broad variety of TPs, resulting from modification reactions like (de-)hydrogenation, hydration, methylation, oxidation as well as adduct formation with methanol. We consistently observed different ion complexations of LAS and LAS-TPs (Na+; 2Na(+) K+; NaNH4+; KNH4+). Two stable methylated EC-TPs were found, structurally annotated, and assigned to a likely modification reaction. Using LM incubation, seven TPs were formed, mostly by oxidation/hydroxylation. After the identification of LM-TPs as Na+-complexes, we identified LM-TPs as K+-complexes.
Conclusion:
We identified and characterized TPs of LAS using EC- and LM-based methods. Moreover, we found different ion complexes of LAS-based TPs. This knowledge, especially the different ion complexes, may help elucidate the metabolic and environmental degradation pathways of LAS.
This paper presents an exploratory study investigating the influence of the factors (1) intermediary participation, (2) decision-making authority, (3) position in the enterprise, and (4) experience in open innovation on the perception and assessment of the benefits and risks expected from participating in open innovation projects. For this purpose, an online survey was conducted in Germany, Austria and Switzerland. The result of this paper is an empirical evidence showing whether and how these factors affect the perception of potential benefits and risks expected within the context of open innovation project participation. Furthermore, the identified effects are discussed against the theory. Existing theory regarding the benefits and risks of open innovation is expanded by (1) finding that they are perceived mostly independently of the factors, (2) confirming the practical relevance of benefits and risks, and (3) enabling a finer distinction between their degrees of relevance according to respective contextual specifics.
Public sector organizations at all levels of government increasingly rely on Big Data Algorithmic Systems (BDAS) to support decision-making along the entire policy cycle. But while our knowledge on the use of big data continues to grow for government agencies implementing and delivering public services, empirical research on applications for anticipatory policy design is still in its infancy. Based on the concept of policy analytical capacity (PAC), this case study examines the application of BDAS for early crisis detection within the German Federal Government—that is, the German Federal Foreign Office (FFO) and the Federal Ministry of Defence (FMoD). It uses the nested model of PAC to reflect on systemic, organizational, and individual capacity-building from a neoinstitutional perspective and allow for the consideration of embedded institutional contexts. Results from semi-structured interviews indicate that governments seeking to exploit BDAS in policymaking depend on their institutional environment (e.g., through research and data governance infrastructure). However, specific capacity-building strategies may differ according to the departments' institutional framework, with the FMoD relying heavily on subordinate agencies and the FFO creating network-like structures with external researchers. Government capacity-building at the individual and organizational level is similarly affected by long-established institutional structures, roles, and practices within the organization and beyond, making it important to analyze these three levels simultaneously instead of separately.
Tissue reconstruction has an unmet need for soft active scaffolds that enable gentle loading with regeneration-directing bioactive components by soaking up but also provide macroscopic dimensional stability. Here microporous hydrogels capable of an inverse shape-memory effect (iSME) are described, which in contrast to classical shape-memory polymers (SMPs) recover their permanent shape upon cooling. These hydrogels are designed as covalently photo cross-linked polymer networks with oligo(ethylene glycol)-oligo(propylene glycol)-oligo(ethylene glycol) (OEG-OPG-OEG) segments. When heated after deformation, the OEG-OPG-OEG segments form micelles fixing the temporary shape. Upon cooling, the micelles dissociate again, the deformation is reversed and the permanent shape is obtained. Applicability of this iSME is demonstrated by the gentle loading of platelet-rich plasma (PRP) without causing any platelet activation during this process. PRP is highly bioactive and is widely acknowledged for its regenerative effects. Hence, the microporous inverse shape-memory hydrogel (iSMH) with a cooling induced pore-size effect represents a promising candidate scaffold for tissue regeneration for potential usage in minimally invasive surgery applications.
The addition of nano-Al2O3 has been shown to enhance the breakdown voltage of epoxy resin, but its flashover results appeared with disputation. This work concentrates on the surface charge variation and dc flashover performance of epoxy resin with nano-Al2O3 doping. The dispersion of nano-Al2O3 in epoxy is characterized by scanning electron microscopy (SEM) and atomic force microscopy (AFM). The dc flashover voltages of samples under either positive or negative polarity are measured with a finger-electrode system, and the surface charge variations before and after flashovers were identified from the surface potential mapping. The results evidence that nano-Al2O3 would lead to a 16.9% voltage drop for the negative flashovers and a 6.8% drop for positive cases. It is found that one-time flashover clears most of the accumulated surface charges, regardless of positive or negative. As a result, the ground electrode is neighbored by an equipotential zone enclosed with low-density heterocharges. The equipotential zone tends to be broadened after 20 flashovers. The nano-Al2O3 is noticed as beneficial to downsize the equipotential zone due to its capability on charge migration, which is reasonable to maintain flashover voltage at a high level after multiple flashovers. Hence, nano-Al2O3 plays a significant role in improving epoxy with high resistance to multiple flashovers.
The Ca Mau peninsula (CMP) is a key economic region in southern Vietnam. In recent decades, the high demand for water has increased the exploitation of groundwater, thus lowering the groundwater level and leading to risks of degradation, depletion, and land subsidence, as well as salinity intrusion in the groundwater of the whole Mekong Delta region. By using a finite element groundwater model with boundary expansion to the sea, we updated the latest data on hydrogeological profiles, groundwater levels, and exploitation. The basic model setup covers seven aquifers and seven aquitards. It is determined that the inflow along the coastline to the mainland is 39% of the total inflow. The exploitation of the study area in 2019 was 567,364 m(3)/day. The most exploited aquifers are the upper-middle Pleistocene (qp(2-3)) and the middle Pliocene (n(2)(2)), accounting for 63.7% and 24.6%, respectively; the least exploited aquifers are the upper Pleistocene and the upper Miocene, accounting for 0.35% and 0.02%, respectively. In the deeper aquifers, qp(2-3) and n(2)(2), the change in storage is negative due to the high exploitation rate, leading to a decline in the reserves of these aquifers. These groundwater model results are the calculations of groundwater reserves from the coast to the mainland in the entire system of aquifers in the CMP. This makes groundwater decision managers, stakeholders, and others more efficient in sustainable water resources planning in the CMP and Mekong Delta (MKD).
An explicit Dobrushin uniqueness region for Gibbs point processes with repulsive interactions
(2022)
We present a uniqueness result for Gibbs point processes with interactions that come from a non-negative pair potential; in particular, we provide an explicit uniqueness region in terms of activity z and inverse temperature beta. The technique used relies on applying to the continuous setting the classical Dobrushin criterion. We also present a comparison to the two other uniqueness methods of cluster expansion and disagreement percolation, which can also be applied for this type of interaction.
Background
Eating in absence of hunger is quite common and often associated with an increased energy intake co-existent with a poorer food choice. Intuitive eating (IE), i.e., eating in accordance with internal hunger and satiety cues, may protect from overeating. IE, however, requires accurate perception and processing of one’s own bodily signals, also referred to as interoceptive sensitivity. Training interoceptive sensitivity might therefore be an effective method to promote IE and prevent overeating. As most studies on eating behavior are conducted in younger adults and close social relationships influence health-related behavior, this study focuses on middle-aged and older couples.
Methods
The present pilot randomized intervention study aims at investigating the feasibility and effectiveness of a 21-day mindfulness-based training program designed to increase interoceptive sensitivity. A total of N = 60 couples participating in the NutriAct Family Study, aged 50–80 years, will be recruited. This randomized-controlled intervention study comprises three measurement points (pre-intervention, post-intervention, 4-week follow-up) and a 21-day training that consists of daily mindfulness-based guided audio exercises (e.g., body scan). A three-arm intervention study design is applied to compare two intervention groups (training together as a couple vs. training alone) with a control group (no training). Each measurement point includes the assessment of self-reported and objective indicators of interoceptive sensitivity (primary outcome), self-reported indicators of intuitive and maladaptive eating (secondary outcomes), and additional variables. A training evaluation applying focus group discussions will be conducted to assess participants’ overall acceptance of the training and its feasibility.
Discussion
By investigating the feasibility and effectiveness of a mindfulness-based training program to increase interoceptive sensitivity, the present study will contribute to a deeper understanding of how to promote healthy eating in older age.
In order to achieve their business goals, organizations heavily rely on the operational excellence of their business processes. In traditional scenarios, business processes are usually well-structured, clearly specifying when and how certain tasks have to be executed. Flexible and knowledge-intensive processes are gathering momentum, where a knowledge worker drives the execution of a process case and determines the exact process path at runtime. In the case of an exception, the knowledge worker decides on an appropriate handling. While there is initial work on exception handling in well-structured business processes, exceptions in case management have not been sufficiently researched. This paper proposes an exception handling framework for stage-oriented case management languages, namely Guard Stage Milestone Model, Case Management Model and Notation, and Fragment-based Case Management. The effectiveness of the framework is evaluated with two real-world use cases showing that it covers all relevant exceptions and proposed handling strategies.
Individuals who score high in self-reported Intolerance of Uncertainty (IU) tend to find uncertainty aversive. Prior research has demonstrated that under uncertainty individuals with high IU display difficulties in updating learned threat associations to safety associations. Importantly, recent research has shown that providing contingency instructions about threat and safety contingencies (i.e. reducing uncertainty) to individuals with high IU promotes the updating of learned threat associations to safety associations. Here we aimed to conceptually replicate IU and contingency instruction-based effects by conducting a secondary analysis of self-reported IU, ratings, skin conductance, and functional magnetic resonance imaging (fMRI) data recorded during uninstructed/instructed blocks of threat acquisition and threat extinction training (n = 48). Generally, no significant associations were observed between self-reported IU and differential responding to learned threat and safety cues for any measure during uninstructed/instructed blocks of threat acquisition and threat extinction training. There was some tentative evidence that higher IU was associated with greater ratings of unpleasantness and arousal to the safety cue after the experiment and greater skin conductance response to the safety cue during extinction generally. Potential explanations for these null effects and directions for future research are discussed.
We develop an encounter-based approach for describing restricted diffusion with a gradient drift toward a partially reactive boundary. For this purpose, we introduce an extension of the Dirichlet-to-Neumann operator and use its eigenbasis to derive a spectral decomposition for the full propagator, i.e. the joint probability density function for the particle position and its boundary local time. This is the central quantity that determines various characteristics of diffusion-influenced reactions such as conventional propagators, survival probability, first-passage time distribution, boundary local time distribution, and reaction rate. As an illustration, we investigate the impact of a constant drift onto the boundary local time for restricted diffusion on an interval. More generally, this approach accesses how external forces may influence the statistics of encounters of a diffusing particle with the reactive boundary.
In this study, we present an empirical model of the equatorial electron pitch angle distributions (PADs) in the outer radiation belt based on the full data set collected by the Magnetic Electron Ion Spectrometer (MagEIS) instrument onboard the Van Allen Probes in 2012-2019. The PADs are fitted with a combination of the first, third and fifth sine harmonics. The resulting equation resolves all PAD types found in the outer radiation belt (pancake, flat-top, butterfly and cap PADs) and can be analytically integrated to derive omnidirectional flux. We introduce a two-step modeling procedure that for the first time ensures a continuous dependence on L, magnetic local time and activity, parametrized by the solar wind dynamic pressure. We propose two methods to reconstruct equatorial electron flux using the model. The first approach requires two uni-directional flux observations and is applicable to low-PA data. The second method can be used to reconstruct the full equatorial PADs from a single uni- or omnidirectional measurement at off-equatorial latitudes. The model can be used for converting the long-term data sets of electron fluxes to phase space density in terms of adiabatic invariants, for physics-based modeling in the form of boundary conditions, and for data assimilation purposes.
Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large-scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large-scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana. We demonstrate the accuracy of RDT through a comparative analysis with atom mappings from a large database of biochemical reactions, MetaCyc. We further show the utility of our automated workflow by simulating N-15 isotope enrichment and identifying nitrogen (N)-containing metabolites which show enrichment patterns that are informative for flux estimation in future N-15-MFA studies of A. thaliana. The automated workflow established in this study can be readily expanded to other species for which metabolic models have been established and the resulting atom mappings will facilitate MFA and graph-theoretic structural analyses with large-scale metabolic networks.
Measuring the variability of incoming neutrons locally would be usefull for the cosmic-ray neutron sensing (CRNS) method. As the measurement of high energy neutrons is not so easy, alternative particles can be considered for such purpose. Among them, muons are particles created from the same cascade of primary cosmic-ray fluxes that generate neutrons at the ground. In addition, they can be easily detected by small and relatively inexpensive detectors. For these reasons they could provide a suitable local alternative to incoming corrections based on remote neutron monitor data. The reported measurements demonstrated that muon detection system can detect incoming cosmic-ray variations locally. Furthermore the precision of this measurement technique is considered adequate for many CRNS applications.
In this paper, we employ an experimental paradigm using insights from the psychology of reasoning to investigate the question whether certain modals generate and draw attention to alternatives. The article extends and builds on the methodology and findings of Mascarenhas & Picat (2019). Based on experimental results, they argue that the English epistemic modal might raises alternatives. We apply the same methodology to the English modal allowed to to test different hypotheses regarding the involvement of alternatives in deontic modality. We find commonalities and differences between the two modals we tested. We discuss theoretical consequences for existing semantic analyses of these modals, and argue that reasoning tasks can serve as a diagnostic tool to discover which natural language expressions involve alternatives.
Patterns of space use are often subject to large temporal and individual-level variation, due to seasonality in behaviour and environmental conditions as well as age- or sex-specific needs. Especially in temperate regions, seasonality likely influences space use even in non-migratory birds. In waterfowl of the family Anatidae, however, few studies have analyzed space use of the same individuals across the full annual cycle. We used a resident population of Mandarin Ducks (Aix galericulata) in northeast Germany to study their year-round space use in relation to season, sex, and age. We marked 172 birds with colour rings and surveyed relevant water bodies for re-encounters for several years. As space-use patterns we derived home ranges from minimum convex polygons and the number of water bodies used by individual birds. Our analysis revealed that individuals shifted their space use between seasons, in particular extending their home ranges during the non-breeding season. Between years, in contrast, birds tended to show season-specific site fidelity. Sex differences were apparent during both breeding and non-breeding season, males consistently having larger home ranges and using slightly more water bodies. No difference was found between first-year and adult birds. Our study demonstrates that mark-resighting can provide valuable information about space use in species with suitable behaviour and readily accessible habitat. In such cases, it may be a valid alternative to more expensive GPS-tracking or short-term manual radio telemetry, particularly within citizen-science projects.
Flexible all-perovskite tandem photovoltaics open up new opportunities for application compared to rigid devices, yet their performance lags behind. Now, researchers show that molecule-bridged interfaces mitigate charge recombination and crack formation, improving the efficiency and mechanical reliability of flexible devices.
Alien Horrors
(2022)
H. P. Lovecraft’s oeuvre abounds with stereotypes of the racialized poor. As scholars have noted, Lovecraft’s work turns those he viewed as ‘Others’ into ‘aliens.’ Poor people of color (as opposed to the orderly White rural population and White working class) in Lovecraft’s stories are foreign, diseased, and criminal, and they threaten social and cosmic orders as they are in league with a nebulous entity that waits to wreak indescribable havoc. This chapter analyzes three ‘Lovecraftian’ novels published in 2016 - Cassandra Khaw’s Hammers on Bone,Victor LaValle’s The Ballad of Black Tom, and Matt Ruff’s Lovecraft Country. These works elucidate the connection of Trump’s 2016 rhetoric in campaign and presidential speeches and the White supremacist imagery used by Lovecraft. In these novels, the racialized poor have a special connection to an astronomical, evil entity à la Lovecraft. As carriers of numinous genes or parasitic entities (literally having ‘an alien within’) they become empowered. They thus occupy a pivotal position in forestalling or bringing about the destruction of societal order; that is, of White supremacy. Exploring the alleged risk posed by this ‘underclass,’ these works seem to foretell current representations of protesters as ‘riotous mobs’ that threaten the body politic Trump sought to make great (and White) again.
Algorithmic management
(2022)
Wild bee species are important pollinators in agricultural landscapes. However, population decline was reported over the last decades and is still ongoing. While agricultural intensification is a major driver of the rapid loss of pollinating species, transition zones between arable fields and forest or grassland patches, i.e., agricultural buffer zones, are frequently mentioned as suitable mitigation measures to support wild bee populations and other pollinator species. Despite the reported general positive effect, it remains unclear which amount of buffer zones is needed to ensure a sustainable and permanent impact for enhancing bee diversity and abundance. To address this question at a pollinator community level, we implemented a process-based, spatially explicit simulation model of functional bee diversity dynamics in an agricultural landscape. More specifically, we introduced a variable amount of agricultural buffer zones (ABZs) at the transition of arable to grassland, or arable to forest patches to analyze the impact on bee functional diversity and functional richness. We focused our study on solitary bees in a typical agricultural area in the Northeast of Germany. Our results showed positive effects with at least 25% of virtually implemented agricultural buffer zones. However, higher amounts of ABZs of at least 75% should be considered to ensure a sufficient increase in Shannon diversity and decrease in quasi-extinction risks. These high amounts of ABZs represent effective conservation measures to safeguard the stability of pollination services provided by solitary bee species. As the model structure can be easily adapted to other mobile species in agricultural landscapes, our community approach offers the chance to compare the effectiveness of conservation measures also for other pollinator communities in future.
Restrictive means to reduce the spread of the COVID-19 pandemic have not only imposed broad challenges on mental health but might also affect cognitive health. Here we asked how restriction-related changes influence cognitive performance and how age, perceived loneliness, depressiveness and affectedness by restrictions contribute to these effects. 51 Germans completed three assessments of an online based study during the first lockdown in Germany (April 2020), a month later, and during the beginning of the second lockdown (November 2020). Participants completed nine online cognitive tasks of the MyBrainTraining and online questionnaires about their perceived strain and impact on lifestyle factors by the situation (affectedness), perceived loneliness, depressiveness as well as subjective cognitive performance. The results suggested a possible negative impact of depressiveness and affectedness on objective cognitive performance within the course of the lockdown. The younger the participants, the more pronounced these effects were. Loneliness and depressiveness moreover contributed to a worse evaluation of subjective cognition. In addition, especially younger individuals reported increased distress. As important educational and social input has partly been scarce during this pandemic and mental health problems have increased, future research should also assess cognitive long-term consequences.
Marine sedimentary archives are routinely used to reconstruct past environmental changes. In many cases, bioturbation and sedimentary mixing affect the proxy time-series and the age-depth relationship. While idealized models of bioturbation exist, they usually assume homogeneous mixing, thus that a single sample is representative for the sediment layer it is sampled from.
However, it is largely unknown to which extent this assumption holds for sediments used for paleoclimate reconstructions.
To shed light on
1) the age-depth relationship and its full uncertainty,
2) the magnitude of mixing processes affecting the downcore proxy variations, and
3) the representativity of the discrete sample for the sediment layer, we designed and performed a case study on South China Sea sediment material which was collected using a box corer and which covers the last glacial cycle.
Using the radiocarbon content of foraminiferal tests as a tracer of time, we characterize the spatial age-heterogeneity of sediments in a three-dimensional setup. In total, 118 radiocarbon measurements were performed on defined small- and large-volume bulk samples ( similar to 200 specimens each) to investigate the horizontal heterogeneity of the sediment. Additionally, replicated measurements on small numbers of specimens (10 x 5 specimens) were performed to assess the heterogeneity within a sample volume. Visual assessment of X-ray images and a quantitative assessment of the mixing strength show typical mixing from bioturbation corresponding to around 10 cm mixing depth.
Notably, our 3D radiocarbon distribution reveals that the horizontal heterogeneity (up to 1,250 years), contributing to the age uncertainty, is several times larger than the typically assumed radiocarbon based age-model error (single errors up to 250 years). Furthermore, the assumption of a perfectly bioturbated layer with no mixing underneath is not met.
Our analysis further demonstrates that the age-heterogeneity might be a function of sample size; smaller samples might contain single features from the incomplete mixing and are thus less representative than larger samples.
We provide suggestions for future studies, optimal sampling strategies for quantitative paleoclimate reconstructions and realistic uncertainty in age models, as well as discuss possible implications for the interpretation of paleoclimate records.
To date, there has been little research on how advocacy coalitions influence the dynamic relationships between norms. Addressing norm collisions as a particular type of norm dynamics, we ask if and how advocacy coalitions and the constellations between them bring such norm collisions to the fore. Norm collisions surface in situations in which actors claim that two or more norms are incompatible with each other, promoting different, even opposing, behavioural choices. We examine the effect of advocacy coalition constellations (ACC) on the activation and varying evolution of norm collisions in three issue areas: international drug control, human trafficking, and child labour. These areas have a legally codified prohibitive regime in common. At the same time, they differ with regard to the specific ACC present. Exploiting this variation, we generate insights into how power asymmetries and other characteristics of ACC affect norm collisions across our three issue areas.
Advances in characteristics improvement of polymeric membranes/separators for zinc-air batteries
(2022)
Zinc-air batteries (ZABs) are gaining popularity for a wide range of applications due to their high energy density, excellent safety, and environmental friendliness. A membrane/separator is a critical component of ZABs, with substantial implications for battery performance and stability, particularly in the case of a battery in solid state format, which has captured increased attention in recent years. In this review, recent advances as well as insight into the architecture of polymeric membrane/separators for ZABs including porous polymer separators (PPSs), gel polymer electrolytes (GPEs), solid polymer electrolytes (SPEs) and anion exchange membranes (AEMs) are discussed. The paper puts forward strategies to enhance stability, ionic conductivity, ionic selectivity, electrolyte storage capacity and mechanical properties for each type of polymeric membrane. In addition, the remaining major obstacles as well as the most potential avenues for future research are examined in detail.
Background
Wearables, as small portable computer systems worn on the body, can track user fitness and health data, which can be used to customize health insurance contributions individually. In particular, insured individuals with a healthy lifestyle can receive a reduction of their contributions to be paid. However, this potential is hardly used in practice.
Objective
This study aims to identify which barrier factors impede the usage of wearables for assessing individual risk scores for health insurances, despite its technological feasibility, and to rank these barriers according to their relevance.
Methods
To reach these goals, we conduct a ranking-type Delphi study with the following three stages. First, we collected possible barrier factors from a panel of 16 experts and consolidated them to a list of 11 barrier categories. Second, the panel was asked to rank them regarding their relevance. Third, to enhance the panel consensus, the ranking was revealed to the experts, who were then asked to re-rank the barriers.
Results
The results suggest that regulation is the most important barrier. Other relevant barriers are false or inaccurate measurements and application errors caused by the users. Additionally, insurers could lack the required technological competence to use the wearable data appropriately.
Conclusion
A wider use of wearables and health apps could be achieved through regulatory modifications, especially regarding privacy issues. Even after assuring stricter regulations, users’ privacy concerns could partly remain, if the data exchange between wearables manufacturers, health app providers, and health insurers does not become more transparent.
Not much is known about how bystanders' emotional reactions after not intervening in cyberbullying might impact their health issues. Narrowing this gap in the literature, the present study focused on examining the moderating effects of emotional reactions (i.e., guilt, sadness, anger) after not intervening in cyberbullying on the longitudinal relationship between cyberbullying bystanding and health issues (i.e., subjective health complaints, suicidal ideation, non-suicidal self-harm). Participants were 1,067 adolescents between 12 and 15 years old included in this study (M-age = 13.67; 51% girls). The findings showed a positive association between Time 1 cyberbullying bystanding and Time 2 health issues. Guilt moderated the positive relationships among Time 1 cyberbullying bystanding, Time 2 subjective health complaints, suicidal ideation, and non-suicidal self-harm. Time 1 sadness also moderated the relationship between Time 1 cyberbullying bystanding and Time 2 suicidal ideation and non-suicidal self-harm. However, anger did not moderate any of the associations.
Reducing greenhouse gas emissions in food systems is becoming more challenging as food is increasingly consumed away from producer regions, highlighting the need to consider emissions embodied in trade in agricultural emissions accounting.
To address this, our study explores recent trends in trade-adjusted agricultural emissions of food items at the global, regional, and national levels.
We find that emissions are largely dependent on a country’s consumption patterns and their agricultural emission intensities relative to their trading partners’.
The absolute differences between the production-based and trade-adjusted emissions accounting approaches are especially apparent for major agricultural exporters and importers and where large shares of emission-intensive items such as ruminant meat, milk products and rice are involved.
In relative terms, some low-income and emerging and developing economies with consumption of high emission intensity food products show large differences between approaches.
Similar trends are also found under various specifications that account for trade and re-exports differently.
These findings could serve as an important element towards constructing national emissions reduction targets that consider trading partners, leading to more effective emissions reductions overall.
Flood risk management in Germany follows an integrative approach in which both private households and businesses can make an important contribution to reducing flood damage by implementing property-level adaptation measures. While the flood adaptation behavior of private households has already been widely researched, comparatively less attention has been paid to the adaptation strategies of businesses. However, their ability to cope with flood risk plays an important role in the social and economic development of a flood-prone region. Therefore, using quantitative survey data, this study aims to identify different strategies and adaptation drivers of 557 businesses damaged by a riverine flood in 2013 and 104 businesses damaged by pluvial or flash floods between 2014 and 2017. Our results indicate that a low perceived self-efficacy may be an important factor that can reduce the motivation of businesses to adapt to flood risk. Furthermore, property-owners tended to act more proactively than tenants. In addition, high experience with previous flood events and low perceived response costs could strengthen proactive adaptation behavior. These findings should be considered in business-tailored risk communication.
Flood risk management in Germany follows an integrative approach in which both private households and businesses can make an important contribution to reducing flood damage by implementing property-level adaptation measures. While the flood adaptation behavior of private households has already been widely researched, comparatively less attention has been paid to the adaptation strategies of businesses. However, their ability to cope with flood risk plays an important role in the social and economic development of a flood-prone region. Therefore, using quantitative survey data, this study aims to identify different strategies and adaptation drivers of 557 businesses damaged by a riverine flood in 2013 and 104 businesses damaged by pluvial or flash floods between 2014 and 2017. Our results indicate that a low perceived self-efficacy may be an important factor that can reduce the motivation of businesses to adapt to flood risk. Furthermore, property-owners tended to act more proactively than tenants. In addition, high experience with previous flood events and low perceived response costs could strengthen proactive adaptation behavior. These findings should be considered in business-tailored risk communication.
Fragmentation of peptides leaves characteristic patterns in mass spectrometry data, which can be used to identify protein sequences, but this method is challenging for mutated or modified sequences for which limited information exist. Altenburg et al. use an ad hoc learning approach to learn relevant patterns directly from unannotated fragmentation spectra.
Mass spectrometry-based proteomics provides a holistic snapshot of the entire protein set of living cells on a molecular level. Currently, only a few deep learning approaches exist that involve peptide fragmentation spectra, which represent partial sequence information of proteins.
Commonly, these approaches lack the ability to characterize less studied or even unknown patterns in spectra because of their use of explicit domain knowledge.
Here, to elevate unrestricted learning from spectra, we introduce 'ad hoc learning of fragmentation' (AHLF), a deep learning model that is end-to-end trained on 19.2 million spectra from several phosphoproteomic datasets. AHLF is interpretable, and we show that peak-level feature importance values and pairwise interactions between peaks are in line with corresponding peptide fragments.
We demonstrate our approach by detecting post-translational modifications, specifically protein phosphorylation based on only the fragmentation spectrum without a database search. AHLF increases the area under the receiver operating characteristic curve (AUC) by an average of 9.4% on recent phosphoproteomic data compared with the current state of the art on this task.
Furthermore, use of AHLF in rescoring search results increases the number of phosphopeptide identifications by a margin of up to 15.1% at a constant false discovery rate. To show the broad applicability of AHLF, we use transfer learning to also detect cross-linked peptides, as used in protein structure analysis, with an AUC of up to 94%.
Dielectrophoresis (DEP) is an AC electrokinetic effect mainly used to manipulate cells. Smaller particles, like virions, antibodies, enzymes, and even dye molecules can be immobilized by DEP as well. In principle, it was shown that enzymes are active after immobilization by DEP, but no quantification of the retained activity was reported so far. In this study, the activity of the enzyme horseradish peroxidase (HRP) is quantified after immobilization by DEP. For this, HRP is immobilized on regular arrays of titanium nitride ring electrodes of 500 nm diameter and 20 nm widths. The activity of HRP on the electrode chip is measured with a limit of detection of 60 fg HRP by observing the enzymatic turnover of Amplex Red and H2O2 to fluorescent resorufin by fluorescence microscopy. The initial activity of the permanently immobilized HRP equals up to 45% of the activity that can be expected for an ideal monolayer of HRP molecules on all electrodes of the array. Localization of the immobilizate on the electrodes is accomplished by staining with the fluorescent product of the enzyme reaction. The high residual activity of enzymes after AC field induced immobilization shows the method's suitability for biosensing and research applications.
Active use of social networking sites (SNSs) has long been assumed to benefit users' well-being. However, this established hypothesis is increasingly being challenged, with scholars criticizing its lack of empirical support and the imprecise conceptualization of active use. Nevertheless, with considerable heterogeneity among existing studies on the hypothesis and causal evidence still limited, a final verdict on its robustness is still pending. To contribute to this ongoing debate, we conducted a week-long randomized control trial with N = 381 adult Instagram users recruited via Prolific. Specifically, we tested how active SNS use, operationalized as picture postings on Instagram, affects different dimensions of well-being. The results depicted a positive effect on users' positive affect but null findings for other well-being outcomes. The findings broadly align with the recent criticism against the active use hypothesis and support the call for a more nuanced view on the impact of SNSs. <br /> Lay Summary Active use of social networking sites (SNSs) has long been assumed to benefit users' well-being. However, this established assumption is increasingly being challenged, with scholars criticizing its lack of empirical support and the imprecise conceptualization of active use. Nevertheless, with great diversity among conducted studies on the hypothesis and a lack of causal evidence, a final verdict on its viability is still pending. To contribute to this ongoing debate, we conducted a week-long experimental investigation with 381 adult Instagram users. Specifically, we tested how posting pictures on Instagram affects different aspects of well-being. The results of this study depicted a positive effect of posting Instagram pictures on users' experienced positive emotions but no effects on other aspects of well-being. The findings broadly align with the recent criticism against the active use hypothesis and support the call for a more nuanced view on the impact of SNSs on users.
This study examines the access to healthcare for children and adolescents with three common chronic diseases (type-1 diabetes (T1D), obesity, or juvenile idiopathic arthritis (JIA)) within the 4th (Delta), 5th (Omicron), and beginning of the 6th (Omicron) wave (June 2021 until July 2022) of the COVID-19 pandemic in Germany in a cross-sectional study using three national patient registries. A paper-and-pencil questionnaire was given to parents of pediatric patients (<21 years) during the routine check-ups. The questionnaire contains self-constructed items assessing the frequency of healthcare appointments and cancellations, remote healthcare, and satisfaction with healthcare. In total, 905 parents participated in the T1D-sample, 175 in the obesity-sample, and 786 in the JIA-sample. In general, satisfaction with healthcare (scale: 0–10; 10 reflecting the highest satisfaction) was quite high (median values: T1D 10, JIA 10, obesity 8.5). The proportion of children and adolescents with canceled appointments was relatively small (T1D 14.1%, JIA 11.1%, obesity 20%), with a median of 1 missed appointment, respectively. Only a few parents (T1D 8.6%; obesity 13.1%; JIA 5%) reported obstacles regarding health services during the pandemic. To conclude, it seems that access to healthcare was largely preserved for children and adolescents with chronic health conditions during the COVID-19 pandemic in Germany.
The use of alternating current (AC) electrokinetic forces, like dielectrophoresis and AC electroosmosis, as a simple and fast method to immobilize sub-micrometer objects onto nanoelectrode arrays is presented. Due to its medical relevance, the influenza virus is chosen as a model organism. One of the outstanding features is that the immobilization of viral material to the electrodes can be achieved permanently, allowing subsequent handling independently from the electrical setup. Thus, by using merely electric fields, we demonstrate that the need of prior chemical surface modification could become obsolete. The accumulation of viral material over time is observed by fluorescence microscopy. The influences of side effects like electrothermal fluid flow, causing a fluid motion above the electrodes and causing an intensity gradient within the electrode array, are discussed. Due to the improved resolution by combining fluorescence microscopy with deconvolution, it is shown that the viral material is mainly drawn to the electrode edge and to a lesser extent to the electrode surface. Finally, areas of application for this functionalization technique are presented.
There is a longstanding and widely held misconception about the relative remoteness of abstract concepts from concrete experiences. This review examines the current evidence for external influences and internal constraints on the processing, representation, and use of abstract concepts, like truth, friendship, and number. We highlight the theoretical benefit of distinguishing between grounded and embodied cognition and then ask which roles do perception, action, language, and social interaction play in acquiring, representing and using abstract concepts. By reviewing several studies, we show that they are, against the accepted definition, not detached from perception and action. Focussing on magnitude-related concepts, we also discuss evidence for cultural influences on abstract knowledge and explore how internal processes such as inner speech, metacognition, and inner bodily signals (interoception) influence the acquisition and retrieval of abstract knowledge. Finally, we discuss some methodological developments. Specifically, we focus on the importance of studies that investigate the time course of conceptual processing and we argue that, because of the paramount role of sociality for abstract concepts, new methods are necessary to study concepts in interactive situations. We conclude that bodily, linguistic, and social constraints provide important theoretical limitations for our theories of conceptual knowledge.
We study the diffusive motion of a particle in a subharmonic potential of the form U(x) = |x|( c ) (0 < c < 2) driven by long-range correlated, stationary fractional Gaussian noise xi ( alpha )(t) with 0 < alpha <= 2. In the absence of the potential the particle exhibits free fractional Brownian motion with anomalous diffusion exponent alpha. While for an harmonic external potential the dynamics converges to a Gaussian stationary state, from extensive numerical analysis we here demonstrate that stationary states for shallower than harmonic potentials exist only as long as the relation c > 2(1 - 1/alpha) holds. We analyse the motion in terms of the mean squared displacement and (when it exists) the stationary probability density function. Moreover we discuss analogies of non-stationarity of Levy flights in shallow external potentials.
Little is known about the current state of research on the involvement of young people in hate speech. Thus, this systematic review presents findings on a) the prevalence of hate speech among children and adolescents and on hate speech definitions that guide prevalence assessments for this population; and b) the theoretical and empirical overlap of hate speech with related concepts. This review was guided by the Cochrane approach. To be included, publications were required to deal with real-life experiences of hate speech, to provide empirical data on prevalence for samples aged 5 to 21 years and they had to be published in academic formats. Included publications were full-text coded using two raters (kappa = .80) and their quality was assessed. The string-guided electronic search (ERIC, SocInfo, Psycinfo, Psyndex) yielded 1,850 publications. Eighteen publications based on 10 studies met the inclusion criteria and their findings were systematized. Twelve publications were of medium quality due to minor deficiencies in their theoretical or methodological foundations. All studies used samples of adolescents and none of younger children. Nine out of 10 studies applied quantitative methodologies. Eighteen publications based on 10 studies were included. Results showed that frequencies for hate speech exposure were higher than those related to victimization and perpetration. Definitions of hate speech and assessment instruments were heterogeneous. Empirical evidence for an often theorized overlap between hate speech and bullying was found. The paper concludes by presenting a definition of hate speech, including implications for practice, policy, and research.
Groundwater recharge (GWR) is one of the most challenging water fluxes to estimate, as it relies on observed data that are often limited in many developing countries.
This study developed an innovative water budget method using satellite products for estimating the spatially distributed GWR at monthly and annual scales in tropical wet sedimentary regions despite cloudy conditions.
The distinctive features proposed in this study include the capacity to address 1) evapotranspiration estimations in tropical wet regions frequently overlaid by substantial cloud cover; and 2) seasonal root-zone water storage estimations in sedimentary regions prone to monthly variations.
The method also utilises satellite-based information of the precipitation and surface runoff. The GWR was estimated and validated for the hydrologically contrasting years 2016 and 2017 over a tropical wet sedimentary region located in North-eastern Brazil, which has substantial potential for groundwater abstraction.
This study showed that applying a cloud-cleaning procedure based on monthly compositions of biophysical data enables the production of a reasonable proxy for evapotranspiration able to estimate groundwater by the water budget method.
The resulting GWR rates were 219 (2016) and 302 (2017) mm yr(-1), showing good correlations (CC = 0.68 to 0.83) and slight underestimations (PBIAS =-13 to-9%) when compared with the referenced estimates obtained by the water table fluctuation method for 23 monitoring wells. Sensitivity analysis shows that water storage changes account for +19% to-22% of our monthly evaluation.
The satellite-based approach consistently demonstrated that the consideration of cloud-cleaned evapotranspiration and root-zone soil water storage changes are essential for a proper estimation of spatially distributed GWR in tropical wet sedimentary regions because of their weather seasonality and cloudy conditions.
A rigorous construction of the supersymmetric path integral associated to a compact spin manifold
(2022)
We give a rigorous construction of the path integral in N = 1/2 supersymmetry as an integral map for differential forms on the loop space of a compact spin manifold. It is defined on the space of differential forms which can be represented by extended iterated integrals in the sense of Chen and Getzler-Jones-Petrack. Via the iterated integral map, we compare our path integral to the non-commutative loop space Chern character of Guneysu and the second author. Our theory provides a rigorous background to various formal proofs of the Atiyah-Singer index theorem for twisted Dirac operators using supersymmetric path integrals, as investigated by Alvarez-Gaume, Atiyah, Bismut and Witten.
A review of source models to further the understanding of the seismicity of the Groningen field
(2022)
The occurrence of felt earthquakes due to gas production in Groningen has initiated numerous studies and model attempts to understand and quantify induced seismicity in this region. The whole bandwidth of available models spans the range from fully deterministic models to purely empirical and stochastic models. In this article, we summarise the most important model approaches, describing their main achievements and limitations. In addition, we discuss remaining open questions and potential future directions of development.
Fluctuating asymmetries (FA) are small stress-induced random deviations from perfect symmetry that arise during the development of bilaterally symmetrical traits. One of the factors that can reduce developmental stability of the individuals and cause FA at a population level is the loss of genetic variation. Populations of founding colonists frequently have lower genetic variation than their ancestral populations that could be reflected in a higher level of FA. The European starling (Sturnus vulgaris) is native to Eurasia and was introduced successfully in the USA in 1890 and Argentina in 1983. In this study, we documented the genetic diversity and FA of starlings from England (ancestral population), USA (primary introduction) and Argentina (secondary introduction). We predicted the Argentinean starlings would have the highest level of FA and lowest genetic diversity of the three populations. We captured wild adult European starlings in England, USA, and Argentina, measured their mtDNA diversity and allowed them to molt under standardized conditions to evaluate their FA of primary feathers. For genetic analyses, we extracted DNA from blood samples of individuals from Argentina and USA and from feather samples from individuals from England and sequenced the mitochondrial control region. Starlings in Argentina showed the highest composite FA and exhibited the lowest haplotype and nucleotide diversity. The USA population showed a level of FA and genetic diversity similar to the native population. Therefore, the level of asymmetry and genetic diversity found among these populations was consistent with our predictions based on their invasion history.
As the use of free electron laser (FEL) sources increases, so do the findings mentioning non-linear phenomena occurring at these experiments, such as saturable absorption, induced transparency and scattering breakdowns. These are well known among the laser community, but are still rarely understood and expected among the X-ray community and to date lack tools and theories to accurately predict the respective experimental parameters and results. We present a simple theoretical framework to access short X-ray pulse induced light- matter interactions which occur at intense short X-ray pulses as available at FEL sources. Our approach allows to investigate effects such as saturable absorption, induced transparency and scattering suppression, stimulated emission, and transmission spectra, while including the density of state influence relevant to soft X-ray spectroscopy in, for example, transition metal complexes or functional materials. This computationally efficient rate model based approach is intuitively adaptable to most solid state sample systems in the soft X-ray spectrum with the potential to be extended for liquid and gas sample systems as well. The feasibility of the model to estimate the named effects and the influence of the density of state is demonstrated using the example of CoPd transition metal systems at the Co edge. We believe this work is an important contribution for the preparation, performance, and understanding of FEL based high intensity and short pulse experiments, especially on functional materials in the soft X-ray spectrum.
The digital transformation sets new requirements to all classes of enterprise systems in companies. ERP systems in particular, which represent the dominant class of enterprise systems, are struggling to meet the new requirements at all levels of the architecture. Therefore, there is an urgent need to reconsider the overall architecture of the systems and address the root of the related issues. Given that many restrictions ERP pose on their adaptability are related to the standardization of data, the database layer of ERP systems is addressed. Since database serve as the foundation for data storage and retrieval, they limit the flexibility of enterprise systems and the chance to adapt to new requirements accordingly. So far, relational databases are widely used. Using a systematic literature approach, recent requirements for ERP systems were identified. Prominent database approaches were assessed against the 23 requirements identified. The results reveal the strengths and weaknesses of recent database approaches. To this end, the results highlight the demand to combine multiple database approaches to fulfill recent business requirements. From a conceptual point of view, this paper supports the idea of federated databases which are interoperable to fulfill future requirements and support business operation. This research forms the basis for renewal of the current generation of ERP systems and proposes to ERP vendors to use different database concepts in the future.
Hegel's many remarks that seem to imply that philosophy should proceed completely a priori pose a problem for his philosophy of nature since, on this reading, Hegel offers an a priori derivation of empirical results of natural sciences. We show how this perception can be mitigated by interpreting Hegel's remarks as broadly in line with the pre-Kantian rationalist notion of a priori and offer reasons for doing so. We show that, rather than being a peculiarity of Hegel's philosophy, the practice of demonstrating a priori the results of empirical sciences was widespread in the pre-Kantian rationalist tradition. We argue that this practice was intelligible in light of the notion of a priori that was still quite prominent during Hegel's life. This notion of a priori differs from Kant's in that, while the latter's notion concerns propositions, the former concerned only their demonstration. According to it, the same proposition could be demonstrated both a posteriori and a priori. Post-Kantian idealists likewise developed projects of demonstrating specific scientific contents a priori. We then make our discussion more concrete by examining a particular case of an a priori derivation of a natural law, namely the law of fall, by both Leibniz and Hegel.
A novel approach for estimating precipitation patterns is developed here and applied to generate a new hydrologically corrected daily precipitation dataset, called RAIN4PE (Rain for Peru and Ecuador), at 0.1 degrees spatial resolution for the period 1981-2015 covering Peru and Ecuador. It is based on the application of 1) the random forest method to merge multisource precipitation estimates (gauge, satellite, and reanalysis) with terrain elevation, and 2) observed and modeled streamflow data to first detect biases and second further adjust gridded precipitation by inversely applying the simulated results of the ecohydrological model SWAT (Soil and Water Assessment Tool). Hydrological results using RAIN4PE as input for the Peruvian and Ecuadorian catchments were compared against the ones when feeding other uncorrected (CHIRP and ERA5) and gauge-corrected (CHIRPS, MSWEP, and PISCO) precipitation datasets into the model. For that, SWAT was calibrated and validated at 72 river sections for each dataset using a range of performance metrics, including hydrograph goodness of fit and flow duration curve signatures. Results showed that gauge-corrected precipitation datasets outperformed uncorrected ones for streamflow simulation. However, CHIRPS, MSWEP, and PISCO showed limitations for streamflow simulation in several catchments draining into the Pacific Ocean and the Amazon River. RAIN4PE provided the best overall performance for streamflow simulation, including flow variability (low, high, and peak flows) and water budget closure. The overall good performance of RAIN4PE as input for hydrological modeling provides a valuable criterion of its applicability for robust countrywide hydrometeorological applications, including hydroclimatic extremes such as droughts and floods. Significance StatementWe developed a novel precipitation dataset RAIN4PE for Peru and Ecuador by merging multisource precipitation data (satellite, reanalysis, and ground-based precipitation) with terrain elevation using the random forest method. Furthermore, RAIN4PE was hydrologically corrected using streamflow data in watersheds with precipitation underestimation through reverse hydrology. The results of a comprehensive hydrological evaluation showed that RAIN4PE outperformed state-of-the-art precipitation datasets such as CHIRP, ERA5, CHIRPS, MSWEP, and PISCO in terms of daily and monthly streamflow simulations, including extremely low and high flows in almost all Peruvian and Ecuadorian catchments. This underlines the suitability of RAIN4PE for hydrometeorological applications in this region. Furthermore, our approach for the generation of RAIN4PE can be used in other data-scarce regions.
Extreme value statistics is a popular and frequently used tool to model the occurrence of large earthquakes. The problem of poor statistics arising from rare events is addressed by taking advantage of the validity of general statistical properties in asymptotic regimes. In this note, I argue that the use of extreme value statistics for the purpose of practically modeling the tail of the frequency-magnitude distribution of earthquakes can produce biased and thus misleading results because it is unknown to what degree the tail of the true distribution is sampled by data. Using synthetic data allows to quantify this bias in detail. The implicit assumption that the true M-max is close to the maximum observed magnitude M-max,M-observed restricts the class of the potential models a priori to those with M-max = M-max,M-observed + Delta M with an increment Delta M approximate to 0.5... 1.2. This corresponds to the simple heuristic method suggested by Wheeler (2009) and labeled :M-max equals M-obs plus an increment." The incomplete consideration of the entire model family for the frequency-magnitude distribution neglects, however, the scenario of a large so far unobserved earthquake.
We discuss Neumann problems for self-adjoint Laplacians on (possibly infinite) graphs. Under the assumption that the heat semigroup is ultracontractive we discuss the unique solvability for non-empty subgraphs with respect to the vertex boundary and provide analytic and probabilistic representations for Neumann solutions. A second result deals with Neumann problems on canonically compactifiable graphs with respect to the Royden boundary and provides conditions for unique solvability and analytic and probabilistic representations.