bluuebunny/crossref_metadata_2025_split huggingface dataset:
Five years of grassland yield and quality assessment in a temperate short-rotation alley cropping agroforestry system
Authors: Langhof Maren , Swieter Anita 
Published: February 2024

AbstractThe biomass yield and the crude protein (CP) content of temperate agroforestry-grassland were compared with that of a treeless control between 2017 and 2021. The single factor cropping system did not determine differences in yield nor CP content, while significant interactions with other studied factors occurred. At 1 m from the field edge, grassland yield was significantly lower in both the agroforestry system and the treeless control than at the other distances studied (4, 7, and 24 m). Overall, grassland yields were similar in agroforestry and control. The CP results were inconclusive. The highest, although not significant, CP levels were found in the agroforestry variant 1 m distance from the tree strip. Our study shows that due to edge effects on biomass yields, which may also occur in the treeless control, sampling of identical distances in agroforestry and control are necessary.
Product liability for defective AI
Authors: Buiten Miriam C. 
Published: February 2024

AbstractThis paper studies the efficient definition of product defects for AI systems with autonomous capabilities. It argues that defining defects in product liability law is central to distributing responsibility between producers and users. The paper proposes aligning the standard for defect with the relative control over and awareness of product risk possessed by the producer and the user. AI systems disrupt the traditional balance of control and risk awareness between users and producers. The paper provides suggestions for defining AI product defects in a way that promotes an efficient allocation of liability in AI-related accidents. It assesses whether the recent EU policy proposal on product liability aligns with this approach.
Microbial, chemical, and isotopic monitoring integrated approach to assess potential leachate contamination of groundwater in a karstic aquifer (Apulia, Italy)
Authors: Beneduce L. , Piergiacomo F. , Limoni P. P. , Zuffianò L. E. , Polemio M. 
Published: February 2024

AbstractLandfill sites are subjected to long-term risks of accidental spill of leachate through the soil and consequential contamination of the groundwater. Wide areas surrounding the landfill can seriously be threatened with possible consequences to human health and the environment. Given the potential impact of different coexisting anthropic pollution sources (i.e., agriculture and cattle farming) on the same site, the perturbation of the groundwater quality may be due to multiple factors. Therefore, it is a challenging issue to correctly establish the pollution source of an aquifer where the landfill is not isolated from other anthropic land uses, especially in the case of a karstic coastal aquifer. The present study is aimed at setting in place an integrated environmental monitoring system that included microbiological, chemical, and isotope methods to evaluate potential groundwater pollution in a landfill district in the south of Italy located in Murgia karstic aquifer. Conventional (microbial plate count and physical–chemical analyses) and advanced methods (PCR-ARISA, isotope analysis of δ18O, δ2H, 3H, δ 13C, δ 15N-NO3−, and δ 18O-NO3−) were included in the study. Through data integration, it was possible to reconstruct a scenario in which agriculture and other human activities along with seawater intrusion in the karst aquifer were the main drivers of groundwater pollution at the monitored site. The microbiological, chemical, and isotope results confirmed the absence of leachate effects on groundwater quality, showing the decisive role of fertilizers as potential nitrate sources. The next goal will be to extend long-term integrated monitoring to other landfill districts, with different geological and hydrogeological characteristics and including different sources of pollution, to support the ecological restoration of landfills.
Heart failure with mildly reduced and preserved ejection fraction: A review of disease burden and remaining unmet medical needs within a new treatment landscape
Authors: Desai Nihar , Olewinska Elzbieta , Famulska Agata , Remuzat Cécile , Francois Clément , Folkerts Kerstin 
Published: February 2024

Abstract This review provides a comprehensive overview of heart failure with mildly reduced and preserved ejection fraction (HFmrEF/HFpEF), including its definition, diagnosis, and epidemiology; clinical, humanistic, and economic burdens; current pharmacologic landscape in key pharmaceutical markets; and unmet needs to identify key knowledge gaps. We conducted a targeted literature review in electronic databases and prioritized articles with valuable insights into HFmrEF/HFpEF. Overall, 27 randomized controlled trials (RCTs), 66 real-world evidence studies, 18 clinical practice guidelines, and 25 additional publications were included. Although recent heart failure (HF) guidelines set left ventricular ejection fraction thresholds to differentiate categories, characterization and diagnosis criteria vary because of the incomplete disease understanding. Recent epidemiological data are limited and diverse. Approximately 50% of symptomatic HF patients have HFpEF, more common than HFmrEF. Prevalence varies with country because of differing definitions and study characteristics, making prevalence interpretation challenging. HFmrEF/HFpEF has considerable mortality risk, and the mortality rate varies with study and patient characteristics and treatments. HFmrEF/HFpEF is associated with considerable morbidity, poor patient outcomes, and common comorbidities. Patients require frequent hospitalizations; therefore, early intervention is crucial to prevent disease burden. Recent RCTs show promising results like risk reduction of composite cardiovascular death or HF hospitalization. Costs data are scarce, but the economic burden is increasing. Despite new drugs, unmet medical needs requiring new treatments remain. Thus, HFmrEF/HFpEF is a growing global healthcare concern. With improving yet incomplete understanding of this disease and its promising treatments, further research is required for better patient outcomes.
Atomistic modeling of idealized equal channel angular pressing process
Authors: Prakash Aruna 
Published: February 2024

AbstractSevere plastic deformation (SPD) processes are forming techniques that impose large plastic strains to achieve ultra-fine grained and nanocrystalline microstructures. The refined microstructure results in a significant increase in strength and in many cases without a considerable loss in ductility. Despite their long existence, a comprehensive understanding of the deformation and grain refinement mechanisms during SPD is still lacking. Atomistic simulations that are regularly used to obtain insights into material behavior have rarely been used to study SPD processes. In this work, we use large scale atomistic simulations of the molecular statics/dynamics kind to model the equal channel angular pressing (ECAP) process, a specific SPD process. Three different materials—Al, Ni and Cu—are used to model high, medium and low stacking fault energy materials. Large simulation cells are used to facilitate grain refinement at the nanoscale. The simulations are carefully analyzed in terms of stress–strain behavior, dislocation activity and grain refinement. All samples show the formation of deformation twins at the nanoscale, which generally detwin at increased strains via dislocation twin interactions. A significant number of stair-rod dislocations form via dislocation–dislocation interactions and are present at low angle grain boundaries in the early stages of deformation. Such stair-rod dislocations also result in the formation of stacking fault tetrahedra which are present in significant numbers in all samples. Finally, difficulties in studying grain refinement at very large strains in atomistic simulations are discussed.
How (if at All) do Perceptions of Supervisor’s Listening Differ from General Relationship Quality?: Psychometric Analysis
Authors: Borut Limor , Kluger Avraham N. , Reis Harry T. , Shapiro Debra L. 
Published: February 2024

Abstract
Employees who perceive their supervisors to listen well enjoy multiple benefits, including enhanced well-being. However, concerns regarding the construct validity of perceived-listening measures raise doubts about such conclusions. The perception of listening quality may reflect two factors: constructive and destructive listening, which may converge with desired (e.g., humility) and undesired (e.g., rudeness) supervisor-subordinate relationship behaviors, respectively, and both may converge with relationship quality (e.g., trust). Therefore, we assessed the convergent validity of four perceived listening measures and their divergent validity with eight measures of supervisor-subordinate relationship behaviors, eight relationship-quality measures, and a criterion measure of well-being. Using data from 2,038 subordinates, we calculated the disattenuated correlations and profile similarities among these measures. The results supported convergent but not divergent validity: 58.7% (12.6%) of the correlations expected to diverge had confidence intervals with upper limits above 0.80 (0.90), and 20% of their profile-similarity indices were close to 1. To probe these correlations, we ran a factor analysis revealing good and poor relationship factors and an exploratory graph analysis identifying three clusters: positive and negative relationship behaviors and relationship quality. A post-hoc analysis indicated that relationship-quality mediates the effect of the positive and negative behaviors on well-being. The results demonstrate the challenge of differentiating the perception of listening from commonly used supervisor-subordinate relationship constructs, and cast doubts on the divergent validity of many constructs of interest in Organizational Behavior. However, using the “sibling” constructs framework may allow disentangling these highly correlated relationship constructs, conceptually and empirically.
The Influence of Health-Related Behavior Profiles on College Students’ Perceptions of COVID-19 Safety Measures
Authors: Shank Faith , Korovich Megan , Nicoletti Alexandra , Angelone DJ , Jones Meredith C. 
Published: February 2024

AbstractCollege students often engage in multiple health-related behaviors simultaneously which can lead to negative outcomes and further risky behaviors. During the COVID-19 pandemic, college students reported decreased condom use, increased solitary cannabis use, and increased alcohol consumption. This current study aimed to (1) identify profiles of health-related behaviors (i.e., alcohol consumption, cannabis use, and sexual behaviors), and (2) determine if these profiles would differ in engagement and perceived effectiveness of COVID-19 preventative measures. Participants were 273 college students from a large Northeastern U.S. public university who completed surveys about health-related behaviors during the 2021 academic year. We used a latent profile analysis to identify distinct subgroups of college students based on their engagement in health-related behaviors. Based on fit indices a three-profile solution showed the best fit: low (N = 196), moderate (N = 54), and high (N = 23). Two one-way ANOVAs examined whether profile membership predicted engagement and perceived effectiveness of COVID-19 safety measures. Participants in the low health-related behaviors profile engaged in preventative measures more than students in the other two profiles. However, profile membership did not predict perceived effectiveness of preventative behaviors. Taken together, our results indicate that college students reporting lower levels of health-related behaviors engage in more preventative measures during a pandemic. Understanding distinct health-related behaviors profiles among college students, and their links with COVID-preventative health-related behaviors, can inform prevention strategies.
Knowledge, Perceptions and Attitude of Researchers Towards Using ChatGPT in Research
Authors: Abdelhafiz Ahmed Samir , Ali Asmaa , Maaly Ayman Mohamed , Ziady Hany Hassan , Sultan Eman Anwar , Mahgoub Mohamed Anwar 
Published: February 2024

Abstract

Introduction
ChatGPT, a recently released chatbot from OpenAI, has found applications in various aspects of life, including academic research. This study investigated the knowledge, perceptions, and attitudes of researchers towards using ChatGPT and other chatbots in academic research.

Methods
A pre-designed, self-administered survey using Google Forms was employed to conduct the study. The questionnaire assessed participants’ knowledge of ChatGPT and other chatbots, their awareness of current chatbot and artificial intelligence (AI) applications, and their attitudes towards ChatGPT and its potential research uses.

Results
Two hundred researchers participated in the survey. A majority were female (57.5%), and over two-thirds belonged to the medical field (68%). While 67% had heard of ChatGPT, only 11.5% had employed it in their research, primarily for rephrasing paragraphs and finding references. Interestingly, over one-third supported the notion of listing ChatGPT as an author in scientific publications. Concerns emerged regarding AI’s potential to automate researcher tasks, particularly in language editing, statistics, and data analysis. Additionally, roughly half expressed ethical concerns about using AI applications in scientific research.

Conclusion
The increasing use of chatbots in academic research necessitates thoughtful regulation that balances potential benefits with inherent limitations and potential risks. Chatbots should not be considered authors of scientific publications but rather assistants to researchers during manuscript preparation and review. Researchers should be equipped with proper training to utilize chatbots and other AI tools effectively and ethically.
Random Frogs: using future climate and land-use scenarios to predict amphibian distribution change in the Upper Missouri River Basin
Authors: Campbell Kaitlyn S. , Baltensperger Andrew P. , Kerby Jacob L. 
Published: February 2024

Abstract
Context
Climate change and anthropogenic stressors have contributed to rapid declines in biodiversity worldwide, particularly for amphibians. Amphibians play important ecological roles, yet little is known about how distribution hotspots may change or how the environmental factors influence distribution patterns in the North American Great Plains.

Objectives
Ecological niche models improve understanding of biotic and abiotic factors associated with species' distributions and can highlight potential threats to species conservation. Here, we identify important predictors of amphibian distributions and predict how land use and climate change may alter amphibian distributions in the Upper Missouri River Basin.

Methods
We used publicly available occurrence data, 16 environmental and climatic predictors, and the machine-learning algorithm, Random Forests, to create spatially explicit distribution models for eight amphibian species. Models were scored to baseline conditions (2005) and two future climate-change/land-use scenarios to predict changes in amphibian distributions for 2060.

Results
Models were highly accurate and revealed more pronounced distribution changes under the intensive RCP8.5/CONUS A2 scenario compared to the moderate RCP6.0/CONUS B2 scenario. Both scenarios predicted gains for most eastern species (i.e., Blanchard’s cricket frogs, Plains leopard frogs, Woodhouse’s toads, and Great Plains toads) and declines for all western montane species. Overall, distribution changes were most influenced by climatic and geographic predictors, (e.g., mean temperature in the warmest quarter, precipitation, and elevation), and geography, versus anthropogenic land-use variables.

Conclusions
Changes in occurrence area varied by species and geography, however, high-elevation western species were more negatively impacted. Our distribution models provide a framework for conservation efforts to aid the persistence of amphibian species across a warming, agriculturally dominated landscape.
Value creation mechanisms in a social and health care innovation ecosystem – an institutional perspective
Authors: Roth Marco , Vakkuri Jarmo , Johanson Jan-Erik 
Published: February 2024

AbstractThis study explores value-creation mechanisms in an institutionally diverse social and health care ecosystem, specifically through the lenses of institutional logics and institutional work. The research context is the social and health care innovation ecosystem in Tampere, Finland, comprising actors from various institutional backgrounds. The research method is an inductive interpretivist analysis, frequently used in studies on institutional logics. The alternation between empirical data—derived from interviews (n = 21), surveys (n = 23), and memos (n = 71)—and the theoretical framework yields new insights. Specifically, the empirical and the theoretical evidence provides practical examples of value-creation mechanisms, institutional logics, and modes of institutional work in social and health care innovation ecosystems. This article is one of the few papers that integrate institutional logics and institutional work to study value creation in a diverse social and health care innovation ecosystem. It contributes to the existing literature on collaborative value creation and the social and health care ecosystem by identifying how different value-creation mechanisms are manifested as hybridity in the ecosystem and how institutional work fosters collaborative value creation. This study fills a research gap by refining the understanding of collaborative value-creation mechanisms and their institutional underpinnings in social and health care ecosystems, thereby enriching both bodies of literature. These insights promote a nuanced understanding of collaborative value-creation practices in institutionalized settings, with implications for both policymaking and further research.
Increase in the solubility of uvsY using a site saturation mutagenesis library for application in a lyophilized reagent for recombinase polymerase amplification
Authors: Morimoto Kenta , Juma Kevin Maafu , Yamagata Masaya , Takita Teisuke , Kojima Kenji , Suzuki Koichiro , Yanagihara Itaru , Fujiwara Shinsuke , Yasukawa Kiyoshi 
Published: February 2024

Abstract

Background
Recombinase uvsY from bacteriophage T4, along with uvsX, is a key enzyme for recombinase polymerase amplification (RPA), which is used to amplify a target DNA sequence at a constant temperature. uvsY, though essential, poses solubility challenges, complicating the lyophilization of RPA reagents. This study aimed to enhance uvsY solubility.

Methods
Our hypothesis centered on the C-terminal region of uvsY influencing solubility. To test this, we generated a site-saturation mutagenesis library for amino acid residues Lys91–Glu134 of the N-terminal (His)6-tagged uvsY.

Results
Screening 480 clones identified A116H as the variant with superior solubility. Lyophilized RPA reagents featuring the uvsY variant A116H demonstrated enhanced performance compared to those with wild-type uvsY.

Conclusions
The uvsY variant A116H emerges as an appealing choice for RPA applications, offering improved solubility and heightened lyophilization feasibility.
Floods have become less deadly: an analysis of global flood fatalities 1975–2022
Authors: Jonkman S. N. , Curran A. , Bouwer L. M. 
Published: February 2024

AbstractFloods are amongst the most frequent disasters in terms of human and economic impacts. This study provides new insights into the frequency of loss of life at the global scale, mortality fractions of the population exposed to floods, and underlying trends. A dataset is compiled based on the EM-DAT disaster database covering the period 1975 until 2022, extending previous studies on this topic. Flood impact data are analysed over spatial, temporal and economic scales, decomposed in various flood types and compared with other natural disasters. Floods are the most frequent natural disasters up to 1000 fatalities, and flash floods lead to the highest mortality fractions per event, i.e. the number of deaths in an event relative to the exposed population. Despite population growth and increasing flood hazards, the average number of fatalities per event has declined over time. Mortality fractions per event have decreased over time for middle- and high-middle-income countries, but increased for low-income countries. This highlights the importance of continuing and expanding risk reduction and adaptation efforts.
Regression modeling of subjective probability of river inundation with epistemic uncertainty: a short-term panel data analysis
Authors: Hidaka Ken , Ikegai Mirai , Masuda Satoki 
Published: February 2024

AbstractLack of sufficient knowledge about flood risk can lead to “don’t know” responses or non-response in risk perception surveys, and incorrect treatment of these responses can lead to bias in the results. In this study, we focus on the possibility that the “50%” response actually means “fifty-fifty” and thus reflects epistemic uncertainty in the subjective probability of river flooding. We conduct an analysis that introduces a concomitant-variable latent class model as a method to adjust for this epistemic uncertainty. The results of the analysis accounting for epistemic uncertainty suggest that risk communication, such as simulated evacuation experiences and flood-related information distribution, increases subjective probability. Moreover, the proportion of latent classes with epistemic uncertainty decreased with each successive wave of the survey, thereby suggesting that knowledge acquisition and learning through the demonstration experiment led to a reduction in epistemic uncertainty. The analysis using the evacuation decision-making model also suggested that the introduction of subjective probability contributed to improving the likelihood of the model. These results suggest that knowledge acquisition through risk communication and short-term panel survey can lead to correct risk perception estimations and influence evacuation decisions.
Temperature and school absences: evidence from England
Authors: Conte Keivabu Risto 
Published: February 2024

AbstractExtreme temperature affects children’s health, cognitive abilities, and behavior with implications for human capital accumulation. For example, several studies documented both heat and cold to decrease cognitive abilities and being consequential for test scores. An alternative, less explored pathway, by which temperature is consequential for educational achievement, is absenteeism. In this study, we explore how heat affects school attendance leveraging administrative data on more than 22,000 schools in England from the school years 2011/2012 to 2018/2019. Using a fixed-effects approach largely used in the literature, we exploit the variations in temperature by school year to estimate the effect of heat and cold days on absences. The results expose hot days to increase absences. Inquiring specific types of absences, we observe hot days to increase illness-related absences and authorized holidays. Conversely, we do not find any substantive impact of cold exposure, except for illness-related absences in energy-poor neighborhoods. In conclusion, we provide additional evidence on the impact of temperature on children and propose an alternative pathway through which societal challenges associated with climate change and energy poverty could affect human capital accumulation.