bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment of health state utilities associated with adult and pediatric acid sphingomyelinase deficiency (ASMD)
Authors: Matza Louis S. , Stewart Katie D. , Fournier Marie , Rowen Donna , Lachmann Robin , Scarpa Maurizio , Mengel Eugen , Obermeyer Travis , Ayik Evren , Laredo Fernando , Pulikottil-Jacob Ruth
Published: February 2024

Introduction

Acid sphingomyelinase deficiency (ASMD) type B is a rare genetic disorder leading to enlargement of the spleen and liver, pulmonary dysfunction, and other symptoms. Cost-utility analyses are often conducted to quantify the value of new treatments, and these analyses require health state utilities. Therefore, the purpose of this study was to estimate utilities associated with varying levels of severity of adult and pediatric ASMD type B.

Methods

Seven adult and seven child health state vignettes describing ASMD were developed based on published literature, clinical trial results, and interviews with clinicians, patients with ASMD, and parents of children with ASMD. The health states were valued in time trade-off interviews with adult general population respondents in the UK.

Results

Interviews were completed with 202 participants (50.0% female; mean age = 41.3 years). The health state representing ASMD without impairment had the highest mean utility for both the adult and child health states (0.92/0.94), and severe ASMD had the lowest mean utility (0.33/0.45). Every child health state had a significantly greater utility than the corresponding adult health state. Differences between adult/child paired states ranged from 0.02 to 0.13. Subgroup analyses explored the impact of parenting status on valuation of child health states.

Discussion

Greater severity of ASMD was associated with lower mean utility. Results have implications for valuation of pediatric health states. The resulting utilities may be useful in cost-utility modeling estimating the value of treatment for ASMD.
The past, present, and a future for native charr in Japan
Authors: Fausch Kurt D. , Morita Kentaro , Tsuboi Jun-ichi , Kanno Yoichiro , Yamamoto Shoichiro , Kishi Daisuke , Dunham Jason B. , Koizumi Itsuro , Hasegawa Koh , Inoue Mikio , Sato Takuya , Kitano Satoshi
Published: February 2024

Charrs (Salvelinus) reach their southernmost distribution in Japan, and are uniquely adapted to the short, steep streams of this island archipelago. Southern Asian Dolly Varden (Salvelinus curilus) occur only in Hokkaido Island, whereas white-spotted charr (Salvelinus leucomaenis) range to southern Honshu. Both species diverged from an ancestral lineage during the late Pliocene/early Pleistocene, when lowered sea levels created semi-enclosed water bodies in the seas of Japan and Okhotsk. Genetic analyses showed S. curilus represents the most ancient divergence from the Dolly Varden (Salvelinus malma) - Arctic charr (Salvelinus alpinus) group, and revealed five lineages of S. leucomaenis which align differently than traditional subspecies. Japanese charr display diverse and flexible life histories including anadromous fish with partial migration, and fluvial, adfluvial, and resident forms. In Hokkaido, Dolly Varden are distributed upstream and white-spotted charr downstream. They coexist in narrow sympatric zones through adaptive shifts by Dolly Varden in behavior and morphology that facilitate benthic foraging. Both species hybridize with native and nonnative salmonids, and are displaced from microhabitats and decline in abundance when rainbow trout (Oncorhynchus mykiss) and brown trout (Salmo trutta) invade. Japan streams contain over 95,000 erosion control dams which create short stream fragments (medians ~200 m). This has increased extirpation of charr populations via lower genetic diversity and stochastic and demographic factors. Tributaries provide complex rearing habitats, afford refuges from floods, and supply recruits that sustain populations in mainstem fragments and create metapopulations in connected riverscapes. Charr play central roles in linked stream-riparian food webs, and cause direct and indirect effects that cascade to streambed algae and riparian predators when linkages are disrupted by anthropogenic effects or altered by native parasites. Many charr populations are threatened by habitat fragmentation and introgression or invasion by nonnative forms, but efforts to conserve charr are growing. These include restoring connectivity among pure populations above barriers that prevent invasions, protecting tributary nurseries, and instituting angling regulations to protect headwater populations. Key steps include inventorying pure populations, identifying conservation units, selecting appropriate management based on connectivity and biotic interactions, and engaging stakeholders and youth to engender an ethic for conserving irreplaceable charr lineages.
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

The 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

This 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

Landfill 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

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

Severe 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

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

College 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

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

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

This 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

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

Floods 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

Lack 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

Extreme 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.
Destructive and non-destructive measurement approaches and the application of AI models in precision agriculture: a review
Authors: Islam Maidul , Bijjahalli Suraj , Fahey Thomas , Gardi Alessandro , Sabatini Roberto , Lamb David W.
Published: February 2024

The estimation of pre-harvest fruit quality and maturity is essential for growers to determine the harvest timing, storage requirements and profitability of the crop yield. In-field fruit maturity indicators are highly variable and require high spatiotemporal resolution data, which can be obtained from contemporary precision agriculture systems. Such systems exploit various state-of-the-art sensors, increasingly relying on spectrometry and imaging techniques in association with advanced Artificial Intelligence (AI) and, in particular, Machine Learning (ML) algorithms. This article presents a critical review of precision agriculture techniques for fruit maturity estimation, with a focus on destructive and non-destructive measurement approaches, and the applications of ML in the domain. A critical analysis of the advantages and disadvantages of different techniques is conducted by surveying recent articles on non-destructive methods to discern trends in performance and applicability. Advanced data-fusion methods for combining information from multiple non-destructive sensors are increasingly being used to develop more accurate representations of fruit maturity for the entire field. This is achieved by incorporating AI algorithms, such as support vector machines, k-nearest neighbour, neural networks, and clustering. Based on an extensive survey of recently published research, the review also identifies the most effective fruit maturity indices, namely: sugar content, acidity and firmness. The review concludes by highlighting the outstanding technical challenges and identifies the most promising areas for future research. Hence, this research has the potential to provide a valuable resource for the growers, allowing them to familiarize themselves with contemporary Smart Agricultural methodologies currently in use. These practices can be gradually incorporated from their perspective, taking into account the availability of non-destructive techniques and the use of efficient fruit maturity indices.
UAV-based canopy monitoring: calibration of a multispectral sensor for green area index and nitrogen uptake across several crops
Authors: Bukowiecki Josephine , Rose Till , Holzhauser Katja , Rothardt Steffen , Rose Maren , Komainda Martin , Herrmann Antje , Kage Henning
Published: February 2024

The fast and accurate provision of within-season data of green area index (GAI) and total N uptake (total N) is the basis for crop modeling and precision agriculture. However, due to rapid advancements in multispectral sensors and the high sampling effort, there is currently no existing reference work for the calibration of one UAV (unmanned aerial vehicle)-based multispectral sensor to GAI and total N for silage maize, winter barley, winter oilseed rape, and winter wheat.

In this paper, a practicable calibration framework is presented. On the basis of a multi-year dataset, crop-specific models are calibrated for the UAV-based estimation of GAI throughout the entire growing season and of total N until flowering. These models demonstrate high accuracies in an independent evaluation over multiple growing seasons and trial sites (mean absolute error of 0.19–0.48 m2 m−2 for GAI and of 0.80–1.21 g m−2 for total N). The calibration of a uniform GAI model does not provide convincing results. Near infrared-based ratios are identified as the most important component for all calibrations. To account for the significant changes in the GAI/ total N ratio during the vegetative phase of winter barley and winter oilseed rape, their calibrations for total N must include a corresponding factor. The effectiveness of the calibrations is demonstrated using three years of data from an extensive field trial. High correlation of the derived total N uptake until flowering and the whole-season radiation uptake with yield data underline the applicability of UAV-based crop monitoring for agricultural applications.
All That Glitters is Not Gold: Examining the Negative Impact of Real Estate Value on Companies' Market Competitiveness
Authors: Liang Fangzhi , Tian Gary Gang , Wei Zhihua , Zeng Aimin
Published: February 2024

This paper introduces and investigates the hypothesis that the crowding-out effect surpasses the collateral effect, suggesting that an increase in the value of real estate holdings by companies hinders their competitiveness in the product market within emerging economies. Through our analysis, we elucidate the underlying mechanism, demonstrating that although Chinese listed companies benefit from their real estate holdings in terms of debt financing, these financial resources are predominantly reinvested in real estate projects rather than other productive endeavors. This effect is particularly pronounced when companies face significant financial constraints, operate in highly monopolistic industries, and are situated in regions where local governments heavily rely on land finance and face substantial pressure for GDP growth. By shedding light on the adverse implications of companies' real estate holdings and uncovering the factors contributing to the crowding-out effect, our research underscores the importance of enhanced regulations in the real estate markets of developing nations during the periods of irrational housing booms.
Contributions to the Legal Semiotics of Facial Recognition Systems: Live Music, Digital Technologies, and the Display of Power
Authors: Marino Gabriele
Published: February 2024

The use of facial recognition systems in concerts provides a perfect pretext to semiotically discuss the role of the face in contemporary culture, identifying different strategies and axiologies (systems of values). In his visionary essay Bruits (“noises”) from 1977, the French thinker Jacques Attali establishes a close connection between music and power and locates it in the site of the collective unfolding of music: the concert hall. Following this hint, the article reconstructs the current debate on facial recognition systems in the music business, with a particular focus on concerts and festivals. The different positions (of musicians, authorities, and professionals) are outlined (some are openly in favor, others openly against), key moments are identified (Beyoncé’s concert in Cardiff, 2017; Jacky Cheung’s in Nanchang, 2018; Taylor Swift’s at the Rose Bowl in Pasadena, 2018; the “banfacialrecognition.com” campaign launched in 2019; the case of Barbara Hart at Brandi Carlile’s show at the Madison Square Garden, 2022) and, finally, the issue is framed within the broader debate about the face as an indexical marker of presence, identity, and humanity (the contrast between Italian philosopher Giorgio Agamben and American sociologist and design theorist Benjamin Bratton is addressed).
Multi-way Analysis of the Gender Dimension of the Sustainable Development Goals
Authors: Medina-Hernández Edith Johana , Fernández-Gómez María José
Published: February 2024

The gender dimension of the Sustainable Development Goals (SDG) is integral to the goals established to foster the development of nations, as it is intertwined with other goals and enhances their attainability. Thus, this study examines 28 indicators belonging to the goals of the sustainable development objectives, distinguishing between the gender SDGs (6 indicators) and other SDGs (22 indicators), all of which were reported by 110 countries in the year 2023. The assessment considers four regions: the African continent (28 countries), the Americas region (21 countries), Asia-Oceania (29 countries), and Europe (32 countries). The STATICO multivariate technique is used (consisting of four Co-inertia analyses and one Partial Triadic Analysis) to study the interactions among the indicators. The goal is to determine whether differences or similarities exist between these indicators within each region and to make a comparative assessment across countries. The study’s findings show the existing covariances between the various targets of the 2030 Agenda and indicate that in Europe, the gender dimension is more closely integrated with the other SDGs than in the other regions. In Africa, substantial variations between countries are observed, while Asia, Oceania, and the Americas face challenges in specific indicators and countries in terms of achieving sustainable development.
RL-CoPref: a reinforcement learning-based coordinated prefetching controller for multiple prefetchers
Authors: Yang Huijing , Fang Juan , Su Xing , Cai Zhi , Wang Yuening
Published: February 2024

Modern processors employ data prefetchers to alleviate the impact of long memory access latency. However, current prefetchers are designed for specific memory access patterns, which perform poorly on mixed applications with multiple memory access patterns. To address these issues, RL-CoPref, a reinforcement learning (RL)-based coordinated prefetching controller for multiple prefetchers, is proposed in this paper. RL-CoPref takes diverse program context information as the input, learns to maximize cumulative rewards, and evaluates prefetch quality based on prefetch hits/misses and memory bandwidth utilization. It can dynamically adjust the prefetch activation and prefetch degree, enabling multiple prefetchers to complement each other on mixed applications. Our extensive evaluation, utilizing the ChampSim simulator, demonstrates that RL-CoPref can effectively adapt to various workloads and system configurations, optimizing prefetch control. On average, RL-CoPref achieves 76.15% prefetch coverage, having 35.50% IPC improvement, outperforming state-of-the-art individual prefetchers by 5.91–16.54% and outperforming SBP, a state-of-the-art (non-RL) prefetch controller, by 4.64%.
A comparative study on the occurrence, genetic characteristics, and factors associated with the distribution of Listeria species on cattle farms and beef abattoirs in Gauteng Province, South Africa
Authors: Gana J. , Gcebe N. , Moerane R. , Ngoshe Y. B. , Tshuma T. , Moabelo K. , Adesiyun A. A.
Published: February 2024

These cross-sectional studies reported the occurrence, genetic characteristics, and factors associated with the distribution of Listeria species on cattle farms and beef abattoirs in Gauteng Province, South Africa. A total of 328 samples (faeces, feeds, silage, and drinking water) were collected from 23 cattle farms (communal, cow-calf, and feedlot), and 262 samples (faeces, carcass swabs, and effluents) from 8 beef abattoirs (low throughput and high throughput) were processed using standard bacteriological and molecular methods to detect Listeria species. The factors associated with the prevalence of Listeria species were investigated, and multiplex polymerase chain reaction (mPCR) was used to determine Listeria species, the pathogenic serogroups, and the carriage of eight virulence-associated genes by Listeria monocytogenes. The overall prevalence of Listeria species in cattle farms was 14.6%, comprising Listeria innocua (11.3%), Listeria monocytogenes (3.4%), Listeria welshimeri (0.0%) compared with 11.1%, comprising Listeria innocua (5.7%), Listeria monocytogenes (4.6%), Listeria welshimeri (0.8%) for beef abattoirs. Of the three variables (area, type of farm/abattoir, and sample type) investigated, only the sample types at abattoirs had a significant (P < 0.001) effect on the prevalence of L. innocua and L. welshimeri. The frequency of distribution of the serogroups based on 11 L. monocytogenes isolated from farms was 72.7% and 27.3% for the serogroup 1/2a-3a and 4b-4d-4e, respectively, while for the 12 L. monocytogenes isolates recovered from abattoirs, it was 25%, 8.3%, 50% and 16.7% for the serogroup 1/2a-3a, 1/2b-3b, 1/2c-3c, and 4b-4d-4e respectively (P < 0.05). All (100%) isolates of L. monocytogenes from the farms and abattoirs were positive for seven virulence genes (hlyA, inlB, plcA, iap, inlA, inlC, and inlJ). The clinical and food safety significance of the findings cannot be ignored.
Analyzing Urban Drinking Water System Vulnerabilities and Locating Relief Points for Urban Drinking Water Emergencies
Authors: Garajeh Mohammad Kazemi , Feizizadeh Bakhtiar , Salmani Behnam , Ghasemi Mohammad
Published: February 2024

Urban water is known as a critical sector of urban environments which significantly impacts the life quality and wellbeing of reinstates. In the context of developing sustainable urban drinking system it is critical to analyze network events and develop sufficient systems of water supply. To the best of our knowledge, fewer studies have examined the potential of automated-based approaches such as deep learning convolutional neural network (DL-CNN) for analyzing urban water network events and identifying the optimal location of urban drinking water relief posts. Therefore, the current study aims to propose an efficient approach for Geospatial based urban water network events analyze and determine the optimal location of urban drinking water relief posts in Zanjan. For this goal, first, we prepared and preprocessed various predisposing variables for analyzing the urban water network events and determining the optimal location of urban drinking water relief posts. We then applied an integrated approach of analytical network process (ANP) and DL-CNN methods to locate the best location of urban drinking water relief posts. Finally, intersection over union and accuracy assessment were employed to evaluate the performance of the results. Our findings show that the DL-CNN performed well with an accuracy of 0.942 compared to the ANP (0.895) for determining the optimal location of urban drinking water relief posts. According to the results, the best place to build a relief post is in the city center, and the surrounding areas may not be suitable, which is in accordance with field work analysis. The results of the study also reveal that areas 5 and 3 are at high risk from the number of urban water network events perspective, which requires the construction of urban water relief stations.
An analysis on the effect of body tissues and surgical tools on workflow recognition in first person surgical videos
Authors: Tomita Hisako , Ienaga Naoto , Kajita Hiroki , Hayashida Tetsu , Sugimoto Maki
Published: February 2024

Purpose

Analysis of operative fields is expected to aid in estimating procedural workflow and evaluating surgeons’ procedural skills by considering the temporal transitions during the progression of the surgery. This study aims to propose an automatic recognition system for the procedural workflow by employing machine learning techniques to identify and distinguish elements in the operative field, including body tissues such as fat, muscle, and dermis, along with surgical tools.

Methods

We conducted annotations on approximately 908 first-person-view images of breast surgery to facilitate segmentation. The annotated images were used to train a pixel-level classifier based on Mask R-CNN. To assess the impact on procedural workflow recognition, we annotated an additional 43,007 images. The network, structured on the Transformer architecture, was then trained with surgical images incorporating masks for body tissues and surgical tools.

Results

The instance segmentation of each body tissue in the segmentation phase provided insights into the trend of area transitions for each tissue. Simultaneously, the spatial features of the surgical tools were effectively captured. In regard to the accuracy of procedural workflow recognition, accounting for body tissues led to an average improvement of 3 % over the baseline. Furthermore, the inclusion of surgical tools yielded an additional increase in accuracy by 4 % compared to the baseline.

Conclusion

In this study, we revealed the contribution of the temporal transition of the body tissues and surgical tools spatial features to recognize procedural workflow in first-person-view surgical videos. Body tissues, especially in open surgery, can be a crucial element. This study suggests that further improvements can be achieved by accurately identifying surgical tools specific to each procedural workflow step.
Whose “place” is it? Using corpus-based techniques to sketch place-based sustainability discourses in public and academic forums
Authors: Wearne Samuel , Riedy Christopher
Published: February 2024

Calls for a “place-based” approach to sustainability are increasingly common in the field of sustainability transitions and transformations (STT). To critically explore the agendas and politics a call towards place carries, we undertook a corpus-assisted discourse study (CADS) to examine a sample of public and academic texts from 2019 to 2020. Two distinct discourses about place were evident: an environmental discourse framing place as an assemblage of more-than-human constituents and an anthropocentric discourse framing place as a human community. These discourses present vastly different priorities about which species matter, what change entails, and what kind of future we should create. Our findings reflect the emergence of a discourse coalition that advocates for a place-based approach to STT, and we discuss how this viewpoint has continued to emerge since the compilation of our data. Our paper provides an overview of the discursive landscape we encountered, synthesises a central narrative about place-based STT based on what we observed, and provides a critical discussion of the tensions and opportunities that this narrative raises. In doing so, we suggest there remains an opportunity for fruitful dialogue amongst sustainability educators, sustainability practitioners, and researchers to refine what a place-based approach to STT looks like. By demonstrating an application of CADS, we hope to show how digital tools and techniques can be used to research discourses in sustainability. We outline specific opportunities to take this forward, including a broad opportunity to use web-derived corpora to help survey discursive landscapes, and a more specific application to explore discursive dynamics between communities, places, and at different spatial scales.