bluuebunny/crossref_metadata_2025_split huggingface dataset:
Production Function and Farmers’ Risk Aversion: A Certainty Equivalent-adjusted Production Function
Authors: Lien Gudbrand , Kumbhakar Subal C. , Mishra Ashok K. 
Published: June 2023

AbstractFaced with risky yields and returns, risk-averse farmers require a premium to take risks. In this paper, we estimate individual farmers’ degrees of risk aversion to adjust for the risk premium in returns and to replace the farmers’ realized returns with their certainty equivalent returns in the production function. In that way, the effect of the inputs on returns will automatically be risk-adjusted, i.e., we obtain risk-adjusted marginal effects of inputs, which can be used in decision-making support of farmers’ input choices in production. Using farm-level data from organic basmati rice smallholders in India, we illustrate this method using nonparametric production functions. The results show that the input elasticities and returns-to-scale estimates change when the farmers’ degree of risk aversion is taken into consideration.
Clinical and Translational Science Personas: Expansion and use cases
Authors: Gonzales Sara , Champieux Robin , Contaxis Nicole , Denton Andrea H. , Hosseini Mohammad , Surkis Alisa , Wescott Annie , Holmes Kristi 
Published: June 2023

Abstract
Twelve evidence-based profiles of roles across the Clinical and Translational Science (CTS) workforce and two patient profiles were developed by CTS Personas collaborators in 2019 as part of the CTSA Program National Center for Data to Health (CD2H). Based on feedback received from the community, CTS Personas team members collaborated to produce five additional Personas to broaden representation of the CTS workforce and enhance the existing portfolio. This paper presents the rationale and methodology used in the latest CTS Personas initiative. This work also includes an implementation scenario incorporating multiple Personas. Using the new National Institutes of Health’s (NIH) Data Management and Sharing Policy as an example, we demonstrate how administrators, researchers, support staff, and all CTS collaborators can use the Personas to respond to this new policy while considering the needs of service providers and users, CTS employees with short- and long-term needs, and interdisciplinary perspectives.
The AfD within the AfD: Radical Right Intra-Party Competition and Ideational Change
Authors: Pytlas Bartek , Biehler Jan 
Published: June 2023

AbstractThe normalization of radical right (RR) politics fosters opportunities for RR parties, but can also facilitate intra-party conflicts over the ‘true’ version of the shared party ideology. Previous research has highlighted two factors that influence ideational change within RR parties: contextual conditions and the formal power of intra-party factions. Yet, surprisingly, the Alternative for Germany (AfD) progressively radicalized to the right and witnessed the increased influence of its extremist grouping Der Flügel, despite contextual normalization pressures and the grouping's lower formal power. Analysing three crucial conflicts within the AfD between 2013 and 2021, we show how intra-party competition additionally plays into nativist party radicalization. Flügel balanced contextual and ‘hard’ power disadvantages by fostering its ‘soft’ power as ‘the true party within the party’. Simultaneously, this power was cemented by more established AfD actors who used Flügel's ideas against other competitors for office. Our conclusions have important implications for comparative research on competition within and between RR parties.
Bright or dark, vain or villainous? How entrepreneurial fitness, Machiavellianism and narcissism relate to entrepreneurial intention
Authors: Hanson Sheila K. , Valentine Sean R. , Shultz Patrick L. 
Published: June 2023

AbstractThis study investigates antecedents of entrepreneurial intentions of young adults, the next generation of entrepreneurs. We determine whether aspiring entrepreneurs' positive and dark traits relate to entrepreneurial intentions. Results indicated that entrepreneurial fitness, a second-order construct comprised of multiple positive and bright traits, positively relates to entrepreneurial intention, while the dark traits of Machiavellianism and narcissism differentially relate to entrepreneurial fitness and intention. Narcissism positively relates to entrepreneurial fitness and intention both directly and indirectly. Though Machiavellianism positively and directly relates to entrepreneurial intention, it also negatively and indirectly relates to intention through a negative relationship with entrepreneurial fitness. However, overall, entrepreneurial fitness positively relates with entrepreneurial intention. Findings extend the core model of entrepreneurial intention by concurrently illuminating the adaptive and maladaptive aspects of the dark side of narcissism and Machiavellianism with the bright, positive antecedents of entrepreneurial intention with entrepreneurial fitness. Theoretical and practical implications are discussed.
Selecting More Informative Training Sets with Fewer Observations
Authors: Kaufman Aaron R. 
Published: June 2023

AbstractA standard text-as-data workflow in the social sciences involves identifying a set of documents to be labeled, selecting a random sample of them to label using research assistants, training a supervised learner to label the remaining documents, and validating that model’s performance using standard accuracy metrics. The most resource-intensive component of this is the hand-labeling: carefully reading documents, training research assistants, and paying human coders to label documents in duplicate or more. We show that hand-coding an algorithmically selected rather than a simple-random sample can improve model performance above baseline by as much as 50%, or reduce hand-coding costs by up to two-thirds, in applications predicting (1) U.S. executive-order significance and (2) financial sentiment on social media. We accompany this manuscript with open-source software to implement these tools, which we hope can make supervised learning cheaper and more accessible to researchers.
Impact assessment of heat stress during post-silking period of summer maize in the Huang-Huai-Hai Plain, China
Authors: Fu Zhenzhen , Liu Zhijuan , Guo Shibo , Zhang Zhentao , Lu Xiaomeng , Gong Jingjin , Dong Meiqi , Yang Xiaoguang 
Published: June 2023

AbstractArising of disasters by climate change had affected crop growth and yield, and then threaten local to global food security, particularly heat stress. Therefore, hazard assessment is essential to develop effective disaster risk management and adaptation interventions to ensure food security. In this study, the accumulated heat stress days (DAY), heat stress intensity (HSI) and heat degree-days (HDD) during the post-silking period of summer maize in The Huang-Huai-Hai Plain were investigated. Based on the optimal probability distribution function of HDD and information diffusion theory, we compute heat stress classification index and the possibility of heat stress, respectively. During 1981–2019, DAY, HSI and HDD were 11.8 d, 31.9°C and 23.6°Cd and increased by 0.67 d/decade, 0.10°C/decade and 3.14°Cd/decade, respectively. The threshold and hazard probability of mild, moderate and severe heat stress were 9.4, 19.4 and 34.2°Cd and 16.6, 9.3 and 4.5%, respectively. The heat stress hazard index (M) was 0.48, ranged from 0 to 0.77 during 1981 to 2019.Mwill increase in the future at all regions, particularly after 2060. Under SSP5-8.5 climate scenario,Mranged from 0.95 to 1.20 in 2080s, about two times than historical period. This could be used in optimizing agricultural management in summer maize production in order to combat heat stress under projected climate change.
How epistemic anxiety and curiosity link perceived value and intended efforts in the language classroom
Authors: Fraschini Nicola , Tao Yu 
Published: June 2023

AbstractLanguage learner anxiety—and emotions in general—has constantly attracted academic attention in the second language acquisition (SLA) field for almost 40 years (Plonsky et al., 2022). However, within the context of the foreign language classroom, epistemic emotions remain understudied, despite their demonstrated effects on performance (D'Mello et al., 2014) and learners’ cognitive processes (Muis et al., 2018a). Epistemic emotions are academic emotions that “relate to knowledge-generating qualities of cognitive tasks and activities” (Pekrun et al., 2017, p. 1268). Their object focus lies in the generation of knowledge (Vogl et al., 2019a) and therefore are prominent during learning activities in academic settings. Recent research in SLA shows that epistemic emotions play a considerable role in instructed language learning (Fraschini, 2023; Nakamura et al., 2022). This current study analyses how two common epistemic emotions—epistemic anxiety and curiosity—mediate the link between a learner's perceived value and intended effort. Empirical data was collected using a tailor-designed survey administered to learners of Korean as a foreign language enrolled in a hybrid university course. Results show that epistemic anxiety and curiosity are independent of each other and coexist during language learning tasks. Furthermore, both epistemic emotions significantly correlate to a learner's perceived value of language learning, with opposite effects. While learners with a higher perceived value tend to be more curious, they also appear less anxious. These results are further discussed considering teachers’ and learners’ characteristics and in relation to theoretical and pedagogical implications for the language classroom.
“My Biggest Fear Is She’ll Die Alone”: Care Partner Perspectives of Institutional COVID-19 Visitor Restrictions in Ontario, Canada
Authors: Reid Julie C. , Carbone Sarah , Shaw Julia F. , Gallibois Molly , Hawkins Stacey A. 
Published: June 2023

AbstractIn March 2020, the Government of Ontario, Canada implemented public health measures, including visitor restrictions in institutional care settings, to protect vulnerable populations, including older adults (> 65 years), against COVID-19 infection. Prior research has shown that visitor restrictions can negatively influence older adults’ physical and mental health and can cause increased stress and anxiety for care partners. This study explores the experiences of care partners separated from the person they care for because of institutional visitor restrictions during the COVID-19 pandemic. We interviewed 14 care partners between the ages of 50 and 89; 11 were female. The main themes that emerged were changing public health and infection prevention and control policies, shifting care partner roles as a result of visitor restrictions, resident isolation and deterioration from the care partner perspective, communication challenges, and reflections on the impacts of visitor restrictions. Findings may be used to inform future health policy and system reforms.
Prediction of the onset of shear localization based on machine learning
Authors: Akar Samet , Aylı Ece , Ulucak Oğuzhan , Uğurer Doruk 
Published: June 2023

Abstract
Predicting the onset of shear localization is among the most challenging problems in machining. This phenomenon affects the process outputs, such as machining forces, surface quality, and machined part tolerances. To predict this phenomenon, analytical, experimental, and numerical methods (especially finite element analysis) are widely used. However, the limitations of each method hinder their industrial applications, demanding a reliable and time-saving approach to predict shear localization onset. Additionally, since this phenomenon largely depends on the type and parameters of the constitutive material model, any change in these parameters requires a new set of simulations, which puts further restrictions on the application of finite element modeling. This study aims to overcome the computational efficiency of the finite element method to predict the onset of shear localization when machining Ti6Al4V using machine learning methods. The obtained results demonstrate that the FCM (fuzzy c-means) clustering ANFIS (adaptive network-based fuzzy inference system) has given better results in both training and testing when it is compared to the ANN (artificial neural network) architecture with an R2 of 0.9981. Regarding this, the FCM-ANFIS is a good candidate to calculate the critical cutting speed. To the best of the authors’ knowledge, this is the first study in the literature that uses a machine learning tool to predict shear localization.
The Role of Exceptionalism in the Evolution of Bioethical Regulation
Authors: Shevchenko Sergei , Zhavoronkov Alexey 
Published: June 2023

AbstractThe paper aims to present a critical analysis of the phenomenon and notion of exceptionalism in bioethics. The authors demonstrate that exceptionalism pertains to phenomena that are not (yet) entirely familiar to us and could potentially bear risks regarding their regulation. After an overview of the state of the art, we briefly describe the origins and evolution of the concept, compared to exception and exclusion. In the second step, they look at the overall development debates on genetic exceptionalism, compared to other bioethical debates on exceptionalism, before presenting a detailed analysis of a specific case of early regulation of genetic screening. In the last part, the authors explain the historical background behind the connection between exceptionalism and exclusion in these debates. Their main conclusion is that while the initial stage of the discussion is shaped by the concept of exceptionalism and awareness of risks of exclusion, the later development centers around exceptions that are needed in detailed regulatory procedures.
Liquid storage of porcine in vitro-produced blastocysts; a practical approach for short storage
Authors: Haug Linda Marijke , Jochems Reina , Gaustad Ann Helen , Kommisrud Elisabeth , Myromslien Frøydis Deinboll , Grindflek Eli , Alm-Kristiansen Anne Hege 
Published: June 2023

SummaryCommercial application of embryo transfer in pig breeding is dependent on the storage of embryos. The aim of this study was to assess the embryo quality of in vitro-produced blastocysts after 3 h liquid storage at 37°C in CO2-free medium by evaluating morphology, in vitro developmental capacity and apoptosis. Blastocysts at days 5 and 6 post-fertilization were randomly allocated to the storage group (HEPES-buffered NCSU-23 medium including bovine serum albumin in a portable embryo transport incubator at 37°C) or a control group (porcine blastocyst medium in a conventional culture incubator). Thereafter, blastocysts were evaluated for morphology and stained to assess apoptosis straight after the 3 h storage period or after a further 24 h conventional incubation. There was no significant difference between the storage and control group after 3 h storage and the further 24 h conventional incubation for any of the parameters, nor for apoptosis straight after the 3 h storage. Embryos that reached the blastocyst stage at day 5 showed less apoptosis (6.6% vs 10.9%, P = 0.01) and a trend for a higher rate of developmental capacity (70.6% vs 51.5%, P = 0.089) than embryos reaching the blastocyst stage on day 6. In conclusion, in vitro-produced porcine blastocysts can be stored for 3 h at physiological temperature in transportable incubators using a CO2-independent medium without compromising quality.
Shirin Nezammafi and the unmaking of postcolonial Japan
Authors: Ghadimi Amin 
Published: June 2023

AbstractThis article takes up the short work of fiction Salam, written in Japanese in 2006 by Shirin Nezammafi, and deploys it as a primary source in the history of the Japanese present. Salam tells the tale of Layla, an Afghan migrant detained in and then expelled from Japan in 2001. The article argues that Salam exposes the unmaking of postcolonial Japan: if postcolonial Japan meant a territorial, sovereign nation-state built on hegemonic national myths, then now it is unsustainable. Salam calls to an inevitable if uncharted post-national, post-territorial future. To advance this argument, the article focuses on Nezammafi's treatment of three humanistic categories tied up with geopolitical territoriality: language, art, and gender. These categories, when associated with the nation-state, generate irony in Salam. That irony stems from the anachronism of nations: territorial nations, Japanese or otherwise, appear as past entities that have outlived their possibility.
Perceiving law without colonialism: Revisiting courts and constitutionalism in South Asia
Authors: Farid Cynthia 
Published: June 2023

AbstractThis article argues that the colonial government in India was shaped by changes in property law, race relations and other institutional interests that accompanied the political and economic restructuring of the colonial state. Therefore, the development of constitutionalism was the outcome of an interplay between institutional and professional interests and larger socio-economic and political forces. Against the backdrop of empire, constitutionalism in British India was defined by a specific form of allocation of powers between the executive (which also exercised legislative powers) and the high courts. The structure that developed as a result was a strong executive government, particularly in its exercise of power in local districts with formal judicial scrutiny introduced after 1861. The relationship between the executive and the judiciary in localities generated a series of conflicts and tensions, which were exacerbated by the expansion of the bureaucracy, the legal profession and gradual inclusion of Indians in the upper strata of governance. Taken together, these factors led to the development of a hybrid model of separation of powers in the Indian subcontinent, which seems to have stood the test of time in post-colonial countries of South Asia despite political elites having invested considerable resources on constitutional reform.
Monitoring Deep Sea Currents With Seafloor Distributed Acoustic Sensing
Authors: Mata Flores Daniel , Sladen Anthony , Ampuero Jean‐Paul , Mercerat E. Diego , Rivet Diane 
Published: June 2023

AbstractUnderwater fiber optic cables commonly traverse a variety of seafloor conditions, which leads to an uneven mechanical coupling between the cable and the ocean bottom. On rough seafloor bathymetry, some cable portions might be suspended and thus susceptible to vortex‐induced vibrations (VIV) driven by deep ocean currents. Here, we examine the potential of distributed acoustic sensing (DAS) to monitor deep‐sea currents along suspended sections of underwater telecom fiber optic cables undergoing VIV. Oscillations of a seafloor fiber optic cable located in southern France are recorded by DAS along cable sections presumably hanging. Their characteristic frequencies are lower than 1 Hz, at different ocean depths, and have an amplitude‐dependency consistent with the driving mechanism being VIV. Based on a theoretical proportionality between current speed and VIV frequencies, we derive ocean current speed time series at 2,390 m depth from the vortex shedding frequencies recorded by DAS. The DAS‐derived current speed time series is in agreement with recordings by a current meter located 3.75 km away from the hanging cable section (similar dominant period, high correlation after time shift). The DAS‐derived current speed time series displays features, such as characteristic periods and spectral decay, associated with the generation of internal gravity waves and weak oceanic turbulence in the Mediterranean Sea. The results demonstrate the potential of DAS along hanging segments of fiber optic cables to monitor a wide range of oceanography processes, at depths barely studied with current instrumentation.
Exploring the Influence of Summer Temperature on Human Mobility During the COVID‐19 Pandemic in the San Francisco Bay Area
Authors: Ly Amina , Davenport Frances V. , Diffenbaugh Noah S. 
Published: June 2023

AbstractStudies on the relationship between temperature and local, small scale mobility are limited, and sensitive to the region and time period of interest. We contribute to the growing mobility literature through a detailed characterization of the observed temperature‐mobility relationship in the San Francisco Bay Area at fine spatial and temporal scale across two summers (2020–2021). We used anonymized cellphone data from SafeGraph's neighborhood patterns data set and gridded temperature data from gridMET, and analyzed the influence of incremental changes in temperature on mobility rate (i.e., visits per capita) using a panel regression with fixed effects. This strategy enabled us to control for spatial and temporal variability across the studied region. Our analysis suggested that all areas exhibited lower mobility rate in response to higher summer temperatures. We then explored how several additional variables altered these results. Extremely hot days resulted in faster mobility declines with increasing temperatures. Weekdays were often more resistant to temperature changes when compared to the weekend. In addition, the rate of decrease in mobility in response to high temperature was significantly greater among the wealthiest census block groups compared with the least wealthy. Further, the least mobile locations experienced significant differences in mobility response compared to the rest of the data set. Given the fundamental differences in the mobility response to temperature across most of our additive variables, our results are relevant for future mobility studies in the region.
The Deep‐Learning‐Based Fast Efficient Nighttime Retrieval of Thermodynamic Phase From Himawari‐8 AHI Measurements
Authors: Tong Xuan , Li Jingwei , Zhang Feng , Li Wenwen , Pan BaoXiang , Li Jun , Letu Husi 
Published: June 2023

AbstractRetrieval of the cloud thermodynamic phase (CP) is essential for satellite remote sensing and downstream applications. However, there is still a lack of efficient nighttime CP data products. A transfer‐learning‐based deep learning model, transfer‐learning‐ResUnet, is proposed to retrieve the nighttime CP of Himawari‐8 from thermal infrared channels. Cloud products of Himawari‐8 and Moderate‐resolution Imaging Spectroradiometers were selected as labels during training. A benchmark obtained by the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations confirmed the accuracy of the CP retrieval. During three independent months, the daytime and nighttime retrieval accuracy of the CP was 0.867 and 0.816, respectively, which was superior to that of the Himawari‐8 operational product in the daytime (0.788).
Implementation and Testing of Radar Data Assimilation Capabilities Within the Joint Effort for Data Assimilation Integration Framework With Ensemble Transformation Kalman Filter Coupled With FV3‐LAM Model
Authors: Park Jun , Xue Ming , Liu Chengsi 
Published: June 2023

AbstractCapabilities to directly assimilate radar data are implemented within the local ensemble transform Kalman filter (LETKF) and the gain‐form LETKF (LGETKF) algorithms of the Joint Effort for Data assimilation Integration (JEDI) system. The capabilities are evaluated for the analysis and forecast of a severe convection case of 20 May 2019 in the Southern Great Plains using the limited area model version of the FV3 dynamical core (FV3‐LAM) from a recent release for Short‐Range Weather Application (SRW App). The LETKF and LGETKF implementations are shown to produce analyses and short‐range forecasts comparable to those using the ensemble square‐root Kalman Filter (EnSRF) within the Gridpoint Statistical Interpolation (GSI) framework used by current NCEP operational models. In addition, LGETKF retaining only 60% variances for model‐space vertical localization performs similarly to LGETKF retaining 99% of variance and LETKF using observation error‐based vertical localization. JEDI LETKF shows better parallel scalability than LGETKF and GSI EnSRF.