bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interruptions in HIV and Behavioral Health Care for Criminal-Legal Involved People Living with HIV Following Implementation of Decarceration and Shelter in Place in San Francisco, California
Authors: Clemenzi-Allen A. Asa , Hebert Jillian , Reid Michael Alistair , Mains Tyler , Hammer Hali , Gandhi Monica , Pratt Lisa , Wesson Paul 
Published: December 2023

AbstractDecarceration policies, enacted for SARS-CoV-2 mitigation in carceral settings, potentially exacerbated barriers to care for people living with HIV (PWH) with criminal legal involvement (CLI) during Shelter-in-Place (SIP) by limiting opportunities for engagement in provisions of HIV and behavioral health care. We compared health care engagement for PWH with CLI in San Francisco, California before and after decarceration and SIP using interrupted time series analyses. Administrative data identified PWH booked at the San Francisco County Jail with at least one clinic encounter from 01/01/2018-03/31/2020 within the municipal health care network. Monthly proportions of HIV, substance use, psychiatric and acute care encounters before (05/01/2019-02/29/2020) and after (03/01/2020-12/31/2020) SIP and decarceration were compared using Generalized Estimating Equation (GEE) log-binomial and logistic regression models, clustering on the patient-level. Of 436 patients, mean age was 43 years (standard-deviation 11); 88% cisgender-male; 39% white, 66% homeless; 67% had trimorbidity by Elixhauser score (medical comorbidity, psychotic disorder or depression, and substance use disorder). Clinical encounters immediately dropped following SIP for HIV (aOR = 0.77; 95% CI: 0.67, 0.90) and substance use visits (aRR = 0.83; 95% CI: 0.70, 0.99) and declined in subsequent months. Differential reductions in clinical encounters were seen among Black/African Americans (aRR = 0.93; 95% CI: 0.88, 0.99) and people experiencing homelessness (aRR = 0.92; 95% CI: 0.87, 0.98). Significant reductions in care were observed for PWH with CLI during the COVID-19 pandemic, particularly among Black/African Americans and people experiencing homelessness. Strategies to End the HIV Epidemic must improve engagement across diverse care settings to improve outcomes for this key population.
Artificial intelligence in compulsory level of education: perspectives from Namibian in-service teachers
Authors: Jatileni Cloneria Nyambali , Sanusi Ismaila Temitayo , Olaleye Sunday Adewale , Ayanwale Musa Adekunle , Agbo Friday Joseph , Oyelere Peter B. 
Published: December 2023

AbstractWith the push to integrate Artificial Intelligence (AI) from kindergarten to twelfth-grade levels comes a need for equipped teachers. However, there needs to be more initiative in professional learning opportunities, which demands the required effort to ensure teachers learn the AI content they will be teaching. To design an effective professional development program, understanding teachers' existing knowledge, interest and disposition towards AI is crucial to devise strategies that could best support the teachers. As a result, this study aims to investigate in-service teachers' perspectives of teaching AI in schools from the perspective of planned behavior theory. Using a 7-factor scale of AI Anxiety, AI Readiness, AI Relevance, Attitude towards using AI, AI for Social Good, Confidence in AI and Behavioral Intention. This study sampled 159 in-service teachers in Namibia. The teachers' responses were analyzed with SmartPLS using Structural Equation Modelling and various Multigroup Analysis techniques. This study found that teachers' behavioral intention to teach AI depends on a combination of factors, including the relevance of AI, attitude towards using AI, the use of AI for social good and confidence. Meanwhile, AI Anxiety and readiness could not be linked to the intention to teach AI. We discussed our findings, highlighted the study implication, and suggested future directions.
Modelling STEM learners’ academic performance in advanced level secondary schools with smart classrooms in Rwanda
Authors: Ngendahayo Emmanuel , Habarurema Jean Baptiste , Limone Pierpaolo , Zhang Wenlan 
Published: December 2023

AbstractSmart classroom setting is an effective technology-enhanced pedagogy when an instructor capitalises on the key drivers underlying its success. The objectives of the study are twofold. First, to investigate the factors that impact learners’ academic performance in the smart classroom setting. Second, to determine whether learners’ performance varies based on their gender and prior experience in the smart classroom. Three schools were selected and sampled from a pool of public advanced level (A’ Level) STEM secondary schools with smart classrooms in Rwanda because they were among the first to set up smart classrooms. Data were randomly obtained from 389 learners, majoring in six different combinations. Exploratory factor analysis (EFA) was used to assess the validity and reliability of the measurement scale. A valid and thought-provoking learners’ academic performance model, to enhance their learning outcomes, is presented. The model was validated using Structural equation modelling (SEM). The results indicated that technology self-efficacy, perceived ease of use, and learning satisfaction were all predictors of learners’ performance. Learners’ perceived ease of use and satisfaction were direct predictors of their performance. Besides, learners’ perceived ease of use and usefulness were directly affected by technology self-efficacy. On the other hand, technology self-efficacy indirectly impacts learners’ performance. The invariance analysis across gender groups revealed that male learners perceive smart classroom technology to be easier to use than females. Meanwhile, no evidence of metric invariance estimation of experience was found. We argue that effective pedagogical approaches can mitigate gender disparities in perceived usability of smart classroom technologies.
Seed treatment with clothianidin induces changes in plant metabolism and alters pollinator foraging preferences
Authors: Klatt Björn K. , Wurz Annemarie , Herbertsson Lina , Rundlöf Maj , Svensson Glenn P. , Kuhn Jürgen , Vessling Sofie , de La Vega Bernardo , Tscharntke Teja , Clough Yann , Smith Henrik G. 
Published: December 2023

AbstractNeonicotinoids, systemic insecticides that are distributed into all plant tissues and protect against pests, have become a common part of crop production, but can unintentionally also affect non-target organisms, including pollinators. Such effects can be direct effects from insecticide exposure, but neonicotinoids can affect plant physiology, and effects could therefore also be indirectly mediated by changes in plant phenology, attractiveness and nutritional value. Under controlled greenhouse conditions, we tested if seed treatment with the neonicotinoid clothianidin affected oilseed rape’s production of flower resources for bees and the content of the secondary plant products glucosinolates that provide defense against herbivores. Additionally, we tested if seed treatment affected the attractiveness of oilseed rape to flower visiting bumblebees, using outdoor mesocosms. Flowers and leaves of clothianidin-treated plants had different profiles of glucosinolates compared with untreated plants. Bumblebees in mesocosms foraged slightly more on untreated plants. Neither flower timing, flower size nor the production of pollen and nectar differed between treatments, and therefore cannot explain any preference for untreated oilseed rape. We instead propose that this small but significant preference for untreated plants was related to the altered glucosinolate profile caused by clothianidin. Thereby, this study contributes to the understanding of the complex relationships between neonicotinoid-treated crops and pollinator foraging choices, by suggesting a potential mechanistic link by which insecticide treatment can affect insect behavior.
Transmission probability of gas molecules through porous layers at Knudsen diffusion
Authors: Macher Wolfgang , Skorov Yuri , Kargl Günter , Laddha Sunny , Zivithal Stephan 
Published: December 2023

AbstractGas flow through layers of porous materials plays a crucial role in technical applications, geology, petrochemistry, and space sciences (e.g., fuel cells, catalysis, shale gas production, and outgassing of volatiles from comets). In many applications the Knudsen regime is predominant, where the pore size is small compared to the mean free path between intermolecular collisions. In this context common parameters to describe the gas percolation through layers of porous media are the probability of gas molecule transmission and the Knudsen diffusion coefficient of the medium. We show how probabilistic considerations on layer partitions lead to the analytical description of the permeability of a porous medium to gas flow as a function of layer thickness. The derivations are made on the preconditions that the molecule reflection at pore surfaces is diffuse and that the pore structure is homogenous on a scale much larger than the pore size. By applying a bi-hemispherical Maxwell distribution, relations between the layer transmission probability, the half-transmission thickness, and the Knudsen diffusion coefficient are obtained. For packings of spheres, expressions of these parameters in terms of porosity and grain size are derived and compared with former standard models. A verification of the derived equations is given by means of numerical simulations, also providing evidence that our analytical model for sphere packing is more accurate than the former classical models.
Agrobiodiversity, Social Institutions, and Indigenous Farming Practices: A Case Study of the Rukai in Wutai, Taiwan
Authors: Ba Qing-Xiong , Wang Hong-Zen , Wang Mei-Hsiang 
Published: December 2023

AbstractAgrobiodiversity plays a crucial role in maintaining sustainable agricultural systems and supporting local livelihoods, but its integration into indigenous social institutions and cultures remains under-researched. We used a qualitative approach entailing in-depth interviews and participant observation to conduct research among the Rukai indigenous farmers in Taiwan focusing on: (1) how Rukai farmers practice agrobiodiversity, and (2) how these agricultural practices integrated into social institutions and cultural norms. Our findings reveal that food security and risk minimization are the prime considerations to preserve agrobiodiversity. Rukai farmers practice swidden cultivation utilizing five mixed cropping systems in seven different ecosystems that vary by elevation, length of exposure to sunlight, and temperature, intercropping, and regular fallows to maintain soil fertility. Importantly, Rukai agricultural practices are integrated into four social institutions that regulate the distribution and management of land and resources, the timing and nature of agricultural activities, and social recognition and status to ensure maximum production throughout the year and reducing risks posed by climate change.
Motor Signature Differences Between Autism Spectrum Disorder and Developmental Coordination Disorder, and Their Neural Mechanisms
Authors: Butera Christiana , Delafield-Butt Jonathan , Lu Szu-Ching , Sobota Krzysztof , McGowan Timothy , Harrison Laura , Kilroy Emily , Jayashankar Aditya , Aziz-Zadeh Lisa 
Published: December 2023

Abstract
Autism spectrum disorder (ASD) and Developmental Coordination Disorder (DCD) are distinct clinical groups with overlapping motor features. We attempted to (1) differentiate children with ASD from those with DCD, and from those typically developing (TD) (ages 8–17; 18 ASD, 16 DCD, 20 TD) using a 5-min coloring game on a smart tablet and (2) identify neural correlates of these differences. We utilized standardized behavioral motor assessments (e.g. fine motor, gross motor, and balance skills) and video recordings of a smart tablet task to capture any visible motor, behavioral, posture, or engagement differences. We employed machine learning analytics of motor kinematics during a 5-min coloring game on a smart tablet. Imaging data was captured using functional magnetic resonance imaging (fMRI) during action production tasks. While subject-rated motor assessments could not differentiate the two clinical groups, machine learning computational analysis provided good predictive discrimination: between TD and ASD (76% accuracy), TD and DCD (78% accuracy), and ASD and DCD (71% accuracy). Two kinematic markers which strongly drove categorization were significantly correlated with cerebellar activity. Findings demonstrate unique neuromotor patterns between ASD and DCD relate to cerebellar function and present a promising route for computational techniques in early identification. These are promising preliminary results that warrant replication with larger samples.
The syntax of individuating and measuring pseudo-partitives in Alasha Mongolian
Authors: Toquero-Pérez Luis Miguel 
Published: December 2023

AbstractPseudo-partitive constructions give rise to multiple interpretive ambiguities including a container interpretation (i.e. individuating) and a contents (i.e. measuring) one. There are two competing analyses: one based on structural ambiguities (Landman in Indefinites and the types of sets, Oxford University Press, Oxford, 2004; Rothstein in Brill’s J Afroasiat Lang Ling 1:106–145, 2009. https://doi.org/10.1163/187666309X12491131130783, a.o.) and one based on a uniform syntax (Lehrer in Lingua 68:109–148, 1986; Matushansky and Zwarts in Lamont and Tetzloff (eds) North East Linguistic Society (NELS) 47, Volume 2, pp 261–274, GLSA, Amherst, 2016, a.o.). I contribute to this debate with data from Alasha Mongolian (Mongolic), which differentiates each interpretation via case marking on the quantizing noun: glass-comitative = individuating vs. glass-genitive/Ø = measuring. I argue that there is no large-scale structural ambiguity: the numeral and the quantizing noun always form a constituent introduced in the specifier position of a null functional head (Schwarzschild in Syntax 9(1):67–110, 2006. https://doi.org/10.1111/j.1467-9612.2006.00083.x; Svenonius in McNally and Kennedy (eds) Adjectives and adverbs: syntax, semantics and discourse, Oxford Studies in Theoretical Linguistics, pp 16–42, Oxford University Press, Oxford, 2008; Ott in J Comp Ger Ling 4:1–46, 2011. https://doi.org/10.1007/s10828-010-9040-x). I propose that (i) case differences on the quantizing constituent boil down to the presence or absence of a case probe on a higher Agr head; (ii) and, the interpretive differences between the individuating and measuring pseudo-partitives are the result of a more subtle syntactic distinction in the feature content of the quantizing noun, i.e. an interpretable [±Container] feature.
Are School-Based Interventions Effective in Preventing Internet Misuse? A Systematic Review
Authors: Martínez-Hernández Nieves , Lloret-Irles Daniel 
Published: December 2023

AbstractProblems related to the use of the internet have triggered the appearance of internet addiction. With this problem comes the need for prevention. The objective of this study is to update the knowledge about the effectiveness of internet addiction prevention programs in schools. The specific aims are: (1) to identify the objectives of school’s prevention programs, (2) to analyse the components and instruments used, (3) to evaluate the quality of the relevant studies and (4) to compare the results of the publications. A search with the terms "Internet", "Internet Use Disorder", "addiction", "prevention", "school", "effectiveness", and "prevention program" was carried out in 10 bibliographic databases in August 2021. For the selection of articles, the 25 quality criteria of the CONSORT 2010 list were used. Only articles that evaluated school prevention programs and had a quality score greater than 10 were selected. The results are shown in three tables. Eleven publications that met the inclusion criteria were identified. The measurement scales used are very heterogeneous. Ten of the 11 programs were effective in preventing adolescent internet misuse, abuse, or addiction. Increasing students' self-control reduces the problem of internet abuse. The validity of the results is discussed considering the methodological quality of the studies.
The study on distribution coefficient of polonium between tri-octylphosphine oxide (TOPO) and tri-butylphosphate (TBP) in toluene and cyclohexane and selected inorganic acids
Authors: Kaczyńska Grażyna , Szaciłowski Grzegorz 
Published: December 2023

AbstractIn this work the distribution coefficients (D) of polonium between 0.1 mol dm−3 TOPO/toluene; TOPO/cyclohexane; TBP/toluene and TBP/cyclohexane and aqueous solutions of inorganic acids (HCl, HNO3, H2SO4 and H3PO4) were determinated. The molarities of inorganic acids were between 0.5 and 12.0 mol dm−3. The activity of extracted Po-209 was measured by means of liquid scintillation counting. The best result was obtained for TOPO/toluene and 2 mol dm−3 H2SO4 system (D = 62 ± 9). The most stable conditions of extraction were found for TOPO/toluene-HCl system.
Solving imbalanced learning with outlier detection and features reduction
Authors: Lusito Salvatore , Pugnana Andrea , Guidotti Riccardo 
Published: December 2023

AbstractA critical problem for several real world applications is class imbalance. Indeed, in contexts like fraud detection or medical diagnostics, standard machine learning models fail because they are designed to handle balanced class distributions. Existing solutions typically increase the rare class instances by generating synthetic records to achieve a balanced class distribution. However, these procedures generate not plausible data and tend to create unnecessary noise. We propose a change of perspective where instead of relying on resampling techniques, we depend on unsupervised features engineering approaches to represent records with a combination of features that will help the classifier capturing the differences among classes, even in presence of imbalanced data. Thus, we combine a large array of outlier detection, features projection, and features selection approaches to augment the expressiveness of the dataset population. We show the effectiveness of our proposal in a deep and wide set of benchmarking experiments as well as in real case studies.
Holistic deep learning
Authors: Bertsimas Dimitris , Villalobos Carballo Kimberly , Boussioux Léonard , Li Michael Lingzhi , Paskov Alex , Paskov Ivan 
Published: December 2023

AbstractThis paper presents a novel holistic deep learning framework that simultaneously addresses the challenges of vulnerability to input perturbations, overparametrization, and performance instability from different train-validation splits. The proposed framework holistically improves accuracy, robustness, sparsity, and stability over standard deep learning models, as demonstrated by extensive experiments on both tabular and image data sets. The results are further validated by ablation experiments and SHAP value analysis, which reveal the interactions and trade-offs between the different evaluation metrics. To support practitioners applying our framework, we provide a prescriptive approach that offers recommendations for selecting an appropriate training loss function based on their specific objectives. All the code to reproduce the results can be found at https://github.com/kimvc7/HDL.
Looking for a Novel Vegan Protein Supplement from Faba Bean, Lupine, and Soybean: a Dietary and Industrial Standpoint
Authors: Hamed Hend A. , Kobacy Walaa , Mahmoud Elsayed A. , El-Geddawy Mennatallah M. A. 
Published: December 2023

AbstractGlobal population growth poses a threat to sustainable development. Meanwhile, the use of plant proteins as healthy and sustainable alternatives to animal proteins needs further research. Therefore, this investigation was designed to study the nutritive, structural, and thermal properties of isolated protein fractions from different legumes, i.e., faba bean (FPI), soybean (SPI), and lupine (LPI). As a prospective plant-based protein powder, an equal mixture (MPI) of the three prior legume samples was formulated to study its properties compared to each sole sample. The alkaline extraction and isoelectric precipitation (AE-IP) technique was used for protein isolation. Results showed that all protein isolates had reasonable levels of protein with maximum protein content in SPI (96.15%). The MPI sample, however, came out on top in terms of amino acid profile followed by FBI. Compared to SPI and LPI, it had the highest isoleucine content and higher methionine, valine, leucine, phenylalanine, and lysine. Moreover, MPI showed a median particle charge (−37.1 mV) compared to FPI, SPI, and LPI samples. MPI sample peak showed resistance to heat denaturation at a temperature greater than 200 °C when the DSC test was conducted. With respect to its rheological characteristics, it outperformed the other three protein isolates and exhibited the highest values of storage modulus G’ and loss modulus G”. Consequently, our study suggests that pulse-derived protein isolate mixture can be used as a unique type of nutritious dietary protein supplement. It could be a good nutritional alternative to proteins derived from animals.
Social performance and impact assessment of an autonomous system in the meat processing sector
Authors: Valente Clara , Danielsen Rannvá , Woodhouse Anna , Johnsen Fredrik Moltu , Forsberg Ellen-Marie 
Published: December 2023

Abstract
Purpose
The automation of pork processing through robotics raises important societal concerns regarding working conditions of slaughterhouse workers and impacts on local communities. This article aims to evaluate the social performance and impacts of implementing an Autonomous Robotic System (ARS) for meat processing, comparing pre- and post-implementation scenarios.

Methods
The methodology of Social Life Cycle Assessment (S-LCA) was applied to the European pork processing sector, focusing on stakeholder categories Workers and Local Community. These were assessed with nine social subcategories in total and 22 corresponding indicators, which were scored to assess the technology in question against a reference scale where each score level has clearly established criteria. The data collection strategy combined a survey, individual interviews, and focus group interviews as well as secondary data collected from desktop research and database data.

Results and discussion
The results suggest a considerable improvement in social performance and impacts when moving from the conventional meat processing scenario to the ARS. All subcategories from both stakeholder categories scored higher in the post-ARS scenario. The most improved social subcategories were Health and safety and Access to immaterial resources. A considerable improvement was identified in social subcategories Working hours, Freedom of association and collective bargaining, and Fair salary. A modest improvement was identified in social subcategories Equal opportunities and discrimination, Employment relationship, and Migration and delocalisation. The ARS is anticipated to mitigate injury risks that workers are exposed to in a conventional meat factory and to reduce sick leave but will also necessitate training and close collaboration between unions and management teams.

Conclusions
Using a reference scale approach, we identified an improvement of the social performance in the pork processing industry post-ARS implementation, both for Workers and Local community. It is important to pay attention to social impacts and performances when introducing new technology such as automation, robotics, and artificial intelligence to ensure that these do not have unintended social impacts and/or poor social performance.

Graphical Abstract