bluuebunny/crossref_metadata_2025_split huggingface dataset:
“Somebody has to be crazy about that kid”: Speculating on the transformative recordkeeping potential of the caring corporate parent
Authors: Ballin Mya 
Published: September 2024

AbstractJust as archival scholarship has increasingly engaged in conversations around care and holistic considerations of the agency of records subjects, the child welfare systems of the modern Western world have been moving towards conversations that aim to centre and celebrate the voice of the child in new and important ways. However, too often are these conversations held back by the enormity of the issue and the overhaul that would have to take place for philosophy to match with practice. In this paper, I suggest that part of the problem is that we have been trying to make these changes philosophy first, placing a new way of thinking on top of an old way of doing—an approach that will never generate change. Leaning in to using speculation to imagine what the new recordkeeping of a caring system might look like, I propose that the act of recordkeeping is the fulcrum that could make caring child welfare a reality and illustrate some of the avenues through which we might pursue instigating the systemic changes needed if we are to see the agency and perspectives of children prioritised in child welfare and protection practices.
ACE2 alleviates sepsis-induced cardiomyopathy through inhibiting M1 macrophage via NF-κB/STAT1 signals
Authors: Xiao Xue , Li Jia-Xin , Li Hui-Hua , Teng Fei 
Published: September 2024

AbstractAngiotensin-converting enzyme 2 (ACE2), a crucial element of the renin-angiotensin system (RAS), metabolizes angiotensin II into Ang (1–7), which then combines with the Mas receptor (MasR) to fulfill its protective role in various diseases. Nevertheless, the involvement of ACE2 in sepsis-induced cardiomyopathy (SIC) is still unexplored. In this study, our results revealed that CLP surgery dramatically impaired cardiac function accompanied with disruption of the balance between ACE2-Ang (1–7) and ACE-Ang II axis in septic heart tissues. Moreover, ACE2 knockin markedly alleviated sepsis induced RAS disorder, cardiac dysfunction and improved survival rate in mice, while ACE2 knockout significantly exacerbates these outcomes. Adoptive transfer of bone marrow cells and in vitro experiments showed the positive role of myeloid ACE2 by mitigating oxidative stress, inflammatory response, macrophage polarization and cardiomyocyte apoptosis by blocking NF-κB and STAT1 signals. However, the beneficial impacts were nullified by MasR antagonist A779. Collectively, these findings showed that ACE2 alleviated SIC by inhibiting M1 macrophage via activating the Ang (1–7)-MasR axis, highlight that ACE2 might be a promising target for the management of sepsis and SIC patients.
Single- and Multilevel Perspectives on Covariate Selection in Randomized Intervention Studies on Student Achievement
Authors: Stallasch Sophie E. , Lüdtke Oliver , Artelt Cordula , Hedges Larry V. , Brunner Martin 
Published: September 2024

AbstractWell-chosen covariates boost the design sensitivity of individually and cluster-randomized trials. We provide guidance on covariate selection generating an extensive compilation of single- and multilevel design parameters on student achievement. Embedded in psychometric heuristics, we analyzed (a) covariate types of varying bandwidth-fidelity, namely domain-identical (IP), cross-domain (CP), and fluid intelligence (Gf) pretests, as well as sociodemographic characteristics (SC); (b) covariate combinations quantifying incremental validities of CP, Gf, and/or SC beyond IP; and (c) covariate time lags of 1–7 years, testing validity degradation in IP, CP, and Gf. Estimates from six German samples (1868 ≤ N ≤ 10,543) covering various outcome domains across grades 1–12 were meta-analyzed and included in precision simulations. Results varied widely by grade level, domain, and hierarchical level. In general, IP outperformed CP, which slightly outperformed Gf and SC. Benefits from coupling IP with CP, Gf, and/or SC were small. IP appeared most affected by temporal validity decay. Findings are applied in illustrative scenarios of study planning and enriched by comprehensive Online Supplemental Material (OSM) accessible via the Open Science Framework (OSF; https://osf.io/nhx4w).
De-Hydration and Remodeling of Biological Materials: Swelling Theory for Multi-Domain Bodies
Authors: Curatolo Michele , van der Sman R. G. M. , Teresi Luciano 
Published: September 2024

AbstractBiological materials always exhibit heterogeneous physical properties, both mechanical and chemical, which give them a rich phenomenology that poses significant challenges in the developing of effective models. The Flory–Rehner theory revolutionized our understanding of the dynamics of the liquid-polymers coupling in soft swollen gels, recognizing polymers as elastic networks stretched by the presence of liquid. Despite its foundational role, applying this theory to bodies with non uniform physical properties requires further improvements. This article proposes a unified approach to address mechano-diffusion challenges in multi-domain bodies, that is in material bodies made of regions having different chemo-mechanical properties, and focuses on the dehydration and remodeling of biological-like materials. Drawing inspiration from natural systems, we integrate principles from nonlinear mechanics and swelling theories; in particular, what is specifically new is the idea of applying the notion of the multiplicative decomposition of the strain–developed for plasticity–to model the swelling properties of a body made of two or more materials. The article gives a systematic presentation of the subject, and guides readers through key concepts and practical insights, aiming to provide a robust framework for modeling chemo-mechanical interactions. Moreover, it paves the way for the modeling of heterogenous bodies having spatially-varying properties.
Comparative Analysis of Foundation Systems in Expansive Soil: A Three-Dimensional Model Approach to Moisture Diffusion and Volume Changes
Authors: Alnmr Ammar , Ray Richard , Alzawi Mounzer Omran 
Published: September 2024

AbstractThis study compares the performance of various foundation systems in expansive soils, such as mats, granular anchor piles, and concrete piles. Expansive soils experience volumetric changes due to moisture fluctuations, which can lead to structural damage. Abaqus software, in conjunction with the SCV approach, is used to analyze soil-foundation interactions. A custom subroutine enhances simulation accuracy by incorporating empirical data on unsaturated clay behavior, matric suction, and variations in effective stress. The method’s accuracy is validated by comparing simulation results to field and laboratory experiments. The findings indicate that increasing the applied load on mats decreases overall heave but increases the differential heave. Additionally, higher soil permeability dereases the differential heave of mats. Granular anchor piles outperform concrete piles by more than 50% in highly expansive soils, suggesting a preference for these foundations. This study provides insights into the behavior of expansive soils, which will assist engineers in designing resilient foundation systems for structures.
A DLTS analysis of alpha particle irradiated commercial 4H-SiC Schottky barrier diodes
Authors: Ahmed Mustafa A. M. , Auret F. D. , Nel J. M. , Venter Andrè 
Published: September 2024

Abstract4H-SiC Schottky barrier diodes (SBDs) were exposed to 5.4 MeV alpha particles with fluences of 2.55× 1011 cm−2, 5.11 × 1011 cm−2 and 7.67 × 1011 cm−2, respectively. Transmission electron microscopy (TEM) and energy dispersive spectroscopy (EDS) was used to determine the structure and cross-sectional elemental composition of the device, while current–voltage and capacitance–voltage profiling were used to determine the primary electrical device-characteristics before and after irradiation. EDS revealed the presence of a <1 μm Ti layer, covered by 5 μm Al layer, in intimate contact with the SiC. Deep level transient spectroscopy (DLTS), performed in the temperature range 15–310 K, revealed one dominant peak around 50 K (Ec - 0.07 eV) in the unirradiated samples. This peak showed asymmetry suggesting that it may consist of more than one defect. Notably, Z1/2, the carbon vacancy-related (Vc) defect commonly observed in as-grown n-type 4H-SiC, was not detected in the unirradiated reference sample. After irradiation, a broad peak emerged around 280 K (at 80 Hz), most likely Z1/2, having a shoulder around 180 K, was detected. Increasing the fluence resulted in a corresponding decrease in the concentration of the electron trap observed around 50 K (Ec - 0.07 eV), while the concentration increases for the defect detected around 280 K. Notably, the concentration of Z1/2 was found to be strongly fluence dependent and linked to what we believe is a related to a silicon vacancy transition, labelled S1/2 in literature. Laplace DLTS confirmed that the peak observed around 50 K is composed of multiple defects.
Longitudinal Associations of (Un)popularity with Weight Perceptions and Dieting in Adolescence
Authors: Swinkels Aafke , van den Broek Nina , Cillessen Antonius H. N. 
Published: September 2024

Abstract
Little is known about the unique effects of (un)popularity on body image and the characteristics influencing these effects. The goals of this study were to examine (1) the longitudinal associations of adolescents’ (un)popularity with weight perception and dieting, (2) whether (dis)liking, self-esteem, and gender moderated these associations. Participants were 1697 Dutch adolescents (M
age = 14.18 years, SD = 1.29; 51% female), from a middle-class population. Participants completed peer nominations and self-reports in three consecutive school years. Mixed-effects models showed that (un)popularity did not predict weight perception and dieting over time. Concurrently, when liking was low, popularity predicted positive weight perception. Higher popularity predicted more dieting in females. This study highlighted that adolescents’ body image varied in subgroups of social status.
The Inherent Normativity of Concepts
Authors: So Wing Yi , Friston Karl J. , Neacsu Victorita 
Published: September 2024

AbstractConcept normativity is a prominent subject of inquiry in the philosophical literature on the nature of concepts. Concepts are said to be normative, in that the use of concepts to categorise is associated with an evaluation of the appropriateness of such categorisation measured against some objective external standard. Two broad groups of views have emerged in accounting for the normativity of concepts: a weaker view traces such normativity to the social practice in which the agent using the concept is embedded, while a stronger view traces such normativity to a first-person capacity of reflection. However, both views have drawbacks: the weaker view seems not to do justice to the basic sense of normativity associated with an individual agent using a concept, while the stronger view ties such normativity with the first-person conscious evaluation, which appears to be too strong. Here, we propose a different view of concepts using principles from the Active Inference framework. We reconceive concepts, defining them as Bayesian beliefs—that is, conditional probability distributions—that represent causes and contingencies in the world, their form grounded in the exchange between the agent and its environment. This allows us to present a different view on the source of normativity, with an emphasis on the structure of the agent itself as well as its interaction with the environment. On the Active Inference view, concepts are normative in that they are intrinsically connected to the self-evidencing nature of an agent, whose very structure implies an evaluation of the concepts it employs.
Real or virtual: a video conferencing background manipulation-detection system
Authors: Nowroozi Ehsan , Mekdad Yassine , Conti Mauro , Milani Simone , Uluagac Selcuk 
Published: September 2024

AbstractIn the past few years, the popularity and wide use of video conferencing software enjoyed exponential growth in market size. This technology enables participants in different geographic regions to have a virtual face-to-face meeting. Additionally, it allows participants to utilize virtual backgrounds to hide their real environment with privacy concerns or to reduce distractions, particularly in professional settings. In scenarios where the users should not hide their actual locations, they may mislead other participants into assuming that the displayed virtual backgrounds are real. In this paper, we propose a new publicly-available dataset of virtual and real backgrounds in video conferencing software (e.g., Zoom, Google Meet, Microsoft Teams). The presented archive was evaluated by an exhaustive series of tests and scenarios using two well-known features extraction methods: CRSPAM1372 and six co-mat. The first verification scenario considers the case where the detector is unaware of manipulated frames (i.e., the forensically-edited frames are not part of the training set). A model trained on zoom frames that were tested with Google Meet frames can detect real background images from virtual ones in video conferencing software with 99.80% detection accuracy. Furthermore, it is possible to distinguish virtual from real backgrounds in videos created for videoconferencing software at a high detection rate of approximately 99.80%. According to our conclusions, the proposed method greatly enhanced the detection accuracy and resistance against diverse adversarial conditions, making it a reliable technique for classifying actual as opposed to virtual backgrounds in video communications. Given the described dataset provided and some preliminary experiments that we performed, we expect that it will lead to more future research in this domain.
Group Consciousness, Organizational Membership, and District Choice: Evidence from the Afro-Colombian Reserved Seats
Authors: Villamizar-Chaparro Mateo , Echeverri-Pineda Cristina 
Published: September 2024

AbstractNumerous countries around the globe have undertaken efforts aimed at enhancing political representation. One of these efforts has taken the institutional form of reserved seats or ethnic districts where individuals must choose where to deposit their votes. In this paper, we ask if group consciousness and organizational membership affect the choice to vote on these types of districts. Using a mixed-methods approach by combining semi-structured interviews with elites and a subgroup analysis of a conjoint experiment in a sample of Afro-Colombians, we find evidence that group consciousness affects the preferences for ethnic districts over territorial ones. Contrary to initial expectations, we observe that membership in ethnic organizations does not significantly alter preferences for ethnic districts among surveyed individuals. These findings indicate that individuals with high levels of group consciousness tend to choose to participate more in mechanisms and institutions that can enhance the group’s political representation.
Phases of Progression: Students’ meaning-making of Epigenetic Visual Representations within and between Levels of Organization
Authors: Thyberg Annika , Schönborn Konrad , Gericke Niklas 
Published: September 2024

AbstractThis study investigates the progression of students’ meaning-making of epigenetic phenomena while discussing multiple visual representations depicted at different levels of biological organization. Semi-structured focus group sessions involving ninth-grade students (aged 15-16) from a Swedish lower secondary school were video recorded. Students’ meaning-making with regard to form, function and transfer of scientific ideas was explored by analyzing students’ physical pointing and verbal utterances while interacting with and discussing the epigenetic visual representations. The study uncovered four phases of progression in students’ meaning-making. In phase 1, students’ focus is on unpacking scientific ideas within a single representation. In phase 2, students apply and transfer scientific ideas between different visual representations at the same organizational level. In phase 3, their meaning-making develops into linking between various levels of organization. Here, downward linking, from higher to lower levels, relies on form descriptions that limit the transfer of scientific ideas. In contrast, upward linking, from lower to higher organizational levels, relies on both descriptions of form and functional explanations, which facilitates the transfer of scientific ideas. Finally, in Phase 4, and manifested as “yo-yo reasoning”, students engage in a dynamic and repeated process of downward and upward linking that expresses a coherent understanding of epigenetics. The study findings underscore the significance of recognizing progression phases in facilitating students’ meaning-making of multiple representations of epigenetic phenomena. Future research could expand on these insights by investigating students’ meaning-making across other science education domains.
Latitudinal Dependence of Variations in the Frequencies of Solar Oscillations Above the Acoustic Cut-Off
Authors: Millson Laura Jade , Broomhall Anne-Marie , Mehta Tishtrya 
Published: September 2024

AbstractAt high frequencies beyond the acoustic cut-off, a peak-like structure is visible in the solar power spectrum. Known as the pseudo-modes, their frequencies have been shown to vary in anti-phase with solar magnetic activity. In this work, we determined temporal variations in these frequencies across the solar disc, with the aim of identifying any potential latitudinal dependence of pseudo-mode frequency shifts. We utilised nearly 22 years of spatially resolved GONG data for all azimuthal orders, $\textit{m}$
m
, for harmonic degrees $0\leq l\leq 200$
0
≤
l
≤
200
, and determined shifts using the resampled periodogram method. Periodogram realisations were created from overlapping, successive 216 day-long segments in time, and cropped to 5600 – 6800 μHz. Cross-correlation functions were then repeatedly generated between these realisations to identify any variation in frequency and the uncertainty. We categorised each mode by its latitudinal sensitivity and used this categorisation to produce average frequency shifts for different latitude bands (15∘ and 5∘ in size) which were compared to magnetic proxies, the $F_{\mathrm{10.7}}$

F
10.7

index and GONG synoptic maps. Morphological differences in the pseudo-mode shifts between different latitudes were found, which were most pronounced during the rise to solar maximum where shifts reach their minimum values. At all latitudes, shift behaviour was strongly in anti-correlation with the activity proxy. Additionally, periodicities shorter than the 11-year cycle were observed. Wavelet analysis was used to identify a periodicity of four years at all latitudes.
Developing a Risk Management Framework for Agricultural Water Systems Using Fuzzy Dynamic Bayesian Networks and Decision-Making Models
Authors: Bozorgi Atiyeh , Roozbahani Abbas , Hashemy Shahdany Seied Mehdy , Abbassi Rouzbeh 
Published: September 2024

AbstractGiven the various natural and human-caused hazards that threaten the agricultural water distribution process from the main source to farms, establishing a framework to analyze these risks is crucial. This study aims to develop an intelligent risk management framework to help stakeholders devise long-term and sustainable solutions for managing agricultural water systems. First, we developed a Fuzzy Dynamic Bayesian Network (FDBN) model for multi-hazard risk assessment, taking into account the temporal causal interactions between parameters and incorporating fuzzy theory. Next, we defined several risk management scenarios across structural, non-structural, automated control, and integrated methods. These scenarios were implemented in the FDBN model to mitigate the risks associated with the system. Various economic, social, environmental, and technical criteria were considered, and scenarios were ranked using the WASPAS, TOPSIS, and MultiMoora methods. The Copeland approach was used to combine the ranking results. The results showed that automated scenarios, specifically Model Predictive Control (MPC) and Proportional-Integral (PI) controllers, could reduce the system's risk by 11.4% and 9.8%, respectively, and were ranked the highest. The findings of this study and the proposed framework can assist operators in the sustainable planning and management of water systems in light of anticipated threats.
Advancing Reservoir Water Level Predictions: Evaluating Conventional, Ensemble and Integrated Swarm Machine Learning Approaches
Authors: Rehamnia Issam , Mahdavi-Meymand Amin 
Published: September 2024

Abstract
Accurate estimation of reservoir water level fluctuation (WLF) is crucial for effective dam operation and environmental management. In this study, seven machine learning (ML) models, including conventional, integrated swarm, and ensemble learning methods, were employed to estimate daily reservoir WLF. The models comprise multi-linear regression (MLR), shallow neural network (SNN), deep neural network (DNN), support vector regression (SVR) integrated with homonuclear molecules optimization (HMO) and particle swarm optimization (PSO) meta-heuristic algorithms, classification and regression tree (CART), and random forest (RF). These models were trained and evaluated using in situ data from three embankment dams in Algeria: the Kramis dam, the Bougous dam, and the Fontaine Gazelles dam. Performance evaluation was conducted using statistical indices, scatter plots, violin plots, and Taylor diagrams. The results revealed superior prediction accuracy for the Fontaine Gazelles dam compared to Kramis and Bougous dams. Particularly, the RF, DNN, and SVR-HMO models exhibited consistent and excellent predictive performance for WLF at the Fontaine Gazelles dam with RMSE values of 0.502 m, 0.536 m, and 0.57 m, respectively. The RF model demonstrates remarkable accuracy across all three case studies. This can be attributed to the ensemble structure of RF, as evidenced by the results. This study underscores the significance of considering factors such as seepage flow intensity in understanding WLF variability. Furthermore, the proposed ML models offer promising capabilities in WLF prediction, highlighting their potential utility in enhancing reservoir management practices and addressing the limitations of traditional regression models. Keys words. Embankment dam, Water level fluctuations, Seepage, Artificial neural network, meta-heuristic algorithm.