bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Case Study of Sending Graph Neural Networks Back to the Test Bench for Applications in High-Energy Particle Physics
Authors: Pfeffer Emanuel , Waßmer Michael , Cung Yee-Ying , Wolf Roger , Husemann Ulrich 
Published: July 2024

AbstractIn high-energy particle collisions, the primary collision products usually decay further resulting in tree-like, hierarchical structures with a priori unknown multiplicity. At the stable-particle level all decay products of a collision form permutation invariant sets of final state objects. The analogy to mathematical graphs gives rise to the idea that graph neural networks (GNNs), which naturally resemble these properties, should be best-suited to address many tasks related to high-energy particle physics. In this paper we describe a benchmark test of a typical GNN against neural networks of the well-established deep fully connected feed-forward architecture. We aim at performing this comparison maximally unbiased in terms of nodes, hidden layers, or trainable parameters of the neural networks under study. As physics case we use the classification of the final state $$\text{X}$$
X
produced in association with top quark–antiquark pairs in proton–proton collisions at the Large Hadron Collider at CERN, where $$\text{X}$$
X
stands for a bottom quark–antiquark pair produced either non-resonantly or through the decay of an intermediately produced $$\text{Z}$$
Z
or Higgs boson.
Improving Children’s Services Engagement of Fathers in Child Protection: Logic Model for an Organisational Development and Staff Training Intervention
Authors: Scourfield Jonathan , Davies Jeremy , Jones Kathy , Maxwell Nina 
Published: July 2024

AbstractThere is a long-standing and ongoing problem of practice with at-risk families in child welfare work focusing primarily on mothers and failing to properly engage fathers. The article describes a child welfare innovation from the UK designed to tackle this issue—the ISAFE (Improving Safeguarding through Audited Father-Engagement) intervention, developed by The Fatherhood Institute and The Children’s Social Care Research and Development Centre (CASCADE) at Cardiff University and based on two previous separate interventions which had positive initial evaluations. ISAFE combines in-service social work practitioner training with other elements of organisational development to improve the engagement of fathers. Activities targeting organisational culture are case file audits, identification and training of team champions, and a webinar for service leaders. The practitioner training involves both awareness raising about the importance of engaging men and skills development via an introduction to motivational interviewing. ISAFE’s theory of change is summarised in the form of a logic model. Limitations of the intervention and its evaluation are discussed.
Role of Silicon in Counteracting Cadmium Stress in Pea Plants (Pisum sativum L.): Insights Into Cadmium Binding Mechanisms and Pectin Methylesterase Activity
Authors: Gołębiowski Adrian , Szultka-Młyńska Małgorzata , Pomastowski Paweł , Rafińska Katarzyna , Orzoł Aleksandra , Cichorek Mateusz , Olszewski Jacek , Buszewski Bogusław , Głowacka Katarzyna 
Published: July 2024

AbstractPurpose: The aim of this study was to investigate the role of silicon (Si) in counteracting a cadmium (Cd) stress to pea plants (Pisum sativum L.) and to identify the mechanism by which Cd is bound within pea roots. Methods: These goals were achieved through (i) a histochemical study of Cd localization in pea roots, (ii) spectrophotometric determination of pectin content and the activity of pectin methylesterase (PME), (iii) speciation of Cd extracted from pea roots conducted through size exclusion chromatography (SEC) and inductively coupled plasma mass spectrometry (ICP/MS). Results: Cd was found mainly in the root stele of the Cd-stressed plants. The pectin content and PME activity were lower in the Cd-stressed plants, but Si supplementation reversed these effects. Selectivity was noticed in Cd extraction efficiency with water being the least effective and enzymatic-assisted extraction proving to be the most effective. Speciation analysis revealed significant heterogeneity in molar mass, ranging from approximately 295 to 95 kDa. Galacturonic acid was identified the dominant species responsible for Cd binding. The choice of solvent for extraction markedly influenced the Cd binding profile, indicating shifts in the distribution of species’ molar mass and their relative concentrations in extracts. Conclusions: Si alleviates Cd toxicity in pea plants, and one of the mechanisms through which it operates involves increasing pectin levels and PME activity. Pectin plays an active role in Cd detoxification in the root cell walls, forming electrostatic bonds with Cd cations through its carboxyl groups.
Implementation Determinants of Problem-Solving Therapy Delivered by Near-Peer Lay Counselors for Youth Living with HIV in Botswana: Lay Counsellor Perspectives
Authors: Ahmed Charisse V. , Van Pelt Amelia E. , Buttenheim Alison M. , Poku Ohemaa , Rice Bridgette M. , Lowenthal Elizabeth D. , Brooks Merrian J. 
Published: July 2024

AbstractAn evidence-based psychological intervention, known as Friendship Bench, for depression and anxiety was adapted among adolescents living with HIV (ALHIV) in Gaborone, Botswana, and renamed Safe Haven. The purpose of this study was to qualitatively describe the barriers and facilitators that influence the implementation of Safe Haven from the perspective of peer counselors delivering the intervention in Gaborone, Botswana. We conducted a secondary analysis using qualitative data from a pilot study to evaluate Safe Haven. Eight peer counselors participated in semi-structured interviews to describe their experiences with implementing Safe Haven during the pilot. We analyzed the interview data thematically using the Consolidated Framework for Implementation Research to guide theme development. We identified six barriers and two facilitators of Safe Haven implementation. The barriers were 1) client reticence and confidentiality concerns, 2) parent disapproval, 3) client accessibility, 4) counselor psychological wellbeing, 5) scheduling conflicts 6) limited financial resources for counselors. The facilitators were 1) peer delivery of counseling was deemed more acceptable among adolescents than counseling delivered by older adults, and 2) the counselors placed high value on the intervention. We found that parental disapproval and shared trauma among counselors and clients are key barriers that may negatively impact implementation outcomes such as sustainability and penetration. To improve accessibility of the intervention, peer counselors recommended implementation in school settings and to educate parents on mental health. Overall, the barriers and facilitators identified in our study can guide larger scale implementation of Safe Haven among ALHIV in resource-poor settings.
Reading Between the Lines: Machine Learning Ensemble and Deep Learning for Implied Threat Detection in Textual Data
Authors: Raza Muhammad Owais , Meghji Areej Fatemah , Mahoto Naeem Ahmed , Al Reshan Mana Saleh , Abosaq Hamad Ali , Sulaiman Adel , Shaikh Asadullah 
Published: July 2024

AbstractWith the increase in the generation and spread of textual content on social media, natural language processing (NLP) has become an important area of research for detecting underlying threats, racial abuse, violence, and implied warnings in the content. The subtlety and ambiguity of language make the development of effective models for detecting threats in text a challenging task. This task is further complicated when the threat is not explicitly conveyed. This study focuses on the task of implied threat detection using an explicitly designed machine-generated dataset with both linguistic and lexical features. We evaluated the performance of different machine learning algorithms on these features including Support Vector Machines, Logistic Regression, Naive Bayes, Decision Tree, and K-nearest neighbors. The ensembling approaches of Adaboost, Random Forest, and Gradient Boosting were also explored. Deep learning modeling was performed using Long Short-Term Memory, Deep Neural Networks (DNN), and Bidirectional Long Short-Term Memory (BiLSTM). Based on the evaluation, it was observed that classical and ensemble models overfit while working with linguistic features. The performance of these models improved when working with lexical features. The model based on logistic regression exhibited superior performance with anF1score of 77.13%. While experimenting with deep learning models, DNN achieved anF1score of 91.49% while the BiLSTM achieved anF1score of 91.61% while working with lexical features. The current study provides a baseline for future research in the domain of implied threat detection.
Sediment distribution and transport pattern in the nearshore region, southeast coast of India
Authors: Pradhan Umakanta , Naik Subrat , Mishra Pravakar , Panda Uma Sankar , Murthy M. V. Ramana 
Published: July 2024

AbstractThe present paper aimed to assess the sediment distribution pattern, mode of transport, and its interaction with hydrodynamic and topographic conditions at different depths and regions along the east coast of India. About 900 surficial sediment samples were collected and analysed on a monthly basis for the Chennai coastal region at 32 stations from 2013 to 2015. The study region is classified into four types, such as beach, inlet, 5 m, and 10 m depth. Sediment textural and grain size trend analyses were conducted to achieve the objectives. Sediment characteristics for the region were recorded as sandy, equally dominated by unimodal and bimodal at the beach, while unimodal at shallow depths (5 and 15 m). The sediments were medium sand to coarse sand at the beach, mostly fine followed by medium at 5 and 15 m depths. The sediment sorting is dominated by moderately well-sorted sediments; the skewness of beach sediments was negative, while nearshore sediments were found positive; average kurtosis values of sediments were noticed to be mesokurtic. The CM plot depicts that the sediments were mostly derived by tractive current, and the modes of transport are “bottom suspension and rolling” and “graded suspension no rolling” at beach locations and shallow water depths, respectively. The GSTA analysis reveals the annual average sediment transport pattern is northerly. The numerical hydrodynamic study confirms the GSTA and CM plot analysis. The study reveals a stable sedimentary environment south of the Chennai port and instability in the northern part. The study includes large spatiotemporal nearshore sediment data with hydrodynamic conditions, immensely helpful to coastal stakeholders and researchers.
Comparative analysis of meteorological parameters and their relationship with NO2, PM10, PM2.5 and O3 concentrations at selected urban air quality monitoring stations in Krakow, Paris, and Milan
Authors: Rowland Olawale Emmanuel 
Published: July 2024

AbstractMeteorological parameters play a major role in air pollutant concentrations as they create conditions that either hinder or facilitate the reaction and dispersion of pollutants in our environments. This is particularly evident in Europe, where frequent alternation of meteorological parameters has the potential to significantly impact pollutant concentrations. This study applied the R openair package to comparatively analyse the relationship between key meteorological parameters and NO2, O3, PM2.5, and PM10 concentrations measured at selected air quality monitoring stations in Krakow, Milan, and Paris in the year 2021. The study made use of meteorological data acquired from National Aeronautics and Space Administration (NASA) Power data repository, and air pollutants data measured at air quality monitoring stations in each of the three cities. The air pollutants data were retrieved from European Environmental Agency’s Airbase. Concentration and correlation analyses were conducted using the relevant functions of the R openair package. Findings in the study revealed a positive relationship between temperature and O3, wind speed and O3; and a negative relationship between temperature and NO2/PM2.5/PM10. The study further revealed a negative relationship between wind speed and NO2/PM2.5/PM10, as well as a negative relationship between precipitation and NO2/PM2.5/PM10. NO2, PM2.5, and PM10 concentrations were higher in winter periods, weekdays, nights, and evenings, but lower in summer periods, weekends, and midday. Whereas O3 concentration was higher in summer periods, weekends, midday, and lower in winter periods, weekdays, nights, and evenings. NO2, PM10, and PM2.5 concentrations were higher during the periods without precipitation than periods with precipitation. In addition, temperature inversions were found to be linked with higher concentrations of NO2, PM2.5, and PM10, but lower concentrations of O3 in Krakow, Paris and Milan. Accordingly, the study recommends effective monitoring, increased awareness, the use of pollutant removing devices, and further research to enhance adaptation and advance knowledge.
Comprehensive geospatial mapping and monitoring of an eastern coalfield in India
Authors: Kumar Pradeep , Choudhary Arti , Kumar Ram Pravesh , Kumar Pushpendra , Kumar Gautam 
Published: July 2024

AbstractGeospatial mapping and monitoring are crucial for designing slopes in opencast mining, as failure can result in significant economic and life loss. To overcome these issues, the present investigation evaluated the Digital Elevation Model (DEM) generated using high resolution Cartosat-1 satellite imagery. Simultaneously, mapping of shaded relief map, aspect map and slope maps was done for the monitoring of Shatabdi opencast coal mine of Jharia region, an eastern coalfield region of India. Shaded relief map was categorized in to low, moderate and high categories and maximum area was covered by moderate to high shades. The constructed aspect map encompasses the range between 0 and 360 degrees of direction, with categorization and representation through distinct colors. The slope map was classified into various categories based on degrees of slope, including very gentle, gentle, moderate, moderately steep, steep, and very steep slopes. The maps were ground validated using Differential Global Positioning System (DGPS) collected data points by field visit in the region. For opencast mines to operate safely and profitably, slope stability in different stages of mining must be mapped and monitored. The study synthesizes data from diverse sources, highlighting the role of geospatial technology in addressing multiple research gaps within the mining industries prior to leveraging Cartosat-1 satellite data. Slope mapping and monitoring of coalfield regions are crucial to reducing construction costs, mitigation of natural hazard risks like flooding and landslides, and effective conservation of natural resources such as soils, vegetation, and water systems. The present study benefits policymakers, environmental planners and government in formulating policies to ensure safety, reliability, and enhance the economic growth of workers and the country.
The psychology of intergroup relations was grounded in intragroup processes
Authors: Montoya R. Matthew , Pinter Brad 
Published: July 2024

Abstract
Although Glowacki proposed that peace developed from the relatively recent advent of intergroup norms and tolerance for out-group members, we submit that (a) positive intergroup relations developed from a psychology grounded in the regulation of intragroup relations, (b) the “default” intergroup orientation is uncertainty, and (c) positive intergroup relations likely existed early in our evolutionary history.
Author's response: The challenge of peace
Authors: Glowacki Luke 
Published: July 2024

Abstract
The 30 commentators are largely sympathetic to the account I develop for the origins of peace in humans, though many suggest that peace has deeper roots and that humans share characteristics of peace with other species. Multiple commentators propose how to extend my framework or focus on the cognitive and psychological prerequisites for peace. In my reply, I discuss these considerations and further my account of why I think peace as defined here was unlikely prior to behavioral modernity which emerged approximately 100,000 years ago. In general, there seems to be a consensus that moving the debate beyond “war versus peace” in human evolution and instead focusing on the conditions that enable war or peace is a fruitful direction for the field to take.
Crustal Electrical Anisotropic Structure of the Altyn Tagh Fault in the Subei Area, NW China: Implications for Fault Zone Architecture
Authors: Dong Zeyi , Xiao Qibin , Sun Zelin , Han Bing , Wang Lifeng , Tang Ji , Wang Jijun 
Published: July 2024

AbstractThe fault zone architecture may provide reliable information about the deformations in both on‐fault and off‐fault media. The outer damage zones of faults may extend for kilometers and exhibit structural anisotropy, which potentially causes electrical anisotropy in rocks. Thus, electrically anisotropic structures may indicate the dimensions and extent of fault damage zones. We investigated the electrical anisotropic structure of the sinistral Altyn Tagh fault (ATF), NW China, using magnetotelluric data collected in and around the Subei Basin. Our three‐dimensional resistivity model reveals widespread anisotropic anomalies at depths <∼5 km. The directions of the minimum horizontal resistivity values of the anomalies inside the Qilian Shan southeast of the ATF are dominantly subparallel to the fault traces at the surface. At deeper levels (∼15–19 km and ∼33–43 km), the anisotropic anomalies are mainly concentrated near the northern strand of the ATF (NATF) and the North Yemahe fault (NYMF) in the northeastern Subei area. The mid‐lower crust (∼33–43 km) inside the Qilian Shan is characterized by isotropy or weak anisotropy with low resistivities (∼10 Ωm), which deviate significantly from the values along the NATF. Our results indicate the presence of a ∼30 km wide off‐fault damage zone along the NATF and NYMF in the shallow crust that thins downward to the lower crust. We propose that the distribution of anisotropic anomalies is influenced primarily by neighboring faults. An independent deformation model could be appropriate for evaluating the relationships between the ATF and thrust faults within the Qilian Shan.
Inner Radiation Belt Simulations During the Successive Geomagnetic Storm Event of February 2022
Authors: Girgis Kirolosse M. , Hada Tohru , Yoshikawa Akimasa , Matsukiyo Shuichi , Chian Abraham C.‐L. , Echer Ezequiel 
Published: July 2024

AbstractStarting from 29 January 2022, a series of solar eruptions triggered a moderate geomagnetic storm on 3 February 2022, followed subsequently by another. Despite the typically minimal impact of unintense storms on space technology, 38 out of the 49 Starlink satellites underwent orbital decay, re‐entering Earth's atmosphere. These satellite losses were attributed to enhanced atmospheric drag conditions. This study employs numerical simulations, utilizing our test particle simulation code, to investigate the dynamics of the inner radiation belt during the two magnetic storms. Our analysis reveals an increase in proton density and fluxes during the transition from the recovery phase of the first storm to the initial phase of the second, primarily driven by intense solar wind dynamic pressure. Additionally, we assess Single Event Upset (SEU) rates, which exhibit a 50% increase in comparison to initial quiet conditions.
Streamflow Prediction at the Intersection of Physics and Machine Learning: A Case Study of Two Mediterranean‐Climate Watersheds
Authors: Adera S. , Bellugi D. , Dhakal A. , Larsen L. 
Published: July 2024

AbstractAccurate streamflow predictions are essential for water resources management. Recent studies have examined the use of hybrid models that integrate machine learning models with process‐based (PB) hydrologic models to improve streamflow predictions. Yet, there are many open questions regarding optimal hybrid model construction, especially in Mediterranean‐climate watersheds that experience pronounced wet and dry seasons. In this study, we performed model benchmarking to (a) compare hybrid model performance to PB and machine learning models and (b) examine the sensitivity of hybrid model performance to PB model parameter calibration, structural complexity, and variable selection. Hybrid models were generated by post‐processing process‐based models using Long Short‐Term Memory neural networks. Models were benchmarked within two northern California watersheds that are managed for both municipal water supplies and aquatic habitat. Though model performance varied substantially by watershed and error metric, calibrated hybrid models frequently outperformed both the machine learning model (for 72% of watershed‐model‐metric combinations) and the calibrated process‐based models (for 79% of combinations). Furthermore, hybrid models were relatively insensitive to PB model calibration and structural complexity, but sensitive to PB model variable selection. Our results demonstrate that hybrid models can improve streamflow prediction in Mediterranean‐climate watersheds. Additionally, hybrid model insensitivity to PB model parameter calibration and structural complexity suggests that uncalibrated or less complex PB models could be used in hybrid models without any loss of streamflow prediction accuracy, improving model construction efficiency. Moreover, hybrid model sensitivity to the selection of PB model variables suggests a strategy for diagnosing poorly performing PB model components.
Assessments of Arctic Cloud Vertical Structure From AIRS Using Radar‐Lidar Observations
Authors: Wang Xi , Liu Jian 
Published: July 2024

AbstractThe Atmospheric InfraRed Sounder (AIRS) aboard Aqua provides essential long‐term data on vertical cloud fraction, particularly valuable in the Arctic region. This study offers a comprehensive assessment of Arctic vertical cloud fraction derived from AIRS through a comparison with independent ground‐ and space‐based radar and lidar observations. In comparison to the measurements at the North Slope Alaska site, results reveal a significant underestimation of low‐level cloud cover by AIRS, especially for near‐surface clouds, while mid‐ and high‐level cloud fractions show better consistency. In comparison to the satellite‐based product from 3S‐GEOPROF‐COMB, the accuracy varies across different underlying surfaces (land vs. sea) and seasons. AIRS shows significant positive biases in mid‐level cloud fraction over sea surfaces with sea ice concentration below 15%, indicating potential limitations in the cloud retrieval algorithm in regions with large sea ice variations. The issue of low‐level clouds identification is primarily caused by the limited penetrating capability of infrared hyperspectral sensing and the accuracy of preceding surface and atmospheric state products, which diminish the accuracy of AIRS low‐level cloud fraction.