bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-agent Reinforcement Learning for the Control of Three-Dimensional Rayleigh–Bénard Convection
Authors: Vasanth Joel , Rabault Jean , Alcántara-Ávila Francisco , Mortensen Mikael , Vinuesa Ricardo 
Published: December 2024

AbstractDeep reinforcement learning (DRL) has found application in numerous use-cases pertaining to flow control. Multi-agent RL (MARL), a variant of DRL, has shown to be more effective than single-agent RL in controlling flows exhibiting locality and translational invariance. We present, for the first time, an implementation of MARL-based control of three-dimensional Rayleigh–Bénard convection (RBC). Control is executed by modifying the temperature distribution along the bottom wall divided into multiple control segments, each of which acts as an independent agent. Two regimes of RBC are considered at Rayleigh numbers $$\textrm{Ra}=500$$

Ra
=
500

and 750. Evaluation of the learned control policy reveals a reduction in convection intensity by $$23.5\%$$

23.5
%

and $$8.7\%$$

8.7
%

at $$\textrm{Ra}=500$$

Ra
=
500

and 750, respectively. The MARL controller converts irregularly shaped convective patterns to regular straight rolls with lower convection that resemble flow in a relatively more stable regime. We draw comparisons with proportional control at both $$\textrm{Ra}$$
Ra
and show that MARL is able to outperform the proportional controller. The learned control strategy is complex, featuring different non-linear segment-wise actuator delays and actuation magnitudes. We also perform successful evaluations on a larger domain than used for training, demonstrating that the invariant property of MARL allows direct transfer of the learnt policy.
Prevalence, Patterns and Correlates of Child and Adolescent Mental Disorders in Kumasi, Ghana: An Urban Community-Based Survey
Authors: Kusi-Mensah Kwabena , Inuwa Kawther , Otu-Ansah Caleb , Ekremet Peggy Asiedu , Sackey Ruth Charlotte , Owusu-Antwi Ruth , Ohene Sammy , Omigbodun Olayinka 
Published: December 2024

AbstractThis study examined the prevalence and correlates of mental disorders among youth in Kumasi, Ghana, through a community-based cross-sectional survey. 672 urban participants aged 6–17 years were surveyed. Mental disorders were screened using Rutter’s A2 Scale for Parent Assessment of Child Behaviour, with diagnoses confirmed by the Kiddie-Schedule for Affective Disorders and Schizophrenia. The Double Sampling method was used for weighted prevalence estimates, and correlates analysed using chi-square and logistic regression. Lifetime weighted prevalence of CAMH disorders was 30.4% (95% CI: 26.9–33.9), predominantly anxiety-related disorders, with current weighted prevalence 18.6% (95% CI: 15.7–21.5). Notably, lacking an active reading habit was associated with nearly three times the odds of mental illness. Children in the 3rd and 4th wealth quintiles had significantly higher odds of mental disorder (12- and 9-times increased odds, respectively), as did lack of caregiver homework supervision among children under 11 years. This study provides the first community-based prevalence figures for childhood mental disorders in Ghana, highlighting the link between poverty-related factors and mental health, and suggesting potential policy interventions to inform policy.
An extended study of syntactic breaking changes in the wild
Authors: Jayasuriya Dhanushka , Ou Samuel , Hegde Saakshi , Terragni Valerio , Dietrich Jens , Blincoe Kelly 
Published: December 2024

AbstractLibraries assist in accelerating the development of software applications by providing reusable functionalities. Libraries and applications that declare these libraries as dependencies become their clients. However, as libraries evolve, maintaining the dependencies in client projects can be challenging if the new version contains breaking changes. Yet, limited research focuses on analyzing the impact of breaking changes on client projects when updating dependencies in the wild. Hence, we conduct an empirical analysis using Java projects built using Maven to investigate the impact of breaking changes introduced between two library versions. Our dataset included 18,415 Maven artifacts, declaring 142,355 direct dependencies, out of which 71.60% were not up-to-date. We automatically updated these dependencies and discovered that 11.58% of the dependency updates resulted in breaking changes that affected the client, and almost half of them were introduced during a non-major update. We analyzed the changes in the libraries that contributed towards these breaking changes, and our results indicate that changes in transitive dependencies were a significant factor in introducing breaking changes. We further investigated if it was common for clients to use functionalities of transitive dependencies directly without declaring them. This showed that over half of the clients use transitive functionality. Therefore, we analyzed actions suggested to resolve these breaking changes introduced by transitive dependencies under the discussions on open-source platforms, and the frequently suggested action was to exclude the transitive dependency from the project configuration.
Their wellbeing affects our wellbeing: student perspectives of lecturer wellbeing and its consequences for student wellbeing
Authors: Rakow Katie E. , Priestley Michael , Byrom Nicola C. , Foster Juliet L. H. , Dommett Eleanor J. 
Published: December 2024

AbstractA “whole university approach” has been recommended for addressing concerns about the wellbeing of UK university lecturers and students. Previously, staff wellbeing has been explored from staff perspectives. Student wellbeing has been explored from the perspectives of both students and staff. However, little research has been conducted on student perspectives on staff wellbeing and its possible impact on students. Addressing this gap, this study explored student perceptions of their lecturers’ wellbeing and ways that it can impact on student wellbeing. Three themes were identified from the thematic analysis of 9 focus groups with 41 undergraduate students. First, students notice their lecturer wellbeing, particularly if they have the opportunity to interact with their lecturers. Second, students perceive that their lecturers’ wellbeing can be affected by university policies and practices, student behaviours, and external factors. Third, lecturer wellbeing and student wellbeing are often reciprocal, emphasising the importance of lecturer-student interactions. These findings have implications for a whole university approach, namely development of university practices that support sufficient time for constructive lecturer-student interactions, such as timetabling, allocation of administrative tasks, class size and staffing levels.
Outlining technical craft as technology and engineering education in Finnish school craft
Authors: Metsärinne Mika , Salonen Anssi , Kallio Manne , Virta Kalle , Hilmola Antti 
Published: December 2024

AbstractTechnology and engineering education (TEE) corresponds to technical craft in Finnish primary and secondary school craft subject. However, there have not been in the specific descriptions of the technology and engineering content in the subject in the national core curricula for basic education since 1994. The research task here was to outline what TEE is in Finnish primary and secondary school craft. The research method was a qualitative case study, based on the experts’ outlines. The core of TEE learning goals definitions, the content of engineering, and its pedagogy was used to analyse the data collected from TEE experts (n = 23). As a result, new theoretical foundations of TEE in general education are presented. The description includes the basics of the conditions of existence for the subject, and its key general leaning goals in the framework of technology education, main in engineering fields and methods and central pedagogical models. The results reveal the diverse and unified structure of TEE to be used in the craft subject in general education and teacher education, and in outlining and studying the future development of TEE.
Effect of cement paste and saline solution composition on chemical and physical binding of chlorides
Authors: Kuzielová Eva , Compeľová Kristína , Peciar Peter , Buňová Lenka , Kureková Valéria , Másilko Jiří 
Published: December 2024

AbstractChloride ingress, along with chemical and physical binding in cement pastes, was studied in relation to the paste composition, saline solution, and hydration regime used. Unblended cement paste and pastes prepared with combinations of SF with MK and SF with BFS, replacing 30% of the cement mass, were exposed to NaCl and geothermal solutions for 7 days, either directly or following 7 days of water curing. The surface and middle parts of the samples were evaluated using TGA, XRD, FTIR, ion chromatography (Cl concentration), and ICP-OES (Na concentration). In addition, compressive strength (CS) measurements were performed. In MK-containing samples, Cl-AFm (hydrocalumite) formed mainly through an ion exchange mechanism, while in BFS-containing samples and the reference pastes, Cl-AFm phases primarily formed through the reaction of Cl− with C3A and Ca(OH)2 and increased physical adsorption of Cl− onto C-(A-)S-H were determined. Exposure to NaCl solution led to more chlorides being chemically incorporated into Cl-AFm, as well as higher levels of physically adsorbed and free chlorides in the pore solutions, compared to the geothermal solution. Pozzolanic reactions of additives, the acceleration of hydration induced by the solutions, especially by the geothermal one, and the densification of the matrix by the products of chloride reactions in blended samples resulted in CSs comparable to or higher than those reached after standard water curing. CSs of referential samples decreased following the decalcification of the initially formed C-(A-)S-H phases.
Assessing the effects of land-use intensity on small mammal community composition and genetic variation in Myodes glareolus and Microtus arvalis across grassland and forest habitats
Authors: Kauer Lea , Imholt Christian , Jacob Jens , Kuehn Ralph 
Published: December 2024

Abstract

Context
Land-use intensification can alter small mammal community composition and induce loss of genetic variation in remaining populations. Fragmented landscapes favor generalist and synanthropic species, which are potential reservoirs of pathogens and pose risks to agriculture and forestry.

Objectives
This study aimed to evaluate the effects of land-use intensity on small mammal diversity in grassland and forest habitats, as well as on genetic variation patterns driven by geographic (isolation by distance) and environmental distance (isolation by resistance) factors.

Methods
We analysed differences in small mammal community diversity on grassland and forest plots with varying land-use intensities. Genetic analyses were conducted on Myodes glareolus and Microtus arvalis populations from each habitat, using microsatellites. Maximum Likelihood Population Effects models were employed to elucidate gene flow patterns and significant differences in genetic structure based on land-use intensity.

Results
Small mammal communities in grasslands were significantly less diverse than in forests. Land-use intensity had a significant effect on diversity within grassland but not within forest habitats. M. glareolus showed three genetic groups, while M. arvalis displayed no discernible population structure or landscape-related pattern. Land-use intensity did not significantly influence the genetic structure of either species. Gene flow in M. glareolus is best described by the IBR model.

Conclusion
Land-use intensity significantly affects small mammal community composition, particularly in grasslands. Neither species' genetics is directly impacted by land-use intensity but rather by landscape connectivity and distance. Risk assessments for rodent-borne zoonotic pathogens and crop damage should be framed within a habitat connectivity context.
A plug-and-play strategy for agrochemical delivery using a plant virus nanotechnology
Authors: Caparco Adam A. , González-Gamboa Ivonne , Chang-Liao Sabrina , Steinmetz Nicole F. 
Published: December 2024

AbstractDelivery of agrochemicals into soil presents a challenge, as the active ingredients are often hydrophobic and do not possess adequate soil mobility to reach their target pest. Previously, plant virus nanoparticles have been shown to penetrate soil and deliver agrochemicals for the treatment of plant parasitic nematodes. For example, tobacco mild green mosaic virus (TMGMV) can be functionalized with agrochemicals through bioconjugation, infusion at the coat protein interface, or encapsulation through thermal shapeshifting (rod-to-sphere). There continues to be a need to expand approaches for agrochemical display and delivery with a need for plug-and-play technology to be applicable for multiple nanoparticle platforms and agrochemicals. Toward this goal, we turned toward a bio-specific coupling strategy making use of the biotin-(strept)avidin system. Herein, we conjugated TMGMV with either avidin or biotin using azide-alkyne cycloaddition. The avidin/biotin-functionalized TMGMV nanoparticles were then characterized by gel electrophoresis and electron microscopy to confirm cargo loading and the nanoparticle’s structural integrity. Soil column assays confirmed that soil mobility was maintained upon chemical modification. Ivermectin modified with biotin or streptavidin linkers was then introduced to the TMGMV-avidin/biotin nanoparticles and binding propensity and loading were validated by QCM-D and a competitive ELISA. Finally, the ivermectin-loaded TMGMV nanoparticles were used to treat C. elegans in a gel burrowing assay, demonstrating that either pesticide loading strategy resulted in active TMGMV nanoparticle formulation that significantly reduced the mobility of nematodes, even after passing through soil. In stark contrast, free ivermectin only exhibited efficacy when applied directly to nematodes; the free pesticide was lost in the soil column—highlighting the need for a delivery system. The presented approach provides a facile plug-and-play approach for pesticide loading onto TMGMV nanoparticles. In particular, biotinylated TMGMV with streptavidin-conjugated ivermectin served as the most effective formulation. Importantly this method does not require heat, which contrasts our previous method of thermal reshaping that requires sample and pesticide exposure to temperatures > 96 °C. We envision the bio-specific loading strategy could be extended to other protein or inorganic nanoparticles to advance soil treatment strategies.
Participatory engagement to reduce communication gaps
Authors: Torres-García Legna M. , Valdés-Pizzini Manuel , Valdés-Calderón Krystalliá , Frank-Gilchrist Donya , Kotowicz Dawn M. , Maldonado-González Emmanuel , Vargas-Babilonia Priscila 
Published: December 2024

AbstractUnderserved communities, especially those in coastal areas in Puerto Rico, face significant threats from natural hazards such as hurricanes and rising sea levels. Limited funding hinders the investment in costly mitigation measures, increasing exposure to natural disasters. Providing coastal resources and data products through effective communication mechanisms is fundamental to improving the well-being of these underserved coastal communities. The overall objectives of the pilot effort to engage and connect with underserved coastal communities in Puerto Rico were the following: (1) compile a comprehensive database of the projects and resources relevant to natural hazards in Puerto Rico; (2) foster connections with Puerto Rican interested parties to better understand their priorities regarding coastal hazards and provide them with pertinent U.S. Geological Survey (USGS) resources; and (3) identify knowledge gaps to guide future USGS projects in Puerto Rico. Here we outline our participatory engagement framework and process, along with two specific resources developed with the information collected from this effort. These resources are available in English and Spanish and consist of user-friendly, non-technical information products. Among them are: (1) a website where users can learn about USGS research on landslides, hurricanes, earthquakes, water resources, coastal hazards, tsunamis, and ecosystem hazards and environmental contaminants, and (2) a geonarrative highlighting shoreline changes in Puerto Rico with sections on historical shoreline trends, hurricane impacts, and potential solutions that could help protect communities and mitigate coastal hazards. Continuing participatory engagement in future projects could enhance the accessibility and usability of natural hazards resources within the community.
Optimizing quantum machine learning for proactive cybersecurity
Authors: Rosa-Remedios Carlos , Caballero-Gil Pino 
Published: December 2024

AbstractThe evolution of cyberattacks requires a continuous race to implement increasingly sophisticated techniques that allow us to stay ahead of cybercriminals. Thus, a relevant inverse problem in cybersecurity involves determining underlying patterns or models of possible cyber threats based on observed data. In particular, the processing of massive data combined with the application of Machine Learning methods and other techniques derived from Artificial Intelligence have so far achieved very significant advances in preventing and mitigating the impact of many cyberattacks. Given that the keyword in cybersecurity is anticipation, this work explores the possibilities of quantum computing and, in particular, of Quantum Machine Learning to have, when the quantum computing era arrives, the most optimal parameterisations to put these models into practice. Although the application of quantum technologies in a real context may still seem distant, having studies to assess the future viability of Quantum Machine Learning to identify different types of cyberattacks may be a differential element when it comes to ensuring the cybersecurity of essential services. For this reason, this work aims to use several datasets of known problems in the field of cybersecurity to evaluate the most optimal parameterisations in some known Quantum Machine Learning models, comparing the results with those obtained using classical models. After analysing the results of this study, it can be concluded that Quantum Machine Learning techniques are promising in the context of cybersecurity, giving rise to future work on a wider range of cybersecurity datasets and Quantum Machine Learning algorithms.
3D radiative transfer modeling of almond canopy for nitrogen estimation by hyperspectral imaging
Authors: Oswald Damian , Pourreza Alireza , Chakraborty Momtanu , Khalsa Sat Darshan S. , Brown Patrick H. 
Published: December 2024

Abstract
Nitrogen (N) is vital for plant growth, but its imbalance can negatively affect crop yields, the environment, and water quality. This is especially crucial for California’s almond orchards, which are the most N-hungry nut crop and require substantial N for high productivity. The current practices of uniform and extensive N application lead to N leaching into the groundwater, creating environmental hazards. Traditional remote sensing methods often rely on data-driven approaches that work well statistically (achieving a high R2 value) with one dataset but aren’t adaptable across different datasets. To create a more robust, data-driven model, one would typically need a vast and varied collection of datasets. Our goal, however, is to develop a more universally applicable model using smaller datasets, typical of commercial orchards, that can accurately estimate N content in tree canopies, regardless of differences in spatial, spectral, and temporal data. In this study, we investigate and evaluate multiple remote sensing approaches for estimating N concentration in Californian almonds, utilizing hyperspectral imaging at the canopy level. We assess various classical vegetation indices, machine learning models, and a physics-informed 3D radiative transfer model. While cross-validated results show comparable results for radiative transfer models and best-performing machine learning models, most single vegetation indices are not capable of exceeding the baseline model
$$\:f\left(\mathbf{x}\right)=\bar{y}$$
and thus had R2 value less than 0. Despite being less commonly used, 3D radiative transfer modeling shows promise as a strong and adaptable method, producing results that are comparable to the best machine learning models.
The impact of handwriting fluency on bursts of written language and text quality in undergraduates
Authors: Carnota Andrés , Pascual Mariona , Suárez-Coalla Paz 
Published: December 2024

AbstractIn this study, we investigated the contributions of handwriting and semantic writing fluency to the bursts of written language during opinion composition among Spanish-speaking undergraduate students (N = 59; Mage = 18.9). Using hierarchical regression analysis, we found that burst length and burst fluency were the primary predictors of text quality. A parallel mediation model further revealed that burst length and burst fluency mediated the relationship between handwriting and semantic fluency and text quality. Specifically, burst length fully mediated the relationship between written semantic fluency and text quality, whereas burst fluency mediated the relationship between both handwriting and semantic fluency and text quality. Notably, handwriting and semantic fluency did not directly influence text quality; rather, their effects were fully mediated by burst length and fluency. These findings highlight the significance of burst length and fluency as robust predictors of text quality in young adults, underscoring their role in the interplay between isolated graphomotor and semantic abilities and writing performance.
The effectiveness of phonological training and morphological training in Chinese children with reading difficulty
Authors: Shen Linling , Feng Guoyan , Shi Liping , Wu Yu , Cao Fan 
Published: December 2024

AbstractPurpose: Reading difficulty (RD) affects 5–10% of the population across languages (Wagner in J Learn Disabil 53(5), 354–365, 2020). However, only a few studies have focused on developing effective interventions for Chinese children with RD. Both the phonological deficit and morphological deficit hypotheses have been proposed to explain the underlying cognitive cores of RD in Chinese, with limited research directly comparing the interventions targeting these skills. Method: In the current study, we designed and directly compared a phonological and a morphological training program in improving reading for Chinese children with RD. The phonological training program addressed phonological awareness and conversion from orthography to phonology, while the morphological training addressed morphological awareness and conversion from orthography to meaning. Sixty-two fifth-grade students with RD were randomly assigned to the phonological, morphological intervention, or a business-as-usual (BAU) group. Results: Both the phonological training (PT) and the morphological training (MT) improved sentence reading fluency, character naming, one-minute irregular character naming, and phonological awareness compared to the BAU group. Furthermore, we found that responsiveness to the PT was negatively correlated with phonological awareness and maternal education, while responsiveness to the MT was positively correlated with rapid automatized naming (RAN) skills. Conclusion: The phonological training and the morphological training had similar effectiveness in promoting reading in Chinese children with RD, which provides important insights into reading intervention for Chinese RD.