bluuebunny/crossref_metadata_2025 huggingface dataset:
A Pilot Study on Understanding the Contextual Factors Impacting the Implementation of Antibiotic Stewardship Program in a Single Health Center Serving Rural and Underserved Communities in the United States – A Mixed Method Approach
Authors: Nkemdirim Okere Arinze , Pinto Anthony Ryan , Suther Sandra
Published: January 2025

Objective: This study aimed to identify contextual factors influencing the implementation of an Antibiotic Stewardship Program (ASP) in a rural primary care center serving underserved communities.
Methods: A mixed-methods approach guided by the Consolidated Framework for Implementation Research (CFIR) was employed. Data were collected through semi-structured interviews, focus groups, and surveys with clinical staff and leadership at a Federally Qualified Health Center (FQHC). The CFIR framework was used to explore barriers and facilitators within the clinic’s inner and outer settings, focusing on staff perceptions, challenges, and readiness for ASP implementation.
Results: Strong staff support for ASPs was identified, with participants emphasizing their potential to improve patient outcomes and antibiotic prescribing practices. Barriers included insufficient training, high workload, and patient pressure to prescribe antibiotics. Leadership commitment, enhanced communication systems, and tailored educational materials were identified as critical facilitators for successful implementation. Participants highlighted the need for accessible educational tools and streamlined protocols to improve engagement and compliance.
Conclusion: Implementing an ASP in rural and underserved settings is feasible but requires addressing site-specific challenges. Insights from this study underscore the importance of understanding contextual factors to inform evidence-based strategies for ASP adoption. The structured use of CFIR provided a comprehensive framework to guide implementation efforts, ultimately supporting better antibiotic use and public health outcomes in resource-constrained healthcare settings.
Efficient Identity-Based Universal Designated Verifier Signature Proof Systems
Authors: Yang Yifan , Zhou Xiaotong , Su Binting , Wu Wei
Published: January 2025

The implementation of Universal Designated Verifier Signatures Proofs (UDVSP) enhances data privacy and security in various digital communication systems. However, practical applications of UDVSP face challenges such as high computational overhead, onerous certificate management, and complex public key initialization. These issues hinder the adoption of UDVSP in daily life. To improve the efficacy of existing UDVSP, Lin et al. in IEEE TSC’23 designed a bilinear pairing-free UDVSP system but their proposal still involves cumbersome certificate management, and inherent interactive operations that can sometimes significantly degrade system efficiency. In this paper, we first utilize the identity-based (ID-based) SM2 digital signature scheme to construct an ID-based UDVSP system which sidesteps the cumbersome certificate management issue. To further remove the interactive requirement, we also employ the OR-proof and Fiat-Shamir technologies to design the other ID-based UDVSP system. Our designs not only own the same bilinear pairing-free advantage as Lin et al.’s proposal, but also achieve the certificate-free or non-interactive goal. Security proofs and performance analysis confirm the viability and efficiency of the systems we have put forward.
Comparative Analysis of Urban and Rural Ecosystems in the Context of Suitability for Honeybees
Authors: Gerula Dariusz , Węgrzynowicz Paweł , Kołtowski Zbigniew
Published: January 2025

The present study set out to compare the performance of honeybees maintained in ur-ban and agricultural environments across various regions in Poland. A range of meas-urements and observations were used to assess overwintering, development, strength, swarming behaviour, honey yield, and Varroa infestation in bee colonies in five towns and five surrounding villages. The rural apiaries were located 4.5-39.5 km away from the urban apiaries. The colonies were kept in wooden Dadant hives and were led by Apis mellifera carnica queens. The brood count and colony strength were assessed based on the Liebefeld method, while Varroa destructor infestation levels in the colonies were determined using icing sugar at the end of July. The urban apiaries exhibited signifi-cantly higher brood rearing dynamics. Consequently, an increase in brood count in spring resulted in a significant increase in Varroa infestation levels in summer. In certain regions, urban apiaries exhibited higher honey production, though this was influenced by geographic location and the availability of bee forage. The significant variation in most traits, including honey production, was observed depending on the region. Vari-ations between years in the study were observed in bee colonies overwintering, brood numbers in the pre-spring period, and bee population in summer. This may suggest the presence of differing weather conditions.
Matrix Reforming of Hydrocarbons: New Possibilities For Low-Tonnage Gas Processing and Energy
Authors: Arutyunov Vladimir , Savchenko Valery , Nikitin Aleksey , Sedov Igor V.
Published: January 2025

The huge unconventional resources of natural gas in the earth's crust make it in the future not only the main source of raw materials for global energy, but also the cheapest and most abundant raw material for the production of many basic petrochemical products. However, technological complexity and high energy consumption for multistage processes of converting methane into thermodynamically less stable products remain the main problem constraining development of gas chemistry. A promising solution may be a matrix technology for the autothermal reforming of natural gas into syngas or hydrogen. This technology is based on internal recuperation of heat of conversion products, which is implemented in the surface combustion mode. The review presents the basic principles of matrix reforming, the results achieved so far and the most promising areas of its application.
Research on the Integration and Innovation of Moral Education Courses in Sustainable Development Education
Authors: Li Wei , Gao Zhi-Qin
Published: January 2025

This study explores the integration of moral education courses and sustainable development education, and provides relevant integration strategies and innovative practice methods. Based on an analysis of the fundamental concepts of sustainable development education and an investigation into the development process and current status of moral education courses, the study elaborates on the objectives, principles, content, and pathways for combining moral education courses with sustainable development education. In the innovative practice section, innovative teaching models such as project-based learning and situational teaching are introduced, and modern teaching technologies such as multimedia and the internet are used to enrich teaching resources. The study also designs an evaluation index system and selects appropriate evaluation methods to assess the integration effects of innovative practices, summarizes the main research findings, theoretical and practical significance, and discusses the limitations of the study and future prospects.
Particulate Matter Quantification via DINÉ (Digitally INtegrated Environmental) Arduino UNO R3 Platform for Environmental Quality, Safety, and Health
Authors: Bahe Ember , Winarski Daniel
Published: January 2025

After the hardware-integration of an Arduino UNO and the PMSA003 particulate matter (PM) sensor, the Arduino UNO was programmed to count six PM diameters: 0.3, 0.5, 1.0, 2.5, 5, and 10 micrometers, for a fixed air volume of 0.1 Liters. Indoor PM data within 12 different locations at Navajo Preparatory School, Farmington, NM. Outdoor atmospheric PM data was then gathered in Tucson, Arizona, before and after various weather events, such as high winds (PM generating) and rain (PM scrubbing). Additionally, indoor and outdoor data gathered in West Virginia during heavy smoke from the 2023 Canadian forest fires. The output of the Arduino UNO included current, average, maximums, and minimums PM values for each particle size. The Arduino UNO also calculated the least-squares fit a negative-exponential model of the particulate matter as a function of count and particle size, and calculated the correlation “R” between the actual PM count data and the model. Correlations as high as 99.99% were achieved at a confidence of 99.95%. This will help to understand the PM problems on the Navajo Nation, which could include radioactive dust from over 500 abandoned uranium mines.
The Influence of Body Composition and Lifestyle Factors on Resting Energy Expenditure and Its Role in Cardiometabolic Risk: A Cross-Sectional Study
Authors: Ostrowska Joanna , Szostak-Węgierek Dorota
Published: January 2025

In this study, we investigated the associations between lifestyle factors (diet, physical activity, sleep), body composition, and resting energy expenditure (REE) in a cohort of 80 healthy, non-obese adults aged 30–45 years. Using indi-rect calorimetry, accelerometers, and bioelectrical impedance analysis (BIA), we assessed REE, physical activity levels, sleep duration, and biochemical parame-ters to identify factors contributing to individual variations in REE and their potential role in modulating cardiometabolic risk. We found that fat-free mass (FFM) was the strongest predictor of REE, along with related metrics such as total body water, body cell mass, and muscle mass (p < 0.0001, adj. R² > 0.5). In univariable models, all physical activity intensities were significantly associated with REE, but only moderate physical activity (MPA) remained significant after adjusting for sex and FFM (β = 2.2 ± 1.0, p < 0.05, adj. R² = 0.589). Similarly, a positive association between HDL-C and REE persisted after adjustments (β = 5.0 ± 2.0 kcal/d, p < 0.05, adj. R² = 0.588). These direct links may be attributed to habitual, spontaneous physical activity, which generates post-exercise metabolic elevation and promotes adipose tissue brown-ing, resulting in favorable metabolic effects. Other biochemical and lifestyle factors, including HOMA-IR, insulin levels, tri-glycerides, and total energy intake, showed positive associations with REE in the crude model. However, these relationships diminished after adjustment, suggesting that their influence is likely mediated by factors such as body compo-sition, body size, and sex. Finally, no significant relationship between sleep and REE was observed in our cohort under naturalistic conditions, possibly due to the alignment of participants’ sleep durations with recommended guidelines.
Investigations on the Design and Implementation of Reinforcement Learning Using Deep Learning Neural Networks
Authors: Tudoroiu Roxana-Elena , Zaheeruddin Mohammed , Curiac Daniel-Ioan , Radu Mihai Sorin , Tudoroiu Nicolae
Published: January 2025

This paper investigates the design and MATLAB/Simulink implementation of two intelligent neural reinforcement learning control algorithms based on deep learning neural network structures (RL DLNNs), in the case of a complex Heating Ventilation Air Conditioning (HVAC) centrifugal chiller system (CCS) selected as a case study. This system poses significant control-related challenges due to its high dimensionality and strong nonlinearity multi-input multi-output (MIMO) structure, coupled with strong constraints and a substantial impact of measured disturbance on tracking performance. As a beneficial vehicle for "proof of concept", two simplified CCS MIMO models were derived. At the same time, many simulations were run to demonstrate the effectiveness of both RL DLNN control algorithm implementations compared to two conventional control algorithms. Moreover, the experiments involving the two investigated data-driven advanced neural control algorithms prove their high potential to adapt to various types of nonlinearities, singularities, dimensions, disruptions, constraints, and uncertainties that inherently characterize real-world processes.
The Formation of Widmanstätten Side-Plate Precipitates Comprising Duplex FCC and L12 Phases in an As-Air-Cooled Fe-Mn-Al Steel
Authors: Chemeli Korir Rosemary , Cheng Wei-Chun
Published: January 2025

Understanding the constituent phases and their corresponding phase transformations are crucial for the determination of the performance and application characteristics of the alloy systems. The methodology in the Fe-0.8 C-8.3 Mn-16.9 Al (at.%) alloy included the annealing at and air cooling from 1100°C. This study investigates the minor Widmanstätten side-plate precipitates (ppts) distributed uniformly in the major body-centered cubic (BCC) matrix. During air-cooling, a face centered cubic (FCC) phase precipitated in the BCC matrix in the form of the Widmanstätten side-plates through a precipitation transformation. Upon further cooling, the high-temperature FCC phase underwent the spinodal decomposition and decomposed into two low-temperature FCC phases, that is, solute-lean FCC′ and solute-enriched FCC′′. The FCCꞌꞌ phase in the form of nanosized particles precipitated homogeneously in the FCCꞌ matrix. For the alloy after further cooling, an ordering reaction occurred, and the solute-enriched FCC′′ phase transformed into the L12 phase. Therefore, The Widmanstätten side-plate ppt consists of duplex FCC and L12 phases. The nanosized L12 particles precipitated homogeneously in the FCC matrix. The insights gained from this study contribute to deeper understandings of phase stability and transformation mechanisms in Fe-Mn-Al alloys, which can inform their future design.
Different Isometric Exercise Modalities Induce Divergent Acute Effects on Myocardial Work in Trained Hypertensive Patients with Ischemic Heart Disease
Authors: Caminiti Giuseppe , Marazzi Giuseppe , Volterrani Maurizio , D'Antoni Valentino , Fecondo Simona , Vadalà Sara , Sposato Barbara , Giamundo Domenico , Vitarelli Matteo , Morsella Valentina , Iellamo Ferdinando , Manzi Vincenzo , Perrone Marco Alfonso
Published: January 2025

Background: Isometric exercise effectively reduces blood pressure (BP) but its effects on myocardial work have been poorly studied. In the present study we compared acute changes in myocardial work during two different isometric exercise, bilateral knee extension and handgrip in patients with hypertension and underlying ischemic heart disease (IHD). Methods: 48 stable, trained patients with hypertension and IHD were enrolled. They were randomly assigned to perform a single session of bilateral knee extension (IKE) or handgrip (IHG) or no exercise (control) with a 1:1:1 ratio. Both exercises were performed at 30% of maximal voluntary contraction and lasted three minutes. Echocardiography and BP measurements were performed at rest, during the exercise and after ten minutes of recovery. Results: both exercises were well tolerated, and no side effects occurred. During the exercise: systolic BP increased significantly in the IKE group compared to IHG and control (ANOVA p <0.001). LVGLS decreased significantly in IKE (-21%) compared IHG and control (ANOVA p 0.002). The global work index increased significantly in KE (+28%) compared to HG and control (ANOVA p 0.034). Global constructive work and wasted work increased significantly in the IKE compared to HG and control (ANOVA p 0.009 and <0.001 respectively). Global work efficiency decreased significantly in the IKE group (-8%) while remained unchanged in the IHG and controls (ANOVA p 0.002). Systolic BP increased significantly in the KE group and was unchanged in HG and control. Conclusion: myocardial work efficiency was impaired during isometric bilateral knee extension but not during handgrip. Handgrip evoked a limited hemodynamic response.
Effects of the Total Thickness of Multilayer Thermite Materials Al-CuO on the Combustion Mode and Morphology of Reaction Products
Authors: Novoselcev Alexander , Shiryaev Maxim , Ryazanov Roman , Volkova Lidiya , Sysa Artem , Dubkov Sergey , Gromov Dmitry , Lebedev Egor
Published: January 2025

Multilayer Al-CuO thermite materials are a prominent representative of metastable intermolecular composites, which are characterized by outstanding energy and combustion properties. In this work, we investigated the effect of the total thickness of the multilayer Al-CuO thermite material (enriched with aluminum), formed on the surface of sitall substrates, on the combustion mode and the morphology of the reaction products. High-speed video recording from different angles allowed us not only to estimate the combustion front propagation velocity, but also to visually estimate the gas evolution intensity. Using scanning electron microscopy in combination with a focused ion beam and energy-dispersive X-ray spectroscopy, the morphology and composition of the combustion products of the multilayer structures were studied. The obtained experimental data allowed us to describe three combustion modes of multilayer thermite materials in terms of the combustion front temperature and to relate this parameter to the total thickness of the multilayer structure.
A Review of Fengshui Forests: Ecological Functions, Humanistic Values, and Potential Applications to Enhance Biodiversity in Urban Green Landscapes and Achieve Sustainable Development Goals
Authors: Liang Lingzi , Wang Xiuzhi , Qiu Jian-Wen , Gong Qin , Li Xun , Tsim Siu-Tai
Published: January 2025

Sustainable urban development increasingly aligns with the Sustainable Development Goals (SDGs), highlighting the importance of integrating local cultural landscapes into city planning. One compelling example is the concept of fengshui forests in China, which are deeply rooted in traditional beliefs associated with prosperity for local communities. This study explores how fengshui forests can inform urban landscape design, particularly in the context of biodiversity conservation. A comprehensive literature review was conducted, examining studies on the ecological functions and cultural significance of fengshui forests. This analysis included research articles, case studies, and ecological assessments, revealing that fengshui forests provide essential ecosystem services—such as preserving biodiversity, regulating microclimates, and sequestering carbon—while also offering unique cultural insights, economic resources, and tourism potential. Recognizing the critical role of plant selection and combination in urban landscape design, we compiled a database of 1,196 recorded plant species from fengshui forests, detailing their physiological traits, geographical distribution, and social values. By employing diverse plant pairing principles, urban landscape designers can select suitable species to create green spaces that support a well-functioning food web and ecosystem, ultimately fostering biodiversity conservation. By harnessing both the ecological functions and cultural values of fengshui forests, this research highlights their potential to enhance urban eco-landscape design, promote eco-tourism, and aid in the preservation of local species. These forests, with their traditional roots and ecological significance, hold promise for advancing ecological civilization through effective biodiversity conservation and sustainable urban planning.
What Personality Dimensions May Influence the Risk of Smartphone Addiction in Children?
Authors: CONTE STELLA , Ghiani Carla , Casati Lorenzo , Truzzoli Roberto , Nicotra Eraldo Francesco
Published: January 2025

Background: Smartphones usage in school-aged children has increased over the last two decades. This overuse interferes in emotions regulation and interpersonal relationships. The purpose of this work was to analyze the interplay between smartphone addiction risk and personality dimensions in primary school children. Methods: The Smartphone Addiction Risk for Children Questionnaire (SARCQ) and the Big Five Children questionnaire (BFC) were administered to a sample (N =94) [EN1] of children. The aim of this research is to verify the percentage of Smartphone Addiction (SA) in a sample of primary school children and to explore the relationship between personality dimensions and SA.Results: We found that, in our sample, the percentage of children matching the definition of emotional addiction from smartphones is 16% and that a subgroup of children using the smartphone as a transitional object represents 15% of the sample. The correlations between the SARCQ and BFC factors showed a significant negative correlation between the “I’m not afraid with you” (INAWY) factor and Friendliness, INAWY and Conscientiousness and between INAWY and Openness. In contrast, a positive correlation between INAWY and the Emotional Instability factor has been observed. For the “Linus Blanket” (LB) factor a significant negative correlation with the Friendliness and with the Conscientiousness factor have been observed. Conclusion: The risk of SA, with the use of the smartphone as "emotion-handling tool" or as a "transitional object", was observed in children with personality negative dimensions.
Geopolitical Shocks and Market Resilience: Evidence from Commodity, Crude Oil, Natural Gas, and Gold Markets
Authors: Aysan Ahmet Faruk , Ullah Mirzat , Mayburov Igor A.
Published: January 2025

Amid heightened geopolitical risk (GPR) shocks this study empirically investigates the dynamic
interconnectedness among key commodities—namely crude oil, natural gas, and gold
markets—to evaluate their potential resilience to unfolding crises, including the Russia-Ukraine
conflict, Middle Eastern supply chain disruptions, the COVID-19 pandemic, and the ongoing
global economic recession. Utilizing a comprehensive daily dataset spanning January 2, 2008, to
November 30, 2024, this research examines a significant time period that encompasses multiple
global and regional financial crises. For empirical validation, the study employs the advanced
econometric framework of TVP-VAR modeling. The findings reveal that commodity indices and
gold primarily function as transmitters of volatility and spillovers, while the crude oil and natural
gas—serves as the principal recipient of external shocks. The results from net—spillover
estimation highlight that GPR, especially those arising from the United States and Russian
Federations exert a more pronounced influence on the interconnectedness of commodity markets
compared to GPR at global-level. This study observed that net volatility spillovers varies across
underlined markets where GPR-Russ found to negatively influence net spillovers in the energy
sector, while exerting a positive effect on gold markets. The study provides practical
market—based insights for policymakers, investors, and stakeholders seeking to navigate periods
of uncertainty where this study underscores the critical role of global and regional GPR in
shaping the interconnected dynamics of global commodity markets.
A Combined Partial and Stochastic Differential Equations Bayesian Framework for Deep-Time Phylogenetic Inference: Integrating Mini-Batch Physics-Informed Neural Networks (PINNs) and Fossil Calibrations
Authors: Montgomery Richard Murdoch
Published: January 2025

We present a unified methodology for reconstructing deep-time evolutionary histories by fusing partial differential equations (PDEs), stochastic PDEs (SPDEs), and Bayesian inference. Starting with a deterministic reaction–diffusion model, we embed fossil calibrations as interior constraints and leverage mini-batch training of physics-informed neural networks (PINNs) to overcome computational challenges. This framework accommodates both deterministic and stochastic trait evolution, capturing logistic selection effects and random environmental fluctuations over tens of millions of years. Fossil data—with time uncertainty of ±0.5 Myr—are assimilated within a Bayesian paradigm, updating PDE/SPDE parameters and morphological trajectories. Our results demonstrate rapid convergence, controlled error accumulation, and flexible handling of large morphological datasets. We further showcase a transition to an SPDE approach for modeling inherent evolutionary noise, revealing nuanced trait trajectories that better mirror real-world uncertainties. The proposed multi-level pipeline provides a robust, scalable toolkit for phylogenetic reconstructions that unify morphological, molecular, and paleontological evidence.
Age-Aware Scheduling for Federated Learning with Caching in Wireless Computing Power Networks
Authors: Zhuang Xiaochong , Luo Chuanbai , Xie Zhenghao , Li Yu , Jiang Li
Published: January 2025

With the rapid development of the Wireless Computing Power Network (WCPN), the urgent need for data privacy protection and communication efficiency led to the emergence of the Federated learning (FL) framework. However, the time delay leads to dragging problems and reduces the convergence
performance of FL in the training process. In this article, we propose a FL resource scheduling strategy based on information age perception in WCPN, which can effectively reduce the time delay and enhance the convergence performance of FL. Moreover, a data cache buffer and a model cache buffer are set up at the user and the central server respectively. Next, we formulate the parametric age-aware problem to minimize the age of global parameter, energy consumption and FL service latency simultaneously. Taking account of the dynamic WCPN environment, the optimization target is modeled as a Markov decision process (MDP), and Proximal Policy Optimization (PPO) algorithm is used to achieve the optimal solution. Finally, a large number of numerical simulation results prove the superiority and outstanding performance of the proposed method.
Malaria and Environmental Determinants in Bangladesh: Implications for Occupational Health and Disease Control
Authors: Rahman Abdur , Hossain Md. Mozammal
Published: January 2025

Malaria remains a significant public health challenge in Bangladesh, driven by a complex interplay of environmental determinants and occupational exposure. This paper explores the climatic and anthropogenic factors influencing malaria transmission dynamics, including temperature, humidity, rainfall, deforestation, urbanization, and agricultural practices. Seasonal variations, particularly during monsoons, create ideal conditions for mosquito proliferation, exacerbating the risk of outbreaks. High-risk occupational groups, such as agricultural workers, forest laborers, and construction workers, face disproportionate exposure due to their prolonged time in vector-rich environments. The analysis underscores the need for integrated malaria control strategies that incorporate environmental management and targeted occupational health interventions. Recommended measures include improved vector control, sustainable land-use policies, protective equipment for workers, and enhanced health education programs. By addressing these environmental and occupational determinants, policymakers can strengthen disease prevention efforts and mitigate the socio-economic burden of malaria in Bangladesh.
Studying the of Anxiety in the Workplace of Generation Y and Z Through Brain Science Methods
Authors: Bold Sanjaa . , Mijiddorj Banzragch . , Sosorbaram Batchimeg .
Published: January 2025

In this research, the personality traits of individuals were studied at the intersection of human resource management, psychology, and neuroscience using experimental research methodologies. The study’s foundation lies in exploring how personality traits relate to workplace interpersonal dynamics, integrating theoretical and methodological frameworks from these three fields. Recent studies in management have focused on interpersonal communication patterns. Therefore, this research aims to examine the personality traits that negatively impact organizational relationships by correlating them with the behavioral patterns of individuals across different age groups. In the management studies, the personality traits identified in the “Five Factor Model” that categorized into positive and negative groups based on their contextual influences. As for Neuroscience, it examines the triggers of positive and negative behaviors using the “Neuropsychological model of emotion (NME)”. The distinct feature of our study lies in integrating models from these fields and applying neuropsychological techniques to explore workplace relationships.The psychological anxiety levels of participants in response to the stimuli were observed through alpha and beta wave activity in the prefrontal regions of the brain’s left and right hemispheres.The reliability of the proposed model was evaluated, yielding a result of 82.6.
Multi-modal Learning with Dynamic Integration for Video Temporal Localization
Authors: Thompson Mia , Hsu Lobry , Harris Liam
Published: January 2025

We investigate the challenging task of text-guided video temporal grounding, which focuses on determining the precise temporal interval of a specific event in a video based on natural language descriptions. Unlike existing methods that primarily rely on RGB visual features, we introduce a novel multi-modal framework designed to extract and integrate complementary information from videos using multiple modalities. Our approach utilizes RGB frames to capture appearance, optical flow to highlight motion dynamics, and depth maps to discern scene structure. While RGB frames provide detailed visual context, they are susceptible to background noise and clutter. Therefore, optical flow is employed to focus on significant motion patterns, and depth maps are incorporated to understand spatial configurations, especially when actions involve objects identifiable by their shapes. To achieve effective integration and cross-modal learning, we propose a dynamic integration mechanism leveraging transformer-based architectures. This mechanism models interactions between modalities and dynamically assigns importance weights to each modality based on contextual relevance. Additionally, we incorporate intra-modal self-supervised learning to enhance feature representations within each modality, promoting robust learning across videos. Extensive experiments conducted on the Charades-STA and ActivityNet Captions datasets validate the superiority of our approach. Our framework, referred to as \textit{MODIFUSE} (Multi-modal Dynamic Integration with Fused Understanding for Scene Events), significantly outperforms state-of-the-art methods, demonstrating its capability to handle complex scenarios with diverse visual and textual content.
Evaluating the Implementation of Early Childhood Care and Education Policies in Debre Tabor City
Authors: Fajinmi John , Naqvi Maahir
Published: January 2025

This study aims to evaluate the implementation of Early Childhood Care and Education (ECCE) policies in Debre Tabor City, Ethiopia. Despite the significant role of ECCE in fostering foundational learning and socio-emotional development in children, the effectiveness of policy implementation remains underexplored in many regions. Through a mixed-methods approach, this research examines the key components of ECCE policy execution, including policy frameworks, resource allocation, stakeholder involvement, and the quality of early childhood education services provided. Data were collected through interviews with policymakers, teachers, and parents, as well as classroom observations and document analysis. The findings indicate that while policies are in place, challenges such as limited resources, inadequate teacher training, and inconsistent enforcement hinder effective implementation. Additionally, the study highlights the importance of community engagement and collaborative efforts in overcoming these barriers. Based on the findings, recommendations are proposed to improve the quality and reach of ECCE services in Debre Tabor City, ensuring a more equitable and effective early education system for all children.
Stimulus-Transcription Coupling of TRPM3 Channels: A Signaling Pathway from the Plasma Membrane to the Nucleus
Authors: Thiel Gerald , Rössler Oliver G
Published: January 2025

Transient receptor potential melastatin-3 (TRPM3) channels are cation channels activated by heat and chemical ligands. TRPM3 regulates heat sensation, secretion, neurotransmitter release, iris constriction, and tumor promotion. Stimulation of TRPM3 triggers an influx of Ca2+ ions into the cells and the initiation of an intracellular signaling cascade. TRPM3 channels are regulated by phosphatidylinositol 4,5-bisphosphate, the  subunit of G-protein-coupled receptors, phospholipase C, and calmodulin. Extracellular signal-regulated protein kinase ERK1/2 and c-Jun N-terminal protein kinase (JNK) function as signal transducers. The signaling cascade is negatively regulated by the protein phosphatases MKP-1 and calcineurin and increased concentrations of Zn2+. Stimulation of TRPM3 leads to the activation of stimulus-responsive transcription factors such as AP-1, CREB, c-Fos, c-Jun, Egr-1, and Elk-1. Potential delayed response genes such as interleukin-8 and calcitonin gene related peptide (CGRP) have been identified. TRPM3-induced gene transcription is controlled by epigenetic regulators, including the histone acetyltransferases CBP and p300, as well as proteins of the bromodomain and extra terminal domain (BET) family. Elucidating the TRPM3-induced signaling cascade provides insights into how TRPM3 stimulation alters numerous biochemical and physiological parameters within the cell and throughout the organism, and offers intervention points for manipulating TRPM3 signaling and function.
Navigating the Alignment Challenges of Diffusion Models: Insights and Innovations
Authors: Jazibiyya Essam , Dina Rasim , Ismaeel Wasim
Published: January 2025

Diffusion models have emerged as a powerful class of generative models, revolutionizing fields such as image synthesis, text-to-image generation, and molecular design. Despite their remarkable capabilities, ensuring that these models are aligned with human values, ethical principles, and societal goals remains a significant challenge. The alignment problem in diffusion models encompasses issues such as safety, fairness, robustness, and controllability, compounded by the stochastic and generative nature of these models. This paper provides a comprehensive exploration of the alignment of diffusion models, beginning with an overview of their foundational principles and applications. We examine the unique challenges posed by their probabilistic outputs, lack of interpretability, and dependence on large-scale, often biased datasets. Existing approaches to alignment, including fine-tuning, reinforcement learning from human feedback, prompt engineering, and post-processing, are analyzed for their strengths and limitations. Building on this foundation, we identify key research gaps and propose future directions, such as the development of scalable alignment techniques, robust evaluation metrics, and interdisciplinary collaboration frameworks. We also highlight the importance of addressing ethical and societal considerations, including bias mitigation, transparency, and equitable access, to ensure the responsible deployment of diffusion models. By addressing these challenges, we aim to foster a new era of generative AI systems that are not only innovative and powerful but also aligned with the values and aspirations of humanity. This work serves as a foundation for advancing the alignment of diffusion models, inspiring further research and collaboration in this critical domain.
Minimally Invasive Salvage Approaches for Management of Recurrence After Primary Renal Mass Ablation
Authors: Askarpour MohammadReza , Aminsharifi Alireza
Published: January 2025

Objectives: Thermal ablation has emerged as an effective, nephron-sparing treatment for small renal masses (SRMs), particularly in patients with comorbidities. However, tumor recurrence remains a challenge, necessitating evidence-based approaches for salvage management. This review examines the outcomes of minimally invasive modalities for managing recurrence following primary ablation of SRMs.
Methods: A literature review was conducted using the Medline database, following PRISMA guidelines. Studies published between 1981 and 2024 were screened based on predefined PICO criteria. Inclusion focused on patients with tumor recurrence after primary ablation therapy who underwent minimally invasive salvage treatments including repeat ablation, laparoscopic/robotic partial or radical nephrectomy, or active surveillance. Data extracted included patient demographics, initial treatments, recurrence timelines, salvage modalities, and outcomes.
Results: Of 364 patients across 29 studies, 249 (68.4%) underwent re-ablation, 82 (22.5%) were treated with laparoscopic/robotic partial or radical nephrectomy, and 33 (9%) were managed with active surveillance. Among 249 patients with re-ablation, 179 (71.9%) showed no evidence of disease, 67 (26.9%) experienced recurrence, and outcomes were indeterminate in 3 (1.2%). Salvage minimally invasive partial or radical nephrectomy outcomes were available for 64 cases, with 63 (98.4%) showing no recurrence. In 33 patients under active surveillance, 4 died, 4 underwent surgery, and 25 remained under monitoring, though follow-up data were limited.
Conclusion: Minimally invasive salvage modalities, such as re-ablation and laparoscopic/robotic partial or radical nephrectomy, effectively manage tumor recurrence, achieving >70% and >98% oncological success, respectively, despite technical challenges. Future studies directly comparing these modalities are essential for establishing standardized protocols for salvage management.
Hybrid Data Mining Technique for Credit Card Fraud Detection
Authors: Salahudin-Mukeem Dhakirah , Ekundayo Olufisayo
Published: January 2025

The rising incidence of credit card fraud underscores the need for innovative strategies to enhance credit card fraud detection and prevention. Numerous approaches have been employed for credit card fraud detection; however, the field continues to seek methods that can adapt to the constantly evolving nature of fraud patterns. In this study, we develop a hybrid model by integrating machine learning algorithms for effective credit card fraud detection. Using a simulated credit card transaction dataset, the model is developed in two stages, the first stage finds a base algorithm for the proposed hybrid model. The second stage focus on developing the hybrid model by combining the base model (Light Gradient Boosting Machine) with each of the selected algorithms. The hybrid models, demonstrated superior performance compare to standalone algorithms. Also, the hybrid of LGBM and XGBoost model outperforms others combinations, having 98.3% accuracy, 98.88% Precision, 98.05% Recall, 98.46% F1-Score, 99.80% AUROC. This proposed hybrid model can enhance security and foster trust in financial institutions and businesses, and in turn contribute to a more stable and efficient financial ecosystem.
Gravity Model Applied on Trade Flows Between Portugal and the OECD
Authors: Sandambi Nerhum
Published: January 2025

The study analyses foreign trade between Portugal and the OECD countries in the period 1980-2020. The objective, of course, is to analyse foreign trade and understand the main factors that influence foreign trade. The analysis is estimated using a gravity model, analysed using ordinary least squares, random effects, fixed effects and the Hausman Taylor estimator. According to the results, there is a negative impact of the real GDP of the country of origin, Portugal being in the sample, and a positive impact on the economies of the destination countries, thus being relevant for explaining trade. These results are related to the fact that most OECD countries have a significantly larger economic size than Portugal. Physical distance produced results that show a negative impact on the volume of trade transacted, so when trade is made with the countries furthest away from Portugal (with Australia, for example), the volume of trade drops to -5.60 ‘coeteris paribus’. On the other hand, the real effective exchange rate (reer) has a positive impact of 1.6. We also used some binary variables to analyse whether trade is made with a country that belongs to an economic integration zone itself, so trade made with a country in the European Union produces negative impacts, unlike the results of the binary variable MERCOSSUR, which characterises whether countries belong to this economic bloc, where there are positive impacts on trade volume when trade is made with Brazil or Argentina, for example.
Chalcogen-Bonded [Se–N]2 Cyclic Supramolecular Synthons Enhanced by Halogen Bonds: Studies in the Gas Phase and Crystalline Phase
Authors: Miao Shaobin , Sun Xiaotian , Zhang Yu , Wang Weizhou
Published: January 2025

Chalcogen-bonded [Se–N]2 is a strong cyclic supramolecular synthon in supramolecular chemistry. Selenadiazole is commonly used in the synthesis of [Se–N]₂. One nitrogen atom in a selenadiazole molecule participates in the formation of [Se–N]₂, while the other nitrogen atom can participate in the formation of other types of noncovalent bonds. Investigating the effect of neighboring noncovalent bonds on [Se–N]₂ is beneficial for its further synthesis and application. In this study, we combined theoretical calculations and crystallography to explore the effect of I···N halogen bonds on [Se–N]₂ in both the gas phase and the crystalline phase. Gas-phase calculations show that the formation of halogen bonds increases the strength of [Se–N]₂, and the strength of halogen bond is directly proportional to the strength of [Se–N]₂. In the crystalline phase, [Se–N]₂ is influenced by more noncovalent bonds in addition to halogen bonds, making the results more complex. However, if the effect of other noncovalent bonds is relatively small, the strength of halogen bond remains directly proportional to the strength of [Se–N]₂. It is believed that the conclusions drawn from halogen bonds are also applicable to other types of noncovalent bonds.
Influence of the Generation-Recombination Term on the Dielectric Relaxation in an Electrolytic Cell
Authors: Lelidis Ioannis , Barbero Giovanni
Published: January 2025

We investigate the influence of the generation-recombination term on dielectric relaxation in an electrolytic cell shaped like a slab, bounded by two parallel blocking electrodes. We show that, in the adiabatic limit, valid when the reaction time is much longer than the dielectric relaxation time, the electric current in the external circuit does not result from a simple relaxation mechanism. Instead, it is characterized by a short relaxation time associated with dielectric relaxation and a long relaxation time related to the dissociation process.
Enlightenment from Lv Shuxiang’s Thoughtss on the Cultural and Creative Design of Silver Ornaments of the She Ethnic Group in Eastern Fujian
Authors: Zhang Yong
Published: January 2025

This paper explores the core concepts of Lv Shuxiang's views on cultural inheritance and innovation. It examines the application of his ideas to the preservation and innovation of She silver jewelry culture. In this study, the unique role of She silver ornaments in cultural inheritance is thoroughly discussed. This paper explains how his ideas guide the creative design of She silver ornaments to harmoniously blend tradition and modernity, demonstrating their practical application. The results indicate that his ideas are significant for both the innovation of She silver jewelry and the broader inheritance and innovation of Chinese culture, forming an important part of China's cultural heritage and innovation efforts.
Modeling Charged Atoms for Atomistic Dynamics, using Equivariant GNNs
Authors: Awasthi Vinay , Ivanov Angel-Raychev
Published: January 2025

Graph Neural Networks have been quiet successful in modeling inter-particle interactions at quantum level for datasets carrying force-fields and atomic charge, detecting efficacy of a drug compounds, preventing further harmful chemical reactions such as drugs targeting cancerous cells, preventing tumor growth (protein ligand interactions). There are various other applications of this approach where one can model inter graph interactions, among nodes belonging to different graphs, using cutoff-radius based sphere as receptive field such as recommendation system taking into account of user’s interactions with influencers on other social networks, interactions among various sets of swarm drones, spread of viruses among multiple species of birds, based on their interactions across flight paths etc... Dataset such as SPICE [3], have information about cutoff-radius embed in them. Selecting right cutoff-radius is key parameter for getting reasonable outcome. Next is AGGR function as authors have notices that charge should not be approximated using SUM but MAX to get current bond-length measure at atomic level. For other domains, prior domain knowledge should guide these decisions. We present a e3nn, nequip, Allegro based GNN with slight modification for SPICE dataset carrying charge, to detect right bond length even with short training of 100 epochs. Ideas presented here can be applied to other node interactions belonging to various graphs. Here we show how we detected ammonium ion N-H bond length, where one N-H bond out of four carried charge. We have a Jupyter notebook for readers to try our approach in less than ten minutes.
Long COVID and Associated Factors Among Chinese Residents Aged 16 Years and Older in Canada: A Cross-Sectional Online Study
Authors: Shariati Matin , Gill Kieran Luke , Peddle Mark , Cao Ying , Xie Fangli , Han Xiao , Lei Nan , Prowse Rachel , Shan Desai , Fang Lisa , Huang Vita , Ding Arianna , Wang Peizhong Peter
Published: January 2025

As the COVID-19 pandemic evolved, long COVID emerged as a significant threat to public health, characterized by one or more persistent symptoms impacting organ systems beyond 12 weeks of infection [9-12]. Informative research has been derived from assessments of long COVID among the Chinese populace. However, none of these studies considered the COVID-19 experience of Chinese residents in Canada. Objectives: We aimed to fill this literature gap by delineating the long COVID experience, prevalence, and associated factors among a sample of Chinese residing in Canada during the pandemic. Methods: The present study employed a cross-sectional online survey questionnaire distributed to a sample of Canadian Chinese using a convenience sampling procedure from December 22, 2022, to February 15, 2023. Respondents were probed for sociodemographic background, health-, COVID-, and vaccine-related characteristics. Logistic LASSO regression was used for model building and multivariate logistic regression was used to identify factors associated with developing long COVID. Results: Among 491 eligible participants, 63 (12.83%) reported experiencing long COVID with a mean duration of 5.31 (95% CI: 4.06–6.57) months, and major symptoms including difficulty concentrating (21.67%), pain/discomfort (15.00%), as well as anxiety/depression (8.33%). Our final model identified significant associations between long COVID and two or more COVID-19 infections (OR = 23.725, 95% CI: 5.098–110.398, p < 0.0001), very severe/severe symptoms (OR = 3.177, 95% CI: 1.160–8.702, p = 0.0246), over-the-counter medicine (OR = 2.473, 95% CI: 1.035–5.909, p = 0.0416), and traditional Chinese medicine (OR = 8.259, 95% CI: 3.016–22.620, p < 0.0001). Further, we identified a significant protective effect of very good/good health status (OR = 0.247, 95% CI: 0.112–0.544, p = 0.0005). Conclusions: Long COVID adversely effected a notable proportion of Canadian Chinese for a prolonged period during the pandemic. Our findings underscore the importance of preexisting health status and reinfection prevention when managing long COVID. Moreover, our work indicates the need for culturally accessible guidance and services pertaining to effective COVID-19 treatment modalities through infection, recovery, and beyond.