bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measuring effectiveness of Integrating Basic Sciences with Clinical Practice through analysis of learning outcome achievement across curriculum phases; a comparative study
Authors: Almaramhy Hamdi 
Published: February 2025

Abstract

Background: Effective integration of basic and clinical sciences is pivotal in medical education, influencing students’ ability to apply knowledge in clinical settings. This study evaluates the integration efficiency of basic sciences in differing phases of a spirally integrated curriculum through the lens of program learning outcomes (PLOs).
Methods: A quantitative comparative analysis was conducted across phases 1 (years 1 and 2) and 3 (year 5) of a medical curriculum. Data were collected from summative assessments, with Multiple-Choice Questions (MCQs) assessing knowledge and Objective Structured Clinical Examinations (OSCEs) assessing psychomotor skills. Achievements of course learning outcomes (CLOs) were quantified as percentages and correlated to PLOs. Statistical evaluation was performed using paired t-tests, setting significance at p < 0.05.
Results: Phase 1 demonstrated successful attainment of all 12 PLOs, with achievement percentages ranging from 70-80% or higher. In contrast, phase 3 revealed lower achievement levels in specific PLOs, notably PLO 1.4. Significant disparities in mean achievements for factual knowledge PLOs (except PLO 1.2) and cognitive PLOs 2.2 and 2.3 were observed between the two phases. No significant differences were noted in psychomotor PLOs.
Conclusion: The study highlights challenges in effectively integrating basic sciences within the clinical components of the curriculum, despite its structural advantages. These findings advocate for refined integration strategies to bolster clinical reasoning and educational efficacy, contributing substantively to discussions on enhancing medical education practices and suggesting directions for future research.
Experimental and Numerical Investigation of Flexural Behavior of Sustainable Self-Compacting Geopolymer RC Beams
Authors: Fathi Mohamed E. , El-Zoughiby Mohamed E. , Mortagi Mohamed , Tahwia Ahmed M. 
Published: February 2025

Abstract

This paper investigates experimentally and numerically the flexural characteristics of sustainable self-compacting reinforced geopolymer concrete beams having granite waste powder and slag with heat curing treatment at first cracking and at strength levels. Five geopolymer and one reference Portland cement reinforced concrete simple beams (100 mm x150 mmx 1500 mm) were tested under 2-point loads. The two main variables are longitudinal reinforcement ratio and shear span-to-depth ratio. Test results of geopolymer and cement reinforced concrete simple beams are presented and compared with numerical results; load-displacement response, flexural strength, strains, failure mode, cracking pattern, etc. Considering the material properties of geopolymer concrete, the concrete modulus and stress- strain relationships have been adapted to do a finite element nonlinear analysis. The developed finite element models and the conventional beam theory can reasonably predict the flexural strength and deflection of geopolymer reinforced concrete beams.
Ultra-fast ammonia decomposition using an electrified tungsten wire lightbulb reactor
Authors: Yan Ning , Indriadi Keshia , Wong Sie Shing , Wang Sikai , Xu Di 
Published: February 2025

Abstract

Ammonia decomposition is a key reaction in the green hydrogen economy as ammonia is an important carbon-free hydrogen carrier. Despite extensive efforts to develop active catalysts to address the reaction's slow kinetics, we introduce a tungsten wire lightbulb reactor that operates at unconventionally high temperatures with enhanced efficiency. Near the wire, temperature reaches up to 1,800 K, enabling ultra-fast ammonia decomposition with rate constants much higher than those of leading catalysts under typical reaction conditions. Concurrently, the sharp temperature decrease along the radial direction allows for low power inputs, thus enhancing energy efficiency. It also realized up to 99.995% conversion at enhanced power input without the use of membrane separation. We further discuss a scale-up reactor design that is two to three orders of magnitude smaller than current state-of-the-art reactors and highlight its potential applications within the emerging hydrogen economy.
Demographic Predictors of Inpatients’ Postdischarge Stay in Referral Hospitals in Kisumu County, Kenya
Authors: Awuor Eunice G. , Ochieng Mary A. , Olang’o Charles O. , Awuor Silas O. 
Published: February 2025

Abstract

Introduction
Globally, inpatients continue to unnecessarily prolong their stay in referral hospital wards upon their medical discharge. This causes congestion in wards, hospital reinfection, relapse, death of PDS inpatients, and financial burden to hospital management. The literature links postdischarge stay (PDS) to economic reasons. This study aimed to investigate the demographic predictors of inpatients’ postdischarge stay in Jaramogi Oginga Odinga Teaching and Referral Hospitals (JOOTRH) and Kisumu County Referral Hospital (KCRH) in Kisumu County, Kenya.
Methodology
This study adopted a correlational cross-sectional research design. A stratified sampling technique was used to select inpatients in the 14 wards, after which systematic random sampling was used to reach the individual PDS inpatients for interviews. To establish the predictors of PDS, binary logistic regression analysis was used, where p values < 0.05 were considered statistically significant, and odds ratios (ORs) and 95% confidence intervals (CIs) were reported to show the magnitude and influence of PDS, resulting in a total sample size of 133 participants.
Results
The majority 72 (54.13%) of the respondents in this study were female. In the age cohort, 43 (32.33%) were aged 20–29 years, 24 (18.05%) were aged 30–39 years, 20 (15.04%) were aged 0–9 years, 17 (12.78%) were aged 40–49 years, 11 (8.27%) were aged over 60 years, and 7 (5.26%) were aged 50–59 years. In terms of marital status, 40 (30.08%) of the respondents were married, 22 (16.54%) were single, 20 (15.04%) were divorced/separated, 16 (12.03%) were widowed, 9 (45.00%) were partial orphans, 8 (40.00%) were both parents, and 3 (15.00%) were total orphans. Most of the respondents 74 (55.64%) had chronic diseases, while 59 (44.36%) had acute illnesses, among which the majority 88 (66.17%) had reached the primary level; hence, 86 (64.66%) unemployed respondents
Conclusion
Individual demographic factors associated with the vulnerability of PDS inpatients to becoming PDS victims in referral hospitals. Elderly individuals, males, unmarried individuals, and chronically ill individuals were more at risk of experiencing episodes of PDS. Older people with complex health needs are particularly vulnerable to PDS. Additionally, males, especially middle-aged individuals, are associated with deviance, rendering them social misfits who face neglect due to their social relationships in hospital wards and thus PDS. The chronically ill were perceived as burdens by their family members, whereas the unmarried experienced PDS due to insufficient social support. Whereas the parental status of the children, religiosity, education, and employment status of the PDS inpatients were insignificant to the study, they were not dismissed because they determined the general health outcomes of the PDS.
Context-Aware Search: LLM-Driven Model for Searching Emerging Topics
Authors: Ray Paramita , Basu Aditi 
Published: February 2025

Abstract

As new topics emerge, users often struggle to find relevant and reliable information due to evolving terminology, ambiguous queries, and a lack of indexed resources. Traditional search engines may fail to capture the context and intent behind such searches, leading to suboptimal results. This study explores how Large Language Models (LLMs) can enhance query expansion and understanding of emerging topics, ensuring more effective and meaningful information retrieval. By leveraging context-aware query reformulation, semantic enrichment, and interactive refinement, LLMs can dynamically adapt search queries to improve recall, relevance, and ranking. This is particularly valuable in rapidly growing fields such as public health, finance, disaster response, and technology, where new terms and concepts emerge frequently. Our approach integrates query expansion, and neural reranking techniques to refine search intent and deliver more accurate results. The goal of this research is to develop a more adaptive, intuitive, and intelligent search framework that enhances the user experience by making web searches more precise, context-aware (Expand queries based on context rather than similarity), and informative, benefiting both general users and domain experts.
Randomized Spatial PCA (RASP): a computationally efficient method for dimensionality reduction of high-resolution spatial transcriptomics data
Authors: Gingerich Ian K. , Goods Brittany A. , Frost H. Robert 
Published: February 2025

Abstract

Spatial transcriptomics (ST) provides critical insights into the spatial organization of gene expression, enabling researchers to unravel the intricate relationship between cellular environments and biological function. Identifying spatial domains within tissues is key to understanding tissue architecture and mechanisms underlying development and disease progression. Here, we present Randomized Spatial PCA (RASP), a novel spatially-aware dimensionality reduction method for ST data. RASP is designed to be orders-of-magnitude faster than existing techniques, scale to datasets with 100,000+ locations, support flexible integration of non-transcriptomic covariates, and reconstruct de-noised, spatially-smoothed gene expression values. It employs a randomized two-stage PCA framework with sparse matrix operations and configurable spatial smoothing. RASP was compared to BASS, GraphST, SEDR, SpatialPCA, and STAGATE using diverse ST datasets (10x Visium, Stereo-Seq, MERFISH, 10x Xenium) on human and mouse tissues. RASP demonstrates comparable or superior tissue domain detection with substantial improvements in computational speed, enhancing exploration of high-resolution subcellular datasets.
Physically consistent mesoscale model evaluation in complex terrain
Authors: Simonet Gaspard , Lehner Manuela , Rotach Mathias 
Published: February 2025

Abstract

This study introduces a novel evaluation technique for mesoscale atmospheric models in complex terrain, addressing challenges related to grid point (GP) selection, model resolution, and differences in the terrain and measurement heights between model and observation sites. The technique includes a pre-evaluation step designed to enhance model evaluation accuracy by correcting for systematic biases arising from discrepancies in sensor height between surface-layer diagnosed variables and actual measurement heights. Additionally, a lapse rate correction is proposed that takes into account the temporal evolution of the valley atmosphere. We use a GP for the evaluation with point measurements that represents the topographic characteristics at the measurement site better than the nearest GP.
The analysis of a case study using a WRF simulation with different grid spacing is conducted for a synoptically undisturbed valley wind day over the Inn Valley, to study the effect of grid resolution during an entire diurnal cycle.
The proposed method shows significant potential in reducing uncertainties in model performance assessments by selecting GPs that better represent in-situ conditions, including accurate land cover and orography characteristics. This approach is expected to facilitate more reliable inter-model comparisons and enhance the overall robustness of atmospheric model evaluations in complex terrains.
Breaking the Glass Ceiling? A Gender Analysis of Employment Trends in Turkish Healthcare Sector
Authors: Urhan Betul , Etiler Nilay 
Published: February 2025

Abstract

Turkiye (Turkey) is experiencing a feminization of its healthcare sector, which is creating employment opportunities for women, but also revealing gendered patterns of employment. This study examines the working conditions of women in Turkiye’s healthcare sector through a gender lens, focusing on how employment growth affects these dynamics. To address these issues, multiple data analyses are used to examine the gender characteristics of women's employment in the health sector. The 2021 Household Labor Force Survey (HLFS) microdata set is used as the main dataset. This analysis focuses on employment in the health sector, coded as 86 in the Classification of Economic Activities (NACE 86), which includes human health services. In addition, we conducted secondary analyses using the aggregate data from Ministry of Health’s labor force statistics and higher education data. The health sector is an important source of employment for women, with 2.4% of men and 7.0% of women employed in the sector. Women constitute 57.8% of the health workforce, which is predominantly professional, and ‘technicians/associate professional’ roles. Despite its predominantly female composition, the health sector still faces a glass ceiling. They are predominantly clustered at the lower rungs of the occupational hierarchy, occupying lower paid and lower status roles. With regard to students in the health sciences, it appears that the feminization of the health sector will continue in the near future. As an important source of employment for women, the growing demand for health services will create new employment opportunities for women. Therefore, the jobs and occupations in which women's employment in the health sector is concentrated, the gender pay gap, and women's current working conditions in the public and private sectors should be monitored. This is essential for policies and interventions against the devaluation of health care work.
Predictive Validity and Differential Prediction of the MCAT Section Scores for Medical Students’ Performance in Preclinical Courses
Authors: Abulela Mohammed A. A. , Dale Esther Dasari , Schowengerdt Bethany , Violato Claudio 
Published: February 2025

Abstract

Purpose: Limited research has been conducted on the differential predictive validity of the Medical College Admission Test (MCAT) section scores (e.g., Biological and Biochemical Foundations of Living Systems [BBLS], Chemical and Physical Foundations of Biological Systems [CPBS]) for basic science courses (anatomy and histology). Accordingly, the purpose was to assess the predictive validity and differential prediction of these section scores to predict anatomy and histology performance across sex (men vs. women) and race (white vs. nonwhite).
Methods: The authors analyzed data from 520 undergraduate medical students (sex: 292 women [56.15%], 228 men [43.85%]) in anatomy and histology courses. The authors utilized multiple linear regression and t-tests to test for statistically significant differences in slopes associated with each section score across sex and race groups.
Results: BBLS and CPBS section scores explained more variance in histology compared to anatomy, particularly for the nonwhite and men groups (25% and 29% vs. 24%). For the differential prediction, t-tests were not statistically significant for most analyses, which provided evidence for the comparable predictive validity across the groups or lack of differential prediction, a desired psychometric property for fair assessments. The t-test associated with the BBLS section score, however, was statistically significant between the women and men groups only in anatomy.
Conclusions: Current results contribute to the broader evidence supporting the validity of MCAT section scores. The general absence of differential prediction (i.e., comparable predictions across groups) supports the fairness of MCAT-based inferences, bolstering confidence in its use for medical school admissions and promoting equity.
Groundwater Potential Zone Mapping In Ajora-Woybo Watershed, OMO Basin, Southern, Ethiopia, Using GIS, RS &amp; AHP Techniques
Authors: Dawana Yohannes 
Published: February 2025

Abstract

Mapping groundwater potential zones is essential for effective well drilling planning. This study focuses on Ajora-Woybo watershed in Southern Ethiopia, which spans 1,787.8 km². The area is experiencing rapid population and livestock growth, leading to increased water demand, while quantity and quality of surface water are declining due to agricultural activities near rivers. The objective of this research was to evaluate groundwater potential zones using geographic information systems, remote sensing, and Analytical Hierarchy Process. Eight thematic layers were utilized for the assessment: geomorphology, lithology, slope, lineament density, soil texture, drainage density, rainfall, and land use/cover. Data for these factors were compiled from remote sensing imagery and various secondary sources, then processed in a geographic information systems environment. The relative weights of the datasets were determined using Analytical Hierarchy Process. The assessment categorized the groundwater potential into four classes: high, moderate, low, and poor. The high potential area, covering 568.4 km², is mainly in the central and northern regions, characterized by flat land and plateau that correspond to volcanic sediment and Nazret group and Dino formation with low slope. Conversely, the poor potential zone spans 152.7 km² in the northeast and southern in mountain peaks. The other classes include low potential (438.1 km²) and moderate potential (628.7 km²). Geomorphology and lithology are sensitive to groundwater occurrence distribution, while land use/cover is less sensitive. The study found 79% agreement between groundwater potential map and observed borehole yield, demonstrating the effectiveness of combining geographic information systems and remote sensing for identifying groundwater zones.
Village councils, social capital and sustainability: a study of urban water management of Shillong in Meghalaya, India
Authors: Kharmylliem Bankerlang , Kipgen Ngamjahao 
Published: February 2025

ABSTRACT
This study examines water governance in Shillong, India, focusing on the role of traditional institutions called dorbar shnongs (village councils) in managing water resources. Through qualitative research methods, including interviews and narrative analysis, the study investigates how these councils interact with clan systems, groundwater management, and broader water distribution challenges in an urban context. The findings reveal significant variations in water governance across different localities, with some councils successfully implementing communal resource management while others struggle with commercialization and inequitable distribution. The research highlights how clan system significantly influences water access and management, particularly through their control of springs and borewells. While some clans adopt profit-driven approaches, others maintain traditional communal sharing practices. The study demonstrates that effective water governance through village councils depends on strong leadership, transparent rules, inclusive decision-making, and robust enforcement mechanisms. However, these institutions face mounting challenges from urbanization, cultural erosion, and other significant factors. The research concludes that while village councils show promise as effective water management institutions in urban settings, their success requires balancing traditional practices with modern governance approaches and addressing locality-specific challenges through customized solutions.
Addressing foundational issues for effective flood risk governance in Pakistan
Authors: Hote Hassan Haren , Koike Toshio 
Published: February 2025

ABSTRACT

Pakistan established a multi-tiered disaster management framework in 2007, yet in 2010 and 2022, it experienced devastating floods. The widespread impact and the similarity of the damage in the two disasters point to systemic issues that contradict disaster risk reduction (DRR) policy. The study utilises an embedded exploratory case study design and deductive thematic analysis to elaborate and analyse two core underlying risk drivers that function as foundational barriers to effective flood risk governance in Pakistan: weak implementation of flood risk management policy at the district level; and the socioeconomic challenge of poverty-induced vulnerability to flood risk. The findings of the paper underscore the need for a systems approach to integrated disaster management to holistically address the interdisciplinary and cross-sectoral character of flood disasters. A primary recommendation is increased legislative and resource support of District Disaster Management Authorities, which function in a local government system that is subject to frequent political transformations. To address the disaster risk-poverty nexus, the combined implementation of DRR and poverty alleviation programmes are recommended. The study has practical utility as it focuses on using existing local structures to improve the disaster risk management (DRM) capacity of both the state and citizens.
Collaborative removal of microplastics, bacteria, antibiotic resistance genes, and heavy metals in a full-scale wastewater treatment plant
Authors: Yu Ran , Li Peng , Shen Rong 
Published: February 2025

ABSTRACT

Plastics are used in large quantities in food packaging and industrial products in China, which results in ecological risks of microplastics (MPs) to the environment. In this study, the MPs’ removal efficiency of a full-scale wastewater treatment plant (WWTP) and the internal interaction of microorganisms, antibiotic resistance genes (ARGs), and heavy metals with MPs were investigated. The dominant MPs in urban sewage were polyurethane (PU), acrylate copolymer (ACR), fluororubber, and polyethylene. MPs in wastewater were removed by WWTP with a total efficiency of 76%. The removal efficiencies of ACR, ethylene-vinyl acetate copolymer, polybutadiene, poly(tetrafluoroethylene), polystyrene, and polypropylene reached 100%. The highest concentration of MPs PU in the influent got a removal efficiency of 93.41%. The interactions between MPs, heavy metals, microorganisms, and ARGs involved adsorption, hydrogen bonds, coprecipitation, and polar interaction. Heavy metals and MPs formed larger aggregated particles, which were removed in the primary process. Heavy metals accumulated in sludge pose ecological risks to soil during landfill or compost to fertilizer. The release of MPs from WWTPs leads to accumulation in organisms and soil. It may affect the entire food chain and promote the transmission of ARGs in the environment, posing potential threats to the entire ecosystem.