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Vector fields as a framework for modelling the mobility of commodities
Commodities flow through trade networks across the world, with trajectories that can be effectively modelled using approaches similar to those used in human mobility studies. Yet, documenting these movements comprehensively is challenging due to data sparsity, cost, and privacy constraints. Origin-destination (OD) matrices provide a widely used framework for representing mobility, although they inherently omit locations not directly observed as either origins or destinations. This incompleteness creates gaps across different geographical scales, constraining our ability to characterise movement patterns in underrepresented areas. In this study, we introduce a vector-field-based method to address these persistent data challenges. By transforming OD data into continuous vector fields, we capture spatial flow patterns more comprehensively than traditional network approaches, while also enabling robust analysis of mobility directions. Our approach incorporates interpolation techniques that handle incomplete and sparse datasets effectively; when approximately 500 out of 853 areas are removed, 189 areas (36%) maintain degree deviations of less than 15 degrees, showing that the general direction of flow is preserved for over one-third of the impacted areas and enabling continuous spatial analysis. We apply this framework to cattle trade data from Minas Gerais, Brazil. Cattle movements are particularly significant as they directly impact disease transmission, including foot-and-mouth disease. Accurately modelling these flows supports effective disease surveillance and preparedness, with benefits for both animal health and economic stability. Our analysis reveals distinct spatial clusters of trade behaviour, temporal patterns in flow directions, and seasonally varying critical points likely associated with known periodicities in cattle trade driven by breeding cycles, slaughter schedules, and fluctuations in global demand. While previous vector-field studies focused on human mobility, our framework addresses the distinct challenges of commodity flows, where aggregated OD data, sparse observations, and lack of data are the norm. It enables inference in unobserved areas which is a critical capability for modelling scenarios such as disease spread. This approach enhances our capacity to infer flow patterns from incomplete datasets and advances understanding of large-scale commodity trade dynamics.
A scoping review of EFL learners’ interlanguage pragmatic development
Interlanguage pragmatics (ILP) development refers to how L2 learners manage actions, identities, and social relations through language in interaction. The rapid transition to multimodal, digitally mediated EFL instruction after 2020 has reshaped the conditions for ILP development. However, existing reviews largely predate this pivotal shift and offer only fragmented coverage on how these new ecologies have changed EFL learners’ prospects for ILP development and its assessment. This scoping review provides the first integrative synthesis of research on EFL learners published since 2020. Its primary goal is to consolidate dispersed evidence to identify key developmental patterns and contextual moderators. Four databases (Web of Science, Scopus, ScienceDirect, and ERIC) were searched for publications from 2021 to 2025 using predefined criteria; 56 studies met the eligibility criteria. Reporting follows PRISMA-ScR, and data were independently double-screened, coded, and analyzed thematically in ATLAS.ti 23. The analysis identified seven thematic categories ranging from core learner-internal pragmatic competencies to external pedagogical and computer-mediated contexts. Despite uneven coverage across themes and regions, findings converge on two patterns: pragmalinguistic gains often outpace sociopragmatic appropriateness and follow nonlinear trajectories, and instruction tends to outperform mere exposure when explicit form-function-context mapping, multimodal modelling, and data-driven feedback are provided. For researchers, the review highlights the need to shift toward longitudinal, interaction-sensitive designs that capture within-learner moderators and situational dynamics across broader learner groups. The distinctive contribution is a set of evidence-informed design principles that help educators and materials developers align ILP-oriented instruction and assessment with EFL learners’ varying developmental needs.
Experiences, outcomes and unmet needs of caregivers of children with Cerebral Palsy in Spain: Protocol for a mixed-methods study
Cerebral Palsy is one of the most prevalent motor disabilities in childhood, significantly impacting both children and their caregivers. This mixed-methods study explores the experiences, psychological well-being, and unmet needs of caregivers of children with Cerebral Palsy. Using an explanatory sequential design (QUAN → QUAL), first it will be assessed burden, stress levels, and quality of life of caregivers through standardized questionnaires (PedsQL-FIM, ZBI, PSS-14). In the second phase, semi-structured interviews will be conducted to provide a deeper understanding of these variables. Other studies indicate that caregivers experience heightened stress and decreased quality of life, influenced by their child’s functional limitations and the lack of adequate social and healthcare support. Moreover, many caregivers struggle with navigating medical systems, balancing personal and professional responsibilities, and managing emotional distress. This study will highlight the urgent need for family-centered interventions, psychosocial support, and healthcare policies that address not only the medical needs of children with Cerebral Palsy but also the well-being of their caregivers. By integrating quantitative and qualitative data, this research will provide comprehensive insights into the caregiving burden and will offer recommendations for improving caregiver support strategies. The Clinical Trial is registered at ClinicalTrials.org with the registration number NCT06912373.
Progressive damage mechanism and multiscale characterization of hard sandstone-coal composite structures under loading
Under geological conditions characterized by deep high-stress zones, intense mining disturbances, and hard roof strata, primary fractures on and within coal bodies are highly susceptible to expansion and propagation. This study investigates the failure characteristics of coal bodies under the combined effects of hard roof strata and sandstone fracture water. Taking the 11129 working face at Zhangji Coal Mine as the study site, this research examines the macro- and micro-scale load-bearing capacity and damage characteristics of coal bodies. The results indicate that: (1) During coal seam mining, the thick layer of hard sandstone roof directly overlying the seam exhibits a large span with minimal deformation while bearing the load of the overlying weak rock strata. By employing pre-splitting blasting technology, the initial roof fracture step length was reduced to 45 m. Stress concentration occurred 5–20 m ahead of the coal face, with peak stress reaching 33.8 kPa. Peak strain appeared 11m behind the coal face, registering a value of 594.3. (2) During the moment of stress-bearing or fracture, coal-rock strata undergo energy accumulation and dissipation. Before the advance distance reaches the minimum roof fracture step length, relatively hard rock layers bear their own weight and the load from overlying softer strata. As the span length of the hard rock increases, the accumulated energy rises. When the internal energy accumulation reaches the rock’s load-bearing limit, the roof fractures, transferring the force to the goaf and releasing the energy. (3) Under dynamic loading, coal sample cracks exhibit a progressive evolution from “development to penetration to failure.” At low impact intensity (0.3 MPa), the incident energy for samples with varying coal-to-rock ratios ranges from 172.64 to 240.89 J, with dissipated energy accounting for 0.249 to 0.44 of the total. When the impact pressure increased to 0.7 MPa and the rock content in the sample rose, the incident energy increased from 265.95 J to 326.87 J, an increase of approximately 60.92 J. The proportion of dissipated energy remained within the range of 0.249 to 0.418. The magnitude of the impact pressure had no significant effect on the degree of energy dissipation. (4) A pre-splitting blast pressure relief scheme employing fan-shaped hole groupings was proposed. Numerical results from the working face indicate that the pre-splitting blast achieved the anticipated roof control effect.
Pruning-fruit retention and plant models strategies to improve growth, quality, and yield of netted melon in Arid regions
Netted melon ( Cucumis melo var. reticulatus ) exhibits strong environmental adaptability and high economic value, making it a widely favored horticultural crop in local markets. In the arid regions of Northwest China, optimizing traditional monoculture planting patterns can fully exploit the production potential of netted melon. Economic benefits and environmental adaptability can be enhanced by adjusting plant spacing and pruning-fruit retention strategies, thus promoting sustainable agricultural development in arid Gobi regions. A field experiment was conducted with two factors: plant spacing and pruning-fruit retention strategies. Three plant spacing were set at 55, 65 and 75 cm, and three pruning-fruit retention methods included two vines with two fruits, three vines with two fruits and three vines with three fruits. The effects of different planting configurations on the growth yield and fruit quality of Gobi netted melon was evaluated. A Back Propagation Neural Network-Non-dominated Sorting Genetic Algorithm II (BP-NSGA-II) model was employed to simulate and optimize planting strategies. Increasing the number of retained vines and fruits moderately delayed plant development and postponed harvesting time. Enlarged plant spacing increased vine diameter and leaf number but inhibited vine elongation and leaf area expansion. Increasing the number of retained vines suppressed vine thickening but promoted leaf number expansion, and increased fruit retention number inhibited vine diameter growth. The effect of plant spacing on yield showed a decreasing trend as plant spacing increased, whereas the three vines with two fruits treatment consistently produced higher yields than the other pruning-fruit retention methods. Increasing plant spacing improved the comprehensive fruit quality, and the three-vine two-fruit method resulted in superior overall fruit quality. By employing BP-NSGA-II multi-objective optimization, the optimal planting configuration was determined to be a plant spacing of 70 cm with a pruning-fruit retention strategy of two vines with two fruits. Under these conditions, according to the model, the optimized growth duration would be 107 days, the maximum yield would reach 48.68 t hm -2 and the optimized fruit quality compliance index (Ci) would be 0.80. This strategy effectively achieves early maturity, high yield and superior fruit quality, contributing to the sustainable development of agriculture in arid Gobi regions.
Early clinical and laboratory markers associated with post-COVID respiratory syndrome: A retrospective analysis
Background Post-COVID-19 respiratory syndrome remains a significant concern, yet early clinical and laboratory markers at the time of admission are not well established. Identifying laboratory markers associated with this condition could help guide clinical management and long-term monitoring. This study aimed to determine which laboratory findings at admission significantly differ between COVID-19 survivors with and without post-COVID respiratory syndrome (PCRS) and assess their potential as markers. Methods A retrospective comparative study was conducted on COVID-19 survivors who has history of hospitalization at Persahabatan National Referral General Hospital, Jakarta, in 2020–2021, divided into case (PCRS, n:43) and control (nonPCRS, n:42) groups. Demographic data, vital signs, and laboratory findings were analyzed, including complete blood count, kidney and liver function, electrolytes, blood gas analysis, D-dimer, and C-reactive protein (CRP). Results Compared with controls, cases demonstrated significantly higher neutrophil percentages, neutrophil-to-lymphocyte ratio (NLR), blood urea nitrogen (BUN), potassium levels, and respiratory rates, along with lower lymphocyte and eosinophil percentages at admission. After Benjamini–Hochberg correction for multiple testing, respiratory rate, potassium, BUN, and neutrophil percentage remained statistically significant. In adjusted multivariable logistic regression models controlling for age, sex, body mass index, and markers of disease severity (SpO₂ and/or respiratory rate), potassium and respiratory rate showed consistent independent associations with case status across several models, while NLR retained a modest association only in models incorporating SpO₂. No significant differences were observed for D-dimer or CRP. Conclusion Neutrophilia, lymphopenia, increased NLR, elevated BUN, potassium levels, and higher respiratory rates at admission were associated with post-COVID respiratory syndrome. Among these, potassium levels and respiratory rate showed more consistent associations after adjustment for demographic factors and disease severity markers. These findings describe admission characteristics linked to post-COVID-19 Respiratory syndrome. Larger prospective studies with serial measurements are needed to confirm their clinical relevance and prognostic value.
Evaluation of alkali residue-stabilized soil in road construction with optimization of mechanical properties and environmental risk assessment
The effective utilization of alkali residue (AR) is a central issue and an urgent challenge for the green transformation of the soda ash industry. While research has primarily focused on the mechanical performance of AR-based materials, their long-term environmental risks, particularly under dynamic conditions, have been relatively overlooked. This study evaluates AR-stabilized soil for road construction by simultaneously optimizing its mechanical properties and conducting a comprehensive environmental risk assessment for shallow groundwater contamination. Through laboratory tests, we identified the AR substitution rate that maximizes the California Bearing Ratio (CBR) and water stability. To address the limitations of traditional static leaching tests, we integrated material degradation and contaminant transport models to dynamically simulate pollutant release and migration under realistic, non-steady conditions. Our findings reveal that an AR substitution rate between 10% and 50% yields optimal mechanical performance. However, environmental risk analysis indicates a significant increase in risk beyond 35%, with manganese (Mn) and nickel (Ni) exposure concentrations potentially exceeding Class III groundwater quality standards. Sensitivity analysis confirms the AR substitution rate as the most critical factor influencing environmental risk. Therefore, we recommend strictly controlling the AR substitution rate to ≤35% in road construction, providing a science-based, dual-criteria (mechanical and environmental) guideline for the safe and sustainable utilization of industrial waste in geotechnical engineering.
Evaluating the quality of social media content on metabolic dysfunction associated steatotic liver disease: An experience from a lower middle-income country
Introduction Metabolic dysfunction associated with steatotic liver disease (MASLD)/non-alcoholic fatty liver disease (NAFLD) represents a significant public health concern. Social media (SoMe) increasingly influences health perceptions in lower-middle-income countries, with one-third of Sri Lanka’s population using SoMe for health information. Assessing MASLD content quality on SoMe is therefore important. Aims & methods This cross-sectional study assessed accuracy, completeness, and quality of MASLD content across Facebook, YouTube, TikTok, Instagram, and X in Sinhala, English, and Tamil from Sri Lanka (January 2005-December 2024). Board-certified gastroenterologists independently reviewed posts using standardised scales for accuracy (0–3), completeness (0–5), and global quality score (GQS) (0–5). Posts were categorised by source profile and content type, with user interactions analysed. Results Analysis included 289 posts: 158 (54.7%) YouTube, 101 (34.9%) Facebook, 14 (4.8%) TikTok, 11 (3.8%) X, 5 (1.7%) Instagram. Languages: 214 (74.0%) Sinhala, 54 (18.7%) Tamil, 21 (7.3%) English. Content sources: undisclosed identity (36.0%), non-healthcare persons (26.0%), healthcare professionals (22.1%), alternative healthcare professionals (14.2%), healthcare institutions (1.7%). Health promotion (61.9%) was the predominant content type. Mean accuracy was 1.78/3 (59.3%), with healthcare professionals scoring highest (2.35/3, 78.5%) versus others (51.0–55.1%; p < 0.001). Completeness averaged 2.1/5 (42%), with English content scoring higher than Sinhala and Tamil. GQS averaged 2.4/5 (48.4%). 82% of posts were classified as “Rotten” (<60% score for each metric). Facebook and YouTube showed significantly higher completeness and GQS (p < 0.05). User engagement metrics showed no correlation with content quality. Conclusion Most SoMe content originated from non-healthcare sources. Healthcare professionals delivered the most accurate content. Facebook and YouTube showed relatively higher content quality scores, though comparisons are limited by the small number of posts from other platforms. Overall quality remained suboptimal across platforms, with 82% failing adequate standards. User engagement didn’t correlate with quality. These findings highlight the need for improved quality control and health literacy initiatives for MASLD information on SoMe platforms.
Antioxidant and antibacterial potential of bioactive extraction from Cadaba glandulosa leaves
This study investigated the bioactive components and explored the antioxidant and antibacterial properties of the methanolic leaf extracts of Cadaba glandulosa (MLCG). The observed activity is related to the diverse chemical composition of the extract as determined by gas chromatography-mass spectrometry (GC-MS) analysis, which tentatively identified 18 distinct compounds. Notable compounds include methyl dodecanoate, methyl tetradecanoate, 9,12-octadecadienoyl chloride, hexadecanoic acid methyl ester, palmitoleic acid, anethole, brefeldin A and oleic acid. The antioxidant tests showed a significant scavenging activity of 88.2% at a concentration of 381.5 µg/mL, which underlines the effectiveness of the extract in neutralizing free radicals. The total phenolic content in MLCG was found to be 79.5%, corresponding to 250.8 mg of gallic acid equivalents (GAE)/ mL.The antibacterial activity of MLCG showed variability between bacterial strains, with the strongest inhibition observed against Staphylococcus aureus and Streptococcus pyogenes , both Gram-positive bacteria. The extract showed moderate activity against Gram-negative bacteria such as Escherichia coli and Pseudomonas aeruginosa , while the least activity was observed against Klebsiella pneumoniae . In this study, the impressive antioxidant and antibacterial properties of MLCG underline the therapeutic potential of Cadaba glandulosa as a natural source of antioxidant and antibacterial agents.
Protocol for a cluster-randomized control trial of a remote workplace resilience intervention for early care and education providers: The OnWARD trial
Work-related stressors take a toll on individuals’ health and well-being, a toll which is often heavier for under-resourced, low-paid segments of the essential workforce who serve our communities. Resilience programs have arisen as a promising workplace strategy to improve mental health and well-being. However, emerging programs are constrained by time and resource-intensive implementation strategies that are challenging to scale for marginalized segments of the workforce, including early childcare education (ECE) staff. The goal of this 15-month cluster randomized control trial is to compare change in resilience assets and resources for ECE staff in centers (n = 80 consisting of 640 ECE workers) randomly assigned to either a remotely delivered resilience (intervention) or physical activity (attention control) program. Measures will be collected at four timepoints: baseline (0 months), post-intervention (3 months), and long-term maintenance (9 and 15 months). Secondary outcomes will include changes in well-being, physical activity, organizational support, absenteeism, and turnover. Additionally, we will explore potential moderators of the treatment effects. The RE-AIM Framework will be used to determine the potential for individual (staff) and organizational (center) level reach, adoption, implementation, and maintenance of the two programs. Results will fill key gaps of prior resilience work by focusing on an underserved population in critical need of well-being resources with implications for the feasibility and impact of remote programming in other segments of the workforce. Trial Registration: This trial is registered with the ClinicalTrials.gov registry (NCT06919952) and approved by the Institutional Review Board (IRB) at the University of North Carolina at Chapel Hill (IRB# 25−0016).
Dense retrieval and reranking for referenced provisions in electric power audit systems
Electric power audits require practitioners to describe an audit issue and justify the final opinion by citing an appropriate referenced provision. In practice, the referenced provision should be retrieved from an authoritative provision corpus rather than generated, because correctness and traceability are critical in audit workflows. This paper proposes a dense retrieval and reranking framework for referenced provision retrieval in electric power audit systems. The method follows a two-stage pipeline: a two-tower dense retriever efficiently recalls a small candidate set (top-20) from a large provision corpus, and a one-tower scoring model performs fine-grained reranking by jointly modeling the audit problem description and each candidate provision. To strengthen semantic matching under audit-specific contexts, the audit issue category is incorporated into the reranking input. Experiments are conducted on a Chinese electric power audit text dataset, demonstrating that the proposed retrieval–reranking design provides an effective and practical solution for accurate referenced provision retrieval.