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Assessing point load strength in irregular phyllite via an equivalent area method

Obtaining intact cylindrical cores from soft, weathered rock is frequently challenging, making the point load test a preferred technique for quickly determining rock strength. This study critically evaluates two widely used point load strength calculations—the loading-span and equivalent-diameter methods—and presents an alternative “equivalent area method” founded on the ratio between the actual failure cross section and the minimum cross section. Irregular phyllite specimens spanning three levels of weathering (heavily, moderately, and slightly) are tested to analyze how shape factor (β) and loading span (D) affect the point load strength index (Is). Results show that the area factor has a skewed distribution, with median values increasing from 1.40 to 1.46 as weathering intensifies—substantially exceeding the 0.3 to 1.0 range in the loading-span method and surpassing the 4/π factor used in the equivalent-diameter approach. A recommended median area factor of 1.43 is therefore proposed. The measured Is decreases following a power-law trend as β and D increase, with weathering reducing the sensitivity of Is to β but not significantly altering its sensitivity to D. For heavily, moderately, and slightly weathered samples, the allowable β should be at least 0.4, 0.5, and 0.6, respectively, and the loading span should lie between 35 and 80 mm. Unlike the traditional loading-span and equivalent-diameter methods, the proposed equivalent area method incorporates a variable area factor ψ that accounts for the actual failure cross section in irregular specimens. This approach reduces scatter in test results and is particularly valuable for soft or weathered rock, where conventional cylindrical core preparation is infeasible. Through extensive testing on phyllite, we demonstrate that this method provides more stable estimates of point load strength and offers practical guidelines for specimen selection, making it highly relevant for geotechnical applications in weak-rock environments.

Histological and molecular characterization of the digestive system of early weaned juveniles of Arapaima sp. reared in a recirculating aquaculture system

Arapaima spp., the world’s largest scaled freshwater fish, native to the Amazon and Essequibo river basins, are valued in aquaculture for their rapid growth and ornamental appeal. However, reliance on natural breeding and parental care in earthen ponds results in variable fingerling survival, hindering production. This study investigated the morphology and functionality of the digestive system of Arapaima sp. fingerlings from the Peruvian Amazon and evaluated the feasibility of early weaning onto compound diets to optimise growth and survival. Fingerlings were collected from a pond at 3.19 ± 0.03 cm total length (TL) and reared in a recirculating aquaculture system at 29 ºC under a 12L:12D photoperiod. Fish were successfully weaned from Artemia spp. nauplii onto an experimental compound diet (60% protein, 15% lipid) from 3.26 ± 0.02 cm TL within three days. Histological and gene expression analyses of key digestive enzyme precursors and appetite-regulating peptides (α-amylase, phospholipase A2, lipoprotein lipase, trypsinogen, chymotrypsinogen, pepsinogen, and peptide YY) revealed a mature digestive system, with enhanced digestive efficiency observed at 5.05 ± 0.34 cm TL. Based on digestive enzyme expression profiles and gut morphology, early juvenile Arapaima sp. possess a digestive physiology consistent with that of an omnivorous species with a preference for animal prey. The middle intestine was identified as a key site for fatty acid absorption and feed intake regulation. This study presents a novel, comprehensive analysis of digestive enzyme gene expression and associated tissue morphology in the genus Arapaima. It provides new insights into their digestive physiology and establishes the feasibility of early weaning onto formulated diets. Future research should explore the interplay between optimised compound feed formulations and refined early rearing protocols to maximise growth and survival throughout development.

Electromagnetic exposure levels of electric vehicle drive motors to cochlear implanted passenger

In order to evaluate the effects of electromagnetic radiation generated by the dual-drive motors of an electric vehicle on special passengers with cochlear implanted, this study considers a cochlear implanted passenger as the research object, takes the drive motors in electric vehicle as the exposure source. A calculation model including the vehicle body, brain tissue, skull, eyes, human body, and cochlear implant is built, and the finite element method is used to calculate the induced electric field (Ein), specific absorption rate (SAR), and temperature changes in different tissues and organs of the passenger’s body. The results show that the maximum value of Ein on the human body surface is 60.8 mV/m at the ankle. The Ein around the cochlear implant inside the human head is also high, with a maximum value of 57.1 mV/m. The maximum SAR of the human body is  1.99×10−6 W/kg, which also appears near the cochlear implant. Besides, the maximum temperature rise of the human body, brain tissue, and cochlear implant is 0.10 °C, 0.28 °C, and 0.0076 °C, respectively. Calculation shows that the Ein  and SAR of the human body and different tissues are much lower than the safety limit specified in the guidelines of the International Commission on Non-Ionizing Radiation Protection (ICNIRP), and the temperature rise does not reach the thermal damage threshold in the guidelines. The electric field around the electrode tip and the surface of the cochlear implant, the temperature rise of the cochlear implant also meet the requirements of the ICNIRP and the International Organization for Standardization’s 14708–7 medical device standard. The results could enrich the study on the electromagnetic environment of electric vehicles and provide references for the design and improvement of cochlear implants and electromagnetic exposure protection for vehicles.

Lipid Scrambling Pathways in the Sec61 Translocon Complex

A novel Fish Protein Hydrolysate supplement enhances honey bee foraging activity and colony strength: A pilot study

Honey bees require diverse nectar and pollen sources for optimal nutrition, especially during late winter and early spring. This study evaluated the effect of a tuna fish protein hydrolysate (FPH)-based dietary supplement on honey bee colonies during winter season. FPH was extracted with Spasmodigestin® tablets, which increased protein content and the availability of 15 amino acids. Colonies were fed 2% FPH extract in sugar syrup (50% W/V) weekly for six weeks, while control colonies received only sugar syrup. The size of brood, honey, and bee bread areas were measured every two weeks, while foraging activity (number of incoming and outgoing foragers) was evaluated weekly. FPH-fed colonies showed improved foraging activity (130 ± 10.65%), larger brood areas (116 ± 11.10%), and higher reserves of honey (152 ± 61.87%) and bee bread (132 ± 61.39%). These findings highlight the potential of tuna FPH-based supplements to strengthen honey bee colonies during periods of limited forage availability.

Coordination Chemistry toward Advanced Zn–I₂ Batteries with Four-Electron I^–/I⁰/I⁺ Conversion

Characterizing physical activity bouts in people with stroke with different ambulation statuses

Background and Purpose While physical activity is crucial for maintaining function, health, and well-being after a stroke, there is limited understanding of how individuals post-stroke accumulate their daily activity in terms of bouts and intensities. This study aimed to characterize and contrast the daily patterns, frequency and intensity of physical activity bouts between people post stroke with different ambulation statuses compared to healthy controls. Methods and Materials In this cross-sectional study, physical activity bouts patterns, frequencies, and intensities were evaluated using Actigraph GT3X+ accelerometers across three groups: 17 limited community ambulators (LCA) post-stroke (walking speed: < 0.8 m/s), 22 community ambulators (CA) post-stroke (walking speed: ≥ 0.8 m/s), and 28 healthy controls. Results People post stroke primarily engaged in 1–5 min bouts (LCA: 79%, CA: 76%), with less frequent engagement in 5–10 min (12–14%) and > 10 min bouts (9–10%) during the day. The LCA group engaged comparable or greater time spent in light physical activity during >5–10 and > 10 min bouts compared to CA and healthy controls, but less time in moderate to vigorous physical activity (P < .009). Both post-stroke ambulation groups were most active between 12–5 pm. Conclusions CA people post stroke exhibited patterns similar to healthy controls in physical activity bouts, whereas LCA primarily engaged in short bouts and light activity. In the context of secondary stroke prevention, encouraging LCA people post stroke to engage in frequent short bouts of moderate to vigorous physical activity or longer bouts of light physical activity might be realistic targets to improve cardiovascular health.

² H Quadrupolar Coupling Constant: A Spectroscopic Ruler for Transition Metal–Hydride Bond Distances in Molecular and Surface Sites

Development and calibration of a mathematical model of HIV outcomes among Rwandan adults: Informing achievement of global targets across sub-populations in Rwanda

Background We developed and calibrated the Central Africa-International epidemiology Databases to Evaluate AIDS (CA-IeDEA) HIV policy model to inform achievement of global goals, overall and across all sub-populations, in Rwanda. Methods We created a deterministic dynamic model to project adult HIV epidemic and care continuum outcomes, overall and for 35 subpopulations (age group, sex, HIV acquisition risk, urbanicity). Data came from the Rwanda cohort of CA-IeDEA, 2004–2020; Rwanda Demographic and Health Surveys, 2005, 2010, 2015; Rwanda Population-based HIV Impact Assessment, 2019; and literature and reports. We calibrated the model to 47 targets by selecting 50 best-fitting parameter sets. Targets reflected epidemic, global goals and other indicators. Best-fitting sets minimized the summed absolute value of the percentage deviation (AVPD) between projections and targets. Good performance was mean AVPD ≤5% across best-fitting sets and/or projections within target confidence intervals; acceptable was mean AVPD >5%–15%. Results Across indicators, 1,843 of 2,350 (78.4%) model projections were a good or acceptable fit to calibration targets. For HIV epidemic indicators, 247 of 300 (82.3%) projections were a good fit to targets, with the model performing better for women (80.3% a good fit) than for men (62.3% a good fit). For global goals indicators, 97 of 100 (97.0%) projections were a good fit; model performance was similar for women and men. For other indicators, 708 of 950 (74.5%) projections were a good or acceptable fit. Fit was better for women than for men (percentage virally suppressed only) and when restricting targets for number on ART to 2013 and beyond. Conclusions The CA-IeDEA HIV policy model fits historical data and can inform policy solutions for achieving global goals across all sub-populations in Rwanda. High-quality population-based data and novel approaches that account for calibration target quality are critical to ongoing use of mathematical models for programmatic planning.

Bioinspired Methionine-Selective Desulfurization Editing of Peptides via the Photocatalysis Strategy

Gender differences in paid work over time: Developments and challenges in comparative research

This paper examines gender differences in paid work over time and illustrates the pitfalls encountered by any comparative research that only considers either labor force participation rates or average working hours. To do so, we analyze harmonized survey data from Europe and the United States from 1992 to 2022 (N = 43,283,172) and show that more progress was made in closing gender gaps in labor force participation rates than in working hours. In most countries, women’s labor force participation rates increased considerably, but their average working hours decreased, whereas both men’s labor force participation rates and average working hours decreased or stagnated (but nonetheless still remained much higher than women’s). We show and argue that these countervailing trends in working hours and labor force participation rates make it difficult to paint a coherent picture of cross-national differences in women’s and men’s paid work and of changes over time. In response, we propose “work volume” as a supplementary or alternative measure for any type of comparative research. Work volume records zero working hours for nonemployed individuals and thus allows straightforward comparisons between women’s and men’s (or any other groups’) involvement in paid work. Using the proposed work volume measure, we show that gender gaps in paid work decreased over time, but that even in 2022, men’s involvement in paid work remained considerably higher than women’s—with gender gaps being lowest in the Scandinavian and the former Communist countries.

Multivariate Tuning of Photosensitization in Mixed-Linker Metal–Organic Frameworks for Efficient CO₂ Reduction

Predicting depression severity using machine learning models: Insights from mitochondrial peptides and clinical factors

Depression presents a significant challenge to global mental health, often intertwined with factors including oxidative stress. Although the precise relationship with mitochondrial pathways remains elusive, recent advances in machine learning present an avenue for further investigation. This study employed advanced machine learning techniques to classify major depressive disorders based on clinical indicators and mitochondrial oxidative stress markers. Six machine learning algorithms, including Random Forest, were applied and their performance was investigated in balanced and unbalanced data sets with respect to binary and multiclass classification scenarios. Results indicate promising accuracy and precision, particularly with Random Forest on balanced data. RF achieved an average accuracy of 92.7% and an F1 score of 83.95% for binary classification, 90.36% and 90.1%, respectively, for the classification of three classes of severity of depression and 89.76% and 88.26%, respectively, for the classification of five classes. Including only oxidative stress markers resulted in accuracy and an F1 score of 79.52% and 80.56%, respectively. Notably, including mitochondrial peptides alongside clinical factors significantly enhances predictive capability, shedding light on the interplay between depression severity and mitochondrial oxidative stress pathways. These findings underscore the potential for machine learning models to aid clinical assessment, particularly in individuals with comorbid conditions such as hypertension, diabetes mellitus, and cardiovascular disease.

Deciphering Catalyst–Support Interaction via Doping for Highly Active and Durable Oxygen Evolution Catalysis

Development of a novel risk score for diagnosing urinary tract infections: Integrating Sysmex UF-5000i urine fluorescence flow cytometry with urinalysis

Background Urinary tract infections (UTIs) are common globally, and are developing increased antibiotic resistance. Despite being the diagnostic “gold standard,” urine culture is limited by slow results and a high rate of false negative findings, leading to treatment delays, higher costs, and overuse of empirical antibiotics. Our study aims to develop a rapid and reliable model to predict clinical outcomes. Methods From January 1st to October 31st, 2023, we enrolled patients with symptoms suggesting UTI from the Outpatient Department of our hospital. Inclusion criteria were patients aged ≥18, initially diagnosed with UTI, available urinalysis, flow cytometry, and urinary culture. Exclusion criteria included failed sample collection and cultures, and pregnant women. A case-control study was conducted, with UTI cases defined as ≥ 10^5 CFU/ µ L and controls as < 10^5 CFU/ µ L, matched for age and sex in a 1:1 ratio. For validation, retrospective cases from July to December 2022 were selected with matching controls. Using urine culture as the gold standard, the predictive model was developed with backward stepwise logistic regression. Model discrimination was assessed using area under the curve (AUC). Results In our discovery cohort, we included 1,335 UTI cases and 1,282 non-UTI controls, with mean ages of 52.9 ± 17.1 years and 51.9 ± 16.4 years, and females of 76.9% and 77.7%. Using 100 cells/uL as a threshold, bacterial counts demonstrated a sensitivity of 91.0% and specificity of 45.7%. Our novel UTIRisk score, developed from urinalysis and flow cytometry parameters, showed strong discrimination for UTI, with a AUC of 0.82 (95% CI: 0.81–0.84). In the validation cohort, the AUC was 0.77 (95% CI: 0.74–0.80). The UTIRisk score exhibited excellent specificity (96.5%) and high positive predictive value (92.6%). The score performed strongly across subgroups, particularly in males and patients aged ≥65. Conclusions Our UTIRisk score can improve diagnosis, reduce unnecessary urine cultures, optimize antibiotic use, and help control antibiotic resistance in LMICs. Multicenter, and intervention-based studies are warranted before clinical implementation.

Designing Highly Conductive Anion Exchange Membranes: Tuning Domain Continuity with ABC Block Copolymer Self-Assembly

Mechanistic role of pyroptosis in Kawasaki disease: An integrative bioinformatics analysis of immune dysregulation, machine learning-based biomarker discovery, WGCNA, and drug repurposing insights

Kawasaki disease (KD) is an acute vasculitis that primarily affects children under five and is a leading cause of acquired heart disease in this age group. Despite the standard treatment with intravenous immunoglobulin (IVIG), approximately 10–20% of patients exhibit IVIG resistance, leading to persistent inflammation and an increased risk of coronary artery aneurysms（CAA）. The underlying molecular mechanisms driving KD, particularly the role of pyroptosis, remain incompletely understood. In this study, we employed integrative bioinformatics approaches to investigate the mechanistic role of pyroptosis in KD. By analyzing transcriptomic datasets, we identified differentially expressed genes (DEGs) associated with pyroptosis and immune dysregulation. Weighted Gene Co-Expression Network Analysis (WGCNA) was utilized to uncover key co-expressed gene modules, followed by functional enrichment analyses to explore the biological significance of these genes. Through machine learning-based biomarker discovery, we identified MYD88 and S100A12 as critical pyroptosis-related genes in KD. Their diagnostic potential was validated using external datasets, and their involvement in immune cell infiltration was assessed through computational deconvolution techniques. Furthermore, drug repurposing analysis and molecular docking simulations suggested that Atogepant, Ubrogepant, and Zanubrutinib could serve as potential therapeutic candidates targeting S100A12 and MYD88. These findings provide novel insights into the molecular pathogenesis of KD and highlight potential biomarkers and therapeutic targets for improving KD diagnosis and treatment strategies.

Coupling Amorphization and Compositional Optimization of Ternary Metal Phosphides toward High-Performance Electrocatalytic Hydrogen Production

Allosteric modulation of Plasmodium falciparum Isoleucyl tRNA synthetase by South African natural compounds

Targeting Plasmodium falciparum (Pf) aminoacyl tRNA synthetases is a viable strategy to overcome malaria parasite multi-drug resistance. Here, we focused on Pf Isoleucyl tRNA synthetase (PfIleRS) to identify potential allosteric inhibitors from 1019 South African Natural Compounds (SANC). Eleven potential hits, which passed ADMET and PAINS, were selected based on their docking binding affinity which was higher for PfIleRS than for human IleRS. Molecular dynamics simulations revealed that the compounds, particularly SANC456, commonly induced considerable changes in the global conformation and dynamics of PfIleRS, suggesting potential allosteric modulatory effects. Importantly, all 11 SANC hits reduced the binding affinity of the nucleotide AMP molecule by at least 25%. Some SANC ligand-bound systems (SANC456, SANC1095, and SANC1104) significantly increased the distance between the AMP and Ile ligands. Possible explanations for these changes were explored using three dynamic residue network centrality metrics. Betweenness centrality identified a major allosteric pathway in holo PfIleRS spanning the entire protein length. In contrast, SANC382, SANC456, SANC522, SANC806 and SANC1095 ligand-bound systems exhibited delta BC pathways (SANC-protein minus holo-protein), induced by the ligands, extending from their respective pockets into the active site. Additionally, eigenvector centrality revealed two important residue clusters either side of the holo active site which became altered in the ligand-bound systems, indicating possible allosteric activity. Lastly, many SANC systems showed decreased closeness centrality of zinc finger and active site residues, including the HYGH and KMSKR motifs. We believe that the compounds identified in this study as potential allosteric inhibitors have strong translational potential and warrant further investigation through in vitro and in vivo experiments. Overall, they hold promise as starting points for the development of new and effective antimalarial therapies, particularly against multidrug-resistant Plasmodium parasites.

Social determinants and risk factors associated with non-communicable diseases among urban population in Nepal: A comparative study of poor, middle and rich wealth categories of urban population using STEPS survey

Background Non-communicable diseases (NCDs) are significant public health concern globally, and the burden is disproportionately high among urban populations. This study aims to compare the social determinants, NCD risk, and NCD prevalence among different wealth categories and to determine the factors associated with hypertension, obesity, and diabetes among the urban population of Nepal. Methods This study used urban population data from cross-sectional STEP wise approach to NCD risk factor surveillance (STEPS) survey of 2019, resulting in a sample of 3460 individuals of 15-69 years for inclusion in the analysis. We used bivariate analysis to compare the social determinants, NCD risk and NCD prevalence among urban poor, urban middle and urban rich and multivariate logistic regression to determine the association between social determinants, NCD risks and obesity, hypertension and diabetes among urban population. Results The study found significant differences in hypertension, obesity and diabetes by gender, ethnicity, education, employment, smoking habits, and cholesterol levels between the three wealth groups. Among the urban poor, low education, unemployment and smoking habits were more prevalent, while high cholesterol was more prevalent among the urban rich. The significant factors associated with overweight and obesity after Bonferroni correction included Hilly region with higher odds of overweight (AOR=2.33, 95% CI=1.45-3.75,). In contrast, being from Karnali (AOR= 0.36, 95% CI=0.22-0.58) and Sudurpaschim (AOR=0.42, 95% CI=0.26-0.66) provinces were associated with lower odds of overweight and cholesterol, while cholesterol was associated with higher odds of obesity (AOR=1.01, 95% CI=1.01-1.02). Disadvantaged janajatis had the lower odds of overweight (AOR = 0.52, 95% CI = 0.36-0.78). Factors that remained significantly associated with hypertension and pre-hypertension after Bonferroni correction included: age, with higher odds of hypertension (AOR=1.03, 95% CI=1.02-1.04); men, who had higher odds of both pre-hypertension (AOR=1.68, 95% CI=1.19-2.36) and hypertension (AOR=2.23, 95% CI=1.56-3.47). Being obese (AOR = 5.12, 95% CI = 2.95-8.87, p = 0.001) and overweight (AOR = 1.69, 95% CI = 1.19-2.39, p = 0.003) were significantly associated with hypertension. Similarly, urban population residing in the hilly region had higher odds of diabetes (AOR=6.44, 95% CI=3.31-11.10) compared to the mountain region; those living in the Tarai region had higher odds of pre-diabetes (AOR=5.07, 95% CI=2.44-10.5) and diabetes (AOR=5.96, 95% CI=3.12-19.86). Respondents with high cholesterol higher odds of both pre-hypertension (AOR=1.00, 95% CI=1.00–1.02) and hypertension (AOR=1.03, 95% CI=1.02-1.04), pre-diabetics (AOR=1.00, 95% CI=1.00–1.02) and diabetics (AOR=1.03, 95% CI=1.02-1.04). Conclusion The findings indicate significant disparities in education, employment, and lifestyle habits across wealth groups; urban poor lacked education and employment. Factors such as ecological region, province, gender and age were associated with an increased risk of various health conditions such as being overweight, pre-hypertension, pre-diabetes, and diabetes. Improved health outcomes among urban populations interventions targeting increased access to education, additional investment in specific areas where outcomes are worst, and interventions to improve equitable access to healthcare are needed.