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Temperature dependence of adhesive friction properties of rubber asphalt mortar and its mechanism of action
The tire-road contact friction system has been widely studied. However, the traditional theoretical model of pavement anti-sliding does not pay attention to the influence of temperature on the tire-road interface friction system. The purpose of this paper is to simulate the adhesive friction process of rubber asphalt mortar under different temperature and different phase conditions by molecular dynamics simulation, so as to explain the adhesive friction mechanism of rubber asphalt mortar. In this study, the molecular model of rubber asphalt mortar with rubber powder content of 0%, 10%, 20% and 30% was first constructed by Materials Studio software. Secondly, the molecular dynamics simulation was carried out by COMPASS II force field, and the glass transition temperature, bulk modulus and Young’s modulus of the molecular model of rubber asphalt mortar were calculated. Then, the variation characteristics of the friction coefficient index of the rubber-asphalt mortar-aggregate three-layer friction pair model with temperature were simulated, and the simulation results of elastic modulus and adhesion work were comprehensively analyzed. The results showed that the glass transition temperature of the molecular model of rubber asphalt mortar is between -20°C and 0°C, and the bulk modulus and Young’s modulus of rubber asphalt mortar show an upward trend with the increase of rubber powder content and temperature. The friction coefficient of the rubber-asphalt mortar-aggregate three-layer friction pair model increases with the increase of temperature and rubber powder content. The results of Young’s modulus and adhesion work simulation show that as the temperature increases, the phase state of the rubber asphalt mortar changes, and the adhesion increases, resulting in an increase in the friction coefficient of the rubber asphalt mortar. In addition, the simulated and predicted values of the friction coefficient of the rubber-asphalt mortar-aggregate three-layer friction pair model with temperature change are well fitted, and the maximum difference is 0.32.
A contrastive learning framework with dual gates and noise awareness for temporal knowledge graph reasoning
Local data for local programming: Results from an HIV biobehavioral survey among people who inject drugs in Livingstone, Lusaka, and Ndola, Zambia, 2021
Introduction People who inject drugs (PWID) in Zambia are an understudied population at high risk for HIV acquisition and transmission. We report here on the progress within the PWID communities of Livingstone, Lusaka, and Ndola, Zambia towards the Joint United Nations Programme on HIV/AIDS (UNAIDS) 95-95-95 targets. Methods A biobehavioral survey used respondent-driven sampling to survey 235 PWID in Livingstone, 349 in Lusaka, and 259 in Ndola in 2021–22. Questions on HIV and injection drug use were administered, and blood was collected for HIV, syphilis, Hepatitis B, and Hepatitis C testing. Weighted prevalence and 95% confidence intervals (CIs) were calculated using Gile’s sequential sampling estimator. Results In Livingstone, Lusaka, and Ndola, HIV prevalence among PWID was 11.9% (95% CI: 7.3, 16.5), 7.3% (95% CI: 4.5, 10.2), and 21.9% (95% CI: 14.5, 29.3), respectively. Among HIV-positive PWID in Livingstone, 70.7% (95% CI: 55.4, 85.0) were aware of their HIV status (95% is 1st UNAIDS target), 100% of those were on antiretroviral therapy (ART) (95% is 2nd UNAIDS target), and 100% of those achieved viral load suppression (VLS) (95% is 3rd UNAIDS target). In Lusaka, 66.0% (95% CI: 49.3, 82.2) were aware, 75.7% (95% CI: 51.1, 99.9) were on ART, and 66.3% (95% CI: 42.1, 90.9) achieved VLS. In Ndola, 60.2% (95% CI: 44.1, 76.0), 100%, and 90.2% (95% CI: 82.2, 98.3) were aware, on ART, and achieved VLS, respectively. Conclusions Awareness of HIV status was low among PWID living in Livingstone, Lusaka, and Ndola, Zambia. Treatment and VLS progress were lacking in Lusaka and Ndola as well with Lusaka showing the least progress toward all three UNAIDS targets. Our site-level findings highlight critical gaps in PWID-specific HIV awareness, treatment, and VLS status in three major urban areas in Zambia that limit progress toward HIV epidemic control in this hard-to-reach population.
Novel ribosome biogenesis-related biomarkers and therapeutic targets identified in psoriasis
Management compliance attention, social performance and pay gap: Evidence from China
The pronounced pay gap prevalent in companies has raised critical concerns regarding organizational equity. This study investigates mechanisms to mitigate pay gap through the lens of management compliance attention, with the dual objectives of enhancing intra-firm distributive justice and fostering sustainable organizational development. Furthermore, this study employs a comprehensive methodology, including textual analysis of annual reports to construct management compliance attention variables and the Chinese Huazheng ESG rating system to measure social performance. The results show that:(1) Management compliance attention is negatively correlated with pay gap(β = -0.010,p < 0.01); (2) Social performance is negatively correlated with pay gap(β = -0.035,p < 0.01); (3) Social performance strengthens the negative effect of management compliance attention on pay gap(β = -0.022,p < 0.05). Based on the results, we find that management compliance attention and social performance can narrow pay gap respectively, and that social performance positively moderates the relationship between compliance attention and pay gap. In addition, organizational resilience is identified as a partial mediator, explaining how compliance attention enhances firms’ ability to adapt to external changes, thereby reducing pay gap. Heterogeneity analysis shows that management compliance attention and social performance effectively narrow pay gap in state-owned shareholding companies, and widen pay gap in private shareholding companies. This study contributes to the literature on the economic consequences of corporate compliance and social performance and the determinants of pay gap. Practical implications involve recommendations for firms to strengthen corporate compliance systems, enhance social performance and organizational resilience, and establish transparent compensation frameworks.
Comprehensive quantitative evaluation and mechanism analysis of influencing factors on yield and quality of cultivated Gastrodia elata Blume
Correction: Detection and position evaluation of chest percutaneous drainage catheter on chest radiographs using deep learning
Author Correction: Comparing two corrective exercise approaches for body image and upper-quadrant posture in schoolgirls with hyperkyphosis
Association between ‘Emergency obstetric & newborn care readiness’ and delivery service utilization in Bangladesh: Evidence from national health facility assessment surveys
Background Bangladesh faces one of the highest global burdens of maternal and newborn deaths, primarily caused by hemorrhage and eclampsia/preeclampsia. Despite reducing maternal mortality by 40%, comprehensive medical interventions remain insufficient in health facilities. Objectives This study assessed the readiness of sub-district hospitals in Bangladesh to provide Emergency Obstetric and Newborn Care (EmONC) and analyzed the association between facility readiness and delivery rates. Methods Using Health Facility Assessment Survey data from 140 hospitals in 2014 and 141 in 2017, facility readiness was measured based on nine signal functions: administering antibiotics, oxytocin, and anticonvulsants; providing blood transfusions; performing cesarean and assisted vaginal deliveries; managing retained placentas and products of conception; and neonatal resuscitation. Donabedian’s model guided the analysis. Multiple linear regression examined associations between facility readiness and delivery rates using 2017 data. Results Between 2014 and 2017, the availability of signal functions such as oxytocin (85% to 95%), anticonvulsants (58% to 63%), and blood transfusions (22% to 38%) improved. In 2014, 77% of facilities had at least 5 signal functions, 49% had 7, and 6% had all 9. By 2017, these increased to 83%, 56%, and 8%, respectively. Despite these improvements, the mean readiness index remained nearly unchanged (0.67 in 2014 vs. 0.69 in 2017). Only 8% of facilities performed fewer than 52 deliveries annually in 2017, while 26% conducted over 500. Regression analysis revealed a significant association between readiness scores and delivery rates (p = 0.009). Conclusion While certain indicators improved, overall readiness stagnated due to shortages of anesthetists, gynecologists, and essential supplies. With 64% of surveyed sub-district hospitals classified as comprehensive care facilities, resource and staffing investments are crucial to enhance readiness and reduce maternal and newborn mortality.
Single view generalizable 3D reconstruction based on 3D Gaussian splatting
Abstract 3D Gaussian Splatting (3DGS) has become a significant research focus in recent years, particularly for 3D reconstruction and novel view synthesis under non-ideal conditions. Among these studies, tasks involving sparse input data have been further classified, with the most challenging scenario being the reconstruction of 3D structures and synthesis of novel views from a single input image. In this paper, we introduce SVG3D, a method for generalizable 3D reconstruction from a single view, based on 3DGS. We use a state-of-the-art monocular depth estimator to obtain depth maps of the scenes. These depth maps, along with the original scene images, are fed into a U-Net network, which predicts the parameters for 3D Gaussian ellipsoids corresponding to each pixel. Unlike previous work, we do not stratify the predicted 3D Gaussian ellipsoids but allow the network to learn the positioning autonomously. This design enables accurate geometric representation when rendered from the target camera view, significantly enhancing novel view synthesis accuracy. We trained our model on the RealEstate10K dataset and performed both quantitative and qualitative analysis on the test set. We compared single-view novel view 3D reconstruction methods across different 3D representation techniques, including methods based on Multi-Plane Image (MPI) representation, hybrid MPI and Neural Radiance Fields representation, and the current state-of-the-art methods using 3DGS representation for single-view novel view reconstruction. These comparisons substantiated the effectiveness and accuracy of our method. Additionally, to assess the generalizability of our network, we validated it across the NYU and KITTI datasets, and the results confirmed its robust cross-dataset generalization capability.
Correction: Medication adherence and quality of life among geriatric patients: Insights from a hospital-based cross-sectional study in India
Integrating machine learning and symbolic regression for predicting damage initiation in hybrid FRP bolted connections
Abstract The increasing adoption of machine learning (ML) in fiber-reinforced polymer (FRP) composite design has led to a reliance on black-box models, which achieve high predictive accuracy but lack interpretability. Python symbolic regression (PySR) offers a solution by deriving explicit equations that reveal the governing mechanics of composite structures. This study focuses on hybrid FRP bolted connections, which are rapidly adopted in the industry but remain insufficiently addressed in academic research. To address this gap, a framework was developed to identify key design parameters and predict damage initiation loads by integrating experimental testing, finite element modeling (FEM), and ML. Feature selection and ML models analyzed the dataset, providing insights that guided PySR in deriving interpretable equations. Hybrid L-joint specimens were fabricated and tested to determine damage initiation loads, with results validating FEM models in ABAQUS. A design of experiments approach structured the dataset, and feature selection identified key factors influencing joint performance. ML models assessed dataset quality, with Huber regression emerging as the best-performing model. Based on insights from feature analysis and ML models, PySR derived a compact, interpretable equation that provided greater accuracy and deeper physical insights than the Huber model. This equation aids hybrid L-joint design by improving the understanding of damage initiation mechanics. Beyond predictive accuracy, the findings highlight the model’s scalability to different bolt sizes, equally spaced row of bolts, and stacking sequences. This study demonstrates the potential of interpretable ML in structural engineering applications, particularly for hybrid composite-metal joints, where transparent models are essential for design optimization and predictive accuracy.
Microbial community succession mediated by planting patterns in the Loess Plateau, China: Implications for ecological restoration
Microbial community succession plays a key role in restoring fragile ecosystems and mitigating ecological degradation. However, the mechanisms by which vegetation restoration promotes ecological restoration and microbial community reconstruction in degraded soils remain unclear. This study utilized metagenomic high-throughput sequencing technology to analyze microbial community dynamics in soil samples collected from eight different planting patterns in the ecologically degraded areas of the Chinese Loess Plateau. The results indicated significant effects of terrain location and restorative cropping patterns on soil microbial abundance and function. In particular, soil C and N nutrient abundance was highest in mixed forest soils, and the total number of microorganisms was highest and more diverse. Therefore, through vegetation restoration, mixed forests significantly enhanced regional ecological functions. Notably, creating mixed forests with both trees and shrubs resulted in optimal ecological functions, providing a valuable direction for vegetation construction and structural optimization in the region.
The effect of operational parameters on the properties of thorium uranium oxide produced via oxalates’ coprecipitation
Advanced strategies for enhancing kaolin ceramics using nanostructured additives: A comprehensive study
In this study, we investigated the enhancement of Egyptian kaolin ceramics using various nanostructured additives: polyvinyl alcohol (PVA), titanium dioxide (TiO2) nanofibers, carbon nanotubes (CNTs), silicon dioxide (SiO2) nanoparticles, and activated carbon (AC). The results showed that PVA and TiO2 nanofibers significantly increased the compression strength of the ceramics, with TiO2 nanofibers providing the highest improvement at 2.47 MPa. SEM analysis revealed that these additives facilitated better particle agglomeration, leading to improved mechanical properties. TGA indicated a shift in the sintering reaction peak from 511°C for pristine kaolin to 548°C for PVA-modified kaolin and slightly higher for TiO2-modified kaolin, suggesting enhanced sintering processes. Additionally, the thermal cycling tests demonstrated that TiO2 nanofibers-modified kaolin exhibited exceptional stability, with no change in apparent density, highlighting its potential for refractory applications. PVA-modified samples also showed a significant decrease in porosity and water absorption. These findings underscore the potential of specific nanostructured additives to enhance the mechanical and thermal properties of kaolin ceramics, offering valuable insights for future research and industrial applications.
Smoking prevalence and correlates among inpatients with schizophrenia or schizoaffective disorder
Abstract Many studies have shown that cigarette smoking prevalence rate is high in patients with schizophrenia. Despite the strong association between smoking and schizophrenia, findings on the relationships between smoking, psychiatric symptoms and cognitive functions remain mixed. Furthermore, the smoking rate among acute inpatients who need tertiary mental health care is still unknown. In this study we investigated the smoking rate in this patient population and examined connections between smoking and cognitive functions, psychiatric symptoms, and clinical and demographic characteristics. A retrospective chart review of patients admitted to a tertiary acute psychiatric facility over a 7-year period was conducted. Information such as patient smoking status, diagnosis, and psychiatric assessment scores, were retrieved. Independent samples t-tests and Chi-squared tests were used to compare variables between smoker and non-smoker groups. The smoking prevalence rate was 72%, approximately four times the smoking rate in the general population in Canada. Compared to the non-smoker group, the smoker group were significantly younger, more likely to be male, had less years of education, shorter illness duration, higher rate of concurrent substance use disorder, and less days of hospital stay. However, the two groups did not show differences in severity of illness, types/numbers of medication used, positive and negative symptoms, and cognitive impairment. Smoking status appeared to be associated with several demographic and clinical features. Smoking did not significantly relate to patients’ illness severity, medication use, psychiatric symptoms, or cognitive functioning.
Effects of an aquatic protocol on electromyography activation and strength of lower limb muscles in blind women: A randomized controlled trial
Purpose Visual impairment poses considerable challenges to mobility and everyday tasks, frequently leading to a more sedentary lifestyle and reduced physical fitness levels. Therefore, this study investigated the effects of a tailored aquatic exercise protocol on muscle activation and strength in visually impaired individuals. Materials and methods Thirty women who were blind (mean age = 29.03 ± 2.20 years) were randomly assigned to an experimental (EX) group and a control (CO) group. The EX group participated in three weekly 60-minute aquatic sessions, while the CO group maintained regular activities. Electromyography (EMG) activation and onset time were measured in the tibialis anterior, gastrocnemius medialis, rectus femoris, and biceps femoris. Muscle strength was also assessed in the ankle dorsiflexors and plantarflexors, as well as the knee flexors and extensors. Results The EX group showed increased EMG activation for the tibialis anterior, gastrocnemius medialis, rectus femoris, and biceps femoris in both anterior-posterior (2.23 MVIC%, 95% CI: 1.13 to 3.34, p < 0.001) and posterior-anterior directions (2.35 MVIC%, 95% CI: 1.80 to 2.91, p < 0.001) compared to CO group. Onset time decreased significantly in the EX group relative to CO group (anterior-posterior: -108.07 ms, 95% CI: -117.23 to -98.89, p < 0.001; posterior-anterior: -98.72 ms, 95% CI: -106.54 to -90.90, p < 0.001). Muscle strength significantly increased in the EX group compared to the CO group, with greater strength in ankle dorsiflexors (4.42 N/kg, 95% CI: 3.42 to 5.42, p < 0.001) and knee extensors (2.72 N/kg, 95% CI: 1.04 to 4.40, p < 0.001). Conclusions The aquatic exercise program improved neuromuscular function and strength in women with visual impairments, supporting its use in rehabilitation. Trial registration IRCT2017022132705N1
Activated carbon from olive pomace for hexavalent chromium removal: synthesis, characterization, and adsorption mechanism analysis
Impact of different harvest times on yield and quality of summer savory (Satureja hortensis L.) genotypes
Summer savory (Satureja hortensis L.) is a plant of the Lamiaceae family that grows in various ecological regions of the world. It is one of the medicinal-aromatic plants with huge economic value. The objective of this study was to determine the yield and quality of eight different summer savory genotypes, harvested at three different developmental stages, i.e., beginning of blooming, 40–50% blooming and full bloom stage. A field experiment was conducted during 2021 and 2022, and parameters related to growth, yield, and essential oil content were recorded. The maximum plant height, fresh and dry herb yield, dry leaf yield and essential oil content were obtained at the full bloom stage. The highest fresh herb yield was attained by genotype G6 and G7during the first and second year, respectively, while genotype G7 produced the highest dry herb and dry leaf yield during both years. The highest essential oil yield was obtained from genotype G8 and G7 in the first and second year of the study, respectively. Carvacrol, γ-terpinene, α-terpinene and p-cymene were the most abundant essential oil components observed in summer savory genotypes harvested at different developmental stages. The frequently detected component in the essential oil was carvacrol, which was recorded at 40–50%blooming period. The results of the current study proved that the most suitable period for harvesting summer savory genotypes was full blooming period in terms of yield values, and 40–50% blooming period for extracting essential oil especially carvacrol.