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Dispute resolution in China: A test of black's theory of legal behavior
Since its introduction, Black’s theory of legal behavior (BBL) has been widely applied in empirical studies to analyze legal decision-making and dispute resolution. However, its applicability in non-Western contexts remains underexplored. This study examines the extent to which Black’s theory explains dispute resolution choices in China. Drawing on nationally representative data from the 2013 Chinese General Social Survey (CGSS), this research systematically investigates how five social dimensions—stratification, morphology, culture, organization, and alternative social control—shape individuals’ choices in resolving disputes. Conflict resolution strategies are categorized into four levels: silent endurance, direct communication, third-party mediation, and litigation. These categories are coded ordinally to reflect increasing degrees of the quantity of law involved. The findings indicate that while BBL offers a useful analytical framework, it does not fully account for all observed patterns. Some apparent alignments between the theory and empirical data may be influenced by challenges in operationalizing key social dimensions and the complex interactions among them. However, these deviations do not necessarily refute Black’s theory; rather, they highlight the need for further refinement in its application to diverse socio-legal contexts.
A bilayered microneedle patch loaded with methotrexate and dexamethasone for transdermal treatment of psoriasis
Abstract Psoriasis is a persistent inflammatory dermatological disorder characterized by dysregulated hyperproliferation of keratinocytes and pathological immune cell infiltration, impacting a significant population globally. Conventional systemic therapies, including oral and injectable formulations, are often limited by adverse off-target effects, which limit their utility in long-term clinical management. To address this challenge, we developed a soluble bilayered microneedle patch (Methotrexate and dexamethasone co-loaded bilayer microneedles, MTX@DXM-MNs), which consists of an outer layer of gelatine-polyvinyl alcohol hydrogel loaded with dexamethasone (DXM) and an inner layer of aminocrystallized hyaluronic acid methacrylate hydrogel loaded with methotrexate (MTX). The patch successfully traversed imiquimod (IMQ)-induced thickened epidermis in murine models to achieve intralesional drug delivery and effectively alleviate psoriasis-like skin inflammation. Versus tacrolimus ointment (positive control), MTX@DXM-MNs markedly alleviated the manifestations of stratum corneum thickening, erythema, and scaling in a mouse model and attenuated the levels of inflammatory mediators in skin tissues and peripheral blood as well as splenic indices. In conclusion, the MTX@DXM-MN bilayered microneedle patch provides a new strategy for the efficient and safe treatment of psoriasis through the temporal and spatial synergistic effects of an outer layer for the immediate release of a hormone and an inner layer for the slow release of an immunosuppressant. Thus, this patch has potential as a future clinical alternative for the treatment of psoriasis.
Mechanization-driven farmland consolidation and farm household labor allocation: Evidence from grain producers in Shandong, China
Mechanization-driven farmland consolidation has become a key component of China’s efforts to raise grain productivity and optimize rural labor allocation. We used a survey of 630 grain-producing households in Shandong Province, and combined a Tobit model with propensity-score matching to identify the causal effects of consolidation on farm-household labor decisions. Consolidation reduced on-farm labor input by 8.4 percentage points through labor-saving technological substitution, yet the magnitude differed sharply between two mechanization pathways. Where households purchased their own machinery, on-farm labor rose by 5.3 percentage points, consistent with specialization incentives. By contrast, the use of custom mechanization services lowered on-farm labor by 7.5 percentage points. Labor-saving effects were strongest among ageing households, smallholders and farmers in hilly areas, suggesting enhanced overall efficiency in constrained settings. Policy implications include expanding service markets, coupling consolidation with vocational training for off-farm employment, and establishing a long-run monitoring framework to ensure sustainable transformation. However, this study relies on cross-sectional data, which limits its ability to capture dynamic change processes. Future research could conduct longitudinal tracking studies to evaluate the sustained effects and sustainability of policies.
Single-shot incoherent imaging with extended and engineered field of view using coded phase apertures
Design and evaluation of structural risk mitigation measures for transmission lines micro-pile foundations in mountainous region
Influenced by the complex geological conditions in mountainous region, micro-pile foundation for transmission line faces the risk of insufficient bearing performance. It is important to study the risk suppression measures of micro-pile foundation and its assessment method to promote the construction of transmission lines in mountainous regions. Firstly, the mechanical simulation model of pile-soil system for the micro-pile foundation is established in this paper, and the field test is carried out to verify the accuracy of the simulation model, thus the ultimate load of the micro-pile foundation is determined according to the current code requirement for maximum displacement in case of damage to the group pile foundation. Secondly, to address the subjectivity of traditional methods, an improved Likelihood-Exposure-Consequence (LEC) method is proposed. Its novelty lies in constructing a quantitative displacement-risk mathematical mapping, directly linking the physical limit state (maximum displacement) to the risk likelihood factor. Thirdly, structural risk reduction measures for the micro-pile foundation using micro-expanded pile foundation and micro-inclined pile foundation are proposed, and the ultimate load of the traditional micro straight pile foundation is used as an excitation to carry out the simulation of the bearing performance of the two improved micro-pile foundations, and the maximum displacements of the two improved micro-pile foundations are calculated. Finally, based on the proposed improved LEC method, the risk values-defined in the LEC framework as the quantitative product of Likelihood ( L ), Exposure ( E ), and Consequence ( C )-and risk classes of the two improved micro-pile foundations are calculated and compared with the conventional micro straight pile. The results demonstrate that the proposed strategies significantly reduce the safety risk class, providing a robust, quantifiable basis for optimizing foundation designs in complex mountainous terrain.
Residue-level determinants of the thermal stability of the extremophilic Ts2631 endolysin
Abstract In the face of the growing crisis of antibiotic resistance, peptidoglycan-degrading endolysins derived from bacteriophages offer a promising alternative to traditional antimicrobials. Thermostable variants, capable of maintaining their structure and activity under extreme conditions, are of particular interest. Here, we present a comprehensive analysis of endolysin Ts2631 from bacteriophage vB_Tsc2631, which infects Thermus scotoductus in Icelandic hot springs. This type 2 amidase exhibits exceptional thermostability, with a melting point ranging from 99.8 °C to 104.7 °C, depending on the solvent. Structural comparison with its mesophilic counterpart, T7 lysozyme, revealed shorter loops with lower B factors, suggesting reduced conformational flexibility. The Ts2631 sequence contains increased levels of tyrosine, proline, tryptophan, and arginine residues, amino acids commonly associated with thermophilic adaptation. To elucidate the contribution of individual residues, the melting temperatures (T m ) of 55 point mutants were determined. Substitutions at the catalytic Zn²⁺-coordinating residues (H30, H131, and C139) led to significant destabilization. Substitutions at positions Y60 and Y69 also reduced stability. In contrast, the disulfide bond (C80-C90) and arginine-mediated salt bridges showed limited effects. Among the aromatic and proline mutants, R20A, W102A, W109A, P140A, and W145A had significantly reduced T m values. R20 proved critical for peptidoglycan binding, while the hidden tryptophan and proline contributed significantly to the thermophilic fold. Overall, the data indicate that buried aromatic residues play a key role in maintaining the remarkable thermal resistance of Ts2631. This suggests a future strategy to enhance the stability of mesophilic endolysins with therapeutic potential by replacing non-conserved amino acids with tryptophan or proline residues.
Perceived sound localization abilities in blind individuals
Purpose There is extensive research on sound localization performance of blind individuals in laboratory settings. However, less is known about their spatial hearing experiences in more complex everyday environments. This study aims to assess the perceived sound localization abilities in blind individuals in common everyday tasks, which is a critical determinant of confidence and engagement in such tasks (e.g., independent travel). Method Fifty-eight adults with total or near-total blindness, including 28 with self-reported normal hearing and 30 with self-reported hard of hearing participated in this study. They completed the Dual Sensory Spatial Localization Questionnaire (DS-SLQ), a recently developed instrument that evaluates perceived difficulty in everyday localization tasks using vision and hearing. Properties of the DS-SLQ for blind individuals, including whether its items measure a single attribute (i.e., unidimensionality) and whether item difficulties match blind individuals’ perceived abilities (i.e., targeting), were validated using Rasch analysis. Multivariable regression models and correlation analysis evaluated the impacts of the onset of blindness, residual vision, hearing status, onset of hearing loss, use of hearing aids, and echolocation skills on perceived sound localization abilities. Results The DS-SLQ showed excellent targeting and good unidimentionality for blind individuals. Individuals with later onset of blindness reported significantly lower perceived sound localization abilities. The presence of hearing loss, particularly early onset, was associated with further reductions in perceived sound localization ability. Those who reported higher echolocation skills also reported better perceived sound localization abilities, regardless of their hearing status. Residual vision and use of hearing aids were not associated with perceived sound localization abilities. Conclusion Beyond frequently studied vision factors, hearing loss and its onset further affect perceived sound localization abilities and the likelihood of an individual being an echolocator. It is critical to consider hearing status in the rehabilitation of blind individuals for maintaining and enhancing spatial localization skills.
SFEL a machine learning framework for forecasting radar backscatter based ground deformation
Towards triple elimination of HIV, syphilis and HBV mother-to-child transmission: Protocol of a simplified and integrated strategy in Burkina Faso and The Gambia: Protocol for the phase 1 of the TRI-MOM project
Introduction Mother-to-child transmission (MTCT) of HIV, syphilis, and hepatitis B virus (HBV) commonly observed in the WHO African region is associated with excess morbidity and mortality. Despite some progress, the coverage of interventions to prevent MTCT of these infections remains insufficient, particularly for syphilis and HBV. To fulfil these gaps and achieve the triple elimination of MTCT of these infections by 2030, the World Health Organization (WHO) advocates for integration of prevention of MTCT (PMTCT) activities for HBV with HIV and syphilis antenatal services. In partnership with the local governments, the TRI-MOM project, conducted in 2 phases, aims to evaluate a simplified (based on inexpensive rapid diagnostic tests), integrated (in maternal and child health services) and coordinated (between the various programs and health care workers) strategy for the triple elimination of HIV, syphilis and HBV MTCT in Burkina Faso and The Gambia. Methods and analysis The strategy will be implemented in 5 rural and urban health facilities in each country and will include four activities: i) training sessions for healthcare workers working in maternal and child health services, ii) screening of pregnant women of the three infections using rapid diagnostic tests at the first antenatal visit, iii) clinical assessment and treatment of women tested positive for any of the 3 infections, and iv) raising awareness on HIV, Syphilis and HBV PMTCT among pregnant women and empowering those screened positive. 17,000 pregnant women are expected to be screened. The strategy will be evaluated through an interdisciplinary, mixed-methods approach comprising three studies: i) a quantitative and qualitative cross-sectional study conducted both before and after the implementation of the strategy to assess its impact on triple screening coverage in pregnant women; ii) a an intervention study with longitudinal follow-up of pregnant women positive for any of the three infections to assess the coverage of PMTCT measures; and iii) a cost and cost-effectiveness analysis of the project compared to the reference situation in each country, which will rely on a micro costing study to estimate the incremental cost of the strategy per mother/child couple compared with the reference situation in each country, and compare it to the number of avoided infections. Ethics and dissemination The study protocol has been approved by the competent authorities of the countries participating to the research (the LSHTM/MRCUG Scientific Coordinating Committee, the Gambia Government/MRC Joint Ethics Committee, the LSHTM ethics committee, the Burkinabe National Ethical Committee for Research in Health and the French Commission on Information Technology and Liberties). Results on the feasibility and acceptability of the triple elimination strategy will be disseminated using different media including policy briefs, posters and articles. Trial registration number ClinicalTrials.gov NCT05951751 .
Assessing the impact of open-circuit voltage estimation methods on UKF performance for lithium-ion battery SOC and SOH estimation
Abstract Accurate estimation of State of Charge (SOC) and State of Health (SOH) in lithium-ion batteries is critical for effective Battery Management Systems (BMS). A key factor in enhancing estimation accuracy is the appropriate selection of the Open-Circuit Voltage (OCV-SOC) model. This study investigates two prevalent methods for OCV modeling: the Low-Current (LC) method and the Incremental Current (IC) method, and evaluates their impact on the performance of the Unscented Kalman Filter (UKF) for SOC estimation and instantaneous internal resistance (R 0 ) tracking. In this work, SOH is primarily assessed through R 0 , which is adopted as the main degradation indicator under dynamic operating conditions. The dynamic model employed is an Equivalent Circuit Model (ECM) of a lithium-ion battery, with estimations conducted using real-world driving data (Federal Urban Driving Schedule, FUDS). The results demonstrate that the IC method, due to its higher local resolution in the OCV modeling, achieves faster convergence and higher estimation accuracy for SOC, particularly when the initial SOC is subject to error. In contrast, the LC method, despite its experimental simplicity, exhibits significant errors in the early stages of simulation due to excessive smoothing of the OCV curve. Furthermore, a comparison of R 0 trends reveals that the IC method provides a more consistent and stable estimation, whereas the LC method shows greater short-term fluctuations and reduced stability. This difference is attributed to the higher accuracy of the OCV curve in the IC method. Ultimately, the choice of the OCV extraction method directly influences the accuracy and stability of SOC estimation and SOH analysis based on R 0 tracking.
Multi-attention cross-scanning VM-UNet for X-ray welding defect detection of steel pipeline
Welding defect detection of steel pipelines (SPWDD) is critical for ensuring the safe use of oil/gas pipelines. Due to the complex morphology of welding defect X-ray images (WDXI) in steel pipes and the/low contrast between the defects and the background, SPWDD is an important and challenging topic. To address these challenges, a Multi-Attention Cross-scanning VM-UNet (MACVM-UNet) for SPWDD is constructed. This model adopts the cross-Scanning Visual State Space Model (CVSS) to capture the local features and long-range dependencies, introduces channel attention skip connections (CASC) instead of the conventional skip connections to enhance the performance of globally and locally feature fusion, and employes the multi-scale Attention Feature Aggregation (MSAFA) module to fuse the multi-scale features. The combination of CVSS, CASC and MSAFA can effectively enhance the performance to extract the global-local features of small-sized and large-sized WDXIs. The experimental results on the WDXI dataset validate that the proposed MACVM-UNet outperforms the state-of-the-art models with superior SPWDD performance while maintaining low computational complexity. It achieves the mAcc 86.03%, mPre of 86.14% and mF1 of 84.6% with lower training time of 1.61 h. The proposed method provides an efficient and feasible solution for non-destructive SPWDD of oil/gas pipelines.
Predictors of unsuccessful tuberculosis treatment outcome in Bhutan: A retrospective study using comprehensive national tuberculosis surveillance data
Abstract Despite the high burden of tuberculosis in Bhutan, data on treatment outcomes are limited. Using a national TB dataset from 2018 to 2021, provided by the National Tuberculosis Reference Laboratory, we conducted a retrospective cohort study to assess treatment outcomes and explore factors associated with unsuccessful TB outcomes. Of the 3,619 patients who received TB treatment, 3,330 had a recorded treatment outcome. Among these, 96.2% ( n = 3,202) had a successful outcome (44.4% ( n = 1,480) were cured and 51.7% ( n = 1,722) completed treatment), and 3.8% ( n = 128) had an unsuccessful outcome (2.8% ( n = 93) died, 0.7% ( n = 23) experienced treatment failure, and 0.4% ( n = 12) were lost to follow-up). Multivariable logistic regression showed patients older than 60 years of age (aOR 4.3; 95% CI 2.09-10.0; p-value < 0.001), diagnosed in 2019 (aOR 1.7; 95% CI 1.03–2.86; p-value 0.041), 2021 (aOR 1.74; 95% CI 1.03–2.97; p-value 0.038), and pulmonary TB (aOR 2.69; 95% CI 1.76–4.27; p-value < 0.001) were more likely to have an unsuccessful treatment outcome. The proportion of successful TB treatment exceeded the global target rate of 90%, with a low rate of unsuccessful outcomes. Patients with pulmonary TB and elderly patients require active follow-up to ensure their treatment success increases. In-depth studies need to be conducted to understand the circumstances leading to the treatment failures and death.
An overdispersed count regression model for analyzing road accident fatalities and injuries in Bangladesh
Road traffic accidents (RTAs) continue to be a major global public health issue, particularly in countries with developing road safety infrastructure like Bangladesh, where the road traffic fatality rate remains alarmingly high. This study aims to examine the relationship between road traffic accident outcomes—fatalities and injuries—and multiple contributing factors, including driver behavior, vehicle characteristics, environmental conditions, and road infrastructure. Using a comprehensive dataset of 64,050 police-reported road traffic accidents in Bangladesh (2006–2015), we apply a Negative Binomial Regression (NBR) model to account for overdispersed count data. Our results highlight that driver-related factors such as seatbelt use and age, vehicle factors such as fitness certification, and environmental conditions such as weather and road geometry significantly influence both fatalities and injuries. Notably, roads without dividers and in rural areas were found to be particularly hazardous. The study underscores the need for targeted road safety interventions, such as improved enforcement of seatbelt use, infrastructure upgrades (e.g., dividers, lighting), and more transparent vehicle fitness monitoring. By integrating driver, vehicle, environmental, and infrastructural variables, this study provides a comprehensive understanding of road traffic accident severity in Bangladesh, offering data-driven insights to inform evidence-based policymaking and infrastructure planning aimed at reducing road traffic injuries and fatalities.
Smart home energy management for sustainable socioeconomic development in Egyptian households
Abstract Smart Home Energy Management Systems (SHEMS) play a critical role in reducing household energy consumption. However, existing solutions often depend on complex infrastructure and dynamic pricing models, limiting their applicability in developing countries like Egypt, where Inclining Block Rate (IBR) tariffs are in effect. This study presents a low-cost, hardware-minimal SHEMS prototype designed for Egypt’s socio-economic and climatic context. The system incorporates a comfort zone-based load scheduling algorithm, which allows users to define acceptable used area for according to its facilities and input the number of active household members over three timeframes (hourly, daily, weekly). Based on this input, the system recommends selective air-conditioner usage to minimize costs without compromising comfort, while leaving the final decision to the user. This approach promotes energy awareness and preserves user autonomy. The prototype integrates photovoltaic (PV) generation and battery storage. Results show that the comfort zone strategy yielded the highest annual savings and fastest payback, while the PV-battery system offered the best long-term return. Environmentally, Greater Cairo scale deployment could reduce CO₂ emissions by over 1.4 million ton annually. The system aligns with SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action), offering a scalable, context-sensitive solution for sustainable energy management in resource-constrained settings.
Carbon storage in Sichuan Province (Southwest China) from 1980 to 2050: Spatial-temporal variation, driving factors and future trends
Research on carbon storage is crucial for guiding regional sustainable development. However, Sichuan Province lacks long-term systematic analyses of carbon storage, and the driving mechanisms behind its changes remain unclear. This study systematically examines the spatiotemporal evolution of LUCC(land use/cover change) and carbon storage in Sichuan from 1980 to 2020, analyzes driving factors of carbon storage changes, and simulates future carbon storage distribution under different scenarios, based on LUCC data and 13 driving factors. Key findings include: (1) Over the 40-year period, land use was dominated by grassland, forest land, and farmland, maintaining a stable “grassland/forest land in the west, farmland in the east” pattern, with notable farmland and water body shrinkage alongside grassland and construction land expansion. (2) Total carbon storage showed minor fluctuations (9,201.53–9,209.52 Tg) but exhibited significant spatial heterogeneity, persistently displaying a “high in the west and low in the east” distribution. Water body-to-grassland and farmland-to-forest land conversions substantially increased carbon storage, while forest land-to-grassland and farmland-to-construction land transitions decreased it. (3) Spatial autocorrelation analysis revealed a negative correlation between carbon storage and land use intensity, with pronounced spatial clustering—High-High clusters concentrated in western regions and Low-Low clusters distributed peripherally. (4) Temperature and Digital Elevation Model emerged as dominant factors, while transportation accessibility and precipitation showed minimal influence. Human activities demonstrated moderate regulatory effects, with factor interactions significantly enhancing explanatory power, indicating multi-factor driven changes. (5) Multi-scenario projections (2030–2050) maintained the “high in the west and low in the east” pattern. Compared to 2020, SSP1–1.9 (Shared Socioeconomic Pathway 1–1.9) showed minimal change (10,711.94 ~ 10,712.16 Tg), SSP2–4.5 (Shared Socioeconomic Pathway 2–4.5) exhibited the largest decline (9,243.73 ~ 9,202.01 Tg), and SSP5–8.5 (Shared Socioeconomic Pathway 5–8.5) also decreased notably (9,015.01 ~ 8,980.07 Tg). This study provides a scientific basis for future land use optimization and carbon sink management in Sichuan Province.
Synthesis of highly conducting molybdenum disulfide electrode for asymmetric supercapacitor applications
Doing more with less: Genomic quasi-G-primes differentiate septic from healthy patients
Sepsis is a life-threatening state of disseminated infection, and treatment requires knowledge of the organism responsible. The gold standard for sepsis diagnosis is blood culture, which requires days of growth. Next-generation sequencing has been proposed as an alternative; however, existing methods may lack sensitivity. In this work, we explore the idea of genomic quasi-G-primes, which are short DNA sequences specific to a single species within a group of relevant species. We first validated the genomic quasi-G-prime classification in controlled Staphylococcus aureus sequencing experiments, and then applied the same approach to blood-derived sequencing data from septic and healthy patients, where genomic quasi-G-prime profiles distinguished disease states. Our method is highly space-efficient, permitting fast classification on modest hardware and enabling it to outperform existing taxonomic classification approaches in this task.
A chain mediation model reveals the association between social capital and successful aging in older adults
Machine learning-inspired similarity measure to forecast M&A from patent data
Defining and finalizing Mergers and Acquisitions (M&A) requires complex human skills, which makes it very hard to automatically find the best partner or predict which firms will make a deal. In this work, we propose the MASS algorithm, which adapts a patent-based measure of similarity between companies to forecast M&A deals. MASS is based on an extreme simplification of tree-based machine learning algorithms and naturally incorporates intuitive criteria for deals; as such, it is fully interpretable and explainable. By applying MASS to the Zephyr and Crunchbase datasets, we show that it outperforms a more “black box” graph convolutional network algorithm. The latter, however, turns out to be the most effective algorithm when considering companies with disjoint patenting activities. This study provides a simple and powerful tool to model and predict M&A deals between companies active in patenting, offering valuable insights to managers and practitioners for informed decision-making.