Browse Articles

Gastrointestinal polyp detection method based on the improved RT-DETR

Study on the influencing factors of shear strength of loess mudstone interface

In Loess Plateau, low shear strength of the loess–mudstone contact interface leads to the loess–mudstone landslides. However, the influencing factors of shear strength of loess-mudstone interface and the disaster-causing effect of interface landslide are not clear. Therefore, this study focus on the loess-mudstone interface, and conducts direct shear tests under different water content, density and morphology conditions. The results show that the shear strength of loess-mudstone interface is always lower than that of homogeneous loess and mudstone. An increase in moisture content leads to a continuous reduction in shear strength, whereas an increase in dry density enhances shear strength. A decrease in interface roughness also results in a reduction in shear strength parameters. Specifically, when interface roughness decreases from 1.72 to 0, cohesion decreases by 42%, and friction angle decreases by 13%. The failure modes in different interface types can be classified into three: interface shear, locked-segment, and partial locked-segment failure model. This study analyzes the influencing factors and internal mechanism of shear strength of loess-mudstone interface, reveals its landslide disaster effect, and puts forward suggestions for risk assessment of loess-mudstone landslide. The results are of great value to the potential risk assessment of loess-mudstone landslide.

Predicting genetic evolution of viruses to identify suitable vaccines using artificial intelligence

Abstract The evolution of the viruses is rapidly becoming a global challenge to the creation of vaccines since the new variants are often capable of escaping the immune system and decreasing the vaccine efficacy. The traditional methods of genomic epidemiology rely on the retrospective phylogenetic analysis, which can elucidate the previous mutations, but cannot predict the evolutionary trends in the future. In order to address these disadvantages, a new Refined Deep Evolutionary Learning Framework (R-DELF) is proposed that combines the genomic, structural, and temporal intelligence in predicting proactive viral mutations and assessing vaccine suitability. The methodology uses an ESM-2 Transformer that extracts structure-aware embeddings, merged with dual-attention Graph Neural Networks (GNNs) which learn phylogenetic and structural dependencies. Evolutionary learning maximiser improves adaptation modelling and an Explainable AI layer, which offers interpretability based on residue-level attribution. Tests indicate that experimentally it achieves 99.2% accuracy, 97.92% precision, 98.89% recall and 99.4% F1, which is higher than the current AI-based virology models. It is implemented in Python and with the help of TensorFlow and genomic and protein data obtained via Kaggle. The framework allows predicting the high-risk mutations in advance, facilitates the production of vaccines on time, and increases the preparedness to pandemics by making intelligent, data-driven predictions of viral evolution.

Differences in the fitness effects of traded resources shape traits and persistence in multi-mutualist communities

Mutualistic interactions, where species reciprocally benefit from each other, are crucial for ecosystem stability and biodiversity. These interactions often involve species that experience different fitness effects for the traded resources or services. Because mutualisms rely on positive feedback between partners, such asymmetries can strongly influence evolutionary outcomes. Differences in fitness effects create divergent selective pressures, shaping trait evolution and determining the persistence of mutualisms. The strength of these effects can also vary depending on the availability of traded resources from other sources. Despite their importance, the evolutionary role of fitness asymmetries in mutualism has received little attention, beyond recognizing that some species may be more dependent on their partners than others. This study investigates how asymmetry in the fitness effects of a traded resource influences the persistence and phenotypic trait evolution of species in multi-mutualist guilds. To test this, we constructed synthetic multi-mutualist communities by combining, reproductively isolated and genetically modified strains of Saccharomyces cerevisiae that engage in a nutritional mutualism by trading adenine and lysine. One guild of four strains cannot produce lysine but overproduces adenine while the other guild cannot produce adenine but overproduces lysine. Lysine overproducers survive periods of low adenine better than adenine overproducers survive low lysine. Over a four-week evolution experiment we observed that strain persistence was strongly influenced by the availability of external resources. Communities in media containing traded resources supported the survival of all strains, whereas obligate conditions led to a significant extinction, especially for adenine overproducers. We observed distinct evolutionary trajectories of traits under obligate versus supplemented conditions. Phenotypic assays revealed that costs and benefits evolved differently depending on the essentiality of the traded resource and nutrient supplementation. These results demonstrate that asymmetries in the fitness effects of traded resources can influence evolutionary outcomes, species persistence, and community stability in multi-mutualist communities.

Sugar-sweetened beverage consumption, waist-to-height ratio and psychological symptoms among Chinese adolescents

Identifying chemicals associated with irritable bowel syndrome by integrating a transcriptome-wide association study with chemical-gene-interaction analysis

Background Irritable bowel syndrome (IBS) is a prominent functional gastrointestinal disorder, yet the precise causes and mechanisms behind it remain largely unclear. Numerous environmental compounds have been associated with the intestinal health of individuals suffering from IBS. This study sought to explore the impact of environmental chemicals on the condition of IBS. Methods We analyzed genome-wide association study (GWAS) data comprising 455,321 individuals of white British descent, among which 28,518 individuals with IBS underwent transcriptome-wide association study (TWAS) analysis. Reference gene expression data were sourced from tissues including the small intestine, transverse colon, sigmoid colon, whole blood, and peripheral blood. Results Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted utilizing the significant genes identified through TWAS. Additionally, protein-protein interaction network analysis was performed using the STRING database to elucidate the functions of the proteins encoded by these genes. Furthermore, chemical-related gene set enrichment analysis (CGSEA) was employed to explore the associations between environmental chemicals and IBS. In total, TWAS identified 33 significant genes ( P FDR  < 0.05), while CGSEA revealed 112 chemicals significantly correlated with IBS ( P FDR  < 0.05, |NES| > 1). Both TWAS (targeting genetic influences) and CGSEA (focusing on environmental influences) were instrumental in pinpointing chemicals associated with IBS. Conclusion The results of this study enhance our comprehension of the genetic and environmental determinants associated with functional gastrointestinal disorders.

A hybrid PSO–FPA metaheuristic algorithm for ultra-low sidelobe and high-directivity synthesis of concentric circular antenna arrays for advanced radar applications

Abstract This paper introduces a novel hybrid PSO–FPA metaheuristic algorithm that integrates the global exploration capability of the Flower Pollination Algorithm (FPA) with the adaptive convergence and dynamic search behavior of Particle Swarm Optimization (PSO) for the efficient synthesis of Concentric Circular Antenna Arrays (CCAAs). By embedding PSO’s inertia-weighted velocity update and acceleration coefficients into FPA’s global and local pollination phases, the proposed approach establishes a self-adaptive optimization framework capable of achieving an effective trade-off between global exploration and local exploitation. The algorithm is applied to the simultaneous optimization of excitation amplitudes and ring radii under four design configurations, considering both with and without central element scenarios. The optimization objective focuses on minimizing Side Lobe Levels (SLL) while maintaining high directivity and narrow Half-Power Beamwidth (HPBW). Comprehensive numerical simulations demonstrate that the proposed hybrid PSO–FPA algorithm outperforms conventional metaheuristics—including FPA, PSO, Artificial Bee Colony (ABC), and Whale Optimization Algorithm (WOA)—in terms of sidelobe suppression, convergence speed, and pattern symmetry. The hybrid method achieves a minimum SLL of − 45.01 dB, representing an improvement of approximately 38–42% over traditional techniques, and enhances beam symmetry and directivity by 24–28%, achieving up to 13.14 dB of main-lobe gain with minimal beamwidth degradation. Moreover, the joint optimization of amplitudes and ring radii yields a balanced radiation performance, characterized by focused beams with sidelobes below − 45 dB and computation times under 12 s per design. The results confirm that the proposed PSO–FPA metaheuristic delivers superior sidelobe suppression, enhanced beam control, and rapid convergence, making it a robust and scalable optimization tool for next-generation antenna synthesis in radar, wireless communication, and smart sensing systems requiring precise directional control and interference mitigation.

Informal institutions and corporate carbon emissions: Evidence from China’s listed companies

This research explores the connection between religious culture and carbon emissions through the lens of informal institutions, offering valuable insights into the shift to a green economy in China. The research sample comprises listed enterprises from 2010–2020 to investigate the influence of indigenous religious culture, represented by Buddhism and Taoism, on the corporate carbon footprint. The results reveal that religious culture has a notable inhibitory effect on corporate carbon outputs. Through a suite of robustness checks, the findings remain in line with the benchmark results. Heterogeneity analysis reveals that the effect of religious culture on corporate carbon emissions is more noticeable in economically thriving areas, state-owned companies, polluting-intensive companies, capital-intensive companies, and high-tech companies. Mechanistic tests suggest that religious culture mainly reduces corporate carbon emissions through three pathways: promoting corporate social responsibility, alleviating corporate financing constraints, and increasing corporate green innovation. Research has shown that both formal institutions and foreign cultural impacts weaken the beneficial impact of indigenous religious culture on corporate carbon reduction but do not eliminate its effect. This study provides practical guidelines and theoretical references for enterprises and policy-makers in addressing climate change and achieving sustainable development.

Single-cell transcriptomics identifies fibroblast associated immune heterogeneity and prognostic signatures in bladder cancer

Abstract The immune microenvironment and prognosis of bladder cancer (BLCA) remain ongoing challenges in its treatment. This study aimed to establish predictive prognostic indicators and investigate the immune microenvironment to enhance clinical treatment strategies. A single-cell transcriptional atlas was constructed using single-cell RNA-seq data from patients with bladder cancer, focusing on fibroblast-related gene expression, intercellular communication, metabolic pathways inferred by single-cell flux estimation analysis, and transcription factor networks. Fibroblast-associated prognostic gene signatures were validated using data from The Cancer Genome Atlas, and a prognostic model was developed to stratify patients with bladder cancer into high- and low-risk groups. Analysis of three para-carcinoma single-cell samples revealed the presence of 3,603 fibroblasts and 500 fibroblast-associated marker genes. Notably, key fibroblast-specific transcription factors, including MAF, TWIST1, and TCF21, were identified through SCENIC analysis. The incorporation of comprehensive RNA sequencing data enabled the discovery of prognostic markers associated with fibroblasts. Using this classification model, patient survival could be stratified into high- and low-risk categories based on the model. The results of our study highlight the prognostic genetic signatures associated with the fibroblast component of the immune microenvironment in BLCA, offering preliminary insights into prognostic assessment and potential therapeutic implications.

Data-driven derivation of macroscopisc fundamental diagram from floating car trajectories

This study proposes a novel GPS-based methodology for Macroscopic Fundamental Diagram (MFD) estimation to overcome limitations of fixed detectors and inaccurate penetration rate assumptions. The approach dynamically identifies stop-line positions using spatiotemporal floating car data, calculates maximum queue lengths per signal cycle by combining floating car positions with estimated arriving vehicle lengths, and establishes a speed-based nonlinear model to determine queuing vehicle counts. A dynamic scaling coefficient derived from maximum queue lengths enables assumption-free estimation of total regional vehicles when applied to the floating car population. Validation using Chengdu data demonstrates significant improvements: unary cubic curves achieve optimal fitting for MFD relationships (R 2 up to 0.9157); the HMM-CRF hybrid map-matching algorithm reduces average position error by 29% and intersection mismatch rate by approximately 40%; simulation results show queue length estimation accuracy of RMSE 22.8m and MAPE 18.5%, while MFD estimation error for maximum network flow drops from −17.5% to −3.5%, representing an 80% relative accuracy improvement. The proposed methodology provides robust technical support for urban road network assessment and management by enabling high-precision acquisition of MFDs from floating car data, effectively addressing critical challenges in macroscopic traffic modeling and monitoring. This advancement presents potential value for perimeter control applications and other MFD-based traffic management strategies.

Machine learning framework for mRNA alternative splicing analysis identifies a signature of progression in colorectal adenocarcinoma

Multilevel factors influencing colorectal cancer screening adherence: A systematic literature review

Introduction Colorectal cancer (CRC) is one of the leading causes of cancer-related morbidity and mortality worldwide. Although early detection through screening significantly reduces mortality, adherence to recommended screening remains suboptimal. This systematic review examines the multilevel factors influencing CRC screening adherence, and integrates the findings within the Socio-Ecological Model to provide a structured analytical framework. Methods A systematic search was conducted across PubMed, Scopus, and Web of Science for studies published between 2000 and 2024 that employed multilevel modeling to examine CRC screening behavior. Eligible studies involved average-risk adults and reported both individual- and contextual level determinants of screening adherence. Studies focusing exclusively on clinical predictors or non-screening outcomes were excluded. Risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Tools. A narrative synthesis was performed to identify key individual, interpersonal, community, institutional, and policy-level determinants of CRC screening adherence. Results Nine studies met the inclusion criteria, predominantly from high-income settings. At the individual level, older age, female sex, higher socioeconomic status, and health insurance coverage were consistently associated with greater screening adherence. Community factors such as neighborhood socioeconomic status and healthcare accessibility, influenced screening behavior, while institutional elements included system structures and service availability. Policy-level determinants, such as national health insurance and national screening guidelines, were less frequently examined but demonstrated measurable effects. Despite heterogeneity in populations, synthesis within the Socio-Ecological Model highlighted the interconnected nature of these determinants and emphasized the need for multilevel interventions targeting individual, social, and structural determinants. Conclusion This review emphasizes the importance of addressing CRC screening behavior through a multilevel perspective that incorporates individual, social, and structural determinants. Future research should explore these determinants in low- and middle-income settings and assess the effectiveness of integrated multilevel interventions in improving CRC screening adherence.

An ancient Erysipelothrix rhusiopathiae genome recovered from 1400-year-old human remains in the Northern Caucasus

Scoping review protocol to investigate the experience of intimate partner violence among Black women and children living in the United Kingdom and how domestic violence specialist organisations support them to thrive

Background This protocol focuses on male-perpetrated intimate partner violence and aims to explore how Black women and children are supported to thrive post-intimate partner violence. Although this form of violence affects women across all cultures, Black women remain significantly underrepresented in the existing literature and often face various barriers to disclosure and help-seeking, including patriarchal silencing, immigration status, language issues and unsupportive attitudes of staff. It remains unclear how they transition from surviving to thriving individuals. The scoping review addresses the question: What are the lived experiences of intimate partner violence among Black women and children, and what factors shape their concept of thrivership?. The scoping review explores the knowledge gap in understanding how Black women and children affected by systemic oppression at the intersection of race, immigration and gender, experience thriving after leaving their abusive relationship. It examines existing research to identify key factors that contribute to their thrivership in the UK context. This study protocol provides a detailed outline of the planned methodology for conducting the scoping review. Methods and analysis The scoping review of qualitative evidence will be guided by the five steps of the framework proposed by Arksey and Malley, which include identifying the research question, identifying relevant studies, selecting studies, charting the data, collating, summarising and reporting the results and an additional consultation stage with stakeholders. The results from the scoping review will be presented using the PRISMA Extension for Scoping Reviews (PRISMA-ScR), and the data will be analysed using thematic analysis. The databases searched will be Ovid PsycINFO, Scopus, ASSIA and Web of Science. Ethics and dissemination The anticipated results from the review will help generate new ideas for future studies and inform policy. The findings will be submitted for publication in relevant peer-reviewed journals and presented at conferences and to appropriate stakeholders. No ethics is required as this is a review without human participants being involved. This protocol has been registered on the Open Science Framework (OSF).

Somatotopy-independent reduction of audio-tactile intersensory facilitation for looming sounds within the peripersonal space during arm movements execution

Novel height estimation formula that accounts for the effects of aging based on lumbar length measurements in postmortem CT images

In forensic practice, personal identification using expert testimony is important in unidentified cases, and the height of the deceased is indispensable in identification. Although many height estimation formulas have been reported, height estimates are often too great in the elderly due to age-related shortening. In this study, we address this problem by developing a height estimation formula based on measurement of the lumbar spine, which is thought to shorten with age. To develop a height estimation equation based on lumbar spine length, 183 postmortem CT images taken at our institute from 2016 to 2023 (ages 19–95 years) were prepared for the training dataset and 78 images were used for the validation dataset. In all training dataset cases, anterior margin height (ALV), central height (CLV), and posterior margin height (PLV) of each lumber vertebra and total lumber spine length including the intervertebral disc (LVTL) were measured on 3D CT-reconstructed images. The sum of the ALV (SALV), CLV (SCLV), and PLV (SPLV) of all lumbar vertebrae were calculated by image analysis software, and the correlation between each index and height was examined. As a control, an estimation equation based on sternal length was developed. Significant positive correlations were observed between each of the lumbar spine indices and height, with the PLV of the second lumbar vertebrate (PLV2) (R = 0.710), SPLV (R = 0.762), and LVTL (R = 0.761) showing the strongest correlation. R 2 and standard error of estimation (SEE) were 0.622 and 4.926 cm for PLV2, 0.683 and 4.515 cm for SPLV, and 0.692 and 4.448 cm for LVTL, respectively. Furthermore, estimation equations based on sternal length often estimated higher values for elderly persons and did not take into account the effect of aging, while those based on PVL2, SPLV, and LVTL showed no correlation with age. In conclusion, we consider that our new formula for estimating height based on lumbar spine length, especially on PLV2, SPLV, and LVTL, is not affected by aging.

Identifying the spatio-temporal pattern and driving factors of drought in Fujian Province, China

Body-worn cameras to prevent workplace aggression among ticket inspectors: Protocol for a randomized controlled trial

Background Service and frontline personnel are among the occupational groups with the highest rates of workplace aggression. To address the risk of victimization, various preventive measures have been introduced, with body-worn cameras increasingly adopted. However, evidence of their effectiveness remains inconclusive, with existing studies heavily concentrated in U.S. policing contexts, limiting the generalizability of findings across settings. This study aims to strengthen the evidence base through a randomized controlled trial testing the preventive effect of body-worn cameras among ticket inspectors in Denmark. Methods The trial will involve approximately 60 inspectors employed by three Danish public transport companies. Randomization will occur at the shift level, yielding approximately 3,000 shifts in total. The main analysis compares wearing a camera versus not wearing a camera, pooling data from all three companies. A secondary analysis, restricted to two companies, additionally tests whether a visible badge notifying passengers of potential recording strengthens any preventive effect. In parallel, field observations of inspection workdays will be conducted to gain in-depth insights into how and why cameras may influence interactions. Discussion This study presents a rare randomized controlled trial on the preventive effect of body-worn cameras against workplace aggression outside a U.S. policing context. If the hypothesis of a preventive effect is confirmed, the findings will have direct practical implications for deploying this technology to reduce workplace aggression.

High proportion of pneumonia morbidity and risk factors in sick under-five children, northwest Ethiopia: a health facility based cross-sectional study

How basic public health services shape social integration: Evidence from domestic migrants in China

The demand for and awareness of utilizing resident health services are increasing, yet uneven development across regions has led to uneven population mobility. Against this backdrop, as a crucial safeguard for the healthy lives of the mobile population, basic public health services profoundly influence the quality of life and development opportunities of these populations in urban settings. To elucidate the impact of basic public health services on the social integration of the urban mobile population, this study utilizes data from the China Migrants Dynamic Survey and employs empirical analysis to investigate the multidimensional effects of basic public health services on the social integration of domestic migrants. According to the results of the study, (1) basic public health services contribute to enhancing the social integration of domestic migrant population. This conclusion remains valid after robustness checks, with self-assessment of health playing a mediating role, and (2) the impact of basic public health services on the social integration of the domestic migrant population varies across different urban groups. This study contributes to examining and clarifying the policy effects of basic public health services in promoting the social integration of domestic migrants, providing empirical evidence for using basic public health services as a key lever to facilitate the social integration of domestic migrants.