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A ZKP-based anonymous biometric authentication scheme for the E-health systems

The widespread adoption of e-health systems raises critical concerns regarding data privacy and network security. Ensuring secure and reliable data sharing between patients and healthcare professionals remains a significant challenge. To address this, we propose a novel anonymous authentication scheme tailored for e-health environments, integrating zero-knowledge proof (ZKP) with multimodal biometrics. Our key contributions are as follows: (1) applying the Pedersen vector commitment algorithm to construct a biometric-based ZKP scheme, thereby ensuring enhanced security and privacy-preserving authentication; (2) utilizing multimodal cancelable biometrics generate (MCBG) technology, integrating fingerprint, face, and iris modalities to strengthen the security of the verification process; and (3) providing a detailed security analysis that demonstrates our scheme meets essential security requirements, including anonymity, authenticity, unlinkability, forward security, and resistance to replay attacks. Experimental results demonstrate stable proving and verification time of approximately 78 ms and 140 ms, respectively, regardless of the proof range, validating its efficiency and practicality for secure authentication in e-health systems.

Publisher Correction: Unveiling the antiviral inhibitory activity of ebselen and ebsulfur derivatives on SARS-CoV-2 using machine learning-based QSAR, LB-PaCS-MD, and experimental assay

Piriformospora indica culture filtrate and cell extract induce chicoric acid production in Echinacea purpurea hairy roots

Echinacea purpurea (L.) Moench, commonly known as purple coneflower, is a significant medicinal plant renowned for its therapeutic properties, which are attributed to various phytochemical compounds, including caffeic acid derivatives (CADs). Chicoric acid is one of the CADs that has important immunostimulatory properties. This study employed a hairy roots (HRs) culture and an elicitation system to enhance the production of chicoric acid in E. purpurea. HRs cultures were established, and different concentrations (0, 1.25, 2.5, 5, and 10% v/v) of elicitors derived from Piriformospora indica culture filtrate (CF) and cell extract (CE) were added at two time points during the HRs growth period (on days 24 and 26). The effects of these treatments on the growth of HRs, chicoric acid production, and the expression of genes involved in the chicoric acid biosynthesis pathway were investigated. The highest dry weight of HRs (2.19 g/L, 1.36% higher than that in the control) was achieved in the HRs culture treated with 5% CF on the 24th day. In contrast, 5 and 10% (v/v) of P. indica CE, regardless of addition time, significantly decreased HRs growth compared to the control. The maximum production of chicoric acid (15.52 mg/g DW) was recorded after 48 h in the HRs culture treated with 5% CE on day 24, representing a 2.6-fold increase compared to the control (5.95 mg/g DW). Additionally, adding 2.5% CF to the HRs culture on day 26 resulted in a 2.3-fold increase compared to the control (13.5 mg/g DW) in chicoric acid biosynthesis. Real-time PCR assays revealed that the expression levels of the genes PAL, C4H, 4CL, C3H, and HCT were significantly upregulated after 3 and 12 h of elicitation with CE and CF. The highest gene expression was recorded for the C4H and PAL genes, 3 h after elicitation by CE (29.64 and 26.2-fold increases compared to the control culture). In contrast, the expressions of the 4CL and C3H genes peaked 12 h after elicitation with CF. The expression of the HCT gene also reached its highest level after 12 h of CE elicitation. Consistent with the chicoric acid production results, CE was found to be a more effective elicitor for inducing gene expression in the chicoric acid biosynthesis pathway. Overall, these findings indicate that HRs cultures and elicitors derived from P. indica are promising strategies to enhance chicoric acid production in E. purpurea (L.).

Diversity and antibiotic susceptibility profiles of bacterial isolates from wound infections in patients at the surgical unit of Kisii teaching and referral hospital, Kenya

Antimicrobial resistance (AMR) poses a growing threat to global health, with wound infections serving as significant reservoirs for multidrug-resistant bacteria. Understanding the socio-demographic, clinical, and microbiological characteristics of wound infections is critical for effective intervention strategies in resource-limited settings. Thus, this study aimed to evaluate the diversity, bacterial profiles, and resistance patterns of wound infections at Kisii Teaching and Referral Hospital. To do this, a total of 118 bacterial isolates from wound swabs were collected from 149 patients who met the eligibility criteria, from May to November 2024. These samples were cultured and analysed using standard microbiological techniques and antibiotic susceptibility testing according to the Clinical and Laboratory Standards Institute guidelines. Resistance genes associated with Vancomycin resistance in Staphylococcus aureus and Staphylococcus xylosus were also investigated using polymerase chain reaction (PCR) with appropriate primers and agarose gel electrophoresis. The results revealed a predominance of male patients (n = 79; 53.02%), avulsions (n = 50; 34.00%), and wounds on lower limbs (n = 63; 42.29%). Escherichia coli (n = 33; 27.97%), Enterobacter gergoviae (n = 20; 16.95%), Staphylococcus aureus (n = 18; 15.25%), and Staphylococcus xylosus (n = 18; 15.25%) were the most frequently isolated pathogens. Alarmingly high resistance rates were observed against ACCESS antibiotics, including Cotrimoxazole-Trimethoprim (n = 114; 97%), Ampicillin (n = 109; 92%), and Streptomycin (n = 100; 85%). Resistance to Watch and Reserve antibiotics, including Vancomycin (n = 11; 29%) and Ceftriaxone (n = 27; 33%), was also documented, particularly among Gram-positive isolates such as Staphylococcus aureus and Gram-negative pathogens like Pseudomonas aeruginosa. Resistance genes (VanA, VanB, VanC) were detected in S. aureus and S. xylosus, underscoring the role of genetic mechanisms in resistance propagation. These findings highlight the critical need for targeted antimicrobial stewardship programmes and strengthened infection prevention measures in high-burden hospital settings, such as Kisii Teaching and Referral Hospital. This study underscores the importance of local resistance data in guiding empirical therapy and informs policies to mitigate AMR in resource-limited contexts. Moreover, enhanced surveillance and research into alternative therapies are crucial to safeguarding the efficacy of life-saving antibiotics and improving patient care outcomes.

Unveiling the spectrum of Arabic offensive language: Taxonomy and insights

This paper presents a novel taxonomy designed to classify offensive language in Arabic, filling a notable void in existing literature primarily concentrated on Indo-European languages. Our taxonomy delineates offensive language into seven distinct levels, comprising six explicit levels and one implicit level. Drawing inspiration from the simplified offensive language (SOL) taxonomy outlined in prior work, we adapted it to accommodate the intricacies and linguistic richness of Arabic. In our study, we analyzed existing datasets containing offensive language in Arabic, examining the range of annotations employed within these datasets. This exploration allowed us to gain insights into the diversity of offensive language instances and the methodologies used for their annotation, thereby informing the development of our streamlined taxonomy for categorizing such expressions. Initial examination of datasets uncovers compelling trends and distributions, emphasizing the intricate and distinct nature of offensive expressions in Arabic. We have also analyzed the performance of pre-trained and fine-tuned Arabic transformer offensive language detection models on these datasets. Our results underscore the importance of acknowledging linguistic and cultural diversity in the study and mitigation of online abusive language. We posit that our refined taxonomy and accompanying dataset will be pivotal in advancing research across Semitic languages, including sociocultural studies, natural language processing, and linguistic analyses.

Integrated multi-omics analysis and predictive modeling of heart failure using sepsis-related gene signature

Background Heart failure (HF) is characterized by complex molecular alterations, and recent studies suggest a potential role for sepsis-related genes in cardiovascular dysfunction. This study aimed to develop a predictive model for HF based on sepsis-related gene signatures. Methods Three sepsis-related datasets (GSE65682, GSE54514, and GSE95233) were analyzed to identify differentially expressed genes (DEGs) following batch effect correction using the ComBat algorithm. With the use of elastic net regularization and the glmnet package in R, Lasso Cox regression was employed to screen out gene signatures. A predictive model was developed based on the expression of each gene signature and the co-efficient values. In addition, the predictive model was validated on independent HF datasets (GSE57345, GSE141910, and GSE5406). Model performance was assessed through receiver operating characteristic (ROC) analysis and AUC values of each gene signature, and immune infiltration was evaluated using CIBERSORT, IPS, and xCell. Sepsis models of C57BL/6 mice were established by cecal ligation and puncture (CLP). Results We identified 340 up-regulated and 333 down-regulated sepsis-related genes. The predictive model, incorporating six key genes, demonstrated superior performance compared to individual genes across both training and validation datasets with the AUC value of the risk score above 0.9, significantly higher than that of a single gene. Immune infiltration profiles differed significantly between HF patients and controls, with more pronounced alterations observed at higher risk score levels. Finally, the expression of six key genes in sepsis models was confirmed to be consistent with our prediction. Conclusion The model constructed through sepsis-related characteristic genes provides a highly advantageous method for predicting HF, and the characteristic genes we have screened may be potential biomarkers for predicting HF. This model has potential application value in early diagnosis and risk stratification, which can help improve the clinical management of heart failure and provide new ideas for preventing HF.

Genetic diversity and phylogenetic relationships of Calotes and Uromastyx in the Cholistan Desert, Pakistan, based on COI gene analysis

The Cholistan Desert of Pakistan harbors unique reptile diversity, including ecologically significant agamid lizards of the genera Calotes and Uromastyx, yet their genetic structure remains poorly understood. This study presents the first mitochondrial DNA barcode assessment of these taxa in the region, analyzing 658 bp of the cytochrome c oxidase I (COI) gene from 19 specimens collected across seven desert sites. We employed a combination of distance-based (p-distance, K2P) and phylogenetic methods (Maximum Likelihood, Bayesian Inference) to evaluate genetic diversity and evolutionary relationships. Results revealed pronounced divergence between genera (24–30% K2P distance), with Uromastyx populations showing remarkably low intraspecific variation (0–1%), contrasting with higher diversity in Calotes (0–14%). Demographic analyses suggested stable populations (Tajima’s D = 0.93, p > 0.10), though haplotype networks indicated limited gene flow (Nm = 0.12). Our findings: (1) provide the first genetic baseline for these ecologically important desert lizards, (2) identify Uromastyx as potentially more vulnerable to genetic erosion, and (3) demonstrate the utility of COI barcoding for rapid biodiversity assessment in understudied arid ecosystems. The study highlights the Cholistan Desert as an evolutionary significant zone for agamid lizards while underscoring the need for integrated taxonomic approaches to address potential cryptic diversity. All sequence data are publicly available (GenBank PQ896696-PQ896705) to support future conservation genomic studies.

The characteristics of latent tuberculosis infection and its influencing factors in hospitalized patients in Suzhou, Jiangsu, China

Objective China is a country with a high burden of tuberculosis (TB). It is vital to reduce the number of new cases of TB in China. We aimed to examine and investigate the distribution and affecting factors of the latent tuberculosis infection (LTBI) detection rate in hospitalized patients in Suzhou, Jiangsu Province. Methods We analyzed the link between LTBI and patients’ information, disease diagnosis, and blood routine indices of hospitalized patients at the Fifth People’s Hospital in Suzhou from January 1, 2018, to March 31, 2024. Results Results indicated that of the 6692 patients included in the study, 39.05% of them were diagnosed with LTBI. Multivariate analysis revealed that sex, AIDS status, testing time, age, lymphocyte count, and neutrophil count were influencing factors for the detection of LTBI ( p < 0.05). However, hepatitis B, diabetes, hypertension, silicosis and monocyte count did not significantly influence LTBI detection. Conclusion Sex, AIDS status, testing time, age, lymphocyte count, and neutrophil count were influencing factors for the detection of LTBI.

Reliability and validity of mental health measurement of young people in a Chinese urban context

Globally, there is increasing attention on mental health promotion for young people because of its great public health and social significance. The scarcity of suitable mental health measures for young people underscores the urgent need for tailored interventions to address their unique mental health challenges. This study explores the reliability and validity of the self-rated mental health measurement scale (SRMHS) for assessing Chinese youth mental health in an urban context in China, addressing a critical research gap in culturally and contextually appropriate mental health measurement instruments. The study responds to the global demand for valid and reliable health data to support mental well-being initiatives. Utilizing a sample of 3,279 participants aged 14–35 years, the study employed rigorous statistical analyses, including Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and tests for convergent, discriminant, and concurrent validity, to evaluate the scale’s psychometric properties. Results confirm a three-dimensional structure of the mental health scale, encompassing positive emotion, psychosocial symptoms and negative emotion, and cognitive function, demonstrating good internal consistency, reliability, and validity. Subgroup consistency categorized across gender, age, and social identity was examined, and the significant correlations between mental health scores with relevant psychological outcomes showed good concurrent validity, indicating the effectiveness of SRMHS in capturing a broad spectrum of psychological states relevant to youth development. Findings highlight the importance of a multidimensional approach to mental health assessment, reflecting global advocacy for recognizing mental well-being as not merely the absence of illness, but also the presence of positive psychological states. This study significantly contributes to the field by providing a scientifically robust and culturally sensitive tool for assessing youth mental health in China, and promotes a more inclusive and holistic approach to mental health research and practice globally. The results of this study could benefit policy-making, targeted interventions, and the overall improvement of youth mental well-being.

Research on the impact of sports event image on tourism loyalty in heritage sites: An empirical study based on the Yongding Tulou marathon

Heritage tourism related to sports events is widely recognized as a new paradigm of integration between culture, sports, and tourism. By combining sports events with world heritage sites, it attracts more tourists to pay attention to world heritage, serving as an important practice for the protection and sustainable development of world cultural heritage. However, the academic community still lacks discussions on its composition and impact effects. This study, based on the event of the 2022 Yongding Tulou Marathon in Fujian, constructs a multiple impact model of sports event events on tourist loyalty to heritage sites, integrating social and market perspectives. It follows the logic of “recognition-emotion-behavior” and uses PLS-SEM for empirical testing. PLS-MGA is conducted based on tourist demographic characteristics to explore the impact of different consumer group characteristics on the influencing paths. The results show: (1) The image of sports events is an important factor affecting tourist loyalty and the image of heritage sites, but it is difficult to directly influence tourists’ sense of place attachment; (2) The image of heritage is more deeply rooted in the heart, prompting tourists to develop loyalty and attachment to the heritage site, while attachment can also directly stimulate tourist loyalty; (3) The image of sports events can enhance the cognitive image of heritage through positive tourist experiences, thereby improving tourist loyalty to the heritage site. Additionally, the image of sports events can also stimulate tourists’ heritage image and sense of place attachment, ultimately strengthening loyalty to the heritage site; (4) Demographic variables such as gender, age, frequency of participation, and monthly running distance are key factors affecting the mechanism through which the image of sports events influences destination loyalty. The research findings not only reveal the theoretical process of how the image of event events influences multiple behaviors of tourists at heritage sites but also provide a comprehensive perspective and methodological tools for the study of sustainable development of world heritage sites. They also offer theoretical references for managers to effectively leverage the positive effects of developing sports tourism projects in heritage tourism destinations.

A comprehensive evaluation of cardiac amyloidosis epidemiology and diagnostics in French Guiana

Background Cardiac amyloidosis (CA) is a potentially fatal systemic disease that has received increasing attention in recent years. However, there is no data on its epidemiology in French Guiana. This study aimed to evaluate the epidemiological characteristics of cardiac amyloidosis and describe the regional diagnostic pathways in French Guiana. Methods We performed a multicenter retrospective study of Guianese patients with confirmed or suspected cardiac amyloidosis who were followed up in hospitals in French Guiana by private cardiologists. Results A total of 47 patients were included. The study population was predominantly male (n = 29, 61.7%). The mean age of the population was 72.8 years (SD = 12.2). Most patients were from the island of Cayenne (n = 34, 72.3%), had at least one cardiovascular risk factor (n = 32, 68.1%), and more than half had extracardiac amyloid involvement (n = 25, 53.2%). More than half of the patients were hospitalized at a reference center outside French Guiana (29, 61.7%), mainly at Henri Mondor Hospital (n = 20, 69%) and Martinique (n = 6, 20.7%). Bone scintigraphy was performed in 27 patients (57.5%) and hyperfixation was observed in 25 patients (93%). Anatomopathological examinations were performed in 33 patients (70.2%). Amyloid typing of the biopsied tissue revealed predominantly ATTR (n = 14, 62.6%), AL amyloidosis (n = 1, 4.5%), and AA amyloidosis (4.5%). Among the ATTR amyloidoses, we found mainly ATTRm (n = 22, 75.8%). Genetic mutation testing was performed in approximately half of the patients (n = 25, 51.1%), mostly for the VAL122ILE mutation (n = 21, 84%), and in one case for the IL107VAL mutation (4%). Of the patients with ATTR amyloidosis, 22 (75.9%) were treated with tafamidis. Of the included patients, 18 (38.3%) died. The median overall survival (OS) was 38 months. Survival analysis from the date of diagnosis showed a probability of survival at 30 days, one year, 1.5 years and 4 years of 97% (95% confidence interval [CI]: 90–100), 68% (95%CI 55–84)), 64% (95%CI 51–79)), 32% (95%CI 29–41)), respectively. Conclusion This study provides the first information on the diagnostic pathway for cardiac amyloidosis in French Guiana. The increasing proportion of undiagnosed patients has led us to create a French Guianese Amyloidosis Team to simplify the diagnostic pathway by focusing on cardiac MRI and biopsy, which can be performed locally. This is particularly important, as current and future therapeutic advances mean that more effective treatments are on the horizon.

Prediction of future aging-related slow gait and its determinants with deep learning and logistic regression

Background Identification of accelerated aging and its biomarkers can lead to more timely therapeutic interventions and decision-making. Therefore, we sought to predict aging-related slow gait, a known predictor of accelerated aging, and its determinants. Methods We applied a deep learning neural network (NN) and compared it to conventional logistic regression (LR) analysis. We incorporated 1,363 participants from the Baltimore Longitudinal Study of Aging to predict current and future slow gait at 6-year and 10-year follow-up using two clinically-relevant cut-points. Results Our NN achieved a maximum sensitivity (specificity) of 81.2% (87.9%), for a 10-year prediction with 0.8 m/s cut-point. We demonstrated the necessity of class balancing and found the NN to perform comparably to or in some cases, better than, LR which achieved a maximum sensitivity and specificity of 84.5% and 86.3%, respectively. Sobol index analysis identified the strongest determinants to be age, BMI, sleep, and grip strength. Conclusions The novel use of a NN for this purpose, and successful benchmarking against conventional techniques, justifies further exploration and expansion of this model.

The effects of rifaximin and lactulose on the gut-liver-brain axis in rats with minimal hepatic encephalopathy

Background The principal therapeutic agents for minimal hepatic encephalopathy (MHE), which focus on the modulation of the gut microbiota, include lactulose and rifaximin; however, the precise mechanisms through which they operate remain unclear. Aim This study aimed to investigate the effects of rifaximin and lactulose on the gut-liver-brain axis in a rat model of MHE and to clarify the underlying mechanisms involved. Methods A rat model of MHE was established by subcutaneous carbon tetrachloride (CCl4) injection. The Morris water maze (MWM) test was used to assess cognitive function in MHE rats following treatment with rifaximin and lactulose. Serum and cerebrospinal fluid ammonia levels were quantified, along with measurements of portal lipopolysaccharide (LPS) and various serum inflammatory markers. Furthermore, the expression of Toll-like receptor 4 (TLR4) in the liver was examined by histopathological evaluation. Additional analyses included the detection of tight junction proteins in the intestinal mucosa as well as colon fecal 16S rRNA sequencing and metabolic pathway assessments. Results Both rifaximin and lactulose were effective in reducing ammonia concentrations in MHE rats and ameliorating cognitive deficits, although they exhibited a minimal impact on hepatic function. Post-treatment assessments revealed significant reductions in portal LPS, serum interleukin-1β (IL-1β), and tumor necrosis factor-α (TNF-α). The expression of TLR4 in the liver and hepatic inflammatory infiltration were notably diminished. Rifaximin administration led to increased occludin expression in the intestinal tissues of MHE rats. Despite no significant alterations in the diversity or composition of the gut microbiota, metabolic pathway analyses indicated a downregulation of glycometabolism pathways following treatment. Conclusion Rifaximin and lactulose may enhance cognitive performance in MHE rats by modulating gut microbiota metabolism and preserving the intestinal barrier integrity. This modulation is associated with lowered ammonia levels, decreased translocation of LPS to the liver, and reduced inflammatory response, both in the liver and systemically.

How the natural environment affects psychological recovery: A case study in Changsha, China

Previous research has demonstrated the role of urban forest parks in the recovery of human psychological well-being, but there is a lack of explanation of the “how” and “why” of experiences in urban forest parks that promote psychological recovery. This study used the structural equation model (SEM) method to explore the influence mechanism and path of the natural environment on the public’s psychological recovery evaluation in urban forest parks through 485 questionnaires. The study findings reveal the following: (1) In urban forest parks, natural environment perception (NEP) exerts significant positive effects on leisure involvement (LI), place attachment (PA), and restorative environment perception (REP). While NEP does not directly influence psychological recovery evaluation (PRE), its effects are mediated through four distinct pathways: First, via the complete mediation of REP; Second, through the serial mediation of LI and REP; Third, by the chain mediation of PA and REP; Fourth, through the sequential chain mediation of LI, PA, and REP. (2) Leisure involvement significantly enhances both place attachment and restorative environment perception. Additionally, place attachment exhibits a significant positive effect on restorative environment perception, while restorative environment perception demonstrates a robust positive association with psychological recovery evaluation. (3) Demographic variables, including gender, age, and educational level, did not demonstrate significant moderating effects on the structural relationship between natural environment perception and psychological recovery evaluation. The findings may have the potential to offer fresh ideas for enhancing the recovery effect of urban forest parks and have significant implications for their management and sustainable development.

Monetary policy effect on income and wealth inequality mechanism

Since the 1990s, global income and wealth inequality has increased significantly, especially in developing countries, where the imbalance in wealth distribution has become increasingly prominent. This study seeks to thoroughly investigate the effects of expansionary monetary policy on income and wealth inequality, using China as a case study and employing extensive household survey microdata for empirical analysis. The findings indicate that expansionary monetary policy has significantly enhanced overall income and wealth levels. However, when considering the extent of wealth growth, it appears that affluent households have benefited more than their low- and middle-income counterparts, thereby widening the wealth gap. In addition, the real estate market boom played an amplifying role in this process, further deepening the impact of monetary policy on wealth inequality. The findings of this paper provide an important empirical basis for understanding the complex relationship between monetary policy and socio-economic inequality, and provide practical references for policymakers to consider the fairness of income and wealth distribution when formulating relevant monetary policies.

Modulating autophagy in KRAS mutant colorectal cancer using combination of oncolytic reovirus and carbamazepine

Oncolytic reovirus is a potential therapeutic for colorectal cancer patients with a mutant KRAS gene. Reovirus hijacks the autophagic machinery and preferentially induces apoptosis in patients with a KRAS mutation. However, reovirus on its own is not currently a viable treatment and requires enhancement with combination therapies. Carbamazepine, an FDA-approved drug in use for epilepsy, is an autophagy inducer and is used in this study in conjunction with reovirus. The dual treatment was able to reduce cancer viability in mutated KRAS cell lines and was more effective than with reovirus alone. Carbamazepine and reovirus increased autophagy-related proteins and mRNA in mutant KRAS compared to wildtype KRAS which is crucial for autophagy-induced apoptosis. Transmission electron microscopy results show increased autophagosome formation in the combination therapy, as well as a decrease in condensed chromatin. The combination therapy effectively increased the apoptosis induced by reovirus alone and is a viable treatment for patients with a mutant KRAS.

Socioeconomic inequalities in access to maternal healthcare in South-Asian countries: A systematic review

Background Despite numerous efforts, South Asia is the second most leading region for maternal mortality and morbidity. Although there have been notable advancements on this continent, progress in maternal healthcare access has been slow. Inequalities remain in different maternal health services across diverse population groups. The aim of this study is to better understand the socioeconomic inequalities in maternal healthcare access in South Asian countries. Methods Two databases (MEDLINE and Google Scholar) were searched for identifying studies. Studies with data on socioeconomic factors, maternal healthcare, inequality, and South-Asian countries were included. Mixed method appraisal tool was used for quality assessment of the identified studies. Results A total of 55 studies from India, Nepal, Bangladesh, Afghanistan and Pakistan were included in the final analysis. Overall, quantitative study showed that maternal healthcare access is linked to economic status, education, occupation, and women’s autonomy. Qualitative studies demonstrated poverty, lack of awareness of complication and service and inability in decision making on healthcare was the reason for not accessing maternal health care. Significant finding from this review includes effect of education mostly evident after secondary education and paternal occupation was significant rather than maternal occupation. Conclusion Findings of this review indicates a large disparity in access to maternal health care services. Policymakers should create interventions and financial schemes that are tailored to the mothers from low socioeconomic background.

PIFR: A novel approach for analyzing pose angle-based human activity to automate fall detection in videos

Falls pose a significant health risk for elderly populations, necessitating advanced monitoring technologies. This study introduces a novel two-stage fall detection system that combines computer vision and machine learning to accurately identify fall events. The system uses the YOLOv11 object detection model to track individuals and estimate their body pose by identifying 17 key body points across video frames. The proposed approach extracts nine critical geometric features, including the center of mass and various body angles. These features are used to train a support vector machine (SVM) model for binary classification, distinguishing between standing and lying with high precision. The system’s temporal validation method analyzes sequential frame changes, ensuring robust fall detection. Experimental results, evaluated on the University of Rzeszow Fall Detection (URFD) dataset and the Multiple Cameras Fall Dataset (MCFD), demonstrate exceptional performance, achieving 88.8% precision, 94.1% recall, an F1-score of 91.4%, and a specificity of 95.6%. The method outperforms existing approaches by effectively capturing complex geometric changes during fall events. The system is applicable to smart homes, wearable devices, and healthcare monitoring platforms, offering a scalable, reliable, and efficient solution to enhance safety and independence for elderly individuals, thereby contributing to advancements in health-monitoring technology.

Quantitative evaluation and obstacle factor diagnosis of drug regulatory capacity in China

Objective To quantitatively evaluate the drug regulatory capacity in China, aiming to optimize the drug regulatory system, precisely enhance local regulatory effectiveness, and reduce regional regulatory disparities. Methods Using the methods of literature research, expert interviews, investigation and analysis, the quantitative evaluation indicator system of supervision ability was established in all directions; the indicator data were collected and quantified; the indicator weight setting algorithm of the evaluation system was improved and the indicator weight was set by combining AHP and entropy method; the differences among eastern, central, and western provincial-level regions were analyzed by variance analysis; panel data were constructed for spatio-temporal evolution analysis; obstacle factor diagnosis model was used to analyze the obstacle factors. Results The quantitative indicator system was constructed from five aspects: resource acquisition, function performance, learning and development, performance level and Internet application,and the relevant indicators of pharmacovigilance and risk response were analyzed at the national macro level. From the analysis of horizontal comparative variance, the comprehensive indicator and resource acquisition indicator of various provincial-level regions were significantly different(P < 0.05), while others were not significant. From the perspective of dynamic development, except for the performance level in 2022, all provincial-level regions were generally on the rise. From the perspective of obstacle factors, they were mainly in the aspects of learning development and functional performance. Regarding national pharmacovigilance and risk response, despite the synergistic development of all links ensuring drug safety and promoting industrial progress, new issues and challenges demand continuous attention and optimization of the regulatory system. Conclusion There are regional differences in drug regulation in China. A drug regulation capacity improvement plan should be formulated in combination with the characteristics of the city itself and obstacle factors to achieve efficient and balanced development of drug regulation.

Tracing CO2 sources in urban and rural areas characterized by different land-use patterns using carbon isotopes

Air samples were collected from urban and rural areas of Korea with different land-use patterns between October 2022 and April 2023 to identify the sources of atmospheric CO2. We analyzed representative end-members from natural and anthropogenic sources (soil, vehicle exhaust gases, and coal) to determine the CO2 concentrations and carbon isotope compositions of CO2 (δ13C-CO2). Urban samples exhibited lower δ13C values and higher CO2 concentrations than rural samples. Both urban and tunnel samples showing similar slopes and intercepts on the plot of 1000/CO2 vs. δ13C-CO2 likely shifted toward the vehicle exhaust end-member. Among the rural samples, those collected from coastal areas showed trends similar to the urban and tunnel samples, which differed from those collected from inland areas. This suggests that samples from coastal areas were affected by CO2 emissions from coal-fired power plants in the region. In contrast, inland samples showed the highest slope and lowest intercept (i.e., estimated δ13C-CO2 value of −27.0‰), suggesting that natural sources such as soil CO2 dominate the contribution to atmospheric CO2 in inland areas. This study demonstrates that the primary CO2 sources in regions with different land-use patterns can be distinguished using the relationship between atmospheric CO2 concentrations and δ13C-CO2 values.