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The effects of crocin nanoparticle on trace elements levels in paraquat-induced oxidative stress in rat
Enhancing electrical conductivity by defects in metals
Innovative temporal summarization for complex video classification
Menstrual cycle does not change sagittal plane segments coordination variability during deadlift, a nonlinear dynamical analysis approach
The 83 symptoms of tinnitus: Content overlap of commonly used scales for tinnitus burden
Background Clinical management of tinnitus remains challenging due to unclear etiology and diverse phenotypic manifestations. To quantify its associated burden, a variety of patient-reported outcome measures (PROMs) are used. This study aims to comprehensively evaluate the content overlap of items between eight PROMs commonly used in tinnitus research. Methods A two-stage, blinded multi-rater process was used to analyze the content of all 199 items from the International Tinnitus Inventory (ITI), Subjective Tinnitus Severity Scale (STSS), Tinnitus Functional Index (TFI), Tinnitus Handicap Inventory (THI), Tinnitus Handicap Questionnaire (THQ), Tinnitus Primary Function Questionnaire (TPFQ), Tinnitus Questionnaire (TQ), and Tinnitus Reaction Questionnaire (TRQ). The Jaccard Index was used to measure pairwise content overlap between scales. Results The analysis revealed 83 distinct symptoms. “Concentration” was the most frequently captured symptom (in seven scales), whereas 41 symptoms (49.4%) were unique to one scale. The TQ exhibited the highest number of unique symptoms (52.5%), while the THI had the least (4%). The Jaccard Index identified very weak/weak scale overlap between the PROMs. The highest overlap was observed between TFI and THI (0.35). The TFI had the highest mean overlap (0.26), coming closest to the content measured by all other PROMs. Conclusion The results demonstrate high heterogeneity and limited content overlap among tinnitus burden PROMs, similar to other conditions. The findings suggest that tinnitus burden is not measured as a unified construct across questionnaires, thus, researchers and clinicians should carefully consider the specific symptoms measured when selecting instruments for treatment evaluation and comparison.
Copper doped hybrid nanosponges functionalized with Aplysina aerophoba extract for enhanced bioactive performance
Study protocol for a multicenter phase II prospective externally controlled non-inferiority trial of hypofractionated re-irradiation in patients with recurrent high-grade glioma (RISinG)
Background Reirradiation is a widely accepted option for second-line treatment in patients with recurrent glioma. However, no standard radiation regimen has been defined. Hypofractionation is aimed at reducing patients’ burden while maintaining the survival benefit, but may increase the risk of radionecrosis. The primary objective of this study is to determine if reirradiation in just 4 fractions is non-inferior to 10 fractions, regarding survival after reirradiation. Methods RISING trial A was an open label, randomized, non-inferiority, phase III trial with 1:1 allocation for 130 patients among all participating centers but failed to recruit according to planning. RISING trial B will be a phase II, multi-center, clinical trial with a historic control group. The experimental group receives 4 stereotactic fractions. The historic control group has received 10 fractions (standard-of-care) with a biologically equivalent dose on surrounding brain tissue. The primary endpoint is overall survival after reirradiation. The key secondary endpoint is progression-free survival. Other secondary endpoints are recurrence patterns, toxicity (specifically clinically relevant radionecrosis) and anti-edema treatment. We will collect and report on Health-Related Quality of Life (HRQoL) data in the experimental arm. Discussion We expect to demonstrate the non-inferiority and safety of a 4-fraction hypofractionation schedule for reirradiation of gliomas. This schedule may then become a standard-of-care option with minimal burden for patients with recurrent glioma, and limited use of scarce healthcare resources. Trial registration Registered at Netherlands Trial Register (NTR), Trial ID: NL72766.041.20, registered at 07-04-2020, https://www.onderzoekmetmensen.nl/en/trial/52643
Integrated modeling and observational analysis of light-saturated electron transport rates in four C3 species
Interpretable ensemble machine learning framework for cardiovascular disease prediction using EMR data and large language models in Ethiopia
Cardiovascular diseases (CVDs) are leading causes of morbidity and mortality globally, with a growing burden in low- and middle-income countries such as Ethiopia. Early detection is limited by resource constraints, low screening uptake, and a lack of predictive tools tailored to local healthcare systems. This study presents an interpretable ensemble machine learning framework for predicting CVD risk via structured electronic medical record (EMR) data from public hospitals in Addis Ababa. We trained an XGBoost classifier on 20,960 anonymized records containing demographic, clinical, and physiological attributes. Preprocessing involves handling missing values, outlier capping, one-hot encoding, rare-category grouping, and dimensionality reduction. SHapley additive explanations (SHAPs) were used for feature attribution, and a large language model (Gemini) was used to translate SHAP outputs into plain-language narratives to enhance interpretability. The model achieved an accuracy of 0.99, with strong precision (0.99), recall (0.98), and F1-scores across both classes. SHAP analysis identified general_plan, history of present illness (HPI), musculoskeletal system (MSS) and diagnosis as key predictors. The integration of SHAP and LLMs provided transparent, clinician-friendly insights into model outputs, supporting adoption in resource-limited settings. This study demonstrates that combining ensemble learning with explainability techniques can yield highly accurate and interpretable CVD prediction models, offering potential for integration into clinical decision-support systems in Ethiopia.
Health risk assessment of air pollution in Xinjiang, Northwest China
Abstract Air pollution disrupts ecological stability, threatens public health, and increases the risk of associated diseases. This study analyzed the spatiotemporal variations of six criteria pollutants from 2015 to 2024 in Xinjiang and their associated health risks using air quality index (AQI), aggregate air quality index (AAQI) and health risk indices (equivalent health risk–based index (EHAQI) and excess risk (ER)). The study was divided into two periods for comparative analysis: period one (2015–2019) and period two (2020–2024). Results showed that PM₁₀ dominated as the primary pollutant, particularly in Southern Xinjiang. Single-pollutant metrics underestimated combined health impacts of the six pollutants. Environmental policies and lockdowns significantly reduced SO₂ (47.9%), CO (41.7%), PM₂.₅ (19.9%), NO₂ (16.4%), and PM₁₀ (12.0%) compared with Period one. The O₃ growth rate in Northern Xinjiang exceeded that in Southern Xinjiang by 3.7%. Health risk assessments revealed that PM₁₀-driven excess risk (ER) accounted for 80% of the total health burdens in Southern Xinjiang. While in Northern Xinjiang, NO₂ dominated ER, surpassing PM 10 . Spring and winter saw peak EHAQI values, and 36.0% of residents were exposed to “severe” pollution in spring. These findings could provide scientific evidence for PM reduction policies in Southern Xinjiang and pollution-related disease prevention.
Association between physical activity levels and functional recovery, quality of life, and psychological well-being in patients undergoing physiotherapy for musculoskeletal disorders: A cross-sectional study
Physical activity is known to enhance functional recovery and quality of life (QoL) in individuals with musculoskeletal disorders; however, the extent to which varying levels of physical activity influence rehabilitation outcomes—and how demographic and clinical factors moderate these effects—remains inadequately understood. This cross-sectional study investigated the associations between physical activity levels and functional recovery, QoL, and psychological well-being among 286 adults undergoing physiotherapy at a tertiary care hospital in Abha, Saudi Arabia. Participants were classified into low, moderate, or high physical activity groups based on metabolic equivalent of task (MET) hours per week, using the culturally adapted Arabic version of the International Physical Activity Questionnaire – Short Form (IPAQ-SF). Outcome measures included the Patient-Specific Functional Scale (PSFS), the 36-Item Short Form Health Survey (SF-36), and the Hospital Anxiety and Depression Scale (HADS). Multiple linear regression analyses, adjusted for age, gender, socioeconomic status, and comorbidities, revealed that higher physical activity levels were significantly associated with greater functional recovery (β = 0.36, 95% CI: 0.06 to 0.66, p = 0.021), higher QoL (β = 0.42, 95% CI: 0.10 to 0.74, p = 0.011), and lower anxiety (r = –0.41, p = 0.013) and depression scores (r = –0.38, p = 0.022). Moderation analysis indicated that age and comorbidities negatively influenced the relationship between physical activity and recovery outcomes. The full model explained 68% of the variance in functional recovery (R² = 0.68, ΔR² = 0.16 with moderators, p = 0.023). These findings indicate that higher physical activity levels are associated with more favorable rehabilitation outcomes among individuals undergoing physiotherapy for musculoskeletal disorders; however, due to the cross-sectional design, causality cannot be inferred, and the generalizability of these associations requires further investigation.
Development and simulation of a novel mathematical model for an intelligent tire system toward predictive maintenance
Abstract An intelligent tire system autonomously collects and transmits key data on tire and road conditions. As vehicle performance depends on tire dynamics governed by tire–road interactions, accurate tire modeling is essential for optimizing overall performance. Tire deformations significantly influence longitudinal and lateral forces, emphasizing the need for accurate predictive models. The growth of autonomous vehicles (AVs), electric vehicles (EVs), and shared mobility has intensified research on tire–vehicle interactions. EVs, in particular, place special demands on tires due to their heavier battery packs, immediate torque output, and regenerative braking, which can increase tire wear by 20–30% compared to traditional vehicles. Smart tire models have been widely explored to improve vehicle control systems, as embedded sensors provide valuable real-time data on tire behavior under actual driving conditions. These models seek to link measured parameters with physical states to improve prediction accuracy. This paper introduces a physical-analytical approach to describe in-plane tire dynamics by connecting deformations to the forces involved. Tire parameters are determined by aligning radial deformation data from a flexible ring model with strain-based simulations. The proposed mathematical model, based on carcass strain and displacement data, provides a solid theoretical foundation for future intelligent tire research and aids further studies on tire wear, lifespan, mechanical performance, and predictive maintenance. This work offers a theoretical foundation for intelligent tire systems, solutions that significantly reduce computational effort compared to numerical methods, and a potential direct indicator for wear estimation algorithms.
Impact of protected areas on deforestation in Madagascar from 2000 to 2023: A pre-analysis plan
Protected areas are the most prevalent strategy to mitigate biodiversity loss and deforestation, especially in biodiversity hotspots like Madagascar. This pre-analysis plan outlines the data, methods, and identification strategy that will be used to assess the impact on deforestation of terrestrial protected areas created in Madagascar between 2002 and 2022. We will employ coarsened exact matching and difference-in-differences methods to evaluate forest cover loss, leveraging 24 years of high-resolution satellite data. We will incorporate buffer zones to assess spillover and leakage effects. This study addresses limitations of previous ones by combining accurate protected area delimitation and characteristics, a longer temporal coverage, improved characterization of the diverse forest ecosystems, and state-of-the art econometric methods. We will then assess heterogeneity of conservation effects, to better understand the determinants of protected area effectiveness.
Iterative localization method for multiple jammers in UAV collaborative jamming attacks
Exploring physicochemical property and food safety in dried shrimp production: Risks and mitigation strategies
Dried shrimp is a widely consumed aquatic product whose safety and quality depend on various physicochemical and microbiological properties influenced by production practices. This study aimed to assess the physicochemical characteristics and levels of bacterial contamination occurring in small-scale dried shrimp production and to propose practical mitigation strategies. Samples of dried shrimp were collected from Nakhon Si Thammarat and Surat Thani, Thailand and analyzed for moisture content, water activity, pH, salt concentration, and bacterial contamination; in addition, we collected information regarding each farmer’s production practices. The main shrimp species were Parapenaeus longipes and Acetes spp. Only 52.0% of samples met the moisture content standard. Production practices, particularly post-cooking handling, were identified as critical points for re-contamination and/or regrowth. While cooking reduced bacterial loads, subsequent handling stages led to significant increases in bacterial loads, emphasizing the need for improved hygiene during post-cooking handling. Average reported measurements from all shrimp species were salt (7.8 ± 5.3 g/100g), moisture (31.2 ± 11.1 g/100g), water activity (0.8 ± 0.09), and pH (7.9 ± 0.33). High overall prevalence of total coliforms (94.0%), fecal coliforms (41.3%), and Escherichia coli (26.4%) were found, with exceedances of standard limits at 71.6%, 19.4%, and 26.4%, respectively. Salmonella enterica subsp. enterica (1.0%; n = 2/201), Staphylococcus aureus (2.5%; n = 5/201), and Vibrio cholerae (2.0%; n = 4/201) were identified at low frequencies. The serovars of Salmonella were Tallahassee and Mount Pleasant. The mean microbial load of S. aureus samples was 4.2 logCFU/g, and all these samples exceeded the microbiological limit of 100 CFU/g set by the Thai Agricultural Standard. Negative binomial regression identified pH, sampling location, shrimp color, and fecal coliforms as predictors of E. coli levels. This study highlights the importance of microbial safety and quality assessment in dried shrimp production, emphasizing the need for stringent hygiene controls and critical control point management to prevent post-processing contamination and to ensure high product quality.
The extended TODIM method under q-rung orthopair fuzzy environment and its application to multi-path parallel transmission in mobile networks
Professional dancers’ beliefs and conceptualisations of their posture and movement: A qualitative research study
Many issues are unresolved regarding posture and movement and their utility as target for rehabilitation and function. As movement experts, elite ballet and contemporary dancers could provide insights regarding whether some postures/movements are ideal, if and how they can be changed, and valuable insight into the apparent paradox between their “exceptional” posture/movement quality and high incidence of musculoskeletal injury and pain. This study aimed to understand dancers’ beliefs and conceptualizations about posture and movement, consider how this relates to theories of motor control and learning, and whether this has relevance for rehabilitation and injury prevention in non-dancers. This study implemented an inductive qualitative design. Thirty-six participants (12 males, 24 females) with 6.9 ± 4.3 years of experience as professional dancers (ballet or contemporary dance) participated. Data were collected via semi-structured focus group interviews. Thematic analysis used an inductive approach to categorise and structure data into codes, themes and sub-themes. Themes were refined and finalised after multiple team discussions. Four themes emerged: (i) Posture being conscious or subconscious, (ii) Posture in “dancer mode” and “non-dancer mode”, (iii) Posture as an ideal, (iv) Adjustment and improvement of posture. Each theme was summarised by a series of sub-themes. Dancers have a detailed and multifaceted understanding of posture and movement. They reconcile the contradiction between good posture and movement and injury by the extreme demands required to achieve aesthetics of dance. Some of their perspectives have potential relevance in injury prevention and rehabilitation in the general population.
An innovative power converter based technique for on-site photovoltaic I-V characterization under natural irradiance
Opportunities and challenges of implementing an urban primary healthcare delivery model: Programmatic lessons from Aalo Clinic, Bangladesh
Background Rapid urbanization in Bangladesh has strained the healthcare system, leaving urbanites underserved in primary healthcare (PHC). To address this gap, a UNICEF-supported Government of Bangladesh initiative introduced the Aalo Clinic model to expand access to affordable PHC. This study explored implementation challenges and opportunities of the Aalo Clinic model from a programmatic perspective for strengthening urban PHC delivery. Methods The opportunities and challenges of implementation were explored through qualitative research conducted between June 2022 and May 2023 in six Aalo Clinic intervention areas across four city corporations in Dhaka, Bangladesh. Twenty-four in-depth interviews with service providers and eighteen key informant interviews with clinic-in-charges, community leaders, scheme operators, and policymakers were conducted, along with periodic observations at clinics. A thematic analysis was performed to analyze the data. Results Three core themes evolved from the analysis – technical, administrative, and financial opportunities and challenges. Aalo Clinic’s integrated digitalized health platform reported to streamline operations through medical documentation and real-time monitoring. Initiatives like prescription audits and client feedback systems reported to promote rational prescribing and delivering quality care. However, key challenges included limited choice of medicine, interrupted internet connection, high patient flow, and longer waiting times. Despite challenges policymakers mentioned Aalo Clinic’s potential to integrate into the national health system, highlighting the need for coordinated efforts to overcome obstacles. Financial sustainability, however, hinges on the model’s integration into the government system and the provision of public funding to support its implementation. Conclusion The study underscores the importance of addressing implementation challenges while capitalizing on opportunities to scale up the Aalo Clinic model. Recommendations include implementing structured monitoring, ensuring need-based medicine supply, fostering collaboration with the government for referrals, and facilitating cross-learning among urban PHC facilities. By addressing implementation challenges and strengthening multisectoral collaboration, the Aalo Clinic model shows potential to contribute to improved access to quality PHC in urban settings, in line with the broader vision of health for all.