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Investigations on Ananas erectifolius fiber/sawdust hybrid epoxy composites for sustainable building applications

Abstract This study investigates the mechanical, thermal, morphological, antibacterial, and water absorption characteristics of Ananas erectifolius fiber (AEF) reinforced epoxy composites filled with sawdust particulates, aiming to develop sustainable alternatives to conventional construction materials. Composites were fabricated using the hand layup method followed by compression molding, incorporating sawdust filler contents ranging from 0 to 24 g while keeping the fiber mass constant at 300 g. The composite containing 18 g of sawdust (Sample C3) demonstrated superior overall performance, achieving a tensile strength of 51.09 MPa, flexural strength of 54.98 MPa, impact strength of 14.98 kJ/m², and a Shore D hardness of 51. SEM analysis confirmed strong fiber–matrix interfacial bonding and uniform filler dispersion in the optimized formulation. Thermal assessments showed that Sample C3 exhibited the lowest thermal conductivity (0.72 W/mK), a reduced coefficient of linear thermal expansion (62.1 × 10⁻⁶/°C), and the highest heat deflection temperature (123 °C). TGA revealed enhanced thermal stability, with ~ 18% residual mass at 600 °C. Antibacterial testing against E. coli produced a 26 mm inhibition zone at 100 µg concentration. The water absorption rate remained low at 5.99%, indicating good dimensional stability. The novelty of this work lies in the Integrated valorization of two underutilized bio-wastes Ananas erectifolius fiber and sawdust to engineer a high-performance, eco-friendly hybrid composite tailored for sustainable building applications.

Fluorine-free binder-based dry thick electrodes with Parafilm® M toward sustainable and efficient battery manufacturing

Correction: Modeling dysentery spread and the impact of public awareness on control dynamics

Processing of natural scenes in the human pulvinar

A systems approach for anticipating post-pandemic forecast challenges for pediatric influenza and hospital burden

Reconstruction and analysis of pore blockage fouling in ceramic ultrafiltration membranes through FIB-SEM

Observation of gapless collective charge fluctuations in an Anderson insulating state

Expanded genetic alphabet increases structural and chemical diversity of six-letter DNA for high-affinity protein-targeting aptamers

Assessment of 137Cs, 90Sr, 241Am, 239+240Pu, 3H (HTO, OBT) in the fish from lakes, rivers, and nuclear shell craters of the semipalatinsk test site

Link between the albumin-corrected anion gap and 28 day all‑cause mortality among patients with sepsis complicated with chronic heart failure: A retrospective analysis using the eICU Collaborative Research Database

Background These two conditions, namely metabolic acidosis and hypoproteinemia, are prevalently observed in patients within intensive care units (ICU), particularly those with sepsis complicated with chronic heart failure. Nevertheless, the impact of the Albumin-Corrected Anion Gap (ACAG), an indicator reflecting the above conditions, on such patient mortality requires further investigation. This retrospective cohort study analyzed the significance of ACAG levels in forecasting 28-day all-cause mortality among these patients admitted to ICU. Methods This was observational cohort study on eICU Collaborative Research Database (eICU-CRD) that included in participants with sepsis complicated with chronic heart failure. In the study, we applied several methods such as multivariate Cox regression models and smooth curve fitting plots combined with Kaplan-Meier analysis to investigate how ACAG is correlated with 28 day all‑cause mortality. To explore the results’ stability, subgroup analysis was performed and a forest plot was plotted. Results The final analysis included 713 eligible participants after rigorous screening procedures. The mean level of ACAG was (16.68 ± 5.20) mmol/l. The 28-day mortality rate was 13.60% (97/713) in our study. The multivariate Cox regression analysis revealed a significant association between ACAG (as a continuous variable) and 28-day all-cause mortality, unadjusted model (HR 1.07, 95% CI 1.04–1.11, p < 0.0001), adjusted model 1 (HR 1.08, 95% CI 1.04–1,12, p  < 0.0001), adjusted model II (HR, 1.08 (1.03,1.13), p  < 0.001). After adjusting for all confounding factors (listed in the Model II), the smoothing curves showed a linear relationship. Mortality in such patients gradually increased with the increase of ACAG according to Kaplan-Meier analysis. Subgroup analysis illustrates the stability of the link between ACAG and 28-day mortality in participants with sepsis complicated with chronic heart failure across various subgroups. Conclusions After adjusting for confounding factors, elevated ACAG is positively linked with increased 28-day mortality in patients with sepsis complicated with chronic heart failure.

Blue-light-enhanced interaction between ZmCRY1s and GL2 modulates epidermal wax composition in Zea mays

Analyzing the effects of physical exercise on procrastination among college students using a chain-of-intermediates model

Prevalence of metabolic syndrome among Iranian postmenopausal females: A systematic review and meta-analysis

Introduction This systematic review and meta-analysis aimed to estimate the prevalence of metabolic syndrome (MetS) among Iranian postmenopausal women by addressing inconsistencies in prior research and providing reliable data to inform evidence-based policies for reducing Iran’s MetS burden. Methods Medline/PubMed, Scopus, Embase, Web of Science, Google Scholar, IMEMR, SID, MagIran, ISC, IranDoc/Ganj, Civilica, and RPIS were searched from their dates of inception until April 2025. The quality of the evidence was assessed using the Joanna Briggs Institute critical appraisal checklist. The prevalence of MetS was calculated using the random effects model using Stata version 17. Additionally, sensitivity analysis, subgroup analysis, meta-regression, and publication bias were assessed. The protocol is registered in PROSPERO, number CRD420251039469. Results A total of 24 papers were enrolled, comprising 17,281 postmenopausal participants with a pooled estimate of 58.42% (95%CI: 52.35–64.48, I 2 : 98.59%, Q: 836.97) MetS among Iranian postmenopausal females. The prevalence of MetS was 64.10%, 47.01%, 63.24%, and 50.16% in high-quality, medium-quality, population-based, and institutional-based studies, respectively. Moreover, meta-regression and subgroup analyses demonstrated study quality, study setting, and age as considerable sources of heterogeneity. Conclusion This study highlights a high prevalence of MetS (≈58.5%) among Iranian postmenopausal women, with even greater estimates in high-quality and population-based studies, which underscores a significant public health concern. Given this substantial burden, routine screening for MetS components should be integrated into standard care for postmenopausal women, complemented by public health initiatives targeting lifestyle modifications and broader preventive strategies.

Spatial engineering and d-orbital coupling in axial dual-atom sites for bifunctional oxygen catalysis

Environmental implications and recovery potential of rare earth elements in solid residues from the incineration of sewage sludge

Abstract The presented research aimed to contribute new insights into the chemical composition of solid waste generated during the incineration of sewage sludge, with a particular focus on the occurrence and behaviour of rare earth elements (REEs). In this study, the total content as well as the mobility of rare earth elements (REE) were determined in disposed fluidized beds (FB), sewage sludge ash (SSA), and air pollution control residues (APC) samples obtained from three Polish facilities engaged in thermal sewage sludge treatment. The mobility of REE was assessed using the BCR sequential extraction procedure. Each type of tested material was characterized by different content of REE (SSA > FB > APC). Moreover, statistically significant differences were observed in the REE content in individual waste fractions depending on the sampling places. The mobility of REE in SSA and FB was determined as very low (approx. 98.5% of Sc and > 99% of other REE in the immobile fraction). Based on the results, it can be concluded that the recovery potential of REE from each fraction of the tested waste is negligible. Because of the very low mobility of REE, these elements should not be considered hazardous during FB and SSA management.

Protocol for an undergraduate student-led scoping review of methods used to conduct inclusive focus groups with autistic adolescents

Although focus groups gather early-stage input effectively, our initial literature review found few focus group studies conducted with autistic adolescents (ages 12–19), despite the potential for focus groups to provide a safe, peer-based setting that encourages autistic adolescent engagement in research. Scoping reviews of focus groups for children and people with disabilities exist, but not for autistic adolescents. We aim to fill this gap. Consequently, we plan to conduct a scoping review to identify the methods used to design inclusive focus groups for autistic adolescents. Because few relevant studies exist, we describe steps to search both academic databases and online sources (X, YouTube, Google). We detail how we will leverage our team composition, which is led by a large group of undergraduate students, some of whom are neurodiverse, to enhance the rigor and reproducibility of the scoping review. These steps include accounting for algorithms personalizing search results from online sources and the risk of encountering false information that could cause harm. We will analyze the results to show 1) the extent to which focus groups on autistic adolescents are conducted with autistic adolescents; 2) characteristics of autistic adolescents included in focus groups and underrepresented populations; 3) steps taken to design accessible focus groups for autistic adolescents; 4) which methods were feasible for and acceptable to autistic adolescents. The results of our scoping review will be an important step toward including input from autistic adolescents in the early stages of a project and, more broadly, in the research process.

Bone regeneration using adipose derived stem cell spheroids within 3D printed scaffolds in a rabbit radial defect model

Predictors of self-reported practice in ventilator-associated pneumonia (VAP) prevention among critical care nurses in Sarawak public hospitals

Background and objective Ventilator-associated pneumonia (VAP), a leading cause of ICU mortality, remains prevalent in Southeast Asia, with limited data on critical care nurses’ knowledge and prevention practices in Malaysia. The purpose of this study was to assess knowledge, self-reported practices, barriers, and predictors of VAP prevention among critical care nurses in Sarawak, Malaysia. Methods This cross-sectional study was conducted from July to August 2023 at four public hospitals in Sarawak, Malaysia. Universal sampling was used to recruit nurses from various critical care units managing patients requiring ventilator support. A self-administered questionnaire, consisting of four sections, was employed to gather background information from nurses, assess their knowledge, self-reported practices, and identify barriers related to VAP prevention. Results A total of 298 critical care nurses participated in the study. Of these, 66.8% demonstrated poor knowledge of ventilator-associated pneumonia (VAP) prevention; however, self-reported practices with VAP prevention were significantly high at 76.5%. A Pearson’s correlation test revealed a significant association between the nurses’ knowledge and their self-reported practices related to VAP prevention (p < 0.001). Additionally, multiple regression analyses identified several significant predictors of critical care nurses’ self-reported practices in VAP prevention, including their level of knowledge, type of unit, number of official beds, and sociodemographic factors (p < 0.05). While knowledge positively influenced self-reported practices, its impact was relatively minor compared to sociodemographic factors. Barriers to VAP prevention included nursing staff shortages, forgetfulness, and lack of written protocols. Conclusions The prevention of ventilator-associated pneumonia (VAP) is a multidisciplinary challenge, emphasizing the crucial role of critical care nurses. The findings from this study underscore the necessity for updated, evidence-based interventions that target knowledge gaps, self-reported practices, and barriers to effective VAP prevention.

A zero-shot LLM framework for multimodal grievance classification, urgency scoring, and abuse detection in civic feedback systems

Predicting and explaining life satisfaction among older adults using tree-based ensemble models and SHAP: Evidence from the digital divide survey

As digital transformation continues to penetrate various sectors of society, the issue of the digital divide has become increasingly prominent. Against the backdrop of accelerating population aging, the barriers that older adults face in accessing and utilizing digital information have exerted a profound impact on their quality of life. This study employs tree-based ensemble learning algorithms to predict and identify the key factors of the digital divide that influence life satisfaction among older adults. It also evaluates the predictive performance of these models, thereby providing interpretive insights into the impact of the digital divide on subjective well-being. Using original data from the ‘2023 Report on Digital Information Divide Survey’ conducted by the National Information Society Agency of South Korea, this study constructs an analytical framework that integrates both predictive capability and interpretability. First, the XGBoost model is employed to conduct feature importance analysis, identifying 15 key variables that are highly influential in predicting life satisfaction. These variables are further examined using the SHAP method to provide interpretive insights into their contributions. Subsequently, multiple tree-based ensemble learning algorithms—including Random Forest, XGBoost, LightGBM, and CatBoost—are applied to compare their predictive performance. The results indicate that variables related to technological self-efficacy, digital information literacy, social capital, experience and perception of AI services, and household monthly income are significant predictors of life satisfaction among older adults. Among the models tested, CatBoost demonstrates superior overall predictive accuracy, suggesting its effectiveness in forecasting life satisfaction in this demographic. This study expands the application of machine learning in areas such as aging research and the digital divide and proves the effectiveness of ensemble learning algorithms in predicting digital divide factors that affect the life satisfaction of older adults. This approach provides a novel and powerful methodological for addressing complex social problems. Moreover, the study uncovers the structural configuration of key digital information factors associated with life satisfaction, offering data-driven insights into the mechanisms through which the digital divide influences well-being. These results have practical implications for enhancing digital inclusion, improving adaptability among older adults, and fostering a stronger sense of participation and happiness in digital society.