Browse Articles
Discover research articles across all indexed journals
A three-dimensional nonlinear finite element model for coupled vibration analysis of rotary steerable systems
Advanced receiver design for AF-FD cooperative schemes
The implications of TMSB4X in TIM3 hypermethylation and CD8+ T cell exhaustion in diffuse large B-cell lymphoma
Effects of vocal hygiene education program delivered via videoconference on acoustic and self-reported voice outcomes in Muslim religious officials in Turkiye
Resting HRV predicts cardiac vagal control during stress, not psychological distress
Abstract Resting heart rate variability (HRV) is considered a marker of individuals’ capacity to adapt to environmental demands, although direct empirical evidence remains limited. This study examined whether resting HRV predicts subjective and cardiac reactivity to stress, psychological distress, and emotional regulation (ER) strategies. Eighty-five healthy young adults completed distress (DASS) and cognitive ER (CERQ) scales before undergoing a virtual reality–adapted Trier Social Stress Test. Heart rate (HR), HRV indexed by RMSSD, skin conductance, and subjective stress were recorded across baseline, stress, and recovery. As expected, tasks elicited subjective and autonomic stress responses, and higher resting RMSSD predicted greater RMSSD reactivity and recovery. Contrary to our hypothesis, Bayesian analyses provided evidence for the absence of association between resting RMSSD and HR reactivity and recovery, subjective stress reactivity, psychological distress, and ER strategies. Overall, our findings challenge the view of resting HRV as a reliable index of adaptive capacity to acute stress or of vulnerability to psychological distress. Instead, resting HRV interpretation should be restricted to a predictor of the degree to which the vagal system can modulate cardiac activity. Furthermore, resting HRV’s health relevance is likely more tied to long-term cardiovascular vulnerability in the context of repeated or chronic stress.
Photonic bandgap properties of hyperuniform systems self-assembled in a microfluidic channel
Abstract Traditional self-assembly methods often rely on densely packed colloidal crystalline structures and have inherent limitations in generating materials with isotropic photonic bandgaps (PBG). This study explores the photonic properties of materials structured according to hyperuniform disordered patterns (HUDS) generated via a hydrodynamic process in a microchannel. This research employs simulations to characterize optical bandgaps and determine the minimum dielectric contrast required for PBG formation in structures based on the templates experimentally formed under various conditions during the hydrodynamic process. The optimal conditions in the hydrodynamic process for realizing PBG have been identified. The findings offer a promising avenue for the large-scale production of isotropic photonic bandgap materials.
Impact of nurse-led postoperative education on health outcomes following endovascular aortic repair: a randomized trial
Abstract The purpose of this randomized controlled clinical trial was to investigate the health effects of an education-based intervention performed at a nurse-led clinic, for patients who underwent endovascular treatment for abdominal aortic aneurysm. Fifty-four adult patients were randomized to the intervention group (n = 26) or the control group (n = 28). The control group received standard care, and the intervention group received standard care alongside two consultations at a specialist surgical nurse-led clinic. The consultations focused on individual motivational support and education about abdominal aortic aneurysm disease. Data was collected prior to surgery (baseline) and at one, six, and 12 months postoperatively for each group. Outcomes of interest included participants’ responses to the Health Education Impact Questionnaire, responses to the EuroQol Five Dimensions Questionnaire, and responses to four complementary items specific to the scope of this study. Both groups reported overall high ratings of perceived health throughout the study period. While there were no statistically significant differences between the two groups, the control group showed a substantial improvement in perceived understanding of their diagnosis over time. This randomized controlled trial did not find any significant health benefits as compared to standard treatment. Trial registration ClinicalTrials.gov (19/05/2025 NCT06986252). Retrospectively registered.
Impacts of structural and soil parameters on the seismic response of neighbouring buildings: a numerical investigation
Nrf2/Bach1-ARE pathway are involved in the ameliorative effects of astaxanthin on D-galactose-induced liver and brain aging and injury
Risk assessment of geologic hazards in county-slope units based on RF-AER-AHP combined models
Optical soliton solutions of the unstable nonlinear Schrödinger equation
Large language model approach to uncover reasoning patterns in forensic psychiatric assessment
Abstract Forensic psychiatric assessment (FPA) evaluates whether mental disorders impair an individual’s criminal responsibility, yet the reasoning underlying these high-stakes judgments remains largely implicit and susceptible to subjectivity. We investigated whether large language models (LLMs) can quantify and elucidate reasoning patterns embedded in FPAs, and which components contribute most. We analyzed 253 FPAs conducted at a Finnish forensic hospital between 2018 and 2023. Text from each report section was embedded using a Finnish Sentence-BERT model, and section-specific embeddings were classified with support vector machines within a nested cross-validation framework. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC), complemented by word- and sentence-level explainability analyses. Among individual sections, the psychiatric evaluation (AUROC 0.90, 95% CI 0.86–0.94), psychological assessment (0.88, 0.84–0.92), and previous records (0.83, 0.78–0.88) were most predictive of criminal responsibility. Combining multiple sections further improved discrimination (0.94, 0.90–0.97). Linguistic markers related to psychosis, disorganization, and psychiatric treatment were associated with criminal irresponsibility, whereas substance use, antisocial traits, and organized behavior were more frequent among those deemed responsible. These findings demonstrate that LLM-based methods can identify and quantify textual patterns associated with forensic psychiatric decision-making.
Development and validation of an effectiveness evaluation scale for low-carbon construction technologies in building engineering based on multi-stage empirical evidence
Strike-slip Pull-apart process of the Jiyang depression during the Yanshanian tectonic cycle and its response to Paleo-Pacific plate movement
Enhancing crop yield prediction accuracy with a novel interpretable deep learning model: MHCNN-LSTM-MHA
EcoImpact: energy conservation using data-driven model predictive control and interpretable machine learning in the buildings sector
Reconstructing charcoal formation temperatures in archaeology and volcanology using an automated 532 nm Raman spectroscopy approach
Abstract Raman spectra of charcoal provide structural information that enables the reconstruction of past combustion conditions. We present a calibration method (532 nm laser excitation) for determining charring temperatures from Raman spectra of amorphous carbon, based on Raman band intensity ratios (HD/HG). Using a pine wood reference dataset, we establish statistical criteria for estimating temperature, identifying sp²-hybridization clustering, and detecting oxidative weathering. To ensure reproducibility and accessibility, we introduce our tool CHARM as a free, automated webpage ( https://olivierbrcknr.github.io/charm/ ) for processing Raman data—including de-noising, baseline correction, parameter extraction, and temperature reconstruction. This tool generates standardized numerical and graphical outputs that drastically reduce processing time and analytical bias. Applications to archaeological ceramics demonstrate that reliable temperature estimates of blackened surfaces can be achieved without destructive sampling, while tests on thin section preparations confirm that Raman parameters remain unaffected. Furthermore, our protocol enables statistical analysis of charcoals from volcanological contexts, revealing interpretable temperature ranges despite charcoal modifications by oxidative weathering. Our calibration provides a robust method for consistent, rapid temperature reconstruction of amorphous carbon across archaeological, volcanological, and related fields.
Integrating multivariate analysis and Air Pollution Tolerance Index (APTI) to evaluate four ornamental plants for sustainable indoor air phytoremediation
Abstract Indoor air pollution, especially in pharmaceutical laboratories, poses significant health risks due to the presence of volatile organic compounds (VOCs) such as benzene, toluene, acetophenone, and benzaldehyde. This study evaluates the efficiency of air phytoremediation technology using four ornamental plant species, Cordyline fruticosa , Syngonium podophyllum , Epipremnum aureum and Chlorophytum comosum to improve Indoor Air Quality (IAQ) by acting as Plant-Based Bio-Filters (PBBFs) in both pot-based and green wall configurations. VOC concentrations were monitored in a real pharmaceutical organic laboratory. Morphological and physiological plant traits including total chlorophyll content, relative water content (RWC), leaf pH, ascorbic acid concentration, stomatal density, and cuticle wax content were evaluated. Air Pollution Tolerance Index (APTI) and dust-capturing potential were calculated to assess the resilience and effectiveness of each species under VOCs exposure. Chemometric tools Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures-Discriminant Analysis (OPLS-DA) were applied to identify species with superior removal efficiency and to explore the relationship between plant traits and VOC uptake. Among the studied species, Cordyline fruticosa demonstrated the highest removal efficiency for VOCs (87.50%), CO (88.23%), and CO₂ (36.78%), as well as the highest APTI (14.76%), stomatal density (94.34 stomata/mm 2 ), and chlorophyll content. Syngonium podophyllum also showed up to 100% removal of particulate matter (PM 2.5 and PM 10 ) and performed effectively in CO (70.58%) and CO₂ (31.27%) reduction. Multivariate analysis confirmed that plants with higher physiological resilience and morphological surface complexity had significantly greater phytoremediation capacity. This study demonstrate the potential of PBBFs, especially using Cordyline fruticosa and Syngonium podophyllum , as a viable, cost-effective, and sustainable approach to mitigate indoor VOCs and improve air quality in pharmaceutical labs. The findings support integrating ornamental plants into indoor environment as a natural solution for IAQ management.
A hybrid multiscale model for predicting CAR-T therapy outcomes in solid tumors
Abstract T cell distribution within tumors (“tumor hotness”) critically determines the success of immunotherapy. However, despite numerous strategies to enhance intratumoral T cell accumulation – such as multi-target CAR-Ts and combinatorial approaches – limited mechanistic understanding of T cell–microenvironment interactions has constrained progress. To address this, we developed a mechanistic physiological model of the 3D tumor microenvironment (TME) to evaluate CAR-T performance under environmental fluctuations and across different infusion strategies. The model integrates key vascular (rolling, firm adhesion, endothelial suppression) and interstitial (ECM density, metabolic competition, chemokine sensitivity) barriers. Our simulations reveal that collagen density and metabolic competition are dominant factors in CAR-T efficacy. Enhancing vascular rolling and firm adhesion improves infiltration but remains limited by collagen and metabolism. Endothelial suppression markedly reduces tumor hotness, while its alleviation enhances response. Systemic infusion yields higher tumor hotness than intratumoral delivery, but combined routes or reduced collagen density restore efficacy, even in dense tumors. This mechanistic framework enables rational optimization of CAR-T strategies.