Browse Articles

Influence analysis of thermal properties of phase-change materials on the thermal efficiency of dynamic rotating latent-energy-storage envelope

Design and experimental validation of a deterministic wireless field-oriented control system for induction motors using low-cost 2.4 GHz transceivers

Robust multimodal expert learning for sentiment analysis with missing modalities

Codette: a multi-perspective cognitive architecture with memory and meta-cognitive strategy evolution

Leaching mechanism and behavior of rare earth elements from roasted coal gangue using citric acid

Abstract The recovery of rare earth elements (lanthanides and yttrium, REY) from coal gangue offers a potential approach for the resource utilization of this industrial waste. In this work, the effect of citric acid on the leaching of REY from roasted coal gangue was systematically investigated. The leaching mechanism of REY was elucidated by comparing the leaching behavior of REY in different acid systems, combined with zeta potential analysis and solution chemical equilibrium calculations. The maximum leaching efficiencies of REY, light REY (LREY), and heavy REY (HREY) were 48.6%, 59.1%, and 17.2%, respectively, achieved at 0.8 mol/L citric acid, a liquid-to-solid ratio of 25 mL/g, 150 min, and 90 °C. Acid leaching experiments at a fixed concentration of 0.8 mol/L showed that hydrochloric acid leached REY more rapidly than citric acid. At the same initial pH (approximately 1.5), citric acid achieved a higher REY leaching efficiency, and the pH change of the solution during leaching was the smallest, at 0.43. The citric acid leaching reaction mainly occurs in the pH range of 1.5–2.0. Meanwhile, the Al leaching efficiency was 51.0% under the condition of 0.8 mol/L citric acid. SEM–EDS analysis reveals that the Si/Al atomic ratio on the solid surface increased from an initial value of 1.0 to 2.6 and 3.0 after leaching with 0.8 mol/L citric acid and hydrochloric acid, respectively. Zeta potential analysis and solution chemical equilibrium calculations indicate that the complexation between citrate ions and rare earth ions is weak during the leaching stage. Therefore, the leaching of REY from roasted coal gangue by citric acid is mainly due to the effect of H + . These findings can provide support for improving sustainable recovery strategies of REY from coal gangue.

Effects of dietary garlic supplementation on growth, hematobiochemical, and molecular responses in stinging catfish (Heteropneustes fossilis)

A systematic study on solvent responses of coumarin-based fluorophores for cellular bioimaging

Finite element analysis of stress distribution in zygomatic implant configurations with different hybrid prosthesis superstructure materials

Synthesis of small planar antenna arrays using collapsed distributions

Genetic contributors to premature coronary artery disease identified by whole-exome sequencing

Atmospheric dispersion modelling of black carbon and PM₂.₅ emissions from an iron and steel plant in Ilorin, Nigeria

Effects of long-term application of organic fertilizer from distillers’ grains on the soil microbiome

Estimating appendicular skeletal muscle mass of dual-energy X-ray absorptiometry using single-slice abdominal computed tomography imaging

Secure dual biometric image steganography via CNN-refined chaotic hybrid transform embedding

CortexNet: convolutional neural networks for alzheimer’s disease diagnosis using brain MRI

Smartwatch-based automated lifelog platform: feasibility and preliminary real-world evaluation with real-world data from post-stroke patients

Abstract Real-world monitoring may complement clinic-based assessment after stroke by capturing daily physiological and activity-related information outside scheduled visits. We developed and evaluated a wearable-to-cloud platform that integrates smartwatch-derived activity and photoplethysmography-derived heart rate variability (PPG-HRV) signals with digital questionnaire-derived clinical scores in post-stroke patients. In this three-center feasibility study, 52 stroke survivors were enrolled, and 47 participants were included in the final analytic cohort after 5 withdrawals. The mean monitoring duration was 2.65 ± 1.69 months per participant. Valid participant-level inertial measurement unit (IMU)-derived activity and PPG-HRV summaries were available for 37 participants, and the primary clinical-wearable association analysis included 36 participants with complete paired data. In the primary eight-test analysis, higher MoCA-K scores were moderately associated with higher HRV/autonomic composite values, indicating that better cognitive performance was associated with a more favorable wearable-derived autonomic/HRV profile (Spearman rho = 0.488, 95% CI 0.19–0.70; raw P  = 0.0026; Benjamini-Hochberg q = 0.021). This association was similar after age adjustment (rho = 0.503). These findings support the feasibility of multi-center smartwatch-based lifelog monitoring and identify an early cognition-autonomic physiology signal requiring validation in larger longitudinal cohorts.

The essential oil extracted with superheated steam extraction from Cinnamomum cassia from Pakistan has potential antimicrobial and antioxidant applications

Common thought patterns reflect generosity, fairness, and social context

Abstract Humans generate thousands of thoughts each day, many of which concern other people. Yet it remains unclear whether these ongoing thoughts vary systematically across social contexts that demand meaningful social behavior, and whether they reflect individual differences in social preferences such as generosity and fairness. To address this question, we combined multidimensional experience sampling (MDES) with an altruism task administered online or in person (total N  = 320). Participants made monetary sharing decisions across social contexts that varied in partner cues (distressed, neutral, unidentifiable), while intermittently reporting their ongoing thoughts using MDES. Dimensionality reduction of MDES responses using principal component analysis revealed a small set of common, interpretable, and robust thought patterns characterizing moment-to-moment cognition during social choice. Critically, the expression of these thought patterns tracked variation in social context, generosity, and model-based parameters indexing fairness preferences. Moreover, these patterns generalized to a separate non-social task that did not require social behavior, indicating that they reflect common patterns of cognition rather than task-specific artifacts. Together, these findings provide initial evidence that ongoing thought states offer reliable insights into social preferences, introducing a novel framework for studying the link between ongoing cognition and social behavior in the laboratory and everyday life.

Clinical and morphological determinants of minimally-invasive electrical impedance spectroscopy measurements in pulmonary nodules: an exploratory correlation pilot study

Hidden multistate models to study multimorbidity trajectories

Abstract Multimorbidity in older adults is common, heterogeneous, and highly dynamic, and it is strongly associated with disability and increased healthcare utilization. However, existing approaches to studying multimorbidity trajectories are largely descriptive or rely on discrete-time models, which struggle to handle irregular observation intervals and right-censoring. We developed a continuous-time hidden multistate modeling framework to capture transitions among latent multimorbidity patterns while accounting for interval censoring and misclassification. A simulation study compared alternative model specifications under varying sample sizes and follow-up schemes, and the best-performing specification was applied to longitudinal data from the Swedish National study on Aging and Care–Kungsholmen (SNAC-K), including 2716 multimorbid participants followed for up to 18 years. Simulation results showed that hidden multistate models substantially reduced bias in transition hazard estimates compared to non-hidden models, with fully time-inhomogeneous models outperforming piecewise approximations. Application to SNAC-K confirmed the feasibility and practical utility of this framework, enabling identification of risk factors for accelerated progression toward complex multimorbidity and revealing a gradient of mortality risk across patterns. Continuous-time hidden multistate models provide a robust alternative to traditional approaches, supporting individualized predictions and informing targeted interventions and secondary prevention strategies for multimorbidity in aging populations.