Browse Articles
Discover research articles across all indexed journals
Mesoscale numerical study on the mechanical behavior of basalt fiber reinforced phosphogypsum-based materials
Resource optimization algorithm for RF-aided NOMA VLC network joint blocklength control and power allocation
To achieve high-reliability in the Industrial Internet of Things (IIoT) and satisfy the low-latency requirements of industrial equipment, this paper proposes a resource optimization scheme that jointly controls information transmission blocklength and power allocation. Specifically, Short Packet Communication (SPC) and Non-Orthogonal Multiple Access (NOMA) technologies are introduced to construct a Radio Frequency (RF)-aided Visible Light Communication (VLC) network system. The successful transmission probability of multiple User Equipment (UE) is analyzed, and the Service Capacity (SC) of each channel is quantified. Then, an optimization problem is formulated to maximize the SC, subject to constraints on statistical Quality of Service (QoS), Service Reliability (SR), and transmission power. To solve this optimization problem, we design a resource optimization algorithm joint blocklength and power allocation. Simulation results demonstrate that the proposed resource optimization scheme for NOMA VLC/RF networks outperforms NOMA VLC and OMA VLC in ensuring highly reliable data transmission. Furthermore, the proposed algorithm could maximize the SC of the NOMA VLC/RF networks by utilizing shorter blocklength.
A bipolar triangular fuzzy ARLON based decision support system for optimal CNC machine tool selection in smart manufacturing
Epigenetic editing makes its mark
Exploring the feasibility and acceptability of Continuous Glucose Monitoring among people with type 1 diabetes and healthcare providers in South Africa’s public sector: A qualitative study
Background Continuous Glucose Monitoring (CGM) is an advancement in diabetes management, offering real-time insights into blood glucose levels and facilitating decision-making around diabetes care. However, its adoption in low- and middle-income countries (LMICs) remains low. This study explored the perceptions and experiences of CGM use among people living with type 1 diabetes (T1D), their caregivers, and healthcare providers (HCPs) in the public sector in South Africa. Methods Convenience sampling was used to recruit participants from the ACCEDE study – a pragmatic randomised controlled trial on CGM use among people living with T1D in South Africa. Between July 2024 and February 2025, we conducted focus group discussions (FGDs) with recipients of care and caregivers and semi-structured interviews (SSIs) with HCPs across study sites in Cape Town and Pretoria. All FGDs and SSIs were audio-recorded, transcribed, and analysed using MAXQDA 2022. Data analysis followed thematic content analysis, and the findings presented according to the socioecological framework. Results A total of 107 participants, including 75 people living with T1D, 17 caregivers, and 15 HCPs, were included in the study. CGM was generally perceived as acceptable due to convenience, reduced need for finger-prick testing, and enhanced understanding of glucose patterns. Feasibility was enhanced by ease of use, access to training, and social support. Key barriers included cost, limited awareness, and socio-economic constraints such as food insecurity and lack of access to transport. Conclusion CGMs are both feasible and acceptable within South Africa’s public healthcare context. However, integration requires a coordinated, multi-level response, strengthening provider and patient awareness, knowledge, adequately resourced multi-disciplinary diabetes care teams, and addressing affordability through supportive health policies.
Investigation of the health and safety conditions in industrial micro, small, and medium enterprises in Iran using a weighted ELMERI method
Exploring DNA methylation profiles in the pathogenesis of human osteoporosis via whole-genome bisulfite sequencing
Osteoporosis is a widespread metabolic bone disorder characterized by diminished bone mass, deteriorated microarchitecture, and increased bone fragility, resulting in elevated fracture risk. This condition adversely affects quality of life and is associated with higher mortality. Growing evidence indicates that DNA methylation serves as a key epigenetic mechanism regulating bone metabolism-related gene expression and may thereby influence osteoporosis pathogenesis. However, the specific relationship between DNA methylation and osteoporosis remains to be fully elucidated. In this hypothesis‑generating pilot study, we demonstrated significant differences in both the extent and distribution of DNA methylation between osteoporosis patients and non‑osteoporosis controls, with notable enrichment in CpG islands. Enrichment analyses based on GO and KEGG pathways revealed distinct biological processes and signaling pathways associated with osteoporosis. Importantly, we identified six genes (MSX1, HOXD4, AXIN2, WNT5A, TGFB1, STAT3) showing directionally consistent methylation‑expression trends, although the DMRs for most genes were located in non‑promoter regions (TTS, exons, introns). After adjusting for the imbalance in sequencing depth, the same directional trends were retained; however, the differences did not reach adjusted statistical significance (median adjusted P > 0.05), likely due to the limited sample size. These genes therefore represent prioritized candidates for exploratory follow‑up in larger, cell‑type‑resolved cohorts. This study provides new insights into the epigenetic mechanisms underlying osteoporosis and highlights potential targets for further investigation.
In vitro evaluation of bactericidal efficacy, cytotoxicity and genotoxicity of combined negative ions and ozone treatment
The rise of evidence-based medicine and the ‘mavericks’ who championed it
Structure function relationships differ between optic neuritis and glaucoma with comparable optical coherence tomography findings
This retrospective study compared structure-function relationships between patients with optic neuritis (ON) and primary open-angle glaucoma (POAG), focusing on the extent of retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) damage and its correlation with visual field (VF) defects. We included 194 patients (ON: 47; POAG: 147) referred to Yonsei University Severance Eye Hospital between 2017 and 2023. RNFL and GCIPL thickness, VF indices, and the relationship between structural and functional measures were assessed. Despite comparable RNFL and GCIPL thinning, ON demonstrated significantly better VF performance than POAG (mean deviation: −2.26 dB vs. −7.32 dB; VF index: 95.48% vs. 80.43%; both p < 0.001). In POAG, VF loss was strongly correlated with structural parameters, whereas in ON, VF remained preserved even at low RNFL and GCIPL values. Linear regression with robust error estimation confirmed significant interaction between disease type and structure–function slopes (p < 0.01). These findings persisted after 1:2 propensity score matching for age and comorbidities (ON: n = 29; POAG: n = 58; all interaction p < 0.05), age-adjusted multivariable regression, and a sensitivity analysis restricted to non-diabetic participants (ON: n = 45; POAG: n = 124; all interaction p < 0.001). This dissociation was evident at RNFL <90 µm and GCIPL <80 µm, where ON showed better VF indices than POAG with similar structural loss. The differences in structure–function relationships underscore the importance of disease-specific diagnostic approaches and unraveling the distinct mechanisms underlying ON and POAG to improve the management of visual impairments.
An efficient framework for real-time colorectal polyp detection using local outlier factor-based preprocessing and YOLOv11n
Rights for rivers and ice cream for all: top reads for the summer holidays
Stimuli‐Responsive Hierarchical Structuring Controls Survival and Programs Hydrogelation of Supramolecular Metallofibers
ABSTRACT Hierarchical organization is a central strategy by which biological systems stabilize fragile assemblies and regulate function in hostile environments. Translating this principle to synthetic polymer systems in water remains challenging, as noncovalent interactions can readily disrupt supramolecular polymerization. Herein, we report on aqueous supramolecular metallofibers formed by Zn(II) Salphen complexes functionalized with poly( N ‐isopropylacrylamide) (PNIPAM), which undergo reversible, multi‐stimuli‐responsive hierarchical structuring. Individual nanofibers form spontaneously in dilute aqueous solution via supramolecular copolymerization with water molecules and reversibly organize into micron‐sized bundles in response to temperature, ionic strength, and solvent composition. This higher‐order organization kinetically stabilizes the assemblies under conditions of dilution, low pH, and chemical degradation, where both monomers and isolated nanofibers rapidly disassemble. Hierarchical structuring further modulates photophysical properties, enables selective sorting and survival of responsive over non‐responsive fibers in mixed systems, and translates microscopic robustness into macroscopic hydrogelation at unusually low concentrations. Leveraging the intrinsic photothermal response of the Zn(II) Salphen chromophore, light irradiation drives an energy‐dependent, out‐of‐equilibrium bundled state that persists only while light energy is supplied, thereby controlling chemical stability in acidic environments. Collectively, this work establishes hierarchical supramolecular structuring in water as a general strategy to program stability, selectivity, and energy‐dependent function in synthetic soft materials.
Acute kidney injury severity in ICU patients: Developing and evaluating a data-driven analysis of clinical covariates using machine learning
Background Acute kidney injury remains a major cause of morbidity and mortality in critically ill patients. Existing classification systems rely on serum creatinine and urine output thresholds and do not fully capture the complex, multifactorial nature of acute kidney injury severity in the ICU. Objective To develop and validate a machine learning model using high-dimensional clinical data to identify covariates associated with the severity of acute kidney injury and enhance early risk stratification. Methods We performed a secondary analysis of 2,281 patients from the ICU in the MIMIC-IV database. Acute kidney injury severity was staged (0–3) based on serum creatinine criteria. After rigorous data cleaning, imputation, and feature selection, an XGBoost model was trained. Model performance was assessed, and gain-based metrics were used to identify the most important predictors of acute kidney injury severity. Results The XGBoost model demonstrated favorable discriminative performance, with an overall accuracy of 77.6% and a mean absolute error of 0.241. It achieved high precision and recall for stage 0 (precision = 0.917) and stage 3 (recall = 0.837), but showed decreased performance for stage 2. The top 10 covariates associated with increasing acute kidney injury severity were chronic kidney disease, sepsis, total bilirubin, norepinephrine, vasopressin, furosemide, phenylephrine, phosphate, potassium, and platelet count. Conclusions Our machine learning-based model effectively identified key covariates of acute kidney injury severity in ICU patients using routinely collected clinical data. The findings provide a foundation for early identification, risk stratification, and targeted intervention strategies for acute kidney injury in critical care settings.
Operational cyber resilience assessment of edge IoT systems using a PH MMPP framework from IDS observable attack regimes
Abstract This study developed an analytical PH/MMPP priority-clearing framework for assessing the operational cyber resilience of Edge-IoT systems. The framework complements intrusion-detection approaches by transforming IDS-observable attack-traffic regimes into quantitative indicators of service degradation, including queue accumulation, latency amplification, residual service capacity, destructive clearing risk, service survivability, and spectral proximity to overload instability. The obtained results demonstrated substantial degradation of Edge-IoT service behaviour under attack escalation: the mean ordinary-queue length increased from 0.74 to 286.91 packets, the virtual ordinary-queueing delay rose from 0.011 to 11.428 s, the operational response-time indicator increased from 0.021 to 23.706 s, and the legitimate-service survivability probability decreased from 0.983 to 0.0064. The framework was calibrated using traffic characteristics extracted from the CICIoT2023 and Edge-IIoTset datasets and subsequently applied to the analysis of generalised operational attack regimes rather than dataset-specific cases. By integrating IDS-observable attack regimes with queueing dynamics, service survivability, and spectral stability analysis within a unified stochastic framework, the proposed approach enables a transition from attack-detection assessment to the quantitative evaluation of the operational cyber resilience of Edge-IoT services.
Stable Nickel‐Rich Layered Oxide Cathodes Enabled by Conformal AlF <sub>3</sub> Nanoshell for High‐Voltage All‐Solid‐State Batteries
ABSTRACT Chloride‐based solid‐state electrolytes (SSEs) emerge as promising catholytes for all‐solid‐state batteries (ASSBs) because of their high ionic conductivity and good oxidative stability. However, their integration with nickel‐rich layered oxides, such as LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM811), remains hindered by poor interfacial stability, leading to continuous performance degradation, particularly at high operation voltages. Herein, we demonstrate that the surface modification of NCM811 particles through the construction of conformal AlF 3 nanoshells enables stable battery operation at voltages up to 4.8 V with chloride‐based SSE Li 3 InCl 6 . Notably, a solution‐based route is developed to first form a uniform (NH 4 ) 3 AlF 6 precursor nanoshell, which was subsequently converted into the AlF 3 surface layer by sintering, thereby overcoming the long‐standing synthetic challenge in building AlF 3 coatings. We found that this AlF 3 surface layer not only enhances the structural robustness of NCM811 against surface degradation during the electrochemical cycling, but also effectively suppresses oxidative decomposition of the interfacial Li 3 InCl 6 electrolyte, thereby enabling a significantly enhanced high‐voltage stability (up to 4.8 V), excellent rate capability (3 C), and prolonged cyclability (≥1000 cycles). This work elucidates the critical role of surface chemistry in governing interfacial and structural evolution in chloride‐based ASSBs and provides a generalizable pathway for designing reliable high‐energy storage devices.
Organizational factors influencing recreational therapy program effectiveness in veterans’ nursing homes: A mixed-methods approach
Background Veterans’ nursing homes face significant challenges in delivering effective recreational therapy (RT) programs due to complex organizational factors and unique veteran care needs. Limited research has systematically examined organizational determinants from leadership perspectives, despite leaders’ critical roles in resource allocation and program implementation. Objective This study examined organizational factors influencing recreational therapy program effectiveness in a veterans’ nursing home through comprehensive analysis of leadership perspectives using a mixed-methods approach. Methods A cross-sectional survey was administered to 19 leadership personnel at NYSVETS Home @ Oxford. The 28-question survey assessed RT program effectiveness across five well-being domains, organizational strengths and weaknesses, participation barriers, and leadership involvement patterns. Analysis included descriptive statistics, correlation analysis, and systematic thematic coding of 192 qualitative responses. Results Leadership rated overall RT program effectiveness highly (78.9%, 95% CI: 60.6–97.3%), with Physical well-being showing the highest impact (3.75 ± 0.62, 95% CI: 3.36–4.14) and no significant differences across domains (χ² = 0.563, p = 0.967, Kendall’s W = 0.007). Organizational strengths significantly outweighed weaknesses (U = 24.0, p = 0.010, effect size r = 0.741), with activity variety (89.5%) as the primary asset and resource limitations (52.6%) as the key deficit. Strong positive correlations emerged between engaged veterans and dedicated staff (r = 0.782, 95% CI: [0.508, 0.912]). Leadership demonstrated strong mission-vision alignment (76.5%) but involvement intensity showed no significant association with effectiveness (r = 0.335, 95% CI: [−0.214, 0.723], p = 0.223). A Resource Adequacy Index of 29.7% indicated critical capacity limitations. Qualitative analysis validated quantitative findings, with Social Interaction (40 mentions) and Physical Health (36 mentions) themes supporting effectiveness priorities while revealing veteran-specific challenges including generational preferences for individualized programming. Conclusions This study provides comprehensive evidence for organizational factors influencing RT effectiveness, demonstrating both program strengths and critical improvement areas. The organizational priority matrix and resource allocation analysis provide evidence-based tools for strategic planning and quality improvement initiatives, informing policy development and practical guidance for healthcare administrators.
A lumped transient analysis of a reflector-enhanced photovoltaic system with paraffin PCM for passive thermal regulation
Characterization and functional analysis of miRNAs in Salvia miltiorrhiza-isolated exosome-like nanoparticles for gastric cancer treatment
Background Gastric cancer (GC) is a widespread global malignancy, frequently diagnosed at advanced stages owing to the subtle nature of early symptoms and low screening rates. Consequently, there is an imperative need to investigate innovative strategies for the treatment of GC. Exosomes, originating from various sources, act as natural nanocarriers enriched with numerous bioactive molecules, showcasing potential as groundbreaking treatments for GC. Materials and methods In the present study, exosome-like nanoparticles (ELNs) were successfully purified from Salvia miltiorrhiza Bunge (Danshen) utilizing ultracentrifugation. The impact of these ELNs on human gastric cancer cells (HGC-27) was evaluated via a suite of viability assays, encompassing CCK-8, colony formation, flow cytometry, transwell migration, and wound healing assays. Furthermore, miRNA sequencing was conducted to identify and analyze the highly abundant miRNA within Danshen-derived ELNs, along with its potential biological functions. Results The HGC-27 cells internalized Danshen-derived ELNs (DS-ELNs), which led to a decrease in cell viability. Concurrently, these ELNs exhibited significant inhibitory effects on cell migration, colony formation, and overall progression of GC in vitro. The functional analysis of the miRNAs harbored by these ELNs indicated that they may serve as a potential therapeutic target for GC. Conclusion In summary, these findings have not only comprehensively characterized the miRNAs present in Danshen-derived exosomes but also provided invaluable insights into the molecular mechanisms by which Danshen exerts its effects in mitigating