Search Results (2,619)

Atrial fibrillation (AF) management has historically relied on thermal ablation modalities—radiofrequency (RF) and cryoballoon—which have established a high benchmark for pulmonary vein isolation (PVI). However, the inherent risk of collateral thermal injury and lesion inconsistency has driven the search for alternative energy sources. The recent clinical adoption of pulsed-field ablation (PFA), based on irreversible electroporation, represents a significant technological evolution. This narrative review provides a critical appraisal of the transition from thermal to pulsed-field technologies. We synthesized data from pivotal trials and recent health-economic analyses to evaluate the biophysical mechanisms, clinical efficacy, and safety profiles of contemporary devices. We conduct a head-to-head comparison of all modalities regarding critical safety endpoints (esophageal, neurological, and vascular), real-world procedural challenges (anesthesia, lesion assessment), and economic sustainability. While PFA offers distinct advantages in procedural speed and tissue selectivity, we highlight that thermal modalities—particularly cryoballoon and very-high-power RF—retain competitive profiles in terms of cost-effectiveness and established long-term durability. This review aims to provide a balanced roadmap for clinicians navigating the complex choice between established thermal efficacy and the promising, yet evolving, landscape of electroporation. Full article

Coal mine ventilation systems face coupled and systemic risks characterized by structural interconnection and disaster chain propagation. In order to accurately quantify and evaluate this overall system risk, this study presents a new method of risk assessment of the coal mine ventilation system based on fuzzy polymorphic Bayesian networks. This method effectively addresses the shortcomings of traditional assessment approaches in the probabilistic quantification of risk. A Bayesian network with 44 nodes was established from five dimensions: ventilation power, ventilation network, ventilation facilities, human and management factors, and work environment. The risk states were divided into multiple states based on the As Low As Reasonably Practicable (ALARP) metric. The probabilities of evaluation-type root nodes were calculated using fuzzy evaluation, and the subjective bias was corrected by introducing a reliability coefficient. The concept of distance compensation is proposed to flexibly calculate the probabilities of quantitative-type root nodes. Through the verification of the ventilation system of H Coal Mine in Shanxi, China, it is concluded that the high risk of the ventilation system is 18%, and the high-risk probability of the ventilation system caused by the external air leakage of the mine is the largest. The evaluation results are consistent with real-world conditions. The results can provide a reference for improving the safety of the ventilation systems. Full article

Nanoplastics (NPs) pose significant risks due to their small size and ability to penetrate biological tissues. However, the molecular pathways and cellular mechanisms affected by NP exposure in marine teleosts remain poorly understood, especially in tropical reef fishes. This study examined the impact of short-term (7 days) waterborne exposure of 100 nm-carboxyl-modified polystyrene NPs on the false clownfish (Amphiprion ocellaris) exposed at two daily concentrations: low (20 µg/L, environmentally relevant) and high (2000 µg/L). A multidisciplinary approach, including biochemical and transcriptomic analyses, was conducted to assess toxic effects. Biochemical assays revealed limited changes in antioxidant defenses (CAT, GR, GST, TOSC). However, the Integrated Biomarker Response index (IBRv2i) suggested a compromised physiological condition, supported by transcriptomic data. Transcriptomic profiling revealed 409 significantly differentially expressed genes (DEGs) in the high-concentration and 354 DEGs in the low-concentration groups, with 120 shared DEGs mostly upregulated and indicative of a core molecular response. Collectively, the transcriptional profile of the low-concentration group resembled an early-warning, energy-reallocation strategy aimed at preserving essential sensory functions while minimizing expendable functions. The high-concentration group amplified the shared stress signature and recruited an additional 289 unique genes, resulting in pronounced enrichment of Gene Ontology terms related to “muscle contraction”, “oxygen transport”, “hydrogen-peroxide catabolism”, and “extracellular-matrix”. This study demonstrates that PS-NP exposure can alter gene expression and physiology in juvenile reef fish, even at environmentally relevant concentrations. Molecular responses varied with concentrations highlighting the role of exposure level in influencing biological systems and potential long-term impacts of NP pollution in marine environments. Full article

Background and Objectives: The vitamin K epoxide reductase complex subunit 1 (VKORC1) plays a central role in the vitamin K cycle, which is essential for γ-carboxylation of multiple bone-related proteins. Genetic variants in VKORC1 may influence bone mineral density (BMD) and osteoporosis risk. Materials and Methods: A systematic review and meta-analysis were conducted to evaluate the association between VKORC1 polymorphisms and osteopenia and osteoporosis. Relevant studies were identified through PubMed, Scopus, and Web of Science databases. Data on study characteristics, genotypes, BMD measurement, ethnicity, sex, and menopausal status were extracted. Results: Six studies comprising 7335 participants were included. All studies assessed BMD using dual-energy X-ray absorptiometry (DXA). The mean participant age ranged from 41.9 to 63.7 years. The VKORC1 variants most frequently studied, which were included in the meta-analysis, were rs9923231 and rs9934438. The overall effect of VKORC1 risk alleles on osteopenia/osteoporosis was significant with a p = 0.041 (fixed effects OR = 1.16, 95% CI = 1.01–1.35). Heterogeneity among studies was insignificant (I² = 0%, p = 0.893). Conclusions: A modest association was observed for the VKORC1 variants. The current body of evidence requires further studies to elucidate whether VKORC1 polymorphisms have a clinically meaningful role in bone health. Full article

Background and Objectives: People living with HIV (PLWH) have excess osteoporosis and fractures not fully captured by dual-energy X-ray absorptiometry (DXA). We evaluated whether trabecular bone score (TBS), calcaneal quantitative ultrasound (QUS) and bone turnover markers improve vertebral fracture risk assessment beyond areal bone mineral density (BMD) in PLWH. Methods: In this cross-sectional study, 87 antiretroviral-treated adults undergoing DXA had lumbar spine TBS and calcaneal QUS. Morphometric vertebral fractures were identified, correlates of degraded TBS were analyzed using multivariable regression, and sequential logistic models quantified the incremental contribution of TBS and CTX to discriminate for prevalent morphometric vertebral fractures. Results: Low BMD (osteopenia/osteoporosis) was present in 62% of participants, degraded TBS in 37% and morphometric vertebral fractures in 17%. Degraded versus normal TBS was associated with older age (49.1 vs. 39.7 years), longer HIV duration and lower nadir CD4+ count, as well as more frequent tenofovir disoproxil fumarate exposure (66% vs. 52%; all p ≤ 0.04). In multivariable analysis, age (per 10-year increase; adjusted odds ratio [aOR] 1.78; 95% CI 1.13–2.83) and nadir CD4+ < 200 cells/mm³ (aOR 2.29; 95% CI 1.06–4.97) independently predicted degraded TBS. In sequential cross-sectional models for prevalent morphometric vertebral fractures, the area under the curve increased from 0.71 (clinical variables) to 0.79 after adding lumbar spine T-score and to 0.85 after adding TBS; adding CTX yielded 0.87 without a statistically significant incremental gain. Conclusions: In PLWH, TBS captures bone quality deficits and improves vertebral fracture risk discrimination beyond BMD, supporting its integration alongside DXA in routine HIV care. Full article

This article is aimed at assessing energy–economy models with a focus on their ability to capture the dynamic structural changes of economic systems and the related energy supply chains. A narrative literature review approach was employed, synthesizing relevant peer-reviewed research. The search yielded 229 publications spanning from 2015 to 2024. After applying screening criteria based on methodological transparency, quantitative modelling, and explicit energy–economy integration, 120 articles were retained, from which 23 representative modelling frameworks were selected. The review identifies five key dimensions shaping the realism and applicability of integrated models: geographical and temporal scope, technological detail, modelling approach, and the degree of micro- and macroeconomic realism. Results show a growing adoption of multi-scale modelling and a gradual shift toward hybrid structures combining technological and macroeconomic components. However, significant gaps remain: only 26% of the models move beyond equilibrium assumptions; 17% incorporate behavioural or heterogeneous agents; and almost half rely on exogenous technological change. Moreover, the representation of policy instruments—particularly performance standards, sectoral benchmarks, and public investment mechanisms—remains incomplete across most frameworks. Overall, this analysis highlights the need for more transparent coupling strategies, enhanced behavioural realism, and improved representation of financial and transition risks. These findings inform the methodological development of next-generation models and indicate priority areas for future research aimed at improving the robustness of policy-relevant transition assessments. Full article

Radon is one of the leading causes of lung cancer worldwide. Following the implementation of the European Council Directive 2013/59/EURATOM, regular measurements of radon concentrations in workplaces have been carried out in European countries for approximately ten years. This provides a basis for assessing the exposure of workers and the general population to radon, as well as for determining the need to implement measures aimed at reducing this exposure. In addition to commonly used methods that focus on eliminating radon sources or minimizing its ingress into buildings, there are also temporary measures available, such as using air purifiers to improve indoor air quality. Although they are not recommended as a standalone or definitive solution, they can be useful as an interim measure—until appropriate actions to reduce indoor radon concentrations are implemented. In this study, five commercially available air purifiers were tested under controlled laboratory conditions to assess their impact on radon and its decay products. The results show that none of the tested devices significantly reduced gaseous radon concentrations. However, the air purifiers were highly effective in removing radon progeny, achieving a 95–99% reduction in potential alpha energy concentration (PAEC) and reducing the equilibrium factor from 48 to 76% to 0–2%. From a sustainability perspective, these findings are relevant for public health protection, responsible consumer decision-making, and evidence-based indoor air quality management. By distinguishing between ineffective radon gas removal and effective reduction of dose-relevant decay products, this study supports sustainable risk mitigation strategies and helps prevent the misuse of energy- and resource-intensive technologies for purposes they cannot fulfill. Full article

The rapid expansion of wind power as a key component of global renewable energy systems has led to the widespread deployment of wind turbines in environments exposed to diverse natural hazards. While hazard effects are often investigated individually, real wind turbine systems frequently experience concurrent or sequential hazards over their operational lifetime, giving rise to interaction effects that are not adequately captured by conventional design approaches. This paper presents Part 2 of a comprehensive review on natural hazards affecting wind turbine performance, combining bibliometric keyword co-occurrence analysis with a critical synthesis of recent technical studies. The review focuses on earthquakes, sea waves, and extreme wind events, while also highlighting other hazard types that have received comparatively limited attention in the literature, examining their effects on wind turbine systems and the mitigation strategies reported to address associated risks. Rather than treating hazards in isolation, their impacts are synthesised through cross-hazard interaction pathways and component-level failure modes. The findings indicate that wind turbine vulnerability under multi-hazard conditions is governed not only by load magnitude but also by hazard-induced changes in system properties and operational state. Key research gaps are identified, emphasising the need for state-aware, mechanism-consistent multi-hazard assessment frameworks to support the resilient design and operation of future wind energy systems. Full article

Circulating irisin, a myokine implicated in energy expenditure and adipose tissue regulation, has been increasingly studied as a potential biomarker of metabolic dysfunction. This study evaluated the relationship between serum irisin and metabolic indices, including the atherogenic index of plasma (AIP), the lipid accumulation product (LAP), and hypertriglyceridemic-waist (HTGW) phenotype in individuals with prediabetes (PreDM) and newly diagnosed type 2 diabetes mellitus (T2DM). A total of 138 participants (48 PreDM, 90 T2DM) were assessed for anthropometric, glycemic, and lipid parameters. Serum irisin levels were measured by enzyme-linked immunosorbent assay (ELISA) and correlated with insulin resistance indices (Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), Quantitative Insulin Sensitivity Check Index (QUICKI)), glycemic control (glycosylated hemoglobin A1c (HbA1c)), and composite lipid markers (total triglycerides-to-high-density lipoprotein cholesterol (TG/HDL-C)). Group differences were evaluated using non-parametric tests; two-way ANOVA assessed interactions between phenotypes and markers; multiple linear regression (MLR) and logistic regression models explored independent associations with metabolic indices and HTGW; receiver operating characteristic (ROC) analyses compared global and stratified model performance. Serum irisin was significantly lower in T2DM than in PreDM (median 140.4 vs. 230.7 ng/mL, p < 0.0001). Irisin levels remained comparable between males and females in both groups. Post hoc analysis shows that lipid indices and irisin primarily distinguish HTGW phenotypes, especially in T2DM. In both groups, irisin correlated inversely with HOMA-IR, AIP, and TG/HDL-C, and positively with QUICKI, indicating a possible compensatory role in early insulin resistance. MLR analyses revealed no independent relationship between irisin and either AIP or LAP in PreDM, while in T2DM, waist circumference remained the strongest negative predictor of irisin. Logistic regression identified age, male sex, and HbA1c as independent predictors of the HTGW phenotype, while irisin contributed modestly to overall model discrimination. ROC curves demonstrated good discriminative performance (AUC = 0.806 for global; 0.794 for PreDM; 0.813 for T2DM), suggesting comparable predictive accuracy across glycemic stages. In conclusion, irisin levels decline from prediabetes to overt diabetes and are inversely linked to lipid accumulation and insulin resistance but do not independently predict the HTGW phenotype. These findings support irisin’s role as an integrative indicator of metabolic stress rather than a stand-alone biomarker. Incorporating irisin into multi-parameter metabolic panels may enhance early detection of cardiometabolic risk in dysglycemic populations. Full article

Background: Healthcare is a large contributor to greenhouse gas (GHG) emissions, contributing to climate change and health impairments. However, the magnitude of health and climate benefits of local and regional GHG mitigation strategies has not been well quantified. Few studies have demonstrated the use of public tools for this purpose in healthcare facilities. Methods: We evaluated several renewable energy and energy efficiency scenarios focused on one academic medical center in New York State. We used the Environmental Protection Agency’s (EPA) publicly available AVoided Emissions and geneRation Tool to estimate avoided GHG and health-harmful air pollutant emissions. The economic value of the resulting avoided health and climate damages was quantified using EPA’s CO-Benefits Risk Assessment screening tool. Results: Transitioning one healthcare institution to 100% solar energy and improving energy efficiency by 25% could yield approximately $807,000 to $1.5 million in annual health savings, with an additional $2.3 million benefits in avoided climate damages. There is an approximate $108.5–$196.6 million in annual climate and health benefits when extrapolating these energy solutions to hospitals across the same state. Conclusions: There are significant health savings from healthcare GHG mitigation strategies. This application of publicly available and accessible tools demonstrates ways to integrate climate and health benefits into local decision-making around climate change mitigation and sustainability efforts. Full article

With the acceleration of digital transformation, open-source software has become a fundamental component of modern smart grids and other critical infrastructures. However, the complex dependency structures of open-source ecosystems and the continuous emergence of vulnerabilities pose substantial challenges to software supply chain security. In power information networks and cyber–physical control systems, vulnerabilities in open-source components integrated into Supervisory Control and Data Acquisition (SCADA), Energy Management System (EMS), and Distribution Management System (DMS) platforms and distributed energy controllers may propagate along the supply chain, threatening system security and operational stability. In such application scenarios, large language models (LLMs) often suffer from limited semantic accuracy when handling domain-specific security terminology, as well as deployment inefficiencies that hinder their practical adoption in critical infrastructure environments. To address these issues, this paper proposes KD-SecBERT, a domain-specific semantic bidirectional encoder optimized through multi-level knowledge distillation for open-source software supply chain security in smart grid applications. The proposed framework constructs a hierarchical multi-teacher ensemble that integrates general language understanding, cybersecurity-domain knowledge, and code semantic analysis, together with a lightweight student architecture based on depthwise separable convolutions and multi-head self-attention. In addition, a dynamic, multi-dimensional distillation strategy is introduced to jointly perform layer-wise representation alignment, ensemble knowledge fusion, and task-oriented optimization under a progressive curriculum learning scheme. Extensive experiments conducted on a multi-source dataset comprising National Vulnerability Database (NVD) and Common Vulnerabilities and Exposures (CVE) entries, security-related GitHub code, and Open Web Application Security Project (OWASP) test cases show that KD-SecBERT achieves an accuracy of 91.3%, a recall of 90.6%, and an F1-score of 89.2% on vulnerability classification tasks, indicating strong robustness in recognizing both common and low-frequency security semantics. These results demonstrate that KD-SecBERT provides an effective and practical solution for semantic analysis and software supply chain risk assessment in smart grids and other critical-infrastructure environments. Full article

Predicting energy consumption in battery electric vehicles (BEVs) is a complex task due to the large number of influencing factors and their interdependencies. Nevertheless, reliable energy consumption estimation is essential to reduce range anxiety, facilitate route planning, manage charging infrastructure, and support more effective travel decisions that lower operational risks in transportation, thereby fostering wider BEV adoption. In this context, the present study examines the existing literature on methodologies for predicting BEV energy consumption through a systematic literature review (SLR) following the Denyer and Tranfield protocol and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The analysis covers modelling approaches, computational tools, model accuracy metrics, variable topology, sampling frequency and analysis period, modelling scale, and data sources. In addition, this review incorporates a structured assessment of the methodological quality of the included studies and a systematic evaluation of risk of bias, enabling a critical appraisal of the reliability and generalisability of reported findings. A comprehensive classification of modelling methodologies and variables is proposed, providing an integrative reference framework for future research. Overall, this study addresses existing research gaps, identifies current methodological limitations, and outlines directions for future work on BEV energy consumption prediction. Full article

This paper presents a prototype of an autonomous hydrochemical monitoring system developed for large freshwater aquaculture facilities, directly addressing the need for smart monitoring in Agriculture 4.0. The proposed solution employs low-power sensor nodes based on commercially available components and long-range LoRaWAN communication to achieve continuous, scalable, and energy-efficient water quality monitoring. Each sensor module performs on-board signal preprocessing, including anomaly detection and short-term forecasting of key hydrochemical parameters. An ecological pond dynamics model incorporating an Extended Kalman Filter is used to fuse heterogeneous sensor data with predictive estimates, thus increasing measurement reliability. High-level data analysis, long-term storage, and cross-site comparison are performed on the server side. This integration enables adaptive tracking of environmental variations, supports early detection of hazardous trends associated with fish mortality risks, and allows one to explain and justify the reasoning behind every recommended corrective action. The performance of the forecasting and filtering algorithms is evaluated, and key system characteristics—including measurement accuracy, power consumption, and scalability—are discussed. Preliminary tests of the system prototype have shown that it can predict the dissolved oxygen level with $RMSE$ = 0.104 mg/L even with a minimum set of sensors. The results demonstrate that the proposed conceptual design of the system can be used as a base for real-time monitoring and predictive assessment of hydrochemical conditions in aquaculture environments. Full article

In fixed orthodontic treatment, brackets are orthodontic attachments bonded to the tooth enamel, and their placement and removal may affect the underlying enamel surface. Enamel degradation is a critical factor for oral health, as it reduces the mechanical strength of teeth and increases susceptibility to caries and erosion. Accurate diagnosis of enamel changes is therefore essential for the evaluation of preventive and restorative treatments. In this study, enamel degradation was investigated via two integrated methods: energy-dispersive X-ray spectroscopy (EDS) and surface roughness measurement. The experimental protocol was performed in three stages: before bracket bonding, after bracket removal, and after applying a remineralization treatment. The experimental design included a repeated-measures structure, with stage (baseline, post-debonding, post-remineralization) as the within-tooth factor and bracket type (sapphire vs. metallic) as the between-tooth factor. Given the violation of the variance homogeneity assumption, group comparisons were ultimately performed using Welch ANOVA followed by Games–Howell post hoc tests, with Bonferroni-adjusted values used for pairwise comparisons. The presence of orthodontic brackets can influence enamel mineralization because the bonding and debonding procedures modify the enamel surface microtopography. These procedures can generate microcracks and surface irregularities, which may affect mineral exchange between enamel and the surrounding environment. In our study, bracket removal led to a significant decrease in the mean atomic percentages of Ca (from 32.65% to 16.37% for sapphire) and P (from 16.35% to 8.60% for sapphire), accompanied by a sharp increase in surface roughness. After remineralization, Ca and P levels increased, while roughness decreased. However, neither the mineral content nor the surface topography fully returned to the initial values, indicating that remineralization achieved only a partial recovery of enamel integrity. These findings highlight that the integrated EDS approach and roughness analysis offer a promising descriptive framework for assessing enamel degradation and monitoring the effectiveness of remineralization therapies. The generated mathematical model provides a powerful descriptive framework for the in vitro data obtained, correlating roughness with mineral composition and treatment stage. However, such a high goodness-of-fit (R² > 0.98) should be interpreted cautiously due to the risk of overfitting. Therefore, rigorous external validation is mandatory before this model can be considered a reliable predictive tool. It also highlights the importance of enamel remineralization therapies after orthodontic treatment, but also the importance of choosing personalized treatment strategies adapted to the enamel type. Full article

Per- and polyfluoroalkyl substances (PFASs), as a class of “permanent chemicals” with high environmental persistence and bioaccumulation, have attracted much attention. In this study, we focused on the molecular mechanism of the interaction between perfluoroalkyl acids (PFAAs) and peroxisome proliferator-activated receptor δ (PPARδ). Using molecular docking, binding free energy calculation, and structural analysis, we systematically investigated the binding modes, key amino acid residues, and binding energies of 20 structurally diverse PFAAs with PPARδ. The results showed that the binding energies of PFAAs with PPARδ were significantly affected by the molecular weight, the number of hydrogen bond donors, and the melting point of PFAAs. PFAAs with smaller molecular weights and fewer hydrogen bond donors showed stronger binding affinity. The binding sites were concentrated in high-frequency amino acid residues such as TRP-256, ASN-269, and GLY-270, and the interaction forces were dominated by hydrogen and halogen bonds. PFAAs with branched structure of larger molecular weight (e.g., 3m-PFOA, binding energy of −2.92 kcal·mol⁻¹; 3,3m₂-PFOA, binding energy of −2.45 kcal·mol⁻¹) had weaker binding energies than their straight-chain counterparts due to spatial site-blocking effect. In addition, validation group experiments further confirmed the regulation law of binding strength by physicochemical properties. In order to verify the binding stability of the key complexes predicted by molecular docking, and to investigate the dynamic behavior under the conditions of solvation and protein flexibility, molecular dynamics simulations were conducted on PFBA, PFOA, 3,3m₂-PFOA, and PFHxA. The results confirmed the dynamic stability of the binding of the high-affinity ligands selected through docking to PPARδ. Moreover, the influence of molecular weight and branched structure on the binding strength was quantitatively verified from the perspectives of energy and RMSD trajectories. The present study revealed the molecular mechanism of PFAAs interfering with metabolic homeostasis through the PPARδ pathway, providing a theoretical basis for assessing its ecological and health risks. Full article