Search Results (92,234)

Radial distribution feeders are especially sensitive to reactive-power deficits, which increase technical losses, deteriorate voltage profiles, reduce energy efficiency, and indirectly raise the emissions associated with the energy required to supply those losses. In this context, this paper proposes a sustainability-oriented planning methodology for the location and sizing of capacitor banks in radial distribution feeders, aimed at jointly improving technical performance, economic viability, and sustainability-related energy benefits. The problem is formulated as a discrete multi-objective model and solved through a constructive Greedy heuristic combined with backward/forward sweep load-flow evaluation, considering commercially available capacitor sizes. The methodology is validated on the IEEE 34-bus feeder, a demanding benchmark that remains less frequently used than the IEEE 33- and 69-bus systems in recent capacitor-planning studies. Seven scenarios are analyzed, from the uncompensated base case to configurations with up to six capacitor banks. The results show that all compensated scenarios improve feeder performance, reducing active losses from 25.3327 kW to a minimum of 20.1468 kW, equivalent to a maximum reduction of 20.47%, and increasing the minimum nodal voltage from 0.95528 p.u. to 0.97038 p.u. From a purely financial perspective, the one-bank scenario yields the highest net present value (USD 16,358.86), whereas the two-bank scenario emerges as the most balanced solution within the evaluated set, with annual savings of USD 5432.29 and a net present value of USD 11,497.58. Overall, the results confirm that capacitor-bank planning should be addressed as a trade-off among electrical efficiency, voltage support, profitability, and sustainability-oriented benefits. The proposed framework provides a simple, reproducible, and interpretable planning tool for radial distribution feeders. Full article

The running reliability of rolling bearings depends on the effective lubrication state, and poor lubrication will induce abnormal vibration. Therefore, vibration-based fault diagnosis is an important means to evaluate the health of bearings through vibration characteristics. However, the lack of fault samples in actual working conditions seriously restricts the generalization ability and accuracy of an intelligent diagnosis model. A novel few-shot diagnosis method integrating multi-layer feature fusion and adaptive similarity measurement is proposed. This method adopts a meta-learning framework to simulate sample scarcity through numerous N-way K-shot diagnostic tasks. An efficient feature extractor with a cross-task feature stitching mechanism is designed to fuse features from support and query sets. To overcome the limitation of fixed-distance metrics in existing meta-learners, a learnable similarity scheduler adaptively generates optimal pseudo-distance functions. In particular, a multi-layer feature fusion strategy is introduced to compute adaptive similarities at multiple network depths, which significantly enhances feature robustness against operational variations. Experimental results demonstrate the method achieves stable diagnostic accuracy above 90% under extremely few-shot conditions and maintains over 90% accuracy when transferring from laboratory-simulated faults to natural operational faults, validating its strong potential for practical industrial applications where annotated fault data is scarce. Full article

Background: Standard spirometry fundamentally overlooks the mechanical dynamics of forced expiration. This study derived novel biomechanical parameters to establish functional phenotypes and predict clinical respiratory impairments. Methods: Utilizing 16,596 acceptable spirometry records from NHANES (2007 to 2012), parameters reflecting kinetic power, mass constraint, and airway instability were mathematically derived. Principal component analysis, K-means clustering, and a Multilayer Perceptron neural network were sequentially applied. Results: Three distinct biomechanical phenotypes emerged: Load-Constrained (45.4%), Mechanically Efficient (23.5%), and Dynamic Collapse (31.0%). Aging significantly degraded kinetic power, demonstrating a steeper functional decline in males (p < 0.001). The neural network achieved 93.2% testing accuracy in classifying spirometric abnormalities. Crucially, Dynamic Airway Collapse Ratio (100% normalized importance), BMI (89.4%), and kinetic power (86.2%) fundamentally outperformed traditional demographic predictors such as chronological age (20.4%) and biological sex (7.1%). Conclusions: Structural and dynamic kinetic factors drive pulmonary dysfunction far more accurately than conventional demographics. Classifying these mechanical phenotypes facilitates highly targeted precision cardiopulmonary rehabilitation. Full article

Keloid is a benign skin disease with excessive growth of fibroblasts, characterized by too much abnormal extracellular matrix deposited in the dermis. It is generally believed that transforming growth factor-β (TGF-β) is the core cytokine that causes keloid. Previously, it was thought that its pathogenic effect was mainly attributed to the classical Smad-dependent pathway. It directly shuttles signals to the nucleus to trigger pro-fibrotic gene transcription. However, accumulating evidence now points to the equally vital role of Smad-independent signaling. Unlike the direct nuclear translocation of Smads, these alternative pathways transmit signals through rapid intracellular kinase cascades. They jointly direct the proliferation, migration, anti-apoptosis, fibrogenesis, and chronic inflammation of fibroblasts in keloids. This review attempts to comprehensively clarify the molecular processes regulated by TGF-β through non-Smad pathways (such as MAPK, PI3K/Akt, Rho GTPase, Wnt/β-catenin, JAK/STAT). Translating these non-Smad insights helps to overcome the high recurrence rates of traditional therapies. Targeting these specific molecular hubs through combination and precision therapies serves to reprogram the fibrotic microenvironment. Full article

In the last few years, universities have increasingly implemented online learning environments, allowing students to study at their own pace. These environments utilize technological tools and implement methods to support training, deliver content, and promote the acquisition of new knowledge and skills. As an example of these technologies, eye tracking has emerged as a powerful tool for studying visual attention, cognitive processes, and learning behaviors. The main aim of this study is to provide a scoping review of recent eye-tracking research across diverse learner populations, ranging from K-12 students to university-level learners and educators. The present study examined recent advances in eye-tracking technologies, focusing on their potential, especially when combined with artificial intelligence (AI) techniques such as machine learning. It analyzed 54 empirical studies in the last few years, highlighting their applicability, strengths, and limitations. The research findings highlight the promise of eye-tracking technology to transform educational practices by providing data-driven insights regarding student behavior and cognitive processes. Future research must address implementation and data-analysis challenges to maximize the educational benefits of eye tracking. Full article

This study explored the physiological responses and gene expression profiles of the Manila clam (Ruditapes philippinarum) and the hard clam (Mercenaria mercenaria) under heat and hyposaline stress. Experimental conditions involved increasing the temperature from 25 °C to 35 °C and decreasing salinity from 25 ppt to 15 ppt over a 6 h acclimation period, followed by 72 h exposure. Key physiological and immune indicators, including filtration rate, oxygen consumption rate, ammonia excretion rate, and the expression of related genes, were measured. Under heat stress, R. philippinarum exhibited higher filtration, oxygen consumption, and ammonia excretion rates than M. mercenaria at most sampling time points. The expression of fatty acid desaturase (Δ6FAD) and heat shock protein (HSP70) genes increased and then decreased for both species, whereas superoxide dismutase (Cu/Zn SOD) gene expression gradually decreased over time. Furthermore, the expression levels of all three genes were generally significantly higher in M. mercenaria compared to R. philippinarum. Under hyposaline stress, R. philippinarum exhibited significantly higher filtration, oxygen consumption, and ammonia excretion rates than M. mercenaria between 24 h and 72 h. Expression levels of the Na⁺-K⁺-ATPase (NKAα), HSP70, and Cu/Zn SOD genes remained higher in M. mercenaria compared to R. philippinarum. Overall, the present study indicates that M. mercenaria maintains relative stability and R. philippinarum exhibits greater physiological fluctuation under both heat and hyposaline stress. This study highlights bivalve species-specific responses to environmental stressors and provides valuable insights for aquaculture planning and ecological management in different environmental regions, particularly in the context of global climate change. Full article

Objective: To evaluate overall survival and to identify clinical, pathological, and demographic factors associated with survival in patients with stage III colon cancer. Methods: This retrospective cross-sectional study included 452 patients with stage III colon cancer who were followed at Ankara Bilkent City Hospital between 2005 and 2025. Patient data, including age, sex, ECOG performance status, comorbidities, tumor characteristics, treatment-related toxicities, and recurrence, were analyzed using PASW Statistics 18.0 (SPSS Inc., Chicago, IL, USA). Kaplan–Meier and log-rank tests were used for survival analysis. Prognostic factors, survival, mortality, and recurrence predictions were evaluated using machine learning algorithms, including coarse tree, bagged trees, support vector machines, and k-nearest neighbors. Furthermore, an explainable artificial intelligence framework was incorporated to improve model transparency and reveal clinically meaningful feature contributions. Model performance was assessed using accuracy, sensitivity, specificity, and F-score. Results: According to statistical analyses, older age, ECOG performance score ≥ 2, stage IIIC disease, N2-level lymph node metastasis, and the presence of comorbidities—particularly diabetes mellitus—were significantly associated with worse survival (p < 0.05). Machine learning analyses identified key prognostic factors, including positive surgical margins, rash, mucositis, thrombocytopenia, number of chemotherapy cycles, pathological tumor subtype, diarrhea, age at diagnosis, and anemia. SHAP analysis further demonstrated that treatment-related variables, particularly surgical margin positivity and chemotherapy-associated toxicities, were among the most influential predictors of survival. Several machine learning models outperformed traditional statistical methods in predicting mortality and recurrence, with the highest accuracy observed in ensemble methods such as coarse tree (87%) and bagged trees. Conclusions: This study identifies key prognostic factors influencing survival in stage III colon cancer and demonstrates that machine learning-based approaches can complement conventional statistical methods. The integration of clinical and treatment-related variables may improve individualized risk stratification and support clinical decision-making. These findings may also guide future large-scale, multicenter, and prospective studies. Full article

Background: Active middle ear implants (AMEIs) provide an alternative auditory rehabilitation strategy for patients who cannot tolerate conventional hearing aids. However, clinical data regarding the outcomes of Vibrant Soundbridge (VSB) implantation using the incus short process (SP) coupler in older adults remain limited. Objective: This study aimed to evaluate the audiological outcomes, patient-reported hearing benefits, tinnitus improvement, and surgical safety of VSB implantation using the SP coupler in older adults with bilateral sloping sensorineural hearing loss. Methods: This retrospective study included 45 older male veterans (mean age 76.1 ± 5.3 years) with bilateral sloping sensorineural hearing loss who underwent unilateral VSB implantation with the SP coupler between 2019 and 2023. Functional hearing gain was assessed using preoperative and postoperative sound-field pure-tone thresholds. Patient-reported outcomes were evaluated using the Speech, Spatial and Qualities of Hearing Scale (SSQ) and the Tinnitus Handicap Inventory (THI). Operative characteristics and postoperative complications were also analyzed. Results: Mean operative time was 40.2 ± 8.7 min. Functional hearing gain increased progressively across speech-critical frequencies, reaching +20 dB at 2 kHz and +30 dB at 4 kHz. The mean four-frequency pure tone average improved from 57.4 ± 8.3 dB HL preoperatively to 35.6 ± 6.9 dB HL postoperatively (p < 0.001). All SSQ subdomains showed significant improvement (p < 0.001). THI scores decreased significantly from 43.2 ± 8.4 to 17.1 ± 6.2 (p < 0.0001), with clinically meaningful tinnitus improvement observed in 75.6% of patients. No major surgical complications occurred. Conclusions: Vibrant Soundbridge implantation using the incus short process coupler provides effective auditory rehabilitation for older adults with sloping sensorineural hearing loss. The procedure yields meaningful high-frequency hearing gain, improved hearing-related quality of life, and significant tinnitus reduction while maintaining a favorable surgical safety profile. Restoration of auditory input through active middle ear implantation may also contribute to improved central auditory processing in older adults. Full article

Jasmonate ZIM-domain (JAZ) proteins, as core negative regulatory factors of the jasmonic acid (JA) signaling pathway, play a key role in the growth and development of plants and the response to biotic and abiotic stress. In this study, 11 flax JAZ members were identified, all of which contain a ZIM domain and a Jas domain. LuJAZs comprise 3–16 exons, encoding 187–808 amino acids (aa) with molecular weights ranging from 20.24 to 88.76 kDa and isoelectric points (PI) of 5.68–9.77. They are all hydrophilic proteins located in the nucleus. These 11 LuJAZ genes are divided into five subfamilies and are unevenly distributed on chromosomes. Transcriptome and qRT-PCR analyses revealed that six LuJAZ genes, including LUSG00004384, LUSG00030782, LUSG00016742, LUSG00004390, LUSG00010997, and LUSG00029783, are significantly induced by JA. The protein–protein interaction (PPI) prediction and analysis of differential expression genes (DEGs) suggest that the MYC2 gene (LUSG00028070) may play a role in the JA-induced response. This study provides a theoretical basis for further exploring the function of the JAZ family in flax. Full article

Na⁺,K⁺-ATPase possesses a highly conserved glycine (G358 in the α3 isoform) that—together with a nearby isoleucine (I363 in α3)—is targeted by mutations causing some of the most severe neurological phenotypes of the clinical spectrum of α3-Na⁺,K⁺-ATPase mutations. The disease mutations α3-G358V and α3-I363N affect Na⁺ and K⁺ transport to an extent incompatible with cell growth. However, alanine replacement of the corresponding glycine G363 in the α1 isoform is compatible with cell growth, allowing the effects on Na⁺,K⁺-ATPase function to be addressed using enzymatic assays on plasma membranes isolated from transfected cells. Occlusion of Na⁺ appears to be defective in mutant G363A, resulting in a reduced rate of phosphorylation from ATP. Furthermore, the mutation displaces the major conformational equilibrium of Na⁺,K⁺-ATPase such that the K⁺-occluded state is destabilized and occluded K⁺ is released faster, thereby leading to accumulation of a non-productive state without bound Na⁺ or K⁺. The critical function of the glycine can be ascribed to a strategic location at the bending point between an α helix and a β strand, where it connects the catalytic ATP hydrolysis site in the cytoplasmic P domain with the ion-binding region in the membrane and coordinates important intramolecular domain movements during the Na⁺,K⁺-ATPase transport cycle. Full article

Understanding the intrinsic Li–H₂ interaction, decoupled from substrate effects, is essential to rationalize the performance of lithium-decorated hydrogen storage materials. To address the current lack of a clean theoretical baseline, we characterized the sequential H₂ adsorption on the gas-phase Li₆ superatomic cluster using high-level density functional theory (DFT), complemented by Energy Decomposition Analysis (EDA), QTAIM, and NICS(0) calculations. Li₆ acts as a structurally rigid platform (RMSD < 0.032 Å) where ligand-induced polarization progressively strengthens its σ-aromaticity (NICS(0) from −2.917 to −13.98 ppm) and increases the HOMO–LUMO gap up to 5.05 eV. EDA identifies the binding as field-activated physisorption, electrostatically dominated (65–67%) and mechanistically distinct from Kubas coordination, as confirmed by QTAIM closed-shell interaction parameters. Negative cooperativity governs an effective loading capacity of n = 2 molecules under cryogenic conditions (T_eq = 143.76 and 114.64 K), while an entropic bottleneck renders higher loading non-spontaneous at all temperatures. These results establish Li₆(H₂)_n as a foundational gas-phase reference, providing a systematic, contamination-free descriptor set for the intrinsic Li–H₂ interaction. This framework is essential for isolating the electronic role of the lithium superatom and unambiguously identifying substrate-induced modulations in supported hydrogen storage materials. Full article

In semi-arid regions, sustainable groundwater management for irrigation is critical for agricultural productivity and food security. This study presents an integrated methodological framework combining hydrochemical characterization, machine learning (ML) modeling, and explainable artificial intelligence (XAI) to predict the Irrigation Water Quality Index (IWQI) in the Ain Oussera plain, Djelfa Province, Algeria. A total of 191 groundwater samples were collected from November 2023 to September 2024 and analyzed for major ions and physicochemical parameters. Multiple irrigation suitability indices were calculated, including Sodium Adsorption Ratio (SAR), Sodium Percentage (Na%), Magnesium Hazard (MH), Permeability Index (PI), Residual Sodium Carbonate (RSC), Soluble Sodium Percentage (SSP), and Kelly’s Ratio (KR). Five ML models were developed and evaluated for IWQI prediction: Random Forest, Gradient Boosting, XGBoost, K-Nearest Neighbors, and Support Vector Regression. Results showed that 55% of groundwater samples exhibited low to no restrictions for irrigation use, while 19% required high to severe restrictions. The XGBoost model demonstrated superior performance, with the highest R² (0.95) and the lowest RMSE (3.22) among all tested algorithms. SHAP (SHapley Additive exPlanations) analysis provided a transparent interpretation of model predictions, identifying electrical conductivity and Sodium Adsorption Ratio as the most influential parameters affecting IWQI, while chloride, sodium, total hardness, and magnesium had minimal impact. Spatial mapping using Inverse Distance Weighting (IDW) interpolation in ArcGIS 10.8 revealed considerable spatial variability in water quality throughout s the plain. This research addresses a critical gap in North African groundwater management by integrating ML predictive capabilities with XAI transparency, providing water resource managers and agricultural stakeholders with interpretable, data-driven tools for sustainable irrigation planning in water-stressed semi-arid environments. Full article

The transformation of waste plastics into hydrogen and functional carbon (C) materials represents a promising pathway for achieving both resource recycling and the production of value-added products. Owing to their tunable physicochemical properties, plastic-derived carbons have attracted significant attention in electrochemical energy storage applications. Various C nanostructures, including graphene, porous C, hard C, and C nanotubes (CNTs), can be generated from discarded plastics through thermochemical processes. The electrochemical performance of these materials is closely governed by their structural characteristics, such as pore architecture, specific surface area, heteroatom doping, surface functionalities, and dimensional morphology. This review aims to provide a comprehensive and systematic overview of the conversion of waste plastics into functional C nanomaterials via thermochemical routes, particularly catalytic pyrolysis and carbonization. The resulting C nanostructures are systematically categorized based on their dimensional architectures (0D, 1D, 2D, and 3D) and comparatively analyzed in terms of their structural features and electrochemical performance. Emphasis is placed on the transformation of diverse plastic feedstocks into high-value C materials with tailored dimensional architectures, including graphene, CNTs, C nanospheres, C nanosheets, porous carbons, and their composites. Furthermore, recent progress and critical challenges in utilizing these materials for electrochemical energy storage systems, such as supercapacitors and rechargeable batteries (Li-ion, Na-ion, K-ion, Li-S, and Zn-air), are discussed. Distinct from previous reports, this review highlights the correlation between thermochemical processing strategies, resulting structural features, and electrochemical performance, providing new insights into the rational design of high-performance C materials. These findings are expected to facilitate the advancement of sustainable energy storage technologies while contributing to effective plastic waste valorization. Full article

Background and Objectives: Venous thromboembolic disease (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE), is a major cause of morbidity and mortality worldwide and imposes a substantial financial burden on health systems due to both the direct and indirect costs of acute management and long-term complications. This systematic review aimed to assess patient satisfaction with anticoagulation therapy for VTE and to highlight potential differences according to the type of anticoagulant. The review focused on factors influencing the patient experience, such as perceived efficacy, ease of use, adverse effects, and health-related quality of life. Materials and Methods: A systematic review, without quantitative meta-analysis, was conducted in accordance with PRISMA 2020 guidelines. Articles were identified through searches in major databases (PubMed, Scopus, Cochrane Library and others) using keywords including “patient satisfaction”, “anticoagulation”, “venous thromboembolic disease”, and “quality of life”. In total, 21 studies published between 2009 and 2025 met the inclusion criteria. The studies assessed patient satisfaction with different types of anticoagulation, including vitamin K antagonists (VKAs), direct oral anticoagulants (DOACs), and low-molecular-weight heparin (LMWH) injections. Results: Across the included studies, patients generally reported higher levels of treatment satisfaction with DOACs compared with VKAs, mainly due to the absence of routine laboratory monitoring and fewer dietary restrictions. However, satisfaction varied according to age, sex, and clinical status. In specific patient populations, such as those with cancer-associated thrombosis, factors including fewer drug–drug interactions and perceptions of safety with LMWH appeared to influence treatment choice and satisfaction. Adverse effects, particularly bleeding, were identified as major drivers of dissatisfaction. Several studies suggested that higher treatment satisfaction was associated with better adherence, while quality of life appeared to improve in patients treated with DOACs in comparison with VKAs. Conclusions: Patient satisfaction is a critical component of successful VTE management. Overall, DOACs appear to be associated with higher treatment satisfaction than traditional therapies such as VKAs, although further high-quality research is needed to individualise anticoagulation strategies. Systematic incorporation of patient-reported satisfaction into clinical decision-making and into international guidelines may improve adherence, enhance quality of life, and ultimately increase the effectiveness of anticoagulation therapy. Full article

This study evaluates the technical feasibility of deploying containerized oxy-combustion power modules with integrated CO₂ capture in remote Ecuadorian Amazon oil fields. Associated petroleum gas is conditioned with a 35 wt.% diethanolamine (DEA) sweetening stage specifically implemented to remove H₂S and reduce acid-gas loading prior to combustion, improving fuel quality and protecting downstream equipment while increasing methane mole fraction for combustion. System efficiency is governed by stoichiometric oxygen demand, with methane requiring 2 mol O₂/mol fuel and hexane requiring 11 mol O₂/mol fuel; favoring methane-rich streams reduces ASU energy demand, enhances combustion performance, and lowers separation costs. The combined oxy-combustion cycle attains a thermal efficiency of 33.10% and an exergetic efficiency of 39.98%. Major energy penalties arise from the cryogenic air separation unit and the CCS train, yet operational tuning of CO₂ recirculation and steam flow could raise thermal efficiency by up to 2%. The ASU produces oxygen at 96.67% purity with an energy consumption of 0.385 kWh/kg O₂, while the CCS achieves 99.99% CO₂ capture at 0.41 kWh/kg CO₂. Sourcing gas from three production blocks provides flexibility to accommodate supply variability. The modular 272 MW unit demonstrates viability for off-grid power supply, routine flaring reduction, and scalable acid-gas valorization in frontier oilfields. Full article