Search Results (1,518)

While direct current (DC) ice-melting is currently adopted for some transmission lines, its application to 10 kV distribution transformers—often located in remote and rugged terrain—presents significant operational challenges. Disconnecting these transformers prior to ice-melting is a complex procedure that incurs substantial labor, material, and financial costs. Leaving transformers connected risks DC current flowing into idle windings, potentially causing damage. Furthermore, existing mobile DC ice-melting power supplies are bulky and impose stringent transportation requirements, rendering them unsuitable for use on mountain roads. To overcome these limitations, this paper proposes a compact, lightweight variable-frequency ice-melting device. The operating principle and output characteristics of the variable-frequency method are investigated in detail. Using Simulink, system modeling and simulation analyses are performed to obtain the voltage and current output characteristics, along with harmonic spectra. Simulation results demonstrate that the proposed device achieves significant miniaturization compared with conventional solutions: within the typical parameter range of conventional devices, the volume can be reduced by 44–58% and the weight by 43–52%. In addition, the selected LC filter parameters (L = 10.39 mH, C = 86.62 μF) represent an optimized compromise solution that effectively suppresses input harmonics while maintaining the output current total harmonic distortion (THD) within an acceptable limit of 3.6%. Experimental results further validate the feasibility of the variable-frequency ice-melting current. Based on a matrix converter topology, the proposed device enables flexible adjustment of the output melting voltage and frequency, exhibits excellent low-frequency performance and dynamic response, and maintains low output harmonic content—fully meeting the application requirements for variable-frequency ice-melting. The key novelty lies in a compact matrix-converter-based de-icing device with systematic low-frequency performance analysis, offering superior portability and adaptability over traditional DC solutions. Full article

Polycyclic aromatic hydrocarbons (PAHs), such as benzo[a]pyrene (B[a]P), are major risk factors for lung cancer and other diseases, acting through the aryl hydrocarbon receptor (AHR). Alveolar macrophages (AMs) help regulate the lung microenvironment by responding to inhaled toxicants and resident microbiota. Although small extracellular vesicles (sEVs, aka exosomes) released by AMs mediate intercellular communication and immune responses, the influence of lung microbiota on sEV biogenesis and the mechanisms underlying sEV dysregulation during PAH exposure remain unknown. Here, we investigated the interplay between AMs, B[a]P, and lung microbiota, focusing on sEV-associated miRNAs (exo-miRNAs). Murine AMs (MH-S) were exposed to varying B[a]P concentrations in the presence or absence of murine lung microbiota with or without an AHR antagonist. sEVs from each condition were characterized and profiled for miRNA. Distinct miRNA signatures emerged: high-dose B[a]P enriched miRNAs linked to cancer progression, whereas lung microbiota alone or with low-dose B[a]P induced tumor-suppressor miRNAs that limit proliferation and metastasis and promote apoptosis, an effect enhanced by AHR antagonism. Lung microbiota appeared to counteract high-dose B[a]P by modulating tumor-suppressive exo-miRNAs. This study demonstrates that lung microbiota-induced exo-miRNAs critically shape AM-derived sEV-miRNA signaling during PAH exposure. The identified exosomal miRNAs could serve as important exposure biomarkers and therapeutic targets for mitigating B[a]P-induced toxicity and cancer development. 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

Peru’s recent national mental health (MH) reforms aim to decentralise care and expand access to MH services for rural populations by integrating services into primary healthcare through the expansion of Community Mental Health Centres (CMHCs). Evidence on the implementation of these reforms at the local level remains limited. This qualitative study aimed to (i) describe the structure and implementation framework of MH services, (ii) analyse local understandings of MH; and (iii) examine pathways to care and identify barriers and facilitators to MH service implementation from both the supply (service providers) and demand (users and community members) perspectives. MH services were mapped across three provinces of northern Peru using a review of national MH policies, 2 focus group discussions, and 31 semi-structured interviews. Data were analysed thematically to explore local understandings of MH, pathways to care, and health system barriers. Local understandings of MH are shaped by cultural beliefs, social norms, and economic conditions, with many individuals experiencing distress initially relying on family networks or traditional healers. Stigma and expectations of a quick recovery hinder engagement with formal services. While the expansion of CMHCs has improved geographical access to specialised care in rural areas through proximity and being patient-centred, the implementation of respectful provider interactions remains uneven. Weak referral pathways and limited coordination between primary care centres and CMHCs frequently shift the responsibility for navigating care onto users and their families. Family involvement and culturally sensitive practices foster trust and support continued engagement. Persistent challenges include the limited capacity of service providers, high staff turnover, and the follow-up mechanisms, stigma, and tensions between cultural and biomedical understandings of MH. Peru’s expansion of CMHCs represents a significant health system reform to improve equitable access for rural populations. To sustain these gains, it will be necessary to strengthen workforce stability, clarify referral processes, and integrate culturally responsive approaches within primary care systems, offering lessons for similar resource-constrained contexts. Full article

Vegetation restoration profoundly impacts soil carbon (C)-nitrogen (N)-phosphorus (P) cycling in arid sandy lands, with vegetation type critically regulating accumulation patterns. However, the magnitudes of soil nutrients and stoichiometry for different vegetation types are still largely unknown. Thus, we conducted a regional-scale study to evaluate the soil nutrients and nutrient stoichiometry under four typical vegetation types in the Mu Us Sandy Land (MUS), including monoculture arbor (MA), monoculture shrub (MS), arbor-shrub mixed (MAS), and monoculture herbaceous (MH), with cropland (Cr) and bare sand (Bs) controls. Our results showed that vegetation type significantly affected SOC and TN content. MS (30–40 years), MA (>40 years), and MH exhibited significant increases of 285.5–305.8% in SOC and 293.6–374.6% in TN in the topsoil, respectively. MS (30–40 years) and MH demonstrated increases of 399.1% and 283.3% in SOC and 250.2% and 162.8% in TN in the subsoil. However, MAS had no significant effect on SOC and TN. MA (>40 years) resulted in a higher TP in the subsoil. Compared to Bs, humic substances significantly increased by 111.1–171.6% under MA (>40 years), MS (>40 years), and MH, exhibiting positive correlations with SOC. Moreover, MAS treatment resulted in a higher C:N, while the MH resulted in a higher C:P and N:P in the topsoil. Despite stable total phosphorus (TP), elevated C:P and N:P ratios under MH indicated emerging P limitation in restoration. Therefore, long-term monoculture shrub, arbor, and herbaceous vegetation effectively enhances soil fertility in arid sandy lands through long-term SOC accumulation and humic substance formation. Full article

Background/Objectives: Chronic obstructive pulmonary disease (COPD) is characterized by incomplete recovery of airflow blockage; however, effective therapeutic agents that can prevent lung function deterioration are limited. East Asian herbal treatments have gained attention for their potential benefits in managing COPD. This study aimed to evaluate the inhibitory effects of Gyeongok-go (GOG) on lung injury in a COPD mouse model. Methods: Lipopolysaccharide (LPS)-induced alveolar macrophage (MH-S) cells were treated with GOG (50, 100, 200, and 400 μg/mL), and analyzed using enzyme-linked immunosorbent assay (ELISA). C57BL/6 mice were challenged with cigarette smoke extract and LPS and then treated with vehicle only, dexamethasone (3 mg/kg), or GOG (100, 200, or 400 mg/kg). Bronchoalveolar lavage fluid (BALF) or lung tissues were analyzed using cytospin, ELISA, real-time PCR, flow cytometry, hematoxylin and eosin, and Masson’s trichrome staining. Results: Treatment with GOG decreased tumor necrosis factor-alpha (TNF-α) and interleukin (IL)-6 expression in LPS-challenged MH-S cells. In COPD mice, GOG significantly decreased the elevated numbers of neutrophils, total cells, macrophages, and Gr-1⁺/Siglec-F, Gr-1⁺/CD11b⁺, and CD44^high/CD62L⁻ cells. It also downregulated the expression of TNF-α, IL-17A, macrophage inflammatory protein-2 (MIP2), and CXC chemokine ligand-1 in BALF. GOG also inhibited the increase in Mip2, Cox-2, and Trpv1 mRNA expression. Moreover, GOG prevented the increase in the number of total cells, neutrophils, Gr-1⁺/Siglec-F, Gr-1⁺/CD11b⁺, CD44^high/CD62L⁻, and CD21⁺/CD35⁺/B220⁺ cells in lung tissues. Notably, GOG decreased the severity of lung injury. Conclusions: Overall, these findings indicate that GOG alleviates lung injury, suggesting its potential in the treatment of COPD. Full article

Background/Objectives: Impairment in pulsatile insulin release contributes to insulin resistance and is one of the earliest markers of developing type 2 diabetes. Insulin delivered to the liver in pulses has a stronger glucose-lowering effect than continuous insulin delivery. Whether pulsatility benefits the islet itself is an open question. We previously showed that reducing glucokinase activity with the glucokinase inhibitor D-mannoheptulose (MH) improves function in islets exposed to prolonged hyperglycemic conditions. In this study, we test whether pulsatile vs. continuous delivery impacts the effectiveness of MH in islets. Methods: Islets were exposed to high-glucose conditions (20 mM glucose) for 24 or 48 h to induce early adaptations to hyperglycemia. We then used a specially designed perifusion system to impose pulsatile activity by exposing mouse islets to 3 min of MH in 20 mM glucose and 3 min of only high levels of glucose. Islets given intermittent MH for 18 h were compared with continuous delivery of MH at a full (2.5 mM) or half (1.25 mM) dose. Results: MH delivered by the forced oscillatory system reversed the effects of hyperglycemia and restored glucose sensing more effectively than continuous delivery. Specifically, fura-2AM imaging of intracellular calcium showed that islets given pulsatile MH had greater reductions in the elevated basal calcium caused by hyperglycemic conditions, improved the glucose stimulation index, and improved phase 0 response (indicating glucose-stimulated calcium uptake by the endoplasmic reticulum). Conclusions: These findings suggest that the loss of oscillatory glucose metabolism in islets contributes directly to beta-cell dysfunction. Full article

The aim of this study was to investigate the ability of sewage sludge-derived biochar to remove PO₄-P from real biologically treated wastewater. Biochar was produced via the pyrolysis of anaerobically digested sewage sludge pretreated with nanoscale zero-valent iron (nZVI) at concentrations of 3%, 1.5%, and 0.5% (w/w, based on total solids). A sample without nZVI addition was used as a control. The properties of biochar samples were analyzed, including elemental composition, specific surface area, and pore size. PO₄-P removal was evaluated using both batch adsorption and column experiments. The highest adsorption capacity determined in the batch experiment was 2.5 mg/g. When wastewater was passed through columns packed with 0.3–0.6 mm biochar particles at a hydraulic loading rate of 1 m/h, a 3-fold-higher phosphorus retention capacity was obtained in the range of 7.26–7.82 mg/g. The column containing biochar derived from sewage sludge with 3% nZVI accumulated 7% more PO₄-P than the biochar without nZVI. All columns effectively removed phosphates from wastewater (efficiency > 80%) due to the chemical composition of biochar, which mainly contained Fe and Ca elements. In contrast to the batch experiment, the columns were subject to the biological sorption of phosphates via microorganisms, physical retention between particles, and the formation of precipitates on the surface of a column. Full article

The lipid composition of meat intended for hamburger patties can be modified through genetic selection in cattle. Cattle carrying the F94L allele have been reported to produce leaner meat with a higher proportion of unsaturated fatty acids than those without this allele. However, evidence concerning the nutritional quality and sensory acceptability of hamburgers produced with meat from these cattle remains limited. In this study, the nutritional quality and sensory properties of hamburger patties formulated with meat and subcutaneous fat from cattle carrying the F94L allele were compared with those of noncarrier animals. Patties were formulated with two fat levels (high fat, HF; low fat, LF) and analyzed under raw and cooked conditions. Compared with the Control formulations, the F94L/− formulations possessed a higher polyunsaturated fatty acid content, with absolute differences of +1.16 in the raw state and +2.04 after cooking compared with the Control formulations. In addition, the PUFA/SFA ratio was higher in the cooked samples (+0.04; p < 0.05). In the sensory analysis, the formulations were not rejected; however, Control HF obtained the highest acceptance score (6.49). These results suggest that the use of meat from F94L/− cattle allows the formulation of hamburger patties with a more favorable fatty acid profile, but with no improvement in sensory acceptance compared with the noncarrier control. Full article

Tight conglomerate reservoirs are characterized by strong heterogeneity, significant in-situ stress differences, and unbalanced fracturing stimulation, which make fracture pressure prediction challenging and severely restrict the effectiveness of reservoir stimulation and ultimate recovery. Although acid pretreatment is an effective means to reduce fracture pressure, its quantitative relationship with fracture pressure remains unclear. There is an urgent need to establish a systematic method that integrates reservoir heterogeneity characterization, data augmentation, and intelligent prediction. Aiming at the tight conglomerate reservoir in the MH Block, this study proposes an intelligent fracture pressure prediction and acid pretreatment optimization method that integrates Self-Organizing Maps (SOMs), Generative Adversarial Networks (GANs), and Transformer models. First, SOM is used to perform unsupervised clustering of logging parameters to identify different geological feature categories and achieve fine-scale characterization of reservoir heterogeneity. Second, to address the issue of limited samples within each cluster, GAN is employed for high-quality data augmentation to expand the training sample set. Finally, a fracture pressure prediction model is constructed based on the Transformer architecture, and the influence of acid treatment parameters on fracture pressure is quantitatively analyzed using the SHAP method and laboratory experiments. The results show that the proposed model achieves a coefficient of determination (R²) of 0.93, a root mean square error (RMSE) of 2.38 MPa, and a mean absolute percentage error (MAPE) of 2.02% on the test set, with prediction accuracy significantly outperforming benchmark models such as BPNN, XGBoost, and LSTM. Ablation experiments verify that both the SOM clustering and GAN augmentation modules effectively enhance model performance. Analysis of acid treatment parameters indicates that hydrofluoric acid (HF) concentration is the dominant factor influencing fracture pressure reduction, and the mud acid system exhibits a stronger synergistic effect compared to the single hydrochloric acid system. Reasonable optimization of acid concentration and dosage can significantly reduce fracture pressure (3.14–5.28 MPa). This method provides a theoretical basis and engineering guidance for accurate fracture pressure prediction and optimal design of acid pretreatment in tight conglomerate reservoirs. Full article

Background: Examining the relationship between burnout and absenteeism is important for understanding how chronic occupational stress translates into economic costs, reduced productivity, and deterioration in the health of nursing staff. The aim of this study was to evaluate absenteeism among nursing staff and its association with burnout from a gender perspective. Methods: A total of 154 nursing professionals with permanent contracts were included. An interview was conducted, which included the collection of sociodemographic data, characteristics related to their employment status, and the Maslach Burnout Inventory questionnaire in its Spanish-validated healthcare personnel version. The absenteeism rate was calculated using information from the hospital’s human resources department. The Mantel–Haenszel test was used to identify the association between burnout and absenteeism from a gender perspective. A p-value < 0.05 was considered statistically significant. Results: The prevalence of burnout was 70.1%; 52.6% reported absenteeism in 2024. The general nursing category was significantly associated with burnout (p = 0.039). Although no association was found between burnout and overall absenteeism, holding multiple jobs was identified as a determinant of partial absenteeism (p < 0.05). The hospital absenteeism rate was 4.8%. No statistically significant difference was found between burnout, gender, and absenteeism, with an adjusted odds ratio of 1.386 (95% CI: 0.75–2.65) after controlling for the effect of gender (χ²_MH = 0.672, df = 1, p = 0.412). Conclusions: Nursing staff present a critical level of burnout. No statistically significant difference was found between burnout, gender, and absenteeism, which could indicate that gender roles in the workforce may be changing in our population. Full article

This study provides a theoretical assessment of the structural, electronic, and thermal properties of MgMH₃ (M = Mn and Ni) compounds using the full-potential linearized augmented plane wave (FP-LAPW) method, with a range of modern functionals. The thermoelectric properties that are surveyed here relate to the power factor, the dimensionless thermoelectric figure of merit, the thermal conductivity, and the electrical conductivity that are associated with these compounds. The study finds that MgNiH₃ has superior thermoelectric properties compared to MgMnH₃. The analysis of the band structure reveals that both materials conduct electricity like metals, as there is no energy gap (0 eV), indicating that the conduction and valence bands overlap. The thermal conductivity was found to be linearly related to an increase in temperature, whereas the electrical conductivity varied with temperature. At elevated temperatures, the maximum power factor values reach 1.45 × 10⁻³ W/(K².m) for MgMnH₃ and 1.96 × 10⁻³ W/(K².m) for MgNiH₃ at 900 K. Upon examination of the electronic states, the contributions to the metallic nature of these hydrides come largely from the Ni and Mn orbitals. This type of prospective information on the potential of MgNiH₃ and MgMnH₃ in industrial applications, especially thermoelectric applications, is a valuable contribution. Understanding their thermal and electronic structure will demonstrate their potential for industry. Full article

Background and Clinical Significance: Vascular lesions of the face, particularly arteriovenous malformations (AVM) and mixed hemangiomas (MH), pose significant diagnostic and therapeutic challenges because of their complex anatomy, unpredictable behavior, and high risk of bleeding. Surgical planning should be individualized and often requires a staged approach with meticulous interdisciplinary coordination to ensure patient safety. The presence of a concomitant odontogenic infection further complicates management, as local inflammation may exacerbate vascular instability and increase the risk of life-threatening complications. Local inflammation and infection might cause some life-threatening conditions, especially when an abscess occurs in the area of any vascular lesion. Ensuring that the oral cavity is free from potential odontogenic infections is a particularly important issue in many complex cases, especially in patients treated for oral, head, and neck cancer or in those with other coexisting morbidities affecting the oral and facial regions. Case Presentation: A 72-year-old man was referred for management of a severe odontogenic infection associated with an extensive facial vascular lesion. The patient’s medical history was significant for arterial hypertension and chronic liver dysfunction (CLD) of unclear etiology. Complete blood testing, including coagulation assessment and liver ultrasonography, was performed, with no contraindication to surgery identified. The scope of odontogenic-related infections was scheduled for simultaneous removal during initial surgery. Preparation for surgery included the local application of sclerotherapy agents. Conclusions: Quite often, a routine panoramic radiograph can help in assessing the status of bone and dentition to undertake all necessary treatment. Severe odontogenic disease, including multiple retained roots, periapical infections, and odontogenic cystic lesions in the context of poor oral hygiene, may lead to the occurrence of possible inflammation. In case of any vascular lesion, a careful diagnostic and therapeutic strategy is needed. This case report highlights that maintaining an infection-free oral environment is a critical component of care in patients with complex facial MH and should be regarded as an essential element of overall treatment planning. Full article

The rapid proliferation of Conversational Artificial Intelligence Assistants (CAIs) has transformed access to mental health information through freely accessible web interfaces, mobile applications, and public APIs (Application Programming Interfaces), yet systematic methodologies for their evaluation remain limited. This paper introduces SELCAI-MH, a multicriteria framework for CAI evaluation and selection. This framework integrates four complementary multicriteria methods: Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Complex Proportional Assessment Method (COPRAS), and Combinative Distance-based Assessment (CODAS), capturing distance-based, compromise-based, proportional, and negative-ideal logics, and proposes SOLAG, an aggregation method that produces a consensus ranking across methods. SELCAI-MH employs a dual evaluation mechanism combining psychiatric expert assessment with AI-based scoring, expert-derived criterion weights, and domain-relevant conversational datasets. The framework is applied to nine internet-accessible CAIs: proprietary platforms (ChatGPT 5.2, Claude Sonnet 4.5, Gemini 1.5 Flash, Perplexity Sonar, Bing AI/Copilot) and open-source Llama variants deployed via cloud inference endpoints. Using a set of anxiety-related questions and CAI responses, evaluated across seven criteria, Claude Sonnet 4.5 emerged optimal, followed by ChatGPT 5.2 and Gemini 1.5 Flash. SOLAG produced highly consistent rankings across the four multicriteria decision-making (MCDM) methods (Spearman ρ ≥ 0.98). Overall, SELCAI-MH provides a structured and reproducible decision-support framework for selecting accessible CAIs in sensitive mental health contexts. Full article