Search Results (47,649)

MnZn ferrites for power electronics require a well-controlled sintering window to balance high initial permeability (µ_i) with low power loss (P_cv). Here, an L9 (3³) orthogonal design was employed to quantify the main effects of sintering temperature, holding time, and oxygen partial pressure on µ_i and P_cv within the investigated processing window, enabling rapid mapping of feasible sintering windows. The orthogonal analysis identifies the relative significance of each factor and reveals a clear performance trade-off between µ_iand P_cv. For maximising µ_i, the optimal sintering condition was 1250 °C, 4 h holding time, and 3.5% oxygen partial pressure, yielding a µ_i of 3453 and a P_cv of 466 mW/cm³ at 100 kHz/200 mT. For minimising P_cv, the optimal condition was 1250 °C, 3.5 h holding time, and 5% oxygen partial pressure, resulting in a µ_i of 2678, with P_cv of 400 mW/cm³ at 100 kHz/200 mT and 182 mW/cm³ at 500 kHz/50 mT. Targeted verification together with XRD, SEM grain-size statistics, and magnetic-loss separation were used to strengthen the process-structure-property interpretation. Overall, the orthogonal-screening-plus-verification strategy provides a practical framework for predicting application-relevant performance trends of MnZn ferrites within a defined processing window. Full article

In signal processing and information analysis, the detection and identification of anomalies present in signals constitute a critical research focus. Accurately discerning these deviations using probabilistic, statistical, and information-theoretic methods is essential for ensuring data integrity and supporting reliable downstream analysis. Outlier detection in functional data aims to identify curves or trajectories that deviate significantly from the dominant pattern—a process vital for data cleaning and the discovery of anomalous events. This task is challenging due to the intrinsic infinite dimensionality of functional data, where outliers often appear as subtle shape deformations that are difficult to detect. Moving beyond conventional approaches that discretize curves into multivariate vectors, we introduce a novel framework that projects functional data into a low-dimensional space of meaningful features. This is achieved via a tailored weighting scheme designed to preserve essential curve variations. We then incorporate the Mahalanobis distance to detect directional outlyingness under non-Gaussian assumptions through a robustified bootstrap resampling method with data-driven threshold determination. Simulation studies validated its superior performance, demonstrating higher true positive and lower false positive rates across diverse anomaly types, including magnitude, shape-isolated, shape-persistent, and mixed outliers. The practical utility of our approach was further confirmed through applications in environmental monitoring using seawater spectral data, character trajectory analysis, and population data underscoring its cross-domain versatility. Full article

Background: Advanced resistance training systems are widely used in practice, yet their comparative effectiveness for hypertrophy and maximal strength in recreationally trained adults remains unclear. This systematic review and meta-analysis evaluated whether advanced methods provide superior adaptations to traditional multiple-set training and whether specific techniques confer distinct advantages for hypertrophy and maximal strength. Methods: A preregistered systematic search identified randomized and non-randomized controlled trials comparing advanced resistance training systems with traditional multiple-set protocols in recreationally trained adults aged 18–45 years. Outcomes included muscle hypertrophy and maximal strength. Random-effects and fixed-effects models with Knapp–Hartung adjustments were applied, and moderator analyses examined method type, volume equivalence and proximity to failure. Results: Twenty-three studies met the inclusion criteria. When all outcomes were pooled, advanced systems produced a small but statistically significant advantage over traditional training (g = 0.159). Strength outcomes showed a moderate, significant benefit for advanced methods (g = 0.351), whereas hypertrophy effects were small and non-significant (g = 0.046). Rest-pause training demonstrated a modest hypertrophic advantage, while velocity-based training and eccentric overload contributed primarily to strength improvements. Drop sets, tempo-controlled training and cluster-type protocols produced adaptations comparable to traditional sets when volume and effort were matched. Across models, τ² estimates were near zero, indicating minimal between-study heterogeneity. Conclusions: Advanced resistance training systems can be used effectively in recreationally trained adults and may offer advantages for maximal strength without compromising hypertrophy. Their hypertrophic superiority is not supported at the aggregate level, and their use should be guided by specific goals, constraints and individual preferences rather than expectations of universally greater muscle growth. Full article

Mining exploitation and copper smelting in Bor (Serbia) have led to long-term environmental pollution with toxic metals, primarily copper (Cu) and arsenic (As). The aim of this research was to assess the contamination of arable land and the bioaccumulation of metals in wheat (Triticum aestivum L.), to determine significant differences in copper and arsenic concentrations between the soil and specific wheat tissues across six locations, and to evaluate environmental and health risks in agricultural areas around the Zijin Copper Mine, Serbia. Sampling was carried out at six locations (Brezonik, Veliki Krivelj, Oštrelj, Slatina, Zlot, and Gornjane; L1–L6, respectively). Analyses of soil and wheat to determine toxic elements were performed using the ICP-MS method, while contamination was assessed using descriptive statistics and a combination of several indices (CV, Igeo, EF, CF, Er, RI, PLI, BAF, TF, and HRA). In addition to Cu and As, accompanying elements (Fe and Al) were also included in the analysis, due to their importance as indicators of geogenic and anthropogenic origin. The analysis of the distribution within the root, stem, leaf, and grain of wheat enabled the assessment of bioaccumulation (BAF and TR) and implications for food safety (HRA). The results showed that concentrations of Cu and As at several locations significantly exceed the regulatory limit values, with Slatina-L4 and Oštrelj-L3 identified as the most polluted areas, while Gornjane-L6 can be considered a reference location with minimal risk. Background values were taken from location L6, considered a reference site due to the absence of direct mining and industrial influence (B_Cu—20 mg/kg, B_As—10 mg/kg, and B_ref._Al—33,300 mg/kg). The MANOVA analysis revealed statistically significant differences in copper and arsenic concentrations between the soil and various wheat tissues, with the effect being more pronounced for arsenic. The integrated analysis of indices (RI and PLI) confirmed the pronounced anthropogenic impact and location-specific risks, emphasizing the need for continuous monitoring, locally adapted remediation strategies, and sustainable land management. Full article

Natural disasters disrupt maritime operations; yet, their environmental consequences remain underexplored. This study quantifies CO₂ emission changes following the February 2023 İskenderun Bay earthquakes (7.6 Mwg and 7.5 Mwg) using AIS-derived port visit data and graph neural network modeling. Analyzing 25,837 port visits across a 36-month period (January 2022–December 2024), we compared emissions during baseline (pre-earthquake), acute disruption (February–June 2023), and recovery phases. Results revealed a statistically significant 35.9% increase in per-visit CO₂ emissions during the acute phase (t = 11.79, p < 0.001, Cohen’s d = 0.27), driven by extended port visit durations (from 77.87 to 105.82 h). Counterfactual analysis estimated 27,574 tonnes of excess CO₂ emissions directly attributable to earthquake disruption. Network analysis showed a 23.8% reduction in edge density during the acute phase. The graph neural network (GNN) emission prediction model achieved R² = 0.985 (baseline) and R² = 0.997 (recovery) in predicting emission patterns, while the acute phase showed predictability collapse (R² = −1.591). These findings demonstrate that seismic events generate sustainability-relevant externalities beyond immediate physical damage, and that quantifying disruption-driven excess emissions supports sustainability-oriented port resilience planning and more robust maritime emission accounting (e.g., under the EU MRV framework). Full article

Background and Objectives: Functional Ankle Instability (FAI) is a sequela of ankle sprains; however, its associated variables in volleyballers have not been studied. This study aimed to determine the prevalence of FAI and the association between FAI and its associated variables in volleyball players. Materials and Methods: An observational study with a sample size of 128 male volleyballers, aged 18 years and older, was conducted using the Arabic-Identification of Functional Ankle Instability (Ar-IdFAI) questionnaire. The prevalence of FAI was analyzed in terms of frequency and percentage. The Mann–Whitney U test, Spearman’s test, and t-test were used to analyze the associations between the demographic variables and the categorical variables, and a logistic regression model was applied to identify the independent associations with FAI. Statistical significance was set at p < 0.05. Results: The prevalence of FAI in the sample was 44.53%. Bivariate analysis and the regression model indicated no significant direct association between FAI and age, Body Mass Index (BMI), playing duration, weekly training hours, or limb dominance in this sample. Conversely, historical injury burden showed strong and statistically significant associations with FAI (Cramér’s V = 0.59–1.00), with “giving way” demonstrating perfect separation. The logistic regression model showed an acceptable fit (p = 0.676) and moderate explanatory power (Nagelkerke R² = 0.540), with excellent discriminatory performance Area Under the Curve (AUC = 0.855) driven primarily by injury-related variables. Conclusions: FAI is highly prevalent among male volleyball players and is linked to injury history rather than demographic or training characteristics. Injury-related characteristics, including previous ankle injury, reinjury, and episodes of ankle “giving way”, demonstrated strong associations with the presence of Functional Ankle Instability, to be interpreted as descriptive associations rather than a causal link due to methodological structure. Full article

The successful integration of autonomous vehicle (AV) technologies into future mobility systems depends not only on technological maturity but also on user acceptance and perceived value. While existing research has identified several demographic determinants of AV acceptance, the role of educational background—particularly differences between humanities and STEM graduates—has received limited attention within the context of user-centred mobility research. This study examines how educational background and gender influence attitudes toward autonomous vehicle technologies using a large-scale survey conducted in Hungary (N = 8663). The analysis combines non-parametric statistical tests with effect size measures, exploratory factor analysis, and structural equation modelling (SEM) to capture both group differences and underlying attitudinal mechanisms. The results indicate no meaningful differences between humanities and STEM graduates in overall acceptance of autonomous vehicles or trust in the technology. Statistically significant differences are observed only in two dimensions: willingness to spend on autonomous driving features and expectations regarding improved travel speed. However, effect size analyses reveal that these differences are negligible in practical terms, indicating substantial overlap in user attitudes. SEM results show that educational background does not directly determine acceptance of autonomous vehicle technologies. Instead, its influence is mediated through three latent attitude dimensions relevant for electric and autonomous mobility adoption: willingness to invest, functional expectations (e.g., time savings and convenience), and safety orientation. Humanities graduates—especially men—exhibit slightly higher financial openness toward autonomous features, whereas STEM graduates place greater emphasis on functional performance. Safety-related attitudes play a central mediating role, with gender-specific patterns. By integrating large-sample effect size interpretation with SEM-based modelling, this study provides a nuanced understanding of user acceptance of autonomous vehicle technologies. The findings suggest that differences between educational groups reflect variations in attitudinal emphasis rather than fundamental divides, offering relevant insights for user-centred AV development, mobility policy design, and communication strategies in the transition toward automated and electric mobility systems. Full article

Alzheimer’s disease (AD) is the most common neurodegenerative disorder worldwide, for which aging represents the main risk factor. As the global elderly population expands, the prevalence of Alzheimer’s disease escalates rapidly. Notably, as AD brain lesions may start 15–20 years before the appearance of the first symptoms, early diagnosis or prognosis of AD is of paramount importance for better patient treatment. Based on the absence of effective cure or early diagnosis of AD, this meta-analysis investigates the differentially expressed genes between Alzheimer’s and a healthy brain and identifies genes that can serve as risk factors for the disease or biomarkers of diagnostic, prognostic, or pharmacological value. Microarray datasets were collected from public repositories, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. Quality control and data normalization were performed. Differentially expressed gene (DEG) lists were created for each study and combined through a Mosteller–Bush meta-analysis, resulting in a final list of DEGs. This list was filtered using an adjusted p-value cut-off of 0.001, and the included statistically significant DEGs were subjected to enrichment analyses. A total of eight microarray studies were identified, producing a combined list of 4218 DEGs, of which 1944 were up-regulated and enriched for immune response processes, and 2274 were down-regulated and enriched for synapse-related pathways. This meta-analysis reveals a distinct transcriptomic profile in Alzheimer’s disease characterized by the prevalence of immune response and inflammation alongside the collapse of essential synaptic and neuronal signaling. Full article

Vertigoheel is a multicomponent medicinal product for the treatment of vertigo and dizziness, containing Anamirta cocculus, Conium maculatum, Ambra grisea, and Petroleum rectificatum. Although clinical efficacy has been reported, the chemical composition and underlying mechanisms remain incompletely characterized. Here, we applied ultra-high-performance liquid chromatography coupled to time-of-flight mass spectrometry (UHPLC-ToF-MS) to profile extracts of each ingredient and the final formulations. Untargeted analysis revealed 68,622 molecular features, and multivariate statistics highlighted ingredient-specific metabolites. Representative markers included picrotoxinin and picrotin from Anamirta cocculus, coniine and N-methylconiine from Conium maculatum, ambrinol and ambroxide from Ambra grisea, and santalyl phenylacetate and mercaptostearic acid from Petroleum rectificatum. Two compounds per ingredient were further quantified by targeted UHPLC-MS/MS, confirming their presence in drops and tablets at nanogram-per-dose levels with moderate variability across batches. These findings demonstrate that Vertigoheel retains characteristic constituents from its natural sources in all tested formulations. The established protocol enabled absolute quantification of neuroactive molecules such as picrotoxinin and coniine with minimal work-up. This molecular characterization provides new insight into Vertigoheel’s composition and supports further investigation of its mechanism of action using network pharmacology approaches. Full article

Background: The incidence of patients with nontuberculous mycobacterial pulmonary disease (NTM-PD) complicated by chronic pulmonary aspergillosis (CPA) has been increasing. CPA is known to be associated with complex treatment regimens and a poor prognosis. However, data from mainland China remain scarce. This single-center retrospective study aimed to evaluate the clinical characteristics, risk factors, and prognoses of patients with concurrent CPA and NTM-PD. Methods: We conducted a retrospective review of the medical records of 248 patients diagnosed with NTM-PD. Risk factors for CPA were analyzed via multiple logistic regression, followed by survival analysis. Results: Among the 248 patients with NTM-PD, 66 (26.6%) were diagnosed with CPA. Independent risk factors for NTM-PD and CPA coinfection included male sex (OR 2.13, 95% CI: 1.03–4.47), dyspnea (OR 27.9, 95% CI: 4.24–570), cavity (OR 5.95, 95% CI: 2.76–13.9), use of oral corticosteroids (OR 4.28, 95% CI: 1.13–16.6), and interstitial lung disease (OR 15.5, 95% CI: 1.89–361). The wide confidence intervals for some risk factors reflect limited precision. The Kaplan–Meier survival curves indicated a significant divergence between the NTM-PD group and the NTM-PD with CPA group (log-rank test, p = 0.00039). However, the adjusted hazard ratio was not statistically significant (HR 2.01, 95% CI: 0.66–6.12, p = 0.217). Conclusions: In patients with NTM-PD, the presence of concurrent CPA was associated with higher unadjusted mortality. Clinicians should maintain a high index of suspicion for CPA to ensure prompt diagnosis and treatment, particularly in high-risk individuals. Full article

Seed priming studies commonly emphasize growth and physiological responses, yet ionomic regulation and tissue-specific nutrient allocation under salinity stress remain poorly explored, particularly in underutilized crops such as Bambara groundnut (Vigna subterranea L.). This study investigated whether Mg(NO₃)₂ seed priming, previously shown to enhance salt tolerance, is associated with consistent ionomic patterns in contrasting Bambara groundnut genotypes (BGN-14 and BGN-25). Seeds were primed with 0.03% Mg(NO₃)₂ and grown under control or saline conditions (200 mM NaCl) for five weeks. Shoot and root tissues were analyzed for macro- and micronutrient composition using ICP-OES. In BGN-14, salinity caused a marked reduction in shoot fresh weight (−49.5%, p < 0.05), whereas Mg(NO₃)₂ priming largely mitigated this effect under salinity (−0.4%, p > 0.05). Root fresh weight declined numerically under salt stress (−70.1%) and primed + salt conditions (−45.5%), but these changes were not statistically significant. Shoot dry weight increased significantly in primed plants (+83.5%, p < 0.05), while salinity reduced SDW (−58.4%); primed + salt plants maintained SDW near control levels (+2.6%). In BGN-25, root biomass was unaffected by treatments, whereas salinity significantly reduced shoot biomass relative to primed plants, with a consistent trend of primed > control > primed + salt > salt. Salinity increased the Na⁺/K⁺ ratio, particularly in roots. In BGN-14, the root Na⁺/K⁺ ratio increased significantly from 1.07 to 4.49 (p < 0.05), indicating enhanced Na⁺ accumulation, while shoot ratios increased non-significantly. BGN-25 showed a more moderate increase in shoot ratios and a pronounced rise in root ratios. Principal component analysis revealed distinct nutrient clustering, with Na, Fe, and Al loading strongly under salinity, while Ca, K, Mg, and Cu aligned with improved physiological performance. Although differences between salt and primed + salt treatments were often not statistically significant, several ion ratios and nutrient relationships were numerically enhanced under Mg(NO₃)₂ priming. This study builds upon earlier physiological findings (where BGN-14 consistently exhibited a stronger positive response to Mg(NO₃)₂ priming, outperforming BGN-25 under salt stress) and provides exploratory, hypothesis-generating evidence that Mg(NO₃)₂ priming may contribute to salinity tolerance through coordinated ionomic adjustments, including altered Na⁺ allocation and improved nutrient balance, rather than complete Na⁺ exclusion. These findings highlight the relevance of ionomic responses in understanding stress adaptation in underutilized legume crops. Full article

Background: Numerous studies have demonstrated the impact of post-transplant immunosuppressive therapy on cancer development, particularly in the skin. Despite the growing number of observations, there is still a lack of comprehensive analyses assessing the influence of specific immunosuppressive regimens on the development of melanoma in kidney transplant recipients. The aim of this study was to describe the incidence and temporal patterns of cutaneous melanoma (CM) among kidney transplant recipients in Poland between 2010 and 2022, with particular focus on recipients treated with calcineurin inhibitor (CNI)-based immunosuppression, including cyclosporine (CsA) and tacrolimus (TAC). Methods: This nationwide, descriptive analysis was conducted using comprehensive national administrative data obtained from the Polish National Health Fund (PNHF) and the Polish National Cancer Registry (PNCR). The study assessed the incidence of cutaneous melanoma and temporal trends over the study period. Results: Melanoma skin cancer occurred in 27 cases observed in a population of 12,205 kidney transplant recipients over 13 years of follow-up, corresponding to a final cumulative incidence of 0.23% (95% CI: 0.15–0.34). Calcineurin inhibitor (CNI)-based regimens in kidney transplant recipients were associated with significantly lower risk profiles over 10 years, with only nine cases observed in a cohort of 7107 patients, culminating in a cumulative incidence of 0.13% (95% CI: 0.06–0.24). The stratified analysis of CM incidence under CNI-based immunosuppressive regimens by calcineurin inhibitor type revealed a modest cumulative risk in the TAC subgroup, reaching 0.14% (95% CI: 0.06–0.26) by year 10, with all nine observed cases occurring exclusively in this group, while the CsA subgroup reported zero events throughout the follow-up period. Risk differences progressively increased to 0.14% (95% CI: −0.20 to 0.26) by year 10, but they were not statistically significant in any year (p ≥ 0.230). Conclusions: Although all melanoma cases occurred in the TAC subgroup, the data do not allow us to conclude that TAC confers a higher risk than CsA. This lack of significance likely reflects both the rarity of events and the limited statistical power to detect small differences between TAC and CsA. These results highlight the need for careful dermatologic monitoring in all kidney transplant recipients, while the choice of calcineurin inhibitor should be individualized based on patient-specific factors. Full article

Background: Distal tibial fractures (DTFs) are a major cause of post-traumatic osteoarthritis (PTOA). The risk of conversion to total ankle arthroplasty (TAA) or ankle fusion (AF) after DTFs remains unclear, and the current literature provides heterogeneous and often incomplete data. The aim of this systematic review was to evaluate the incidence of TAA and AF following DTF-related PTOA and to explore potential predictors of conversion, including initial treatment strategy. Methods: A systematic review was conducted according to PRISMA guidelines. The PICO framework was applied during the study design and literature search phase to define the research question and eligibility criteria. Studies reporting adult patients with a history of DTFs who later developed PTOA and underwent TAA or AF were included. Descriptive statistics were performed. Study-level proportions of conversion to TAA, AF, or both were analyzed using random-effects meta-analysis with logit transformation. Results: Eight studies comprising 190,383 fractures met the inclusion criteria. Overall, 31,269 patients underwent TAA or AF, corresponding to a conversion rate of 16.4%. The pooled conversion incidence from the random-effects model was 5.6%, with considerable heterogeneity (I² ≈ 100%). When procedures were analyzed separately, the pooled incidence was 0.25% for TAA and 0.76% for AF. Conclusions: The risk of conversion to TAA or AF after DTFs appears to be relatively low, despite the high prevalence of PTOA. The higher conversion rate observed in surgically treated fractures likely reflects the complexity of the initial fracture rather than the failure of surgical management itself. Level IV, systematic review of retrospective studies. Full article

Background: Low birth weight (LBW) is one of the most significant health issues worldwide, especially in countries with fewer resources. No systematic reviews or meta-analyses on LBW have been conducted in Sudan, the third largest African country. Methods: A systematic review and a meta-analysis were conducted to assess the pooled prevalence of LBW in Sudan and the associated factors. PubMed, Google Scholar, and ScienceDirect were searched for studies on LBW in Sudan. The meta-analysis was performed by calculating the pooled prevalence of LBW. The meta package in R was used for statistical analysis. Results: The final sample comprised 10 studies, with 10,043 neonates enrolled. The overall pooled prevalence of LBW was 13.0% (95% CI [13.0, 14.0]; I² = 47.0%, p = 0.05), without significant heterogeneity. Primiparity (adjusted odds ratio [AOR] = 1.4, 95% CI [1.1, 2.1]), a short interpregnancy interval, lack of iron–folic acid supplementation (AOR = 3.33, CI [1.47, 5.88]), a low level of antenatal/perinatal care (AOR = 2.10, 95% CI [1.30, 3.57]), maternal undernutrition (AOR = 1.66, 95% CI [1.09, 2.53]), and decreasing gestational age of pregnancy (AOR = 0.80, 95% CI [0.66, 0.96]) were associated with LBW in different studies. In three studies, anemia was associated with LBW. Conclusions: This review reveals a high prevalence of LBW in Sudan. The factors identified in this review may help health planners and policymakers design and implement preventive interventions for LBW. Full article

To address the information-processing burden faced by consumers in green consumption markets due to complex carbon footprint labels, opaque certification standards, and vague descriptions of environmental benefits, this study proposes a generative artificial intelligence (GenAI)-based precision recommendation mechanism for green products. The mechanism aims to enhance cognitive fluency and promote low-carbon purchase decisions. An experimental system, termed Eco-GenRec, is developed by integrating large language models (LLMs), multimodal generation, and retrieval-augmented generation (RAG) techniques to enable personalized presentation of green product information. Based on inferred user cognitive styles, the system transforms product information into chart-based representations for analytical users or emotionally framed scenario narratives for intuitive users. This study is conducted on a web-based simulated shopping platform and employs a fully randomized design. A total of 1000 participants are randomly assigned to either a standardized information display group (control group) or an Eco-GenRec-generated display group (experimental group). Participants are drawn from diverse socioeconomic backgrounds and cover a wide age range. The sample exhibits substantial demographic diversity, which enhances the representativeness of the findings. Cognitive fluency and low-carbon purchase conversion rates are measured as the primary outcomes. The results show that the Eco-GenRec group achieves a significantly higher cognitive fluency score (M = 5.68, SD = 0.89) than the control group (M = 4.60, SD = 1.01). This represents an increase of 23.4% (t = 18.34, p < 0.001, effect size d = 1.17). In addition, the low-carbon purchase conversion rate in the experimental group (36.3%) is significantly higher than that in the control group (17.6%). The absolute increase of 18.7% is statistically significant (χ² = 70.28, p < 0.001, effect size Cramér’s V = 0.265). Under conditions of high cognitive-style matching, the conversion rate improvement reaches 27.2%. Mechanism analysis shows that cognitive fluency mediates the relationship between GenAI-based recommendations and purchase intention. By transforming abstract environmental parameters into intuitive and easily interpretable content, artificial intelligence reduces information-processing burden and activates positive affect and trust among consumers. Overall, this study empirically validates the effectiveness of GenAI in green product recommendation. It provides a practical pathway for addressing the “comprehension barrier” in green consumption and extends the theoretical boundaries of research on cognitive fluency and low-carbon decision-making. Full article