Search Results (26,470)

As an important aerodynamic configuration of the new-generation UAV, the dorsal S-shaped inlet’s performance is affected by the complex coupling of inflow conditions and the boundary layer ingestion effect. To investigate the influence mechanisms of these factors on inlet performance, CFD based on the scale-adaptive simulation (SAS) turbulence model is used to systematically analyze the flow field and performance of a UAV dorsal S-shaped inlet within a typical flight envelope. It is found that with increasing Mach number (0.6–0.9), the exit total pressure recovery decreases significantly, while the circumferential distortion coefficient almost doubles. As the angle of attack varies from −10° to 10°, a slight decrease in total pressure recovery is observed, but distortion improves due to a relatively stable separation region. Changes in sideslip angle have minimal impact on overall performance but notably alter the symmetry of the vortex system, resulting in a decrease in distortion coefficient. Additionally, at a specific Mach number, back pressure correlates positively with inlet performance. The increase in back pressure can effectively inhibit the flow separation and enhance the total pressure recovery, while the distortion coefficient decreases. The research results provide an important theoretical basis for the design optimization of the new-generation UAV. Full article

The unit costs of power generation of onshore wind and photovoltaics in China have dropped rapidly and significantly since 2010. Recent studies have indicated that the learning effect on cost reduction could have been overestimated due to the exclusion of the equipment-level installed capacity and the price of capital. To address this estimation bias, we constructed a research framework comprising a one-factor analysis model (OFAM), a two-factor analysis model (OFAM), and a multi-factor analysis model (MFAM) based on the Cobb–Douglas function and the cost minimization problem. This framework examines the determinants of unit costs in renewable energy generation in consideration of learning effects, scale effects, and price effects. This paper uses data from institutions such as IRENA and the World Bank to empirically analyze the contributions of these factors to reductions in the cost of onshore wind and photovoltaic power generation in China from 2010 to 2022. The results indicate that the learning-by-doing (LBD) effect has been overestimated, with scale effects accounting for a significant portion of the cost reduction. Moreover, the price of capital exerts a more pronounced influence on the levelized cost of electricity (LCOE) for photovoltaics. After factoring in equipment scale and capital costs, LBD continues to significantly reduce the LCOE of photovoltaics, with the LBD learning rate declining from 23.85% to 6.30%. Meanwhile, the impact of LBD on the LCOE of onshore wind technology ceases to be significant. Both technologies exhibit economies of scale, with scale effects accounting for 41.60% and 34.12% of the LCOE reductions for onshore wind and photovoltaics, respectively. Capital costs accounted for 32.50% of the LCOE reduction for photovoltaics. Therefore, future large-scale deployments of other costly renewable energy technologies may also benefit from the equipment-level scale and favorable bank interest rates in addition to learning-by-doing. Full article

Background/Objectives: Anterior cruciate ligament reconstruction (ACLR) is a common orthopedic procedure; however, successful return to sport (RTS) remains a major challenge influenced by both physical and psychological factors. Kinesiophobia and psychological readiness are crucial yet inadequately studied components of rehabilitation that may change across distinct phases. This study aimed to examine longitudinal, phase-specific changes in kinesiophobia, psychological readiness, and patient-reported knee function across standardized ACLR rehabilitation phases. Methods: A retrospective longitudinal cohort design was employed. Data were extracted from 45 patients who completed ACLR rehabilitation at a specialized musculoskeletal center in Riyadh, Saudi Arabia. Participants were assessed across four rehabilitation phases: Phase One (0–1 month), Phase Two (>1–3 months), Phase Three (>3–6 months), and Phase Four (>6 months post-ACLR). Outcomes included the Tampa Scale of Kinesiophobia (TSK-17), the ACL–Return to Sport after Injury scale (ACL-RSI), and the International Knee Documentation Committee subjective knee form (IKDC), administered using validated Arabic versions. Linear mixed-effects models with Bonferroni-adjusted pairwise comparisons were used to evaluate phase-related changes. Results: Significant fixed effects of rehabilitation phase were observed for all outcomes (p < 0.001). Kinesiophobia declined substantially from Phase One (mean 51.5) to Phase Three (34.7), with the greatest reduction between Phases Two and Three, followed by stabilization in Phase Four. Psychological readiness increased progressively across all phases (ACL-RSI: 37.1 to 61.8). Knee function demonstrated the greatest improvement during late rehabilitation (IKDC: 37.6 to 75.8). Conclusions: Psychological and functional recovery following ACLR follow distinct temporal trajectories rather than improving synchronously. Kinesiophobia declines most markedly during mid-rehabilitation, while functional gains peak in late rehabilitation. These findings support integrating structured psychological screening into phase-specific ACLR rehabilitation protocols. Full article

Plant growth-promoting microorganisms (PGPMs) and microbial biocontrol agents have emerged as key tools for improving crop productivity while maintaining environmental sustainability. However, central questions remain regarding which factors determine their consistent field performance and how these factors interact under real agronomic conditions. Previous research has demonstrated that PGPMs enhance nutrient acquisition, regulate phytohormone balance, improve stress tolerance, and suppress plant pathogens through diverse biochemical and ecological mechanisms. Advances in omics technologies, genome mining, and synthetic microbial communities have further expanded understanding of their functional potential. Nevertheless, many studies rely on laboratory-scale experiments or short-term trials, with limited multi-season and cross-regional validation. This gap contributes to inconsistent field outcomes and restricts large-scale agricultural adoption. Long-term multi-season validation and reproducibility assessment remain essential priorities for improving reliability of microbial agricultural products. This review synthesizes recent advances in PGPM-based biofertilizers and microbial biocontrol technologies, critically examining their mechanisms of action, scalability constraints, formulation challenges, and regulatory limitations. It identifies major translational barriers, including context dependency, mechanistic uncertainties, reproducibility gaps, and insufficient systems-level integration. Full article

Background: Tuberculosis (TB) has long been suspected to contribute to lung carcinogenesis through chronic inflammation and immune dysregulation. However, contemporary controlled evidence quantifying this association remains limited. We aimed to systematically evaluate the relationship between prior TB and subsequent lung malignancy, using recent observational studies and complementary case reports. Methods: A systematic review and random-effects meta-analysis were conducted, including controlled cohort and case–control studies published from 2020 onward. Adjusted effect estimates were converted to the logarithmic scale for pooling. Heterogeneity and small-study effects were assessed using standard meta-analytic techniques. Additionally, published case reports were descriptively analyzed to explore clinicopathological patterns. Results: Across eligible studies, prior TB was consistently associated with an increased risk of subsequent lung cancer (LC). The pooled estimate demonstrated a statistically significant positive association, despite moderate heterogeneity. Larger nationwide cohorts contributed greater statistical weight, while smaller studies showed wider variability. Case reports revealed heterogeneous temporal patterns, including long-latency scar-associated carcinoma and concurrent inflammatory–malignant presentations. Conclusions: Contemporary controlled evidence supports an association between prior tuberculosis and increased risk of subsequent lung malignancy. However, despite strong biological plausibility and the abundant literature on cancer-associated tuberculosis, modern longitudinal studies specifically evaluating tuberculosis as a preceding independent risk factor remain limited. The small number of eligible post-2020 investigations identified in this meta-analysis highlights a significant contemporary research gap and underlines the need for well-designed prospective studies to clarify causality and guide surveillance strategies in TB-exposed populations. Full article

The tractor road, as the core scene for autonomous driving of grain transport vehicles, is unstructured, complex, and obstacle-rich, leading to poor real-time performance and accuracy of joint road and obstacle detection with existing YOLOv5s. Furthermore, the reliability of passable area evaluation is low solely based on environmental factors. Therefore, YOLOv5s-C2S is proposed, fusing multi-scale features, attention mechanism, and dynamic features for joint detection. Firstly, YOLOv5s-CC is proposed for road detection by fusing context and spatial details and introducing Criss-Cross attention. Secondly, YOLOv5s-SGA is proposed for obstacle detection by grouped and spatial convolution, parameter-free attention, and adaptive feature fusion. By reusing YOLOv5s-CC weights, YOLOv5s-C2S shares low-level features and decouples high-level specificity. Based on the tractor road and obstacle information, combined with vehicle factors, a weighted scoring–based comprehensive method for passable area evaluation is proposed. Finally, the method was verified through experiments with an intelligent tracked grain transport vehicle using self-constructed datasets, including VOC_Road (11,927 images) and VOC_Obstacle (21,779 images). Compared with existing YOLOv5s, Deeplabv3+, FCN, Unet and SegNet, the mAP₅₀ of road detection by YOLOv5s-CC increased by over 1.2%. Compared with existing YOLOv5s, R-CNN, YOLOv7, SSD and YOLOv8n, the mAP₅₀ of obstacle detection by YOLOv5s-SGA increased by over 2%. Compared with YOLOv5s-SD, the mAP₅₀ of joint detection by YOLOv5s-C2S increased by 9.3%, and the frame rate increased by 7.0 FPS. The proposed passable area evaluation method exhibits strong robustness and reliability in complex environments, meeting the accuracy and real-time requirements in autonomous driving of grain transport vehicles. Full article

Activated sludge treatment is plagued by high secondary pollution risks, and ship antifouling paint particles (APPs) as hazardous heavy metal-rich solid wastes generated from hull derusting wastewater, pose severe environmental threats and intractable disposal dilemmas. This study developed a novel pilot-scale activated sludge reduction process coupling APPs-derived carbon-based catalysts with ultrasound-Fe²⁺/peroxydisulfate (PDS) advanced oxidation. Columnar catalysts were fabricated via direct carbonization-molding using waste APPs from an 82,000 deadweight bulk carrier were used as the sole raw material to prepare columnar catalysts via direct carbonization-molding; single-factor and orthogonal experiments optimized process parameters, Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS) and X-ray Photoelectron Spectroscopy (XPS) characterized catalyst and sludge properties, free radical quenching experiments elucidated reaction mechanisms and a 90-day continuous pilot run assessed catalytic stability. The process achieved a 43.5% sludge removal rate under optimal conditions, accompanied by 100% toluene and 92.3% phenolic compound degradation, as well as efficient total phosphorus (TP) and total nitrogen (TN) removal. Mechanistic studies via characterization and quenching experiments confirmed the catalyst enhanced PDS activation through free/non-free radical synergy and accelerated Fe²⁺/Fe³⁺ redox cycling. A 90-day continuous pilot operation demonstrated excellent long-term catalytic stability, with sludge removal rate remaining above 38%. This “waste treating waste” technology realizes high-value APPs resource utilization, provides a low-carbon sludge disposal pathway, and offers a scalable solution for collaborative pollution control in the wastewater treatment and shipping industries. Full article

To address the challenges of small targets, severe background clutter, and high deployment cost in UAV-based power-line defect detection, this paper proposes a lightweight defect detection model based on an improved YOLOv8n. In the downsampling stage, we design an improved lightweight adaptive downsampling module (ADownPro) to replace part of conventional convolutions, which uses a dual-branch parallel structure for stronger feature interaction and depthwise separable convolutions (DSConv) for complexity reduction. In the feature extraction stage, an integration of cross-stage partial connections and partial convolution (CSPPC) is proposed to replace the C2F module for efficient multi-scale feature fusion. In the detection head, mixed local channel attention (MLCA), which combines channel-spatial information and local–global contextual features, is introduced to strengthen defect-focused representations under complex backgrounds. For the loss function, a scale-annealed mixed-quality EIoU loss (SAMQ-EIoU) is proposed by combining iso-center scale transformation, scale factor annealing and focal-style quality reweighting to improve localization accuracy at high IoU thresholds. Experiments on a constructed dataset covering six typical defect categories show that the improved YOLOv8n achieves 91.4% mAP@0.50 and 64.5% mAP@0.50:0.95, with only 1.59 M parameters and 4.9 GFLOPs. Compared with mainstream detectors, the proposed model achieves a better balance between detection accuracy and lightweight design. In particular, compared with the recently proposed YOLOv8n-DSN and IDD-YOLO, it improves mAP@0.50 by 0.6% and 0.8%, and mAP@0.50:0.95 by 1.2% and 4.8%, respectively, while further reducing the parameter count by 1.00 M and 1.26 M, and the FLOPs by 1.7 G and 0.2 G. Moreover, the cross-dataset evaluation on the public UPID and SFID datasets further demonstrate the robustness and generalization ability of the proposed method. Full article

Background and Objectives: Despite critically low levels of chronic kidney disease (CKD) awareness worldwide, there is no psychometrically validated instrument to comprehensively assess CKD awareness across socioecological levels. This study aimed to develop, psychometrically evaluate and validate a multidimensional awareness scale grounded in socioecological theory for patients with stage 3–4 CKD. Materials and Methods: This methodological study enrolled 908 stage 3–4 CKD patients. Scale development proceeded through systematic stages: comprehensive literature review, qualitative interviews (n = 15), expert panel evaluation (n = 25), and pilot testing. The initial 72-item pool was refined to 41 items (Content Validity Index = 0.912). The sample was randomly split for exploratory factor analysis (EFA; n = 454) and confirmatory factor analysis (CFA; n = 454). Psychometric evaluation encompassed internal consistency (Cronbach’s α, McDonald’s ω), test–retest reliability (n = 30; 4-week interval), convergent validity (average variance extracted [AVE], composite reliability [CR]), discriminant validity (Fornell–Larcker criterion), and criterion validity (correlation with Turkish Health Literacy Scale-32 [TSOY-32]). Results: EFA revealed a seven-factor structure with an acceptable explained variance of 43.8%. Following iterative item elimination based on communalities (h² < 0.20) and factor loadings (λ < 0.30), CFA confirmed the final 34-item model with good fit (CFI = 0.972; RMSEA = 0.070 [90% CI: 0.067–0.074]). The factor structure captured awareness across core socioecological levels (Individual, Interpersonal/Institutional, Community, and Systemic), complemented by Treatment Adherence and Social Impact dimensions. Internal consistency coefficients were α = 0.884 and ω = 0.889 for the total scale. Test–retest reliability yielded an ICC of 0.954 (95% CI: 0.907–0.978). Convergent and discriminant validity were confirmed via composite reliability (CR: 0.740–0.953) and the Fornell–Larcker criterion. Criterion validity analysis revealed a significant correlation with TSOY-32 (r = 0.810, p < 0.001). Conclusions: The CKD Awareness Scale (CKD-AS-34) represents a novel, psychometrically validated, multidimensional awareness instrument for CKD. This scale enables clinicians to identify awareness deficits spanning individual to systemic levels, facilitating personalised patient education and targeted public health interventions. Full article

Background/Objectives: Midwifery workforce sustainability faces critical challenges including high burnout and turnover rates threating the service quality and the maternal health outcomes. While self-leadership and self-compassion represent promising psychological resources, their roles relative to organizational factors remain underexplored. This study examined associations between self-leadership, self-compassion, and workforce outcomes (job satisfaction, turnover intention, performance) among Turkish midwives. Methods: A cross-sectional survey was conducted with 346 midwives working in diverse healthcare settings across Turkey from May 2021 to April 2022. Data were collected through an online self-report questionnaire using validated scales for self-leadership and self-compassion as well as measures of job satisfaction, turnover intention, and job performance, and including demographic and organizational items. Descriptive statistics, one-way ANOVA (with Eta-squared [η²] calculated to determine effect size), and correlation analyses were conducted, followed by hierarchical multiple regression and binary logistic regression to examine predictive relationships, with organizational factors entered before psychological resources. Results: Self-leadership and self-compassion demonstrated a moderate positive correlation (r = 0.342, p < 0.01). Self-leadership strongly predicted job performance (OR = 2.497, p = 0.001), particularly through natural reward strategies emphasizing intrinsic motivation (OR = 1.970, p < 0.001). However, neither psychological resource significantly predicted job satisfaction or turnover intention when organizational factors were included. Work schedule, healthcare setting, professional position, and income emerged as primary predictors of satisfaction and retention. Work experience predicted increased psychological distress (OR = 1.073, p = 0.003). Conclusions: Psychological resources demonstrate domain-specific effects on workforce outcomes in midwifery: self-leadership strategies strongly enhance job performance, whereas job satisfaction and turnover intention are influenced primarily by organizational conditions. These findings highlight the need for multi-level strategies to support the sustainability of the midwifery workforce. Full article

Background/Objectives: Maternal postpartum depressive symptoms and the COVID-19 pandemic have both been identified as potential risk factors for socioemotional difficulties in children. This study aimed to assess behavioral outcomes in young children born to mothers previously screened for postpartum depressive symptoms, comparing cohorts evaluated during and after the pandemic using the Child Behavior Checklist (CBCL 1½–5). Methods: An observational follow-up cohort study was conducted on 52 mother–child dyads derived from a previously established maternal cohort screened with the Edinburgh Postnatal Depression Scale (EPDS). Two cohorts were defined according to the child’s birth period: during-pandemic (January–April 2022) and post-pandemic (October–November 2023) groups. Behavioral outcomes were assessed using CBCL 1½–5. Group differences were tested using parametric or non-parametric methods for continuous variables and χ2 or Fisher’s exact tests for categorical variables. Exploratory regression models and sensitivity analyses were also performed. Results: Children assessed in the post-pandemic cohort showed a lower prevalence of non-normal internalizing scores than those assessed in the during-pandemic cohort, whereas externalizing outcomes and Total Problems did not significantly differ between groups. In exploratory models, a child’s age showed a near-significant association with internalizing outcomes, suggesting that developmental stage at assessment may have contributed to the observed cohort difference. Maternal SARS-CoV-2 infection at delivery was not associated with children’s behavioral outcomes. Conclusions: These findings suggest a possible difference in internalizing behavioral profiles between children assessed in during-pandemic and post-pandemic cohorts. However, this pattern should be interpreted cautiously because the cohorts differed substantially in age at follow-up, and age-related factors may have affected symptom detectability. Continued longitudinal follow-up will be important to clarify whether the observed differences persist over time. Full article

The beneficial use of mining waste aligns with circular economy thinking: saving primary resources can extend their lifetime and maintain availability, reduce the volume of legacy mining waste and its environmental impacts, and develop a resource beneficiation industry that is less energy and water intensive; mining lower grades at larger scale inevitably requires more beneficial reuse. Existing classifications applicable to different types of mine waste were reviewed. These include factors such as the mode of origin during the mining operation, grain size, chemical composition and stability. The result shows that these factors also largely control their civil engineering applications, suitability for end use sectors and potential hazards. Long-term liabilities related to chemical stability were identified as the most difficult challenge. When developing a reuse project, either by the end users or by the mine operator, it is likely that resource screening covering a comprehensive range of factors will be required, as none of the existing schemes individually cover all of the aspects needed to fully assess suitability for beneficial use. In conclusion, there is a need for a systematic and structured approach to classification of mining waste to facilitate reuse as raw materials, such as that presented in our review. Full article

Objective: This study aimed to examine the effects of personality features and attitudes toward the nursing profession on job motivation and intention to quit among male nurses within the framework of the Job Demands–Resources (JD-R) model. In this framework, personality traits and perceptions of the profession were conceptualized as personal resources, while job motivation represents a motivational process that may influence turnover intention. Methods: A cross-sectional design was employed with 303 male nurses actively working in different regions of Turkey. Data were collected via an online survey using non-probability sampling methods. The measurement tools included the Attitude Scale Toward the Nursing Profession, Job Motivation Scale, Personality Features Scale, and the Nurse Turnover Intention Scale. Data were analyzed using descriptive statistics, confirmatory factor analysis, and structural equation modeling. Results: Structural equation modeling revealed that attitudes toward the nursing profession (β = −0.90, p < 0.001), personality features (β = −0.10, p < 0.001), and job motivation (β = −0.14, p < 0.001) had significant and negative effects on intention to quit. Attitudes toward the profession emerged as the strongest predictor, explaining 49% of the variance in intention to quit. Attitudes toward the nursing profession, personality features, and job motivation were found to have significant and negative effects on intention to quit among male nurses. Consistent with the JD-R model, the findings suggest that personal resources (personality and professional perception) and motivational processes (job motivation) may play an important role in shaping turnover intentions among male nurses. Accordingly, professional identity-strengthening initiatives, role model-based mentoring, and motivation-enhancing training programs may help support the retention of male nurses in the profession. Full article

Background: Recent data show that approximately 3.8% of the global population has a diagnosis of depression. Understanding psychological risk and protective factors is crucial for improving prevention strategies and mental health interventions. Among these, worry and emotional intelligence (EI) have emerged as relevant, yet they are rarely studied together. To date, no studies that analyzed the relationship between emotional intelligence, worry, and depression have been found. Therefore, this study aims to investigate the association among EI, worry, and depression. Methods: This study included 924 participants (N = 806 non-clinical and N = 118 subclinical sample with elevated depressive symptoms), with a mean age of M = 25.55 years (SD = 11.38). A total of 118 participants (12.8%) met the criteria for clinical depression based on the BDI-II cut-off. All participants completed the Penn State Worry Questionnaire, the Beck Depression Inventory-II, and the Emotional Intelligence Scale. To examine the relationships among all variables examined, zero-order correlation coefficients were calculated. To investigate the predictive power of EI and worry on depression, Bayesian linear regression was conducted. Results: The results showed significant and positive correlations between worry and depression in both samples. EI showed significant and negative correlations with both depression and worry in both the subclinical sample with elevated depressive symptoms and the non-clinical sample. Finally, worry emerged as the strongest contributor to the somatic dimension of depression in both groups. In the subclinical sample with elevated depressive symptoms, age and Evaluation and Expression of Emotion to Self, along with worry, were the best predictors of somatic symptoms. Conclusions: Our data suggest that higher worry levels are associated with higher levels of depressive symptoms, whereas higher EI was negatively associated with depressive symptoms and may play a potential buffering role. Training programs designed to enhance EI could help mitigate the impact of negative events, improve problem-solving skills, and enhance the expression of one’s own emotions. Full article

Background: Aneurysmal subarachnoid hemorrhage (aSAH) remains a devastating neurological condition, with patients presenting with poor-grade aSAH having a particularly limited potential for recovery. Data on outcome trajectories after microsurgical clipping in this subgroup are scarce. The objective of this study was to analyze the functional outcomes in patients with poor-grade aSAH treated with microsurgical clipping, and to identify clinical factors associated with recovery. Methods: This retrospective study included 38 patients (median age 55 years; 60.5% female) with World Federation of Neurosurgical Societies (WFNS) grades 4–5, who underwent microsurgical clipping at a single tertiary care centre between 2016 and 2023. Functional outcome was assessed using the modified Rankin Scale (mRS) at hospital discharge and 6 months follow-up, and functional outcome was analyzed in relation to clinical variables (delayed cerebral ischemia (DCI), intracerebral hemorrhage (ICH), initial seizures, the need for decompressive craniectomy) using correlation and group comparison analyses. Results: The indication for microsurgical clipping was primarily driven by the need for ICH evacuation (50%) or by aneurysm configuration (47.5%). Microsurgical aneurysm clipping was performed on the day of hemorrhage in 25 patients (65.8%), with 16 patients (42.1%) undergoing immediate surgery following direct transfer from the emergency department to the operating theatre. ICH was present in 60.5% and IVH in 92.1%. Decompressive craniectomy was performed in 42.1%. DCI occurred in 21.6% of patients. In-hospital mortality was 15.8%, increasing to 22.6% at 6 months follow-up. Good functional outcome (mRS 0–2) was observed in 10.5% of patients at discharge and improved to 25.8% at 6 months. At hospital discharge, higher mRS scores were associated with the need for immediate aneurysm repair (p = 0.04), primary decompressive craniectomy (p = 0.02), and DCI (p = 0.006). Primary decompressive craniectomy (p = 0.04), reflecting greater disease severity, and DCI (p = 0.002) remained associated with worse functional outcome at 6 months. Conclusions: In poor-grade aSAH patients undergoing microsurgical clipping, mortality remains substantial; however, functional recovery may extend beyond hospital discharge. The need for immediate surgical intervention and primary decompressive craniectomy likely reflects a particularly severe hemorrhagic burden in patients and is associated with worse early functional outcomes, whereas DCI remains an important factor in overall functional recovery. Full article