Search Results (9,692)

High-molecular-weight polycyclic aromatic hydrocarbons (PAHs), such as pyrene, are persistent environmental pollutants that threaten soil health and agricultural productivity due to their resistance to degradation. This study evaluated the efficacy of domesticated bacteria isolated from contaminated farmland soil and activated sludge, used alone and in combination with corn (Zea mays L.), to remove pyrene from soil, enhance plant growth, improve tolerance, and ensure crop safety. Six bacterial strains were isolated: three from polluted farmland soil (WB1, WB2, and WF2) and three from activated sludge (WNB, WNC, and WH2). High-throughput 16S rRNA amplicon sequencing profiled bacterial communities after 30 days of treatment. Analytical tools, including LEfSe, random forest, and ZiPi analyses, identified biomarkers and core bacteria associated with pyrene degradation, assessing their correlations with plant growth, tolerance, and pyrene accumulation in corn straw. Bacteria from activated sludge (WNB, WNC, and WH2) outperformed farmland soil-derived strains and the inoculant strain ETN19, with WH2 and WNC achieving 65.06% and 87.69% pyrene degradation by days 15 and 30, respectively. The corn–bacteria consortium achieved up to 97% degradation. Activated sewage sludge (ASS)-derived bacteria were more effective at degrading pyrene and enhancing microbial activity, while soil-derived bacteria better promoted plant growth and reduced pyrene accumulation in straw. Microbial communities, dominated by Proteobacteria, exhibited high species richness and resilience, contributing to xenobiotic degradation. The corn-domesticated bacteria consortia effectively degraded pyrene, promoted plant growth, and minimized pollutant accumulation in crops. This remediation technology offers a promising strategy for rapid and sustainable bioremediation of agricultural soils contaminated with organic compounds such as PAHs or other complex pollutants, while promoting the development of efficient bacterial communities that enhance crop growth. Full article

To capture bus passenger flow fluctuations and address the problems of slow convergence and high error in machine learning parameter optimization, this paper develops an improved Whale Optimization Algorithm (IWOA) integrated with a Bidirectional Gated Recurrent Unit (BiGRU). First, a Logistic–Tent chaotic mapping is introduced to generate a diverse and high-quality initial population. Second, a hybrid mechanism combining elite opposition-based learning and Cauchy mutation enhances population diversity and reduces premature convergence. Third, a cosine-based adaptive convergence factor and inertia weight strategy improve the balance between global exploration and local exploitation. Based on the correlation analysis between bus passenger flow and weather condition data in Harbin, and combined with the fluctuation characteristics of bus passenger flow, the data were divided into windows with a 7-day weekly cycle and processed by fuzzy information granulation to obtain three groups of fuzzy granulated window data, namely LOW, R, and UP, representing the fluctuation trend and spatial characteristics of bus passenger flow. The IWOA was employed to optimize and solve parameters such as the hidden layer weights and bias vectors of the BiGRU, thereby constructing a bus passenger flow fluctuation trend and spatial prediction model based on FIG-IWOA-BiGRU. Simulation experiments with 21 benchmark functions and real bus data verified its effectiveness. Results show that IWOA significantly improves optimization accuracy and convergence speed. For bus passenger flow forecasting, the average MAE, RMSE, and MAPE of LOW, R, and UP data are 2915, 3075, and 8.1%, representing improvements over existing classical models. The findings provide reliable decision support for bus scheduling and passenger travel planning. Full article

Origami structures exhibit significant potential for rapid deployment in post-disaster response and temporary architecture due to their ability to quickly fold and deploy. Further development of these structures into modular components that can be assembled into large-scale architectural systems holds great importance for the fields of architecture and civil engineering. In this study, a thin-walled foldable column was developed based on the “pillow box” origami pattern. This column maintains its three-dimensional configuration during folding, owing to its inherent self-locking characteristic. Two crease-weakening strategies (“dashed-line” and “slit-hole”) were proposed and experimentally validated. A systematic numerical study was conducted to investigate the axial compressive performance of pillow box columns with weakened curved creases. The results indicate that both weakening strategies effectively enable folding while preserving global integrity under compression. The pillow box column with “dashed-line” creases (OCC-D) demonstrated superior load-bearing capacity, with a load-to-weight ratio of up to 658.9, nearly twice that of the corresponding conventional square tube. Parametric analysis of the crease geometry further revealed that increasing the number of crease units enhances the load-bearing performance, and the optimal performance is achieved when the spacing between slit openings equals the slit length ($l_h=l_c$). These findings highlight the advantages of pillow box origami columns as thin-walled load-bearing components, offering new insights for the rapid construction and lightweight design of architectural structures. Full article

Light quality is a recognized driver of plant growth and secondary metabolism in Coleus blumei, a valuable source of rosmarinic acid (RA) and quercetin (QU), whereas its combination with salinity stress represents a potential strategy that still requires further investigation. We evaluated four LED spectra, red–blue (RB) (6:1, control), blue (B), red (R), and RB + Far-Red, under both control (0 mM NaCl) and moderate salt stress (120 mM NaCl), measuring biomass (dry weight) and RA/QU in leaves and roots after three (T1) and five weeks (T2). Blue light produced the greatest root biomass, while the leaf dry weight under B did not differ significantly from RB or RBfr. RA peaked at T2 under B in leaves and under R in roots; QU was maximal under B in leaves and under RB in roots. Extending exposure from T1 to T2 markedly increased both metabolites’ yield. Salinity had little effect on biomass, increased the total QU yield, and did not enhance the total RA yield. These results indicate that targeted LED regimes and longer exposure can raise the yields of bioactive compounds, and that combining specific spectra with moderate salinity is an effective strategy for selectively increasing quercetin accumulation in indoor-grown C. blumei. Full article

To address the challenges of weight redundancy, low material utilization, and excessive performance margins in the design of electric cable-hauling machines, this study proposes a novel multi-objective optimization framework. The framework integrates Latin hypercube experimental design, Kriging surrogate modeling, a Non-dominated Sorting Genetic Algorithm III (NSGA-III), and a coupled TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach. A high-fidelity finite element model based on extreme operating conditions was established to simulate the performance of the electric towing winch. The Kriging model was employed to replace time-consuming finite element calculations, significantly improving computational efficiency. The NSGA-III algorithm was then utilized to search for the Pareto front, identifying a set of optimal solutions that balance multiple design objectives. Finally, the TOPSIS method was applied to select the most preferable solution from the Pareto front. The results demonstrate a 7.32% reduction in the overall mass of the towing winch, a 7.34% increase in the safety factor, and a 4.57% reduction in maximum structural deformation under extreme operating conditions. These findings validate the effectiveness of the proposed Kriging-NSGA-III-TOPSIS strategy for lightweight design of ship deck winch machinery. Full article

Background: Pediatric asthma is a multifactorial condition influenced by environmental, biological, and social determinants. The COVID-19 pandemic introduced new variables that may have affected the severity and management of asthma in children and adolescents, particularly through changes in healthcare access, treatment adherence, and exposure to environmental risk factors. Objective: To evaluate the association between asthma severity and various factors including nutritional status, corticosteroid use, COVID-19 vaccination, and pollutant exposure before and during the COVID-19 pandemic in a pediatric population. Methods: A retrospective analysis was conducted using 307 medical records of patients aged 3 to 17 years. Data collected included sociodemographic characteristics, nutritional indicators, history of corticosteroid use, vaccination status against COVID-19, and exposure to environmental pollutants. Asthma severity was assessed using the pulmonary score, and multiple statistical analyses, including logistic regression using the Bayesian Logistic Regression Model (BLRM), were employed to identify significant associations. Results: The analysis revealed a statistically significant impact of the pandemic on hospitalization rates (p = 0.0187) and the use of corticosteroids (p = 0.009), indicating changes in asthma management during this period. Notable differences were observed in the geographic distribution of mild versus severe asthma cases prior to the pandemic, associated with nutritional status and gender (p = 0.018). During the pandemic, breastfeeding history, body weight, and hospitalization emerged as significant predictors of asthma severity (p < 0.05). In addition, breastfeeding in young children (aged 3 to 6 years) and hospitalization were strongly associated with pulmonary scores, with significance values of 0.022 and 0.012, respectively, as identified by the BLRM. Conclusions: These findings suggest that the pandemic context influenced both the clinical course and management of pediatric asthma. Preventive strategies should consider individual and environmental factors such as nutrition, early-life health practices (e.g., breastfeeding), and equitable access to appropriate asthma care and vaccination. Tailoring pediatric asthma management to these variables may improve outcomes and reduce disparities in disease severity. Full article

Wireless Sensor Networks (WSNs) consist of numerous battery-powered sensor nodes that operate with limited energy, computation, and communication capabilities. Designing routing strategies that are both energy-efficient and attack-resilient is essential for extending network lifetime and ensuring secure data delivery. This paper proposes Adaptive Federated Reinforcement Learning-Hunger Games Search (AFRL-HGS), a Hybrid Routing framework that integrates multiple advanced techniques. At the node level, tabular Q-learning enables each sensor node to act as a reinforcement learning agent, making next-hop decisions based on discretized state features such as residual energy, distance to sink, congestion, path quality, and security. At the network level, Federated Reinforcement Learning (FRL) allows the sink node to aggregate local Q-tables using adaptive, energy- and performance-weighted contributions, with Polyak-based blending to preserve stability. The binary Hunger Games Search (HGS) metaheuristic initializes Cluster Head (CH) selection and routing, providing a well-structured topology that accelerates convergence. Security is enforced as a constraint through a lightweight trust and anomaly detection module, which fuses reliability estimates with residual-based anomaly detection using Exponentially Weighted Moving Average (EWMA) on Round-Trip Time (RTT) and loss metrics. The framework further incorporates energy-accounted control plane operations with dual-format HELLO and hierarchical ADVERTISE/Service-ADVERTISE (SrvADVERTISE) messages to maintain the routing tables. Evaluation is performed in a hybrid testbed using the Graphical Network Simulator-3 (GNS3) for large-scale simulation and Kali Linux for live adversarial traffic injection, ensuring both reproducibility and realism. The proposed AFRL-HGS framework offers a scalable, secure, and energy-efficient routing solution for next-generation WSN deployments. Full article

Introduction: Occupational allergic rhinitis (OAR) is a common respiratory condition that can lead to varying degrees of symptom severity, significantly impacting workers’ quality of life and productivity. While occupational risk factors are well established, the influence of nonoccupational factors, such as obesity, that contribute to OAR severity remains largely unexplored. Aims: This study aims to study the association between obesity and the severity of OAR. Methods: A cross-sectional analytical study was conducted among patients diagnosed with OAR at the Occupational Medicine Department of Farhat Hached University Hospital of Sousse. It combines a retrospective review of medical records (2013–2021) with prospective structured telephone interviews (January–March 2023). Data were collected from medical records and supplemented with telephone interviews. The severity of OAR was assessed via the PAREO score and rhinomanometry results. Results: A total of 196 patients were included. The mean age was 39.69 ± 7.92 years, with a sex ratio of 0.53. The most frequently reported symptoms were nasal obstruction (78.6%) and sneezing (88.8%). The mean PAREO score was 5.78 ± 1.61, with severe OAR reported in 59.2% of the patients. Obesity was significantly associated with increased severity of OAR symptoms (p < 0.001; OR = 5.4; 95% CI [2.6–11.1]), a finding confirmed after adjustment for variables such as age, sex, and occupational seniority. Conclusion: Obesity appears to be a modifiable risk factor influencing OAR severity. Integrating weight management strategies into the treatment of OAR patients may contribute to significant symptom relief and improved quality of life. Further longitudinal studies are needed to confirm these findings and explore the underlying mechanisms involved. Full article

Aim: This study analyzed the concurrent validity of the Optojump infrared photocell system for estimating lower limb peak power by comparing it with the 15 s Wingate anaerobic test (WAnT) and examining relationships with sprint performance indicators. Methods: Twelve physically active university students (ten males, two females; age: 23.39 ± 1.47 years; body mass: 73.08 ± 9.19 kg; height: 173.67 ± 6.97 cm; BMI: 24.17 ± 1.48 kg·m⁻²) completed a cross-sectional validation protocol. Participants performed WAnT on a calibrated Monark ergometer (7.5% body weight for males, 5.5% for females), 30 s continuous jump tests using the Optojump system (Microgate, Italy), and 30 m sprint assessments with 10 m and 20 m split times. Peak power was expressed in absolute (W), relative (W·kg⁻¹), and allometric (W·kg^−0.67) terms. Results: Thirty-second continuous jump testing produced systematically higher peak power values across all metrics (p < 0.001). Mean differences indicated large effect sizes: relative power (Cohen’s d = 0.99; 18.263 ± 4.243 vs. 10.99 ± 1.58 W·kg⁻¹), absolute power (d = 0.86; 1381.71 ± 393.44 vs. 807.28 ± 175.45 W), and allometric power (d = 0.79). Strong correlations emerged between protocols, with absolute power showing the strongest association (r = 0.842, p < 0.001). Linear regression analysis revealed that 30 s continuous jump-derived measurements explained 71% of the variance in Wingate outcomes (R² = 0.710, p < 0.001). Sprint performance showed equivalent predictive capacity for both tests (Wingate: R² = 0.66; 30 s continuous jump: R² = 0.67). Conclusions: The Optojump infrared photocell system provides a valid and practical alternative to laboratory-based ergometry for assessing lower limb anaerobic power. While it systematically overestimates absolute values compared with the Wingate anaerobic test, its strong concurrent validity (r > 0.80), large effect sizes, and equivalent predictive ability for sprint performance (R² = 0.66–0.71) confirm its reliability as a field-based assessment tool. These findings underscore the importance of sport-specific, weight-bearing assessment technologies in modern sports biomechanics, providing coaches, practitioners, and clinicians with a feasible method for monitoring performance, talent identification, and training optimization. The results further suggest that Optojump-based protocols can bridge the gap between laboratory precision and ecological validity, supporting both athletic performance enhancement and injury prevention strategies. Full article

Selecting an appropriate Multi-Criteria Decision-Making (MCDM) algorithm for optimizing marine diesel engine operation presents a complex challenge due to the diversity in mathematical formulations, normalization schemes, and trade-off resolutions across methods. This study systematically evaluates fourteen MCDM algorithms, which are grouped into five primary methodological categories: Scoring-Based, Distance-Based, Pairwise Comparison, Outranking, and Hybrid/Intelligent System-Based methods. The goal is to identify the most suitable algorithm for real-time performance optimization of two stroke marine diesel engines. Using Diesel-RK software, calibrated for marine diesel applications, simulations were performed on a variant of the MAN-B&W-S60-MC-C8-8 engine. A refined five-dimensional parameter space was constructed by systematically varying five key control variables: Start of Injection (SOI), Dwell Time, Fuel Mass Fraction, Fuel Rail Pressure, and Exhaust Valve Timing. A subset of 4454 high-potential alternatives was systematically evaluated according to three equally important criteria: Specific Fuel Consumption (SFC), Nitrogen Oxides (NO_x), and Particulate Matter (PM). The MCDM algorithms were evaluated based on ranking consistency and stability. Among them, Proximity Indexed Value (PIV), Integrated Simple Weighted Sum Product (WISP), and TriMetric Fusion (TMF) emerged as the most stable and consistently aligned with the overall consensus. These methods reliably identified optimal engine control strategies with minimal sensitivity to normalization, making them the most suitable candidates for integration into automated marine engine decision-support systems. The results underscore the importance of algorithm selection and provide a rigorous basis for establishing MCDM in emission-constrained maritime environments. This study is the first comprehensive, simulation-based evaluation of fourteen MCDM algorithms applied specifically to the optimization of two stroke marine diesel engines using Diesel-RK software. Full article

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder connected with insulin resistance (IR), low-grade inflammation, dyslipidemia, and altered adipokine secretion. We evaluated serum levels of leptin, adiponectin, visfatin, resistin, IL-6, and TNF-α in 150 women with PCOS, stratified by IR status (IR, n = 76; non-IR, n = 74), and examined their associations with anthropometric, metabolic, hormonal, inflammatory, and atherogenic parameters. Anthropometric data included body weight, height, BMI, waist circumference, and waist-to-height ratio (WHtR), while IR was assessed using HOMA-IR and the Matsuda index. Serum adipokines were measured using ELISA, and lipid parameters and atherogenic indices—including non-HDL cholesterol, AIP, leptin/adiponectin, and adiponectin/resistin ratios—were calculated. Women with IR had higher levels of leptin, visfatin, resistin, and TNF-α, and lower levels of adiponectin. Leptin correlated positively with weight, WHtR, HOMA-IR, and atherogenic indices. Adiponectin showed the strongest and most consistent associations with anthropometric indices, HOMA-IR, and the Matsuda index. Resistin was linked to IR indices and IL-6, and visfatin correlated negatively with HDL-C and insulin sensitivity. In a multivariate general linear model, WHtR, but not HOMA-IR, remained independently associated with higher leptin levels and with atherogenic indices. These findings suggest that in PCOS, central adiposity rather than IR explains a substantial part of the adverse adipokine and inflammatory profile, thereby contributing to elevated cardiometabolic risk and highlighting the need for targeted treatment strategies. Full article

Background: Recurrent urinary tract infections (rUTIs) significantly impair women’s quality of life, making antimicrobial prophylaxis a critical preventative strategy. This retrospective observational study aimed to characterize antibiotic prophylaxis patterns, relapse rates, comparative efficacy of different agents, and tolerability in 908 women (663 postmenopausal, 245 premenopausal) with rUTIs managed at a tertiary university hospital. Methods: Data from medical records (January 2022–December 2024) were analyzed. Patients were stratified by menopausal status. We assessed antibiotic usage, relapse rates (per 100 patient-months), and adverse events. Comparative efficacy of nitrofurantoin-based versus fosfomycin/other prophylaxis was evaluated for rUTIs caused by E. coli, E. faecalis, or E. coli ESBL using weighted and matched analyses to control for covariates. Results: Continuous antimicrobial prophylaxis was the primary strategy, with nitrofurantoin being most frequently used. Premenopausal women showed a greater tendency for intermittent or combined prophylactic approaches. Postmenopausal women exhibited a higher overall crude relapse rate (5.54/100 p-m) compared to premenopausal women (3.14/100 p-m), with E. coli being the most common causative agent in relapses. For rUTIs caused by E. coli, E. faecalis, or E. coli ESBL, nitrofurantoin-based prophylaxis demonstrated significantly lower adjusted relapse rates than fosfomycin/other regimens (rate ratio: 0.47 for postmenopausal, 0.35 for premenopausal women). This observed efficacy for nitrofurantoin was robust against potential unmeasured confounding. Prophylaxis was generally well-tolerated (3.0% gastrointestinal adverse events overall); however, premenopausal women reported a higher adverse event incidence. Conclusions: Our findings strongly suggest that nitrofurantoin is an effective prophylactic choice for rUTIs caused by common uropathogens (E. coli, E. faecalis, E. coli ESBL), particularly in postmenopausal women. The diverse prophylactic strategies highlight the need for individualized care. While generally well-tolerated, adverse event profiles vary between menopausal groups, necessitating careful monitoring. Full article

Polyploidization is a rapid breeding strategy for producing new varieties with superior agronomic traits. Kenaf (Hibiscus cannabinus L.), an important fiber crop, exhibits high adaptability to diverse stress conditions. However, comprehensive studies on polyploid induction, screening, and genetic identification in kenaf remain unreported. This study first established an optimal tetraploid induction system for diploid kenaf seeds using colchicine. The results showed that a 4-h treatment with 0.3% colchicine yielded the highest tetraploid induction rate of 37.59%. Compared with diploids, tetraploid plants displayed distinct phenotypic and physiological characteristics: dwarfism with shortened internodal distance, increased stem thickness, larger and thicker leaves with deeper green color and serration, as well as enlarged flowers, capsules, and seeds. Physiologically, tetraploid leaves featured increased chloroplast numbers in guard cells, reduced stomatal density, and larger pollen grains, elevated chlorophyll content. Further analyses revealed that tetraploid kenaf had elevated contents of various trace elements, enhanced photosynthetic efficiency, prolonged growth duration, and superior agronomic traits with higher biomass (54.54% higher fresh weight, 79.17% higher dry weight). These findings confirm the effectiveness of colchicine-induced polyploidization in kenaf, and the obtained tetraploid germplasm provides valuable resources for accelerating the breeding of elite kenaf varieties with improved yield and quality. Full article

Background/Objectives: Glioblastoma (GBM) is an aggressive primary brain tumor with limited therapeutic options despite multimodal treatment. Small interfering RNA (siRNA)-based therapeutics can silence tumor-promoting genes, but achieving efficient and tumor-specific delivery remains challenging. Lipid nanoparticles (LNPs) are promising siRNA carriers; however, conventional antibody conjugation can impair antigen recognition and complicate manufacturing. This study aimed to establish a modular Fc-binding peptide (FcBP)-mediated post-insertion strategy to enable PD-L1-targeted delivery of VEGF-siRNA via LNPs for GBM therapy. Methods: Preformed VEGF-siRNA-loaded LNPs were functionalized with FcBP–lipid conjugates, enabling non-covalent anchoring of anti-PD-L1 antibodies through Fc interactions. Particle characteristics were analyzed using dynamic light scattering and encapsulation efficiency assays. Targeted cellular uptake and VEGF gene silencing were evaluated in PD-L1-positive GL261 glioma cells. Anti-tumor efficacy was assessed in a subcutaneous GL261 tumor model following repeated intratumoral administration using tumor volume and bioluminescence imaging as endpoints. Results: FcBP post-insertion preserved LNP particle size (125.2 ± 1.3 nm), polydispersity, zeta potential, and siRNA encapsulation efficiency. Anti-PD-L1–FcBP-LNPs significantly enhanced cellular uptake (by ~50-fold) and VEGF silencing in PD-L1-expressing GL261 cells compared to controls. In vivo, targeted LNPs reduced tumor volume by 65% and markedly suppressed bioluminescence signals without inducing weight loss. Final tumor weight was reduced by 63% in the anti-PD-L1–FcBP–LNP group (656.9 ± 125.4 mg) compared to the VEGF-siRNA LNP group (1794.1 ± 103.7 mg). The FcBP-modified LNPs maintained antibody orientation and binding activity, enabling rapid functionalization with targeting antibodies. Conclusions: The FcBP-mediated post-insertion strategy enables site-specific, modular antibody functionalization of LNPs without compromising physicochemical integrity or antibody recognition. PD-L1-targeted VEGF-siRNA delivery demonstrated potent, selective anti-tumor effects in GBM murine models. This platform offers a versatile approach for targeted nucleic acid therapeutics and holds translational potential for treating GBM. Full article

Background/Objectives: Late-onset neonatal sepsis (LOS) remains a leading cause of morbidity and mortality in very low birth weight (VLBW) infants (<1500 g and/or gestational age <32 weeks), with limited preventive strategies. We evaluated whether early enteral bovine lactoferrin (bLf), given its antimicrobial, immunomodulatory, and antioxidant properties, reduces LOS and improves immunologic, antioxidant, and hematologic markers in these infants. Methods: In this randomized, double-blind, placebo-controlled trial, 103 VLBW infants received bLf (150 mg/kg/day; n = 50) or the placebo (n = 53) within 72 h of birth for four weeks or until discharge. Outcomes included culture-confirmed LOS, mortality, and major morbidities. Risk ratios (RRs) were calculated, adjusting for gestational age, human milk intake, and ventilatory support when ≥25 events occurred. Pre/post changes in cytokines, total antioxidant capacity (TAC), and hemoglobin (Hb) were analyzed for interaction effects (time x intervention). Results: bLf reduced LOS (adjusted RR 0.54; 95% CI 0.31–0.93; p = 0.028), without differences in other morbidities or mortality. bLf preserved MCP-1 levels, declining in the placebo group (interaction p = 0.022). Among LOS infants receiving bLf, IL-6 remained stable and MCP-1 increased, while both declined in other groups (interaction p = 0.007 for IL-6; p = 0.052 for MCP-1). Although TAC showed a non-significant interaction, the placebo group declined (p = 0.002), while bLf remained stable (p = 0.400) in the post hoc analysis. In non-transfused infants, bLf increased Hb by 0.9 g/dL vs. controls (p = 0.028). Conclusions: Early bLf supplementation safely reduces LOS in VLBW infants and may support immunologic, antioxidant, and hematologic stability. Full article