Search Results (15,591)

Improving the effluent quality of municipal wastewater treatment plants (WWTPs) is essential for sustainable water management and water quality protection in the Yellow River Basin. Many existing WWTPs in northern China were constructed under earlier discharge requirements and now face dual challenges of stricter effluent standards and poor low-temperature performance in winter. In this study, a municipal WWTP with a design capacity of 5 × 10⁴ m³/d in northern China was upgraded to improve winter treatment performance and support stable compliance with the discharge requirements of the Yellow River Basin. The original anaerobic + oxidation ditch process suffered from unstable effluent quality, excessive sludge loading, and insufficient pollutant removal under low-temperature conditions. A land-saving retrofit strategy was therefore proposed, involving oxidation ditch wall-height raising to extend the hydraulic retention time (HRT) and membrane bioreactor (MBR) integration to increase the mixed liquor suspended solids (MLSS) concentration. After the retrofit, the total HRT increased to 19.82 h, and the average MLSS concentration reached 7050 mg/L. The relative abundances of key nitrogen-removing bacteria, including Nitrospiraceae, Nitrosomonadaceae, and Rhodocyclaceae, increased markedly. Meanwhile, denitrification sludge loading and BOD₅ sludge loading decreased to 0.030 and 0.033 kg/(kg·d), respectively. Under low-temperature conditions, the theoretical removal capacities of total nitrogen (TN) and BOD₅ reached 44.32 and 286.19 mg/L, respectively, enabling stable effluent compliance. The results show that this retrofit strategy can improve WWTP effluent quality while avoiding large-scale land expansion, providing a practical and sustainable solution for upgrading cold-region WWTPs along the Yellow River Basin. Full article

Background: This study proposes a cascade strategy for the comprehensive valorization of Rosa canina L. leaves, considered an underutilized agricultural by-product. Methods: The approach is based on a combination of optimized Ultrasound-assisted extraction (UAE) followed by High-pressure homogenization (HPH) of the residual biomass from both whole and ground leaves. UAE parameters (temperature, process duration, and ethanol concentration) were optimized to maximize the yield of total phenolic content (TPC), total flavonoid content (TFC), and antioxidant activity (DPPH, FRAP). Results: The optimal conditions (55.5 °C, 69.7 min, 40.8% ethanol) yielded extracts with a high TPC (289.55 mg GAE/g) and TFC (177.88 mg CE/g), reducing the processing time by 22% while increasing the TPC yield by 31% compared to the conventional solid–liquid extraction (SLE). It was found that primary extraction from whole leaves is more efficient than extraction from ground leaves, suggesting that the energy-intensive preliminary grinding step could be eliminated. The application of HPH to the residual biomass provided a significant secondary release of bioactive compounds, exceeding high-shear mixing (HSM) by up to 1.5 times for whole leaves. Kinetic analysis showed a higher release of bioactive compounds from whole leaves compared to ground leaves. Conclusions: The proposed UAE + HPH cascade process is a sustainable approach, ensuring rational use of resources and a significant increase in the total yield of antioxidants from Rosa canina L. leaves. Overall, the study may contribute to the circular economy by promoting valorization of agricultural by-products through an energy-efficient, sustainable cascade approach. Full article

EEG-based driver fatigue detection faces three signal-level challenges: inter-subject spectral variability, coupled frequency–spatial–temporal dynamics that existing methods process independently, and dependence on a single labeling scheme. This paper presents DCAMNet, a lightweight CNN (12.3 K parameters) that addresses these challenges through three end-to-end blocks. An SE-driven dynamic convolution block adapts spectral sensitivity per sample via input-dependent kernel weighting—applied here for the first time to fatigue detection. A spatial convolution block encodes electrode-level cortical patterns, and a temporal attention block captures fatigue dynamics through windowed variance descriptors with group-wise attention scoring. DCAMNet was evaluated on SEED-VIG (PERCLOS labels) and MESD (reaction-time labels) under both subject-mixed and leave-one-subject-out (LOSO) protocols. Under LOSO cross-validation—the operationally relevant test that eliminates within-subject information leakage and simulates deployment on unseen drivers—DCAMNet achieved 85.43% accuracy on SEED-VIG with a 2.86-point advantage over the strongest baseline, and $79\pm 5$% accuracy on MESD with a 3-point advantage. As upper-bound estimates under the subject-mixed protocol, accuracy reached 97.47% (SEED-VIG) and 96.52% (MESD). With 1.35 ms inference latency on a standard GPU, the compact architecture suggests potential suitability for real-time embedded deployment, although on-device validation on representative automotive hardware remains necessary. Full article

The present study examined for the first time the effect of native yeasts on the fermentation of artisanal Spondias purpurea L., wine produced in Santa Elena, Ecuador. To achieve this goal, three inoculation strategies were compared: a mixed culture containing Saccharomyces cerevisiae and Candida spp. (CLX), commercial S. cerevisiae (CL), and a spontaneous fermentation without added inoculum (SL). Five yeast isolates were identified from the fermentations, four belonging to Candida spp. and one to Kloeckera spp., using microbiological and biochemical methods. The CLX treatment showed the greatest yeast proliferation on PDA plates (2.7 × 10⁶ CFU/mL) and yielded the highest levels of higher alcohols, while the CL treatment produced the highest ethanol (3.72% ABV) and glycerol content (0.46%). All treatments were free of total and fecal coliforms, and their pH values (2.49–2.56) satisfied the requirements of the current Ecuadorian standard for wine production NTE INEN 374. Residual glucose content was specifically quantified using an enzymatic colorimetric (GOD-POD) assay, confirming the dry character of the wines. Molecular analysis of the final preparation obtained from the variant corresponding to the spontaneous fermentation without inoculum (SL) confirmed the presence of Hanseniaspora spp. (Kloeckera spp.), Diutina rugosa (C. rugosa), C. zeylanoides and Pichia kudriavzevii, after the obtained PCR amplicons using ITS1 and ITS4 were subjected to a blast analysis. Sensory evaluation by panelists (n = 15) favored the CLX wine, particularly for aroma and flavor attributes. The final glucose content reached a low value of 0.28 g/L, indicative of an extremely dry wine, with almost no fermentable sugar. Due to the lack of information related to wines produced from Spondias purpurea L., this study could contribute to a better understanding of the biological behavior and biodiversity of the microorganisms present in this fermentation process. These findings will help to improve wine regionality production, supporting the potential application of native regional yeasts in Spondias purpurea L. wine biotechnology. Full article

Background/Objectives: The COVID-19 pandemic intensified concerns regarding the resilience and financing architecture of mental health services, yet it remains unclear whether crisis-induced adjustments fundamentally altered hospital case-mix complexity or merely exposed pre-existing structural configurations. This study examines the relationship between financing regimes and case-mix complexity in psychiatric hospitals in Romania, a Central and Eastern European health system characterized by mixed financing arrangements and pronounced interregional heterogeneity. Methods: Using administrative data comprising 752 hospital section–year observations (2019–2024), we identify structural financing–organization regimes through a two-step clustering procedure (hierarchical Ward method followed by K-means refinement) based on revenue composition, expenditure allocation, workforce structure, and operational pressure indicators. Results: Three distinct regimes emerge, reflecting persistent institutional configurations rather than temporary crisis-induced groupings. Chi-square tests confirm that regime membership is statistically independent of pandemic timing. A multivariate regression model controlling for financing composition and expenditure structure shows that structural variables (particularly the share of contract-based revenues and the allocation of expenditures) exert systematic and economically meaningful effects on the case-mix index (CMI). Pandemic and post-pandemic indicators do not retain robust explanatory power once structural determinants are accounted for. Regional robustness analyses further demonstrate that financing architecture consistently outweighs temporal shock effects in explaining territorial variation in clinical complexity. Conclusions: The findings suggest that psychiatric hospital case-mix dynamics are structurally embedded within differentiated financing regimes whose influence persists beyond crisis periods. By integrating regime identification with outcome modeling in a Central and Eastern European context, this study contributes to the international literature on health system resilience and highlights the primacy of institutional financing architecture over episodic shock effects in shaping hospital complexity. Full article

Forest areas may represent an important component of everyday urban environments, yet evidence remains mixed regarding whether perceived proximity and actual use show similar associations with health-related outcomes. Using a cross-sectional descriptive–correlational design, this study examined associations of perceived stress and self-rated health with perceived walking access to the nearest forest, residential green view, visit frequency, and visit duration among adults living in İstanbul, Türkiye. The study included 345 adults aged 18 years and older; complete PSS-14 data were available for 332 participants. In bivariate analyses, older age was associated with lower perceived stress, whereas longer perceived walking time was associated with higher perceived stress. Greater residential green view, more frequent visits, and longer visit duration were associated with lower perceived stress. For self-rated health, only visit frequency showed a significant bivariate association. In adjusted analyses, visit frequency remained independently associated with lower PSS-14 scores, whereas green view showed a borderline inverse association. In the ordinal logistic regression model, female sex was associated with higher odds of reporting worse self-rated health, while visit frequency and green view remained borderline. These findings indicate modest associations, with the clearest pattern observed for visit frequency and perceived stress. Given the convenience-sample design, self-reported exposure measures, and low model explanatory power, the findings should be interpreted as correlational and hypothesis-generating rather than causal. Full article

The increasing electrification of urban transportation has formulated a tightly coupled energy-mobility nexus. Under extreme disaster events or grid faults, rapidly restoring power supply capacity and re-dispatching shared electric vehicle (EV) fleets are critical for enhancing system resilience. Existing co-optimization methods face the curse of dimensionality when dealing with high-dimensional discrete grid reconfigurations and continuous spatio-temporal EV queuing dynamics. While multi-agent deep reinforcement learning (MADRL) offers real-time responsiveness, it inherently struggles to satisfy strict physical constraints, frequently generating infeasible and unsafe actions. To bridge this gap, this paper proposes a heuristic-guided safe multi-agent reinforcement learning (Safe-MADRL) framework for the resilient dispatch of the energy-mobility nexus. Instead of relying solely on black-box neural networks, the framework structurally embeds physical models and heuristic solvers into the learning loop. A quantum particle swarm optimization (QPSO) algorithm acts as a heuristic action refiner to ensure that grid topology actions strictly comply with non-linear power flow and voltage constraints. Simultaneously, a mixed-integer linear programming (MILP) model coupled with a single-queue multi-server (SQMS) model serves as a safety projection layer. This layer mathematically guarantees EV battery energy continuity and accurately quantifies spatio-temporal queuing delays at charging stations. Case studies on a coupled IEEE 33-node distribution system and a regional transportation network demonstrate that the proposed Safe-MADRL framework achieves zero physical violations during training and significantly outperforms traditional mathematical optimization and pure learning-based methods in computational efficiency, system power loss reduction, and overall operational economy. Full article

Background: Functional gastrointestinal disorders (FGIDs) are highly prevalent among infants. Exclusive breastfeeding has been consistently associated with better gastrointestinal health. However, current evidence regarding the associations between early feeding practices and infant gastrointestinal development remains limited. Objectives: To examine the associations between early feeding practices at 1 month of age and gastrointestinal symptoms and overall gastrointestinal burden in infants during the first 12 months of life. Methods: In this multicenter prospective cohort study, 669 healthy mother–infant pairs were finally included. According to feeding practices at 1 month of age, infants were categorized into three groups: exclusive direct breastfeeding (EDB, n = 236, 35.28%), bottle-fed expressed breastmilk (EBB, n = 150, 22.42%), and mixed feeding (MF, n = 283, 42.30%). Gastrointestinal (GI) symptoms were assessed using the Infant Gastrointestinal Symptom Questionnaire (IGSQ) and symptom items from the PedsQL™ Infant Scales. Generalized estimating equations (GEEs) were used to assess the associations. Results: Infants in the EDB group had the lowest incidence of GI symptoms and lower IGSQ scores throughout the follow-up period. Compared with EDB, the MF group showed higher IGSQ scores (β = 0.95, p = 0.002) and higher odds of constipation (OR = 1.64, p < 0.001), vomiting (OR = 1.70, p < 0.001), and swallowing difficulty (OR = 1.79, p = 0.002); these associations remained robust across multiple sensitivity analyses. The EBB group showed higher odds of certain symptoms in the main analysis, but sensitivity analyses (e.g., time-varying exposure) indicated that these associations were not robust, except for bloating (OR = 1.31, p = 0.042). Conclusions: The EDB is the optimal strategy for infant gastrointestinal health and should be prioritized. The MF is robustly associated with increased odds of constipation, vomiting, swallowing difficulty, and overall gastrointestinal burden. The EBB may slightly increase the odds of bloating, which can be mitigated by paced feeding and adequate burping. Full article

Atypical visual attention to aversive or threatening stimuli is a clinically relevant feature of aggressive behavior. However, the developmental dissociation between sustained visual allocation and early orienting remains unclear. This study examined the temporal dynamics of visual attentional biases in a sample of 119 children and adolescents (51 males, 68 females), clinically and behaviorally categorized into aggressive and non-aggressive cohorts. Using a free-viewing paradigm with standardized emotional stimulus pairs selected from the International Affective Picture System (IAPS), eye-tracking analysis focused on first-fixation direction and dwell time. Inferential analyses were conducted using Linear Mixed-Effect Models (LMM) and Generalized Linear Mixed-Effects Models (GLMM). The linear model revealed a significant main effect of behavioral condition: individuals with aggressive traits, regardless of their stage of development, showed greater sustained visual allocation toward negative stimuli. In contrast, the GLMM for first-fixation direction identified a significant age-by-condition interaction, indicating that early orienting differences were more clearly expressed in the aggressive adolescent cohort. These findings suggest that sustained visual preference for negative content may represent a relatively stable correlate of aggressive traits, whereas early orienting differences may vary across developmental stages. Together, these two temporal eye-tracking measures may provide complementary information for future computational approaches to aggression screening. In conclusion, these two temporal oculomotor dimensions may provide a useful feature space for future machine-learning pipelines and may serve as complementary candidate markers for comparing computational predictions against clinically established ground truth in aggression screening research. Full article

Wheat streak mosaic (WSM), historically attributed to wheat streak mosaic virus (WSMV) and transmitted by the wheat curl mite (WCM; Aceria tosichella), remains a major cause of yield loss in the Texas High Plains. In recent years, Triticum mosaic virus (TriMV), also transmitted by WCM, has emerged as an increasingly important component of the WSM disease complex. Under field conditions, TriMV is most frequently detected in mixed infections with WSMV. Management of WSM relies primarily on resistant cultivars carrying genes such as Wsm1 or Wsm2. Although synergistic interactions between WSMV and TriMV have been documented under controlled conditions, their dynamics during natural field infections—particularly during the latent phase between initial infection and symptom development—remain poorly understood. Moreover, the extent to which host genotype influences virus–virus interactions and vector acquisition dynamics in the field has not been fully resolved. Replicated field trials conducted over two growing seasons were used to quantify temporal accumulation patterns and relative ratios of WSMV and TriMV in susceptible (TAM 304) and resistant cultivars differing in resistance source (BT [Wsm1] and Joe [Wsm2]) under natural disease spread. WSMV remained the predominant virus in mixed infections across cultivars, sampling times, and disease stages. However, as plants aged and entered senescence, WSMV titers declined more rapidly than TriMV titers, resulting in a progressive reduction in the WSMV-to-TriMV ratio. From early infection through disease development, the Wsm1 cultivar (BT) consistently supported significantly lower TriMV accumulation than the Wsm2 cultivar (Joe), providing a mechanistic explanation for the comparatively stronger disease suppression associated with WSM. Mites feeding on BT also acquired lower TriMV titers. Although viral concentrations in wheat tissue were strongly correlated with those detected in feeding mites, substantial differences in plant-level WSMV-to-TriMV ratios among cultivars were not mirrored within the vector. These findings indicate that while host resistance regulates absolute virus accumulation, vector-associated factors may influence the relative proportions of viruses detected following acquisition, with important implications for WSM epidemiology and resistance deployment in field systems. Full article

In this study, electrospun poly(3-hydroxybutyrate-co-3-hydroxyhexanoate) (PHBH) biopapers were produced by annealing electrospun fiber mats from two commercial grades (151C and X131A) and compared with films prepared by the conventional melt-mixing/compression molding method. To obtain continuous biopapers, the fiber mats were subjected to mild thermal post-processing at various temperatures. The selected annealing temperatures were 140 °C (151C) and 130 °C (X131A), where interfiber coalescence occurred within a short annealing time (10 s), yielding continuous fibrous films (biopapers). To elucidate the structural mechanisms underlying interfiber coalescence, time-resolved synchrotron SAXS/WAXS and temperature-dependent FTIR spectroscopy were performed. These analyses showed that coalescence occurred through an interplay between thermally induced local ordering at sub-melting temperatures and premelting/partial melting of thin, ill-defined lamellae, with grade-dependent contributions. The resulting biopapers were evaluated against compression-molded films for optical, mechanical, and barrier properties relevant to packaging. All samples showed similar transparency, although compression-molded films were slightly more opaque. The lower-rigidity grade (151C) exhibited more ductile and tougher behavior than X131A. Biopapers showed slightly lower water and oxygen barrier performance than compression-molded films, attributed to differences in material compactness. Overall, brief mild annealing after electrospinning enabled continuous PHBH biopapers with balanced properties, supporting their potential for sustainable PHBH-based food-packaging applications. Full article

Engineered cementitious composite (ECC) is an advanced material known for its superior flexibility, high durability, and crack resistance, making it ideal for a variety of structural applications. However, it uses cement at a rate of 2–3 times more than conventional concrete which raises environmental concerns. This study focused on the production of eco-friendly ECC by incorporating various waste materials as partial cement and sand substitutes. Cement kiln dust (CKD), ceramic powder waste (CPW), and eggshell waste (ESW) were used as partial substitutes for cement in doses of 10% and 20%. Crumb rubber (CR) was used as a partial substitute for sand in doses of 25, 50, 75, and 100%. Chemical treatments using sodium hydroxide, sodium silicate, and a mix of both of them were carried out for the CR in the production of the proposed ECC. Physical treatment using the same cement substitute materials (CKD, CP and ESP) was also carried out for the CR. The effect of fiber type—such as basalt fibers (BF), polypropylene fibers (PPF), and steel fibers (S_tF)—on the performance of ECC was also investigated. Slump, compressive strength, uniaxial tensile strength, flexural strength, and sorptivity were the measured properties for the proposed ECC. Microstructure analyses were also conducted on some selected ECC mixtures. Among the tested mixtures, the results showed that replacing 10% of the cement with CKD improved the compressive strength by up to 22.6% and the tensile strength by up to 18.3%. Using 50% untreated CR reduced compressive and tensile strength by 32.8% and 28.1%, respectively, compared to the control ECC. The physical treatment of CR using CKD improved the compressive strength by up to 12.7% and the tensile strength by up to 3.2% compared to untreated CR. The microstructure analyses revealed an improvement in fiber-matrix bonding and a reduction in crack width in the mixtures, especially in the BF and PPF blends. Full article

Accurate measurement of the 2D soot spatial distribution is vital for optimizing combustion efficiency and reducing pollutant emissions. While 1D laser extinction (LE) is robust and cost-effective, it provides only line-of-sight integrated information, lacking the spatial resolution required to resolve complex soot topologies. We propose Soot-MixFormer, a hybrid deep learning model designed for the high-fidelity inversion of 2D soot distributions from 1D extinction data. The architecture integrates CNN-based local feature extraction with Transformer-based global dependency modeling. Key innovations include a dynamic decoupled generation head and a Dual-Axial Gated Refinement (DAGR) module coupled with a physical hard constraint layer to ensure mass conservation and physical consistency. Experimental results demonstrate that Soot-MixFormer significantly outperforms baseline MLP and CNN models, achieving a Structural Similarity Index (SSIM) of 0.800 and a Pearson Correlation Coefficient (PCC) of 0.915, and a highly suppressed Root Mean Square Error (RMSE) representing less than 10% relative error in high-concentration zones. Furthermore, the model exhibits exceptional robustness, maintaining a cosine similarity above 0.72 even under 10% simulated measurement noise. The model is highly efficient, with only 0.97 M parameters and a real-time inference speed of ~246 FPS. This study provides a novel, low-cost diagnostic paradigm for real-time, high-accuracy monitoring of soot fields in industrial combustion environments, effectively bridging the gap between simple 1D sensing and complex 2D spatial reconstruction. Full article

Type 1 diabetes (T1DM) is associated with elevated cardiovascular (CV) risk, often exacerbated by the rising prevalence of obesity. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) reduce CV risk in type 2 diabetes, but their role in T1DM is less well-defined. This umbrella review synthesizes evidence from systematic reviews, meta-analyses, and Mendelian Randomization (MR) studies to evaluate the metabolic efficacy and safety of GLP-1 RAs in T1DM. Adjunctive therapy, particularly with liraglutide and exenatide, was associated with clinically meaningful weight reduction (mean difference: −4.35 kg to −5.1 kg) and lower total daily insulin doses. HbA1c reductions were statistically significant but modest (0.2–0.3%), with no improvement in Time in Range. Secondary benefits included lower systolic blood pressure. Safety data were mixed: the risk of severe hypoglycemia was not increased, whereas Time Below Range and gastrointestinal adverse events were more frequent. Evidence on diabetic ketoacidosis (DKA) was inconsistent across studies. Overall, GLP-1 RAs improve weight and reduce insulin requirements in T1DM, potentially mitigating indirect CV risk factors; however their direct cardiovascular benefits remain unproven in the absence of dedicated outcome trials. Full article

This study examined the implementation and instructional effectiveness of a multimodal AI-supported instructional framework integrating a generative AI assistant (Microsoft Copilot) with a speech-recognition-based mobile learning application (Mondly) to support productive vocabulary development in EFL higher education. Unlike studies focusing on single AI tools, this study evaluates a coordinated dual-module instructional configuration combining LLM-based lexical support with ASR-based spoken retrieval practice within a structured classroom routine. The proposed framework can be viewed as a lightweight socio-technical instructional arrangement in which learners engage with complementary AI components through guided feedback and repeated practice. A quasi-experimental pretest–post-test control group design was conducted over an eleven-week semester with 64 first-year EFL students at an Iraqi university. Productive vocabulary knowledge was measured using the Productive Vocabulary Levels Test (PVLT), and data were analyzed using mixed-design ANOVA. Results revealed a statistically significant Time × Group interaction with a large effect size, indicating greater productive vocabulary gains in the AI-supported condition compared with traditional instruction. Qualitative findings further suggested perceived improvements in lexical retrieval, sentence construction, pronunciation accuracy, and learner engagement. From an instructional perspective, the findings suggest that learning gains were associated with the coordinated use of complementary AI tools within a structured classroom workflow. This study provides a practical instructional model that may be adaptable to comparable resource-constrained higher-education contexts. Full article