Search Results (64,774)

The global interest in utilizing waste from agro–industrial processes through the implementation of clean technologies is rapidly increasing. This study evaluates the technical, economic, and environmental feasibility of valorizing regional agro–industrial residues in Santander, Colombia, specifically coffee mucilage, cocoa mucilage, and pig manure, using integrated biorefinery scenarios. Modernizing these processes is essential given a theoretical energy potential of 75,000 TJ/year, which could generate up to 20,833 GWh/year. Three biorefinery scenarios were designed and simulated using Aspen Plus^® to produce bio-hydrogen, methane, and methanol. The total plant capacity was established at 31.7 t/day, distributed according to regional biomass availability: 4.62 t/day of cocoa mucilage, 1.83 t/day of coffee mucilage, and 25.25 t/day of pig manure. The technical results for Scenario 1 indicated a reformed H₂ production of 0.15 t/day with an associated preheating energy requirement of 193,365 kJ/h. Environmental impact assessment using the ReCiPe 2015 Midpoint methodology identified Scenario 3 as having the lowest direct CO₂ mass flow (9.28 t/day) due to carbon consumption during methanol synthesis. However, Scenario 1 reported a CO₂ equivalent (CO₂e) of 194.37 t/day, reflecting indirect emissions from thermal and energy requirements. Economic analysis, validated through engineering cost references, demonstrated that while Scenario 3 offers a diverse product portfolio, it is currently not cost-effective as the production costs exceed the total expected income. Consequently, Scenario 2 is identified as the most balanced alternative for the Santander context, offering a sustainable compromise between technical efficiency, environmental mitigation, and economic viability. Full article

A propeller intended for aerial–aquatic vehicles must maintain adequate propulsive performance and structural reliability in both air and water, where the fluid properties and load levels differ substantially. This study presents an engineering workflow combining blade element momentum theory (BEMT), computational fluid dynamics (CFD), and one-way fluid–structure coupling to evaluate a propeller under separate air and water operating conditions. Candidate geometries were first screened using a two-stage BEMT procedure. The selected baseline configuration was subsequently analyzed by CFD under three steady operating conditions: air start, water start, and water inflow. The resulting non-uniform surface pressures and centrifugal loads were transferred to a finite element model. The blade root transition was identified as the dominant stress concentration region under all conditions, and the water inflow case produced the most critical structural response, with a maximum von Mises stress of 129.8 MPa and a maximum deformation of 5.378 mm. After local blade root optimization, these values decreased to 87.0 MPa and 3.669 mm, respectively. The proposed workflow provides an efficient approach for preliminary structural assessment and local optimization of propellers operating separately in air and water. The transient air–water interface-crossing process and associated multiphase effects are beyond the scope of the present study. Full article

Accurate assessment of irrigation water quality is essential for sustainable groundwater management in semi-arid regions. Conventional Irrigation Water Quality Index (IWQI) assessment requires multiple physicochemical measurements and manual computation of a composite index, which can be time-consuming, costly, and difficult to scale across repeated monitoring campaigns. Machine learning (ML) approaches may provide a practical surrogate for reconstructing IWQI from a reduced set of routinely measured variables. This study developed an interpretable ML framework for IWQI reconstruction in the shallow phreatic aquifer of the Sedrata Plain, northeastern Algeria. One hundred groundwater samples were collected from 25 open wells across four seasonal campaigns (February 2023–May 2024). IWQI was calculated from EC, Na⁺, Cl⁻, HCO₃⁻, and SAR using the weighted aggregation approach of Meireles et al. Six ML algorithms were assessed using nested Recursive Feature Elimination with Cross-Validation (RFECV) within a Leave-One-Campaign-Out (LOCO) validation framework, with predictive performance evaluated using R², RMSE, and MAE. IWQI values ranged from 28.72 to 76.28, with 8%, 56%, 28%, and 8% classified as low, moderate, high, and severe restriction, respectively. Extreme Gradient Boosting (XGBoost) achieved the highest LOCO performance (R² = 0.732 ± 0.109; RMSE = 5.075 ± 1.403 IWQI units), compared with Multiple Linear Regression (MLR) (R² = 0.563 ± 0.304). SHapley Additive exPlanations (SHAP) identified Cl⁻, EC, and SAR as the dominant predictors. The findings demonstrate the potential of an interpretable ML framework for grouped-validation IWQI reconstruction from routinely measured variables, supporting efficient irrigation-water quality screening. External validation is required before wider application. Full article

Background/Objectives: Bacterial wound infections remain a significant clinical burden because of prolonged healing and the increasing prevalence of multidrug-resistant bacteria. This study aimed to develop a curcumin-loaded liposomal nanosystem (Lipo-Cur) for light-triggered photodynamic antibacterial therapy and enhanced wound repair. Methods: Lipo -Cur was prepared and characterized in terms of morphology, particle size, dispersibility, drug en-capsulation, curcumin solubility, and photostability. Reactive oxygen species generation under 430 nm blue-light irradiation was evaluated. The antibacterial activity of Lipo-Cur against Staphylococcus aureus and Escherichia coli was assessed in vitro. Its effects on the proliferation, migration, and colony formation of L929 and HaCaT cells were also examined. Therapeutic efficacy and biosafety were further evaluated in a murine S. aureus-infected wound model. Results: Lipo-Cur exhibited a near-spherical morphology with an average diameter of 134.8 nm, excellent dispersibility, high drug encapsulation, and improved curcumin solubility and photostability. Under 430 nm blue-light irradiation, Lipo-Cur efficiently generated reactive oxygen species. It exhibited minimum inhibitory concentrations of 100 and 125 μg/mL against S. aureus and E. coli, respectively, and achieved bactericidal rates exceeding 95%, outperforming free curcumin. Lipo-Cur also significantly enhanced L929 and HaCaT cell proliferation, migration, and colony formation, indicating favorable biocompatibility. In the murine infect-ed-wound model, Lipo-Cur combined with blue-light irradiation (Lipo-Cur-BL⁺) achieved 93.76 ± 1.56% wound closure by day 12, accelerated tissue regeneration, reduced inflammation, and caused no evident systemic toxicity or hemolysis. Conclusions: These findings demonstrate that Lipo-Cur is a safe and effective photodynamic antibacterial platform with considerable potential for treating bacterially infected wounds and promoting wound healing. Full article

Land-use change affects regional carbon accounting through ecological conversion and the concentration of energy-intensive economic activity. We combined 30 m China Land Cover Dataset maps for 2010, 2015, 2020, and 2025 with provincial socioeconomic and energy statistics to quantify land-use transitions and carbon emissions across nine Yellow River Basin provinces. Construction-land-associated emissions were decomposed using the logarithmic mean Divisia index, factors associated with land expansion were examined using random-forest models, and three 2030 scenarios were evaluated. Construction land expanded by 38.87% from 2010 to 2025, with 71.33% of new construction land converted from cropland and 17.75% from grassland. Net land-use carbon emissions increased by 69.82%, from 1139.06 to 1934.33 million t C. Economic-output density contributed 1144.84 million t C to the increase in construction-land-associated emissions, compared with 576.11 million t C from land expansion, whereas declining energy intensity offset 922.72 million t C. Projected 2030 emissions ranged from 2124.72 million t C under ecological protection to 2866.55 million t C under urban expansion. Construction-land expansion was substantial, but economic-output density made the larger positive contribution to historical emission growth. The projected 2030 estimates depended on the combined trajectories of construction-land demand, economic growth, and energy intensity. These findings highlight the importance of coordinating land-use planning, economic development, and energy-efficiency improvement for sustainable low-carbon transitions. Full article

Portfolio reinforcement learning (RL) commonly represents each action as a complete asset-weight vector, causing the action dimension and exploration difficulty to grow with the investment universe. This study proposes FrontierStep-RL, which replaces the direct N-dimensional action with two bounded variables: a frontier coordinate and a rebalancing step. At each decision date, rolling estimates of expected returns and covariance define a regularized efficient frontier. A cost–risk-aware coordinate organizes the frontier using normalized local changes in predicted volatility and one-way turnover. The coordinate selects a frontier-supported target portfolio, while the step controls how far the pre-trade portfolio moves toward that target. We evaluate FrontierStep-RL on FF49, FF100, and FNSPID-50 against traditional strategies, controlled direct-weight RL policies, and recent portfolio-management methods. FrontierStep-RL achieves net Sharpe ratios of 0.75 on both FF49 and FNSPID-50 while maintaining comparatively low volatility, drawdown, and turnover. In the 100-asset setting, it achieves 0.68, compared with 0.52 for the strongest direct-weight baseline, and completes all runs. At a transaction cost of 50 basis points, it retains net Sharpe ratios of 0.559 and 0.568. The results support fixed-dimensional target selection and controlled execution for scalable, transaction-cost-aware portfolio RL. Full article

Detecting small person and bicycle instances with lightweight models is relevant to resource-aware visual sensing, but evidence from a category-filtered general-purpose dataset cannot establish performance in dense surveillance, traffic monitoring, or aerial environments. This study therefore examines a narrower question: whether replacement-style Coordinate Attention (CA) integration can improve coordinate-sensitive representation in YOLOv11m under a controlled VOC-based person and bicycle setting without increasing model complexity. In the official Ultralytics YOLO11m architecture, the Spatial Pyramid Pooling–Fast (SPPF) layer is followed by a C2PSA block. The proposed configuration replaces this post-SPPF C2PSA block with CA, while retaining the remaining backbone, neck, and detection head. CA encodes directional positional information along the horizontal and vertical axes. Experiments are conducted on a filtered subset of PASCAL Visual Object Classes (VOC) 2012 that retains only the person and bicycle categories; this subset is not a dedicated small-object or surveillance benchmark. Within this setting, the proposed model improves mean average precision at an intersection-over-union threshold of 0.50 (mAP@50) from 79.2% to 81.5%. It also improves mean average precision averaged over thresholds from 0.50 to 0.95 (mAP@50–95) from 53.9% to 54.8% and small-instance average precision (${\mathit{AP}}_{\mathrm{s}}$) from 68.1% to 72.4%. The parameter count decreases from 20.03M to 19.07M, and the model achieves 90 frames per second (FPS) on the tested NVIDIA GeForce RTX 4060 Laptop GPU (NVIDIA Corporation, Santa Clara, CA, USA). These results provide incremental evidence for a complexity-aware CA replacement strategy within the evaluated VOC distribution; they do not demonstrate cross-domain generalization or deployment performance in real surveillance or aerial scenarios. No embedded platform was evaluated, and the reported RTX 4060 throughput should not be interpreted as evidence of edge-device latency, energy efficiency, or deployment readiness. Full article

The growing accumulation of microplastics in marine ecosystems, coupled with the presence of emerging contaminants such as pharmaceuticals, represents an environmental problem that has received little attention to date. The present study evaluates the potential of microplastics to act as transport vectors for pharmaceuticals through their adsorption onto two plastic polymers widely used today: polyethylene terephthalate (PET) and medium-density polyethylene (MDPE) in seawater. As a control, the same experiments were conducted in ultrapure water (Milli-Q). Both plastics were exposed to a mixture of 29 pharmaceuticals belonging to different therapeutic classes over a 28-day period, with sampling conducted at various time intervals. The identification, quantification, and characterization of the compounds were performed using ultra-high-performance liquid chromatography coupled with mass spectrometry detection. Statistical analysis was performed using R-Studio software. Outcomes reveal that the type of polymer significantly influences adsorption, with MDPE being more efficient than PET. In contrast, the type of water and the therapeutic class of the drugs were not identified as determining factors. Furthermore, a positive, albeit moderate, correlation was observed between the hydrophobicity of the pharmaceutical and its adsorption efficiency on MDPE. These findings suggest that hydrophobic interactions play a key role in the adsorption of drugs onto microplastics, providing a solid foundation for future research, such as predictive models or mitigation strategies in aquatic ecosystems. Full article

Public procurement tenders in Bulgaria are in the focus of public attention, despite the transparency of the process, which is conducted online through the Public Procurement Agency platform, participants require greater trust in the conduct of the procedures themselves, as they are not yet fully automated. Blockchain solutions are used in a wide range of businesses, as they offer transparency of transactions, trust between parties and data immutability and also seem suitable for conducting e-tenders for public procurement. This publication offers a solution based on a private blockchain HyperLedger Fabric, which in terms of structure and functionality builds on the existing solution. It ensures bidder identities are confidential from the unauthorized participants and transparency of the work of administrators in the platform and their actions when changing the status of a public procurement. The proposed blockchain based solution improves the evaluation process, reducing certain technical and human-error risks. The results show that it provides greater transparency and efficiency in the spending of public funds, achieving the set quantitative indicators with automated evaluation and qualitative factors defined in the smart contract. Full article

Vertical circulating rice seedling racks in cold regions of northeast China face limited natural radiation, uneven light distribution, and high energy demand. This study develops a digital twin optimization framework integrating dynamic light field reconstruction, crop physiological response, surrogate modeling, and multi-objective analysis. A solar position algorithm-based simulator reconstructs the spatiotemporal PPFD distribution along the circulating trajectory and couples it with stage-specific rice seedling light response curves. An XGBoost surrogate model is then used to accelerate parameter evaluation for stage-wise optimization. Preliminary measurements using a plant light analyzer showed limited PPFD deviations from simulation, with a mean deviation of −3.4% and a maximum deviation of +11.4%. The surrogate model achieved a test R² of 0.9955 and a five-fold cross-validation R² of 0.9933 ± 0.0024. Under the engineering constraint of CV ≤ 0.10, stage-wise optimization identified max yield, best efficiency, and balanced operating strategies. The balanced strategy predicted a 7.7% increase in YI, a 6.0% reduction in energy use, and a decrease in CV from 0.0353 to 0.0058 relative to the fixed-parameter baseline. SHAP analysis further identified growth stage as the dominant structural factor, while lighting duration and rack speed mainly regulated within-stage performance. This framework provides a quantitative basis for stage-aware light environment optimization and subsequent experimental validation. Full article

Thyroid hormone physiology has traditionally been understood through the hypothalamic–pituitary–thyroid (HPT) axis and the genomic actions of triiodothyronine (T3). However, advances in thyroid hormone biology have expanded this classical paradigm, demonstrating that thyroid hormone signaling is regulated through a coordinated network involving tissue-specific deiodination, specialized membrane transporters, genomic and non-genomic signaling pathways, and mitochondrial regulation of cellular bioenergetics. Among the iodothyronine metabolites generated through thyroid hormone metabolism, 3,5-diiodothyronine (3,5-T₂) has emerged as one of the most extensively investigated because of its reported ability to rapidly influence mitochondrial respiration, oxidative metabolism, and energy expenditure. Experimental studies suggest that 3,5-T₂ enhances mitochondrial respiration, fatty acid oxidation, oxidative phosphorylation, and metabolic efficiency, particularly in metabolically active tissues such as liver and skeletal muscle. These findings have generated considerable interest in the potential role of 3,5-T₂ in metabolic disorders characterized by mitochondrial dysfunction, including metabolic dysfunction-associated steatotic liver disease (MASLD), obesity, and insulin resistance. However, important translational challenges remain. Most available data derive from animal studies using pharmacologic doses, while the endogenous physiology of 3,5-T₂ in humans, its molecular targets, tissue-specific regulation, and long-term endocrine effects remain incompletely understood. In addition, evidence of hypothalamic–pituitary–thyroid axis suppression following exogenous 3,5-T₂ administration and limitations in accurately measuring circulating 3,5-T₂ continue to complicate clinical translation. This review critically evaluates the emerging biology of 3,5-diiodothyronine, integrating current evidence regarding its biosynthesis, mechanisms of thyroid hormone signaling, mitochondrial actions, metabolic effects, translational challenges, and future research priorities. By synthesizing findings from primary experimental studies and emerging translational investigations, this review places 3,5-T₂ within the broader framework of contemporary thyroid hormone biology while highlighting key knowledge gaps that must be addressed before its physiological and therapeutic significance can be fully established. Full article

Prestressed and post-tensioned concrete structural elements constitute approximately 43.4% of modern bridge infrastructure, representing 58.2% of the total bridge surface area due to their long-span capabilities. Despite their structural efficiency, evaluating residual post-tensioning forces and diagnosing localized degradation within internally grouted tendons—such as localized stress corrosion cracking (SCC), grout voids, and moisture infiltration—remains a critical challenge due to geometric confinement and high material attenuation. This paper presents a non-destructive Structural Health Monitoring (SHM) methodology optimized for the continuous and periodic assessment of post-tensioned anchorage zones under operational traffic loads. The proposed Identification of Active Anomalies (IAA) system integrates the Acoustic Emission (AE) method with unsupervised machine learning to classify multi-mechanism structural degradation. By implementing a mathematically transparent k-means clustering framework initialized via the k-means++ heuristic, high-velocity multi-parameter AE data streams are partitioned within an n-dimensional Euclidean feature space. The scientific novelty of this work lies in its real-scale validation on an operational, highly complex cable-stayed bridge, establishing a previously unpublished acoustic signature database (the 2025 Signal Database). The empirical validity of the algorithm’s predictive boundaries was confirmed through forensic physical inspections and material sampling during a major structural rehabilitation in 2026, which corroborated the active corrosion states within heavily confined post-tensioned anchorage blocks. Furthermore, extracted AE pattern classes are explicitly correlated with structural crack opening widths, enabling real-time tracking of macro-defect propagation, anchorage slippage, and active micro-structural corrosion. Full article

High-starch diets can impair gastrointestinal homeostasis in growing cattle by promoting dysbiosis, inflammation, and oxidative stress. This study evaluated the effects of a multi-active phytogenic blend containing Macleaya cordata extract, essential oils, live yeast, silymarin, bentonite, and beta-glucans on performance, inflammatory and oxidative biomarkers, volatile fatty acids (VFA) production, and microbiota composition in calves fed a high-starch diet. Twenty-eight 5-month-old Holstein males were assigned to a control diet (control group) or the same diet with addition of 15 g/animal/day of the additive (Phytogenic group) for 70 days. Calves fed with additives had greater weight gain and average daily gain (p = 0.05), whereas dry matter intake and feed efficiency were unchanged. The additive reduced total leukocytes and lymphocytes number, decreased of biomarker in serum as TNF-α, IL-1, C-reactive protein, ferritin, haptoglobin, creatine kinase, cholinesterase, TBARS, and reactive oxygen species. These animals of the Phytogenic group also have increased IL-10, IgA, IgG, total protein, and globulin concentrations compared to the control group. Ruminal and fecal VFA concentrations were higher in animals of Phytogenic group, including acetate, propionate, and butyrate. In addition, intake of additives increased ruminal microbial richness and altered beta diversity, indicating a marked shift in rumen microbial structure, while altering the relative abundance of specific taxa associated with high-starch feeding. These findings indicate that this phytogenic blend improves growth performance and exerts immunomodulatory, antioxidant, and microbiota-modulating effects, supporting its use as a nutritional strategy to mitigate the metabolic challenges associated with high-starch diets in growing cattle. Full article

In this study, nine barium sulfate (BaSO₄)-supported heterogeneous catalysts (C1–C9) were synthesized via three modification strategies: stearic acid coating (C1–C3), physical doping (C4, C6, and C8), and sol-gel processing with calcination (C5, C7, and C9). Their comprehensive characterization revealed that sol-gel-synthesized C7 exhibited the most favorable surface properties, including well-dispersed Al–O–Si species, tetrahedrally coordinated Al³⁺, and abundant Brønsted acid sites. Their catalytic performance was evaluated in the chlorination of toluene, fluorobenzene, bromobenzene, and iodobenzene, using hydrochloric acid (HCl) as the chlorine source and either hydrogen peroxide (H₂O₂) or ammonium persulfate ((NH₄)₂S₂O₈) as the oxidant. C7 achieved complete toluene conversion (100%) at 60 °C under optimized conditions and exhibited high conversions of fluorobenzene (55%), bromobenzene (76%), and iodobenzene (46%). Notably, ammonium persulfate enabled a unique in situ halogen exchange pathway, yielding chlorobenzene as the exclusive product from bromobenzene and iodobenzene. XRD and XPS analysis of crystalline by-products confirmed the formation of NH₄HSO₄, BaSO₄, and NH₄Cl, providing evidence for the persulfate-driven radical mechanism. Iodine detection in upper-layer crystals confirmed iodobenzene products, while the absence of chlorine signals in the upper layer confirmed separation of organic and inorganic species. The detection of barium sulfate peaks confirms that the catalyst support retains its structural integrity under harsh reaction conditions, demonstrating chemical stability and reusability potential. Collectively, these findings establish a clear structure–activity relationship and demonstrate that the synergy between modified BaSO₄ surfaces and persulfate-generated radicals provides an efficient, sustainable platform for aromatic chlorination, offering significant potential for pharmaceutical, agrochemical, and fine chemical manufacturing applications. Full article

Optimizing nitrogen (N) management is essential for improving grain yield, quality, and nitrogen use efficiency (NUE) in low-gluten wheat, yet the optimal fertilizer strategy remains unclear. A two-year field experiment was conducted to evaluate the effects of common urea (CU), controlled-release urea (CRU), and their combination on yield, quality, NUE, and soil N content in low-gluten wheat. The results showed that, compared with 100% common urea (CU100), 100% controlled-release urea (CRU100) increased grain yield by 8.51% in 2023 and 14.3% in 2024, while 80% controlled-release urea and 20% common urea (CRU80CU20) increased grain yield by 19.2% in 2023 and 23.3% in 2024. These increases were accompanied by enhanced grain number per spike and dry matter accumulation. CRU-based treatments improved NUE, with the highest NUE observed in the CRU80CU20 treatment. Compared with CU100, CRU80CU20 significantly decreased grain protein content while maintaining high grain yield. Path analysis indicated that CRU was positively associated with dry matter accumulation, which in turn was positively associated with grain yield, whereas N translocation was closely associated with grain protein-related quality. In conclusion, CRU80CU20 provided a favorable combination of high grain yield, high NUE, and lower grain protein content, indicating that it is a promising N management strategy for the production of low-gluten wheat. Full article