Search Results (25,673)

Feed efficiency traits are increasingly important in pig production for improving profitability and environmental sustainability. Understanding their genetic basis is crucial for uncovering underlying biological mechanisms and informing selection strategies. In this study, we analyzed residual feed intake (RFI), feed conversion ratio (FCR), and average daily feed intake (ADFI) in 201 animals. Three separate Bayesian GWASs were conducted using 29,844 SNPs in a case–control design, with the lowest and highest 15% of the phenotypic distribution selected as controls and cases (N = 30 per group), respectively, for each trait. The results confirmed the polygenic nature of the traits, identifying 4 SNPs for RFI on Sus scrofa chromosomes (SSC) 3, 13, and 15 with high posterior probability for the direction of their effects; 4 SNPs for FCR on SSC 8, 14, and 17; and 8 SNPs for ADFI on SSC 1, 2, 6, 8, and 11. A candidate gene search identified 41 potential genes involved in diverse biological processes, including feed efficiency, intestinal development, tissue remodeling and integrity, nutrient transport and absorption, metabolic homeostasis, cellular signaling, energy sensing, and neurological regulation. These genes formed a highly interconnected network, highlighting the complexity of feed efficiency and the interplay among multiple physiological, metabolic, and regulatory pathways. Full article

Cacao swollen shoot disease (CSSD) remains a major viral threat to cacao production in West Africa and is associated with a genetically diverse complex of badnaviruses. We combined alignment-free whole-genome distances with circular sliding-window mosaic barcodes to characterize global divergence and local compositional modularity across 48 full-length CSSD-associated badnavirus genomes, hereafter termed the cacao swollen shoot virus (CSSV) complex. Whole-genome tetranucleotide cosine distance clusters matched published species assignments exactly (adjusted Rand index = 1.00; normalized mutual information = 1.00; silhouette = 0.703) and were strongly concordant with an alignment-based distance derived from open reading frame 3 (ORF3) proteins (Spearman ρ ≈ 0.951; permutation p ≈ 0.0002). A three-component mosaic-complexity score summarized low dominant-label purity, barcode entropy normalized by log₂(K), and circular switch rate; ORF–mosaic agreement was retained as a separate diagnostic and did not contribute to the ranking. Threshold sensitivity showed that barcode switchpoints were enriched within ±100 and ±200 bp of predicted ORF boundaries, but not within ±400 bp. The ten highest-scoring genomes showed slightly higher mean local nucleotide entropy but lower entropy variance and dispersion than the remaining genomes, indicating more uniformly distributed compositional complexity rather than isolated local spikes. These analyses provide a transparent framework for post-sequencing classification, comparison, and prioritization of complete viral genomes. The barcode and score outputs are exploratory summaries and are not direct field diagnostic assays or nucleotide-resolution recombination tests. Full article

The increasing generation of construction and demolition waste, along with the depletion of natural aggregates, has driven growing interest in recycled concrete aggregate (RCA) and reclaimed asphalt pavement (RAP) as sustainable alternatives in concrete production. However, a direct and systematic comparison between the two materials remains limited. This review addresses this gap by applying PRISMA guidelines to analyze 82 peer-reviewed studies published between 2010 and 2026. Both materials are evaluated across three key domains: physical properties, mechanical performance, and microstructural characteristics. The findings indicate that RCA can reduce compressive strength by up to 26%, mainly due to the presence of porous adhered mortar and a complex interfacial transition zone (ITZ). In contrast, RAP weakens bonding with cement paste because of its hydrophobic bituminous coating, leading to adhesive failure at the mortar asphalt interface. Despite these limitations, RCA and RAP exhibit distinct behaviors in terms of shear capacity, ductility, energy absorption, and durability. Enhancement techniques such as surface treatment, carbonation, supplementary cementitious materials, and fiber reinforcement show potential in improving performance. Additionally, life cycle and economic analyses reveal that RAP can reduce total costs and carbon emissions when efficiently processed. This study provides a unified comparative framework to support sustainable material selection and design optimization. Full article

Nerve injuries are frequent complications of complex oral and maxillofacial surgical procedures, particularly following extensive tumor resections. Secretome-based, cell-free therapies derived from mesenchymal stromal cells have emerged as promising regenerative approaches; however, robust manufacturing requires the identification of critical quality attributes (CQAs) that ensure product potency and consistency. The influence of replicative senescence during in vitro expansion on the quality of jaw periosteum-derived mesenchymal stromal cell (JPC) secretomes has not yet been established. This study investigated whether the expansion state of JPCs affects the composition and neuro-supportive potency of their secretomes. Secretomes from four independent JPC donors were collected separately at early and late passages, pooled within each passage-specific preparation, and applied to human induced pluripotent stem cell-derived neurons. Neuronal survival, neurite outgrowth, and neuronal marker expression were assessed as functional readouts. Secretome composition was characterized by quantitative proteomics and enzyme-linked immunosorbent assay (ELISA) of selected senescence-associated secretory phenotype (SASP) factors. Secretomes derived from early-passage JPCs significantly enhanced neuronal survival and neurite outgrowth, whereas late-passage secretomes displayed reduced neuro-supportive activity. Proteomic profiling identified a pronounced shift toward inflammatory and stress-associated signaling, whereas performed ELISAs confirmed senescence-associated remodeling of the secretome, including increased abundance of SASP-associated factors in late-passage preparations. These findings demonstrate that prolonged in vitro expansion profoundly influences both the composition and biological potency of JPC-derived secretomes. Collectively, this study identifies the passage-associated senescence-like phenotype of JPCs as a key determinant of secretome quality and supports its consideration as a critical quality attribute for the manufacturing and standardization of JPC-derived secretome products. Monitoring and controlling the expansion state of JPCs may therefore be essential to ensure the consistency, potency, and clinical translation of secretome-based regenerative therapies. Full article

Flammulina velutipes roots, abundant edible mushroom by-products, have potential for value-added utilization. This study evaluated the effects of Lactiplantibacillus plantarum (Lpb. plantarum) and Lactobacillus delbrueckii subsp. bulgaricus (Lab. bulgaricus) fermentation on the physicochemical properties, antioxidant activity, flavor characteristics, sensory characteristics, and metabolite profiles of F. velutipes roots. Fermentation significantly increased soluble dietary fiber (SDF) from 1.537 to 1.722 g/100 g and DPPH radical scavenging activity from 27.88% to 59.92% in Lpb. plantarum-treated samples. GC-IMS analysis showed that fermentation increased several flavor-active aldehydes, esters, alcohols, organic acids, and ketones, thereby improving aroma complexity. LC-MS-based untargeted metabolomics revealed that amino acid metabolism, fatty acid metabolism, organic acid metabolism, and phenylpropanoid-related pathways were closely associated with flavor formation and antioxidant enhancement. Both Lpb. Plantarum and Lab. bulgaricus fermentation enhanced the accumulation of organic acids, sugar alcohols, and aromatic precursors, supporting improved antioxidant activity. Notably, Lpb. plantarum elicited broader metabolic shifts involving hydroxy fatty acids, esters, while Lab. bulgaricus more strongly promoted organic acid and aromatic metabolite accumulation, contributing to a more acidic and malty flavor profile. Sensory evaluation and electronic tongue analysis further confirmed that fermentation enhanced aroma and palatability, while increasing sourness and reducing bitterness and astringency. These results suggest that starter-culture-dependent lactic acid bacteria fermentation is an effective strategy for improving the functional and sensory characteristics of F. velutipes root by-products. Full article

Refugee camps have evolved from temporary shelters into permanent, complex urban systems, yet policy models often fail to address their long-term systemic marginality. To bridge this gap, this study conducts a comparative qualitative analysis of three protracted cases in the Middle East: Shatila (Lebanon), Yarmouk (Syria), and Jabalia (Gaza). Using a directed qualitative content analysis, the study evaluates secondary data, spatial reports, and institutional archives across five core System Pillars: Governance Configurations, Legal Regimes, Humanitarian Mediation, Spatial Violence, and Grassroots Agency. Findings show that conditions of urban exception are sustained by a self-reinforcing nexus of these processes. Furthermore, a dual-process model of refugee agency emerges, distinguishing short-term adaptive survival tactics (e.g., informal DIY utility grids) from constitutive practices of urban citizenship that reconfigure institutional aid protocols. In post-conflict contexts, physical destruction is systematically coupled with state-led property legislation to enforce permanent displacement. We conclude that protracted camps must be recognized as dynamic, co-produced urban systems rather than static zones of exception. Effectively breaking cycles of socio-spatial marginalization requires international actors to transition from short-term emergency assistance to rights-based metabolic planning, legal tenure protection, and formalized institutional co-production frameworks. Full article

Satellite precipitation products like GPM IMERG are crucial for hydrological modeling and disaster prevention; yet, their reliability in complex mountainous monsoon regions remains challenging. While the latest IMERG V07 introduces key upgrades, including a Climatological Calibration Algorithm (CCA), its cross-scale error propagation mechanisms and performance heterogeneity in complex underlying surfaces are poorly understood. This study evaluates the daily and monthly performance of IMERG V07 and V06 (Early, Late, and Final Runs) from 2014 to 2020 against 91 rain gauges in Guangxi, China—a typical mountainous monsoon region. The evaluation employs multiple statistical metrics and a multi-dimensional stratification approach based on elevation, precipitation intensity, and seasonality to quantify error propagation and climate-topography coupling effects. The results reveal that V07, particularly the Late Run, enhances daily precipitation detection capabilities, it significantly increases the proportion of systematic positive bias from 62.3 to 64.8% (V06) to 67.2–68.9% (V07). Consequently, upon temporal aggregation to the monthly scale, this systematic overestimation is severely amplified, leading to degraded performance, with the Final Run suffering the most substantial accuracy loss. Furthermore, retrieval accuracy is heavily constrained by surface heterogeneity, with systematic overestimation surging in areas where relatively dry (mean annual precipitation < 1300 mm) and complex terrain (elevation 100–500 m) coincide. The introduced CCA effectively improved dry season estimations but failed during wet season by introducing substantial positive biases. Ultimately, while V07 better captures short-term precipitation dynamics, its structural systematic biases compromise long-term cumulative reliability, highlighting the necessity for physics-based bias correction in hydrological applications and dynamic calibration in future algorithm upgrades. Full article

Warm-season precipitation over Sichuan, China, is jointly modulated by complex terrain, monsoon water vapor transport, and local convective activities, leading to significant spatiotemporal heterogeneity. However, radar observations over mountainous areas are frequently impaired by terrain blockage, beam shielding, and insufficient network coverage, which cause missing data and spatial discontinuity, thereby restricting the accurate monitoring of precipitation systems. To alleviate these problems, this study develops an Efficient Multi-Scale Attention (EMA) U-Net model integrated with Digital Elevation Model (DEM) information, termed EMA-U-Net-DEM, to retrieve radar composite reflectivity by utilizing multi-channel observations from the Fengyun-4A (FY-4A) Advanced Geostationary Radiation Imager (AGRI). In the experiments, FY-4A AGRI multi-spectral measurements were used as model inputs, while radar composite reflectivity products from the Severe Weather Automatic Nowcasting (SWAN) system were applied as reference labels. The modeling and validation were carried out using warm-season (June–August) datasets over Sichuan Province. The results indicate that the proposed EMA-U-Net-DEM exhibits better performance than the traditional U-Net and several typical attention-based benchmark models. Quantitatively, the model achieves a root mean square error (RMSE) of 6.728 dBZ, a mean absolute error (MAE) of 4.788 dBZ, a coefficient of determination $R^2$ of 0.656, a peak signal-to-noise ratio (PSNR) of 25.243 dB, and a structural similarity index measure (SSIM) of 0.793. Categorical verification further reveals that the model yields the highest critical success indices (CSI) of 0.850, 0.560, and 0.364 in the reflectivity ranges of 0–25 dBZ, 25–45 dBZ, and 45–70 dBZ, respectively, demonstrating its superior ability in characterizing weak precipitation backgrounds, moderate precipitation structures, and intense convective cores. The performance enhancements are mainly attributed to the strengthened multi-scale feature extraction by the EMA module and the effective topographic constraints introduced by DEM data. This study confirms that the fusion of FY-4A multi-spectral observations and topographic information can effectively improve radar composite reflectivity retrieval over complex terrain, providing a feasible solution for precipitation monitoring, quantitative precipitation estimation, and severe weather nowcasting in mountainous regions with limited radar coverage. Full article

Background/Objectives: Propolis is a resinous natural product rich in phenolic acids and flavonoids, recognized in ethnopharmacology for its antioxidant and anti-inflammatory properties. This study aimed to identify the most bioactive Saudi propolis extract using a bioassay-guided strategy and investigate its chemical profile and mechanistic anti-inflammatory potential. Methods: Four propolis extracts (P1–P4) collected from different regions of Saudi Arabia were evaluated for their antioxidant (DPPH and ABTS) and anti-inflammatory (COX-1 and COX-2) activities. The most active extract was profiled using liquid chromatography–mass spectrometry (LC–MS), followed by molecular docking and molecular dynamics simulations. Results: Among all samples, P3 demonstrated the strongest antioxidant activity, with IC₅₀ values of 25.84 ± 0.96 µg/mL (DPPH) and 32.30 ± 1.20 µg/mL (ABTS), comparable to ascorbic acid (27.45 ± 1.42 and 21.22 ± 0.79, respectively). P3 also exhibited potent and selective COX-2 inhibition with an IC₅₀ of 6.19 ± 0.21 µg/mL (relative to celecoxib, IC₅₀ 0.681 ± 0.02 as positive control). LC–MS analysis identified 26 secondary metabolites. Computational studies ranked kaempferol as forming the most conformationally stable COX-2 complex among the ligands examined, including the reference inhibitor, on the basis of molecular dynamics descriptors of pose persistence and conformational confinement. Conclusions: Saudi propolis P3 is a potent source of bioactive compounds with strong antioxidant and selective COX-2 inhibitory activity. These findings highlight its anti-inflammatory potential and suggest its value as a natural lead for developing safer therapeutics targeting inflammation-related chronic diseases. Full article

Sclerotinia sclerotiorum causes destructive sclerotinia stem rot and severe yield losses in global rapeseed production. The Bacillus biocontrol strain YZUS007 serves as an eco-friendly alternative to synthetic fungicides, yet its control efficacy fluctuates under complex field conditions. This study aimed to investigate whether low-dose ZnO NPs could enhance the biocontrol efficacy of YZUS007 and to elucidate the underlying mechanisms. We isolated and identified the antagonistic strain Bacillus siamensis YZUS007 from the rhizosphere soil of healthy Brassica napus, which exhibited an in vitro pathogen inhibition rate of 78.4 ± 0.7%. Pot tests showed that YZUS007 (BC) achieved 60.79% control efficacy, whereas the YZUS007 + 20 μg/mL ZnO NPs group (BZ) reached 74.68%. Cell-free filtrate of YZUS007 (EC) had a 50.44% control efficacy, and filtrate with ZnO NPs (EZ) increased efficacy to 58.08%. LC-MS/MS identified four extracellular metabolites with increased relative abundances: cinnamic acid, sesamol, patchouli alcohol and 2-phenylbutyric acid. The combined treatment boosted defense enzyme activities and induced higher expression of the defense-related genes RBOH, PR1 and WRKY33. Collectively, low-concentration ZnO NPs significantly enhanced the biocontrol performance of YZUS007 by promoting antifungal metabolite accumulation, providing a low-dose, nanomaterial-assisted strategy for sustainable sclerotinia rot management. Full article

To address the issue where information asymmetry in third-party logistics (3PL)-led low-carbon supply chain coordination undermines coordination efficiency, thereby threatening the sustainability and resilience of supply chain cooperation, this paper develops a Stackelberg dynamic game model with the 3PL as the leader. This model is constructed within the context where consumers’ low-carbon preferences influence product demand, and a government carbon cap policy is implemented. By comparing decentralized and centralized equilibria, we verify that centralized collaboration achieves dual gains: higher carbon reduction levels and greater overall supply chain profits, which strengthens sustainability and resilience. To address efficiency losses from three types of information asymmetry, we propose a two-stage dynamic coordination mechanism adapted to evolving cooperation transparency. At the initial stage with opaque information, a bargaining-power-weighted profit-sharing contract is adopted, where negotiation weights are quantified by enterprise scale, resource control and industry influence. After data transparency improves, the system switches to a Nash bargaining framework supported by blockchain carbon data sharing to realize stable long-term collaboration. Numerical cases and sensitivity analysis demonstrate that manufacturer cost information asymmetry is the primary constraint on coordination efficiency. The proposed dynamic coordination scheme effectively mitigates systemic complexity, balancing economic benefits and carbon reduction targets. This study provides practical pathways for supply chain participants to navigate complex low-carbon environments and advance sustainable, resilient supply chain operation. Full article

In this paper, we investigate a simulation-based optimization framework that implements discrete-event simulation with evolutionary search methods to optimize stochastic manufacturing systems efficiently. The proposed methodology couples a Tecnomatix Plant Simulation model with a MATLAB R2025b-based optimization environment using a data exchange interface, allowing for the iterative assessment of complex manufacturing systems. The study examines an adaptive replication strategy designed to manage stochastic variability in simulation outcomes. In the proposed method, the required number of simulation runs are determined dynamically based on confidence interval estimation. The stopping criterion is specified using a 95% confidence interval, ensuring adequate statistical accuracy while decreasing excess computational effort. The framework allows multiple performance indicators, such as throughput, congestion levels, and machine failures, which are built into an objective function. The optimization is driven by a (1, λ)-evolution strategy with Gaussian mutation and adaptive step-size control, allowing robust search in noisy objective function. However, thanks to the framework presented, it is also possible to apply other optimization algorithms. A case study of a manufacturing system was built and modeled in Tecnomatix Plant Simulation to validate the proposed methodology. In comparison with the baseline production configuration in one of the simulation runs, the suggested framework reduced the objective function by 43.36%. Benchmark experiments demonstrated that the adaptive replication strategy achieved a solution quality comparable to fixed replication schemes while requiring fewer simulation evaluations on average, thereby reducing the computational effort without compromising statistical reliability. The benchmark comparison showed that the adaptive replication strategy improved the objective value by up to 17.20% compared with fixed-replication strategies while requiring substantially less computational time than the fixed-20 and fixed-30 strategies. The robustness analysis further demonstrates that the adaptive replication strategy produces consistent optimization results across independent runs despite the stochastic nature of both the simulation model and the optimization process. From an industrial perspective, the proposed framework provides a practical decision-support tool for the optimization of manufacturing systems under uncertainty, enabling more reliable parameter tuning with reduced computational effort and facilitating the implementation of digital twin technologies. Full article

This study investigates the effect of a brand-new tank-mix adjuvant, Spray Adjuvant—Paraffinic Hydrocarbon Surfactant Complex (SA-PHSC), in enhancing the efficacy of commonly used insecticides and acaricides against two significant pests of tea plantations, the black looper (Hyposidra talaca) and the red spider mite (Oligonychus coffeae). Given the pest’s major influence on tea cultivation, which can result in output reductions of up to 55%, this study addresses mounting concerns of pesticide resistance and climate change. Laboratory bioassays showed that the combination of SA-PHSC with the insecticides quinalphos, deltamethrin, and emamectin benzoate, and acaricides etoxazole and fenpyroximate, significantly increased the mortality rates of H. talaca larvae (76.67–100.0%) and O. coffeae adults (100.0%). Additionally, enhancements were noted in the mechanisms of pest cuticular penetration and contact toxicity. These observations were corroborated by field trials, which demonstrated enhanced control of H. talaca (70.47–97.63%) and O. coffeae (75.87–96.59% reduction) populations, as well as increased green tea leaf yields, as a result of SA-PHSC treatment in conjunction with the evaluated pesticides. In addition, the study evaluated the phytotoxicity and organoleptic attributes of the made tea after application, confirming the safety and absence of any off-flavors in the final product (scoring 6.6–7.0). These findings indicate that SA-PHSC could serve as a valuable adjuvant for sustainable pest management in tea cultivation, as it has the ability to optimize the application of currently recommended insecticides and acaricides and restore pest susceptibility. Full article

The transition of adsorbent materials from laboratory synthesis to industrial application requires a rigorous assessment of their durability under high concentrations. This study evaluates composite alginate hydrogels incorporating mill scale-derived magnetite (Fe₃O₄), activated carbon, and L-ascorbic acid (Fe₃O₄/AC/VitC alginate hydrogels) for the detoxification of highly concentrated chromium effluents. We investigated the operational limits of these hydrogel bubbles through three distinct scenarios: (1) Single-Batch Adsorption–Regeneration Cycling in Fresh Cr(VI) Solutions, (2) Sequential Reuse of Single-Batch Hydrogel Bubbles in the Same Effluent for Complete Cr(VI) Removal, and (3) the Multi-Batch Treatment Capacity Test for highly concentrated Cr(VI) loads. The composite demonstrated exceptional robustness, maintaining >80% removal efficiency over five cycles for 100 mg/L Cr(VI) without chemical treatment. For higher loads (150–400 mg/L), a simple regeneration protocol effectively restored performance, reducing Cr(VI) levels to below stringent discharge limits (<0.25 mg/L). Furthermore, in “worst-case” scenarios involving synthetic solutions (2500 mg/L) and real electroplating wastewater (~2000 mg/L), a multi-batch approach achieved complete abatement within 8–9 cycles. Notably, the treatment simultaneously neutralized the effluent pH from ~1.0 to 7.0, confirming the potential of this waste-derived material as a resilient, multi-functional solution for complex industrial wastewater management. Beyond performance, a techno-economic analysis was conducted to evaluate the economic feasibility of industrial-scale production. The results indicate that by utilizing industrial-grade reagents and waste-derived precursors, the production cost of the dry adsorbent can be estimated at ~45 EUR/kg. These findings confirm the potential of this material as a cost-effective, multi-functional solution for SMEs struggling with high operational costs and stringent environmental regulations. Full article

Cross-phase collaborative management in complex product systems (CoPS) development is inherently challenged by heterogeneous organizational coupling and stochastic disturbances. Although digital twin (DT) and model-based systems engineering (MBSE) technologies provide foundations for physical–virtual synchronization and model traceability, existing approaches remain fragmented in three respects: insufficient requirements-traceable architectural integration, limited cross-phase semantic interoperability and runtime evolution, and weak operational links between semantic reasoning and adaptive decision models. To address these gaps, this paper proposes an MBSE-driven digital twin framework with semantic enhancement. First, a four-layer architecture is derived using the MagicGrid methodology, encompassing physical–virtual mapping, semantic reasoning, decision support, and service interaction. Second, a collaboration-oriented SysML profile is developed to standardize the representation of tasks, resources, materials, disturbances, and management constraints across engineering phases. Third, a knowledge-driven adaptive collaboration mechanism maps runtime disturbance inputs into semantic states, propagates their cross-phase impacts, supports process-topology reconfiguration, and generates decision-ready constraints for adaptive management. A case-based prototype for aero-engine turbofan blade development demonstrates the feasibility of the mapping–reasoning–decision chain and provides case-level evidence of improved cross-phase coordination under controlled disturbance scenarios. The results indicate a feasible engineering pathway from perceptive DT functions toward reasoning-enabled collaborative decision support. Full article