Search Results (24,832)

The invasive yellow-legged hornet Vespa velutina nigrithorax has spread across Europe following its accidental introduction into France in 2004. This species adversely affects biodiversity, apiculture, pomiculture and viticulture, and human health. Current management relies predominantly on nest destruction; however, manual removal is often logistically challenging and costly because nests are typically located high in trees (up to 30 m), frequently necessitating vehicle-mounted lifts. Ground-based application of biocides using long injection lances is comparatively rapid and inexpensive, but in many countries, insecticides are not permitted because the products are not specifically authorized for hornet control. Consequently, alternative approaches are needed. Here, we evaluated the efficacy of activated charcoal for nest destruction in V. v. nigrithorax. We injected 145 nests with 50–100 g of activated charcoal and subsequently destroyed the nests. One week later, we assessed worker survival and the establishment of new nests. Emergency nest construction by surviving workers was observed in three of 145 cases (2.1%). This rate was comparable to that observed following insecticide treatment (two of 136 cases; 1.5%). Activated charcoal therefore appears to be similarly effective to insecticide-based control while offering advantages in terms of environmental compatibility, user safety, ease of handling, and legal applicability in Europe. Activated charcoal may represent a practical alternative to manual nest removal and unauthorized insecticide use. Full article

Flocs, visible particles formed in sugar-sweetened beverages, reduce clarity and consumer acceptance of products. Their presence can be caused not only by different types of trace impurities in the sugar but also by interactions among beverage components. In this review, scientific reports on acid beverage flocs (ABFs) and alcohol flocs are summarized, the main pathways for their formation are described, and practical options for detecting them and preventing their formation in beverages are compiled. Using Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 and related guidance, literature searches of Scopus, Web of Science (WoS), PubMed, Food Science and Technology Abstracts (FSTA), CAB Abstracts, and International Commission for Uniform Methods of Sugar Analysis (ICUMSA) resulted in the inclusion of 56 studies. In various types of beverages, complexes formed between proteins (Ps) and polyphenols (PPs) often initiate haze and floc formation, while polysaccharides (dextran, pectin, and starch), silica or silicates, and inorganic ions influence charge balance, particle bridging, and floc growth rate. Ethanol in alcohol beverages can further destabilize colloids and promote aggregation. For beet sugars, saponin–protein interactions are a likely pathway for the formation of ABF, but the available evidence is not consistent. In cane sugars, the reported roles of proteins, polysaccharides, silica, and starch in floc formation vary considerably between studies. For quality assurance, ICUMSA floc tests (GS2-40 and GS2-44) should be complemented by turbidity or haze measurement and colloid characterization such as light scattering, ζ–potential, and infrared IR-based analytical methods supported by chemometrics. Risk mitigation works best as a two-level strategy that combines impurity removal during sugar production and stabilization steps in beverage formulation and storage, including the use of clarification agents and control of pH, temperature, ionic strength, and oxygen exposure. Standardized reporting and validation of rapid predictors against ICUMSA benchmarks remain essential. Full article

Aquaculture marks the transition from the simple activity of harvesting aquatic animal resources, carried out through the catching practices of fishing, to the farming of aquatic organisms in fresh, brackish and sea waters, carried out through human intervention aimed at increasing production. To date, research is proceeding towards expanding the range of species that can be farmed, improving the number and quality of products, and reducing the environmental impact of aquaculture activities; these efforts are supported by the improvement of our knowledge of the biology of the relevant species, the significant updating/upgrading of the rearing technologies, and the increasing awareness of the importance of water quality in optimising farming conditions. While necessarily dependent on market demand, aquaculture needs to fully leverage its environmental potential; and the relationship between aquaculture and the environment requires a system of production that combines eco-compatibility and eco-sustainability. Here, we report and analyse insights and perspectives in eco-sustainable aquaculture, spanning from sustainability and innovation processes in aquaculture to antibiotic control and aquaculture ecosystem services, in the context of the United Nations Sustainable Development Goals. Full article

The Historic Urban Landscape (HUL) approach provides a vital and extensive framework for heritage conservation. However, local practices often struggle to spatially translate qualitative assessments into quantitative controls at the urban block level, the most effective basic scale for administrative implementation, thereby limiting effective responses to the Management of Change. By integrating HUL with the theory of Dynamic Integrity, this study constructs a multi-dimensional evaluation index system and proposes a HUL evaluation method based on Character-Based Zoning. Taking the 125 urban block units of the historic urban area of Jingdezhen as a case study, this research integrates historical mapping, GIS spatial analysis, and Co-occurrence Network Analysis to reveal the internal structural logic of the heritage system. The study finds that the HUL of Jingdezhen is a multi-nodal dynamic system driven by four core elements: ritual beliefs, administrative management, production activities, and commercial guilds. Critically, modern visual intrusions severely impact the core heritage components within this system, specifically the Dubang and ritual culture. Based on the three dimensions of Heritage Richness, Landscape Sensitivity and Value Centrality, the study systematically identifies a total of 11 types of urban block units within the plots that characterize distinct historic landscape features and transformation patterns. This research not only deepens the localized application of HUL theory but also provides a scientific basis and methodological support for the Management of Change and periodic assessment in dynamic heritage environments. Full article

Accurate and scalable body condition scoring (BCS) is important for health monitoring and productivity management in precision livestock farming. However, manual scoring is subjective, labor-intensive, and difficult to standardize, while many automated methods are too computationally demanding for edge deployment in real farm environments. This study proposes EdgeBCS-YOLO, a lightweight object detection framework for real-time beef cattle BCS in unstructured farming scenarios. Built on YOLO11n, it combines Position-Sensitive Feature Fusion (PSFF), a Texture-Aware Star Module (TASM), an Efficient Grouped Detection Head (EGDH), and a Focal and Global Knowledge Distillation (FGD)-based distillation strategy. On a dynamic blurring dataset, EdgeBCS-YOLO achieved 90.8% precision, 82.7% recall, and 88.9% mAP@50. On the NVIDIA Jetson Orin NX Super, it achieved a model size of 3.95 MB, a system FPS of 33.35, and an average inference latency of 13.26 ms. These results suggest that it is a practical and potentially efficient solution for automated BCS on edge devices. Full article

Understanding crop water use is essential for improving agricultural water management and ensuring sustainable food production, especially in regions with limited water resources. Evapotranspiration (ET) is a key component of the hydrological cycle, directly influencing irrigation planning and crop productivity. However, accurately estimating ET at local scales remains a challenge due to the limitations of conventional measurement methods and the difficulty of integrating high-resolution remote sensing data. This study investigates the estimation of terrestrial evapotranspiration (ET) in a sugarcane cultivation area located in the northern coastal region of Paraíba, Brazil, using meteorological data and aerial images acquired by an Unmanned Aerial Vehicle (UAV). We adapted the PT-JPL model to estimate ET at the local scale, using thermal and multispectral imagery obtained from UAVs. Data validation was performed using surface energy balance measurements obtained from a micrometeorological tower, thereby enabling comparison of estimated and observed ET values. The results demonstrated strong correlations between modeled predictions and field measurements of net radiation (R² = 0.85), with performance metrics indicating moderate reliability for local-scale simulated ET when compared to flux-tower-based ET (R² = 0.48; RMSE ≈ 0.045 mm/30 min). This research highlights the potential of integrating UAV-based remote sensing with the PT-JPL model to improve understanding of crop water use, support irrigation management, and contribute to sustainable agricultural practices. Full article

Irreversible covalent enzyme inhibitors, including targeted covalent inhibitors (TCIs) and mechanism-based enzyme inhibitors (MBEIs), play an increasingly important role in drug discovery. Their pharmacological behavior is governed by intrinsic inactivation parameters, typically described by the inactivation constant K_I, the maximal inactivation rate constant k_inact, and their ratio k_inact/K_I. However, no consensus exists regarding how these parameters should be experimentally determined and interpreted, particularly in high-throughput screening environments where IC₅₀ values are often used as primary descriptors. This article presents a critical survey of the kinetic methodologies employed to characterize irreversible enzyme inhibition. Continuous progress-curve analysis, discontinuous end-point assays, IC₅₀-based estimation strategies, direct mass-spectrometric monitoring of covalent modification, and numerical approaches required by pre-incubation protocols are examined and compared. Attention is given to the statistical robustness of parameter estimation under realistic experimental error, including bootstrap-based uncertainty analysis. For mechanism-based enzyme inhibitors, the kinetic consequences of branching between productive turnover and irreversible inactivation are analyzed, and limitations of classical half-life-based linearization methods are discussed. Intrinsic inactivation parameters are distinguished from protocol-dependent observables, and experimental conditions that may compromise reliable parameter extraction are identified. The objective is to clarify how irreversible inhibitors should be kinetically characterized when the goal is mechanistic understanding and rational drug design. By bridging classical enzymology with current discovery practices, this review provides practical guidance on what experimental data can legitimately support and where caution is required. Full article

Methane steam reforming (MSR) is the most widely used industrial process for hydrogen production. However, catalyst deactivation, carbon emissions, and energy inefficiencies limit its sustainable performance. Therefore, improving catalyst selection and optimizing operating conditions are essential for efficient hydrogen generation. This study proposes an artificial intelligence-driven framework to optimize catalyst–condition combinations in MSR systems. The framework integrates Hybrid Golden Beetle Optimization (HGBO), VIKOR-based multi-criteria decision making, and Convolutional Long Short-Term Memory (ConvLSTM) modeling. HGBO explores the solution space and generates Pareto-optimal combinations of catalysts and operating conditions. These solutions are then ranked using the VIKOR method. The ranking considers hydrogen yield, methane conversion, energy efficiency, CO₂ emissions, and catalyst lifetime. Economic feasibility is also included in the decision process. ConvLSTM modeling captures spatiotemporal relationships in catalyst and process data and predicts catalyst degradation under different operating conditions. The framework is evaluated using 620 experimentally reported MSR cases collected from the published literature within industrial ranges of 600–1200 °C, 1–40 bar, and H₂O/CH₄ ratios of 1–6. The optimized configurations achieve hydrogen yields up to 98.5%, energy efficiency approaching 99%, and reduced CO₂ emissions of about 0.85 kg h⁻¹. The results provide practical guidance for catalyst selection and process optimization in industrial hydrogen production systems. Full article

Membrane distillation (MD) is an attractive technology for desalination driven by renewable energy and low-grade heat sources. However, specific practical guidelines for intermittent operations, typical of such alternative energy sources, are still limited—particularly with respect to established shutdown measures to mitigate adverse effects on the overall system performance. The present study compares continuous and intermittent air-gap MD desalination at a lab-scale by evaluating performance parameters and scaling development. Apart from a slightly lower distillate productivity and a similar distillate quality under intermittent conditions, no direct difference in MD performance between continuous and intermittent experiments was detected. Nevertheless, online monitoring by image analysis with optical coherence tomography revealed more advanced scaling development during intermittent operation, with larger scaling volumes and cover ratios, particularly after implementing a membrane rinsing and preservation protocol with demineralized water. Membrane autopsies revealed that intermittency led to alterations in the development of the crystal morphology of predominantly CaCO₃ scaling. These changes were attributed to enhanced nucleation and modified growth kinetics triggered by recurring shutdown and start-up phases. Overall, the findings showed that intermittency had an adverse effect in terms of scaling behavior, highlighting the need for operating protocols tailored to each specific MD application. Full article

Mesoscale modeling provides an efficient and cost-effective approach for investigating the damage mechanisms of fiber-reinforced concrete. To address the physical distortion in conventional models that arises from neglecting the volumetric effect of steel fibers and to construct a more realistic random mesoscale model of steel fiber-reinforced concrete (SFRC), this study proposes an efficient modeling method based on geometric entity expansion and point–line topology. First, polygonal aggregates with diverse morphologies are generated using a polar-coordinate perturbation scheme combined with a convex-hull correction algorithm. Next, abandoning the traditional zero-thickness line-segment assumption, steel fibers are expanded into rectangular entities via rigid-body kinematics to explicitly represent their excluded volume. Furthermore, a vector-cross-product-based Point–Line Method is developed to replace conventional circumscribed-circle screening, enabling accurate discrimination of interference interactions between fiber–aggregate and fiber–fiber pairs. An automated framework—consisting of skeleton placement, entity generation, topological discrimination, and mesh mapping—is implemented through a Python 3.13.9 scripting interface, allowing efficient batch generation of high-content mesoscale models with aggregate area fractions up to 70%. The proposed model is then used to simulate the failure process of SFRC specimens under uniaxial compression and benchmarked against experimental results. The results show that the developed mesoscale model accurately reproduces the nonlinear mechanical response and the strengthening–toughening effects of SFRC, achieving a relative error of only 0.31% in peak stress and a root mean square error (RMSE) as low as 1.70 MPa over the full stress–strain curve. The simulations not only confirm the pronounced strength gain due to steel fiber incorporation (~19.7%), but also reveal, at the mesoscale, the mechanism by which fiber bridging suppresses damage localization, thereby demonstrating the reliability and practical effectiveness of the proposed modeling approach. Full article

Introduction: The growing demand for traditional medicines and health supplements (TMHS) in Malaysia has raised concerns regarding microbial contamination in hard-shell capsule products. Despite regulatory oversight, recurring recalls highlight persistent non-compliance with Good Manufacturing Practice (GMP) standards. This study examines the risks of microbial contamination, recall patterns, and encapsulation practices among TMHS hard-shell capsule manufacturers in Malaysia. Methods: A cross-sectional approach was employed, comprising a review of regulatory guidelines, analysis of NPRA recall data from 2020 to 2024, and a structured survey of 86 TMHS manufacturers on equipment and production parameters. Results: Review of GMP guidance indicated that greater automation and reduced manual handling in capsule-filling processes help minimise microbial contamination. In line with this, TMHS products were recalled at a rate of 4.73%, more than 4 times the pharmaceutical recall rate (1.09%). Among the 245 TMHS recalls, 68 involved hard-shell capsule products that failed microbial testing, primarily total aerobic microbial count (73.53%). Additionally, manufacturers with 50–100 registered products had significantly higher odds of recall (OR = 10.0, 95% CI: 2.35–42.47). However, no significant associations were found between recall status and equipment type, capsule size, or production frequency. Conclusions: Microbial contamination remains a critical issue in TMHS hard-shell capsule products. Regulatory efforts should focus on medium-scale manufacturers and reinforce risk-based GMP adherence to enhance product safety and public health protection. Full article

Background: Early pregnancy loss, defined as the spontaneous loss of a pregnancy before 20 weeks of gestation or when the fetus weighs less than 500 g, remains a common obstetric complication, affecting up to 15% of clinically recognized pregnancies. Chromosomal abnormalities, particularly aneuploidies such as trisomies and monosomy X, account for 50–60% of first-trimester losses, with incidence increasing alongside maternal age. Additional risk factors include maternal medical conditions, uterine anomalies, infections, and modifiable lifestyle factors. Pregnancies conceived through assisted reproductive technologies also carry a slightly higher risk of miscarriage, often influenced by maternal age and embryo quality. Methods: Two pathologists, blinded to each other’s assessments, analyzed abortive material from patients who experienced spontaneous first-trimester abortion between January 2012 and January 2025 at Agostino Gemelli Hospital, Rome, Italy. Inclusion criteria were defined independently of patient demographics. No restrictions were applied regarding maternal age. With respect to gestational age, only first-trimester miscarriages (≤12 weeks of gestation) were considered. In cases of discordance, the case was reviewed and re-evaluated to reach a final diagnosis. Results: The findings of this study are presented as a proposed histopathological classification and diagnostic framework for first-trimester miscarriages. Specifically, a total of 1168 cases were categorized into eight distinct groups of miscarriage etiology based exclusively on the histomorphological features of chorionic villi and maternal decidua. Conclusions: Histopathological examination of products of conception is essential for confirming intrauterine pregnancy, identifying underlying maternal or fetal causes, and guiding future reproductive management, particularly in recurrent pregnancy loss. This study evaluates histopathological features of first-trimester losses, classifies findings by etiology, and proposes a practical diagnostic guide to support clinical decision-making and improve outcomes in subsequent pregnancies. Full article

While Generative Artificial Intelligence technology empowers content production on user-generated content platforms, it also gives rise to novel risks of disinformation dissemination. The effective governance of these risks is critical to ensuring the cybersecurity of the online ecosystem and maintaining long-term social stability. To address the collaborative governance dilemma, this study constructs a tripartite “platform-user-government” evolutionary game model based on prospect theory. It explores the evolutionarily stable strategies and stability conditions of each actor, supplemented by numerical simulations and practical case validation. The results indicate that: (1) under specific conditions, the system can converge to an ideal equilibrium {active platform governance, engaged user participation, stringent government supervision}; (2) the government’s reward–penalty mechanisms can drive the system towards this ideal equilibrium; (3) users’ digital literacy is a key variable influencing the system’s evolutionary path; (4) both the risk preference coefficient (β) and loss aversion coefficient (λ) from prospect theory have a significant moderating effect on the system’s evolution. Finally, targeted recommendations are proposed for the three aforementioned stakeholders to accelerate the improvement of China’s collaborative governance of the content ecosystem. Full article

Bohr’s correspondence principle acts as a link between quantum physics and classical physics theory, while squeezed light, as a special nonclassical quantum state in quantum physics, achieves precision measurements and gravitational wave detection by minimizing quantum noise in one quadrature component of the optical field. Consequently, determining whether the classical counterpart of the squeezing operator reflects classical spatial scaling transformations is of significant theoretical importance. This paper establishes a universal integral formula that transforms any operator into its Weyl ordering form using the method of integration within the ordered product of operators, combined with the coherent state representation and integration theory within Weyl ordering. By transforming both single-mode and two-mode squeezing operators into their corresponding Weyl ordering forms, their classical counterpart functions are derived. This elucidates the classical correspondence of the squeezed light field density operator and demonstrates that this correspondence fundamentally represents a classical scaling transformation. As a practical application of the classical counterpart of the single-mode squeezing operator, the photon number distribution characteristics in a single-mode squeezed light field are obtained, confirming its noise-squeezing effect. This study not only deepens the theoretical implications of Bohr’s correspondence principle from the perspective of “transformation correspondence” but also introduces novel insights into the establishment of the mathematical foundations of quantum optics and quantum statistical theory. Full article

Human liver stem cells (HLSCs) are a mesenchymal stromal cell (MSC)-like population isolated from adult liver biopsies. HLSCs share key characteristics with MSCs, including phenotype and differentiation capabilities. Previous studies have demonstrated that HLSCs promote regeneration in different experimental models of acute and chronic tissue injury and that HLSC-derived extracellular vesicles (HLSC-EVs) recapitulate the therapeutic effects of the cells of origin. This study aimed to determine whether HLSC-EVs, obtained and characterized under good manufacturing practice (GMP) conditions, can influence the progression of liver fibrosis in vivo. The EV production process was carried out under GMP conditions to generate batches of HLSC-EVs by tangential flow filtration. To assess their therapeutic potential, an in vivo model of hepatic fibrosis was established through administration of thioacetamide (TAA). In TAA-treated mice, EV administrations attenuated fibrosis progression. Molecular analyses showed a significant reduction in the expression levels of key pro-fibrotic genes. At the functional level, EV administration resulted in a significant reduction in plasma alanine aminotransferase levels and an increase in albumin levels, indicating improved liver function. These data indicate that HLSC-EVs, produced under GMP conditions, display antifibrotic effects in a chronic liver disease model, leading to improved liver function and histology. Full article