Search Results (14,060)

This review analyses and logically structures modern intelligent sensor technologies in the context of animal husbandry, feed production, and veterinary medicine. The main research discussed in the article focuses on machine learning based on modern neural network models, computer vision, and sensor systems that are transforming the methods for assessing the health, behavior, and nutrition of farm animals. The first part examines modern approaches to quality control and optimization of mineral and vitamin premixes, including visual inspection using visual sensors and neural networks. Key roles are played by precise dosing, component stability (minerals, vitamins), and the transition to more bioefficient organic forms of micronutrients to reduce environmental impact. Improvements in feed and premix production are analyzed, including automation, energy management, and the use of machine learning for non-destructive quality control, defect detection, mixing homogeneity assessment, and vitamin stability prediction. The second part analyzes methods for animal location and behavior detection. This article presents computer vision-based systems, including modifications of YOLO, for automatically tracking and classifying key behavioral patterns (lying down, standing, feeding, and aggression) in cattle and pigs, even in crowded conditions. It also discusses the use of ultra-wideband (UWB) systems and accelerometers combined with machine learning for high-precision positioning and detection of specific behavioral anomalies, such as lameness and playfulness. The third section focuses on the application of machine learning in veterinary diagnostics, including the automated interpretation of medical images (X-ray, ultrasound, and MRI) as sensor data streams for the diagnosis of cardiovascular, oncological, and orthopedic diseases in farm and small animals. Furthermore, the article examines the use of machine learning models for proactive disease diagnosis in farm animals and poultry based on multimodal data and image analysis. Considerable attention is given to methods and tools for radiometric diagnosis of animal diseases at an early stage using microwave sensors, as well as laser therapy and surgery in veterinary medicine. The review concludes that the integration of intelligent systems enables a transition to data-driven livestock management, significantly improving animal welfare and, consequently, the efficiency and sustainability of agricultural production. Full article

Environmental policies and intermittent renewable energy (RE) drive large-scale hydrogen production towards hybrid supply configurations, combining collocated RE units and the electricity market (EM). This links the power and hydrogen sectors through EM/hydrogen prices, dispatch, and hydrogen demand profiles. In a hybrid configuration, the strategic role of RE in the EM enhances these links by creating profit opportunities. This work develops a bi-level model, optimizing electrolyzer size and location, operational decisions and RES bidding strategies, while explicitly modeling EM clearing. In the upper-level, an EM player, owning strategically bidding RE assets, evaluates expanding into the use of electrolyzers that act as price-takers. The lower-level problem clears the EM. The proposed framework is applied to an IEEE 24-node test system. The results show how EM conditions determine investments for different hydrogen price cases. It is revealed that differentiated electricity sourcing across electrolyzers and efficiency-preserving dispatch impact operational decisions, leading to revenue improvements. Moreover, renewable capacity withholding is used to avoid zero EM prices and mitigate the economic impact of unmet hydrogen demand when RE availability is limited and electrolyzer participation in the EM is restricted. Time-window-constrained hydrogen demand mitigates unutilized RE by 39% compared to that for hourly demand. Full article

The electrification of long-haul freight transport requires a comprehensive public charging infrastructure along motorways. This study presents a framework combining multi-agent transport simulation (MATSim) with evolutionary bi-objective optimization (NSGA-II) to determine the number and spatial distribution of high-power charging (HPC) points for battery-electric trucks (BETs) on the German motorway network. Beyond infrastructure sizing, the approach also quantifies the impact of BET charging on the duration and distance of long-haul truck trips. The optimization simultaneously addresses the perspectives of two key stakeholders: charge point operators (CPOs), who seek to maximize charger utilization, and logistics operators, who aim to minimize waiting times. The results yield a range of Pareto-optimal configurations balancing the two objectives. A multi-iteration replanning step further lets trucks adapt their routes to experienced waiting times for a more realistic performance assessment, reducing mean waiting times by up to 92%. We evaluate five electrification levels from 1% to 20% across two charging network scenarios with 347 and 779 potential locations, respectively. For the balanced solutions—the knee-point configurations that best reconcile both objectives—at a 10% electrification level, the optimized network reaches a temporal charger utilization of 23% to 32% at mean waiting times of about 1.4 to 1.9 min per charging process. Compared with an internal combustion engine truck (ICET) reference, BET trip durations increase by only 0.9% to 1.3% due to charging detours. Overall, the fast-charging network planned by the German federal government appears sufficient for the HPC demand at electrification levels up to 10% to 15%, whereas additional low-power charging (LPC) infrastructure beyond the planned locations will be needed to cover overnight charging requirements. Full article

Large-scale location-based virtual reality (LBE VR) has become an important form of immersive cultural tourism, but its role in supporting sustained value transformation remains insufficiently understood. In this study, “sustained value transformation” refers to the extension, reinterpretation, and circulation of cultural, educational, social, and engagement-related value across physical venues, embodied virtual narratives, and digital platforms. Rather than assessing economic performance, environmental impact, or long-term operational viability, this study focuses on the cultural and social circulation of experiential value. It examines how physical venues, embodied virtual narratives, and digital platforms jointly mediate visitor experience in LBE VR-based cultural tourism. It compares representative LBE VR projects in museums and heritage institutions, emerging public cultural spaces, and commercial venues in China. A total of 10,862 project-related textual items and 464 visual samples were collected from Xiaohongshu and Douyin and analyzed through comparative content and visual analyses. The findings show that visitor choices are shaped by both the spirit of place in physical venues and platform-visible experience labels. In museums and heritage institutions, institutional knowledge authority and embodied narrative depth help visitors recognize interactive educational value. In emerging public cultural spaces, the intertwining of historical narratives and commercial operations produces more ambiguous experience labels. In commercial venues, platform discussions focus more strongly on value-for-money judgment, sensory stimulation, product quality, and service experience. The study argues that sustained value transformation in LBE VR-based cultural tourism cannot rely solely on platform traffic. Instead, it depends on collaboration among cultural institutions, tourism enterprises, platform content creators, educational actors, and community stakeholders to preserve cultural distinctiveness, improve experience quality, and extend cultural and social value beyond the immediate on-site experience. Full article

Background/Objectives: The genes encoding HSPA1A, HSPA1B, and HSPA1L, located in the MHC class III region at 6p21.3–22.1, a region implicated in susceptibility to schizophrenia, are critical regulators of neurodevelopmental processes and contribute to synaptic neuroprotection. This study investigated whether the HSPA1A, HSPA1B, and HSPA1L genes are associated with schizophrenia. Methods: We sequenced the coding regions of HSPA1A, HSPA1B, and HSPA1L from 100 patients with schizophrenia to identify genetic variants. Further, we conducted a genetic association analysis of three SNPs (rs9469057, rs142416335, and rs2075800) in the HSPA1L gene in 519 patients with schizophrenia and 1492 healthy controls from the Taiwan Biobank. We analyzed the function of the HSPA1L protein via immunoblotting. Results: We identified 17 coding variants, including 8 missense and 9 synonymous mutations, in 100 patients with schizophrenia. Three variants (HSPA1L^p.Ala8Pro, HSPA1L^p.Ala8Thr, and HSPA1L^p.Glu602Lys) in the HSPA1L gene did not exhibit any significant differences in allele or genotype frequencies between patients and control subjects. Notably, one ultra-rare missense mutation, HSPA1L^p.Val262Met, was not documented in the control sample in Taiwan BioBank. Immunoblotting revealed HSPA1L^p.Val262Met mutant with decreased protein expression in SH-SY5Y cells compared with the wild type. Conclusions: While common variants in the HSPA1A, HSPA1B, and HSPA1L genes do not seem to be significant genetic risk factors for schizophrenia in this cohort, the ultra-rare mutation, HSPA1L^p.Val262Met, significantly reduces protein expression. These preliminary findings suggest that a potential loss-of-function or reduced expression of the HSPA1L gene may be a predisposing factor contributing to schizophrenia vulnerability in certain individuals. However, the finding should be replicated in other independent samples. The in vitro and in vivo impacts of the associated mutation at the HSPA1L gene on the pathophysiology of schizophrenia are worthy of future investigation. Full article

Seawater intrusion presents a significant risk to coastal aquifers, particularly in low-lying locations where groundwater resources are intensively exploited. This study assesses the vulnerability of the Keta Strip aquifer in Southeastern Ghana to seawater intrusion using the GALDIT model; a widely applied index-based approach that evaluates seawater intrusion risk based on six key hydrogeological indicators: groundwater occurrence (G), aquifer hydraulic conductivity (A), groundwater level above sea level (L), distance from the shoreline (D), impact of existing intrusion (I), and aquifer thickness (T). These parameters were analyzed using data from 105 monitoring wells within a Geographic Information System (GIS) environment. The resulting vulnerability index was spatially grouped into four categories: low, moderate, high, and very high vulnerability. Results indicate that very high and high vulnerability regions are predominantly clustered along the coastal margins and central portions of the study area, driven mainly by low hydraulic gradients, proximity to the shoreline, and high hydraulic conductivity. Moderate vulnerability zones dominate inland areas, while low vulnerability zones are limited and confined to northern sections. Sensitivity analysis reveals that hydraulic head (L) and distance from shoreline (D) are the most influential parameters, whereas TDS exhibits relatively low contribution to overall vulnerability. The findings highlight the critical role of hydrogeological controls and anthropogenic pressures in shaping seawater intrusion risk and provide a scientific basis for sustainable groundwater management in the Keta Strip and similar coastal environments. Full article

With the increase in operation time of DC traction systems due to the environment of tunnel and stress rupture, the insulation between the rail and ground inevitably decreases, causing increased stray current leakage. In view of this, we present an analytical and electrochemical study of stray current behavior and its corrosion impact arising from local rail-to-ground insulation damage in DC urban rail systems. A two-layer rail–earth continuous model of stray current distribution is developed (unilateral and bilateral supply cases) using Kirchhoff network formulations with insulation damage boundary conditions. Numerical simulations quantify the effects of damage location and grounding resistance on rail potential shifts, abrupt changes in rail and stray currents, and total leakage. To assess electrochemical consequences for nearby buried pipelines, the electrical model is proposed in this work with an impedance-informed corrosion model and Monte Carlo sampling of operational and electrical uncertainties to estimate dynamic corrosion rates and pitting evolution. The results show that single–point insulation faults shift the rail zero potential toward the fault, leading to instantaneous jumps in leakage and rail currents whose magnitude grows as damaged-point resistance decreases, markedly increasing pipeline corrosion risk. The integrated electrical-electrochemical framework provides a tool for detection, risk assessment, and mitigation planning for stray current-induced pipeline corrosion. Full article

Slaughterhouse wastewater introduces potentially toxic elements into aquatic ecosystems, yet bioaccumulation patterns in commercial fish species and associated human health risks remain underexplored in West Africa. This study quantified zinc (Zn), lead (Pb), iron (Fe), magnesium (Mg), chromium (Cr), and cadmium (Cd) in three ecologically distinct fish species—Oreochromis niloticus (Nile tilapia), Clarias gariepinus (African sharptooth catfish), and Mugil cephalus (Flathead grey mullet)—from two slaughterhouse-impacted rivers (Transamadi and Mgbuosimini) and a control site (Iwofe) in Rivers State, Nigeria. Metal concentrations were measured using atomic absorption spectrophotometry. Two-way ANOVA assessed species and location effects. Principal component analysis (PCA) was performed, with Mg used as a potential geogenic tracer, as its loading pattern was independent of Pb and Cd and consistent with the natural background. A Water Quality Index (WQI) classified Mgboshimini and Iwofe as having poor water quality (WQI > 75), while Transamadi had medium quality. Health risks were evaluated using estimated daily intake (EDI), target hazard quotients (THQ), and hazard indices (HI) following USEPA guidelines. Metal levels varied significantly by species and location (p < 0.001). Flathead grey mullet from Mgbuosimini had the highest Pb (1.50 ± 0.05 mg/kg) and Cd (0.41 ± 0.02 mg/kg), exceeding EU maximum levels for fish muscle (Pb 0.30 mg/kg, Cd 0.05 mg/kg) by 500% and 800%, respectively. PCA explained 77.5% of the variance, with Pb and Cd clustering as anthropogenic sources, while Mg loaded independently. THQ for Pb approached unity in Flathead grey mullet (0.88), and THQ for Cd reached 0.97. HI exceeded 1.0 in all species from Mgbuosimini, peaking at 2.07 in Flathead grey mullet. Uncertainty analysis (using ±SD) gave a HI range of 1.89–2.25 for this species, all above the safety threshold. Carcinogenic risk for Flathead grey mullet (3.97 × 10⁻⁴) approached the upper acceptable limit. Slaughterhouse effluent appears to elevate Pb and Cd burdens in fish, with detritivorous Flathead grey mullet posing the highest health risk. Exceedance of safety thresholds and HI > 1.0 indicate potential non-carcinogenic and carcinogenic risks. We recommend improved wastewater treatment and species-specific consumption advisories. Full article

The linguistic landscape is a significant aspect of the cultural landscape and heritage. Istria, a region and peninsula located in the Republic of Croatia, has experienced various influences over the years that have shaped language use, impacting the linguistic landscape and the identity of the local population. This paper aims to investigate how the linguistic and spatial identity of the people in Istria has been represented in the region’s cultural landscape during two comparative periods: the turn of the 20th century (the local population’s fight for their national language against the languages imposed by the European powers that governed this region—Italy and Austria) and the turn of the 21st century (the status of minorities in the present Croatian region of Istria). This diachronic research employs a cross-sectional method to compare findings and establish cause-and-effect relationships. This study involves analyzing linguistic data from historical postcards, conducting field studies, and using the pin placement feature on Google Maps to assess recent periods. This research identified Italian and Croatian as the dominant languages during different periods, with English being increasingly prevalent in contemporary times. The results demonstrated that the spatial identity of the Italian minority community is strongly reflected in the linguistic landscape, primarily due to bilateral interstate agreements. Full article

Landfill tire fires are complex environmental disasters generating toxic pollutants with severe health risks. This study quantified emission dynamics and toxicological consequences of a large-scale tire fire in an urban ecosystem. A comprehensive source-to-receptor approach was applied, integrating Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) atmospheric dispersion modeling with comparison against air quality monitoring data. Soil samples collected from the fireground and surrounding urban allotment gardens were analyzed for tire-specific tracers (Zn) and 16 priority polycyclic aromatic hydrocarbons (PAHs). Human health risks were assessed using Incremental Lifetime Cancer Risk (ILCR), Toxic Equivalency Quotient (TEQ), and Mutagenic Equivalency Quotient (MEQ) metrics. Fire emissions were dominated by particulate matter (PM₁₀: 1.34 t) and PAHs (17.7 kg). Soil at the fire site showed severe contamination (Σ PAHs: 148.9 mg/kg), with benzo[a]pyrene as the primary carcinogen. The cumulative ILCR for children reached 9.7 × 10⁻⁴, exceeding the commonly used upper regulatory benchmark of 10⁻⁴. Dermal contact was identified as the dominant exposure pathway for pyrogenic PAHs. Elevated risk levels persisted at distal residential sites (ILCR: 10⁻⁵–10⁻⁴), indicating long-term environmental contamination Ecological risk quotients (RQ) exceeded unity for PAHs across all fire-impacted locations and for Zn and Cu in the immediate vicinity of the fire scene. These findings demonstrate that acute tire fire events can evolve into persistent terrestrial health hazards, highlighting the critical role of dermal exposure in PAH uptake and the need for long-term environmental monitoring and adaptive land-use management strategies to mitigate chronic health risks in urban populations. Full article

Groundwater level mapping is used in order to detect aquifer locations, flow paths, recharge zones, and contamination/pollution of groundwater. This is crucial for water management, environmental studies and resource planning focusing on landfills. This study involves the collection of monitoring well data and the mapping of the groundwater table at the Mavrorachi landfill site using Geographic Information Systems (GISs). The monitoring period spans from 2008 (startup) to 2025 (the current full year) for the 11 monitoring boreholes. Interpolation methods in GISs enabled us to map the groundwater level, while spatial analysis tools modeled the potential groundwater flow. The above process proved to be a valuable tool for modeling groundwater resources. The monitoring of groundwater level is essential to prevent the impact of leachate generated from landfill. Full article

Introduction: Artificial infrastructure interrupts river longitudinal connectivity, preventing the free flow of water, matter, energy, and organisms through the system, altering the habitat and impacting freshwater biodiversity. Freshwater fishes are especially sensitive to this threat, since they are constrained to the limits of the river network. Transversal obstacles, such as dams and weirs, hinder their movements upstream and downstream and fragment populations. Longitudinal connectivity can be simply measured as the proportion of connected river length in a basin. However, other indices have been suggested more recently, measuring connectivity as the proportion of connected elements of interest (e.g., populations of a species) in a river basin. Objective: The aim of this work was to study (1) the degree of connectivity of native freshwater fish species populations in eleven Spanish river basins and (2) the impact of artificial river fragmentation in these basins on population connectivity. Methodology: Fish populations’ location and size were estimated through sampling presence data, and completed using the predicted occurrence of each species in a river basin, calculated through Species Distribution Models (SDMs). To estimate the degree of connectivity between populations of each species, the Population Connectivity Index (PCI) was calculated under two scenarios: the “current” scenario, considering all the artificial obstacles fragmenting the river network and their specific passabilities, and the “natural” scenario, considering that all the artificial obstacles in the river network were completely passable. Results: Native freshwater fish populations are severely fragmented in Spanish rivers, with a mean current PCI of 9.8% across species and river basins. The impact of artificial fragmentation is high, causing a mean decrease in PCI of 52 percentage points across species and river basins. Moreover, although the impact of artificial river fragmentation is high in all river basins, it is important to point out that there are significant differences between river basins attributed to their size and the specific traits of the ichthyofauna inhabiting them. Conclusions: The degree of connectivity in a river basin varies depending on the elements of interest considered. Therefore, incorporating ichthyofauna into the decision-making process is essential to improve the effectiveness of river restoration actions. Full article

The Five Domains Model has become one of the most widely adopted frameworks in animal welfare science and practice. The Model is now applied in a range of ways; among the most prominent are (1) as a framework for systematic and structured welfare assessment and (2) as an organising structure for planning and communicating appropriate (i.e., welfare-focused) care provisions, education, and standards. This paper focuses on these two applications and proposes a corresponding update to the affiliated Five Provisions and Welfare Aims. Specifically, we revise: (1) Provision 4 from “Appropriate Behaviour” to “Appropriate Choices” to reflect the 2020 update of the Model incorporating human–animal interactions and the 2023 operationalisation of agency in Domain 4; (2) Provision 2 from “Good Environment” to “Good Living Space” to resolve ambiguity with Domain 4’s “Interactions with the Environment”; and (3) Provision 5 from “Positive Mental Experiences” to “Integrated Care,” which captures consistent delivery of the first four provisions over time and across all those who interact with the animal. This update also pairs Provision 5 with a welfare aim that specifies the integrated mental state the animal should experience as a result. This change makes the distinction between care (provisions) and welfare (aims) consistent throughout the framework. It also makes explicit the integrative role of Provision 5, which parallels Domain 5’s role in the Model. We then describe the reasoning process that distinguishes welfare assessment from welfare-focused care provision. Welfare assessment uses the domain structure as a reasoning pathway, with the assessor using indicators and their impacts in Domains 1 to 4 to infer named mental (affective) experiences in Domain 5. Planning and communicating appropriate (i.e., welfare-focused) care uses the same structure to organise information about what is provided to animals, without executing the inferential step to Domain 5. Drawing on examples from organisations that use the Model for different purposes, we show that both applications are legitimate but produce different outputs. The Five Provisions framework, with its dual structure of provisions paired with welfare aims, serves the care planning and communication function more effectively than does the Model’s domain structure alone. Recognising these different uses also helps to locate where recent critiques of the Model apply and where they do not. Finally, we propose that the provisions and welfare aims framework can supplement “needs” language in legislation and policy to better reflect the distinction between animal care and animal welfare. Full article

Monitoring genetic gain is critical for evaluating breeding program performance. This study assessed genetic trends in the Zambia national maize breeding program using historical data (2001–2017) from 2225 hybrids tested across years and locations. Best linear unbiased estimates (BLUEs) were calculated, and genetic trends were determined by regressing entry means on first-year testing data. Mean heritability was moderate for grain yield, plant height, and ear height, and high for anthesis and silking dates, indicating strong reliability for flowering traits. Significant positive genetic gains were observed for most traits except days to silking. Grain yield (GY) increased at 0.021 t ha⁻¹ per year (0.85% annually), reflecting progress but remaining below levels required to meet regional future production demands. Plant and ear height increased by more than 1.3 cm annually, suggesting directional selection for taller plant architecture. Grain texture declined by 1.28% per year, indicating a shift toward flint-type kernels. Anthesis date and ears per plant showed minimal genetic variation. Regression models explained more than 15% of the total variation in plant height, ear height, ear number, and grain texture, confirming consistent genetic progress. Although measurable gains were achieved, the study’s baseline indicates that accelerating yield improvement will require rapid-cycle breeding, enhanced trait heritability, modern breeding tools, and a strategic reallocation of resources to sustain long-term impact. Full article

With the digital economy advancing at a fast pace, digital transformation plays a pivotal role in reinforcing firms’ innovation capability and promoting high-quality development. This study analyzes Chinese non-financial publicly listed firms on the A-share market over the period 2009–2023. Based on text mining of annual reports, this study constructs an index capturing digital transformation and empirically evaluate its impact on innovation output with firm and year fixed effects. The estimates suggest that digital transformation meaningfully increases firms’ innovation output; the inference is unchanged when applying instrumental-variable approaches and conducting extensive robustness checks. Mechanism analysis reveals two parallel channels: (1) the R&D investment mechanism, characterized by improvements in R&D intensity, capitalization rate, per capita efficiency, and investment growth; (2) the governance environment mechanism, reflected in enhanced internal control, improved information disclosure quality, and strengthened audit supervision. Once firms are stratified by characteristics, the estimated positive effect of digital transformation is most pronounced for firms with low financial constraints, large size, eastern locations, and state ownership. This study identifies both direct and indirect mechanisms linking digital transformation to innovation and highlights how firm- and region-specific features condition the magnitude of this effect, thereby offering empirical implications for corporate digitalization strategies and policy design. Full article