Search Results (182)

Sediment accumulation in irrigation channels poses a significant challenge to water resource management, impacting hydraulic efficiency and agricultural sustainability. This study introduces an innovative multidisciplinary framework that integrates advanced image analysis (FIJI/ImageJ 1.54p), statistical validation (RStudio), and vector field modeling with a novel Sinusoidal Morphodynamic Bedload Transport Equation (SMBTE) to predict sediment deposition patterns with high precision. Conducted along the Malacatos River in La Tebaida Linear Park, Loja, Ecuador, the research captured a natural sediment transport event under controlled flow conditions, transitioning from pressurized pipe flow to free-surface flow. Observed sediment deposition reduced the hydraulic cross-section by approximately 5 cm, notably altering flow dynamics and water distribution. The final SMBTE model (Model 8) demonstrated exceptional predictive accuracy, achieving RMSE: 0.0108, R²: 0.8689, NSE: 0.8689, MAE: 0.0093, and a correlation coefficient exceeding 0.93. Complementary analyses, including heatmaps, histograms, and vector fields, revealed spatial heterogeneity, local gradients, and oscillatory trends in sediment distribution. These tools identified high-concentration sediment zones and quantified variability, providing actionable insights for optimizing canal design, maintenance schedules, and sediment control strategies. By leveraging open-source software and real-world validation, this methodology offers a scalable, replicable framework applicable to diverse water conveyance systems. The study advances understanding of sediment dynamics under subcritical (Fr ≈ 0.07) and turbulent flow conditions (Re ≈ 41,000), contributing to improved irrigation efficiency, system resilience, and sustainable water management. This research establishes a robust foundation for future advancements in sediment transport modeling and hydrological engineering, addressing critical challenges in agricultural water systems. Full article

Urban historic parks face the dual challenge of achieving the living preservation of historic buildings while enhancing contemporary visitor satisfaction. In the context of accelerating urbanization and growing demand for immersive cultural experiences, it is increasingly important to conserve historical and cultural values while maintaining relevance and emotional engagement. This study adopts a mixed-methods approach to develop a predictive model for visitor satisfaction within the framework of living preservation, using Yingzhou West Lake in Fuyang City, Anhui Province, as a representative case. Qualitative methods were employed to identify key landscape narrative dimensions, while quantitative data from structured questionnaires highlighted critical experiential elements such as environmental restoration perception, flow experience, and cultural identity. Three machine-learning algorithms—random forest, Support Vector Machine (SVM), and XGBoost—were applied, with the most accurate model used to analyze the relative contribution of each component to visitor satisfaction. The findings revealed that immersive experiential elements play a central role in shaping satisfaction, while physical and cultural elements, particularly historic buildings and their contextual integration, provide essential structural and emotional support. This study offers data-driven insights for the adaptive reuse and interpretive activation of historic architecture, proposing practical strategies to harmonize cultural continuity with visitor engagement in the sustainable management of urban historic parks. Full article

Ticks are key vectors of zoonotic pathogens, and their expanding distribution in Europe heightens public health concerns. In Bosnia and Herzegovina, while tick distribution is well documented, molecular data on tick-borne pathogens remain limited. This study aimed to illustrate the presence and diversity of these pathogens, focusing on areas with high human activity. Ticks (n = 556) were collected in April 2022 from eight diverse locations, including urban parks, private properties, and rural sites. PCR-based screening was employed to detect Anaplasmataceae, Borrelia, Francisella, Piroplasmida, Rickettsia, and tick-borne encephalitis virus (TBEV), with subsequent sequencing to confirm results. Further characterization of Borrelia burgdorferi sensu lato was achieved via reverse line blotting (RLB) hybridization and sequencing. Ixodes ricinus was the most prevalent species, followed by Dermacentor marginatus and D. reticulatus. Our analysis revealed an overall infection rate of 22.1% in questing ticks, with Rickettsia spp. and Borrelia spp. predominating. Notably, seven Borrelia species were identified in I. ricinus, alongside Anaplasma phagocytophilum, Rickettsia helvetica, and R. monacensis, with co-infections mainly observed in peri-urban areas. This study provides the first molecular evidence of multiple tick-borne pathogens in the region, underscoring the need for further surveillance and risk assessment of tick-borne diseases in the region. Full article

The open-circuit fault diagnosis of switching devices in 3ϕ V/F-controlled voltage source inverters is critical, since diagnostic parameters change with varying load conditions and frequency. Park’s vector transform-based approaches depend on threshold values for fault diagnosis, demanding continuous modifications based on load variations, making them prone to improper diagnosis. Artificial intelligence-based methods give good accuracy, but they require extensive data collection under varying load conditions, creating implementation efforts that are considerably high. This paper focuses on optimizing threshold-independent methods and reducing data requirements for the artificial intelligence-based open-circuit fault diagnosis of 3ϕ V/F-controlled VSIs. To mitigate the problem of fault misclassification under variable load conditions at different frequencies, the stator current is normalized using Park’s vector transform. Normalized currents ensure that the extracted features remain the same under all load conditions while providing distinctive features for faulty and healthy conditions. Feature extraction is implemented using the wavelet transform, and feature selection is carried out using a ReliefF algorithm, which enhances classification by selecting key features. The selected features are then used to diagnose faults using an extreme gradient boosting algorithm. In XGBoost, a random search is preferred over a grid search to find the best hyperparameters for optimal performance, as it speeds up tuning, explores more options, and efficiently balances accuracy. The proposed system outperforms current open-switch fault diagnosis approaches by providing high effectiveness, strong resistivity, and a fast detection time. The results are presented for different combinations of single and multiple open-switch faults under variable load conditions at different frequencies. Full article

Rapid environmental changes driven by human activities are contributing to a significant decline in global biodiversity, with avian species being particularly affected due to their migratory behavior. As highly mobile hosts, birds facilitate the geographic dispersal of ectoparasites, including ticks, which serve as vectors for numerous zoonotic pathogens. This study, conducted in collaboration with the Faunistic Observatory of the Asinara National Park between 2021 and 2023, aimed to investigate the potential role of migratory birds in tick dispersal and the presence of Borrelia spp. DNA. Birds were captured using mist nets during pre-breeding (April–May) and post-breeding (October–November) migration periods. Ticks were systematically collected and identified at the species level, and molecular analyses were performed using real-time and conventional PCR to detect the presence of Borrelia spp. DNA. Results showed a distinct seasonal variation in tick species composition. In autumn, Ixodes ricinus was predominant (99%), whereas Hyalomma species were more frequently observed in spring (78%). Molecular screening revealed Borrelia spp. DNA in 26.1% of the collected ticks, with Borrelia garinii being the most prevalent species. These findings underscore the ecological significance of migratory birds in the dissemination of ticks and tick-borne pathogens, highlighting their potential role in shaping disease transmission dynamics across different geographic regions. This study provides valuable insights into the seasonal fluctuations in tick populations associated with migratory avifauna and the epidemiological risks posed by these interactions. Continued surveillance of migratory birds as vectors of zoonotic pathogens is essential for informing public health strategies and mitigating the risks of emerging infectious diseases, but further investigation is needed to clarify the actual role of migratory birds in the transmission of Borrelia spp. Full article

The environment is being affected by the great development of human activities, which is why, in recent years, the need to protect the environment has increased, through the carrying out of a Strategic Environmental Assessment (SEA). Within this assessment, environmental geology constitutes an instrument for territorial and urban planning based on the analysis of conservation and the integral analysis of risks, obtaining cartography that can be useful in territorial and regional planning strategies. The methodology carried out in this article consists of applying a multi-criteria analysis in territorial planning, combining vector and raster data. This novel, low-cost, and effective methodology assesses conservation areas and risks, using map algebra and network analysis to identify priority areas and facilitate decision-making in a precise and quantitative manner. This analysis has been carried out in the Arribes del Duero Natural Park, which stands out as a place where numerous environmental values coexist, i.e., geological, geomorphological, and edaphological, forming unique landscapes. With regard to the results obtained, the cartography of conservation quality classifies the territory into four categories according to its degree of conservation: very high, high, low, and very low quality. The integral risk cartography identifies the areas with the greatest geological risks, such as erosion and landslides, and establishes limitations for land use. Also, by integrating both cartographies, it is determined which activities are compatible with each zone, considering both conservation and risks. Finally, it can be concluded that the cartographies obtained are useful for efficient land management, protecting the environment, and allowing human development in a controlled manner. Full article

Since the emergence of serotype BTV-3, another bluetongue virus, in fall 2023, this variant has been causing great losses in livestock farming in Europe. The virus spreads faster than the epidemic BTV-8, which appeared on the continent nine years earlier. This study describes the first case of BTV-3 in Poland detected in a European bison (Bison bonasus) in Poland’s Wolin National Park, approximately 15 km from the German–Polish border. The animal suffered from a severe and fatal hemorrhagic disease. The symptoms included respiratory problems, bloody diarrhea, and rapidly progressive cachexia. In addition to the virus’s confirmation as BTV-3 and the presence of the infecting agent in the blood and spleen of the animal, the virus was also detected in one pool of blood-fed Culicoides punctatus caught near the bison enclosure two weeks after the death of the bison. This is the first detection of BTV-3 in C. punctatus, which suggests vector competency for this serotype. Phylogenetic analysis based on segment 2 of the virus revealed the homology of the Polish isolate to the BTV-3 strains circulating in the Netherlands, Germany, and Portugal, and slightly lower similarity to the BTV-3 strains detected in sheep in Sardinia (Italy) in 2018 and in Tunisia in November 2016. A retrospective serosurvey of the exposure to BTV in thirteen other European bison populations distributed over the country indicated that the observed case at the Wolin National Park was the first BTV-3 to be detected in Poland. Full article

Fault diagnosis in power converters is essential for keeping electrical systems stable, efficient and long-lasting. Park’s Vector Transform, discrete wavelet transform, Artificial Neural Network, Fuzzy Logic and other methods are used to diagnose faults in the power converter in both single and multiple open switch situations. These methods are implemented on the digital signal processor or controller, which needs additional hardware and consumes more processing time. This paper presents a hardware-based open switch fault diagnostic method in a 3ϕ voltage source inverter to minimize fault diagnosis time and cost. An innovative hardware-based approach that utilizes a single neuron for open switch fault diagnosis in 3ϕ voltage source inverters was successfully implemented without using a digital signal processor or controller. A gradient descent algorithm calculates the weight and bias values of a single processing neuron. Furthermore, a high-speed multiplier and adder circuit seamlessly integrate with the single processing neuron, enabling rapid real-time fault diagnosis. This method is capable of diagnosing single and multiple switch open circuit faults in switching devices under variable load conditions at different frequencies. The proposed system ensures good effectiveness and resistivity, detecting faults in less than one cycle with low implementation effort and no tuning or threshold dependence. It achieves 98% accuracy, 96% precision and 95% recall, with a 2% false positive rate. Unlike traditional methods, it eliminates DSP/controller dependency by using a single neuron-based processing circuit, reducing cost and improving real-time fault diagnosis in three-phase voltage source inverters. Full article

Phytotelmata are aquatic microenvironments formed by the accumulation of water and organic matter in cavities of plants. These microenvironments serve as breeding sites for various species of mosquitoes, including some of epidemiological importance. Our objective was to identify the mosquito fauna in these microenvironments and to analyze variations in mosquito fauna diversity between bromeliads, tree holes, and bamboo internodes in Cantareira State Park, São Paulo (CSP), Brazil, where there have been reports of yellow-fever epizootics in non-human primates and circulation of plasmodia. Collections were carried out monthly from February 2015 to April 2017. The bromeliads showed greater mosquito species richness and diversity than the tree holes and bamboo internodes, as well as a very different composition. Of the 11 genera collected and 49 taxa identified, Culex (Carrolia) iridescens, Cx. ocellatus, Cx. (Microculex) imitator, and Anopheles (Kerteszia) cruzii were the most abundant. The phytotelmata in the CSP showed significant differences in species richness, diversity, and composition and were found to support a diverse mosquito fauna to develop, including An. cruzii and the sylvatic yellow fever virus vector Haemagogus leucocelaenus. The finding of these epidemiologically important species highlights the key role played by phytotelma breeding sites as places of refuge and species maintenance for these vectors in green areas close to urban centers. Full article

Expo parks are characterized by dense crowds and a high risk of accidents. A multi-robot patrolling system equipped with multiple sensors can provide personalized services to visitors and quickly locate emergencies, effectively accelerating response times. This study focuses on developing efficient patrolling strategies for multi-robot systems. In expo parks, this requires solving the multiple traveling salesman problem (MTSP) and addressing multi-robot obstacle avoidance in static environments. The main challenge is to plan paths and allocate tasks effectively while avoiding collisions and balancing workloads. Traditional methods often struggle to optimize task allocation and path planning at the same time. This can lead to an unbalanced distribution of patrol tasks. Some robots may have too much workload, while others are not fully utilized. In addition, poor path planning may increase the total patrol length and reduce overall efficiency. It can also affect the coordination of the multi-robot system, limiting its scalability and applicability. To solve these problems, this paper proposes a multi-objective immune optimization algorithm based on the Van der Waals force mechanism (VDWF-MOIA). It introduces an innovative double-antibody coding scheme that adapts well to environments with obstacles, making it easier to represent solutions more diversely. The algorithm has two levels. At the lower level, the path cost matrix based on vector rotation-angle-based obstacle avoidance (PCM-VRAOA) calculates path costs and detour nodes. It effectively reduces the total patrol path length and identifies optimal obstacle avoidance paths, facilitating collaborative optimization with subsequent task allocation. At the higher level, a crossover operator inspired by the Van der Waals force mechanism enhances solution diversity and convergence by enabling effective crossover between antibody segments, resulting in more effective offspring. The proposed algorithm improves performance by enhancing solution diversity, speeding up convergence, and reducing computational costs. Compared to other algorithms, experiments on test datasets in a static environment show that the VDWF-MOIA performs better in terms of total patrol path length, load balancing metrics, and the hypervolume (HV) indicator. Full article

Motor fault detection plays a vital role in industrial maintenance. Timely detection of faults in their early stages can prevent catastrophic consequences and reduce maintenance costs. Traditional methods face challenges in motor broken rotor bar (BRB) detection: model-driven methods are difficult to apply accurately in complex and changing environments, while data-driven methods usually require sophisticated feature extraction and classification processes. In this paper, we propose a novel non-invasive fault detection method. The method preprocesses motor currents by Hilbert-Huang Transform (HHT) and Park’s Vector Modulus (PVM) and then uses a merged convolutional neural network (CNN) for classification. This experiment investigates the detection of broken rotor bars of motors with different loads (25%, 50%, 75%, and 100% of rated load) and different fault levels (Normal, 1BRB, 2BRB, 3BRB, and 4BRB). The results show that the model’s classification accuracy exceeds 95% under various operating conditions and can maintain high accuracy under low load conditions, thus addressing the limitations faced by existing methods. In addition, it is computationally efficient and can guarantee high real-time performance. This method combines advanced signal processing techniques and deep learning algorithms to provide a practical solution for motor broken rotor bar detection. Full article

Urban greenspaces, including residential parks and conservation areas, provide ecological and recreational benefits. This study reports mosquito surveillance and blood meal analysis data from greenspaces in Vero Beach, Florida. It also compares mosquito assemblages and host associations across residential and conservation greenspaces to assess how greenspace type impacts mosquito abundance and host interactions. Using CO₂-baited traps and large-diameter aspirators, mosquitoes were collected over 26 sampling weeks (February–December 2023) yielding over 19,000 female mosquitoes from 32 species. Although mosquito species richness and community composition were similar across greenspace types, relative abundance of some key vector and nuisance species differed significantly. For example, Aedes taeniorhynchus was more common in preserved coastal wetland greenspaces, while Aedes aegypti and Aedes albopictus were more common in residential greenspaces. Generalized linear models revealed the impacts of climatic variables on the abundance of many key mosquito species. Blood meal analyses showed that host associations did not vary significantly by greenspace type, suggesting stable mosquito–host interactions across the landscape. These results highlight that greenspaces are not uniform in their mosquito species composition. Further studies on the effects of different greenspace types on mosquito communities can help to identify urban landscape features that minimize mosquito-borne disease risk. Full article

Located in the Rocky Mountains within the Arapahoe and Roosevelt National Forests, Colorado State University’s Mountain Campus in Pingree Park hosted the 24th Annual Rocky Mountain Virology Association’s meeting in 2024. A total of 165 participants, both regional and international, participated in the 3-day event, which consisted of 48 talks and 42 posters. These presentations discussed developments in prion research, current affairs, and novel tools in virology; investigated arboviruses and their vectors, as well as molecular foundations of viral interactions; and provided increased understanding of viral immunology and vaccines. This year’s Randall Jay Cohrs keynote presentation unveiled how viral infections disrupt intestinal homeostasis via Sting-dependent NK-kB signaling. This novel research demonstrated the importance of immunological pathways in the virus-induced disruption of homeostasis. Nested in the valley of the Rocky Mountains, participants could enjoy the fall colors and partake in hiking and fishing all while discussing science and networking amongst a variety of scientists. This report encapsulates selected presentations from the 24th Annual Rocky Mountain Virology Association meeting. Full article

Throughout Europe, including Poland, Ixodes ricinus ticks are the main vector of numerous pathogenic agents that pose a serious threat to public health. Southern Poland attracts many tourists with its scenic landscapes and abundant recreational opportunities. These areas are ideal habitats for wild fauna, which serve as the main reservoirs and hosts for these pathogens and ticks. The large population and biodiversity of these hosts facilitate the proliferation of ticks. The aim of this study was to determine the potential exposure of humans to ticks and tick-borne pathogens such as Borrelia burgdorferi sensu lato, Anaplasma phagocytophilum, and Babesia spp., along the nature-educational and tourist trails of the Poprad Landscape Park. From 2020 to 2021, ticks were collected using the flagging method on three tourist trails and nature-educational paths within the Poprad Landscape Park. DNA was isolated from 213 I. ricinus ticks using the ammonia method. To detect pathogens in ticks, PCR and nested PCR methods were used. To detect B. burgdorferi s.l. and A. phagocytophilum, two pairs of primers specific to the flaB gene fragment and 16S rRNA gene fragment were used, respectively. For Babesia spp. detection, primers specific to the 18S rRNA gene were used. The amplification products were separated electrophoretically and visualized under ultraviolet light. In total, among the 213 examined ticks, B. burgdorferi s.l. was detected in 31% of the samples. Neither A. phagocytophilum nor Babesia spp. were detected in the studied material. These results indicate a potentially high risk of ticks and tick-borne B. burgdorferi s.l. infections for residents and tourists in the recreational areas of the Poprad Landscape Park. Full article

Urban parks are important components of the urban green space system, providing residents with a variety of leisure options. The design’s focal point is the spatial layout of the different use scenarios within these parks. Previous studies have largely concentrated on the scene and macro layout of urban public spaces but have not thoroughly investigated the digital characteristics and corresponding parametric methods for the layout of different internal use scenes in urban green spaces. This research selected 18 urban parks from various global regions as case samples and categorized eight typical park scene space types based on common activity scene requirements in park design using AutoCAD to identify vector boundaries in each sample. To examine the digital characteristics of these scene space types, a quantitative index system was established, including spatial density and scale indicators, spatial connection relationship indicators, and spatial unit morphology indicators. The analysis of these indicators across the samples shows that the number of scene spaces is positively correlated with the total park area, while natural experience scenes constitute the largest proportion of urban parks. Different scene types exhibit distinct spatial layouts; for example, circulation spaces demonstrate high connectivity due to their role in directing visitor flow. Some spaces exhibit a more fixed scale and size, while others vary considerably. Finally, this research develops a parametric design framework using the Grasshopper platform. By taking a park in Nanjing as a case study, this paper illustrates how to utilize digital layout features to generate scene space layouts, offering insights into intelligent generative design. This approach provides a structured method to enhance urban park design through the application of digital and parametric tools, contributing to the broader field of urban park design. Full article