Search Results (174)

Participation in horse-related activities frequently involves relocating horses from the home stable to an activity venue, which might require local, regional, or international travel. In these circumstances, horses are exposed to unfamiliar surroundings and experience changes to their daily routines, which could have negative welfare impacts. An online survey was conducted in 2021 to ask experienced horse sector participants about the horse management practices that they perceived worked well and provided for positive horse welfare when undertaken at venues. Qualitative analysis identified four themes: ‘managing venues’, ‘monitoring fitness to participate’, ‘maintaining a healthy equine digestive system’, and ‘using horse behaviors to inform decision-making’. The findings indicate that activity-related individuals selected practices that assisted horses to adapt to venue surroundings, remain calm, and stay healthy. The co-authors propose that experienced participants recognize that practices include both provisions (inputs) and outcomes (the horse’s subjective experiences), resonating with the Five Freedoms and Five Domains models. For horse activity organizations proposing to implement the Five Domains model, the findings indicate that reviewing practices and implementing updates is timely and achievable. The authors propose that continuously updating practices will contribute to safeguarding horses and maintaining the sector’s social license to operate. Full article

Sustainable development remains a crucial global priority. Despite significant progress at both the policy and technical levels, disparities in urban development and the absence of a comprehensive evaluation framework impede practical outcomes in China. While previous research has established the value of multidimensional frameworks and international indices for assessing urban sustainability, existing studies often lack the integration of local dynamics and rely on linear methods that cannot fully capture the complex, nonlinear changes in Chinese cities. This study proposes a four-dimensional indicator system and employs the catastrophe progression method to evaluate sustainable development levels. This study used ten years of panel data (2012–2022) from eight representative Chinese cities and normalized and analyzed 38 sub-indicators to derive membership values for each city and dimension. The findings reveal substantial disparities in sustainable development across the cities, with notable improvements in environmental indicators but persistent volatility in social welfare and resource efficiency. Technological innovation and education resource allocation emerge as management priorities for most cities. This methodological innovation fills a critical gap, offering a replicable framework for other developing countries and supporting the localization of global sustainability agendas. The study’s findings directly inform policy, advancing the achievement of the UN Sustainable Development Goals. Full article

One of the primary goals of smart cities is to enhance the welfare and comfort of their citizens. In this context, minimizing the time required to detect fault events becomes a crucial factor in improving the reliability of distribution networks. Fault detection presents a notable challenge in the operation of Smart City Distribution Networks (SCDN) due to complex operating conditions, such as changes in the network topology, the connection and disconnection of distributed energy resources (DERs), and varying microgrid operation modes, all of which can impact the reliability of protection systems. To address these challenges, this paper proposes a fault detection system based on Long Short-Term Memory (LSTM), leveraging instantaneous local current measurements. This approach eliminates the need for voltage signals, synchronization processes, and communication systems for fault detection. On the other hand, LSTM methods enable the implicit extraction of features from current signals and classifies normal operation and fault events through a binary classification formulation. The proposed fault detector was validated on several intelligent electronic devices (IED) deployed in the modified IEEE 34-node test system. The obtained results demonstrate that the proposed detector achieves a 90% accuracy in identifying faults using instantaneous current values as short as 1/4 of a cycle. The results obtained and its easy implementation indicate potential for real-life applications. Full article

As urbanization has accelerated, rail transit has evolved from being a mere means of transportation to a public area that houses the city’s cultural memory and serves as a crucial portal for the public to understand the culture of the city. As an urban public space with huge passenger flow, the metro (or subway) cultural space has also become a public cultural space, serving communal welfare and representing the image of the city. It is currently attracting more and more attention from the academic community. Wuhan, located in central China, has many subway lines and its engineering construction has set several national firsts, which is a typical sample of urban subway development in China. In this study, we use Python 3.13.0 crawler technology to capture the public’s comments on cultural space of Wuhan metro in social media and adopt SnowNLP sentiment score and LDA thematic clustering analysis to explore the overall quality, distinct characteristics, and deficiencies of Wuhan metro cultural space construction, and propose targeted design optimization strategies based on this study. The main findings are as follows: (1) The metro cultural space is an important window for the public to perceive the city culture, and the public in general shows positive perception of emotions: among the 16,316 data samples, 47.7% are positive comments, 17.8% are neutral comments, and 34.5% are negative comments. (2) Based on the frequency of content in the sample data for metro station exit and entrance space, metro train space, metro concourse and platform space, they are ranked as weak cultural spaces (18%), medium cultural spaces (33%), and strong cultural spaces (49%) in terms of the public’s perception of urban culture. (3) At present, there are certain deficiencies in Wuhan metro cultural space: the circulation paths in concourses and platforms are overly dominant, leaving little space for rest or interaction; the cultural symbols of metro train space are fragmented; the way of articulation between cultural and functional space in the metro station exit and entrance space is weak, and the space is single in form. (4) Wuhan metro cultural space needs to be based on locality landscape expression, functional zoning reorganization, innovative scene creation to optimize the visual symbol system and behavioral symbol system in the space, to establish a good image of the space, and to strengthen the public’s cultural identity and emotional resonance. Full article

Pastoral activities are an essential part of the cultural and ecological landscape of Central Italy. This traditional practice supports local economies, maintains biodiversity, and contributes to the sustainable use of natural resources. Understanding livestock behavior in response to environmental variability is essential for improving grazing management and animal welfare and ensuring the sustainability of these systems. This study evaluated the movement patterns of sheep grazing on pastures with differing vegetation indices in the Sibillini Mountains. Twenty lactating ewes foraging on two different pastures were monitored from June to October 2023 using GPS collars and accelerometers. GPS tracks were segmented using the Expectation Maximization Binary Clustering (EmBC) method to characterize movement behaviors, such as foraging, traveling, and resting. The NDVI was used to characterize vegetation dynamics, showing notable differences between the two pastures and across the grazing season. Additive mixed models were used to analyze data, accounting for individual variability and temporal autocorrelation in the sample. The results suggest that variations in the NDVI influence grazing behavior, with sheep in areas of lower vegetation density exhibiting increased movement during foraging. These findings provide valuable insights for optimizing grazing practices and promoting sustainable land use. Full article

Convolutional neural networks (CNNs) and their application in animal husbandry have in-depth mathematical expressions, which usually revolve around how well they map input data such as images or video frames of animals to meaningful outputs like health status, behavior class, and identification. Likewise, computer vision and deep learning models are driven by CNNs to act intelligently in improving productivity and animal management for sustainable animal husbandry. In animal husbandry, CNNs play a vital role in the management and monitoring of livestock’s health and productivity due to their high-performance accuracy in analyzing images and videos. Monitoring animals’ health is important for their welfare, food abundance, safety, and economic productivity. This paper aims to comprehensively review recent advancements and applications of relevant models that are based on CNNs for livestock health monitoring, covering the detection of their various diseases and classification of their behavior, for overall management gain. We selected relevant articles with various experimental results addressing animal detection, localization, tracking, and behavioral monitoring, validating the high-performance accuracy and efficiency of CNNs. Prominent anchor-based object detection models such as R-CNN (series), YOLO (series) and SSD (series), and anchor-free object detection models such as key-point based and anchor-point based are often used, demonstrating great versatility and robustness across various tasks. From the analysis, it is evident that more significant research contributions to animal husbandry have been made by CNNs. Limited labeled data, variation in data, low-quality or noisy images, complex backgrounds, computational demand, species-specific models, high implementation cost, scalability, modeling complex behaviors, and compatibility with current farm management systems are good examples of several notable challenges when applying CNNs in animal husbandry. By continued research efforts, these challenges can be addressed for the actualization of sustainable animal husbandry. Full article

Health care systems rely on geographical boundaries that secure financial stability and adequate planning. Quality differences across regions often arise for efficiency reasons, causing patient flows if mobility is free. In this paper, a theoretical spatial competition model is developed to study the role of patients’ mobility on quality setting and to draw policy implications on its use as an instrument to reduce disparities, in a setting where regions differ in efficiency, costs, and market structure. From the analysis, it emerges that the institutional setting matters and a trade-off may appear between equity (in terms of quality difference across patients) and welfare (finding an allocation that maximizes social benefits). In a centralized setting, it is optimal to regulate mobility and increase the quality gap, while allowing free mobility calls for a refined quality setting, in which, depending on a balance between costs and benefits, the quality gap may be either increased or decreased. In decentralization the gap is generally lower, compared to centralization: the different consideration of benefits from local quality provision results in higher quality levels where the market structure is vertically integrated. Full article

Based on the framework of the United Nations 2030 Agenda for Sustainable Development, this study takes Hainan Province of China as a typical case. It evaluates a comprehensive sustainable development assessment system covering six dimensions: economic development, social welfare, resources and environment, consumption and emission, governance and protection, and agricultural development through the entropy method. It quantifies the sustainable development levels of the entire province from 2015 to 2023 and of 18 cities and counties in 2023 using cluster analysis. It also analyzes the mechanism of the local government’s role through policy text analysis. The study shows that, firstly, the comprehensive sustainable development level of Hainan Province has been steadily rising. Economic development, social welfare, resources and environment, and consumption and emission have generally improved, but the governance and protection and agricultural development indicators have shown significant phased fluctuations. Secondly, in 2023, the sustainable development levels of cities and counties in Hainan Province presented a “stepwise distribution” spatial differentiation feature. Central cities such as Haikou and Sanya have developed ahead, while the development in the central and western regions has been relatively moderate. Thirdly, local governments have achieved multi-dimensional goal coordination through policies such as industrial structure optimization and ecological compensation mechanisms. The study suggests that while strengthening the leading role of local governments, it is necessary to build a multi-party collaborative mechanism involving enterprises, social organizations, and the public to address the regional imbalance in the implementation of SDGs. Full article

The buffalo species (Bubalus bubalis) is crucial for the global economy, supplying high-nutritional-value animal proteins vital for children’s growth. These animals efficiently convert fiber into energy and thrive in various harsh environments, from frigid climates to hot, humid areas, including wetlands. They produce milk and meat while supporting the sustainability of ecosystems that other ruminants cannot inhabit. Buffalo offers a unique opportunity to supply resources for both rural communities and larger farms located in specific regions, such as marshlands and humid savannahs. They also thrive on extensive pastures and family farms, thus preserving biodiversity, habitats, and cultural practices. Intensive farming brings distinct challenges and is often criticized for its negative effects on climate change. To counter these impacts, multiple strategies have been researched and implemented. These include enhancing livestock genetics, adopting sustainable agricultural practices, optimizing local feed resources (including by-products), managing manure (with an emphasis on renewable energy), and improving animal health and welfare. This review explores various buffalo farming system applications in different global contexts. It is based on the hypothesis that the adaptable traits of buffalo, as well as the environmental and economic challenges that must be addressed for sustainability, are the key factors in determining the viability of such enterprises. Full article

Background/Objectives: The Republic of Korea is undergoing a significant demographic shift toward a population with a high proportion of older adults. In response, the Act on Integrated Support for Community Care was enacted. This study explores the role of tertiary hospitals in integrated care, aiming to enhance healthcare systems that support older individuals by facilitating the transition from hospital- to community-based care. Methods: Seoul St. Mary’s Hospital, operating under the Catholic Foundation, provides care grounded in healing and spirituality. As part of its mission, a multidisciplinary task force (TF) was formed to examine the hospital’s role in integrated care for an aging society. The TF, composed of eight experts from various departments, engaged in open discussions from September 2024 to January 2025. Results: The Integrated Care Act, which seeks to integrate medical care and caregiving within communities, requires the development of a digital system, the establishment of a governance framework for multidisciplinary collaboration, and the creation of institutions for training professionals in integrated care. Tertiary hospitals must develop department-specific models for transitional care and establish policy research institutes focused on holistic, patient-centered care. Family medicine departments can play a central role in coordinating between tertiary hospitals and local communities. Conclusions: This study highlights the importance of collaboration between medical, caregiving, and social welfare professionals as key enablers of “aging in place”. The findings underscore the evolving role of tertiary hospitals and contribute to fostering a more sustainable healthcare model for Korea’s aging population. Full article

The aim of this paper is to review the literature on the environmental impacts of pasture-based dairy cattle systems, focusing on the factors affecting the main impact categories. This paper also aimed at comparing data of the literature on environmental impacts in pasture-based vs. confined systems. The environmental impact of pasture-based dairy cattle systems appears to be highly influenced by several input factors. Life cycle assessments have shown significant variability in methodological approaches, which complicates the comparison of results across studies. The different variables affecting environmental impacts make it challenging to draw universally valid conclusions regarding the comparison of pasture-based and confined dairy systems on a global scale. In addition, the analysis of the variables highlights the considerable potential to reduce the environmental impact of milk production in both systems by adopting productivity-enhancing activities, low inputs and best management practices. Further aspects such as geographical factors, carbon sequestration, animal health and welfare, toxicological aspects due to the use of drugs and antimicrobials in animals and the maintenance of local animal breeds should be incorporated into LCAs for a full comprehensive understanding of the environmental impacts of dairy farms. Full article

Precision Livestock Farming (PLF) applies a complex of sensor technology, algorithms, and multiple tools for individual, real-time livestock monitoring. In intensive livestock systems, PLF is now quite widespread, allowing for the optimisation of management, thanks to the early recognition of diseases and the possibility of monitoring animals’ feeding and reproductive behaviour, with an overall improvement of their welfare. Similarly, PLF systems represent an opportunity to improve the profitability and sustainability of extensive farming systems, including those of small ruminants, rationalising the use of pastures by avoiding overgrazing and controlling animals. Despite the livestock distribution in several parts of the world, the low profit and the relatively high cost of the devices cause delays in implementing PLF systems in small ruminants compared to those in dairy cows. Applying these tools to animals in extensive systems requires customisation compared to their use in intensive systems. In many cases, the unit prices of sensors for small ruminants are higher than those developed for large animals due to miniaturisation and higher production costs associated with lower production numbers. Sheep and goat farms are often in mountainous and remote areas with poor technological infrastructure and ineffective electricity, telephone, and internet services. Moreover, small ruminant farming is usually associated with advanced age in farmers, contributing to poor local initiatives and delays in PLF implementation. A targeted literature analysis was carried out to identify technologies already applied or at an advanced stage of development for the management of grazing animals, particularly sheep and goats, and their effects on nutrition, production, and animal welfare. The current technological developments include wearable, non-wearable, and network technologies. The review of the technologies involved and the main fields of application can help identify the most suitable systems for managing grazing sheep and goats and contribute to selecting more sustainable and efficient solutions in line with current environmental and welfare concerns. Full article

Animal welfare in barns is strongly influenced by air quality, with gaseous emissions like ammonia posing significant respiratory health risks. However, current state-of-the-art ammonia monitoring systems are labor-intensive and expensive. Metal Oxide Semiconductor (MOS) sensors offer a promising alternative due to their compatibility with sensor networks, enabling high-resolution ammonia monitoring across spatial and temporal scales. While MOS sensors exhibit high sensitivity to various volatile compounds, temperature-cycled operation is commonly employed to enhance selectivity, effectively creating virtual sensor arrays. This study aims to improve ammonia detection by designing a virtual sensor array through a cyclic data-driven approach, integrating machine learning with solid-state sensor modeling. The results of a two-week dataset with measurements of four different pig barns demonstrate ammonia sensing with a sampling rate of about 2/min and a range of 1–30 ppm. The method is robust and exhibits a 10% increase in normalized RMSE when comparing testing results of an unseen sensor module with results of the training dataset. A filter membrane boosts accuracy and prevents data loss due to contamination, such as flyspecks. Overall, the used MOS sensor BME688 is effective and economical for widespread continuous ammonia monitoring and localization of ammonia sources in pig barns. Full article

In Europe, intensive agriculture threatens species-rich semi-natural communities that have emerged from traditional agricultural activities. To protect these communities, subsidies are given to farmers through agri-environmental schemes (AESs). However, after nearly twenty years in operation, the uniform support system for farmers has not produced the expected results. Therefore, we conducted 15 semi-structured, in-depth qualitative interviews with beef cattle farmers in Estonia and identified the socio-ecological aspects of their activities. We found that small-scale farmers cannot compete with intensive farmers in the meat market because many breeds with slower weight gain and smaller body weights are grazed in semi-natural grasslands. Although two food quality schemes have been created in Estonia to value extensively grown meat, the permanent agricultural grasslands are under-supported, and the family farmers managing these areas feel the unfair distribution of subsidies. Moreover, family farms cannot compete with large farms, as the availability of pastures on family farms limits the number of livestock, and European Union animal welfare requirements and extreme weather conditions in 2023 have limited the number of herds. Since AESs have a large impact on farmers, we recommend that they be more flexible and consider the socio-cultural background of farmers and their impact on local communities when defining support. Full article

Real-time pricing is an ideal pricing mechanism for regulating the balance of power supply and demand in smart grid. Considering the differences in electricity consumption risks among different types of users, a social welfare maximization model with user risk classification is proposed in this paper. Also, a smoothing Newton method is investigated for solving the proposed model. Firstly, the convexity of the model is discussed, which implies that the local optimum of the model is also the global optimum. Then, by transforming the proposed model into a smooth equation system based on the Karush–Kuhn–Tucker (KKT) conditions, we devise a smoothing Newton algorithm integrated with Powell–Wolfe line search criteria. The nonsingularity of the corresponding function’s Jacobian matrix is obtained to ensure the stability of the proposed algorithm. Finally, we give a comparison between the proposed model and the unclassified risk model and the proposed algorithm and the distributed algorithm for real-time pricing, time-of-use pricing, and fixed pricing, respectively. The numerical results demonstrate the effectiveness of the model and the algorithm. Full article