Search Results (13,875)

Calf welfare is critically influenced by early-life husbandry practices and health conditions. This narrative review synthesizes current evidence on key management practices affecting calf welfare, including calving, colostrum intake, milk feeding, water provision, weaning, housing, mutilations, and transport. A structured literature search was conducted in Web of Science and Scopus using general and topic-specific keywords, complemented by expert opinions from EFSA. Evidence-based recommendations are presented to improve calf welfare, emphasizing timely colostrum administration, biologically appropriate milk volumes, access to clean water from birth, gradual weaning, and stable social housing. Pain mitigation during disbudding and castration, along with strict biosecurity and hygiene, are essential to reduce disease risk. Despite advancements, significant knowledge gaps persist, including practical tools for on-farm colostrum assessment, optimal weaning protocols, the long-term impacts of early-life pain, and alternatives to current transport practices. The review highlights the need for standardized protocols, validated technologies, and enhanced training for farmers and veterinarians. Improving husbandry practices based on scientific evidence is essential to enhance calf health, productivity, and ethical sustainability in modern rearing systems. Full article

Environmental protection is an essential path to achieving high-quality economic development, and green tax policies are an effective means of achieving environmental protection. This study categorizes green tax policies into environmental protection-oriented green tax policies, resource-oriented green tax policies, and guidance-oriented green tax policies based on the nature of the tax. The fixed-effect model, the system GMM model and the continuous DID model are used to explore the causal relationship between the overall green tax policy, the classified green tax policy and the use of natural resources. The spatial Durbin model is used to explore the spatial spillover effect of the green tax policy and the regional heterogeneity in the east, central, west and northeast of China. Finally, the role of trade openness in the relationship between the green tax policy and natural resource use is explored. The research results show that (1) the green tax policy has a positive effect on natural resource use, but the green tax policy in the previous period has no promoting effect, and the natural resource use in the previous period has a positive impact on the current period. Among them, there is no causal relationship between the resource-occupying green tax and natural resource use. (2) All three types of green tax policies studied in this paper have spatial spillover effects, but the spillover effects of the three types of green tax policies are relatively small in the eastern region. The spillover effects of the three types of green tax policies in the central region are significantly negative. In the western region, only the guiding green tax policy has a spillover effect. In the northeastern region, the environmental protection green tax policy and the resource-based green tax policy are significantly negative, while the guiding green tax spillover effect is significantly positive. (3) In the mechanism test, the guiding green tax policy has an impact on natural resource utilization through trade openness, while the environmental protection green tax policy and the resource-based green tax policy cannot affect natural resource utilization through the level of trade openness. Finally, based on the research conclusions, policy recommendations are proposed from the perspectives of policy timeliness, tax structure adjustment, and trade network optimization to maximize economic benefits. Full article

The Yangtze River fishing ban policy is a central measure in China’s watershed governance, and the adaptability of its policy tools and collaborative mechanisms directly influences the sustainability and effectiveness of basin management. This study systematically examines the evolution of policy themes, the characteristics of policy tool combinations, and their alignment with intergovernmental collaborative governance needs, drawing on 120 central government policy texts issued between 2002 and 2024. Using frequency analysis and policy tool coding, the findings reveal that (1) policy themes have shifted from fishery resource control to comprehensive ecological protection and, more recently, to integrated watershed management, thereby driving progressively higher demands for intergovernmental collaboration. (2) The policy tool structure has long been dominated by environmental tools, supplemented by supply-side tools, while demand-side tools remain underdeveloped. Imbalances persist, such as excessive emphasis on resource inputs over capacity building in supply-side tools, rigid constraints with limited flexibility in environmental tools, and a reliance on publicity while underutilizing market incentives in demand-side tools. (3) Tool combinations have adapted to changing collaboration needs, evolving from rigid constraints and fiscal subsidies to institutional frameworks and cross-regional cooperation, ultimately forming a governance model characterized by systemic guarantees and diversified collaboration. Based on these findings, this study recommends strengthening long-term governance mechanisms, improving cross-regional collaborative structures, authorizing local governments to design context-specific implementation details, enhancing fishermen’s livelihood security and social development, expanding public participation and oversight, and exploring market mechanisms for realizing ecological product value. These measures aim to advance collaborative governance in the Yangtze River Basin and foster a balanced integration of ecological protection and social development. Full article

The integrated rice–aquaculture farming system (IRAFS), which combines rice cultivation with aquaculture, is a crucial strategy for improving economic efficiency, ecological sustainability, and social welfare. This model has been widely adopted across most regions of China, recognized for its sustainability and environmental benefits. The study analyzes the economic, social and environmental benefits of the current integrated rice–aquaculture integrated farming practices while assessing its market prospects. It identifies key limitations in existing models, particularly regarding water conservation, pollution reduction and system performance. Additionally, the study highlights future research directions and offers actionable recommendations to fully leverage the development potential of IRAFS. Through comparative analysis, this study identifies shortcomings in current water-saving and emission-reduction practices. It proposes an integrated model to balance grain production, environmental benefits, and economic returns. The aim is to provide theoretical support for enhancing agricultural quality and efficiency while promoting sustainable development. Full article

Digital Twins (DTs) are poised to transform personalized medicine by enabling real-time, multiscale simulations of individual patients. By integrating genomics, imaging, wearable sensor data, and clinical records, DTs offer a powerful platform for predictive, adaptive, and patient-centered decision-making. Recent advances have highlighted their potential across a range of clinical domains, including cardiology, oncology, pharmacogenomics, and neurology. Yet, their routine application in clinical practice remains limited, underscoring a growing translational gap between digital innovation and healthcare delivery. In this review, we explore the scientific maturity and emerging clinical use cases of DTs, while critically analyzing the systemic, regulatory, ethical, and infrastructural barriers that hinder their widespread adoption. We outline a translational roadmap that emphasizes dynamic model validation, clinician co-development, equitable data representation, and regulatory harmonization. Uniquely, we reframe DTs as cognitive tools for clinical reasoning and decision support. We further clarify translational pathways through explicit evaluation and reporting recommendations. By positioning DTs within this practical framework, we outline how responsible, inclusive, and interdisciplinary implementation can establish them as foundational elements of 21st century precision medicine. Full article

Large Language Models (LLMs) are increasingly proposed to personalize healthcare delivery, yet their real-world readiness remains uncertain. We conducted a systematic literature review to assess how LLM-based systems are designed and used to enhance patient engagement and personalization, while identifying open challenges these tools pose. Four digital libraries (Scopus, IEEE Xplore, ACM, and Nature) were searched, yielding 3787 studies; 16 met the inclusion criteria. Most studies, published in 2024, span different types of motivations, architectures, limitations and privacy-preserving approaches. While LLMs show potential in automating patient data collection, recommendation/therapy generation, and continuous conversational support, their clinical reliability is limited. Most evaluations use synthetic or retrospective data, with only a few employing user studies or scalable simulation environments. This review highlights the tension between innovation and clinical applicability, emphasizing the need for robust evaluation protocols and human-in-the-loop systems to guide the safe and equitable deployment of LLMs in healthcare. Full article

(1) This study aims to enhance the precision of ergonomic fitting in traditional shoe size selection by integrating literature and measured biometric data. (2) A correlation table between biometric features and shoe models was established, which was then embedded into a knowledge graph (KG) for visual, accurate recommendations. The experiment employed pressure sensors and depth cameras to collect biometric data from the foot and leg, evaluating the consistency of the system’s recommendations and user satisfaction. (3) The results indicate that the biometric-driven shoe recommendation system significantly outperforms traditional size-based systems in terms of stability and satisfaction. (4) The KG framework has notably improved ergonomic adaptability in the early prototype stage, offering a viable technological approach for intelligent shoe selection and holding significant potential for further optimization. Full article

Against the backdrop of expanding off-farm employment, it is of great practical significance to examine how off-farm employment affects grain production and its underlying mechanisms, in order to build a more stable and sustainable national food security system. Drawing on micro-level data from wheat-producing households in the national Rural Fixed Observation Points survey from 2004 to 2021, this study systematically investigates the impact of off-farm employment on wheat planting decisions and the channels through which it operates. The findings reveal the following: (1) Off-farm employment encourages farmers to adjust their factor input structure and crop choices, leading to an increased proportion of wheat sown area. (2) Agricultural socialized services, especially mechanized operations, enhance the feasibility of factor substitution and effectively channel off-farm income into agricultural investment. Furthermore, the number of service providers at the village level plays a significant moderating role in this process; the more adequate the service supply, the stronger the positive effect of off-farm employment on wheat cultivation. (3) The influence of off-farm employment on wheat production is more pronounced in plain regions with favorable topographic conditions and among large-scale farming households. Based on these findings, the study recommends improving the agricultural service system, promoting better coordination between off-farm employment and agricultural development, and fostering a more stable and sustainable support system for grain production. Full article

A precise understanding of the carbon dynamics of agricultural land use is essential for advancing China’s “dual carbon” goals and promoting sustainable rural development. Drawing on panel datasets for 31 Chinese provinces over the period 1997–2022, this study comprehensively analyzes the spatiotemporal evolution, regional disparities, and transition dynamics of agricultural carbon capture and emissions. Using a combination of the emission factor method, the Dagum Gini coefficient, kernel density estimation, and Markov chain models, the study finds that China’s total agricultural carbon capture has continued to increase, yet regional disparities are widening, with the central region leading and the northeastern region lagging. Meanwhile, agricultural carbon emissions exhibit a “strong west, weak east” spatial pattern and demonstrate a high degree of club convergence. Club convergence refers to the phenomenon where regions with similar initial levels converge to the same steady-state over the long run, while remaining persistently different from other regions. The net carbon effect exhibits a dual structure of carbon surplus zones and carbon deficit zones: 23 provinces act as carbon surplus zones, while 8 provinces are carbon deficit zones, primarily located in ecologically fragile or special-function regions. These findings highlight the spatial heterogeneity, path dependence, and policy sensitivity of carbon effects from agricultural land use. Accordingly, the study proposes differentiated policy recommendations, including region-specific carbon management strategies, the establishment of a unified agricultural carbon trading system, and the integration of technological and institutional innovations to achieve a balanced and low-carbon agricultural transformation. Full article

Compared with other fossil energy sources, natural gas is characterized by compressibility, low energy density, high storage costs, and imbalanced usage. Natural gas pipeline supply systems possess unique attributes such as closed transportation and a highly integrated upstream, midstream, and downstream structure. Moreover, pipelines are almost the only economical means of onshore natural gas transportation. Given that the upstream of the pipeline features multi-entity and multi-channel supply including natural gas, coal-to-gas, and LNG vaporized gas, while the downstream presents a competitive landscape with multi-market and multi-user segments (e.g., urban residents, factories, power plants, and vehicles), there is an urgent social demand for non-discriminatory and fair opening of natural gas pipeline network infrastructure to third-party entities. However, after the fair opening of natural gas pipeline networks, the original “point-to-point” transaction model will be replaced by market-driven behaviors, making the verification and allocation of gas transmission capacity a key operational issue. Currently, neither pipeline operators nor government regulatory authorities have issued corresponding rules, regulations, or evaluation plans. To address this, this paper proposes a multi-dimensional quantitative evaluation model based on the Analytic Hierarchy Process (AHP), integrating both commercial and technical indicators. The model comprehensively considers six indicators: pipeline transportation fees, pipeline gas line pack, maximum gas storage capacity, pipeline pressure drop, energy consumption, and user satisfaction and constructs a quantitative evaluation system. Through the consistency check of the judgment matrix (CR = 0.06213 < 0.1), the weights of the respective indicators are determined as follows: 0.2584, 0.2054, 0.1419, 0.1166, 0.1419, and 0.1357. The specific score of each indicator is determined based on the deviation between each evaluation indicator and the theoretical optimal value under different gas volume allocation schemes. Combined with the weight proportion, the total score of each gas volume allocation scheme is finally calculated, thereby obtaining the recommended gas volume allocation scheme. The evaluation model was applied to a practical pipeline project. The evaluation results show that the AHP-based evaluation model can effectively quantify the advantages and disadvantages of different gas volume allocation schemes. Notably, the gas volume allocation scheme under normal operating conditions is not the optimal one; instead, it ranks last according to the scores, with a score 0.7 points lower than that of the optimal scheme. In addition, to facilitate rapid decision-making for gas volume allocation schemes, this paper designs a program using HTML and develops a gas volume allocation evaluation program with JavaScript based on the established model. This self-developed program has the function of automatically generating scheme scores once the proposed gas volume allocation for each station is input, providing a decision support tool for pipeline operators, shippers, and regulatory authorities. The evaluation model provides a theoretical and methodological basis for the dynamic optimization of natural gas pipeline gas volume allocation schemes under the fair opening model. It is expected to, on the one hand, provide a reference for transactions between pipeline network companies and shippers, and on the other hand, offer insights for regulatory authorities to further formulate detailed and fair gas transmission capacity transaction methods. Full article

This study presents SAIL-Y (Sailing Artificial Intelligence for Learning in Youth), a novel gender-focused recommender system designed to promote female participation in STEM careers through data-driven guidance. Drawing inspiration from the metaphor of an academic journey as a voyage, SAIL-Y functions as a digital compass—leveraging socioeconomic profiles and standardised test results (Saber 11, Colombia) to help students navigate career decisions in high-impact academic fields. SAIL-Y integrates multiple machine learning strategies, including collaborative filtering, bootstrapped data augmentation to rebalance gender representation, and socioeconomic-aware conditioning, to generate personalised and bias-controlled career recommendations. The system is explicitly designed to skew recommendations toward STEM disciplines for female students, countering systemic underrepresentation in these fields. Using a dataset of 332,933 Colombian students (2010–2021), we evaluate the performance of different recommendation architectures under the SAIL-Y framework. The results show that a gender-oriented recommender design increases the proportion of STEM career recommendations for female students by up to 25% compared to reference models. Beyond technical contributions, this work proposes an ethically aligned paradigm for educational recommender systems—one that empowers rather than merely predicts. SAIL-Y is thus envisioned as both a methodological tool and a socio-educational intervention, supporting more equitable academic journeys for future generations. Full article

Precision dicing with diamond wheels is a key technology in semiconductor dicing, integrated circuit manufacturing, aerospace, and other fields, owing to its high precision, high efficiency, and broad material applicability. As a critical processing stage, a comprehensive analysis of dicing technologies is essential for improving the machining quality of hard-and-brittle optoelectronic materials. This paper reviews the core principles of precision diamond wheel dicing, including dicing processes and blade preparation methods. Specifically, it examines the dicing mechanisms of composite and multi-mode dicing processes, demonstrating their efficacy in reducing defects inherent to single-mode approaches. The review also examines diverse preparation methods for dicing blades, such as metal binder sintering and roll forming. Furthermore, the roles of machine vision and servo control systems are detailed, illustrating how advanced algorithms facilitate precise feature recognition and scribe line control. A systematic analysis of key components in grinding wheel dicer is also conducted to reduce dicing deviation. Additionally, the review introduces models for tool wear detection and discusses material removal mechanisms. The influence of critical process parameters—such as spindle speed, feed rate, and dicing depth—on dicing quality and kerf width is also analyzed. Finally, the paper outlines future prospects and provides recommendations for advancing key technologies in precision dicing, offering a valuable reference for subsequent research. Full article

Lymphomas involving the central nervous system (CNS) have worse outcomes, including both primary and secondary CNS lymphomas, which are associated with poorer overall survival outcomes. The World Health Organization classifies CNS lymphoma as arising from the brain, leptomeninges, and spinal cord, but this simplified CNS anatomical definition fails to incorporate areas of ambiguity that can be clinically relevant for treatment decision making. In this article, we review the anatomical boundaries of CNS lymphoma within select border-zone biological structures located at the CNS borders in order to gain a consensus working definition of CNS disease boundaries. We review anatomical localizations with border-zone CNS boundaries, including the dura, cavernous sinus, circumventricular organs, pituitary gland, and cranial nerves. Though some portions of the eye would be considered CNS and others extra-CNS, recommendations for this structure are outside the scope of this review. Through this review, we examine the impact of lymphomatous invasion on select CNS-bordering anatomical structures, aiming to better define treatment categorization as CNS or extra-CNS, with a focus on B cell lymphoma types. Full article

This article investigates strategies for advancing sustainable learning among learners with visual impairments (LVIs) in historically disadvantaged schools in Lesotho, a low-income country. Despite global efforts to promote inclusive education, LVIs in Lesotho continue to experience multiple barriers, including limited access to adapted learning materials and inadequately resourced learning environments. Employing a qualitative participatory case study design and focus group discussions, the study engaged 12 purposively selected participants, including school principals, special education teachers, and general education teachers, from two rural primary schools. Grounded in the principles of the inclusive special education framework, this study contributes to the discourse on promoting sustainable learning by examining specific experiences of LVIs in these contexts. While the focus on LVIs in rural contexts represents one subset of historically disadvantaged institutions, the findings highlight persistent systemic challenges, such as insufficient resources, restrictive learning conditions, and the underutilisation of teachers’ specialised expertise in visual impairment education, that resonate more broadly across marginalised educational settings. Even though its generalisation remains, the study recommends recognising and enhancing the professional status of educators trained in visual impairment, strengthening policy support for sustainable infrastructure, and embedding sustainable learning principles to promote LVI independent learning. By centring the voices of teachers in disadvantaged settings, this research contributes to the discourse on advancing sustainable learning, which offers accessible contextually relevant strategies to advance educational equity and justice for LVIs in Lesotho. Full article

Urban green space (UGS) is a fundamental element of urban systems for enhancing the quality of urban life. UGS plays a pivotal role in promoting urban ecological sustainability if important criteria are integrated into urban planning programs. This paper explores the impacts of the ecological criteria on urban sustainability through UGS planning and examines these criteria within the context of the Adelaide Metropolitan Area as a case study. To address the study’s goals, a content analysis was conducted to identify the most critical criteria affecting urban ecological sustainability through UGS planning. Subsequently, based on the identified criteria, a household survey was conducted to evaluate the status of the case study concerning the ecological sustainability factors. In this stage, 100 responses were collected through a questionnaire survey. Then, based on the household survey results, a solution was provided to the challenging criteria by a local experts’ interview. For promoting urban ecological sustainability, ten criteria were identified as the most important and effective criteria based on the previous studies. Household survey data was analysed using one-sample T-test, multiple linear regression, and geographically weighted regression (GWR) model. The results indicated that the criteria of reviving ecological networks, water resources, and the protection of UGS with the score below standard average (which is 3), require practical guidelines and policies to enhance the sustainability of Adelaide Metropolitan Area. The regression analysis demonstrated that ecological landscape and design had the strongest positive effect on sustainability (adjusted R² = 0.685), while the geographically weighted regression highlighted biodiversity and vegetation as particularly influential in Plympton (local R² = 0.866) and Unley (local R² = 0.488). Expert interviews recommended strategies such as wastewater recycling, long-term conservation planning, and restoring ecological connectivity. This study provides a practical framework to guide urban planners and policymakers in enhancing ecological sustainability through UGS planning. Full article