Search Results (5,201)

With the digital economy continuing to integrate deeply into the agricultural sector, agricultural digital transformation has emerged as a pivotal driver of rural revitalization and the development of a robust agricultural economy. Although existing studies have affirmed the positive role of agricultural digital transformation in promoting rural development and enhancing agricultural efficiency, its spatiotemporal evolution patterns, regional disparities, and underlying driving factors have not yet been systematically and thoroughly investigated. This study seeks to fill that gap. Based on provincial panel data from China spanning 2011 to 2023, this study employs the Theil index, kernel density estimation, Moran’s index, and quantile regression to systematically assess the spatiotemporal dynamics and driving factors of agricultural digital transformation at both national and regional levels. The results reveal a steady overall improvement in agricultural digital transformation, yet regional development imbalances remain prominent, with a shift from inter-regional disparities to intra-regional disparities over time. The four major regions exhibit a stratified evolutionary trajectory marked by internal differentiation: the eastern region retains its lead, while central and western regions show potential for catch-up, and the northeastern region faces a “balance trap.” Economic development foundation, human capital quality, and policy environment support are identified as the core driving forces of transformation, while other factors demonstrate pronounced regional and phase-specific variability. This study not only deepens theoretical understanding of the uneven development and driving logic of agricultural digital transformation but also provides empirical evidence to support policy optimization and promote more balanced and sustainable development in the agricultural sector. Full article

West Africa faces persistent food and nutrition insecurity despite agricultural efforts, exacerbated by population growth, climate change, and socio-economic vulnerabilities. This study argues that integrating food processing principles with nutrition-sensitive agriculture (NSA) and nutrition-smart agriculture (NSmartAg) offers a transformative solution for human health. Therefore, we delineate these interconnected concepts and highlight their synergistic potential for a nutrition-focused food system. Likewise, critical analysis of key regional challenges, including infrastructural weaknesses, policy gaps, and gender inequities, was made prior to identifying significant opportunities for leveraging food processing as a strategic entry point to accelerate the implementation of NSA and NSmartAg. Based on these insights, six strategic pathways are proposed to achieve this objective: (i) integrating food processing into policies; (ii) investing in interdisciplinary R&D that puts nutrition and health benefits at the forefront of desired outcomes along with others; (iii) strengthening farmer and food processor capacities; (iv) improving agri-food infrastructure; (v) fostering multi-sectoral collaboration; and (vi) prioritizing youth engagement and market development. By adopting these integrated strategies, West African countries can build more resilient, equitable, and nutrition-centered food systems, ultimately improving public health outcomes and fostering sustainable regional development. Full article

Sign language recognition plays a crucial role in enabling communication for deaf individuals, yet current methods face limitations such as sensitivity to lighting conditions, occlusions, and lack of adaptability in diverse environments. This study presents a wearable multi-channel tactile sensing system based on smart textiles, designed to capture subtle wrist and finger motions for static sign language recognition. The system leverages triboelectric yarns sewn into gloves and sleeves to construct a skin-conformal tactile sensor array, capable of detecting biomechanical interactions through contact and deformation. Unlike vision-based approaches, the proposed sensor platform operates independently of environmental lighting or occlusions, offering reliable performance in diverse conditions. Experimental validation on American Sign Language letter gestures demonstrates that the proposed system achieves high signal clarity after customized filtering, leading to a classification accuracy of 94.66%. Experimental results show effective recognition of complex gestures, highlighting the system’s potential for broader applications in human-computer interaction. Full article

In the age of artificial intelligence (AI), architectural practice faces a paradox of immense potential and creeping standardization. As humans are increasingly relying on AI-generated outputs, architecture risks becoming a spectacle of repetition—a shuffling of data that neither truly innovates nor progresses vertically in creative depth. This paper explores the critical role of data in AI systems, scrutinizing the training datasets that form the basis of AI’s generative capabilities and the implications for architectural practice. We argue that when architects approach AI passively, without actively engaging their own creative and critical faculties, they risk becoming passive users locked in an endless loop of horizontal expansion without meaningful vertical growth. By examining the epistemology of architecture in the AI age, this paper calls for a paradigm where AI serves as a tool for vertical and horizontal growth, contingent on human creativity and agency. Only by mastering this dynamic relationship can architects avoid the trap of passive, standardized design and unlock the true potential of AI. Full article

In recent years, the biomedical startup industry has flourished, and yet, it still faces challenges in adapting to changing market demands. Meanwhile, the widespread use of single-use medical devices generates significant waste, posing threats to environmental sustainability. Addressing this issue has become a critical challenge for humanity today. The study aimed to delve into the specific difficulties faced by Taiwanese biomedical entrepreneurs during the innovation and development of medical devices from a sustainability perspective and to explore solutions. This study collected first-hand experiences and insights from Taiwanese biomedical entrepreneurs through a literature review and expert questionnaires. It employed Interpretive Structural Modeling to analyze the development stages and interrelationships of biomedical device startups for building sustainable biomedical innovation. The Clinical Needs Assessment is revealed as the most influential factor, shaping Regulatory Feasibility Evaluation, Clinical Trial Execution, and Market Access Compliance. Our findings provide a structured problem-solving framework to assist biomedical startups in overcoming challenges while incorporating energy-saving and carbon reduction processes to achieve environment sustainability goals. The results of this study show that biomedical innovation practitioners should prioritize integrating sustainability considerations directly into the earliest stage of a Clinical Needs Assessment. Full article

Small-scale farms deserve attention and support because they play crucial and important roles. Apart from ensuring provision of food security, they also provide other economic, environmental, and social–cultural benefits. In the United States of America, these farms are agriculturally, culturally, and geographically different. They have varied needs that trigger an array of distinct biophysical, socioeconomic, and institutional challenges. The effects of these challenges are exacerbated by economic uncertainty, technological advancements, climate change, and other environmental concerns. To provide ideal services to the small-scale farm audience, it is necessary to understand these challenges and opportunities that can be leveraged to enhance their productivity and profitability. This article reviews the challenges faced by small-scale farming in the United States of America. It then reviews possible pathways to enhance their productivity and profitability. The review revealed that U.S. small-scale farms face several challenges. They include accessing farmland, credit and capital, lack of knowledge and skills, and technology adoption. Others are difficulties to insure, competition from corporations, and environmental uncertainties associated with climate change. The paper then reviews key pathways to enhance small-scale farmers’ capacities and resilience with a positive impact on their productivity and profitability. They are enhanced cooperative extension services, incentivization, strategic marketing, annexing technology, and government support, among others. Based on the diversity of farms and their needs, responses should be targeted towards individual needs. Since small-scale farm products have an effect on human health and dietary patterns, strategies to increase productivity should be linked to nutrition and health. Full article

Street view imagery has become a vital tool for assessing urban street greenery, with the Green View Index (GVI) serving as the predominant metric. However, while GVI effectively quantifies overall greenery, it fails to capture the nuanced, human-scale experience of urban greenery. This study introduces the Front-Facing Green View Index (FFGVI), a metric designed to reflect the perspective of pedestrians traversing urban streets. The FFGVI computation involves three key steps: (1) calculating azimuths for road points, (2) retrieving front-facing street view images, and (3) applying semantic segmentation to identify green pixels in street view imagery. Building on this, this study proposes the Street Canyon Green View Index (SCGVI), a novel approach for identifying boulevards that evoke perceptions of comfort, spaciousness, and aesthetic quality akin to room-like streetscapes. Applying these indices to a case study in Nanjing, China, this study shows that (1) FFGVI exhibited a strong correlation with GVI (R = 0.88), whereas the association between SCGVI and GVI was marginally weaker (R = 0.78). GVI tends to overestimate perceived greenery due to the influence of lateral views dominated by side-facing vegetation; (2) FFGVI provides a more human-centered perspective, mitigating biases introduced by sampling point locations and obstructions such as large vehicles; and (3) SCGVI effectively identifies prominent boulevards that contribute to a positive urban experience. These findings suggest that FFGVI and SCGVI are valuable metrics for informing urban planning, enhancing urban tourism, and supporting greening strategies at the street level. Full article

Wildfires increasingly threaten human life, ecosystems, and infrastructure, with events like the 2025 Palisades and Eaton fires in Los Angeles County underscoring the urgent need for more advanced prediction frameworks. Existing physics-based and deep-learning models struggle to capture dynamic wildfire spread across both 2D and 3D domains, especially when incorporating real-time, multimodal geospatial data. This paper explores how generative artificial intelligence (AI) models—such as GANs, VAEs, and transformers—can serve as transformative tools for wildfire prediction and simulation. These models offer superior capabilities in managing uncertainty, integrating multimodal inputs, and generating realistic, scalable wildfire scenarios. We adopt a new paradigm that leverages large language models (LLMs) for literature synthesis, classification, and knowledge extraction, conducting a systematic review of recent studies applying generative AI to fire prediction and monitoring. We highlight how generative approaches uniquely address challenges faced by traditional simulation and deep-learning methods. Finally, we outline five key future directions for generative AI in wildfire management, including unified multimodal modeling of 2D and 3D dynamics, agentic AI systems and chatbots for decision intelligence, and real-time scenario generation on mobile devices, along with a discussion of critical challenges. Our findings advocate for a paradigm shift toward multimodal generative frameworks to support proactive, data-informed wildfire response. Full article

Swine infectious diseases, often caused by multiple co-infecting agents, pose severe global threats to pig health and industry economics. Conventional single-plex testing assays, whether relying on pathogen antigens or nucleic acids, exhibit limited efficacy in the face of co-infection events. The modern nucleic acid-based multiplex testing (NAMT) methods demonstrate substantial strengths in the simultaneous detection of multiple pathogens involving co-infections owing to their remarkable sensitivity, exceptional specificity, high-throughput, and short turnaround time. The development, commercialization, and application of NAMT assays in swine infectious disease surveillance would be advantageous for early detection and control of pathogens at the onset of an epidemic, prior to community transmission. Such approaches not only contribute to saving the lives of pigs but also aid pig farmers in mitigating or preventing substantial economic losses resulting from infectious disease outbreaks, thereby alleviating unwanted pressure on animal and human health systems. The current literature review provides an overview of some modern NAMT methods, such as multiplex quantitative real-time PCR, multiplex digital PCR, microarrays, microfluidics, next-generation sequencing, and their applications in the diagnosis of swine infectious diseases. Furthermore, the strengths and weaknesses of these methods were discussed, as well as their future development and application trends in swine disease diagnosis. Full article

As a type of distinctive pit on Mars, skylights are entrances to subsurface lava caves. They are very important for studying volcanic activity and potential preserved water ice, and are also considered as potential sites for human extraterrestrial bases in the future. Most skylights are manually identified, which has low efficiency and is highly subjective. Although deep learning methods have recently been used to identify skylights, they face challenges of few effective samples and low identification accuracy. In this article, 151 positive samples and 920 negative samples based on the MRO-HiRISE image data was used to create an initial skylight dataset, which contained few positive samples. To augment the initial dataset, StyleGAN2-ADA was selected to synthesize some positive samples and generated an augmented dataset with 896 samples. On the basis of the augmented skylight dataset, we proposed YOLOv9-Skylight for skylight identification by incorporating Inner-EIoU loss and DySample to enhance localization accuracy and feature extracting ability. Compared with YOLOv9, the P, R, and the F1 of YOLOv9-Skylight were improved by about 9.1%, 2.8%, and 5.6%, respectively. Compared with other mainstream models such as YOLOv5, YOLOv10, Faster R-CNN, Mask R-CNN, and DETR, YOLOv9-Skylight achieved the highest accuracy (F1 = 92.5%), which shows a strong performance in skylight identification. Full article

Background/Objectives: P-glycoprotein (P-gp), an ATP-binding cassette (ABC) transporter, plays a key role in multidrug resistance by actively exporting chemotherapeutic agents and xenobiotics from cells. Overexpression of P-gp significantly reduces intracellular drug accumulation and compromises treatment efficacy. Despite extensive research, clinically approved P-gp inhibitors remain elusive due to toxicity, poor specificity, and limited efficacy. This study investigates DMH1, a selective type I BMP receptor inhibitor, as a novel P-gp inhibitor. Methods: DMH1 cytotoxicity was assessed in P-gp-overexpressing (PC3-TxR, K562/Dox) and P-gp-deficient (PC3) cell lines using MTT assays. P-gp inhibition was evaluated using calcein AM retention and daunorubicin (DNR) accumulation assays. Kinetic analysis determined DMH1’s effect on P-gp-mediated transport (Vmax and Km). ATPase activity assays were performed to assess DMH1’s impact on ATP hydrolysis. Preliminary molecular docking (CB-Dock2) was used to predict DMH1’s binding site on the human P-gp structure (PDB ID: 6QEX). Results: DMH1 showed no cytotoxicity in P-gp-overexpressing or deficient cells. It significantly enhanced intracellular accumulation of Calcein AM and DNR, indicating effective inhibition of P-gp function. Kinetic data revealed that DMH1 reduced Vmax without affecting Km, consistent with noncompetitive, allosteric inhibition. DMH1 also inhibited ATPase activity in a dose-dependent manner. Docking analysis suggested DMH1 may bind to an allosteric site in the transmembrane domain, potentially stabilizing the inward-facing conformation. Conclusions: DMH1 is a promising noncompetitive, allosteric P-gp inhibitor that enhances intracellular drug retention without cytotoxicity, supporting its potential as a lead compound to overcome multidrug resistance and improve chemotherapeutic efficacy. Full article

Aquaculture is a crucial food-producing sector that can supply more essential nutrients to nourish the growing human population. However, it faces challenges, including limited water quality and space competition. These constraints have led to the intensification of culture systems for more efficient resource use while maintaining or increasing production levels. However, intensification introduces stress risks to cultured organisms by, for instance, overcrowding, waste accumulation, and water quality deterioration, which can negatively affect the growth, health, and immunity of animals and cause diseases. Additionally, environmental changes due to climate and anthropogenic activities further intensify the environmental stress for aquaculture organisms, including crustaceans. Shrimp are one of the most widely cultured and consumed farmed crustacea. Relative to aquatic vertebrates such as fish, the physiology of crustaceans has simpler physiological structures, as they lack a spinal cord. Consequently, their stress response mechanisms follow a single pathway, resulting in less complex responses to stress exposure compared to those of fish. While stress is considered a primary factor influencing the growth, health, and immunity of shrimp, comprehensive research on crustacean stress responses remains limited. Understanding the stress response at the organismal and cellular levels is essential to identify sensitive and effective stress biomarkers which can inform the development of targeted intervention strategies to mitigate stress. This review provides a comprehensive overview of the physiological changes that occur in crustaceans under stress, including hormonal, metabolic, hematological, hydromineral, and phenotypic alterations. By synthesizing current knowledge, this article aims to bridge existing gaps and provide insights into the stress response mechanisms, paving the way for advancements in crustacean health management. Full article

Immigrant households frequently face liquidity constraints upon arrival, which potentially hinders their long-term economic integration. The Family Investment Hypothesis (FIH) suggests that couples may respond to these constraints by coordinating their labor supply: one spouse works to finance the other’s investment in local human capital. Previous studies have tested the FIH by comparing married immigrants to married natives, attributing differences in outcomes to financial constraints. However, this approach may conflate such constraints with other inherent differences between immigrants and natives. This paper introduces a novel identification strategy that compares the differences in labor market outcomes of married and single immigrants to those of their native-born counterparts, allowing for better isolation of the effects of liquidity. Applying this strategy to repeated cross-sectional data on immigrants from the Former Soviet Union who arrived in Israel during the 1990s, the analysis finds no supporting evidence for the FIH. One possible explanation for this finding is the substantial government support extended to these immigrants, which may have mitigated their financial constraints. Alternatively, the results may indicate that immigrant households do not systematically adjust their labor supply in accordance with the FIH framework. These findings highlight the importance of the institutional context in shaping household labor supply decisions. Full article

In the current era, when civilizations are in constant conflict and humankind is facing a series of serious existential crises, there is an urgent need for universal love to unite humankind. As models of world religions, Christianity and Buddhism provide rich intellectual resources for the construction of such universal love. Regarding Thomistic Christianity, its philosophy of friendship has gradually achieved a dual transformation from virtue-oriented to love-oriented, and from God-centered to human-centered. In the case of Mahayana Buddhism, its philosophy of friendship has evolved with the “Humanistic Buddhism” movement, increasingly demonstrating a compassionate spirit of saving the world. By comparing Thomistic Christianity with Mahayana Buddhism, we can see that although they exhibit different models of friendship, their main developmental trends are consistent. Both are committed to demonstrating a human-centered model of friendship, both emphasize the value of self-reduction in friendship, and both demonstrate the unique and irreplaceable role of religion in friendship. The goal of the philosophy of friendship is universal love and harmonious development of civilizations, while its future development depends on the joint efforts of contemporary religious scholars and philosophers. Full article

According to Victor Ernest Shelford’s ‘Law of Tolerance,’ organisms within ecosystems thrive optimally when environmental conditions are favorable. Applying this principle to ecosystems and agro-ecosystems facing water scarcity or environmental challenges can significantly enhance their productivity. In these ecosystems, phytocenosis adjusts its conditions by utilizing water with varying salinity levels. Moreover, establishing optimal drinking water conditions for human populations within an ecosystem can help mitigate future negative succession processes. The purpose of this study is to evaluate the quality of two distinct water sources in the Amudarya district of the Republic of Karakalpakstan, Uzbekistan: collector-drainage water and groundwater at depths of 10 to 25 m. This research is highly relevant in the context of climate change, as improper management of water salinity, particularly in collector-drainage water, may exacerbate soil salinization and degrade drinking water quality. The primary methodology of this study is as follows: The Food and Agriculture Organization of the United Nations (FAO) standard for collector-drainage water is applied, and the water quality index is assessed using the CCME WQI model. The Canadian Council of Ministers of the Environment (CCME) model is adapted to assess groundwater quality using Uzbekistan’s national drinking water quality standards. The results of two years of collected data, i.e., 2021 and 2023, show that the water quality index of collector-drainage water indicates that it has limited potential for use as secondary water for the irrigation of sensitive crops and has been classified as ‘Poor’. As a result, salinity increased by 8.33% by 2023. In contrast, groundwater quality was rated as ‘Fair’ in 2021, showing a slight deterioration by 2023. Moreover, a comparative analysis of CCME WQI values for collector-drainage and groundwater in the region, in conjunction with findings from Ethiopia, India, Iraq, and Turkey, indicates a consistent decline in water quality, primarily due to agriculture and various other anthropogenic pollution sources, underscoring the critical need for sustainable water resource management. This study highlights the need to use organic fertilizers in agriculture to protect drinking water quality, improve crop yields, and promote soil health, while reducing reliance on chemical inputs. Furthermore, adopting WQI models under changing climatic conditions can improve agricultural productivity, enhance groundwater quality, and provide better environmental monitoring systems. Full article