Hasil untuk "Rural industries"

Fei DAI, Yaru XU, Yun WANG et al.

ObjectiveAgainst the backdrop of China’s ecological civilization construction and comprehensive green transition, the national strategy of “synergistic promotion of carbon reduction, pollution reduction, greening expansion, and growth” has become a core policy orientation. How to foster effective synergies among these four objectives—carbon reduction, pollution reduction, greening expansion, and growth—have consequently emerged as a key research agenda across multiple disciplines. As the primary research object of landscape architecture, green space constitutes a crucial spatial carrier for “greening expansion” and offers a distinctive spatial planning and design perspective for simultaneously advancing carbon reduction, pollution mitigation, and high-quality development. This study aims to clarify the policy evolution, disciplinary research patterns, and spatial mechanisms underlying such synergies, and to explore how landscape architecture can contribute more systematically to this national strategic framework.MethodsThe study first reviews major national policies issued since 2005 that relate to carbon reduction, pollution control, ecological conservation, greening expansion, and green growth. It outlines their advancement pathways, summarizes evolving objectives and conceptual connotations, and identifies linkage mechanisms among “carbon reduction, pollution reduction, greening expansion, and growth”. Second, based on literature statistics and disciplinary mapping, the study examines publication trends and disciplinary distribution of collaborative research focusing on different combinations of these four goals, thereby revealing the dominant paradigms and existing gaps. Third, from the standpoint of landscape architecture, it analyzes how different forms and configurations of “greening expansion” can be leveraged to achieve synergistic improvements across carbon reduction, pollution mitigation, and economic growth, with particular attention to spatial characteristics, ecological processes, socioeconomic feedbacks, and the translation of scientific findings into planning, design, and management strategies.Results1) The relationships among carbon reduction, pollution reduction, greening expansion, and growth are strongly shaped by successive rounds of policy guidance. With the institutionalization of ecological civilization and the proposal of the “dual carbon” targets, policy documents have gradually shifted from sectoral management to integrated, cross-sectoral governance. During 2022−2025, China has entered a stage of deepening policy coordination, in where the four targets are no longer pursued in isolation but are embedded in systematic frameworks for territorial spatial planning, environmental management, and industrial restructuring. 2) As of 2025, the academic literature still focuses predominantly on pairwise synergies: carbon reduction−growth, pollution reduction−growth, greening expansion−carbon reduction, greening expansion−pollution reduction, greening expansion−growth, and carbon reduction−pollution reduction. Studies simultaneously addressing three or more objectives remain relatively scarce. Publications are heavily concentrated in environmental science and engineering, energy and climate studies, economics, and public policy. These works are largely driven by top-down policy agendas and oriented toward macro-level assessment, scenario simulation, and policy evaluation. In contrast, there is a clear deficiency of research within human settlement and built environment disciplines—including landscape architecture, urban and rural planning, and architecture—that take spatial localization, spatial configuration, and site-scale intervention as core entry points. 3) From the perspective of landscape architecture, existing studies primarily focus on how the spatial characteristics of green spaces—such as area and scale, type composition, landscape pattern, connectivity, configuration, and functional zoning—affect carbon sequestration, pollutant removal, microclimate regulation, and socio-economic benefits. These studies translate such relationships into principles that inform green space planning, design, and management. Current evidence demonstrates that “greening expansion” can effectively contribute to carbon reduction (e.g., through vegetation carbon sinks, reduced building energy consumption, and promotion of low-carbon mobility), pollution reduction (e.g., through air and water purification, noise mitigation, runoff regulation, and alleviation of urban heat islands), and growth (e.g., through enhancement of property values, attraction of investment, promotion of recreation and tourism, improvement of public health, and support for green industries and employment).ConclusionIt is necessary to further strengthen multidimensional synergy research led by “greening expansion” under the disciplinary framework of landscape architecture, with spatial planning and design as a primary leverage. Future work should move beyond isolated pairwise relationships and pay greater attention to multi-objective coupling mechanisms that integrate carbon reduction, pollution control, ecosystem restoration, and high-quality development. Specifically, green space planning should be more closely aligned with the hierarchical management requirements of territorial spatial planning, coordinating national, regional, urban-rural, and site-specific scales. Taking synergistic carbon and pollution reduction, as well as integrated “carbon reduction-pollution reduction-growth” goals, as core targets, research should develop systematic strategies for green space planning, design, and management that cover multiple spatial levels, including “urban−rural systems, space types, plots”. This implies establishing quantitative indicators and spatial configuration guidelines for different categories of green space; embedding ecosystem service optimization, low-carbon transition objectives, and environmental health considerations into zoning, layout, and design codes; and strengthening adaptive management based on continuous monitoring, performance assessment, and feedback adjustment. By leveraging the spatial carrier function of green spaces and integrating ecological, social, and economic objectives coordinated, landscape architecture can play a pivotal role in realizing the synergy of carbon reduction, pollution mitigation, greening expansion, and sustainable growth, providing spatial solutions, design pathways, and technical support for national strategies on ecological civilization and comprehensive green transformation.

Viralkumar B. Mandaliya

BackgroundBamboo is a strategic resource for poverty alleviation, rural growth, ecological restoration, sustainable jobs, and industrial innovations. The function of bamboo goes beyond conventional uses and extends to the international policy reformation toward sustainable transitions. Its alignment with the United Nations Sustainable Development Goals (SDG) has been increasingly recognized.AimThis article aimed to assess bamboo for qualitative and quantitative attainment of the 169 targets of the 17 goals of the UN SDG Framework.MethodologyThe qualitative assessment was classified into three grades: high, medium, and low. The quantitative assessment examined the individual 169 targets on a scale of 1–10.Key findingsThe average percent score (APS) from the qualitative assessment of bamboo was ranked and graded for SDGs 1–17 into five major groups: group A—with APS above 50%, targets achieved (SDGs 7, 13, 1, 11, and 9); group B—with APS 40%–50%, challenges remain (SDGs 12, 6, 15, and 2); group C—with APS 30%–40%, significant challenges (SDGs 4, 5, 8, and 10); group D—with APS 15%–30%, major challenges (SDGs 17, 14, and 3); and group E—with APS below 15%, not achieved (SDG 16). Subsequently, quantitative assessment of each of the 169 UN SDG target achieved by bamboo showed that 45 targets achieved the highest scale of 8–10, 35 medium (on a scale of 4–7), 25 low (on a scale of 1–3), and 64 no connection (on a scale of 0). The highest score of 10 was shown for four targets, i.e., 8.4 (efficiency of resources and circular production), 9.2 (green industrialization, composites, and textiles), 11.6 (minimize city environmental footprint and waste), and 15.3 (land degradation neutrality through revegetation and biochar).Case studies and policy implicationsThis article further delved into case studies on bamboo for sustainability from nine countries. Based on these case studies, we derived a seven-point policy intervention integrating the UN SDG Framework for bamboo as the green gold of ecosystems.ConclusionsIn a nutshell, this article could be the first of its kind to quantify the 169 targets for bamboo on a scale of 1–10. This article provides a comprehensive review for policymakers, industries, and researchers for the integration of bamboo into climate-resilient strategies aligned with global sustainability goals.

Till Koebe, Emmanuel Letouzé, Tuba Bircan et al.

The paper titled ''Global gridded population datasets systematically underrepresent rural population'' by Josias Láng-Ritter et al. provides a valuable contribution to the discourse on the accuracy of global population datasets, particularly in rural areas. We recognize the efforts put into this research and appreciate its contribution to the field. However, we feel that key claims in the study are overly bold, not properly backed by evidence and lack a cautious and nuanced discussion. We hope these points will be taken into account in future discussions and refinements of population estimation methodologies. We argue that the reported bias figures are less caused by actual undercounting of rural populations, but more so by contestable methodological decisions and the historic misallocation of (gridded) population estimates on the local level.

Iris Hordijk, Lourens Poorter, Jingjing Liang et al.

Abstract Species’ traits and environmental conditions determine the abundance of tree species across the globe. The extent to which traits of dominant and rare tree species differ remains untested across a broad environmental range, limiting our understanding of how species traits and the environment shape forest functional composition. We use a global dataset of tree composition of >22,000 forest plots and 11 traits of 1663 tree species to ask how locally dominant and rare species differ in their trait values, and how these differences are driven by climatic gradients in temperature and water availability in forest biomes across the globe. We find three consistent trait differences between locally dominant and rare species across all biomes; dominant species are taller, have softer wood and higher loading on the multivariate stem strategy axis (related to narrow tracheids and thick bark). The difference between traits of dominant and rare species is more strongly driven by temperature compared to water availability, as temperature might affect a larger number of traits. Therefore, climate change driven global temperature rise may have a strong effect on trait differences between dominant and rare tree species and may lead to changes in species abundances and therefore strong community reassembly.

Nadjemat El Houda Issaad, Ismail Lotfi, Mohamed Senouci et al.

Rural healthcare faces numerous challenges, including limited access to specialized medical services and diagnostic equipment, which delays patient care. Enhancing the ability to transmit medical images and data from rural areas to urban hospitals via wireless networks is critical. However, bandwidth limitations, unreliable networks, and concerns over data security and privacy hinder efficient transmission. Additionally, the high data volume of medical content and the limited battery life of IoT devices pose further challenges. To address these challenges, data compression techniques such as Autoencoders (AEs) offer promising solutions by significantly reducing the communication overhead without sacrificing essential image quality or details. Additionally, spectrum allocation mechanisms in rural areas are often inefficient, leading to poor resource utilization. Auction theory presents a dynamic and adaptive approach to optimize spectrum allocation. This paper proposes a novel hybrid framework that integrates AE-based data compression with auction-based spectrum allocation, addressing both communication efficiency and spectrum utilization in rural wireless networks. Extensive simulations validate the framework's ability to improve spectrum utilization, transmission efficiency, and overall connectivity, offering a practical solution for enhancing rural telemedicine infrastructure.

Isabel Copsey, Quentin Hanley, Jack Sutton

Road traffic accidents remain a major public health challenge worldwide, with urbanisation and population density identified as key factors influencing risk. This study analyses monthly accident data from 2009 to 2023 across 632 parliamentary constituencies in England, Wales, and Scotland, using an area-normalised approach based on population density. Segmented power law models consistently identified breakpoints separating sublinear rural from superlinear urban scaling behaviours. Seasonal variation in scaling exponents was pronounced in rural regions but less evident in urban ones. Fourier-based cross-spectral analysis of yearly cycles revealed systematic phase shifts: rural exponents lagged pre-exponential factors by 4.5 months, while urban exponents were 2.7 months out of phase, producing a 5.3 month shift between rural and urban exponents. These findings highlight the importance of pre-exponentials-defined as the expected density of accidents at unit population density-as comparable descaled metrics, revealing both long-term national declines and recurring seasonal peaks. Notably, the phase offsets suggest structurally distinct causes of rural and urban accident risk, with urban regions exhibiting increasing acceleration in accident scaling, potentially linked to growth in vehicle numbers, size, and weight. Residuals, modelled with the Type I Generalised Logistic Distribution (GLD), captured skewness and heterogeneity more effectively than normal assumptions. Geospatial mapping highlighted persistent urban hotspots alongside rural and coastal constituencies with systematically lower accident densities than predicted. Together, these findings advance understanding of how density and urbanisation shape accident risk and provide evidence to support more targeted road safety interventions and policy planning.

Ziyuan Gao

While frameworks such as the WHO Age-Friendly Cities have advanced urban aging policy, rural contexts demand fundamentally different analytical approaches. The spatial dispersion, terrain variability, and agricultural labor dependencies that characterize rural aging experiences require moving beyond service-domain frameworks toward spatial stress assessment models. Current research on rural aging in China exhibits methodological gaps, systematically underrepresenting the spatial stressors that older adults face daily, including terrain barriers, infrastructure limitations, climate exposure, and agricultural labor burdens. Existing rural revitalization policies emphasize standardized interventions while inadequately addressing spatial heterogeneity and the spatially-differentiated needs of aging populations. This study developed a GIS-based spatial stress analysis framework that applies Lawton and Nahemow's competence-press model to quantify aging-related stressors and classify rural villages by intervention needs. Using data from 27 villages in Mamuchi Township, Shandong Province, we established four spatial stress indicators: slope gradient index (SGI), solar radiation exposure index (SREI), walkability index (WI), and agricultural intensity index (AII). Analysis of variance and hierarchical clustering revealed significant variation in spatial pressures across villages and identified distinct typologies that require targeted intervention strategies. The framework produces both quantitative stress measurements for individual villages and a classification system that groups villages with similar stress patterns, providing planners and policymakers with practical tools for designing spatially-targeted age-friendly interventions in rural China and similar contexts.

Sabab Al Farabi

This research presents a novel framework that combines traditional Optical Time-Domain Reflectometer (OTDR) signal analysis with machine learning to localize and classify fiber optic faults in rural broadband infrastructures. The proposed system addresses a critical need in the expansion of middle-mile and last-mile networks, particularly in regions targeted by the U.S. Broadband Equity, Access, and Deployment (BEAD) Program. By enhancing fault diagnosis through a predictive, AI-based model, this work enables proactive network maintenance in low-resource environments. Experimental evaluations using a controlled fiber testbed and synthetic datasets simulating rural network conditions demonstrate that the proposed method significantly improves detection accuracy and reduces false positives compared to conventional thresholding techniques. The solution offers a scalable, field-deployable tool for technicians and ISPs engaged in rural broadband deployment.

Pavel Malinovskiy

We propose an integrated architecture combining Software-Defined Wireless Mesh Networks (SDWMN), Direct-to-Mobile (D2M) broadcasting, and Kafka-based hybrid cloud streaming to improve wireless network performance in both urban and rural settings. The approach addresses urban congestion and rural digital exclusion through traffic offloading, enhanced fault tolerance, and equitable resource allocation. We model urban congestion $ρ_u = λ_t / μ_c$ and rural coverage deficit $δ_r = 1 - C_r / C_{req}$, and aim to minimize global performance loss $GPL = w_1 \cdot ρ_u + w_2 \cdot δ_r + w_3 \cdot T_{rec}$, where $T_{rec}$ is recovery time. Experiments in Bangkok, Mumbai, and rural Finland demonstrate latency reduction over 32%, bandwidth offloading of 40%, rural coverage gain of 28%, and fairness index rising from 0.78 to 0.91. The system achieves recovery under 10 s using SDWMN and Kafka. We recommend optimal spectrum allocation $α_s$, targeted subsidies, and device mandates to promote adoption. This scalable, fault-tolerant design supports equitable digital transformation and suggests directions for future research.

Yandiswa Mtimkulu, Muinat N. Lewu, Azwimbavhi R. Mulidzi et al.

Background: Pelargonium sidoides (P. sidoides) DC. (Geraniaceae) is one of several geophytic species of the genus that are important traditional medicines in South Africa. P. sidoides has been identified as a potential future economic species known to cure various ailments, including respiratory infections. Aim: This review was aimed at addressing concerns around the overexploitation of P. sidoides in the wild. Setting: This review provides an overview of P. sidoides cultivation and usage. Method: A comprehensive literature search involving mainly electronic and library sources of information was used to collate and synthesise published data. Results: According to the findings of the study, there has been a huge increase in demand for the plant and it has been overexploited locally as a result of increased domestic and global demand from native consumers and the pharmaceutical industries. Conclusion: The review emphasises the necessity of cultivation in ensuring the sustainability of P. sidoides in the wild. Cultivation is a crucial component of conservation attempts which is under threat because of increasing urbanisation, habitat degradation, and population growth. Furthermore, producing medicinal plants allows new rural farmers to produce them as a new crop option, reducing unsustainable wild collection and competition with established commercial farmers who mostly raise food crops. Lastly, the study reveals the benefits in cultivating medicinal plants namely the strengthening of primary healthcare through traditional medicine, the preservation of indigenous knowledge, local economic growth, and job creation. Contribution: The benefits of cultivation and using P. sidoides medicinally are reviewed in this essay.

Yun Shen, Ghulam Raza Sargani, Rui Wang et al.

China’s urban–rural dichotomy has resulted in a widening gap between urban and rural areas, posing significant challenges to rural development. This study aims to investigate the spatio-temporal differentiation and driving mechanisms of rural industry integration within the Chengdu–Chongqing Economic Circle in China. Using panel data from 2011 to 2020, we employed the entropy weight TOPSIS method to construct a comprehensive index that charts the evolution of rural industry integration across various districts and counties. Additionally, we utilized fixed-effect and spatio-temporally weighted regression models to analyze the underlying driving forces behind this integration. Our findings reveal a dynamic and varied landscape of rural industry integration, with different levels of depth and breadth across various subsystems. Spatially, we observed a transition from a dispersed to a more concentrated agglomeration pattern within the Chengdu–Chongqing Economic Circle. This shift suggests a diffusion effect emanating from core metropolitan areas, as well as an attracting force exerted by adjacent metropolitan circles. In terms of drivers, market demand, openness level, financial development, policy support, and agricultural insurance breadth significantly contribute to rural industry integration. However, technological progress and rural human capital exhibit a weaker correlation. Notably, our models identified pronounced spatial–temporal heterogeneity among these influencing factors, highlighting a nuanced and dynamic relationship between them. Overall, our study emphasizes the crucial role of rural industry integration in bridging the urban–rural divide and fostering sustainable agricultural development and rural revitalization. The insights gained from this research provide valuable guidance for policymakers and stakeholders seeking to optimize rural development strategies and unlock the potential of integrated rural industries.

Neena Albarus, J’Anna-Mare Lue, Erin Kerrison et al.

Jamaica is an island nation with a history that is informed by Taino settlement, European colonisation, chattel slavery, disinvestment, and continued extractivism. This perspective paper leverages a historical analysis to explore environmental injustices affecting the health and quality of life of Jamaicans living in Jamaica. This article hopes to contribute to a growing but limited body of scholarly research that contends with environmental and climate justice in the context of the Caribbean. In discussing a lack of critical environmental infrastructure, such as reliable solid waste management, and the impacts of extractive industries, such as bauxite mining, the paper intends to highlight the environmental, public health, and social harms that are produced. Employing an intersectional approach grounded in Black feminist epistemology put forward by Patricia Hill Collins, the authors use their lived experiences as a source of knowledge. The paper analyses how these environmental injustices harm Jamaican communities at large but underscores the compounded challenges faced by Jamaican women who experience marginalisation on the basis of gender, urban/rural residency, and class. The paper concludes by urging researchers, policymakers, regulatory bodies, and other stakeholders to conduct further research and create sustainable and equitable environmental standards that have considerations for environmental injustice in Jamaica.

Pawan Kumar, Gagan Matta, Amit Kumar et al.

The Ramganga River basin, comprising three rivers, the Dhela, Dhandi, and Ramganga, plays a vital role in groundwater recharge, sustaining numerous industries, urban areas, and rural communities reliant on these rivers for daily activities. The study’s primary purpose was to analyze the groundwater quality in the context of potability, irrigation, and health risks to the local inhabitants of the Ramganga River basin. In 2021–2022, 52 samples (26 × 2) were collected from 13 locations in two different seasons, i.e., pre-monsoon and post-monsoon, and 20 physico-chemical and heavy metal and metalloids were analyzed using the standard protocols. The result shows that heavy metal and metalloids and metalloid concentrations of Zn (0.309–1.787 and 0.613–1.633); Fe (0.290–0.965 and 0.253–1.720), Cd (0.001–0.002 and 0.001–0.002); As (0.001–0.002 and 0.001–0.002), Cr (0.009–0.027 and 0.011–0.029), and Pb (−0.001–0.010 and 0.00–0.010) values in mg/L are present in both seasons. The groundwater quality index (GWQI), heavy metal pollution Index (HPI), and heavy metal evaluation index (HEI) were used to assess the water quality and metal pollution in the basin area. As per GWQI values, water quality lies from excellent water quality (41.639 and 43.091) to good water quality (56.326 and 53.902); as per HPI values, it shows good (29.51 and 30.03) to poor quality (60.26 and 59.75) and HEI values show the low-level contamination (1.03–2.57 and 1.13–3.37) of heavy metal and metalloids in both seasons. According to the potential health risk assessment, infants show low risk in pre-monsoon and low risk to medium post-monsoon, while children and adults show low risk to high risk in both seasons. From the health risk perspective, it shows that children and adults have more concerns about non-carcinogenic effects, so adequate remedial measures and treatment are required to avoid the groundwater quality of the Ramganga River basin.

Fatemeh Shafiee, Mahdiye Esmaeili, Mojtaba Sookhtanlou

Extended Abstract Background: Today, medicinal plants play a vital role in health, creating employment, and economic development. Despite paying attention to the development of medicinal plant cultivation in Mazandaran province in recent years, resulting in employment creation in rural communities and the reduction of migration, farmers in rural areas are facing challenges to cultivate these plants and employment in this field. Furthermore, the unemployment rate index in this county is higher than the country and the province. Therefore, this research aimed to analyze employment challenges and obstacles in the field of medicinal plants in North Svadkuh County, Mazandaran province. Methods: In this survey with a quantitative approach, the statistical population consisted of the farmers in North Savadkuh county of Mazandaran province, and 204 farmers were selected using Daniel's formula and simple random sampling. The data collection tool was a questionnaire, and its content validity was confirmed by a group of horticultural, extensional, and educational experts. In addition, Cronbach's alpha coefficient was used to determine its reliability with an appropriate value (0.7-0.9). Moreover, 175 out of 204 distributed questionnaires were returned to the researchers. Data were analyzed using SPSSV26 software. Results: The findings in the descriptive statistics section showed that most of the farmers (64.6%) were men, mostly with a bachelor’s educational level (37.1%), and their main occupation was agriculture for the majority of the farmers (60.6%). In total, four factors were identified based on the results of exploratory factor analysis on 15 variables of the farmers facing challenges and obstacles in Northern Svadkuh county, Mazandaran province. These factors include skill-logistic factors (17.749%), harvesting and postharvest stage problems, lack of good stories for harvested medicinal plants, damage to the product due to improper handling, and the absence of harvesting machines for medicinal plants in the region, extension-infrastructural factors (17.493%), planting, growing, harvesting, and postharvest stages problems, inattention to medicinal plant cultivation capacity in the region by policymakers, the absence of experts and specialists of medicinal plants in the Agricultural Jihad Organization of the city, the absence of model farms for medicinal plants in the region, limited extension training and classes-farmer field school (FFS), and lack of proper mechanization in the planting, growing, harvesting, and processing of medicinal plants. The rest of the factors include processing industries-marketing factors (16.735%) postharvest stage problems, raw sales and non-processing of medicinal plant products, the absence of medicinal plant packaging companies in the region, the problem of sending raw medicinal plants to other cities, traditional use (without processing) of most medicinal plants in the region, the absence of foreign market and export of medicinal plant products, technical knowledge and information factors (10.983%), growing stage problems, limited knowledge of experts and farmers in the non-chemical control of weeds and diseases of medicinal plant in the region, and farmers' unfamiliarity with the water requirements of medicinal plants). Conclusion: According to the results, the main challenges of farmers for employment in the field of medicinal plants are skills and logistics, extension and infrastructure problems, and transformation and marketing industries of these plants. Thus, it is suggested to teach the skills of harvesting medicinal plants to the farmers and rural youth of the region by holding educational-extension classes. Besides, policymakers, executives, and planners are suggested to pay more attention to the creation of employment in rural areas, which is achieved through the cultivation of these plants, considering the conditions of the province and the capabilities of the Northern Svadkuh County in the production of medicinal plants. It is suggested to try in every district center, especially in the central and eastern regions of the province, which are susceptible to the cultivation of medicinal plants according to the document of the province. The presence of one or more experts with expertise in medicinal plants and proficiency in educational-extension methods should be facilitated to train farmers to promote employment and increase the cultivated area of the mentioned plants. The farmers should be trained in a practical and individual or group form by using suitable extension methods such as result and method demonstrations, a model site, and holding the FFS. In addition, it is possible to provide suitable tools and mechanization in all production stages of medicinal plants for the farmers of the region. The next suggestions are to create processing and packaging industries by providing low-interest and long-term facilities in the region, empowering farmers in terms of knowledge and skills regarding the marketing and processing of medicinal plant products, creating permanent and seasonal markets for direct sales, guaranteed purchase of products, facilitating domestic shipping to different provinces, paying attention to exports, and removing obstacles to international exports. The last suggestion is that a revision is necessary for the training courses of Agricultural Jihad experts of the county and the region, as well as agricultural students. The training should be changed from the theoretical presentation of topics, information, and knowledge into practical and field activities that lead to gaining more experience.

Agasthya Gangavarapu, Ananya Gangavarapu

Since the onset of COVID-19, rural communities worldwide have faced significant challenges in accessing healthcare due to the migration of experienced medical professionals to urban centers. Semi-trained caregivers, such as Community Health Workers (CHWs) and Registered Medical Practitioners (RMPs), have stepped in to fill this gap, but often lack formal training. This paper proposes an advanced agentic medical assistant system designed to improve healthcare delivery in rural areas by utilizing Large Language Models (LLMs) and agentic approaches. The system is composed of five crucial components: translation, medical complexity assessment, expert network integration, final medical advice generation, and response simplification. Our innovative framework ensures context-sensitive, adaptive, and reliable medical assistance, capable of clinical triaging, diagnostics, and identifying cases requiring specialist intervention. The system is designed to handle cultural nuances and varying literacy levels, providing clear and actionable medical advice in local languages. Evaluation results using the MedQA, PubMedQA, and JAMA datasets demonstrate that this integrated approach significantly enhances the effectiveness of rural healthcare workers, making healthcare more accessible and understandable for underserved populations. All code and supplemental materials associated with the paper and IMAS are available at https://github.com/uheal/imas.

Yadira Sanchez Benitez

I present an open-source, ecologically integrated model for rural connectivity, merging the location of nodes mesh networks with renewable energy systems. Employing evolutionary algorithms, this approach optimizes node placement for internet access and symbiotic energy distribution. This model, grounded in community collaboration, demonstrates a balance between technological advancement and environmental stewardship, offering a blueprint for sustainable infrastructure in similar rural settings.

S. Goel, Renu Sharma

Shengfeng Xie, Caimin Jin, Ting Song et al.

Digital finance provides a long-tail mechanism for alleviating relative poverty caused by unequal opportunities and rights. According to the inference of an improved Cobb-Douglas production function and Ramsey-Cass-Koopmans two-stage household consumption model, the long-tail mechanism for digital finance to alleviate the relative poverty of farmers includes productive investment mechanism, credit mechanism, financial asset allocation and entrepreneurial mechanism. An empirical analysis of 11,519 rural households across China based on CHFS2019 data shows that digital finance can significantly and steadily alleviate relative poverty by improving credit availability and promoting household entrepreneurship, while its effect on increasing productive investment opportunities and optimizing financial asset allocation is less certain. Therefore, it is necessary to continue to improve the "blood making" long tail mechanism of digital finance for farmers' credit and innovation and entrepreneurship, and at the same time guide the digital finance to empower the development of rural industries to increase farmers' productive investment opportunities, cultivate endogenous growth momentum, and improve the wealth allocation function of rural digital financial market.

Mengyao Guo, Xiaolin Zhang, Yuan Zhuang et al.

This paper explores using generative AI and aesthetics to promote cultural creativity in rural China amidst COVID-19's impact. Through literature reviews, case studies, surveys, and text analysis, it examines art and technology applications in rural contexts and identifies key challenges. The study finds artworks often fail to resonate locally, while reliance on external artists limits sustainability. Hence, nurturing grassroots "artist villagers" through AI is proposed. Our approach involves training machine learning on subjective aesthetics to generate culturally relevant content. Interactive AI media can also boost tourism while preserving heritage. This pioneering research puts forth original perspectives on the intersection of AI and aesthetics to invigorate rural culture. It advocates holistic integration of technology and emphasizes AI's potential as a creative enabler versus replacement. Ultimately, it lays the groundwork for further exploration of leveraging AI innovations to empower rural communities. This timely study contributes to growing interest in emerging technologies to address critical issues facing rural China.

P. Das, Manashjyoti Mili