Search Results (3,892)

Based on niche theory, this study pioneered the application of the niche state-role model, suitability model, subgroup model, and overlap model in evaluating small-town communities, integrating both their endowment attributes and relational attributes. Taking Pingshan County, Hebei Province, China, as a case study, it revealed the evolution patterns of suburban small-town communities from 2000 to 2020. The results indicated significant changes in the comprehensive niche indices and rankings of small-town communities, though top-ranking towns remained relatively stable. Niche indices varied from dimensions, primarily manifesting a binary opposition between natural and humanistic factors. The overall suitability of small-town communities showed little change, but internal disparities gradually narrowed. The niche subgroups of small-town communities displayed a gradient distribution pattern: ecological functions significantly strengthened in the west of the county; population and economy functions continuously intensified in southeastern towns; while central-region towns maintained intermediate levels. Regarding niche overlap based on population and economy flows, the overall competitive intensity of small-town communities weakened, but competition among central region towns intensified. Regarding niche overlap based on ecology flows, the overall competitive intensity strengthened, with particularly notable changes in the central and eastern regions. Moreover, the spatial evolution of county-level small towns exhibited scale-dependent differences: while the macro-scale pattern remained relatively stable, the micro-scale pattern underwent significant changes, with the driving force gradually shifting from local endowments to factor flows. Full article

Poor diet is the leading preventable risk factor for death worldwide, associated with over 10 million premature deaths and USD 8 trillion related costs every year. Artificial intelligence or AI is rapidly emerging as the most historically disruptive, innovatively dynamic, rapidly scaled, cost-efficient, and economically productive technology (which is increasingly providing transformative countermeasures to these negative health trends, especially in low- and middle-income countries (LMICs) and underserved communities which bear the greatest burden from them). Yet widespread confusion persists among healthcare systems and policymakers on how to best identify, integrate, and evolve the safe, trusted, effective, affordable, and equitable AI solutions that are right for their communities, especially in public health nutrition. We therefore provide here the first known global, comprehensive, and actionable narrative review of the state of the art of AI-accelerated nutrition assessment and healthy eating for healthcare systems, generated by the first automated end-to-end empirical index for responsible health AI readiness and maturity: the Responsible Health AI readiness and Maturity Index (RHAMI). The index is built and the analysis and review conducted by a multi-national team spanning the Global North and South, consisting of front-line clinicians, ethicists, engineers, executives, administrators, public health practitioners, and policymakers. RHAMI analysis identified the top-performing healthcare systems and their nutrition AI, along with leading use cases including multimodal edge AI nutrition assessments as ambient intelligence, the strategic scaling of practical embedded precision nutrition platforms, and sovereign swarm agentic AI social networks for sustainable healthy diets. This index-based review is meant to facilitate standardized, continuous, automated, and real-time multi-disciplinary and multi-dimensional strategic planning, implementation, and optimization of AI capabilities and functionalities worldwide, aligned with healthcare systems’ strategic objectives, practical constraints, and local cultural values. The ultimate strategic objectives of the RHAMI’s application for AI-accelerated public health nutrition are to improve population health, financial efficiency, and societal equity through the global cooperation of the public and private sectors stretching across the Global North and South. Full article

Invasive insects increasingly threaten ecosystems worldwide, with wetlands especially vulnerable to unpredictable climate. Phragmites australis is a dominant plant species in Louisiana’s Mississippi River Delta and a critically important component of the wetland ecosystem. However, the invasive scale insect, Nipponaclerda biwakoensis, has contributed to large-scale dieback of this foundation species, jeopardizing erosion control, water filtration, and wildlife habitat. Despite rapid regional spread, the fine-scale dispersal of N. biwakoensis within host plants remains poorly understood. We examined whether the crawler-stage of N. biwakoensis scales preferentially settled on the bottom or top sections of P. australis stems, and whether plant nutritional and/or defensive traits shaped this preference. In field surveys, scale densities varied along the length of P. australis stems, with gravid females occurring 3.5× more frequently at the stem base than at the top; parasitism rates were similarly elevated, reaching 12× higher at the base. To evaluate potential drivers of this pattern, we quantified carbon, nitrogen, water, and phenolic content in lower and upper stem tissues and conducted complementary laboratory assays to test crawler settlement preferences. Under controlled conditions, crawlers settled most densely on middle stem sections, with lower densities at the base and the fewest near the top. The basal sections also contained 50% less nitrogen and 47% lower phenolic concentrations compared to the upper stem. The divergence in crawler settlement patterns between field and controlled conditions likely reflects the influence of additional environmental factors present in the field—such as habitat structure, microclimate, and natural enemies—that are absent or minimized in laboratory conditions. By applying a trait-based approach to insect dispersal, we link plant functional traits to N. biwakoensis crawler settlement patterns, strengthening our understanding of of insect distribution and guiding predictions of long-term dispersal in N. biwakoensis. Full article

The objective of the next POI recommendation is using the historical check-in sequences of users to learn the preferences and habits of users, providing a list of POIs that users will be inclined to visit next. Then, there are some limitations in existing POI recommendation algorithms. On the one hand, after obtaining the user’s preferences for the current period, if we consider the entire historical check-in sequence, including future check-in information, it is susceptible to the influence of noisy data, thereby reducing the accuracy of recommendations. On the other hand, the current methods generally rely on modeling long- and short-term preferences within a fixed time window, which possibly leads to an inability to capture users’ behavior characteristics at different time scales. As a result, we proposed a Multimodal Temporal Fusion for Next POI Recommendation(MTFNR). Firstly, to understand users’ preferences and habits at different periods, multiple hypergraph neural networks are constructed to analyze user behavior patterns at different stages, and in order to avoid introducing interference factors, only the check-in sequences visited in the current period are considered to reduce the impact of noise on the model’s recommendation performance. Secondly, modeling the next POI recommendation task through the fusion of time information and long- and short-term preferences in order to gain a more comprehensive understanding of users’ preferences and habits, enhance the timeliness of recommendations, and improve the accuracy of recommendations. Lastly, introducing spatio-temporal interval information into the GRU model, capturing dependencies in sequences to improve the overall performance of the model. Extensive experiments on the real LBSN datasets demonstrated the superior performance of the MTFNR model. The experimental results indicate that Top-10 recall improved 2.81% to 15.97% compared to current methods. Full article

Bacterial blight in rice, caused by Xanthomonas oryzae pv. oryzae (Xoo), poses a serious threat to global rice production. The ability of Xoo to form biofilms is a key factor for its virulence. The OryR protein is a LuxR-type quorum-sensing regulator essential for biofilm formation and Xoo pathogenicity. However, the three-dimensional structure of OryR remains poorly understood. This study integrates homology modeling, molecular dynamics (MD) simulations, and virtual screening to elucidate the structure of OryR and identify potential inhibitors that target its ligand-binding domain. MD simulations confirmed the structural stability of OryR, and comparative analysis with experimentally determined structures of ligand- or inhibitor-bound homologs revealed a binding site in OryR with a distinct hourglass-like shape for long-range contacts. Virtual screening of over 200,000 compounds from four chemical libraries identified several promising inhibitor candidates, with the top compounds showing strong binding energies in both molecular mechanics-generalized Born surface area (−68.3 kcal/mol) and molecular mechanics Poisson–Boltzmann surface area (−19.3 kcal/mol) calculations. Overall, this study provides insights into the OryR structure and highlights potential inhibitors that can be developed as novel agents to control bacterial blight. However, additional experimental validations are required to refine and optimize these leads for drug development. Full article

Against the backdrop of accelerating global energy transition, China, as the world’s largest energy producer and consumer, has a crucial impact on achieving carbon neutrality goals through the green development of its power industry. Green total factor productivity is an important indicator for measuring the green development of the power industry. Utilizing provincial panel data from 30 regions in China covering the period 2012–2023, using MATLAB R2021a software, this study firstly measures the static GTFP of China’s power industry using a Super-Efficiency Slack-Based Measure (SBM) model incorporating undesirable outputs. Subsequently, the dynamic GTFP is measured and analyzed using the Global Malmquist–Luenberger (GML) index model. The model decomposes GTFP change to examine the contributions of technical efficiency change and technological progress. The findings reveal that (1) the static GTFP of China’s provincial power industry is generally low, with significant regional disparities, with Jiangsu, Yunnan, Beijing, Zhejiang and Sichuan ranking among the top five nationally; (2) the average GTFPs in eastern and western China are higher than in the central region. Overall, the GTFP of China’s power industry exhibits an upward trend, which is primarily driven by technological progress. Based on these conclusions, the study proposes policy recommendations to enhance the power industry’s GTFP, which can offer theoretical insights for facilitating its green transition and sustainable development. Full article

Environmental factors motivate migration across the globe, calling for better planning. Although the US experienced such movements during the COVID-19 pandemic, literature on population mobility and outcomes for receiving communities in the US is scarce. We use a mixed-methods case study approach to explore the COVID-era population movement trends in the US Northeast (NE) Region and their outcomes for receiving communities to draw lessons for strategic regional planning aiming to achieve sustainable and equitable outcomes of disaster-induced movements. Utilizing the Statistics of Income data and focus group data collected from 27 local experts in 22 rural counties of NE, which experienced the highest relative numbers of in-movers between 2016 and 2020, the findings revealed the top receiving counties were predominantly rural areas where urbanites moved from within NE. This movement challenged the housing market and services, disproportionately burdening socioeconomically disadvantaged groups in receiving communities. The COVID-19 experience opened a window of opportunity for regional planning to prepare desirable outcomes of such mobilities by addressing existing issues in receiving communities while incorporating pulse and slow population movements into the agenda. The right policy timing and communication among communities are keys to building trust and ensuring integration of newcomers into receiving communities. Full article

As global climate change intensifies, research on low-carbon practices has become a critical component of sustainable tourism development. The carbon emission profile of ski tourism differs significantly from other tourism sectors. Ski resorts have a mountainous terrain and typically maintain relatively high levels of vegetation, endowing them with inherent advantages for pioneering low-carbon and sustainable tourism practices. However, the substantial energy demands associated with artificial snowmaking systems and advanced infrastructure pose significant challenges to reducing carbon emissions in ski resort operations. This study gathers first-hand data on sustainable tourism development in the Chongli ski resort—the region that hosted the 2022 Winter Olympics—through field investigations and interviews with key industry stakeholders. It develops a comprehensive framework accounting for carbon emissions in ski resorts by integrating input–output analysis with enterprise-level data, focusing on four core operational sectors: catering, skiing, wholesale and retail, and leasing and business services. Furthermore, this study examines the coupling relationship between carbon emissions and operating revenue. Using correlation and regression analyses, this study identifies the key drivers of carbon emissions across these operational departments within the ski tourism sector. The results indicate that carbon emissions from these four sectors in the Chongli ski resort exhibit periodic fluctuations with an overall upward trend year by year. Nevertheless, progress in low-carbon development is evident, suggesting that the resort is on a trajectory toward achieving peak carbon emissions and eventual carbon neutrality. The inclusion of natural endowments, market-scale effects, festival and special events, and capital investment in ski tourism collectively serve as crucial drivers for low-carbon sustainability in Chongli. Based on these findings, this study proposes targeted recommendations to support low-carbon sustainable development, offering scientific insights for similar Winter Olympics host cities. This study integrates top-down input–output analysis with bottom-up enterprise data, taking Chongli, the host city of the Winter Olympics, as a timely case study. It constructs a four-dimensional low-carbon development model based on the identification of key natural, social, and economic driving factors, and strengthens the reliability of the conclusion by relying on first-hand field research and operator interview data. Our study provides an analysis of methodological innovation, framework integrity, and solid empirical evidence that accounts for micro-scale carbon emissions in ski resorts. Full article

Nature bonding (NB), alongside place identity and place dependence, is among the most frequently discussed and empirically validated contributing factors of place attachment (PA) within urban environments. While PA has been extensively studied through its psychological, personal, and spatial dimensions, the specific contribution of NB across these dimensions and spatial scales remains insufficiently understood. To address this gap, this study aims to demonstrate the importance of NB in fostering PA by highlighting the need for spatially sensitive urban planning that integrates natural elements across scales to enhance community satisfaction and well-being. Elmwood Village in Buffalo, New York, recognized as one of the top ten most livable American neighborhoods and part of the historic Frederick Law Olmsted-designed parkway system was chosen as a case study. A three-stage investigation was conducted using survey data. First, the three dimensions of PA—place, person, and psychology—were identified. Second, NB was categorized into three levels: attachment, enjoyment, and oneness with nature. Third, the variability of these bonds across three spatial scales—building, street, and neighborhood—was tested to assess their spatial relevance. The findings reveal that the strength and form of NB differ significantly across spatial contexts, shaping how individuals emotionally and behaviorally connect to urban places. By integrating NB into the spatial understanding of PA, this research provides a framework for urban designers and environmental psychologists to better interpret and enhance human–nature relations in the built environment. Full article

This study explores the potential of Precision Agriculture (PA) to optimize top-dressing nitrogen (N) fertilization in rainfed barley under drought conditions in Central Catalonia (Spain). Efficient N management is critical in Mediterranean dryland winter cereal systems, where water scarcity and environmental regulations limit fertilization strategies. Two plots (2.93 ha and 1.80 ha) were zoned using soil apparent electrical conductivity (ECa) and elevation data obtained with the VERIS 3100 ECa soil surveyor. An on-farm experimental design tested four N dose rates (0 kg N/ha, 32 kg N/ha, 64 kg N/ha, and 96 kg N/ha) across two management zones per plot. Yield data were collected using a combine harvester equipped with a yield monitor and were mapped using geostatistical methods. A linear model (ANOVA) was used to analyze barley yield (kg/ha at 13% moisture), with nitrogen rate and soil zone (management class) as explanatory factors. Results showed low average yields (~1200 kg/ha–1300 kg/ha) due to severe water stress during the 2022–2023 season. Non-fertilized plots (N0) and those receiving moderate (N64) or high fertilization (N96) achieved the best performance, with the latter likely enhancing crop N uptake during the post-stress recovery period. In contrast, low fertilization (N32) proved less effective. Marginal return analysis supported variable-rate N application only in one plot, whereas under drought conditions, a no-fertilization strategy proved more suitable in the other. Ultimately, additional trials conducted under more favourable climatic scenarios are necessary to assess and validate the effectiveness of Precision Agriculture-based fertilization strategies in rainfed barley. Full article

Public health emergencies (PHEs) test the crisis response capacity of grassroots organizations like China’s Residential Committees (RCs). While existing research attributes this capacity to factors like resource mobilization or state-society relations, its deeper structural foundations in land regimes and spatial configurations remain underexplored, particularly in Global South urbanization contexts. To fill this gap, this study develops a “Grassroots Organizational Capacity” (GOC) analytical framework, which disaggregates capacity into four dimensions: information, implementation, mobilization and cooperation, and coercion. We then employ this framework in a comparative case study of urban (Jiayi) and rural (Hedong) neighbourhoods in Nanhai, China, during the 2022 lockdown. Drawing on semi-structured interviews with ten key stakeholders in 2022, the findings reveal divergent types of governance. In the rural case, collective land ownership and open spaces foster an “Embedded Autonomy” type, enabling a proactive response through dense social networks. In the urban case, state land dependency and spatial fragmentation lead to a “Reactive Co-Governance” type, which relies on top-down state intervention. This study’s contribution is to provide a case-based illustration of how land and space structures are actively associated with grassroots crisis response effectiveness, rather than serving as passive backdrops. Full article

To address the issues of high energy consumption and high carbon emissions associated with the steam injection development of ultra-heavy oil in China, technological exploration focusing on electrical heating and solvent substitution was conducted. Firstly, experiments on the heat transfer and temperature rise characteristics in the near-wellbore formation via electrical heating revealed its feasibility. Considering that ultra-heavy oil reservoirs in China suitable for Steam-Assisted Gravity Drainage (SAGD) have already been converted to SAGD production, and considering the certain safety risks of solvent extraction, a development strategy of SAGD—Electrical Heating Solvent Extraction—SAGD was formulated. A multi-stage drainage theoretical model coupling SAGD with electrical heating solvent extraction was established. The similarity criteria for 3D-scaled physical simulation of electrical-heating-assisted production were derived. Through three-stage (SAGD—Electrical Heating Solvent Extraction—SAGD) scaled physical simulation experiments, the development performance of converting a SAGD-developed reservoir to thermal solvent extraction was analyzed. Results indicate that the higher the oil content in the electrically heated wellbore and nearby formation, the faster the heat transfer rate. This confirmed the decision to conduct experiments on electrical-heating-assisted solvent extraction (without steam injection) in SAGD-developed reservoirs. After the SAGD steam chamber reaches the top, switching to electrical heating solvent extraction results in a drainage zone along the flanks of the horizontal section comprising: a high-temperature zone of vaporized solvent from electrical heating, a medium-low temperature oil dissolution zone from the solvent, and an untouched zone. Along the horizontal section, it is divided into a solvent chamber rising zone, a slow expansion zone, and a rapid expansion zone. Experiments confirmed that electrical heating can vaporize the solvent, continuously expanding the drainage chamber scale. Furthermore, the solvent continues to function in the subsequent SAGD stage, increasing the recovery factor from 64.4% to 71.2%, an improvement of 6.9%. The established multi-stage coupled drainage theoretical model, compared with experimental and analytical calculations, showed an overall agreement rate of 95.3%, and can be used for production prediction in electrical-heating-assisted solvent extraction composite recovery. Full article

This study investigates how stakeholder pressures (SSTPR) prompt SMEs to perform green innovation (GRNI) activities by grounding the analysis exclusively in stakeholder theory. It employs a survey questionnaire to gather information from 141 top- and mid-level executives working in various SME manufacturing firms (listed in DSE, CSE, foreign SMEs) in Bangladesh. The structural equation modeling (SEM) technique is used to analyze data and test hypotheses. The study’s findings reveal that SSTPR, both primary and secondary, have a significant positive impact on the firm’s degree of GRNI. Moreover, it has also been found that environmental commitment (ENVC) has a positive moderating effect on the relation between stakeholder influences and GRNI. On the other hand, environmental ethics (ENVE) has a partial mediation impact on this relationship. The results shed light on the crucial role of stakeholder influence, ENVC, and ENVE in promoting GRNI behavior. These findings will fill knowledge gaps on the factors that drive SMEs’ investments in GRNIs with insightful implications for regulators, managers, and policymakers. This study also assists Bangladesh’s sustainable agenda by bolstering green and sustainable innovation activities. Full article

Biochar has gained significant attention as a multifunctional material linking biomass energy technologies with sustainable agriculture, providing combined benefits in soil improvement, waste valorization, and climate mitigation. This review examines biochar within the context of thermochemical conversion processes—pyrolysis, gasification, and torrefaction—and summarizes the operational parameters that influence both energy yields and biochar quality. It synthesizes agronomic, environmental, and engineering research to explain the mechanisms through which biochar enhances soil structure, nutrient retention, water availability, microbial activity, and carbon stability. The review also assesses its role as a long-term carbon sink and its potential integration into negative-emission systems such as bioenergy with carbon capture and storage (BECCS). However, the way that biomass conversion factors concurrently influence energy performance, biochar physicochemical quality, and its agronomic and climate-mitigation consequences across many environmental contexts is rarely integrated into a unified analytical framework in current evaluations. To close that gap, this review identifies cross-cutting patterns, trade-offs, and uncertainties while methodically integrating the information on the co-behavior of various aspects. Circular economy initiatives, carbon markets, and rural development are mentioned as key potential. On the other hand, economic variability, variable performance across soil types, lack of regulatory harmonization, rivalry for biomass, and logistical limits are big hurdles. Standardized production techniques, long-term field research, life cycle and techno-economic evaluations, and integrated system design are among the top research priorities. Overall, the evidence suggests that biochar is a promising tool for creating resilient and low-carbon agriculture and energy systems, provided that scientific, technological, and governance advancements are coordinated. Full article

In many traditional villages in China, substantial government investment has been directed toward reconstructing public spaces for tourism development. Yet, many of these newly built spaces remain underused, revealing a persistent mismatch between top–down planning and villagers’ everyday needs. To address this gap, this study employs a mixed-methods approach to evaluate the quality of rural public spaces. Drawing on a systematic review, a four-dimensional assessment model—encompassing environmental, social, cultural, and economic attributes—was developed and operationalized through 17 specific indicators. The model was applied to three traditional villages in Chongqing, Southwest China, using field observation, questionnaire surveys, confirmatory factor analysis, and semi-structured interviews. The findings show that while environmental and cultural qualities are generally appreciated, villagers’ overall evaluations are strongly shaped by livelihood considerations and the extent to which public spaces support everyday practices. In tourism-oriented villages, public spaces often function primarily as attractions rather than as sites of daily life, limiting their social usefulness despite significant investment. The results demonstrate that economic indicators, which are often overlooked in existing studies, are essential for assessing the quality of public space in traditional villages and for strengthening community engagement. These insights contribute to a more comprehensive understanding of rural public space and offer practical guidance for rural revitalization and community-based planning. Full article