Search Results (49)

Tea cultivation faces significant threats from red spider mite (RSM: Oligonychus coffeae) infestations, which reduce yields and economic viability in major tea-producing regions. Current automated detection methods rely on supervised deep learning models requiring extensive labeled data, limiting scalability for smallholder farmers. This article proposes AIM-Net (AI-based Infestation Mapping Network) by evaluating SwAV (Swapping Assignments between Views), a self-supervised learning framework, for classifying RSM infestation severity (Mild, Moderate, Severe) using a geo-referenced, field-acquired dataset of RSM infested tea-leaves, Cam-RSM. The methodology combines SwAV pre-training on unlabeled data with fine-tuning on labeled subsets, employing multi-crop augmentation and online clustering to learn discriminative features without full supervision. Comparative analysis against a fully supervised ResNet-50 baseline utilized 5-fold cross-validation, assessing accuracy, F1-scores, and computational efficiency. Results demonstrate SwAV’s superiority, achieving 98.7% overall accuracy (vs. 92.1% for ResNet-50) and macro-average F1-scores of 98.3% across classes, with a 62% reduction in labeled data requirements. The model showed particular strength in Mild_RSM-class detection (F1-score: 98.5%) and computational efficiency, enabling deployment on edge devices. Statistical validation confirmed significant improvements (p < 0.001) over baseline approaches. These findings establish self-supervised learning as a transformative tool for precision pest management, offering resource-efficient solutions for early infestation detection while maintaining high accuracy. Full article

As a catalyst for sustainable urbanization, urban vibrancy drives human interactions, economic agglomeration, and resilient development through its spatial manifestation of diverse activities. While previous studies have emphasized the connection between built environment features—especially street network centrality—and urban vibrancy, the broader mechanisms through which the full spectrum of street configuration dimensions shape vibrancy patterns remain insufficiently examined. To address this gap, this study applies a GeoXAI approach that synergizes random forest modeling and GeoShapley interpretation to reveal the influence of street configuration on urban vibrancy. Leveraging multi-source geospatial data from Xiamen Island, China, we operationalize urban vibrancy through a composite index derived from three-dimensional proxies: life service review density, social media check-in intensity, and mobile device user concentration. Street configuration is quantified through a tripartite measurement system encompassing network centrality, detour ratio, and shape index. Our findings indicate that (1) street network centrality and shape index, as well as their interactions with location, emerge as the dominant influencing factors; (2) The relationships between street configuration and urban vibrancy are predominantly nonlinear, exhibiting clear threshold effects; (3) The impact of street configuration is spatially heterogeneous, as evidenced by geographically varying coefficients. The findings can enlighten urban planning and design by providing a basis for the development of nuanced criteria and context-sensitive interventions to foster vibrant urban environments. Full article

In Europe and elsewhere in the world, current ambitious decarbonization targets push towards a gradual decommissioning of all fossil-fuel-based dispatchable electrical generation and, at the same time, foster a gradual increase in the penetration of Renewable Energy Sources (RES). Moreover, considerations tied to decarbonization as well as to the security of supply, following recent geo-political events, call for a gradual replacement of gas appliances with electricity-based ones. As RES generation is characterized by a variable generation pattern and as the electric carrier is characterized by scarce intrinsic flexibility, and since storage capabilities through electrochemical batteries, as well as demand-side flexibility contributions, remain rather limited, it is quite natural to think of other energy carriers as possible service providers for the electricity system. Gas and heat networks and, in the future, hydrogen networks could provide storage services for the electricity system. This could allow increasing the amount of RES penetration to be managed safely by the electric system without incurring blackouts and avoiding non-economically motivated grid reinforcements to prevent the curtailment of RES generation peaks. What is explained above calls for a new approach, both in electricity network dispatch simulations and in grid-planning studies, which extends the simulation domain to other carriers (i.e., gas, heat, hydrogen) so that a global optimal solution is found. This simulation branch, called multi-energy or multi-carrier, has been gaining momentum in recent years. The present paper aims at describing the most important approaches to static ME modeling by comparing the pros and cons of all of them with a holistic approach. The style of this paper is that of a tutorial aimed at providing some guidance and a few bibliographic references to those who are interested in approaching this theme in the next years. Full article

This study aimed to determine the characteristics and driving factors of spatial evolution in urban historical areas during urbanization and urban renewal and recommend how to protect these areas. The urban historical district of Zhangye, a famous historical and cultural city in China, was chosen as the study area. The research used a land transfer matrix, spatial design network analysis (sDNA), GIS analysis, and relevant statistical methods. It analyzed the spatial evolution characteristics of the district by considering the transformation of land use, the evolution of road networks, and the renewal of building profiles. GeoDetector was used to explore the effects of the factors. The study found that in the district, commercial and business land increased while industrial, manufacturing, logistics, and warehouse land decreased. The evolution speed at each stage had a wave-like development. The street pattern maintained the basic “cross” shape, with continuous improvements in the road system and overall accessibility. The building volume also increased gradually. The main types of architectural renewal included setback, integration, demolition, and addition. Meanwhile, economic and industrial factors had the most significant influence on the renewal of the district, whereas cultural factors had increasing influence. Finally, the dual-factor effects were more significant than the single-factor impacts. Full article

What is the impact of geopolitics on the geometry of global trade? What is the key structural role that led to the emergence of the US–China trade bipolarity? Here, we study the geometry of international trade, taking into account not only the direct but also the indirect trade relations. We consider the self-weight of each country as an indicator of its intrinsic robustness to exogenous shocks. We assess the vulnerability of a country to potential demand or supply shocks based on the entropy (diversification) of its trade flows. By considering the indirect trade relations, we found that the key structural role that led to the emergence of the US–China trade bipolarity is that of the intermediary hub that acts as a “bridge” between different trade clusters. The US and China occupied key network positions of high betweenness centrality as early as 2010. As international trade was increasingly dependent on only these two intermediary trade hubs, this fact led to geopolitical tensions such as the US–China trade war. Therefore, betweenness centrality could serve as a structural indicator, forewarning of possible upcoming geopolitical tensions. The US–China trade bipolarity is also strongly present in self-weights, where a race in terms of their intrinsic robustness to exogenous shocks is more than evident. It is also interesting that the US and China are not only the top shock spreaders but also the most susceptible to shocks. However, China can act more as a shock spreader than a shock receiver, while for the USA, the opposite is true. Regarding the impact of geopolitics, we found that the Russia–Ukraine conflict forced Ukraine to diversify both its exports and imports, aiming to lower its vulnerability to possible shocks. Finally, we found that international trade is becoming increasingly oligopolistic, even when indirect trade relationships are taken into account, thus indicating that a “Deep Oligopoly” has formed. Full article

The Napo Sumaco Aspiring UNESCO Global Geopark (NSAUGG) in Ecuador represents a genuine variety of geological, cultural, and natural heritage, which aims to promote sustainable development through geotourism. This study describes the significance of NSAUGG, emphasizing its geological diversity which includes a variety of geosites, and focusing on three recently annexed geosites: the Wawa Sumaco Quarry, Puka Urku, and the Pucuno River, where geological analyses, including petrographic and mineralogical assessments, were conducted. To enhance community engagement and educational outreach, a multi-platform mobile application, “SumAppGeo”, was developed using ArcGIS and Flutterflow. This application serves as an interactive tool for visitors and local communities, providing detailed geological information, interactive maps, and educational content. The findings reveal the presence of significant geological features, such as haüyne-bearing alkaline rocks, which indicate specific volcanic activity in this region and are an element of geodiversity, validating the Wawa Sumaco Quarry, Puka Urku, and the Pucuno River as geosites. The implementation of SumAppGeo aims to foster a deeper understanding of the region’s geodiversity while promoting responsible tourism practices. This initiative not only supports the recognition of NSAUGG as part of the UNESCO Global Geoparks Network but also contributes to the socio-economic development of local communities through sustainable tourism practices. Full article

This paper explores the feasibility of floating urban development in Italy, given its extensive coastline and inland hydrographic network. The key drivers for floating urban development, as an adaptive approach in low-lying waterfront areas, include the increasing threats posed by rising sea levels and flooding and the shortage of land for urban expansion. However, as not all waterfront areas are suitable for floating urban development, a geographical analysis based on a thorough evaluation of multiple factors, including urban–economic parameters and climate-related variables, led to the identification of a specific area of the Lazio coast, the river Tiber Delta. A comprehensive urban mapping process provided a multifaceted geo-referenced information layer, including several climatic, urban, anthropic, and environmental parameters. Within the GIS environment, it is possible to extract and perform statistical analyses crucial for assessing the impact of flood and sea-level rise hazards, particularly regarding buildings and land cover. This process provides a robust framework for understanding the spatial dimensions of flood and sea-level rise impacts and supporting informed design-making. A research-by-design phase follows the simulation research and mapping process. Several design scenarios are developed aimed at regenerating this vulnerable area. These scenarios seek to transform its susceptibility to flooding into a resilient, adaptive, urban identity, offering climate-resilient housing solutions for a population currently residing in unauthorized, substandard housing within high flood-risk zones. This paper proposes a comprehensive analytical methodology for supporting the design process of floating urban development, given the highly determinant role of site-specificity in such a challenging and new urban development approach. Full article

The electrification of mobility has introduced considerable challenges to distribution networks due to varying demand patterns in both time and location. This underscores the need for adaptable tools to support strategic investments, grid reinforcement, and infrastructure deployment. In this context, the present study employs real-world datasets to propose a comprehensive spatial–temporal energy model that integrates a traffic model and geo-referenced data to realistically evaluate the flexibility potential embedded in the light-duty transportation sector for a given study region. The methodology involves assessing traffic patterns, evaluating the grid impact of EV charging processes, and extending the analysis to flexibility services, particularly in providing primary and tertiary reserves. The analysis is geographically confined to the Lombardy region in Italy, relying on a national survey of 8.2 million trips on a typical day. Given a target EV penetration equal to 2.5%, corresponding to approximately 200,000 EVs in the region, flexibility bands for both services are calculated and economically evaluated. Within the modeled framework, power-intensive services demonstrated significant economic value, constituting over 80% of the entire potential revenues. Considering European markets, the average marginal benefit for each EV owner is in the order of 10 € per year, but revenues could be higher for sub-classes of users better fitting the network needs. Full article

Building resilient infrastructure is at the core of sustainable development, as evidenced by the UN Sustainable Development Goal 9. In fact, the effective operation of road networks is crucial and strategic for the smooth functioning of a nation’s economy. This is also fundamental from a sustainability perspective, as efficient transportation networks reduce traffic, and thus, their environmental impact. However, road networks are constantly at risk of traffic closure and/or limitations due to a plurality of natural hazards. These environmental stressors, among other factors like aging and degradation of structural materials, negatively affect the disaster resilience of both single components and the system of road networks. However, the estimation of such resilience indices requires a broad multidisciplinary vision. In this work, a framework for application to large road networks is delineated. In the proposed methodology, seismic hazard is considered, and its corresponding impacts on road networks are evaluated. The assessment encompasses not only the road network system (including squares, roads, bridges, and viaducts) but also the buildings that are located in the urban area and interact with the network. In this context, the probability that buildings will suffer seismic-induced collapse and produce partial or total obstruction of roads is considered. This scheme is designed for implementation in different geographical contexts using geo-referenced data that include information about specific risks and alternative rerouting options. The proposed methodology is expected to support the mitigation of functionality loss in road networks after disasters, contributing to both the economic and social dimensions of sustainability. To evaluate the methodology, two case studies focusing specifically on hospital-to-hospital connections were conducted in Naples and Turin, Italy. However, the proposed approach is versatile and can be extended to other critical infrastructures, such as theatres, stadiums, and educational facilities. Full article

Muscle growth stands as a pivotal economic trait within pig production, governed by a complex interplay of multiple genes, each playing a role in its quantitative manifestation. Understanding the intricate regulatory mechanisms of porcine muscle development is crucial for enhancing both pork yield and quality. This study used the GSE99749 dataset downloaded from the GEO database, conducting a detailed analysis of the RNA-seq results from the longissimus dorsi muscle (LD) of Tibetan pigs (TP), Wujin pigs (WJ) and large white pigs (LW) at 60 days of gestation, representing diverse body sizes and growth rates. Comparative analyses between TPvsWJ and TPvsLW, along with differential gene expression (DEG) analysis, functional enrichment analysis, and protein–protein interaction (PPI) network analysis, revealed 1048 and 1157 significantly differentially expressed genes (p < 0.001) in TPvsWJ and TPvsLW, respectively. With stricter screening criteria, 37 DEGs were found to overlap between the 2 groups. PPI analysis identified MYL5, MYL4, and ACTC1 as the three core genes. This article focuses on exploring the MYL4 gene. Molecular-level experimental validation, through overexpression and interference of the MYL4 gene combined with EDU staining experiments, demonstrated that overexpression of MYL4 significantly promoted the proliferation of porcine skeletal muscle satellite cells (PSMSC), while interference with MYL4 inhibited their proliferation. Furthermore, by examining the effects of overexpressing and interfering with the MYL4 gene on the muscle hypertrophy marker Fst gene and the muscle degradation marker FOXO3 gene, the pivotal role of the MYL4 gene in promoting muscle growth and preventing muscle degradation was further confirmed. These findings offer a new perspective on the molecular mechanisms behind porcine muscle growth and development, furnishing valuable data and insights for muscle biology research. Full article

Given the effect of urbanization on land use and the allocation and implementation of urban green spaces, this paper attempts to analyze the distribution and accessibility of public parks in India’s Bengaluru city (previously known as Bangalore). Availability, accessibility, and utilization—the key measures of Urban Green Spaces (UGS)—are mostly used in health research and policy and are important components of Planetary Health Equity in the context of studying UGSs and health. A geo-spatial method was used for mapping the park’s distribution and measuring its accessibility, using road network data. To understand equitable access to the parks, four socio-economic parameters—population density, the percentage of the population below 6 years of age, the proxy wealth index, and scheduled caste population—were correlated with the parks’ accessibility. This spatial distribution revealed that 19 of 198 wards did not have a single park and that 36 wards only had one park. About 25–29% of wards did not have accessibility to neighborhood-level and community-level parks within a 400–800 m distance. These parks must be accessible within a walking distance of 400–800 m but were found to most likely be inaccessible on the periphery of the city where the population density is low and the children population is high, in comparison to the central part of the city. Similarly, parks were found to be inaccessible in the eastern part of the city where the scheduled caste population is high and also found to be inaccessible for the low-income neighborhoods residing in the western part and southern periphery of the city, indicating the uneven distribution of and inequitable access to public parks. Our study proposes a reshaping of both neighborhood parks and community parks in an attempt to look beyond biodiversity, through the planetary health equity approach, by noting that, while biodiversity indirectly has a positive effect on health, public parks should not only be considered as advancing environmental sustainability and climate resilience, but also as improving the health and wellbeing of the population. Affirmative action in terms of the availability of public parks with adequate area requirements and essential services at a neighborhood scale is required to redress the inequity of access; in addition, the accessibility of parks must be considered important during urban planning. Full article

Satellite communications systems provide a means to connect people and devices in hard-to-reach locations. Traditional geostationary orbit (GEO) satellite systems and low Earth orbit (LEO) constellations, having their own strengths and weaknesses, have been used as separate systems serving different markets and customers. In this article, we analyze how satellite systems in different orbits could be integrated together and used as a multi-layer satellite system (MLSS) to improve communication services. The optimization concerns combining the strengths of different layers that include a larger coverage area as one moves up by each layer of altitude and a shorter delay as one moves down by each layer of altitude. We review the current literature and market estimates and use the information to provide a thorough assessment of the economic, regulatory, and technological enablers of the MLSS. We define the MLSS concept and the architecture and describe our testbed and the simulation tools used as a comprehensive engineering proof-of-concept. The validation results confirm that the MLSS approach can intelligently exploit the smaller jitter of GEO and shorter delay of LEO connections, and it can increase the availability and resilience of communication services. As a main conclusion, we can say that multi-layered networks and the integration of satellite and terrestrial segments seem very promising candidates for future 6G systems. Full article

The Renewable Energy Directive II introduces renewable energy communities, enhancing energy sharing. However, many existing initiatives, focussing only on electricity, overlook the substantial energy demand in building sector comprising residential and commercial spaces. Energy communities in this sector can leverage district heating and cooling technology for thermal energy sharing, contributing to carbon neutrality by enhancing efficiency and reducing primary energy usage. Advanced strategies such as integrating renewables into heating and cooling grids, sector coupling, and utilising waste heat are key in moving away from fossil fuels. The Campania Region (Italy), abundant in geothermal energy potential, chose a district in which to implement the GeoGRID system. This innovative setup combines a four-pipe district heating and cooling network with an Organic Rankine Cycle plant, tapping into geothermal energy from the Solfatara area. The geothermal fluid’s heat feeds the ORC evaporator and then powers the thermal network, allowing direct heating and domestic hot water supply during winter. A thorough techno-economic analysis assessed the energy potential extractable from the geothermal fluid. Crucial aspects of this study are the evaluation of the energy and environmental efficiency of the system within the renewable energy community framework. Additionally, the paper introduces a methodology applicable for assessing geothermal energy communities on a global scale. Full article

Long-term exposure to high concentrations of fine particles can cause irreversible damage to people’s health. Therefore, it is of extreme significance to conduct large-scale continuous spatial fine particulate matter (PM_2.5) concentration prediction for air pollution prevention and control in China. The distribution of PM_2.5 ground monitoring stations in China is uneven with a larger number of stations in southeastern China, while the number of ground monitoring sites is also insufficient for air quality control. Remote sensing technology can obtain information quickly and macroscopically. Therefore, it is possible to predict PM_2.5 concentration based on multi-source remote sensing data. Our study took China as the research area, using the Pearson correlation coefficient and GeoDetector to select auxiliary variables. In addition, a long short-term memory neural network and random forest regression model were established for PM_2.5 concentration estimation. We finally selected the random forest regression model (R² = 0.93, RMSE = 4.59 μg m⁻³) as our prediction model by the model evaluation index. The PM_2.5 concentration distribution across China in 2021 was estimated, and then the influence factors of high-value regions were explored. It is clear that PM_2.5 concentration is not only related to the local geographical and meteorological conditions, but also closely related to economic and social development. Full article

The Yellow River Basin is an important energy base and economic belt in China, but its water resources are scarce, its ecology is fragile, and the task of achieving the goal of carbon peak and carbon neutrality is arduous. Carbon compensation potential can also be used to study the path to achieving carbon neutrality, which can clarify the potential of one region’s carbon sink surplus to be compensated to the other areas. Still, there needs to be more research on the carbon compensation potential of the Yellow River Basin. Therefore, this study calculated the carbon compensation potential using the β convergence test and parameter comparison method. With the help of spatial measurement tools such as GIS, GeoDa, Stata, and social network analysis methods, the spatiotemporal pattern and network structure of the carbon compensation potential in the Yellow River Basin were studied from the perspective of urban agglomeration. The results demonstrate the following: (1) The overall carbon compensation rate of the YRB showed a downward trend from 2005 to 2019, falling by 0.94, and the specific pattern was “high in the northwest and low in the southeast”. The spatial distribution is roughly spread along the east–west axis, and the distribution axis and the center of gravity keep shifting to the northwest. It also showed a weak divergence and a bifurcation trend. (2) The carbon compensation rate in the YRB passed the spatial correlation and β convergence tests, demonstrating the existence of spatial correlation and a “catch-up effect” among cities. (3) The overall distribution pattern of the carbon compensation potential in the YRB is a “low in the west and high in the east” pattern, and its value increased by 8.86% during the sampled period. (4) The network correlation of carbon compensation potential in the YRB has been significantly enhanced, with the downstream region being more connected than the upstream region. (5) The Shandong Peninsula Urban Agglomeration has the largest network center, followed by the Central Plains Urban Agglomeration, and the Ningxia along the Yellow River Urban Agglomeration has the fewest linked conduction paths. According to the research results, accurate and efficient planning and development suggestions are proposed for urban agglomeration in the Yellow River Basin. Full article