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Remote sensing thematic data products are critical for assessing and analyzing geological environments, while efficient generation of thematic products is also highly significant for achieving corresponding sustainable development goals (SDGs). Currently, remote sensing thematic product generation has problems like low levels of automation and efficiency. Addressing these challenges is imperative for advancing sustainable development within the geological environment. This paper aims to address issues related to the generation of geological environment remote sensing thematic products, sorting through the overall process of remote sensing thematic product generation, exploring algorithm encapsulation, combination, and execution under technical methods for container and workflow, and relies on the Spark distributed processing architecture to achieve efficient thematic product generation supported by multiple geological environment data processing models. Finally, taking the three SDGs of SDG6, SDG11, and SDG15 as examples, we achieved the generation of a variety of thematic products such as the interpretation of water body distribution, extraction of urban informal settlements and distribution of water and soil erosion. Meanwhile, we comparatively analyzed the efficiency of thematic product generation on different processing architectures, and the experimental results further verified the feasibility and effectiveness of our proposed solution. This research provides a programme for the automated and intelligent generation of geological environment remote sensing thematic products and effectively assists the construction of sustainable development in the geological environment. [ABSTRACT FROM AUTHOR]

Evaluating the vulnerability of urban transportation systems to flood disasters can provide scientific support for urban disaster prevention and mitigation. Current methods for assessing the flood vulnerability of urban roads often overlook the internal relationships within the complex spatial composition of road networks and surface structures. In this study, based on the theory of complex networks, a dual-layer network assessment model is established for evaluating the flood vulnerability of urban transportation systems by coupling basic geographic data with road network vector data. Unlike traditional methods, this model considers the complex relationship between road network structures and ground surfaces, uncovering a correlation between road network structure and road flood vulnerability. By utilizing this model, the flood vulnerability of road networks in Shenzhen, as well as the city's spatial flood vulnerability, are quantitatively assessed. Based on the quantitative results, we create maps illustrating the distribution of road and spatial flood vulnerability in Shenzhen. The study results reflect that roads highly vulnerable to flooding are mainly located in the central urban area of the southwest, with the flood vulnerability spatially concentrated primarily in the northern and western regions. Using data from government reports, news stories, and other sources over the past five years, we compile recorded instances of urban waterlogging. The quantitative results of the model are consistent with the distribution trend in recorded waterlogging points, indicating that the model's outcomes are authentic and reliable. [ABSTRACT FROM AUTHOR]

Coastal cities are increasingly vulnerable to urban storm surge hazards and the secondary hazards they cause (e.g., coastal flooding). Accurate representation of the spatio-temporal process of hazard event development is essential for effective emergency response. However, current knowledge graph representations face the challenge of integrating multi-source information with various spatial and temporal scales. To address this challenge, we propose a new information model for storm surge hazard events, involving a two-step process. First, a hazard event ontology is designed to model the components and hierarchical relationships of hazard event information. Second, we utilize multi-scale time segment integer coding and geographical coordinate subdividing grid coding to create a spatio-temporal framework, for modeling spatio-temporal features and spatio-temporal relationships. Using the 2018 typhoon Mangkhut storm surge event in Shenzhen as a case study and the hazard event information model as a schema layer, a storm surge event knowledge graph is constructed, demonstrating the integration and formal representation of heterogeneous hazard event information and enabling the fast retrieval of disasters in a given spatial or temporal range. [ABSTRACT FROM AUTHOR]

Cooperation among tourist attractions has encouraged a new form of competition among tourist destinations. Regional tourism cooperation can create win–win scenarios for participating tourist destinations, such as complementary advantages and improved comprehensive competitiveness. This study constructed a competitiveness measurement model and evaluated the competitiveness of tourist attractions. The index variables were set to modify and establish the gravity models (GMs). The cooperation network was established using Ucinet 6.0 software, and the competitive value of the tourist attractions and the structure characteristics of the network were analyzed. The results indicate that the competitiveness of tourist attractions in Jiangsu Province and Zhejiang Province is strong, while that of attractions in Anhui Province and Shanghai is weak. Tourist attractions in Shanghai, Suzhou, and Hangzhou have strong gravity for cooperation. Furthermore, the density of the cooperation network is high. The core members of the network are mainly distributed in the eastern region of the YRD and play a core role in the tourism cooperation therein. The cooperation network can be divided into four subgroups at level 2 and seven subgroups at level 3. The conclusions of this study can help the government formulate more targeted regional tourism cooperation policies. [ABSTRACT FROM AUTHOR]

Brain diseases remain a significant global healthcare burden. Conventional pharmacological therapy for brain diseases encounters huge challenges because of the blood–brain barrier (BBB) limiting the delivery of therapeutics into the brain parenchyma. To address this issue, researchers have explored various types of drug delivery systems. Cells and cell derivatives have attracted increasing interest as "Trojan horse" delivery systems for brain diseases, owing to their superior biocompatibility, low immunogenicity, and BBB penetration properties. This review provided an overview of recent advancements in cell- and cell-derivative-based delivery systems for the diagnosis and treatment of brain diseases. Additionally, it discussed the challenges and potential solutions for clinical translation. [ABSTRACT FROM AUTHOR]

Tourism experiences bring about physical or psychological feelings in tourists, which can not only leave tourists with deep memories, but also affect their behavioral intentions. Tourism experiences are meaningful only if they can be remembered and influence word of mouth and decision making. A better understanding of what influences tourism experience memory will help optimize the supply and further development of tourism destinations. This study explores the antecedents of rural tourism experience memory from the tourism supply perspective, revealing the mechanism of effect of these antecedents on tourists' tourism experience memory formation through a questionnaire-based survey of 556 participants in Xidi Village, China, and correlation and multiple regression analyses. The results show that perceptions about the supply of rural tourism destinations trigger positive emotions that, in turn, affect the formation of rural tourism experience memory. Through the mediating role of positive emotions, there is a significant correlation between perception of rural tourism destination supply and the formation of rural tourism experience memories. [ABSTRACT FROM AUTHOR]

With the development of global economic integration and the gradual formation of unified tourism markets, strengthening regional tourism cooperation has become an internal requirement of regional tourism development but also a new way of sustainably developing tourism. This study selected the key factors affecting the cooperation of tourist attractions, including the competitiveness of tourist attractions and the relationships among tourist attractions, and established an evaluation index system and mathematical model of tourist attractions' cooperation. Furthermore, the level of cooperation was evaluated. According to the value of the cooperation level, the spatial characteristics of the cooperation level were analyzed using a geographic information systems analytical method, which can better reflect the competitiveness, relationships, and overall cooperation level of tourist attractions. The results showed that the tourism competitiveness of tourist attractions was generally strong and their internal relations relatively close, and the overall tourism cooperation level was high. However, a two-dimensional four-quadrant map revealed that there were still great differences in tourism competitiveness among tourist attractions and their internal relations. Twenty-three tourist attractions exhibited weak tourism competitiveness and sparse relationships with other tourist attractions. The tourism competitiveness of tourist attractions and their internal relations and tourism cooperation level showed positive spatial autocorrelation and spatial agglomeration characteristics. The spatial differentiation of an "inverted U-shape" indicated that the cooperation level, tourism competitiveness, and mutual relations of tourist attractions were not balanced and that a stable and gradual spatial transformation had not been achieved. This study can provide valuable insights for the government to formulate policies and measures for regional tourism cooperation, carry out regional joint marketing, and help tourism enterprises design tourist routes. [ABSTRACT FROM AUTHOR]

Tourism is distinctly regional with respect to the regional distribution of tourism resources, tourist attractions and supply, and spatial continuity of tourist activities. Using point-of-interest data from 2166 tourist attractions in the Yangtze River Delta, this study analyzes the spatial distribution pattern of tourist attractions and their influencing factors by applying the methods of nearest proximity index, kernel density analysis, standard deviation ellipse, hotspot analysis, and spatial superposition analysis. The results show that the number of modern recreational tourist attractions accounts for the largest proportion. The spatial distribution pattern shows more attractions in the north than the south and more in the east than the west. The spatial density of tourist attractions in Shanghai is far greater than that in other regions, followed by Jiangsu and Zhejiang. The five types of tourist attractions show a significant aggregation state. Natural ecological tourist attractions are clustered near Nanjing and Huangshan; historical and cultural tourist attractions are formed in a T-shape by Shanghai, Hangzhou, and Nanjing; modern recreational tourist attractions are clustered in Shanghai and Hangzhou; and industrial integration tourist attractions are clustered in Shanghai, Nanjing, and Hangzhou. Physical geography, traffic, and social economy are the main factors affecting the spatial distribution of tourist attractions. [ABSTRACT FROM AUTHOR]

This study's purpose was to analyze the network structural characteristics, nodal roles, spatial structure, and evolution laws from the dual network perspective, and apply the Quadratic Assignment Procedure (QAP) to conduct correlation analysis and regression analysis on the influencing factors of tourism flow networks in the Yangtze River Delta urban agglomerations. Using a mixed-method of social network and spatial analysis, Ucinet and ArcGIS software were used to comprehensively analyze the nodes in the travel routes covered in travel notes. The results show that the density of tourism flow network increases on the whole, while the spatial difference decreases, and the overall network density value is much lower than the average of the network density of provinces. Degree centrality, closeness centrality, betweenness centrality and the core–periphery structure analysis were used to examine the tourism function, distribution function, connection function and the position of nodes in the network, and nodes were divided into various types of roles according to their function. Meanwhile, the role changes of each node in different periods were also investigated. This study also builds an evaluation model of the influencing factors of the evolution of tourism flow network structure and uses QAP to find that the tourism network is affected by factors such as tourism resource endowment, transportation convenience, economic development level, tourism reception and service capacity. The research results are helpful for the Chinese government and tourism enterprises to understand the spatial behavior of tourists and its evolution rules, and to clarify the role and status of node cities in the tourism flow network and their influencing factors. It is of great significance for the formulation of joint marketing measures and promotion of the sustainable development of tourism in the Yangtze River Delta urban agglomeration. [ABSTRACT FROM AUTHOR]

This study aimed to examine the spatial structure of the tourist attraction cooperation network in the Yangtze River Delta, from the perspective of tourist flow. This study conducted spatial and social network analyses of 470 popular tourist attractions in the Yangtze River Delta region of China, accounting for the occurrence and co-occurrence of tourist attraction information in tourist travel notes. The analyzed tourist attractions show an obvious spatial agglomeration effect, including four high-density agglomeration areas and two medium-density agglomeration areas. Degree centrality, closeness centrality, and betweenness centrality were used to examine the tourism function, distribution function, and connection function of nodes in the network; nodes were divided into various types of roles according to their function. There are eight condensed subgroups, but their scales are unbalanced. In these condensed subgroups, several tourist attractions with an intermediate function can be selected as transit and stopover points on tourist routes. This study can contribute to the understanding of tourists' spatial behavior, clarify the role and status of nodes in the cooperation network of tourist attractions based on tourism flow, and help them to formulate measures for the joint marketing of tourist attractions, and promote the development of tourism in the Yangtze River Delta region. [ABSTRACT FROM AUTHOR]

Oxygen is an important parameter for organic-waste composting, and continuous control of the oxygen in a composting pile may be beneficial. The oxygen consumption rate can be used to measure the degree of biological oxidation and decomposition of organic matter. However, without having a real-time online device to monitor oxygen levels in the composting pile, the adjustment and optimization of the composting process cannot be directly implemented. In the present study, we researched and developed such a system, and then tested its stability, reliability, and characteristics. The test results showed that the equipment was accurate and stable, and produced good responses with good repeatability. The equilibrium time required to detect oxygen concentration in the composting pile was 50 s, and the response time for oxygen detection was less than 2 s. The equipment could monitor oxygen concentration online and in real time to optimize the aeration strategy for the compost depending on the concentration indicated by the oxygen-measuring equipment. [ABSTRACT FROM AUTHOR]