bluuebunny/crossref_metadata_2025 huggingface dataset:
Multicomponent Training and Optimal Dosing Strategies for Adults with Hypertension: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: López-Ruiz Isabel , Lozano Fernando , Masia María Dolores , González-Gálvez Noelia
Published: June 2023

(1) Background: Non-pharmacological interventions have demonstrated efficacy in the prevention, management, and control of hypertension. Multicomponent training confers a host of benefits to the general populace. The aim of this research was to assess the impact of multicomponent training on the blood pressure of adults with hypertension and ascertain the nature of the dose–response relationship. (2) Methods: This systematic review adhered to the PRISMA guidelines and was registered in PROSPERO. Eight studies were included, following a literature search across PubMed, Web of Science, Cochrane, and EBSCO. Randomized controlled trials implementing multicomponent training interventions on adults with hypertension were considered for inclusion. A quality assessment was performed using the PEDro scale, with a random-effects model utilized for all analyses. (3) Results: Multicomponent training yielded a significant reduction in systolic (MD = −10.40, p < 0.001) and diastolic (MD = −5.97, p < 0.001) blood pressure relative to the control group. Interventions lasting over 14 weeks with a minimum frequency of three sessions per week, each lasting 60 min, were deemed most effective. (4) Conclusion: An optimal training intensity was achieved with 30 min of aerobic exercise at 75% of the heart rate reserve, whereas sets of 10 repetitions at 75% of one repetition maximum produced the best outcomes in strength training.
Potential Benefits and Disbenefits of the Application of Water Treatment Residuals from Drinking Water Treatment Processes to Land in Scotland: Development of a Decision Support Tool
Authors: Minto Andrew , Gilmour Daniel , Jorat M. Ehsan , Tierney Irene
Published: June 2023

Water Treatment Residuals (WTRs) are a by-product of the addition of chemical coagulants to water during the water treatment process and are a mixture of water and organic and inorganic matter that coagulates during the treatment process. WTRs often contain metals such as iron, aluminium, and manganese that have been oxidised as part of the process or are constituents of the coagulation chemicals used. The metals within WTRs are of interest with regard to applying these sludges to agricultural land. WTRs can also contain beneficial organic matter and nutrients (primarily nitrogen). The nature of the benefits delivered is largely dependent on the quality of the raw water and these beneficial components are generally found in much smaller quantities in WTRs than are found in sewage sludge produced from wastewater. However, WTRs can still be used to enhance the physical properties of soils. As urban populations increase in size, it is anticipated that the tonnage of WTRs will increase significantly in the future. At present, the majority of WTRs are disposed of in landfills; however, landfill charges are increasing significantly, making disposal of an increasing tonnage of WTRs financially unviable. In terms of a circular economy, the procedure of reusing WTRs for alternative applications satisfies the Scottish Government’s goals in terms of waste prevention and reducing the amount of material being sent to landfill as set out in the Proposals for Legislation in 2019. Given the potential benefits in terms of cost savings and compliance with government legislation, and the complexities of understanding where and when WTRs can be used in land applications, we developed a Decision Support Tool (DST) that uses data obtained from an extensive review of approaches in other countries to assist in decision making. We also conducted a pre-application analysis and provided guidance on when and where WTRs can be used in land applications and when they are not suitable, presented in a simplified format that requires few inputs from the user in order to simplify the process and removes the requirement for a specialist operator during pre-application analyses.
Habitat Quality Assessment under the Change of Vegetation Coverage in the Tumen River Cross-Border Basin
Authors: Wang Yue , Quan Donghe , Zhu Weihong , Lin Zhehao , Jin Ri
Published: June 2023

The continuous deterioration of terrestrial ecosystems has led to the destruction of many biological habitats in recent years. The Tumen River cross-border basin, an important biological habitat, is also affected by this changing situation. Assessing habitat quality (HQ) is crucial for restoring and protecting habitats, and vegetation plays a significant role in this process. In this study, we used geographical detector (GD) to extract fraction vegetation coverage (FVC) features and quantify the contribution of driving factors. By coupling vegetation cover and land use data, we assessed HQ. Our findings reveal a declining trend in FVC from 2000 to 2020, which mainly assumed a spatial pattern inclined from northeast and southwest to southeast. Human activities and natural factors interacted to cause these changes in FVC, with human activities having a more significant impact. Vegetation and land use changes led to a decline in the basin’s HQ index. This study highlights the crucial role of FVC in HQ and provides a relevant scientific reference for optimizing the evaluation of HQ in the Tumen River cross-border basin and promoting the sustainable development of regional ecology.
Regional Water Stress Forecasting: Effects of Climate Change, Socioeconomic Development, and Irrigated Agriculture—A Texas Case Study
Authors: Su Qiong , Karthikeyan Raghupathy
Published: June 2023

Climate change, socioeconomic development, and irrigation management are exacerbating water scarcity in many regions worldwide. However, current global-scale modeling approaches used to evaluate the impact of these factors on water resources are limited by coarse resolution and simplified representation of local socioeconomic and agricultural systems, which hinders their use for regional decision making. Here, we upgraded the irrigation water use simulation in the system dynamics and water environmental model (SyDWEM) and integrated it with the water supply stress index (WaSSI) ecosystem services model. This integrated model (SyDWEM-WaSSI) simulated local socioeconomic and agricultural systems to accurately assess future water stress associated with climate change, socioeconomic development, and agricultural management at subbasin levels. We calibrated the integrated model and applied it to assess future water stress levels in Texas from 2015 to 2050. The water stress index (WSI), defined as the ratio of water withdrawal to availability, was used to indicate different water stress levels. Our results showed that the integrated model captured changes in water demand across various sectors and the impact of climate change on water supply. Projected high water stress areas (WSI > 0.4) are expected to increase significantly by 2050, particularly in the Texas High Plains and Rolling Plains regions, where irrigation water use was projected to rise due to the impact of climate change. Metropolitan areas, including Dallas, Houston, Austin, and San Antonio, were also expected to experience increased domestic water demand, further exacerbating water stress in these areas. Our study highlights the need to incorporate socioeconomic planning into water resources management. The integrated model is a valuable tool for decisionmakers and stakeholders to evaluate the impacts of climate change, socioeconomic development, and irrigation management on water resources at the local scale.
Exploring the Discrepancy between Projected and Perceived Destination Images: A Cross-Cultural and Sustainable Analysis Using LDA Modeling
Authors: Chen Qiuying , Xu Shangyue , Liu Ronghui , Jiang Qingquan
Published: June 2023

The projected image, created by destination marketing organizations, and the perceived image, formed by tourists’ perceptions, are crucial factors in destination selection. In this paper, machine learning models are used to construct projected image dimensions and perceptual dimensions for Chinese and English to analyze the similarities and differences between projected and perceptual images and their Chinese sustainability and cultural differences issues. We take Xiamen, a seaside tourist city in China, as an example, and analyze it by collecting 110,098 official promotional texts (both in Chinese and English) and tourist online review feedback as data sources using a latent Dirichlet allocation (LDA) model of natural language processing. The findings show that (1) the official projected image focuses on the overall image of the destination, while the tourists’ perceived image focuses on the specific image. (2) The official projected image covers the whole area of tourism, while the tourists’ perceived image focuses on Xiamen’s well-known attractions. The results of the above two points are the same for both the Chinese and English Topic models. (3) The official projected image focuses on three dimensions of destination: sustainability-economic, socio-cultural and environmental, while the tourist perception is more in the socio-cultural and environmental dimensions. (4) Both the projected and perceived images in Chinese and English differ in cross-cultural situations. The perceived images of Chinese and British tourists are influenced by their respective cultural backgrounds. Chinese tourists’ perceptions reflect cultural values associated with collectivism, long-term orientation, and uncertainty avoidance. On the other hand, British tourists’ perceptions align with cultural values of individualism, short-term orientation, and lower uncertainty avoidance. These differences can be explained using Hofstede’s cultural dimensions theory. The research in this paper can provide a reference for the promotion of tourism cities, and tourism destination organizations should not only focus on sustainable promotion, but also attract domestic and foreign tourists through differentiated promotion.
Entomophagy—Acceptance or Hesitancy in Romania
Authors: Zamfirache Irina
Published: June 2023

This study analyzes the attitudes and perceptions of Romanian individuals regarding entomophagy, which is the practice of eating insects, with the explicit purpose of finding out the factors that influence acceptance and hesitancy using a questionnaire with 470 respondents. The study tackles various issues related to insect consumption, current eating habits, shopping habits, culture and tradition, the willingness and curiosity to try new foods, nutritional aspects, environment, knowledge about current events, and sustainability. The acceptance of insects as food, although studied more and more in the last few years, still has more questions than answers. Neophobia is part of the explanation, but so are the cultural determinants. The people who make the decisions could be an important matter, so targeting the decision makers with specific campaigns could make them more open to try new foods. Out of the factors that influence food choices, the top three answers were: taste, whether the food is perceived as healthy or not, and the price, so palatability is the most important aspect. Knowledge is another key factor that has to be improved, as most respondents do not have proper information about the benefits or the positive aspects of eating insects.
Status and Perspectives of the Ichthyofauna of the Labudovo okno Ramsar Site: An Analysis of 14 Years of Data
Authors: Nikolić Vera , Nedić Zlatko , Škraba Jurlina Dubravka , Djikanović Vesna , Kanjuh Tamara , Marić Ana , Simonović Predrag
Published: June 2023

Over the last 14 years, ichthyological and ecological parameters have been monitored in the Labudovo okno Ramsar site. This area is important for its biodiversity as it is home to many rare and endangered plants and animal species. A total of 3861 fish specimens were sampled and measured at six sampling sites four times during the sampling period. An analysis of biodiversity indexes, relative biomass (kg/ha), and relative annual production (kg/ha) was carried out to assess the effectiveness of existing conservation measures. The results obtained show a trend decline in biodiversity, relative biomass, and relative annual production. This indicates a biodiversity conservation problem that should be addressed through other mechanisms in addition to the principles of the Ramsar Convention.
Baseline Soil Dioxin Levels from Sites Where Municipal Solid Waste Incineration Construction Is Planned throughout China: Characteristics, Sources and Risk Assessment
Authors: Wan Ruxing , Wu Jun , Guo Jing , Qu Jiabao , Li Ling , Tang Ling
Published: June 2023

The determination of baseline dioxins levels in soils is fundamental for the quantitative assessment of the net environmental and health impacts of municipal solid waste (MSW) incineration plants, which remains unexplored. Therefore, this study develops a Chinese baseline soil dioxins database (covering 918 soil samples from 292 pre-construction MSW incineration plants nationwide during 2016–2020) to thoroughly explore the baseline contamination characteristics and health risks of dioxins in soils. The empirical results show that (1) for concentration levels, the baseline international toxic equivalency (I-TEQ) concentrations vary from 0.0015 to 32 ng I-TEQ/kg, which are close to or even lower than those in most existing studies and show significant heterogeneity across provinces; (2) for dioxins homolog, highly chlorinated dioxins (i.e., PCDDs) are the dominant contributor to the total dioxins in soils (contributing 54.30% of the total I-TEQ concentrations), implying that dioxins in baseline soils often have an atmospheric fingerprint; and (3) for health risks, the carcinogenic risk and non-carcinogenic risk of dioxins in soils are mostly below acceptable levels, close to or even lower than the results of previous studies. Despite these results being considered as quite preliminary, they have certain implications for local authorities. Future studies can expand the size of the database and the generalizability of the results, and if necessary, establish a long-term dynamic monitoring of dioxins in soils for systematically evaluating the net impact of MSW incineration on environment and human health.
Definition and Classification of Potential of Forest Wood Biomass in Terms of Sustainable Development: A Review
Authors: Konstantinavičienė Julija , Vitunskienė Vlada
Published: June 2023

The role of sustainable biomass, including wood biomass, is becoming increasingly important due to the European Green Deal. In the context of developing a sustainable bioeconomy, the use of wood depends on many physical, biological, technological, environmental, economic, social and political constraints. This study presents a systematic literature review by types of wood biomass potential. The literature review has shown that there is a lack of a comprehensive framework for wood biomass potential (for all needs, not only for energy production) in terms of sustainable development and that there is no general agreement on how to describe the sustainable potential of wood biomass nor how to measure it. Furthermore, the analysis has revealed certain uncertainties in describing the constraints of the potential of wood biomass. These uncertainties highlight the complexity of understanding the concept of sustainable wood biomass potential. The study addressed a definition potential of forest wood biomass for the needs of energy and industry in terms of sustainable development. The theoretical, technical and sustainable potentials of wood biomass were defined and their constraints were detailed. This study’s contributions to the conceptual clarity of the definition of the sustainable potential of wood biomass are (1) the definition of forest sustainable development, (2) the definition and classification of the potential of wood biomass, and (3) the synthesis of conceptual frameworks for the sustainable potential of wood biomass from forests.
Explore the Complex Interaction between Green Investment and Green Ecology: Evaluation from Spatial Econometric Models and China’s Provincial Panel Data
Authors: Xiao Yao , Yan Weimin , Peng Benhong
Published: June 2023

From the economic perspective, China has made remarkable progress, yet environmental concerns represent an alarm to the country’s long-term prosperity. The associated relationship between green investment and the green economy has important implications for the environment. Whether there is an interactive relationship between green investment and green ecology, current views seem to be at odds with each other. This paper employs a panel vector autoregressive model to construct an empirical analysis of China’s provincial panel data from 2005 to 2019. Specifically, generalized moment estimation, impulse response function, variance decomposition, and other measurement methods were applied to study the interaction between green investment and green ecological development. The research results show the following: (1) the inertial development of the green investment system seriously restricts the progress of green investment levels, and the long-term development of green ecology has a significant self-reinforcing trend; (2) the two-way interaction between green investment and green ecology shows a positive spillover effect in the short term, but the positive effect gradually weakens in the long run; (3) the impact of green ecology on green investment is most significant in the interactive relationship, and the positive effect of green ecology on green investment in the western region is the most prominent. Therefore, the government should standardize green investment standards and use policy guidance to promote the regional transfer of green investment and green ecological resources. Financial institutions should appropriately lower the financing threshold for polluting enterprises and municipal construction and leverage more social funds to flow into long-term green technologies and green industries. Companies should raise awareness of environmental disclosure, ban outdated production capacity, and transition to cleaner production models to secure green funding.
ROAD: Robotics-Assisted Onsite Data Collection and Deep Learning Enabled Robotic Vision System for Identification of Cracks on Diverse Surfaces
Authors: Popli Renu , Kansal Isha , Verma Jyoti , Khullar Vikas , Kumar Rajeev , Sharma Ashutosh
Published: June 2023

Crack detection on roads is essential nowadays because it has a significant impact on ensuring the safety and reliability of road infrastructure. Thus, it is necessary to create more effective and precise crack detection techniques. A safer road network and a better driving experience for all road users can result from the implementation of the ROAD (Robotics-Assisted Onsite Data Collecting) system for spotting road cracks using deep learning and robots. The suggested solution makes use of a robot vision system’s capabilities to gather high-quality data about the road and incorporates deep learning methods for automatically identifying cracks. Among the tested algorithms, Xception stands out as the most accurate and predictive model, with an accuracy of over 90% during the validation process and a mean square error of only 0.03. In contrast, other deep neural networks, such as DenseNet201, InceptionResNetV2, MobileNetV2, VGG16, and VGG19, result in inferior accuracy and higher losses. Xception also achieves high accuracy and recall scores, indicating its capability to accurately identify and classify different data points. The high accuracy and superior performance of Xception make it a valuable tool for various machine learning tasks, including image classification and object recognition.
Pandemic Impacts on Athlete Competitive Anxiety and Its Relationship with Sex, Competitive Level and Emotional Self-Control: A Cohort Study before and after COVID-19
Authors: Tomé-Lourido David , Ponte Dolores , Sampedro María José , Arce Constantino
Published: June 2023

The COVID-19 pandemic caused a great emotional impact on the general population, with specific consequences in the field of sport and physical activity. The present study was conducted to meet two objectives: (1) to investigate if the pandemic had an impact on competitive anxiety and if the sex and competitive level played a mediating role, and (2) to investigate if the relationship between emotional self-control and anxiety was affected by the pandemic. An amount of 608 Spanish athletes participated, divided into two cohorts, before and after the pandemic. Measurements of competitive anxiety and emotional self-control were made at both time points, which were processed by combining analysis of variance and regression models. Differences were found in competitive anxiety before and after COVID-19, with athlete’s competitive level acting as a mediating variable. For high-level athletes, there was an increase in anxiety, while for lower-level athletes, there was a decrease in anxiety. The pandemic seems to have led to higher levels of anxiety in elite athletes, compared to amateur athletes. There was no interaction between the sex of the participants and the cohort. Emotional self-control remained a significant predictor of low competitive anxiety levels.
Study on the Influence of Window Glass Size on Blast-Resistant Performance
Authors: Wang Xiufen , Zhong Bo , Tang Jie , Gao Chen , Li Mei
Published: June 2023

As the most commonly used exterior-protecting components for buildings, window glass, due to its typical brittle characteristics, is more prone to break under the action of blast loads and produce high-speed flying fragments, which can pose a great threat to personal safety. This paper studies the influence of the size of window glasses on their failure characteristics. A simplified numerical simulation-based method for evaluating the P–I (pressure–impulsive) curve of window glass failure under blast loads is proposed. The influences of the length–width ratio, the area, and the thickness of the P–I curves of window glasses are systematically investigated. It was found that smaller a length–width ratio, smaller area, and thicker panel could increase the blast resistance of the window glasses. The empirical prediction formulae for the P–I curves of window glasses with different geometrical dimensions are established, and the validity of the proposed empirical formula is verified.
The Dynamic Impact of Financial Technology and Energy Consumption on Environmental Sustainability
Authors: Afjal Mohd , Kathiravan Chinnadurai , Dana Leo Paul , Nagarajan Chitra Devi
Published: June 2023

This research investigates the dynamic interplay between financial technology, information and communication technology, energy consumption, and economic growth on environmental sustainability within Emerging and Growth-Leading Economies (EAGLEs) from 2005 to 2020. Utilizing advanced econometric techniques, such as Fully Modified Least Squares (FMOLS) and Vector Autoregressive Error Correction Model (VECM), the investigation scrutinizes the hypothesized relationships among these variables. Panel unit root tests were deployed to assess stationarity, while panel least squares methodology was employed to determine the presence of co-integration among the variables under study. The analysis reveals that internet usage, GDP, and renewable energy consumption exhibit a notable influence in diminishing CO2 emissions within EAGLE economies. Additionally, the findings substantiate the existence of long-term causality originating from these variables and impacting CO2 emissions. Conversely, the role of ATM networks in CO2 emissions remains ambiguous, implying that financial technology’s influence on environmental sustainability is inconclusive. Consequently, the research posits that environmental sustainability in EAGLE economies is chiefly determined by factors such as internet usage, economic expansion, and renewable energy consumption, with financial technology demonstrating no discernable impact. In light of these findings, the study advocates for the reevaluation and adaptation of existing policies and strategies to account for shifting climatic conditions. By doing so, decision-makers can better align their efforts with the pursuit of environmental sustainability in the context of rapidly evolving economies.
Determinants of Economical High School Students’ Attitudes toward Mobile Devices Use
Authors: Moca Mihaela , Badulescu Alina
Published: June 2023

Due to recent considerable technology breakthroughs in the education sector, new tools have been developed to improve learning. Motivating students to use new devices for learning rather than just for amusement, however, is a difficulty. The COVID-19 pandemic prompted the adoption of technological devices for course delivery, thereby highlighting the significance of mobile learning (m-learning) and allowing educators, students, and other stakeholders in the education sector to recognize its potential, advantages, drawbacks, and challenges. As m-learning has been an essential aspect of education for some time now, there is growing interest in assessing its long-term viability and usefulness across various educational domains, including economics. New technologies like computers, the internet, and related tools can help by bringing life to the classroom, gauging student progress, simulating economic activities and phenomena, and teaching vital skills needed for the economic world, like entrepreneurship. This study aims to explore the potential of incorporating new technologies in economic education, we study the tendency of the economical high school students towards using mobile devices for learning activities. A total of 407 participants were involved in research, the data from these respondents being collected with the help of a questionnaire survey. The original technology acceptance model (TAM) has been extended and the role of various external factors such as the subjective norm, learning autonomy, facilitating conditions or self-efficacy has been addressed. A list of hypotheses was proposed to validate the underlying model and provide guidance on how external factors affect attitudes towards using mobile devices. The empirical results indicated that perceived ease of use and perceived usefulness are significant predictors to explain the attitudes towards mobile devices use and m-learning and the analyzed external factors have a positive influence on them. In terms of methods used, we characterize the perception of students by structural equations modelling (SEM). This study identifies and analyzes the factors that influence students’ attitude and readiness towards mobile technology use in education, providing valuable insights into improving the adoption of new technologies and to evaluate the sustainability of m-learning in economic education.
Research Status and Challenges on the Sustainable Development of Artificial Intelligence Courses from a Global Perspective
Authors: Yang Ying , Qin Jinruo , Lei Jing , Liu Yanping
Published: June 2023

The widespread application of artificial intelligence technology in various fields has made the sustainable development of artificial intelligence courses an important direction in the field of artificial intelligence education and teaching. Therefore, it is particularly important to conduct an in-depth analysis of the current research status of “artificial intelligence courses” from a global perspective. Firstly, this article clarifies the three stages of slow development, rapid development, and mature development of artificial intelligence curriculum research through the number and distribution years of the literature. It also conducts a co-authorship analysis on the distribution of countries, institutions, and authors of artificial intelligence curriculum research and identifies countries, institutions, and core authors that have made greater contributions to artificial intelligence curriculum research. Secondly, due to the involvement of artificial intelligence in many different fields of knowledge, an analysis is conducted on the journals that published papers on artificial intelligence courses. Finally, based on the analysis of keyword density and time span, the current research hotspots of artificial intelligence courses are summarized: artificial intelligence technology empowerment courses, two education directions at different stages of artificial intelligence courses, and teaching forms in the field of artificial intelligence courses. The current research trend of artificial intelligence courses is analyzed from three aspects: teaching format, teaching content, and teaching objects. This article provides a theoretical reference value and practical basis for future research and development in the field of artificial intelligence courses, while also providing experience for the efficient and sustainable development of artificial intelligence courses to a certain extent.
Innovative City Construction and Urban Environmental Performance: Empirical Evidence from China
Authors: Gao Jun , Xu Ning , Zhou Ju
Published: June 2023

Environmental performance is a key issue that relates to the sustainable development of the economy and the environment. Innovation-driven approaches are fundamental in improving environmental performance; however, innovation activities come with uncertainties and require supportive policies from the government. This study utilizes the implementation of the Innovation City Pilot (ICP) policy in China as a quasi-natural experiment. It employs a progressive Difference-in-Differences (DID) model using panel data from 283 Chinese cities during the period of 2005–2019 to evaluate the impact of the ICP policy on Urban Environmental Performance (UEP) and its underlying mechanisms. The empirical results indicate that (1) the ICP policy significantly promotes the improvement of UEP and robustness analyses further support this conclusion; (2) compared to cities in the central and western regions, resource-dependent cities, and higher administrative level cities, the ICP policy is more beneficial for enhancing UEP in eastern, non-resource-dependent, and lower administrative level cities; (3) mechanism tests suggest that the ICP policy facilitates UEP improvement by leveraging technological innovation, upgrading industrial structure, and optimizing resource allocation; (4) the ICP policy not only benefits the UEP enhancement in local cities but also promotes UEP improvement in neighboring cities through spatial spillover effects. This study provides evidence and insights from China, contributing to the global implementation of innovation-driven development strategies for sustainable urban economic and environmental development.
Multi-Level Participatory GIS Framework to Assess Mobility Needs and Transport Barriers in Rural Areas: A Case Study of Rural Mumias East, a Sub-County of Kakamega, Kenya
Authors: Munyaka Jean-Claude Baraka , Chenal Jérôme , de Roulet Pablo Txomin Harpo , Mandal Anil Kumar , Pudasaini Uttam , Otieno Nixon Ouku
Published: June 2023

In recent decades, there has been a growing interest in the application of GIS to community empowerment or new policy development through participatory design, information gathering and implementation. This study, therefore, aims to apply a multi-level participatory GIS (PGIS) framework to assess mobility needs and barriers in rural areas from different available transport modes. This assessment was applied to three sub-locations (Lusheya, Khaunga and Mahola) located in the sub-county of Mumias East, Kakamega, Kenya. The study brings two main contributions: (1) an overview of mobility needs and barriers in Sub-Saharan Africa (SSA) and (2) an introduction of a PGIS framework that integrates in-depth local knowledge of rural mobility needs and mobility barriers. This PGIS framework was applied to mobility issues based on three main dimensions: context, process and content. The context in the PGIS framework focuses on identifying the right stakeholders and putting on suitable structures for their training as well as the collection of data. The process considers the collection, analysis and visualization of rural mobility data. The content of the data collected are validated for accuracy in the form of maps and are evaluated for relevance by stakeholders. Local youths with GIS knowledge and digital tools were mobilized along with community people having a solid understanding of the local geographical contexts to collect geographically referenced data related to community resources, transport networks, and mobility barriers. The application of the multi-level PGIS framework has brought to the mainstream daily mobility challenges faced by rural communities in Sub-Saharan Africa. Community members, even those from remote areas, also have access to decision making, reversing the previous structure that strongly relied on often-irrelevant, top-down decision making.
A Systematic Literature Review on the Transition to Circular Business Models for Small and Medium-Sized Enterprises (SMEs)
Authors: Kuik Swee , Kumar Akhil , Diong Li , Ban Joowon
Published: June 2023

The transition of a business to a circular business model (CBM) calls for significant and ongoing shifts in different business management models and strategies. However, there is a lack of research focused on the technological, financial, societal, and institutional influences on the CBM transition in small and/or medium-sized enterprises (SMEs). To address this gap, our study develops a theoretical framework for the transition towards CBM. We conducted a systematic literature review with the objective of determining the relationships among technological, financial, societal, and institutional influences for CBMs. Following this, we then established a conceptual framework that comprises these four key influences for a transition plan in the context of an innovative business model with a focus on the value proposition, value creation, and value delivery. An illustrative case example of the manufacturing industry for the transition plan to CBM was presented as well. The proposed framework is designed to lead the shift towards circular economy-oriented business models that aim to promote sustainability in business. In addition, we uncovered several potential avenues for further investigation. We expect the framework towards both contribute to the expansion of the existing body of research in the field and provide business practitioners with guidelines on the CBMs’ transition for SMEs.
The Relationship between ICT Use and Perceived Life Satisfaction among Older People in Korea: The Mediating Effect of Social Capital
Authors: Kong Haiyan , Liu Huifang
Published: June 2023

The advent of the Fourth Industrial Revolution and the spread of infectious diseases have increased people’s reliance on information and communication technology (ICT). However, older adults are the most marginalized group affected by ICT, and their activities and daily life have become more difficult than ever during the pandemic. Based on the theory of the TAM, this study analyzed the effect of ICT use on life satisfaction among older adults during the pandemic, and examined the mediating role of social capital. The partial least squares structural equation modeling (PLS-SEM) was applied to test the relationships among ICT use, social capital, and life satisfaction, and the Sobel test was used to test the mediating effect and statistical significance of social capital. The results of the analysis confirmed the positive effects of technology’s perceived usefulness and self-efficacy on attitudes and ICT use among older adults. ICT use had a positive effect on life satisfaction. In addition, it was found that social capital had a mediating effect on the relationship between ICT use and life satisfaction. During the pandemic, ICT use not only had a direct effect on life satisfaction but also had an indirect effect through social capital among older adults. The results of this study have implications for research on ICT use and life satisfaction among older adults, and have implications for formulating public policies for active aging. The results of this study can facilitate a comprehensive understanding of the antecedents and consequential factors of the use of digital information among older adults, which not only complements previous studies but also provides a theoretical basis for systematic research on digital literacy and well-being in older adults.
Study on the Maximum Level of Disposable Plastic Product Waste
Authors: Hong Yizhao
Published: June 2023

Plastic is a widely used material in daily life that has brought huge social benefits to society with the advantages of low-cost manufacturing and mildness. However, due to their high resistance to degradation and diversity of chemical components, plastics pose a great threat to human health and the living environment. Aiming to address the problem that there is a lot of plastic waste and its impact on the environment, this paper puts forward an effective plan to reduce plastic waste and tests the relevant models. First, based on the pollution index data of plastic waste, it uses the Analytic Hierarchy Process and the entropy weight model to determine the evaluation index weight of plastic waste pollution impact and judge the environmental damage ability and environmental recovery ability. Secondly, in order to measure the level of environmental safety, it establishes an evaluation index system and uses the gray correlation method to determine the weight value of the evaluation index and calculate the environmental safety scores of each country. Thirdly, according to the second index system, it selects the relevant data from 10 countries, establishes a BP neural network model, and calculates the level of security and the intensity of responsibility. Finally, based on the results of the model and the global goal of achieving the minimum level of plastic waste, it offers a memorandum with a schedule and discusses the measures needed to achieve this goal and the factors to be considered. Overall, compared with the existing research, this paper presents a different approach to the assessment and measurement of the use of the environment and its capacity for pollution, combining multi-disciplinary influencing factors.
Remote Sensing Surveillance of NO2, SO2, CO, and AOD along the Suez Canal Pre- and Post-COVID-19 Lockdown Periods and during the Blockage
Authors: Gamal Gamil , Abdeldayem Omar M. , Elattar Hoda , Hendy Salma , Gabr Mohamed Elsayed , Mostafa Mohamed K.
Published: June 2023

This study investigates the impact of the COVID-19 pandemic and the Ever Given ship blockage on the air quality in Suez Canal region. Nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and aerosol optical depth (AOD) were studied, and data were obtained from satellite instruments. The study compared monthly average data for 2020, 2021, and 2022 with a baseline period of 2017–2019 to investigate the pandemic’s effect. The study also analyzed the corresponding period of the canal blockage to identify its impact on air pollution levels. The pandemic had a significant role in decreasing NO2 by 2.5 × 1014 molecule/cm2 and SO2 by 0.05 DU due to reduced car traffic and industrial activities. A reduction in AOD by 20% and CO concentration in the range from 3.5% to 4.7% was reported in early 2020. During the blockage, NO2 and SO2 levels decreased by 14.4% and 66.0%, respectively, while CO and AOD index increased by 12.68% and 51.0%, respectively. The study concludes that the containment measures during the pandemic had a positive impact on the environment, which shows how the reduction in the anthropogenic activities, especially industrial and transportation activities, have improved the air quality. Thus, stricter actions are needed to protect the environment; for example, the transition towards the using of electric vehicle is necessary, which is part of Egypt’s strategy to transition towards a green economy. The government should also adopt a policy to trade carbon emissions reduction certificates to help reduce air pollution.
Research on the Characteristics and Influencing Factors of Provincial Urban Network from the Perspective of Local Governance—Based on the Data of the Top 100 Enterprises in Four Categories in Fujian Province
Authors: Zhao Jialiang , Wei Suqiong , Su Qingmu
Published: June 2023

With the development of the division of labor in product value chains and the specialization of urban functions, the network link structure model among cities is being reshaped. Studying the structure of urban networks and its related theories in the context of scale, place and policy is still an open area. This study constructs a research framework to study the urban network formed by the synergy of scale, place and policy. It mainly takes enterprises in different industries in different provinces as the empirical scale and object, and uses methods such as a social network and Geo Detector to analyze the characteristics and influencing factors of the provincial network relationship mode of enterprises among cities. The main findings are as follows. (1) Firstly, the urban network linkage in general shows strong coastal centrality and small-world network characteristics. The urban network linkages reflected by different types of enterprises all have obvious spatial directionality and polarization effects. (2) Coastal cities have strong centrality, and the specialized division of urban functions emerges, with large cities becoming a concentration area for different types of corporate headquarters, while small- and medium-sized cities carry a large number of processing and assembly enterprises. (3) The networks of different types of enterprises have different sensitivity to each influencing factor. For example, emerging industries have the strongest correlation with the economic scale and social services; manufacturing industries are most influenced by the public services, administrative level and development zone level; and service industries are most influenced by science and technology expenditure and the same metropolitan area. In conclusion, this study contributes to the understanding of network heterogeneity at the provincial scale and provides policy support for the local governance scale, as well as promotes the expansion of the urban network theory to network governance applications in the “flow space”.
Investigation on Hazardous Material Truck Involved Fatal Crashes Using Cluster Correspondence Analysis
Authors: Sun Ming , Zhou Ronggui
Published: June 2023

Although hazardous material (HAZMAT) truck-involved crashes are uncommon compared to other types of traffic crashes, these crashes pose considerable threats to the public, property, and environment due to the unique feature of low probability with high consequences. Using ten-year (2010–2019) crash data from the Fatality Analysis Reporting System (FARS) database, this study applies cluster correspondence analysis to identify the underlying patterns and the associations between the risk factors for HAZMAT-truck-involved fatal crashes. A low-dimensional space projects the categorical variables (including the crash, road, driver, vehicle, and environmental characteristics) into different clusters based on the optimal clustering validation criterion. This study reveals that fatal HAZMAT-truck-involved crashes are highly distinguishable concerning collision types (angle and front-to-front crashes, single-vehicle crashes, and front-to-end crashes) and roadway geometric variables, such as two-way undivided roadways, curve alignments, and high-speed (65 mph or more) urban interstate highways. Driver behavior (distraction, asleep or fatigue, and physical impairment), lighting conditions (dark–lighted and dark–not lighted), and adverse weather are also interrelated. The findings from this study will help HAZMAT carriers, transportation management authorities, and policymakers develop potential targeted countermeasures for HAZMAT-truck-involved crash reduction and safety improvement.
Ternary Hybrid Nanofluid Flow Emerging on a Symmetrically Stretching Sheet Optimization with Machine Learning Prediction Scheme
Authors: Priyadharshini P. , Archana M. Vanitha , Shah Nehad Ali , Alshehri Mansoor H.
Published: June 2023

Nanofluids holding three distinct sorts of nanosized particles suspended in base fluid possess excellent thermal performance. In light of this novel use in coolant applications, the current work dealt with the optimal design and performance estimation of a ternary hybrid nanofluid, based on a modern machine learning prediction technique. The synthesis of (Cu), (TiO2), and (SiO2) ternary hybrid nanoparticles suspended in water over a symmetrically stretching sheet was scrutinized. The flow over a stretching sheet is the most noteworthy symmetry analysis for momentum and thermal boundary layers, due to the implications of heat transfer, and is applied in various industries and technological fields. The governing equations were transformed to a dimension-free series of ODEs, by handling similarity transformable with symmetry variables, after which, the series of ODEs were treated scientifically, with the help of the Wolfram Language tool. The precision of the current estimates was assessed by comparison to existing research. Moreover, the natures of the physical phenomena were forecast by designing a support vector machine algorithm with an emphasis on machine learning, which delivers a robust and efficient structure for every fluid application that infers physical influences. To validate the proposed research, some of the statistical metrics were taken for error assessment between true and anticipated values. It was revealed that the presented approach is the best strategy for predicting physical quantities. This investigation established that ternary hybrid nanofluid possesses excellent thermal performance, greater than that of hybrid nanofluid. The current optimization process delivers a new beneficial viewpoint on the production of polymer sheets, glass fiber, petroleum, plastic films, heat exchangers, and electronic devices. Hence, the obtained results are recommended for the development of industrial devices setups.
The Convergence of Symmetric Discretization Models for Nonlinear Schrödinger Equation in Dark Solitons’ Motion
Authors: Li Yazhuo , Luo Qian , Feng Quandong
Published: June 2023

The Schrödinger equation is one of the most basic equations in quantum mechanics. In this paper, we study the convergence of symmetric discretization models for the nonlinear Schrödinger equation in dark solitons’ motion and verify the theoretical results through numerical experiments. Via the second-order symmetric difference, we can obtain two popular space-symmetric discretization models of the nonlinear Schrödinger equation in dark solitons’ motion: the direct-discrete model and the Ablowitz–Ladik model. Furthermore, applying the midpoint scheme with symmetry to the space discretization models, we obtain two time–space discretization models: the Crank–Nicolson method and the new difference method. Secondly, we demonstrate that the solutions of the two space-symmetric discretization models converge to the solution of the nonlinear Schrödinger equation. Additionally, we prove that the convergence order of the two time–space discretization models is O(h2+τ2) in discrete L2-norm error estimates. Finally, we present some numerical experiments to verify the theoretical results and show that our numerical experiments agree well with the proven theoretical results.