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Sustainability, Volume 14, Issue 23 (December-1 2022) – 838 articles

Cover Story (view full-size image): We determined the effect that the individual and combined action of an EM microbiological preparation and the Asahi SL biostimulator in various stubble management systems had on the biological and chemical soil properties and the phytosanitary condition of wheat. The preparations we tested that are based on the activity of microorganisms and natural phenolic compounds are treated as potential substitutes for traditional fertilizers and pesticides, the abuse of which is considered to be a cause of environmental degradation. The results of this, by expanding the information base upon which the principles of eco-friendly product application will be clarified, may support their wider-scale introduction into agricultural practice, while also ensuring their efficacy and environmental benefits. View this paper
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14 pages, 2455 KiB  
Article
Auditing and Sustainability Accounting: A Global Examination Using the Scopus Database
by Mohammed Muneerali Thottoli, Md. Aminul Islam, Farid Ahammad Sobhani, Shafiqur Rahman and Md. Sharif Hassan
Sustainability 2022, 14(23), 16323; https://doi.org/10.3390/su142316323 - 6 Dec 2022
Cited by 2 | Viewed by 2635
Abstract
Purpose: Sustainability accounting measures performance toward sustainability that ensures accountability of the provision of conventional accounting information. A compliance audit is a thorough examination of a company’s compliance with regulatory requirements. Compliance audit reports assess the strength and diligence of regulatory compliance measures, [...] Read more.
Purpose: Sustainability accounting measures performance toward sustainability that ensures accountability of the provision of conventional accounting information. A compliance audit is a thorough examination of a company’s compliance with regulatory requirements. Compliance audit reports assess the strength and diligence of regulatory compliance measures, security guidelines, risk management processes, and user control regulations during a compliance audit and sustainability accounting reports. Auditing plays an important role in ensuring that all financial information-related conventions are followed properly. Hence, the current research aims to explore the conceptual structure in the knowledge of auditing and sustainability accounting using a bibliometric analysis, intending to contribute to a better understanding of this field of study. Design/methodology/approach: This study used bibliometric analysis to examine the research on compliance audits between 2000 and 2021, using a sample of 330 research articles from Scopus databases, with only articles and review papers published on the business subject. This study also examines the applicability of Bradford’s laws and Lotka’s law. Findings: The bibliometric analysis reveals trends in the field of auditing and sustainability accounting research publications, indicating that compliance audit is a developing subject, and it still confronts challenges in mainstream accounting and auditing research. The high proportion of cited articles by a few authors, on the other hand, suggests that compliance audit is still a niche field of study. Between 2009 and 2021, the number of articles increases significantly, and the leading Scopus indexed journals, authors, and collaboration networks are identified. In light of the preceding literature’s views, some significant research gaps and further proposals for future studies are identified. Research limitations/implications: This research analysis is based on data taken only from the Scopus database; some flaws will be apparent in the findings. Originality/value: This research contributes to the area by examining the present advancements of the compliance audit and sustainability accounting, highlighting existing gaps in the literature, and, most importantly, proposing future research for the field. Full article
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13 pages, 1786 KiB  
Article
Nature-Inspired Cloud–Crowd Computing for Intelligent Transportation System
by Vandana Singh, Sudip Kumar Sahana and Vandana Bhattacharjee
Sustainability 2022, 14(23), 16322; https://doi.org/10.3390/su142316322 - 6 Dec 2022
Cited by 2 | Viewed by 2055
Abstract
Nowadays, it is crucial to have effective road traffic signal timing, especially in an ideal traffic light cycle. This problem can be resolved with modern technologies such as artificial intelligence, cloud and crowd computing. We hereby present a functional model named Cloud–Crowd Computing-based [...] Read more.
Nowadays, it is crucial to have effective road traffic signal timing, especially in an ideal traffic light cycle. This problem can be resolved with modern technologies such as artificial intelligence, cloud and crowd computing. We hereby present a functional model named Cloud–Crowd Computing-based Intelligent Transportation System (CCCITS). This model aims to organize traffic by changing the phase of traffic lights in real-time based on road conditions and incidental crowdsourcing sentiment. Crowd computing is responsible for fine-tuning the system with feedback. In contrast, the cloud is responsible for the computation, which can use AI to secure efficient and effective paths for users. As a result of its installation, traffic management becomes more efficient, and traffic lights change dynamically depending on the traffic volume at the junction. The cloud medium collects updates about mishaps through the crowd computing system and incorporates updates to refine the model. It is observed that nature-inspired algorithms are very useful in solving complex transportation problems and can deal with NP-hard situations efficiently. To establish the feasibility of CCCITS, the SUMO simulation environment was used with nature-inspired algorithms (NIA), namely, Particle Swarm Optimization (PSO), Ant Colony Optimization and Genetic Algorithm (GA), and found satisfactory results. Full article
(This article belongs to the Special Issue Control System for Sustainable Urban Mobility)
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16 pages, 12000 KiB  
Article
Dynamic Characteristics of Reinforced Soil Retaining Wall with Composite Gabion Based on Time Domain Identification Method
by Xiaoguang Cai, Shaoqiu Zhang, Sihan Li, Honglu Xu, Xin Huang, Chen Zhu and Xin Liu
Sustainability 2022, 14(23), 16321; https://doi.org/10.3390/su142316321 - 6 Dec 2022
Cited by 1 | Viewed by 1561
Abstract
A series of shaking table tests was carried out on the dynamic performance and working mechanism of a gabion reinforced soil retaining wall under seismic load. The test results show that the panel presents the deformation mode of middle and upper bulging at [...] Read more.
A series of shaking table tests was carried out on the dynamic performance and working mechanism of a gabion reinforced soil retaining wall under seismic load. The test results show that the panel presents the deformation mode of middle and upper bulging at the contact point between the rigid box and the retaining wall The settlement of top backfill is relatively uniform, and there is basically no differential settlement, the natural frequencies at different positions and heights inside the retaining wall are basically the same, and the natural frequencies are stable between 22.61 and 23.04 Hz below 0.8 g. The damping ratio decreases with the increase in wall height, and the damping ratio at each stage after vibration is greater than that before vibration. The seismic earth pressure is nonlinearly distributed. The measured value of the lower part of the retaining wall is smaller than that calculated by the Seed–Whitman method with an increase in peak acceleration, and the measured value of the upper part of the retaining wall is larger than the theoretical calculation results. The position of the resultant action point of seismic earth pressure is greater than 0.33 times the wall height specified by the Mononobe–Okabe method. Full article
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19 pages, 1215 KiB  
Article
Evaluating Influencing Factors of Tourists’ Experiences with Smart Tour Guide System: A Mixed Method Research
by Junjie Gao and Younghwan Pan
Sustainability 2022, 14(23), 16320; https://doi.org/10.3390/su142316320 - 6 Dec 2022
Cited by 4 | Viewed by 2409
Abstract
The issue that this study explores is evaluation of tourists’ experiences with smart tour guide system (STGS). To address this issue, the purpose of this study is to explore what factors influence tourists’ experiences with STGS in four Chinese smart tourism destinations (STDs). [...] Read more.
The issue that this study explores is evaluation of tourists’ experiences with smart tour guide system (STGS). To address this issue, the purpose of this study is to explore what factors influence tourists’ experiences with STGS in four Chinese smart tourism destinations (STDs). An exploratory sequential mixed method was used to collect the data. Tourists who had used STGS in four Chinese STDs participated in the research. In the first and second phase, Semi-structured interviews with 12 interviewees were conducted, and these interviewees put forward six factors affecting tourists’ experiences with STGS: approachability, visual, operability, function, offline service, and interactivity. The third phase involved an analysis of a survey of 248 participants who had used STGS in the Chinese four STDs to verify the influencing factors. By using the method of linear regression analysis, we found that approachability, visual, operability, function and offline service have a significant impact on tourists’ experiences with STGS while interactivity contributes little impact to tourists’ experiences with STGS. The findings will be useful for STDs to explore and promote STGS services, as well as enhancing tourists’ smart experiences with STTs. Full article
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20 pages, 1586 KiB  
Systematic Review
Digital Bicycling Planning: A Systematic Literature Review of Data-Driven Approaches
by Parisa Zare, Christopher Pettit, Simone Leao and Ori Gudes
Sustainability 2022, 14(23), 16319; https://doi.org/10.3390/su142316319 - 6 Dec 2022
Cited by 2 | Viewed by 2104
Abstract
To increase the amount of bicycling as a mode of transport, many countries are developing placed based bicycling plans and strategies. However, this approach necessitates considering a fine-scale mapping of bicycling patterns and a detailed description of urban spaces. The rise of new [...] Read more.
To increase the amount of bicycling as a mode of transport, many countries are developing placed based bicycling plans and strategies. However, this approach necessitates considering a fine-scale mapping of bicycling patterns and a detailed description of urban spaces. The rise of new data and technologies offers much promise to planners and researchers to access diverse and richer sources of information to optimise the bicycling network design. This review aims to comprehensively examine the role of data and technology in bicycling planning, historical changes in using data-driven approaches, and current domains in the existing body of research in bicycling planning from 1990 to 2021. For this, a systematic literature review has been conducted according to PRISMA framework. A total number of 1022 studies was analysed and synthesised with the VOS Viewer and CiteSpace platforms. Upon completing the review, we extracted the most-used datasets, tools, and methodologies. The results of the systematic review reveal three evolutionary phases in using data-driven approaches from 1990 to 1999, 2000 to 2009, and 2010 to 2021. In addition, we identified six knowledge domains in using data-driven approaches in bicycling planning that is (i) smart city, (ii) infrastructure, (iii) built environment, (iv) decision making, (v) people, and (vi) safety. Full article
(This article belongs to the Special Issue Integrating Sustainable Transport and Urban Design for Smart Cities)
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27 pages, 7781 KiB  
Article
Development of a Fuzzy Inference System Based Rapid Visual Screening Method for Seismic Assessment of Buildings Presented on a Case Study of URM Buildings
by Nurullah Bektaş, Ferenc Lilik and Orsolya Kegyes-Brassai
Sustainability 2022, 14(23), 16318; https://doi.org/10.3390/su142316318 - 6 Dec 2022
Cited by 6 | Viewed by 1672
Abstract
Many conventional rapid visual screening (RVS) methods for the seismic assessment of existing structures have been designed over the past three decades, tailored to site-specific building features. The objective of implementing RVS is to identify the buildings most susceptible to earthquake-induced damage. RVS [...] Read more.
Many conventional rapid visual screening (RVS) methods for the seismic assessment of existing structures have been designed over the past three decades, tailored to site-specific building features. The objective of implementing RVS is to identify the buildings most susceptible to earthquake-induced damage. RVS methods are utilized to classify buildings according to their risk level to prioritize the buildings at high seismic risk. The conventional RVS methods are employed to determine the damage after an earthquake or to make safety assessments in order to predict the damage that may occur in a building before an impending earthquake. Due to the subjectivity of the screener based on visual examination, previous research has shown that these conventional methods can lead to vagueness and uncertainty. Additionally, because RVS methods were found to be conservative and to be partially accurate, as well as the fact that some expert opinion based developed RVS techniques do not have the capability of further enhancement, it was recommended that RVS methods be developed. Therefore, this paper discusses a fuzzy logic based RVS method development to produce an accurate building features responsive examination method for unreinforced masonry (URM) structures, as well as a way of revising existing RVS methods. In this context, RVS parameters are used in a fuzzy-inference system hierarchical computational pattern to develop the RVS method. The fuzzy inference system based RVS method was developed considering post-earthquake building screening data of 40 URM structures located in Albania following the earthquake in 2019 as a case study. In addition, FEMA P-154, a conventional RVS method, was employed to screen considered buildings to comparatively demonstrate the efficiency of the developed RVS method in this study. The findings of the study revealed that the proposed method with an accuracy of 67.5% strongly outperformed the conventional RVS method by 42.5%. Full article
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20 pages, 1142 KiB  
Article
Solar and Wind Energy Forecasting for Green and Intelligent Migration of Traditional Energy Sources
by Syed Muhammad Mohsin, Tahir Maqsood and Sajjad Ahmed Madani
Sustainability 2022, 14(23), 16317; https://doi.org/10.3390/su142316317 - 6 Dec 2022
Cited by 5 | Viewed by 2102
Abstract
Fossil-fuel-based power generation leads to higher energy costs and environmental impacts. Solar and wind energy are abundant important renewable energy sources (RES) that make the largest contribution to replacing fossil-fuel-based energy consumption. However, the uncertain solar radiation and highly fluctuating weather parameters of [...] Read more.
Fossil-fuel-based power generation leads to higher energy costs and environmental impacts. Solar and wind energy are abundant important renewable energy sources (RES) that make the largest contribution to replacing fossil-fuel-based energy consumption. However, the uncertain solar radiation and highly fluctuating weather parameters of solar and wind energy require an accurate and reliable forecasting mechanism for effective and efficient load management, cost reduction, green environment, and grid stability. From the existing literature, artificial neural networks (ANN) are a better means for prediction, but the ANN-based renewable energy forecasting techniques lose prediction accuracy due to the high uncertainty of input data and random determination of initial weights among different layers of ANN. Therefore, the objective of this study is to develop a harmony search algorithm (HSA)-optimized ANN model for reliable and accurate prediction of solar and wind energy. In this study, we combined ANN with HSA and provided ANN feedback for its weights adjustment to HSA, instead of ANN. Then, the HSA optimized weights were assigned to the edges of ANN instead of random weights, and this completes the training of ANN. Extensive simulations were carried out and our proposed HSA-optimized ANN model for solar irradiation forecast achieved the values of MSE = 0.04754, MAE = 0.18546, MAPE = 0.32430%, and RMSE = 0.21805, whereas our proposed HSA-optimized ANN model for wind speed prediction achieved the values of MSE = 0.30944, MAE = 0.47172, MAPE = 0.12896%, and RMSE = 0.55627. Simulation results prove the supremacy of our proposed HSA-optimized ANN models compared to state-of-the-art solar and wind energy forecasting techniques. Full article
(This article belongs to the Special Issue Smart Grid Analytics for Sustainability and Urbanization in Big Data)
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22 pages, 7234 KiB  
Article
Spatial Performance Measurement and the Resource Organization Mechanism of Rural Tourism Resources in Developing Countries: A Case Study on Jilin Province, China
by Xue Jiang, Nan Li and Shuhan Man
Sustainability 2022, 14(23), 16316; https://doi.org/10.3390/su142316316 - 6 Dec 2022
Cited by 2 | Viewed by 1463
Abstract
Many developing countries are challenged with the revival of rural vitality against increasing urbanization. Rural tourism is effective in enhancing the countryside’s vitality. Previous studies used qualitative methods to explore the spatial organization of resources, but it was difficult to quantify the effective [...] Read more.
Many developing countries are challenged with the revival of rural vitality against increasing urbanization. Rural tourism is effective in enhancing the countryside’s vitality. Previous studies used qualitative methods to explore the spatial organization of resources, but it was difficult to quantify the effective organization of tourism resources. Taking the example of Jilin Province, China, this study quantitatively measured the use of tourism resources in rural areas at the initial stage and created a developmental model to organize tourism resources more effectively. The organization mechanism has specific reference significance for the optimization model of upgrading rural tourism in developing countries. Spatial performance measurement was used to evaluate the spatial performance of rural tourism resources in the case area. The specific research included analyzing the coupling mechanism of rural tourism resources, constructing an evaluation system, analyzing a resource regulation mechanism, and establishing a rural tourism network model through a complex network analysis method and dynamic simulation. According to the spatial performance analysis, the allocation and linkage of various tourism-related elements are not yet mature. The structural restructuring mode in Jilin Province is mainly divided into internal and external dual-drive guidance, secondary integration, and a characteristic linkage mode. An organizational mechanism for optimizing tourism resources was proposed, which could be referred to for evaluating and optimally organizing the tourism resources in the rural areas of developing countries. Full article
(This article belongs to the Section Tourism, Culture, and Heritage)
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16 pages, 296 KiB  
Article
Expanding Formal School Curricula to Foster Action Competence in Sustainable Development: A Proposed Free-Choice Project-Based Learning Curriculum
by Mahima Kalla, Micheal Jerowsky, Benjamin Howes and Ann Borda
Sustainability 2022, 14(23), 16315; https://doi.org/10.3390/su142316315 - 6 Dec 2022
Cited by 2 | Viewed by 2491
Abstract
A key determinant and outcome of successful environmental education is ‘pro-environmental behavior’, i.e., behavior that involves conscious action to mitigate adverse environmental impacts at personal or community level, e.g., reducing resource consumption and waste generation, avoiding toxic substances, and organizing community awareness initiatives. [...] Read more.
A key determinant and outcome of successful environmental education is ‘pro-environmental behavior’, i.e., behavior that involves conscious action to mitigate adverse environmental impacts at personal or community level, e.g., reducing resource consumption and waste generation, avoiding toxic substances, and organizing community awareness initiatives. However, some theorists have sought to move away from rationalist models of behavioral modification, towards holistic pedagogical initiatives that seek to develop action competence. In light of the global push towards achievement of the Sustainable Development Goals (SDGs), emerging evidence suggests that education initiatives should foster action competence so students may be equipped to contribute to sustainable development as part of their education. The UNESCO Education for Sustainable Development (ESD) Roadmap 2030 has also identified key priority areas to strengthen ESD in formal curricula. This article reports two informal environmental education initiatives for promoting action competence and pro-environmental behaviors in school-aged children. The authors recommend that formal education settings (e.g., schools) should incorporate self-directed, free-choice project-based learning to augment environmental education programs and promote students’ action competence for contribution to attainment of SDGs. To this end, we propose a Free-Choice Project-based Learning for Action Competence in Sustainable Development (ACiSD) Curriculum, comprising six implementation dimensions, namely: (1) project duration and teaming arrangements, (2) topic selection, (3) student support, (4) teacher support, (5) learning environments, and (6) digital access and equity. For each implementation dimension, we recommend action steps to help educators implement this curriculum in their own educational settings, with the aid of an illustrative worked example. Full article
(This article belongs to the Special Issue Nature and Well-Being Science: Environments for Thriving)
21 pages, 5413 KiB  
Article
Spatial Heterogeneity Analysis for Influencing Factors of Outbound Ridership of Subway Stations Considering the Optimal Scale Range of “7D” Built Environments
by Zhenbao Wang, Jiarui Song, Yuchen Zhang, Shihao Li, Jianlin Jia and Chengcheng Song
Sustainability 2022, 14(23), 16314; https://doi.org/10.3390/su142316314 - 6 Dec 2022
Cited by 6 | Viewed by 1762
Abstract
The accuracy of the regression model of ridership of subway stations depends on the scale range of the built environment around the subway stations. Previous studies have not considered the Modifiable Area Unit Problem (MAUP) to establish the regression model of subway station [...] Read more.
The accuracy of the regression model of ridership of subway stations depends on the scale range of the built environment around the subway stations. Previous studies have not considered the Modifiable Area Unit Problem (MAUP) to establish the regression model of subway station ridership. Taking Beijing as an example, this paper expanded the built environment variables from “5D” category to “7D” category, added indicators such as parking fee standard and population density factor, and proposed a Multi-Scale Geographical Weighted Regression (MGWR) model of outbound ridership of subway stations with standardized variables. The goodness of fit of regression models under 10 spatial scales or built environment around subway stations are compared, and the spatial heterogeneity of built environment factors under the optimal spatial scale of outbound ridership of subway stations during the morning peak on weekdays is discussed. The results show that: (1) the scale range overlapped by 1000 m radius circular buffer zone and Thiessen polygon has the highest explanatory power for the regression model, and is regarded as the optimal scale range of built environment; (2) the density of office facilities, sports and leisure facilities, medical service facilities, building density and floor area ratio (FAR) has a significant impact on the outbound ridership of all subway stations; (3) office facilities, catering facilities, FAR, number of parking lots, and whether subway stations are transfer stations have a positive impact on outbound ridership. The number of medical service facilities, sports and leisure facilities, bus stops and building density have a negative impact on outbound ridership; (4) the two added factors in this study: parking charge standard and population density, as the influencing factors of the built environment, have a significant impact on the outbound ridership of some subway stations; and (5) the different local coefficients of the built environment factors at different stations are discussed, which indicate the spatial heterogeneity on the outbound ridership. The results can provide an important theoretical basis for the prediction and analysis of demand of ridership at subway stations and the integration of the built environment around the stations. Full article
(This article belongs to the Special Issue Urban and Social Geography and Sustainability)
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23 pages, 6990 KiB  
Article
Spatiotemporal Variations of Air Pollution during the COVID-19 Pandemic across Tehran, Iran: Commonalities with and Differences from Global Trends
by Mohsen Maghrebi, Ali Danandeh Mehr, Seyed Mohsen Karrabi, Mojtaba Sadegh, Sadegh Partani, Behzad Ghiasi and Vahid Nourani
Sustainability 2022, 14(23), 16313; https://doi.org/10.3390/su142316313 - 6 Dec 2022
Viewed by 1916
Abstract
The COVID-19 pandemic has induced changes in global air quality, mostly short-term improvements, through worldwide lockdowns and restrictions on human mobility and industrial enterprises. In this study, we explored the air pollution status in Tehran metropolitan, the capital city of Iran, during the [...] Read more.
The COVID-19 pandemic has induced changes in global air quality, mostly short-term improvements, through worldwide lockdowns and restrictions on human mobility and industrial enterprises. In this study, we explored the air pollution status in Tehran metropolitan, the capital city of Iran, during the COVID-19 outbreak. To this end, ambient air quality data (CO, NO2, O3, PM10, SO2, and AQI) from 14 monitoring stations across the city, together with global COVID-19-related records, were utilized. The results showed that only the annual mean concentration of SO2 increased during the COVID-19 pandemic, mainly due to burning fuel oil in power plants. The findings also demonstrated that the number of days with a good AQI has significantly decreased during the pandemic, despite the positive trend in the global AQI. Based on the spatial variation of the air quality data across the city, the results revealed that increasing pollution levels were more pronounced in low-income regions. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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17 pages, 1670 KiB  
Article
Impact of High-Speed Rail on Spatial Structure in Prefecture-Level Cities: Evidence from the Central Plains Urban Agglomeration, China
by Xiaomin Wang, Jingyu Liu and Wenxin Zhang
Sustainability 2022, 14(23), 16312; https://doi.org/10.3390/su142316312 - 6 Dec 2022
Cited by 5 | Viewed by 1379
Abstract
The impact of high-speed rail (HSR) on urban spatial structure has attracted much attention since the 1970s. It mainly realizes the change of urban spatial structure by affecting the spatial distribution of population and economy. Based on population and industry data on 29 [...] Read more.
The impact of high-speed rail (HSR) on urban spatial structure has attracted much attention since the 1970s. It mainly realizes the change of urban spatial structure by affecting the spatial distribution of population and economy. Based on population and industry data on 29 cities in the Central Plains Urban Agglomeration (CPUA) located in central China during 2005–2017, in this paper difference-in-difference (DID) models are utilized to explore the influence of HSR on the spatial structure of prefecture-level cities at the single/multicenter levels according to the dimensions of polycentricity and dispersion. The main conclusions are shown as: (1) HSR on the spatial structure of the CPUA has a monocentric trend, but the characteristics of different prefecture-level cities vary. Currently, agglomeration remains the dominant force of the spatial structure of the CPUA in prefecture-level cities. (2) HSR have a noticeable effect on the spatial structure of industry, whereas the influences of the HSR on the spatial structure of the population are insignificant. Its development is the result of the combined effects of many factors, including natural factors, socioeconomic factors, policies, and transportation factors. Among the controlling factors, the administrative area, economic development level, urban population, and number of research units are the critical factors having a hold on the population spatial structure of the CPUA. Full article
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22 pages, 11626 KiB  
Article
A Deep Learning Semantic Segmentation Method for Landslide Scene Based on Transformer Architecture
by Zhaoqiu Wang, Tao Sun, Kun Hu, Yueting Zhang, Xiaqiong Yu and Ying Li
Sustainability 2022, 14(23), 16311; https://doi.org/10.3390/su142316311 - 6 Dec 2022
Cited by 4 | Viewed by 2181
Abstract
Semantic segmentation technology based on deep learning has developed rapidly. It is widely used in remote sensing image recognition, but is rarely used in natural disaster scenes, especially in landslide disasters. After a landslide disaster occurs, it is necessary to quickly carry out [...] Read more.
Semantic segmentation technology based on deep learning has developed rapidly. It is widely used in remote sensing image recognition, but is rarely used in natural disaster scenes, especially in landslide disasters. After a landslide disaster occurs, it is necessary to quickly carry out rescue and ecological restoration work, using satellite data or aerial photography data to quickly analyze the landslide area. However, the precise location and area estimation of the landslide area is still a difficult problem. Therefore, we propose a deep learning semantic segmentation method based on Encoder-Decoder architecture for landslide recognition, called the Separable Channel Attention Network (SCANet). The SCANet consists of a Poolformer encoder and a Separable Channel Attention Feature Pyramid Network (SCA-FPN) decoder. Firstly, the Poolformer can extract global semantic information at different levels with the help of transformer architecture, and it greatly reduces computational complexity of the network by using pooling operations instead of a self-attention mechanism. Secondly, the SCA-FPN we designed can fuse multi-scale semantic information and complete pixel-level prediction of remote sensing images. Without bells and whistles, our proposed SCANet outperformed the mainstream semantic segmentation networks with fewer model parameters on our self-built landslide dataset. The mIoU scores of SCANet are 1.95% higher than ResNet50-Unet, especially. Full article
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17 pages, 713 KiB  
Article
“We Like That It Matters!”: Towards a Socially Sustainable Retail Store Brand Experience
by Alessia Grassi
Sustainability 2022, 14(23), 16310; https://doi.org/10.3390/su142316310 - 6 Dec 2022
Cited by 1 | Viewed by 2033
Abstract
Social sustainability is a topic that is gaining increased attention and yet has not been overly discussed, in particular with reference to the fashion industry. There is a shift in consumer demands, where brands are urged to stand for values, affect change in [...] Read more.
Social sustainability is a topic that is gaining increased attention and yet has not been overly discussed, in particular with reference to the fashion industry. There is a shift in consumer demands, where brands are urged to stand for values, affect change in the industry, and have a clear purpose and positive impact over society. At the same time, brands are struggling to provide offers beyond products, or product-related experiences, at the risk of dissatisfying consumers expectations. Part of such dissatisfaction is clearly represented by the lack of footfall in retail stores and the fast-pace abandonment of the high-street by brands that cannot afford empty stores. This paper suggests an opportunity to rethink the retail store functionality as a space for brands to provide consumers with educational initiatives related to important societal issues, hence build their socially responsible profile. A netnographic exploratory analysis of Patagonia platforms was conducted in order to pinpoint potential positive reaction to a purpose-driven brand and its educational initiatives. The brand was chosen due to its value-committed strategy and constant educational effort towards consumers, both offline (product-related) and online (societal-related). This paper suggests that brands such as Patagonia, purpose and value driven in positively impacting society, should bring their activism and educational efforts on the high-street and in the retail spaces. By doing so, brands would concurrently provide consumers with experiences beyond product consumption, could revitalise our high-street, and could reinstate a sense of community belonging while raise their socially sustainable profile. This paper contributes to the existing literature of consumer education in retailing by expanding into the specific domain of fashion, a domain in which many social issues could be successfully addressed through a socially-driven consumer education at the moment still overlooked by researchers and brands. Full article
13 pages, 2383 KiB  
Article
Regime Shifts in the Hexi Oases over the Past Three Decades: The Case of the Linze Oasis in the Middle Reaches of the Heihe River
by Jinglin Zhang, Wei Zhang, Dongsheng Li, Xueliang Chen and Wei Zhang
Sustainability 2022, 14(23), 16309; https://doi.org/10.3390/su142316309 - 6 Dec 2022
Viewed by 1202
Abstract
Oases regime shifts in the context of integrated water resource management have a significant impact on ecosystem functions and services and affect regional sustainable development and human wellbeing. Taking the Linze Oasis in the middle reaches of the Heihe River as a case [...] Read more.
Oases regime shifts in the context of integrated water resource management have a significant impact on ecosystem functions and services and affect regional sustainable development and human wellbeing. Taking the Linze Oasis in the middle reaches of the Heihe River as a case study, we evaluated the regime shifts of the oases over the past 30 years from the two perspectives of scale and structure, considering the structural diversity index (H), water savings (Cn), productivity (WP), and other indicators. Furthermore, the driving factors of the socio-hydrological processes and the corresponding effects of the regime stages were discussed. The results indicate that the oases expanded concurrently with the increase in the regional water consumption from 1.09 × 108 m3 to 1.93 × 108 m3. The production of low-water-consumption and high-yield crops was found to be the main cause for the oases structure’s adjustment. The regime shifts in the oases comprised three main stages from 1990 to 2020, based on the interaction of socio-ecological elements. Water management policies promoted the regime shift process, while economic factors determined the long-term shifts. The improvement in water-saving practices driven by economic benefits is an effective way to realize the sustainable development of the Hexi oases. Full article
(This article belongs to the Section Sustainable Water Management)
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109 pages, 17398 KiB  
Review
Smart Distribution Mechanisms—Part I: From the Perspectives of Planning
by Shahid Nawaz Khan, Syed Ali Abbas Kazmi, Abdullah Altamimi, Zafar A. Khan and Mohammed A. Alghassab
Sustainability 2022, 14(23), 16308; https://doi.org/10.3390/su142316308 - 6 Dec 2022
Cited by 4 | Viewed by 3166
Abstract
To enhance the reliability and resilience of power systems and achieve reliable delivery of power to end users, smart distribution networks (SDNs) play a vital role. The conventional distribution network is transforming into an active one by incorporating a higher degree of automation. [...] Read more.
To enhance the reliability and resilience of power systems and achieve reliable delivery of power to end users, smart distribution networks (SDNs) play a vital role. The conventional distribution network is transforming into an active one by incorporating a higher degree of automation. Replacing the traditional absence of manual actions, energy delivery is becoming increasingly dependent on intelligent active system management. As an emerging grid modernization concept, the smart grid addresses a wide range of economic and environmental concerns, especially by integrating a wide range of active technologies at distribution level. At the same time, these active technologies are causing a slew of technological problems in terms of power quality and stability. The development of such strategies and approaches that can improve SDN infrastructure in terms of planning, operation, and control has always been essential. As a result, a substantial number of studies have been conducted in these areas over the last 10–15 years. The current literature lacks a combined systematic analysis of the planning, operation, and control of SDN technologies. This paper conducts a systematic survey of the state-of-the-art advancements in SDN planning, operation, and control over the last 10 years. The reviewed literature is structured so that each SDN technology is discussed sequentially from the viewpoints of planning, operation, and then control. A comprehensive analysis of practical SND concepts across the globe is also presented in later sections. The key constraints and future research opportunities in the existing literature are discussed in the final part. This review specifically assists readers in comprehending current trends in SDN planning, operation, and control, as well as identifying the need for further research to contribute to the field. Full article
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20 pages, 1679 KiB  
Article
DCKT: A Novel Dual-Centric Learning Model for Knowledge Tracing
by Yixuan Chen, Shuang Wang, Fan Jiang, Yaxin Tu and Qionghao Huang
Sustainability 2022, 14(23), 16307; https://doi.org/10.3390/su142316307 - 6 Dec 2022
Cited by 3 | Viewed by 1724
Abstract
Knowledge tracing (KT), aiming to model learners’ mastery of a concept based on their historical learning records, has received extensive attention due to its great potential in realizing personalized learning in intelligent tutoring systems. However, most existing KT methods focus on a single [...] Read more.
Knowledge tracing (KT), aiming to model learners’ mastery of a concept based on their historical learning records, has received extensive attention due to its great potential in realizing personalized learning in intelligent tutoring systems. However, most existing KT methods focus on a single aspect of knowledge or learner, not paying careful attention to the coupling influence of knowledge and learner characteristics. To fill this gap, in this paper, we explore a new paradigm for the KT task by exploiting the coupling influence of knowledge and learner. A novel model called Dual-Centric Knowledge Tracing (DCKT) is proposed to model knowledge states through two joint tasks of knowledge modeling and learner modeling. In particular, we first generate concept embeddings in abundant knowledge structure information via a pretext task (knowledge-centric): unsupervised graph representation learning. Then, we deeply measure learners’ prior knowledge the knowledge-enhanced representations and three predefined educational priors for discriminative feature enhancement. Furthermore, we design a forgetting-fusion transformer (learner-centric) to simulate the declining trend of learners’ knowledge proficiency over time, representing the common forgetting phenomenon. Extensive experiments were conducted on four public datasets, and the results demonstrate that DCKT could achieve better knowledge tracing results over all datasets via a dual-centric modeling process. Additionally, DCKT can learn meaningful question embeddings automatically without manual annotations. Our work indicates a potential future research direction for personalized learner modeling, which is of both accuracy and high interpretability. Full article
(This article belongs to the Collection Science Education Promoting Sustainability)
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17 pages, 2316 KiB  
Article
H2O2-Enhanced As(III) Removal from Natural Waters by Fe(III) Coagulation at Neutral pH Values and Comparison with the Conventional Fe(II)-H2O2 Fenton Process
by Stefanos Koutzaris, Maria Xanthopoulou, Asterios Laskaridis and Ioannis A. Katsoyiannis
Sustainability 2022, 14(23), 16306; https://doi.org/10.3390/su142316306 - 6 Dec 2022
Cited by 3 | Viewed by 1264
Abstract
Arsenic is a naturally occurring contaminant in waters, which is toxic and adversely affects human health. Therefore, treatment of water for arsenic removal is very important production of safe drinking water. Coagulation using Fe(III) salts is the most frequently applied technology for arsenic [...] Read more.
Arsenic is a naturally occurring contaminant in waters, which is toxic and adversely affects human health. Therefore, treatment of water for arsenic removal is very important production of safe drinking water. Coagulation using Fe(III) salts is the most frequently applied technology for arsenic removal, but is efficient mostly for As(V) removal. As(III) removal usually requires the application of a pre-oxidation step, which is mainly conducted by chemical or biological means. In this study, we show that Fe(III) coagulation in the presence of H2O2 can be a very efficient treatment process for As(III) removal, which has been never been shown before in the literature. The results showed that addition of 8.7–43.7 mM hydrogen peroxide to Fe(III) coagulation process was able to increase the effectiveness of As(III) removal in synthetic groundwater by 15–20% providing residual concentrations well below the regulatory limit of 10 μg/L from initial As(III) concentrations of 100 μg/L, at pH 7. The enhanced coagulation process was affected by the solution pH. The removal efficiency substantially declined at alkaline pH values (pH > 8). Addition of EDTA in the absence of H2O2 had a strong inhibiting effect where the As(III) removal was almost zero when 88.38 μΜ EDTA were used. Radical quenching experiments with 50, 100 and 200 mM DMSO, methanol and 2-propanol in the H2O2-coagulation process had a slightly adverse effect on the removal efficiency. This is considered as indicative of an adsorption/oxidation of As(III) process onto or very near the surface of iron oxide particles, formed by the hydrolysis of Ferric iron ions. In practice, the results suggest that addition of H2O2 increases the As(III) removal efficiency for Fe(III) coagulation systems. This is an important finding because the pre-oxidation step can be omitted with the addition of H2O2 while treating water contaminated with As(III). Full article
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20 pages, 924 KiB  
Review
Blockchain, Data Protection and P2P Energy Trading: A Review on Legal and Economic Challenges
by Alessandra Chiarini and Lorenzo Compagnucci
Sustainability 2022, 14(23), 16305; https://doi.org/10.3390/su142316305 - 6 Dec 2022
Cited by 6 | Viewed by 3002
Abstract
Blockchain technology (BCT) enables the automated execution of smart contracts in peer-to-peer (P2P) energy trading. BCT-based P2P platforms allow the sharing, exchange and trade of energy among consumers or prosumers as peers, fostering the decarbonization, decentralization and digitalization of the energy industry. On [...] Read more.
Blockchain technology (BCT) enables the automated execution of smart contracts in peer-to-peer (P2P) energy trading. BCT-based P2P platforms allow the sharing, exchange and trade of energy among consumers or prosumers as peers, fostering the decarbonization, decentralization and digitalization of the energy industry. On the other hand, BCT-based P2P energy trading relies on the collection, storage and processing of a large amount of user data, posing interdisciplinary challenges, including user anonymity, privacy, the governance of BCT systems and the role of energy market players. First, this paper seeks to review the state of the art of European data protection law and regulations by focusing on BCT compliance with the General Data Protection Regulation (GDPR) of 2018. Second, it explores both the potentials and the challenges of BCT-based P2P energy trading from a legal–economic perspective. To do so, the paper adopts an interdisciplinary approach which intertwines both law and economics, by reviewing the recent literature on BCT and P2P energy trading. Findings have revealed that the deployment of BCT-based P2P energy trading is still in its pilot stage because of technology immaturity, data protection uncertainty, incomplete disintermediation and the lack of both user awareness and collaboration among market players. Drawing on the review, the paper also proposes a selection of solutions to foster the implementation of BCT-based P2P energy trading. Full article
(This article belongs to the Collection Blockchain Technology)
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18 pages, 8330 KiB  
Article
Evaluating Environmental Quality and Its Driving Force in Northeastern China Using the Remote Sensing Ecological Index
by Enjun Gong, Fangxin Shi, Zhihui Wang, Qingfeng Hu, Jing Zhang and Hongxin Hai
Sustainability 2022, 14(23), 16304; https://doi.org/10.3390/su142316304 - 6 Dec 2022
Cited by 7 | Viewed by 2089
Abstract
As one of the three major black soil regions in the world, northeastern China has an important strategic position there. Since the 20th century, the local environment has undergone great changes under the influence of the natural economy, and it is particularly important [...] Read more.
As one of the three major black soil regions in the world, northeastern China has an important strategic position there. Since the 20th century, the local environment has undergone great changes under the influence of the natural economy, and it is particularly important to quantitatively assess the degree of change. However, there have been few long-term quantitative studies of environmental spatial-temporal variances in the three northeastern provinces. Therefore, in this study, four typical remote sensing indices of the normalized difference vegetation index (NDVI), land surface temperature (LST), normalized differential building–soil index (NDBSI) and wetness (WET) were employed to construct the remote sensing ecological index (RSEI) using a principal component analysis (PCA) method based on the Google Earth Engine (GEE) platform in northeastern China. The spatiotemporal variations in the eco-environmental quality were detected using linear slope and M–K test, and the direct and interactive effects of different influencing factors on the RSEI changes during 2000–2020 were explored based on geographic detection. The results show that the interannual variations in the RSEI show a fluctuating upward trend, with an increase percentage of 12.45% in the last two decades, indicating that the ecological quality of northeast China has gradually improved. Furthermore, that the western and eastern Heilongjiang provinces and western Jilin provinces contributed substantially to the improvement of environmental quality, while the environmental quality of Jilin provinces and central Liaoning provinces decreased to varying degrees. Compared with 2000, the area with a fair environmental quality grade had the greatest change, and had decreased by 60.69%. This was followed by the area with an excellent quality grade, which increased by 117%. Land-use type had the greatest impact on environmental changes in northeastern China, but the impact degree gradually decreased, while the impact of socioeconomic factors such as the gross production of agriculture, forestry, animal husbandry and fishery and population density on environmental quality gradually increased. The major reason for the decline of environmental quality in central Jilin and central Liaoning is that urbanization development had occupied a large amount of cropland. This shows that taking into account the virtuous cycle of an ecological environment while promoting urban and rural development may be an important task for northeastern China in the future. Full article
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17 pages, 269 KiB  
Article
Corporate Communication of CSR in China: Characteristics and Regional Differences
by Ruixin Su and Weizhou Zhong
Sustainability 2022, 14(23), 16303; https://doi.org/10.3390/su142316303 - 6 Dec 2022
Cited by 2 | Viewed by 2949
Abstract
This article investigates CSR issues publicized by websites, annual reports, and social responsibility reports by companies in mainland China from the perspective of corporate communication. The empirical study is surrounded by issues about the motives of CSR, the content of CSR, and the [...] Read more.
This article investigates CSR issues publicized by websites, annual reports, and social responsibility reports by companies in mainland China from the perspective of corporate communication. The empirical study is surrounded by issues about the motives of CSR, the content of CSR, and the applications of stakeholders. Empirical tests are distinguished by CSR motives, characteristics, and stakeholder issues for companies from Eastern, Central, and Western regions. Our research results indicate that although corporate social responsibility implementation and communication in China have made great progress compared with the past, there are still problems, such as the incomplete implementation of CSR, unbalanced communication of CSR, and lack of integrity and pertinence. Enterprises in different regions are affected by the degree of local economic development, social development environment, and government intervention, which leads to obvious differences in geographical and political attributes of enterprises in different regions in communicating social responsibility. This article focuses on the impact of institutional (consists formal and informal) and regional influencing factors on CSR communication. Therefore, political, cultural, and regional differences are expected to be conducted by corporate culture and government policy in future CSR activities. Full article
20 pages, 698 KiB  
Article
Stakeholder Pressure Engaged with Circular Economy Principles and Economic and Environmental Performance
by Juan Cristóbal Hernández-Arzaba, Sarfraz Nazir, Sandra Nelly Leyva-Hernández and Sanar Muhyaddin
Sustainability 2022, 14(23), 16302; https://doi.org/10.3390/su142316302 - 6 Dec 2022
Cited by 2 | Viewed by 2614
Abstract
The study aims to investigate the impacts of internal and external stakeholder pressures on the adoption of circular economy (CE) principles. The study explores the primary barriers to and causes (external or internal stakeholder pressures) of CE’s transition across Mexico and explores the [...] Read more.
The study aims to investigate the impacts of internal and external stakeholder pressures on the adoption of circular economy (CE) principles. The study explores the primary barriers to and causes (external or internal stakeholder pressures) of CE’s transition across Mexico and explores the effects of stakeholder pressures (internal and external) on the adoption of CE principles on economic and environmental performance. For this, data were collected from 433 respondents using a structured questionnaire. For analysis, the study used the PLS-SEM technique to examine internal and external stakeholders as barriers and motivators of economic and environmental performance through CE principles. Both the structural model and the measurement model were assessed. As well as mediation analysis, the direct and indirect effects were determined. The study found that economic (β = 0.178, p = 0.000) and environmental performance (β = 0.233, p = 0.000) is affected by most external stakeholders through the adoption of circular economy principles. Although the internal stakeholders don’t affect the environmental performance (β = 0.040, p = 0.492), with the adoption of circular economy principles mediating the relationship, internal stakeholders encourage environmental performance (β = 0.201, p = 0.000). The study motivates the public, non-governmental organisations (NGOs) and the government to adopt CE principles for the achievement of economic and environmental performance and participation in the sustainable development agenda. Full article
(This article belongs to the Special Issue Circular Economy, Sustainable Production and Consumption)
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15 pages, 884 KiB  
Article
The COVID-19 Pandemic Response and Its Impact on Post-Pandemic Health Emergency and Disaster Risk Management in the United States
by Allison P. Chen, Bhakti Hansoti and Edbert B. Hsu
Sustainability 2022, 14(23), 16301; https://doi.org/10.3390/su142316301 - 6 Dec 2022
Cited by 4 | Viewed by 2957
Abstract
Among the impacts of the Coronavirus Disease 2019 (COVID-19) pandemic on the public health system in the United States has been a reevaluation of emergency response systems and procedures. This study uses publicly available literature from government, private sector, and academic sources to [...] Read more.
Among the impacts of the Coronavirus Disease 2019 (COVID-19) pandemic on the public health system in the United States has been a reevaluation of emergency response systems and procedures. This study uses publicly available literature from government, private sector, and academic sources to identify changes and lessons learned during the COVID-19 pandemic in specific aspects of emergency response, namely human resources, health service delivery, and logistics, determined based on the World Health Organization Health Emergency and Disaster Risk Management (WHO Health EDRM) Framework. Major themes of changes implemented include those intended to increase mobility and flexibility of workforce and resources, integration of various parts of the health system, and effective communication, and are anticipated to be incorporated into response systems going forward. Full article
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25 pages, 8681 KiB  
Article
Effective Utilization of Copper Slag for the Production of Geopolymer Concrete with Different NaOH Molarity under Ambient Curing Conditions
by Nagarajan Arunachelam, Jeyaprakash Maheswaran, Maheswaran Chellapandian and Togay Ozbakkaloglu
Sustainability 2022, 14(23), 16300; https://doi.org/10.3390/su142316300 - 6 Dec 2022
Cited by 10 | Viewed by 1817
Abstract
In spite of the considerable research on the mechanical and durability properties of geopolymer concrete, its widespread applicability is hindered due to the difficulties involved in achieving ambient curing conditions and awareness of the effective utilization of industrial by-products. This study investigates the [...] Read more.
In spite of the considerable research on the mechanical and durability properties of geopolymer concrete, its widespread applicability is hindered due to the difficulties involved in achieving ambient curing conditions and awareness of the effective utilization of industrial by-products. This study investigates the physical and microstructure characterization of sustainable geopolymer concrete (GPC) developed with copper slag as a replacement for fine aggregate. In total, forty-four geopolymer concrete mixtures were prepared to examine their fresh and hardened properties. Four different NaOH molarities (10, 12, 14 and 16) and the replacement levels of copper slag, ranging from 0 to 100% with an increase of 10%, were considered as variables in this research. The study parameters examined includes the fresh (slump) and hardened concrete properties. Additionally, the microstructural characterization for different mixes were studied using the Fourier Transform Infrared Spectroscopy (FTIR), Electron Dispersive Spectrum (EDS) analyses and Scanning Electron Microscope (SEM). Results indicated that replacing fine aggregate with copper slag up to 100% showed no strength reduction. Increasing the molarity of the NaOH solution to 16M led to an increased strength of about 35% compared to the concrete with 10 M in all the mixes. The microstructural analysis performed using SEM/EDS and FTIR showed that a cohesive and fully compact geopolymer matrix was achieved together with the use of low-calcium fly ash and copper slag under ambient curing conditions. Full article
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15 pages, 958 KiB  
Article
A Two-Stage Deep-Learning Model for Link Prediction Based on Network Structure and Node Attributes
by Peng Liu, Liang Gui, Huirong Wang and Muhammad Riaz
Sustainability 2022, 14(23), 16299; https://doi.org/10.3390/su142316299 - 6 Dec 2022
Cited by 1 | Viewed by 1728
Abstract
Link prediction, which is used to identify the potential relationship between nodes, is an important issue in network science. In existing studies, the traditional methods based on the structural similarity of nodes make it challenging to complete the task of link prediction in [...] Read more.
Link prediction, which is used to identify the potential relationship between nodes, is an important issue in network science. In existing studies, the traditional methods based on the structural similarity of nodes make it challenging to complete the task of link prediction in large-scale or sparse networks. Although emerging methods based on deep learning can solve this problem, most of the work mainly completes the link prediction through the similarity of the representation vector of network structure information. Many empirical studies show that link formation is affected by node attributes, and similarity is not the only criterion for the formation of links in reality. Accordingly, this paper proposed a two-stage deep-learning model for link prediction (i.e, TDLP), where the node representation vector of the network structure and attributes was obtained in the first stage, while link prediction was realized through supervised learning in the second stage. The empirical results on real networks showed that our model significantly outperforms the traditional methods (e.g., CN and RA), as well as newly proposed deep-learning methods (e.g., GCN and VGAE). This study not only proposed a deep-learning framework for link prediction from the perspective of structure and attribute fusion and link distribution capture, but also lays a methodological foundation for practical applications based on link prediction. Full article
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26 pages, 3151 KiB  
Article
Evaluation of the Perception and Experience of Rural Natural Landscape among Youth Groups: An Empirical Analysis from Three Villages around Hefei
by Yanlong Guo, Pengyu Chen, Han Zhang and Zuoqing Jiang
Sustainability 2022, 14(23), 16298; https://doi.org/10.3390/su142316298 - 6 Dec 2022
Cited by 4 | Viewed by 1853
Abstract
Research on the perception and evaluation degree that the rural natural landscape plays an important role in improving rural sustainable development and construction. However, the views of young people, who play a key role in social development, on the natural landscape of the [...] Read more.
Research on the perception and evaluation degree that the rural natural landscape plays an important role in improving rural sustainable development and construction. However, the views of young people, who play a key role in social development, on the natural landscape of the countryside have been neglected. Based on the perspective of the rural natural landscape in China, this study combines the field research of Ma Ying, San Shi Gang, and Shen Fu villages around Hefei, Anhui Province, and constructs a perception and experience evaluation index and questionnaire of the rural natural landscape from four dimensions of rural landscape ecology, water environment, climate, and sound. Through the online questionnaire, 316 questionnaires were distributed to young people aged 18 to 35 years old, and 283 valid questionnaires were recovered with an effective recovery rate of 89.56%. The Cronbach coefficient was 0.954, and the KMO value was 0.968. The reliability and validity were good. The analytic hierarchy process (AHP) combined with the entropy method was used to calculate the weight of each index and analyze the influencing factors of young people’s perception evaluation of the rural landscape. Firstly, young people have a good perception of rural climate conditions, but the planning and layout of rural landscape ecology need to be improved. Secondly, sound comfort, air cleanliness, and landscape adaptation in a rural environment are the key factors that affect young people’s perception and experience of rural areas. Thirdly, improving the adaptability of the rural natural landscape to the local environment and the richness of vegetation is conducive to improving young people’s favorable understanding of the rural environment. Full article
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23 pages, 2385 KiB  
Article
Consistency of Central and Regional Planning in the Agricultural Sectors and the Factors Affecting It in Indonesia
by Wahyudi, Imam Mujahidin Fahmid, Darmawan Salman and Sultan Suhab
Sustainability 2022, 14(23), 16297; https://doi.org/10.3390/su142316297 - 6 Dec 2022
Cited by 1 | Viewed by 1458
Abstract
A strategic issue in national development is the integration between national and regional planning. This research had the aims to: (1) analyse the consistency and integration between national and regional plans, (2) analyse the consistency of national and regional planning with the actual [...] Read more.
A strategic issue in national development is the integration between national and regional planning. This research had the aims to: (1) analyse the consistency and integration between national and regional plans, (2) analyse the consistency of national and regional planning with the actual implementation, and (3) analyse the factors that influenced the inconsistencies of national and regional planning in the agricultural sectors. The research was carried out by the Ministry of Agriculture (MoA), Indramayu Regency, in West Java Province and South Lampung Regency in Lampung Province. The data were analysed using both content and consistency analyses and a comparative case study. The research results showed that: (1) the level of consistency between the planning documents from the MoA and those from Indramayu Regency reached 87.68% and 95.81%, when compared with those from South Lampung Regency; (2) in terms of the consistency between the documents and the actual implementation, South Lampung Regency had programs/activities which were more integrated with the MoA programs compared with Indramayu Regency; and (3) there were five main factors which caused inconsistencies: policies from the district heads and the parties involved, force majeure, the development priorities, the communication distortion, and support from the political parties. The central government (the MoA) and the Regional Agriculture Office must collaborate by making an electronic-based priority scale of development planning and by reinforcing the capacities of regional planners. Full article
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17 pages, 2923 KiB  
Article
Experimental Investigation and Micromechanical Modeling of Hard Rock in Protective Seam Considering Damage–Friction Coupling Effect
by Chuangye Zhang, Wenyong Liu, Chong Shi, Shaobin Hu and Jin Zhang
Sustainability 2022, 14(23), 16296; https://doi.org/10.3390/su142316296 - 6 Dec 2022
Viewed by 1154
Abstract
The hard rock in the protective coal seam of the Pingdingshan Mine in China is a typical quasi-brittle material exhibiting complex mechanical characteristics. According to available research on the mechanical property, the inelastic deformation and development of damage are considered related with crack [...] Read more.
The hard rock in the protective coal seam of the Pingdingshan Mine in China is a typical quasi-brittle material exhibiting complex mechanical characteristics. According to available research on the mechanical property, the inelastic deformation and development of damage are considered related with crack initiation and propagation, which are main causes of the material degradation. In the present study, an original experimental investigation on the rock sample of the Pingdingshan coal mine is firstly carried out to obtain the basic mechanical responses in a conventional triaxial compression test. Based on the homogenization method and thermodynamic theory, a damage–friction coupled model is proposed to simulate the non-linear mechanical behavior. In the framework of micromechanics, the hard rock in a protective coal seam is viewed as a heterogeneous material composed of a homogeneous solid matrix and a large number of randomly distributed microcracks, leading to a Representative Elementary Volume (REV), i.e., the matrix–cracks system. By the use of the Mori–Tanaka homogenization scheme, the effective elastic properties of cracked material are obtained within the framework of micromechanics. The expression of free energy on the characteristic unitary is derived by homogenization methods and the pairwise thermodynamic forces associated with the inelastic strain and damage variables. The local stress tensor is decomposed to hydrostatic and deviatoric parts, and the effective tangent stiffness tensor is derived by considering both the plastic yield law and a specific damage criterion. The associated generalized Coulomb friction criterion and damage criterion are introduced to describe the evolution of inelastic strain and damage, respectively. Prepeak and postpeak triaxial response analysis is carried out by coupled damage–friction analysis to obtain analytical expressions for rock strength and to clarify the basic characteristics of the damage resistance function. Finally, by the use of the returning mapping procedure, the proposed damage–friction constitutive model is applied to simulate the deformation of Pingdingshan hard rock in triaxial compression with respect to different confining pressures. It is observed that the numerical results are in good agreement with the experimental data, which can verify the accuracy and show the obvious advantages of the micromechanic-based model. Full article
(This article belongs to the Special Issue Sustainability in Geology and Civil Engineering)
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31 pages, 7314 KiB  
Article
Rural Tourism—Viable Alternatives for Preserving Local Specificity and Sustainable Socio-Economic Development: Case Study—“Valley of the Kings” (Gurghiului Valley, Mureș County, Romania)
by Andreea M. Crăciun, Ștefan Dezsi, Florin Pop and Pintea Cecilia
Sustainability 2022, 14(23), 16295; https://doi.org/10.3390/su142316295 - 6 Dec 2022
Cited by 4 | Viewed by 3402
Abstract
Rural tourism, defined as a form of local initiative tourism, has at its forefront the involvement of the local community, who contribute significantly to the affirmation and promotion of this type of tourism. In order to be able to speak of the practice [...] Read more.
Rural tourism, defined as a form of local initiative tourism, has at its forefront the involvement of the local community, who contribute significantly to the affirmation and promotion of this type of tourism. In order to be able to speak of the practice of this type of tourism in a given geographical area, it is first necessary to highlight the existence of a tourist heritage, both natural and anthropic, which identifies itself with the authentic character of the area, satisfying the need of the tourist to discover activities and tourist attractions with local specificity. The purpose of this research is to investigate the role of socio-economic and cultural aspects in the sustainable development of tourism in the Gurghiului Valley. The present study also aims to highlight the role of local entrepreneurs in the process of economic development in the area by means of new practices and sustainable approaches; this is based on efficient capitalization of the natural and anthropic tourism heritage of the area, defined by elements of authenticity. The methodology applied in this work is based on the study of specialized literature, along with case study on tourist activity in rural tourism. The research carried out is based on analysis of data from official sources of tourist data (the National Tourism Agency (hereafter NTA) and the National Institute of Statistics (hereafter NIS)), as well as research carried out in the field to see if there are discrepancies between what these two aforementioned official sources provide and the reality on the ground. Our research finally revealed the fact that Gurghiului Valley officially entered into the tourist landscape in 1990 through the lens of the Lăpușna student and preschool camp, and rural tourism has been organized in the study area since 2005. At the same time, research has shown that there is currently a need for much greater involvement and awareness both from local authorities and the resident population regarding the importance of rural tourism in the social and economic evolution of the local community. Full article
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18 pages, 1511 KiB  
Article
Building a Low-Carbon Community: Influencing Factors of Residents’ Idle Resource-Sharing Behaviors
by Li Yan and Xiao Dou
Sustainability 2022, 14(23), 16294; https://doi.org/10.3390/su142316294 - 6 Dec 2022
Viewed by 1343
Abstract
Promoting the sharing of idle resources to community residents is a potential means to building a low-carbon community. This study examined three communities with different attributes (college/university, middle and high income, and the elderly). An extended hypothesis model was constructed based on the [...] Read more.
Promoting the sharing of idle resources to community residents is a potential means to building a low-carbon community. This study examined three communities with different attributes (college/university, middle and high income, and the elderly). An extended hypothesis model was constructed based on the theory of planned behavior. The influencing factors of community residents facing idle resource-sharing services were explored. Based on the equal sampling method, 100 questionnaires were randomly distributed in each community to verify the validity of the hypothesis model. The results show that residents’ attitudes, subjective behavioral norms, perceived behavioral control, service expectations, and environmental motivations positively influence residents’ behavioral intention to share their idle resources. The residents’ service expectations for idle resource-sharing are the most critical. Moreover, in terms of community attributes, its attitudes, subjective behavioral norms, and perceived behavioral control significantly influence residents’ behavioral intention to share idle resources. Specifically, the attitudes in the middle- and high-income community have opposite effects on residents from the attitudes in the college/university community and the elderly community. The hypothesis model proposed in this study provides a reference for building a low-carbon community from the perspective of residents’ restriction of resource-sharing. Full article
(This article belongs to the Special Issue Human Behavior, Urban Health and Sustainability)
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