bluuebunny/crossref_metadata_2025 huggingface dataset:
Reducing Urban Traffic Congestion via Charging Price
Authors: González-Aliste Pablo , Derpich Iván , López Mario
Published: January 2023

Traffic jams are one of the major transportation problems. The United States spends USD billions to mitigate the problem, and not always with good outcomes. This problem increases and has effects on sustainable transport, such as life quality, pollution, perishables, and costs. Large cities reduce traffic jams through congestion charges. This paper aims to reduce urban traffic congestion by estimating the charge through a multivariable model. It studies the main jammed areas in Santiago, Chile. The data came from published surveys. The model evaluation included Fisher multiple regression (F) and the determination coefficient (R2). These validations showed that the model is statistically significant. They also showed that the parameter estimation was good. Finally, this model contributes to improving the Sustainable Development Goals, such as SDG 3, SDG 11, and SDG 13, which may be successfully applied to Santiago City, as well as to any city worldwide.
Land- and Water-Based Adaptive Farming Practices to Cope with Waterlogging in Variably Elevated Homesteads
Authors: Rahman Md. Moshiur , Chakraborty Tapan Kumar , Al Mamun Abdullah , Kiaya Victor
Published: January 2023

Waterlogging is a major problem in the south-western region of Bangladesh; this study was conducted in the eight most affected areas in order to enhance agricultural production by applying Land- and Water-based adaptive and alternative Farming Practices (LWFP). The study was designed to support target (research) farmers by raising one part of their homestead to use for living and agricultural farming, with the other part excavated to store rainwater and use for aquaculture. The study selected two groups of control farmers: those with ponds and those without. The study was conducted in two phases (i.e., phase 1—pilot phase and phase 2—extended phase), with each year divided into three cropping seasons: summer, rainy, and winter. The study found that the research farmers’ income was significantly higher from vegetables (both pilot and extended phases: p < 0.001), dike crops (both pilot and extended phases: p < 0.001), fish (both pilot and extended phases: p < 0.001), livestock (pilot phase: p < 0.01 and extended phase: p < 0.001), and poultry (pilot phase: p < 0.05 and extended phase: p < 0.001) compared to the control farmers. Moreover, the research supported the empowerment of women, which was not found in the control farms. Overall, the research program was embraced by the local communities as a very successful model. Furthermore, the study showed how waterlogging marginally affects very poor people, and that they can cope with this severe problem by adopting various farming practices. Therefore, the application of this research approach is suggested for similarly affected areas.
Government Subsidy Strategies for the New Energy Vehicle Power Battery Recycling Industry
Authors: Wang Enci , Nie Jianyun , Wang Yuhan
Published: January 2023

The rapid development of the new energy vehicle industry is an essential part of reducing CO2 emissions in the transportation sector and achieving carbon peaking and carbon neutrality goals. This vigorous development of the new energy vehicle industry has generated many end-of-life power batteries that cannot be recycled and reused, which has brought serious consequences for the environment. In order to solve the negative externality problem brought by EoL power batteries, how the government intervenes in the development of the market and guides multiple parties to cooperate in recycling EoL power batteries is a question worthy of deep consideration. In this paper, we consider that the government acts before recycling companies and consumers, and recycling companies and consumers act again according to the policy. First, we examine an evolutionary game model of recycling companies and consumers in the absence of the government and explore their choice strategies in various scenarios. Second, we examine how government subsidies to recycling companies and consumers may change the trend toward positive recycling in different circumstances. This paper compares the effects of government policies on subsidies to recycling companies, subsidies to consumers, and subsidies to recycling companies and consumers. Finally, the paper proposes policy suggestions from the perspectives of the government, recycling companies, and consumers. The conclusion suggests that the market does not guarantee a high return for both parties without government subsidies. It is difficult for recyclers and consumers to cooperate proactively in recycling end-of-life power batteries. Thus, it is found that government subsidies to recycling companies and consumers can maximize social welfare at the lowest government cost. Even though government subsidies are currently targeted at recycling companies, they should gradually be extended to consumers as the industry develops.
Mechanical and Hygrothermal Properties of Zeolite-Modified Pervious Concrete in Hot and Humid Area
Authors: Guo Kaiwen , Guo Shiping , Chen Xingji , Qi Qianlong
Published: January 2023

Pervious concrete has good permeability and moisture adjustment properties due to its rich pore structure. It can not only reduce surface runoff by infiltration of rainfall, but also retain a certain amount of water inside, and then decrease the surface temperature via evaporation. In order to optimize the evaporative cooling performance of pervious concrete, this study introduces a modified method of incorporating superabsorbent zeolite produced from industrial wastes into pervious concrete as hygroscopic filler. The effects of zeolite dosages on the basic physical and mechanical properties of pervious concrete were analyzed, and then the evaporative cooling performance of zeolite-modified pervious concrete with the optimum replacement rate was studied. The results showed that the zeolite addition significantly reduced the density of pervious concrete, while having little impact on the permeability. The compressive and splitting tensile strength of pervious concrete increased first and then decreased as the replacement rate of zeolite powder increased, and the content of 15% zeolite powder and 20% zeolite aggregate was beneficial to improve the mechanical properties of pervious concrete. Contributing to the abundant micro-pores and higher specific surface area of zeolite particles, this could improve capillary water absorption and the water storage ability of pervious concrete. During the process of evaporation, the water absorption increment could effectively reduce the surface temperature by 5–8 °C, and maintain the evaporation cooling effect for 10–12 h.
Taxonomic Diversity and Selection of Functional Traits in Novel Ecosystems Developing on Coal-Mine Sedimentation Pools
Authors: Kompała-Bąba Agnieszka , Bąba Wojciech , Ryś Karolina , Hanczaruk Robert , Radosz Łukasz , Prostański Dariusz , Woźniak Gabriela
Published: January 2023

Coal-mine sedimentation pools are extrazonal habitats in which the anthropogenic changes of all historic, abiotic, and biotic components, followed by conditions of extreme environmental stress, lead to the formation of novel ecosystems. Our study aims to (i) classify the vegetation on the basis of floristic and ecological criteria, (ii) detect the main environmental gradients responsible for the diversity of vegetation, and (iii) present the selection of species’ functional traits along environmental gradients. A cluster analysis of the floristic data revealed 14 distinct combinations of species. Short- and long-lived ruderals, meadow, xerothermic, and psammophilous species make up the floristic composition of vegetation. A canonical correspondence analysis on the floristic data and average Ellenberg’s indicator values confirmed moisture, soil reaction, and salinity as the main gradients, while fertility and insolation were secondary gradients shaping the diversity of vegetation. A RLQ with a subsequent cluster analysis revealed four groups of species traits selected along environmental gradients. These differed with reference to morphological (canopy height) and physiological traits (specific leaf area, or SLA), as well as persistence (life span), regeneration (reproduction by seeds or vegetative reproduction), and dispersal functional traits. This knowledge can be crucial when planning the restoration of these sites by using spontaneous succession and learning how the various environmental resources can be used to restore or provide new ecosystem services.
Spatial Inequalities in Access to Micromobility Services: An Analysis of Moped-Style Scooter Sharing Systems in Barcelona
Authors: Bach Xavier , Miralles-Guasch Carme , Marquet Oriol
Published: January 2023

Micromobility services hold substantial potential in terms of promoting shared and electric-powered mobility modes, however, little is known about their accessibility and what shapes their spatial coverage. These two issues are important to understand how socially equitable these modes can really be and how public policies should manage their implementation in urban areas. Hence, this study examines the determinants of the spatial coverage of four moped-style scooter sharing services (MSS) in Barcelona. The article examines the socio-territorial characteristics of the coverage areas of each MSS, as defined in 2019, together with the minimum area that operators had to provide service in 2020 according to the local regulation. For each MSS, a binomial generalized linear mixed model is employed to predict the odds of each cadastral parcel being covered by the service and analyzed the main spatial determinants associated with it. The results suggest that territorial coverage is defined by centrality, household disposable income, and topography, with low-accessibility areas consistently omitted from services. The conclusions underline the need for the public sector to participate in the design of spatial coverage areas of MSS to guarantee spatial equity and transportation justice and avoid private sector designs that systematically exclude less attractive areas.
Collaborative Decision-Making Method of Emergency Response for Highway Incidents
Authors: Yao Junfeng , Yan Longhao , Xu Zhuohang , Wang Ping , Zhao Xiangmo
Published: January 2023

With the continuous increase in highway mileage and vehicles in China, highway accidents are also increasing year by year. However, the on-site disposal procedures of highway accidents are complex, which makes it difficult for the emergency department to fully observe the accident scene, resulting in the lack of sufficient communication and cooperation between multiple emergency departments, making the rescue efficiency low and wasting valuable rescue time, and causing unnecessary injury or loss of life due to the lack of timely assistance. Thus, this paper proposes a multi-agent-based collaborative emergency-decision-making algorithm for traffic accident on-site disposal. Firstly, based on the analysis and abstraction of highway surveillance videos obtained from the Shaanxi Provincial Highway Administration, this paper constructs an emergency disposal model based on Petri net to simulate the emergency on-site disposal procedures. After transforming the emergency disposal model into a Markov game model and applying it to the multi-agent deep deterministic strategy gradient (MADDPG) algorithm proposed in this paper, the multiple agents can optimize the emergency-decision-making and on-site disposal procedures through interactive learning with the environment. Finally, the proposed algorithm is compared with the typical algorithm and the actual processing procedure in the simulation experiment of an actual Shaanxi highway traffic accident. The results show that the proposed emergency-decision-making method could greatly improve collaboration efficiency among emergency departments and effectively reduce emergency response time. This algorithm is not only superior to other decision-making algorithms such as genetic algorithm (EA), evolutionary strategy (ES), and deep Q network (DQN), but also reduces the disposal processes by 28%, 28%, and 42%, respectively, compared with the actual disposal process in three emergency disposal cases. In summary, with the continuous development of information technology and highway management systems, the multi-agent-based collaborative emergency-decision-making algorithm will contribute to the actual emergency response process and emergency disposal in the future, improving rescue efficiency and ensuring the safety of individuals.
CSR and Sustainable Growth in China’s Technology Firms between 2010 and 2021
Authors: Ma Chen , Yu Changjiang , Latif Yasir
Published: January 2023

In this study, we examine the relationships between CSR (e.g., CSR aimed at employees, customers, suppliers, and governments) and firm sustainable growth, and how dysfunctional competition moderates these relationships. Based on resource dependence theory, we argue that CSR aimed at four chosen groups of stakeholders (e.g., employees, customers, suppliers, and governments) is positively related to firm sustainable growth and that the levels of dysfunctional competition will positively moderate these relationships. Our results, using a sample of technology firms in China, provide support for these arguments. We find that CSR aimed at employees, customers, suppliers, and governments is positively related to firm sustainable growth. In addition, using the contingence approach, we find that CSR aimed at the four chosen groups of stakeholders has a stronger positive relationship with firm sustainable growth when the level of dysfunctional competition is high than when it is low. Our findings have important theoretical and managerial implications, which are discussed in this study.
Development of the Sustainable Extraction Procedures of Bioactive Compounds from Industrial Food Wastes and Their Application in the Products for Human Uses
Authors: Savic Ivan M. , Savic Gajic Ivana M.
Published: January 2023

Reducing natural resources caused by the growth of the world’s population, meeting the growing demands of consumers, and preventing environmental pollution requires the development of sustainable and efficient procedures that include the valorization of wastes [...]
Prediction of Electric Vehicles Charging Demand: A Transformer-Based Deep Learning Approach
Authors: Koohfar Sahar , Woldemariam Wubeshet , Kumar Amit
Published: January 2023

Electric vehicles have been gaining attention as a cleaner means of transportation that is low-carbon and environmentally friendly and can reduce greenhouse gas emissions and air pollution. Despite EVs’ many advantages, widespread adoption will negatively affect the electric grid due to their random and volatile nature. Consequently, predicting the charging demand for electric vehicles is becoming a priority to maintain a steady supply of electric energy. Time series methodologies are applied to predict the charging demand: traditional and deep learning. RNN, LSTM, and transformers represent deep learning approaches, while ARIMA and SARIMA are traditional techniques. This research represents one of the first attempts to use the Transformer model for predicting EV charging demand. Predictions for 3-time steps are considered: 7 days, 30 days, and 90 days to address both short-term and long-term forecasting of EV charging load. RMSE and MAE were used to compare the model’s performance. According to the results, the Transformer outperforms the other mentioned models in terms of short-term and long-term predictions, demonstrating its ability to address time series problems, especially EV charging predictions. The proposed Transformers framework and the obtained results can be used to manage electricity grids efficiently and smoothly.
Empowering High-Quality Development of the Chinese Sports Education Market in Light of the “Double Reduction” Policy: A Hybrid SWOT-AHP Analysis
Authors: Liu Zelin , Duan Xiyan , Cheng Hongling , Liu Zhaoran , Li Ping , Zhang Yang
Published: January 2023

Background: The “Double Reduction” policy changed the education market landscape overnight in China. This study aimed to develop a strategic development model for the sports education market within the context of the “Double Reduction” policy. Methods: This study employed a hybrid model of SWOT (strengths, weaknesses, opportunities, and threats) and AHP (analytic hierarchy process). First, SWOT factors were identified by a literature review and survey. In 2022, 30 managers and 251 parents from Changsha and Tianjin were surveyed regarding the sports education market. Second, five decision-makers from the Changsha sports education market performed a pairwise comparison of the AHP analysis, which was used to determine weights, consistency ratios, and intensities of SWOT factors. Third, the strategic vector method was used to develop the strategic development model. Results: Sixteen SWOT factors were determined. The strategic quadrilateral’s center of gravity is positioned in quadrant II (−0.0595, 0.0246). The strategic azimuth is 157.5°, and the strategic coefficient is 0.49. The strategic vector is located at the striving zone of the adjustment type. Conclusions: A conservative business strategy should be implemented in the current sports education market. Four novel strategies were proposed to support the high-quality development of the Chinese sports education market.
Fatigue Tests and Failure Mechanism of Rib-to-Deck Welded Joints in Steel Bridge
Authors: Fan Chuanbin , Da Letian , Wang Kangchen , Song Shenyou , Chen Huanyong
Published: January 2023

The fatigue cracks of rib-to-deck welded joints in an orthotropic steel deck are one of the critical conundrums that restrict the sustainable development of steel bridges. Double-sided welded joints were achieved by introducing internal welding technology to overcome the initial “crack-like” manufacturing defects at the welding roots of single-sided welded joints. Through the observation of the macro-section of the welded joint, the differences between single-sided welding, partial-penetration welding, and full-penetration welding in rib-to-deck welded joints are compared. Relying on the Shenzhen–Zhongshan link, the fatigue failure and mechanism of single-sided rib-to-deck welded joints are clarified by the nominal stress and structural stress methods, and those of double-sided welded joints were determined through fatigue tests. The fatigue strength of rib-to-deck welded joints is higher than the FAT90 of Chinese standard and the FAT C joints of American standard. The fatigue strength of double-sided rib-to-deck welded joints is significantly higher than that of single-sided welded joints. The fatigue strength of rib-to-deck welded joints is within a ± 2σ range of main S-N curves by the structural stress method. It is suggested to adopt the double-sided welded joints in practice, and to ensure that the penetration rate is beyond 80%. The trial data are limited, and further tests are needed to confirm the results.
Achieving UN SDGs in Food Supply Chain Using Blockchain Technology
Authors: Chandan Anulipt , John Michele , Potdar Vidyasagar
Published: January 2023

Food supply chains are highly distributed, collaborative, heterogeneous, diverse, and varied by product, process, and destination. The global food supply chain (FSC) objective is to maintain a good balance between supply and demand and move products from producer to market. However, sustainability of the FSC has become a major concern as limited resources and increasing population pressure threaten its existence. Supply chain management is an important issue for FSC due to information flow throughout the supply chain. Industry-specific characteristics and extensive integration among multiple actors in an entire supply chain exacerbate this situation. The agri-food sector has one of the lowest rates of information technology penetration for innovation. Over the past thirty years, information and communication technology (ICT) has been introduced into the agricultural and food sectors, helping to improve food production and transportation. However, there are various challenges, such as transparency, accountability, food scandal, trust, and inefficient information flow, that the food supply chain is still facing in reaching sustainable goals. The complexity of food supply systems and the opportunities and challenges faced regarding desired sustainability performance need to be examined to achieve the United Nations Sustainable Development Goals (SDGs). Blockchain is an emerging and disruptive digital technology that can transform governance and sustainability in integrated food supply chains. It provides a transparent, immutable, and traceable ledger that minimizes anomalies and information fraud, making it a potential solution for designing a transparent, traceable food system. Blockchain can potentially improve the sustainability of the food supply chain by providing a transparent traceability system. Food traceability is important for managing the food supply chain and protecting public health. It allows quick and accurate traceability of contaminated food that causes foodborne illness outbreaks, leading to the withdrawal of contaminated food from markets. Blockchain can achieve traceability, provenance tracking, transparency, and reduce environmental impact in the food supply chain. It also helps in achieving sustainable development goals set by the UN. However, there is no scientific research on blockchain’s contribution to achieving these goals in the food supply chain. Therefore, this article presents a systematic literature review and thematic analysis to study the relationship between FSC sustainability, blockchain, and sustainable development goals.
Noise Pollution Analysis Using Geographic Information System, Agglomerative Hierarchical Clustering and Principal Component Analysis in Urban Sustainability (Case Study: Tehran)
Authors: Forouhid Amir Esmael , Khosravi Shahrzad , Mahmoudi Jafar
Published: January 2023

In this study, a new approach has been used with SPSS and MATLAB analysis to study urban road traffic noise distribution mapping, to obtain the representative road traffic noise maps. The observation has been performed at a high traffic highway. The factors influencing noise level (traffic, road width, slope, and residential or administrative–commercial land) use were surveyed and recorded for each point and their local and time dependencies were computed. According to the analysis, the maximum value of goodness of fit index for the traffic and noise level relationship was 0.64, followed by 0.489 for the percentage of residential land use. The result of this study showed that the vehicle speed, width of the road, and the land use can affect different sound levels emitted by moving vehicles on road. The model predicts that by increasing one vehicle per hour, an increase in noise level by 0.002 dB will happen.
Portfolio Analysis of Clean Energy Vehicles in Japan Considering Copper Recycling
Authors: Osawa Jun
Published: January 2023

Several countries are moving toward carbon neutrality to mitigate climate change. The introduction of clean energy vehicles (CEVs) is a measure to offset the adverse effects of global warming. However, each CEV has its strengths and weaknesses. An optimal CEV portfolio must be formulated to create effective policies that promote innovative technologies and introduce them into the market. CEVs also consume more copper than gasoline vehicles. Copper is associated with supply risks, which most previous conventional studies have failed to address. Therefore, this study proposes a novel CEV optimization model for sustainable consumption of copper resources through recycling along with reduction of CO2 emissions. This study aims to analyze the optimal portfolio for domestic passenger vehicles and the assumed effects of copper recycling and usage reduction. For this analysis, this study set up scenarios for the recycling rate of copper contained in end-of-life vehicles and the reduction rate of copper used in newly sold vehicles. Our simulation results showed that increased recycling rates and reduced use of copper are necessary for the diffusion of battery electric vehicles. Furthermore, the simulation results indicated that if these improvements are not implemented, the deployment of fuel cell vehicles needs to be accelerated.
Exploring Social Media and Organisational Sustainability Performance Goals: Themes, Functional Areas, and Practices Learning from the Preceding Decade
Authors: Alsehani Fayez Nahedh , Wahab Ainuddin Wahid Bin Abdul , Shuib Liyana
Published: January 2023

Enterprises have increased their involvement in sustainability because of social and ecological trends and quickly changing settings. The large-scale environmental influence in attaining sustainability is a serious problem for organisations. Organisations are coping with various negative environmental challenges, and social media is one of the driving forces involved in dealing with this difficulty owing to the enormous number of users of social media. Organisations embrace social media to accomplish various goals, such as information sharing, connection building, brand development, boosting awareness, and gathering customer insights. In addition, social media is a critical factor in influencing organisational sustainability performance on an individual and group level. This paper aimed to examine social media and organisational sustainability performance goals, namely themes, functional areas, and practices in the age of social networking. Identifying the goals and themes provided us with the limitations of the research areas. The PRISMA statement 2020 was adopted to include and exclude results and extract the data from three renowned databases: Scopus, Web of Science, and Google Scholar. The major themes were established using the VOSviewer software by using the occurrences of key terms and content analysis. Three major literature themes were identified: organisations and sustainability, corporate social responsibility, and social media. The results indicated that few researchers have contributed to the areas of social media and organisational sustainability performance in the past decade. However, due to the importance of social media in achieving good organisational sustainability performance, organisations have been encouraging the adoption of the use of social media for sustainable development. In addition, Twitter is a social media platform that is widely used by organisations to promote sustainability practices. This study investigated the novel concept of social media to achieve sustainability in organisations, and the results of the study showed that limited research has been conducted, and this could be further explored by researchers in future work.
The Impact of Digital Transformation on Corporate Sustainability: Evidence from Listed Companies in China
Authors: Ji Zhiying , Zhou Tingyu , Zhang Qian
Published: January 2023

This study investigated whether digital transformation improves corporate sustainability. In particular, we focused on the mediating effects of operation efficiency and corporate innovation in the ability of digital transformation to enhance corporate sustainability. A novel analytical framework was constructed incorporating the resource-based view (RBV), institution-based view (IBV), enterprise efficiency theory and dynamic capability theory to explain the relationship between digital transformation and corporate sustainability. Fixed effects estimation and the 2SLS method were used to test our analytical framework based on Chinese A-share listed companies over the sample period, 2014–2020. We found that digital transformation is an important means to improve corporate sustainability, but this relationship is impacted by the heterogeneous factors of ownership, industry and location. At the end of the paper, implications, limitations and future research directions are discussed.
Analysis of Air Quality Evolution Trends in the Chinese Air Pollution Transmission Channel Cities under Socioeconomic Development Scenarios
Authors: Shi Kaihe , Liu Huiru , Zhang Li , Li Qing
Published: January 2023

In this paper, based on the traditional grey multivariate convolutional model, the concept of a buffer operator is introduced to construct a single-indicator buffered grey multivariate convolutional model applicable to air quality prediction research. The construction steps of the model are described in detail in this paper, and the stability of the model is analyzed based on perturbation theory. Furthermore, the model was applied to predict the air quality composite index of the “2 + 26” Chinese air pollution transmission corridor cities based on different socioeconomic development scenarios in a multidimensional manner. The results show that the single-indicator buffered grey multivariate convolutional model constructed in this paper has better stability in predicting with a small amount of sample data. From 2020 to 2025, the air quality of the target cities selected in this paper follows an improving trend. The population density, secondary industry, and urbanization will not have a significant negative impact on the improvement of air quality if they are kept stable. In the case of steady development of secondary industry, air quality maintained a stable improvement in 96.4% of the “2 + 26” cities. The growth rate of population density will have an inverted U-shaped relationship with the decline in the city air quality composite index. In addition, with the steady development of urbanization, air quality would keep improving steadily in 71.4% of the “2 + 26” cities.
The Influence of Different Factors of Product Attachment on Taoist Tourism Loyalty
Authors: Shen Ching-Cheng , Liu Hsi-Lin , Wang Dan
Published: January 2023

Zinan Temple is one of the Taoist temples in Taiwan, demonstrating the vital status of religious activities and beliefs. Creating religious products that tourists like through unique religious resources and conducting product differentiation competitions is essential for religious tourism to attract tourists. The research used a convenience sampling method, and 377 online questionnaires were distributed and used SPSS 21.0 to conduct linear regression. This research affirms the positive effect of product attachment on loyalty through indispensability and irreplaceability, as well as irreplaceability being a more critical intermediary variable. This research has verified the theoretical impact of religious tourism products on loyalty and makes specific recommendations on improving Taoist tourists’ loyalty to enhance the tourism competitiveness of Zinan Temple. Therefore, this research provides practical suggestions for religious development and cultural sustainability.
Application of Circular Economy in Oil and Gas Produced Water Treatment
Authors: Waly Marwa M. , Mickovski Slobodan B. , Thomson Craig
Published: January 2023

The circular economy (CE) is a promising model in industrial waste management, offering viable long-term resource sustainability. The rising costs of the oil and gas industry make circularity a reliable approach for saving materials, money, and energy. In recent years, attention has risen to the need to apply CE within oil and gas produced water (PW) treatment. The most common treatment practice for PW is based on mechanical treatment, with optional disposal of treated water into deep wells. However, this procedure consumes a lot of energy, increases operational costs, and causes environmental risks. This research aims to propose sustainable treatment technology promoting circularity by introducing a novel nature-based solution to treat PW. The main research objective is to develop a circular model for PW treatment by investigating the treatment of PW using constructed wetlands (CWs) to sustainably reduce the amount of waste in oil and gas fields. Additionally, investigate the use of industrial wastes as filtration materials for CW systems. In this study, eight different laboratory-scale CWs models were designed and tested. The CWS operated in two different types of flow directions: vertical (VF) and horizontal flow (HF). The main filter media for the CW system included aggregates, activated carbons, plastic, and shredded tires. The study investigated the removal rates of Total suspended solids (TSS), Total dissolved solids (TDS), Oil and Grease (OG), and Total Petroleum Hydrocarbon (TPH) from the PW. Testing the CWs, it was found that the results of the PW treatment were promising, with the potential for more future shredded tires and plastic applications. All systems were effective at removing contaminants from produced water, with the highest recorded removal efficiencies of 94.8% TSS, 33.7% TDS, 90.2% OG, and 98.4% TPH. The research results were efficient and promoted the circular use of CW in PW treatment in addition to the possibility of reusing the treated effluent in agriculture and irrigation.
E-Learning Web-Apps Use Acceptance: A Way to Guide Perceived Learning Outcomes in Blended Learning
Authors: Marín-Vinuesa Luz María , Rojas-García Paula
Published: January 2023

This study empirically examines the effects of the acceptance of e-learning Web-apps by student on the learning outcomes achieved with their use. With this objective, two theoretically recognized purposes for use these apps were tested in a blended learning model, as a way to change the traditional face-to-face classrooms activities (apps we called ICTf) and as a virtual evaluation platform in learning (ICTv apps). The data was collected through online surveys from university students of a blended Master’ degree, enrolled in different specialties. PLS-SEM analysis of the data was performed. A proportion of the variance of student learning outcomes was explained by the level of ICTv acceptance. However, the positive effect of the ICTf acceptance on this performance was not significant. Heterogeneity was observed in students’ ratings on the acceptance of the Web-apps by different master’s specialties, and it was higher in ICTf than in ICTv. Our research highlights the important role that the acceptance of use of electronic learning resources plays in boosting their effective learning performance.
A Bi-Level Optimization Model for Virtual Power Plant Membership Selection Considering Load Time Series
Authors: Wang Yantao , Zhang Yinhan , Qi Xuesong , Wang Meiqi , Wang Xinyue
Published: January 2023

In order to improve the level of new energy consumption and reduce the dependence of the power system on traditional fossil energy, this paper proposed a bi-level optimization model for virtual power plant member selection by means of coordination and complementarity among different power sources, aiming at optimizing system economy and clean energy consumption capacity and combining it with the time sequence of load power consumption. The method comprises the following steps: (1) The processing load, wind power, and photovoltaic data by using ordered clustering to reflect the time sequence correlation between new energy and load and (2) uses a double-layer optimization model, wherein the upper layer calculates the capacity configuration of thermal power and energy storage units in a virtual power plant and selects the new energy units to participate in dispatching by considering the utility coefficient of the new energy units and the environmental benefit of the thermal power units. The Latin hypercube sampling (LHS) method was used to generate a large number of subsequences and the mixed integer linear programming (MILP) algorithm was used to calculate the optimal operation scheme of the system. The simulation results showed that by reducing the combination of subsequences between units and establishing a reasonable unit capacity allocation model, the average daily VPP revenue increased by RMB 12,806 and the proportion of new energy generation increased by 1.8% on average, which verified the correctness of the proposed method.
Circular Economy and Sustainable Rural Development
Authors: Mihai Florin-Constantin
Published: January 2023

Rural communities are facing serious waste mismanagement practices around the world (e [...]
Study on High-Speed Machining of 2219 Aluminum Utilizing Nanoparticle-Enhanced Minimum Quantity Lubrication (MQL) Technique
Authors: James Sagil , Mazaheri Mehrshad
Published: January 2023

High-speed machining processes are significantly affected by the accumulation of heat generated by friction in the cutting zone, leading to reduced tool life and poor quality of the machined product. The use of cutting fluids helps to draw the heat out of the area, owing to their cooling and lubricating properties. However, conventional cutting fluid usage leads to considerable damage to human health and the environment, in addition to increasing overall manufacturing costs. In recent years, minimum quantity lubrication (MQL) has been used as an alternative lubricating strategy, as it significantly reduces cutting fluid consumption and eliminates coolant treatment/disposal needs, thereby reducing operational costs. In this study, we investigated microstructural surface finishing and heat generation during the high-speed cutting process of 2219 aluminum alloy using an MQL nanofluid. 2219 aluminum alloy offers an enhanced strength-to-weight ratio and high fracture toughness and is commonly used in a wide range of aerospace and other high-temperature applications. However, there is no relevant literature on MQL-based high-speed machining of these materials. In this study, we examined flood coolant and five different MQL nanofluids made by synthesizing 0.2% to 2% concentrations of Al2O3 nanoparticles into ultra-food-grade mineral oil. The study results reveal the chemistry between the MQL of choice and the corresponding surface finishing, showing that the MQL nanofluid with a 0.5% concentration of nanoparticles achieved the most optimal machining result. Furthermore, increasing the nanoparticle concentration does result in any further improvement in the machining result. We also found that adding a 0.5% concentration of nanoparticles to the coolant helped to reduce the temperature at the workpiece–tool interface, obtaining a good surface finish.
Classification of the Lie and Noether Symmetries for the Klein–Gordon Equation in Anisotropic Cosmology
Authors: Paliathanasis Andronikos
Published: January 2023

We carried out a detailed group classification of the potential in Klein–Gordon equation in anisotropic Riemannian manifolds. Specifically, we consider the Klein–Gordon equations for the four-dimensional anisotropic and homogeneous spacetimes of Bianchi I, Bianchi III and Bianchi V. We derive all the closed-form expressions for the potential function where the equation admits Lie and Noether symmetries. We apply previous results which connect the Lie symmetries of the differential equation with the collineations of the Riemannian space which defines the Laplace operator, and we solve the classification problem in a systematic way.
Dynamic Chaotic Multi-Attribute Group Decision Making under Weighted T-Spherical Fuzzy Soft Rough Sets
Authors: Zhang Fu , Ma Weimin , Ma Hongwei
Published: January 2023

In this article, the parameter of the decision maker’s familiarity with the attributes of the alternatives is introduced for the first time in dynamic multi-attribute group decision making to avoid the disadvantages arising from the inappropriate grouping of decision makers. We combine it with fuzzy soft rough set theory and dynamic multi-attribute-grouping decision making to obtain a new decision model, i.e., dynamic chaotic multiple-attribute group decision making. Second, we provide an algorithm for solving this model under a weighted T-spherical fuzzy soft rough set, which can not only achieve symmetry between decision evaluation and fuzzy information but also establish a good symmetrical balance between decision makers and attributes (evaluation indexes). Finally, a specific numerical computation case is proposed to illustrate the convenience and effectiveness of our constructed algorithm. Our contributions to the literature are: (1) We introduced familiarity for the first time in dynamic multi-attribute group decision making. This makes our given dynamic chaotic multi-attribute group decision-making (DCMAGDM) model more general and closer to the actual situation; (2) we combined dynamic chaotic multi-attribute group decision making with T-spherical fuzzy soft rough set theory to make the model more realistic and reflect the actual situation. In addition, our choice of T-spherical fuzzy soft rough set allows the decision maker to engage in a sensible evaluation rather than sticking to numerical size choices; and (3) we constructed a new and more convenient sorting/ranking algorithm based on weighted T-spherical fuzzy soft rough sets.
Effects of Joule Heating, Viscous Dissipation, and Activation Energy on Nanofluid Flow Induced by MHD on a Vertical Surface
Authors: Jayanthi Senthil , Niranjan Hari
Published: January 2023

This study investigates magnetohydrodynamic (MHD) nanofluid flow through a stretching vertical surface influenced by Joule heating, chemical reaction, viscosity dissipation, thermal radiation, and activation energy. Such physical problems have significance in applied mathematics, engineering, and physics, and they are frequently found in symmetrical scenarios. A transformation of the similarity technique is used to reduce the difficulty of the boundary layer equations for nonlinear motion, energy, solute, and nanoparticle concentration. To identify these variations with local similarity, we employ symmetry analysis. The altered equations were solved using the shooting technique with Matlab bvp4c. It was found that raising the Schmidt number increases the impact of temperature and concentration profiles. As the Biot number and thermal radiation rise, the local Nusselt number, local Sherwood number, and skin friction increase as well. The comparative table shows good agreement with the current results.
Acceleration in Exoplanet Magnetospheres
Authors: Belenkaya Elena , Alexeev Igor
Published: January 2023

We briefly review the various acceleration mechanisms working in exoplanetary magnetospheres. The proposed scenarios are based on the investigation of planetary magnetospheres of the Solar System. Primary attention is paid to Earth and Jupiter, as the most characteristic examples of the various types of magnetospheric features determining different acceleration processes.
Ratio Data: Understanding Pitfalls and Knowing When to Standardise
Authors: Bishop Chris , Shrier Ian , Jordan Matthew
Published: January 2023

Ratios represent a single-value metric but consist of two component parts: a numerator variable and a denominator variable [...]
Modeling the Covariance of Financial Assets Using Neutrosophic Fuzzy Numbers
Authors: Boloș Marcel-Ioan , Bradea Ioana-Alexandra , Delcea Camelia
Published: January 2023

This paper aims to model the covariance of financial assets using neutrosophic fuzzy numbers. Two main concepts are discussed and used, namely the neutrosophic covariance of the financial assets and the independent neutrosophic portfolios. In terms of methodology, a three-step approach is proposed with the purpose of identifying the independent neutrosophic portfolio return, the independent neutrosophic portfolio risk and the structure of the independent neutrosophic portfolio. For this purpose, neutrosophic fuzzy theory is chosen for this type of approach as it allows a proper modeling of the financial performance indicators by taking into account the probabilities of their achievement. This action is possible even in the situation in which linguistic variables are used for better characterizing the values of the recorded data. Numerical examples are provided in each stage of the methodology description for a better understanding of the proposed approach. The results of the study can be used to substantiate the decisions made by the capital market investors.
Vortex Dynamics in a Hybrid Aligned Nematic Microvolume with an Orientational Defect
Authors: Śliwa Izabela , Maslennikov Pavel , Zakharov Alex
Published: January 2023

The aim of this theoretical paper is to investigate the physical mechanism responsible for the appearance of vortex flow in a hybrid aligned nematic (HAN) microvolume with an orientational defect, excited by a temperature gradient ∇T. This was done in the framework of the classical Ericksen-Leslie theory, supplemented by thermomechanical correction of the shear stress and Rayleigh dissipation function, as well as taking into account the entropy balance equation. We have carried out a numerical study of the system of hydrodynamic equations including director reorientation, fluid flow v, and the temperature redistribution across the HAN microvolume under the influence of ∇T, when the HAN microvolume is heated from above. Calculations show that, due to the interaction between the gradient of the director field ∇n^ and ∇T, the HAN microvolume settles down to a stationary complex vortex flow regime.
How Transformative Business Model Renewal Leads to Sustained Exploratory Business Model Innovation in Incumbents: Insights from a System Dynamics Analysis of Case Studies
Authors: Franco Matheus , Minatogawa Vinicius , Quadros Ruy
Published: January 2023

The digital era and mounting sustainability pressures have reinforced incumbents’ need to respond to radical innovation through business model innovation. Despite advancements in the literature on incumbent business model innovation, there are still open debates regarding strategies for achieving systematic innovation and poor integration between the literature on managing multiple business models and the strategic management of business model innovation. To address these gaps, we investigated three Brazilian incumbents that developed systematic business model innovation processes and analyzed their evolution. We followed a multiple case study methodology, deploying system dynamics as an analytical lens. Our findings showed that the evolution of innovation departments from business model renewal to exploration is based on a systemic tension between solving the core problems of the business and creating openness to innovation, innovation capabilities, and resources. By assigning the innovation departments a vital role in the renewed business model and exploring synergies to manage multiple business models, the companies create a “buffer” to sustain exploratory business model innovation. We suggest that the strategy for conducting business model renewal matters, especially when the renewal is transformative, aiming to shape the future. We contribute to incumbent business model innovation theory by showing the system dynamics behind the evolution from business model renewal to exploration and by connecting the management of parallel business models to the strategic management of business model innovation.
Trajectory Generation of Ultra-Low-Frequency Travel Routes in Large-Scale Complex Road Networks
Authors: Li Jun , Zhao Wenting
Published: January 2023

Trajectory generation can help predict the future road network state and properly deal with the privacy issues of trajectory data usage. To solve the problem that routes with very few journeys (ultra-low-frequency journey routes) are difficult to generate in the large-scale complex road network scenarios, the study designs a framework focusing on ultra-low-frequency route generation, ULF-TrajGAIL, and proposes an original trajectory-augmentation method called the combined expansion method. The specific original trajectory-augmentation method is determined by the pre-trajectory-generation experiment, and high-quality synthetic trajectories with higher diversity and similarity are output based on the final generation experiments which take the augmented trajectories as references. Based on the real trajectories of a complex road network in a region of Guangzhou, the quality of synthetic trajectories under different original trajectory-augmentation methods from the route, link and origin and destination pairs levels has been compared. The results show that the method can generate more ultra-low-frequency routes and help improve the overall diversity of routes and the similarity between routes and the number of journeys as well.