bluuebunny/crossref_metadata_2025 huggingface dataset:
Resilience of Public Open Spaces to Earthquakes: A Case Study of Chongqing, China
Authors: Alawi Mohsen , Chu Dongzhu , Hammad Seba
Published: January 2023

Public open spaces (POSs) can be crucial during earthquakes, serving as essential places for recovery and mitigation. However, the ability of POSs to respond to earthquakes varies based on their degree of resilience. Resilience plays a significant role in ensuring effective responsiveness to earthquakes in POSs, in addition to enhancing their daily use in normal times. By exploring and examining the earthquake resilience criteria that can be incorporated into the planning and design of POSs, this study aims to determine and enhance the ability of POSs to provide an effective response during earthquakes. Four main criteria consisting of twelve sub-criteria of earthquake resilience are investigated. The resilience criteria are applied and compared in 169 POSs in three different areas in Chongqing municipality in China. A geographic information system (GIS) is used to study the earthquake-resilience criteria of the POSs. The analytic hierarchy process (AHP) is used to weight the resilience criteria. Weighted overlay analysis (OWA) is used to determine the degrees of earthquake resilience of POSs. The results show the different potentials for earthquake resilience in POSs according to the area characteristics and POS type. The results also show that the current resilience degree of POSs is insufficient to respond effectively to earthquakes, especially severe ones. This study provides a valuable source for enhancing cities’ resilience against earthquake disasters.
How Do E-Brand Experience and In-Store Experience Influence the Brand Loyalty of Novel Coffee Brands in China? Exploring the Roles of Customer Satisfaction and Self–Brand Congruity
Authors: Pu Yibei , Zaidin Norzaidahwati , Zhu Yaodong
Published: January 2023

China’s coffee sector is experiencing a transformation related to sustainability. While the media have reported various novel coffee brands in China, scholars have mostly focused on established non-Chinese coffee brands. These studies still cite the relevance of the growing middle class, which adopts coffee as part of an ‘exquisite Western lifestyle’ and form the antecedents of brand loyalty from an established coffee brand perspective. These antecedents may not directly apply to novel coffee brands that face the changing consumption habits of younger Chinese consumers, who stress coffee’s functionality and price performance. Drawing on a social service perspective, this study addresses how E-brand experience and in-store experience each affect customer satisfaction and brand loyalty, as well as the role of customer’s self–brand congruity. The conceptual model was empirically tested using an online survey of 332 Chinese novel coffee brand customers. Our results suggest that E-brand experience (EBE) and in-store experience (SBE) both affect customer satisfaction (CA), with each relationship moderated by self–brand congruity (SBC); CA mediates the relationship between EBE and brand loyalty and that between SBE and brand loyalty. Moreover, younger respondents in this study were more likely to develop customer satisfaction and brand loyalty toward novel Chinese coffee brands.
Energy Storage Configuration of Distribution Networks Considering Uncertainties of Generalized Demand-Side Resources and Renewable Energies
Authors: Sun Weiqing , Gong Yao , Luo Jing
Published: January 2023

With the growing proportion of advanced metering infrastructures and intelligent controllable equipment in power grids, demand response has been regarded as an effective and easily implemented approach to meet the demand–supply equilibrium. This paper innovatively proposes generalized demand-side resources combining the demand response with an energy storage system and constructs a configuration model to obtain scheduling plans. Firstly, this paper analyzes the characteristics of generalized demand-side resources and models the translational loads, reducible loads and energy storage system. Secondly, a deterministic energy storage configuration model aiming at achieving the lowest operation cost of distribution networks is established, from which the scheduling scheme of generalized demand-side resources can be obtained. Then, the fuzzy membership function and the probability density function are used to represent the uncertainty of the demand response, the prediction error of renewable energy output and the generalized demand-side resources that do not participate in the demand response. Therefore, this paper simulates daily operations to modify the capacity of energy storage. The problem is solved by using Monte Carlo simulation, fuzzy chance-constrained programming and mixed-integer programming. Finally, the effectiveness of this model is demonstrated with case studies in a 33-node distribution network. The results show that the uncertainty of this system is solved effectively. When only considering generalized demand-side resources, the total cost is reduced by 9.5%. After considering the uncertainty, the total cost is also decreased 0.3%. Simultaneously, the validity of the model is verified.
Satisfaction with and Continuous Usage Intention towards Mobile Health Services: Translating Users’ Feedback into Measurement
Authors: Fu Yu , Wang Yuanyuan , Ye Xinhui , Wu Weifang , Wu Jianfeng
Published: January 2023

With advances in information and communication technology and the rapid development of the mobile Internet, mobile health (m-health) management applications (apps) play a key role in modern health assistance programs. However, m-health management apps still face major dilemmas in ensuring user satisfaction and continuous use. Based on resolving the contradiction between the multiple complex and ambiguous demands of users and the limited development resources of companies, this study explores ways to improve user satisfaction and the willingness to sustain m-health management app usage to build efficient and clear m-health management app demand insights and development strategies. This study integrates the advantages of the Kano model and the decision-making trial and evaluation laboratory (DEMATEL) method. From the systematic level, an attribute acquisition-classification-key attribute extraction and influence relationship quantification-hierarchy analytic hierarchy model was built. The research results provide implications for further improvement efforts to consider not only technological capabilities but also effective insights into the attributes that are highly expected by users, thus improving the accuracy of app function positioning and, in turn, enhancing user satisfaction and continuous usage intention. Additionally, the results provide decision-makers in enterprises and relevant research and development (R&D) departments with clear and efficient app requirement relationships and development strategies.
Environmental Impact Comparison Analysis between a Traditional Hot Mixed Asphalt (HMA) and with the Addition of Recycled Post-Consumer Polyethylene Terephthalate (RPET) through the Life Cycle Assessment (LCA) Methodology
Authors: Osorto Mario Rene Rivera , Casagrande Michéle Dal Toé
Published: January 2023

The present study presents a cradle-to-built life cycle assessment (LCA) for a road pavements structure of hot mixed asphalt (HMA) with recycled post-consumer polyethylene terephthalate (RPET) addition through the “dry” process using a comparison analysis between declared units equivalent of 1 ton of produced mix and functional units equivalent of 1 m2 pavement variants under the Brazilian “National Design Methodology” (MeDiNa), in contrast with a conventional mix variant. The Tool TRACI 2.0 for reducing and assessing chemical and other environmental impacts was applied for each alternative, assessing the impacts into categories such as acidification, eutrophication, freshwater ecotoxicity, global warming potential, human health, ozone depletion, and smog formation. The life-cycle impact assessment results were interpreted through an internal normalization criteria and weighting rule, obtaining an environmental score for each alternative and allowing an easy stakeholder interpretation. Considering the better mechanical properties and overall functional performance of the HMA + RPET mixes, the functional unit comparison on LCA methodology results in savings in all environmental impact categories for each square meter of pavement constructed and ready to use. For the functional units, the HMA + RPET pavement structures (FU 2 and FU 3) resulted in lower environmental scores (ES) with 49.2 and 47.1, respectively, representing a difference of 26.9 and 29 score points in comparison to the conventional pavement structure (FU 1 − C), with an ES of 76.1. It represents 38% of environmental savings in terms of the environmental score in favor of sustainable pavement alternatives. Focusing on the impact in global warming potential, the use of RPET in the HMA mixes for pavement design can result in savings up to 47.44% of impact decrease (20.4 ES) in comparison with the conventional-mix pavement structure proposal. This result supports the environmental sustainability of the HMA + RPET mixes and is a precedent for future research on new geotechnical and pavement alternative materials.
Static and Dynamic Load Transfer Behaviors of the Composite Foundation Reinforced by the Geosynthetic-Encased Stone Column
Authors: Liu Mengjie , Wang Kaifeng , Niu Jiayong , Ouyang Fang
Published: January 2023

An accurate description of the load transfer behaviors of the geosynthetic-encased stone column (GESC) is of great importance for revealing the bearing capacity of GESC. Static load tests and shake table model tests were performed to characterize the static and dynamic load transfer behaviors of the composite foundation reinforced by the GESC. Under static loading, static load tests were conducted on a fully geosynthetic-encased stone column (FGESC), partially geosynthetic-encased stone column (PGESC) and traditional stone column (TSC). The influence of length and stiffness of the encasement on the stone columns were investigated. Under seismic loading, the shake table model tests were performed to analyze the differences of the dynamic pile-soil stress responses between the composite foundations with the GESC and the TSC. The results show that the static pile-soil stress ratios of the composite foundation with the FGESC are about three to six times of those of the composite foundation with the TSC, and the difference increases with the increase in the stiffness or length of the encasement. The static vertical stress of 60% acting on the pile top can be transferred to the pile bottom for the FGESC, while only 27~45% for the TSC. The dynamic pile-soil stress ratios of the GESC and the TSC first decrease and then increase slightly with the increase of the input peak acceleration. The dynamic pile-soil stress ratio of the GESC is about three times that of the TSC under seismic excitation with the same type and peak acceleration. The attenuation rate of dynamic stress along the pile body under dynamic loading is much faster than that under the static loading. Under the static and dynamic conditions, the load transfer capacity and pile efficacy of the GESC are always better than those of the TSC.
Prediction of Streamflow Drought Index for Short-Term Hydrological Drought in the Semi-Arid Yesilirmak Basin Using Wavelet Transform and Artificial Intelligence Techniques
Authors: Katipoğlu Okan Mert
Published: January 2023

The prediction of hydrological droughts is vital for surface and ground waters, reservoir levels, hydroelectric power generation, agricultural production, forest fires, climate change, and the survival of living things. This study aimed to forecast 1-month lead-time hydrological droughts in the Yesilirmak basin. For this purpose, support vector regression, Gaussian process regression, regression tree, and ensemble tree models were used alone and in combination with a discrete wavelet transform. Streamflow drought index values were used to determine hydrological droughts. The data were divided into 70% training (1969–1998) and 30% (1999–2011) testing. The performance of the models was evaluated according to various statistical criteria such as mean square error, root means square error, mean absolute error, and determination coefficient. As a result, it was determined that the prediction performance of the models obtained by decomposing into subcomponents with the discrete wavelet transform was optimal. In addition, the most effective drought-predicting model was obtained using the db10 wavelet and MGPR algorithm with mean squared error 0.007, root mean squared error 0.08, mean absolute error 0.04, and coefficient of determination (R2) 0.99 at station 1413. The weakest model was the stand-alone FGSV (RMSE 0.88, RMSE 0.94, MAE 0.76, R2 0.14). Moreover, it was revealed that the db10 main wavelet was more accurate in predicting short-term drought than other wavelets. These results provide essential information to decision-makers and planners to manage hydrological droughts in the Yesilirmak basin.
Modelling Cover-Collapse Sinkholes That Appeared after the M6.2 Petrinja Earthquake in Croatia Using Electrical Resistivity Tomography Data
Authors: Šumanovac Franjo , Pekaš Želimir
Published: January 2023

After the destructive earthquake in Petrinja measuring M6.2 occurred on 29 December 2020, which was followed by a series of foreshocks and aftershocks in the area of the rural settlements in Mečenčani and Borojevići, cover-collapse sinkholes suddenly appeared. The investigated area is located 20 km southeast of the epicentre. Some months later, more than 90 cover-collapse sinkholes appeared, jeopardising local infrastructure and residential buildings. The sinkholes appear in the area of covered karst, where there are clastic deposits 2–10 m thick on the fractured and weathered limestone bedrock. There are two geological models located in the investigated area: GM-1, where the base consists of clastic strata covering comprising Lithothamnium limestone, which in turn leads to the formation of underground cavities and cover-collapse sinkholes, and the GM-2, where the base comprises clay deposits without any cover-collapse sinkholes. These models can be effectively distinguished due to tomographic resistivity models; hence, numerous measurements were undertaken using two-dimensional electrical tomography in several phases. An estimate of the threat to infrastructural facilities was conducted, and the boundaries of the geological models were precisely determined according to which underground cavities and cover-collapse sinkholes did not develop. Tomographic measurements were also conducted over the largest cover-collapse sinkhole measuring 25 m in diameter and helped to more precisely define the entire hydrogeological model and the mechanisms involved in the formation of cover-collapse sinkholes.
Collaborative Determination Method of Metro Train Plan Adjustment and Passenger Flow Control under the Impact of COVID-19
Authors: Pan Fuquan , Li Jingshuang , Tang Hailiang , Ma Changxi , Zhang Lixia , Yang Xiaoxia
Published: January 2023

Aiming at the problem of metro operation and passenger transport organization under the impact of the novel coronavirus (COVID-19), a collaborative determination method of train planning and passenger flow control is proposed to reduce the train load rate in each section and decrease the risk of spreading COVID-19. The Fisher optimal division method is used to determine reasonable passenger flow control periods, and based on this, different flow control rates are adopted for each control period to reduce the difficulty of implementing flow control at stations. According to the actual operation and passenger flow changes, a mathematical optimization model is established. Epidemic prevention risk values (EPRVs) are defined based on the standing density criteria for trains to measure travel safety. The optimization objectives of the model are to minimize the EPRV of trains in each interval, the passenger waiting time and the operating cost of the corporation. The decision variables are the number of running trains during the study period and the flow control rate at each station. The original model is transformed into a single-objective model by the linear weighting of the target, and the model is solved by designing a particle swarm optimization and genetic algorithm (PSO-GA). The validity of the method and the model is verified by actual metro line data. The results of the case study show that when a line is in the moderate-risk area of COVID-19, two more trains should be added to the full-length and short-turn routes after optimization. Combined with the flow control measures for large passenger flow stations, the maximum train load rate is reduced by 35.18%, and the load rate of each section of trains is less than 70%, which meets the requirements of COVID-19 prevention and control. The method can provide a theoretical basis for related research on ensuring the safety of metro operation during COVID-19.
Sustainable Consumer Behaviors: The Effects of Identity, Environment Value and Marketing Promotion
Authors: Wang Bei , Udall Alina M.
Published: January 2023

As the extreme climate crisis increases, sustainable development is at the forefront of the public mind. However, as one of the major catalysts of sustainable development, sustainable consumer behavior (SCB) is still not being adopted by mainstream consumers. Therefore, this study attempted to find a new way to encourage sustainable consumer behaviors. Based on identity theory, environment value research, and marketing practice, three important factors relevant to SCB are yet to be combined into one model: specifically, moral identity, altruistic values and promotion. Therefore, this study aimed to clarify the relationship between SCB, moral identity and altruistic values and study whether promotion influences the link between SCB and altruistic values. A survey that adopted the previously validated scale was distributed on social media to collect the data. The findings show that: (1) moral self- and group-identity encourage SCB; (2) altruistic values predicts moral self- and group- identity; (3) the relationship between altruistic values and SCB is fully mediated by moral self- and group-identity; (4) promotion does not affect the relationship between altruistic values and SCB. Finally, this study contributes by giving policy makers tools that show how to use identities and values to encourage SCB.
The Effects of Green Innovations in Organizations: Influence of Stakeholders
Authors: Jayaraman Kalaivani , Jayashree Sreenivasan , Dorasamy Magiswary
Published: January 2023

Organizations moving towards adopting sustainable business development has become a necessity. As more and more stakeholders increasingly show interest in pollution and environmental degradation and the major impacts on the economic activities of organizations, it has become a necessity for organizations to move towards adopting sustainable business development. To achieve this goal, organizations need to invest in green innovations (GIs). Therefore, this paper examines the important influence of internal and external stakeholders on organizations that choose to pursue sustainable development with the help of implementing green innovations. It has certain theoretical and practical implications, but the following problems exist: (a) the usage of energy has increased in recent years and further creates a warning sign that precautionary measures need to be taken soon, and if not, the situation will impact the environment and organizations’ sustainable performance; (b) stakeholders’ raise concerns about pollution and environmental deterioration and urge industrialists to incorporate green innovation into all aspects of production and processes. A positivist research paradigm is applied, and the hypotheses will be tested using Structural Equation Modelling (SEM). This study analyzes how green innovation interacts with the linkage between stakeholders and organizational sustainable performance. The contribution hopes to benefit the growth of the economy, promote a cleaner environment, and enhance the wellbeing of the country. This study will further help to enlighten the importance of embracing green innovation in industries to policy makers and manufacturers, which is currently lacking. This initiative is in line with Malaysia’s 12th plan, which aims to promote green innovation to boost the Gross Domestic Product (GDP) and push the country above the high-income barrier.
Comparative Study on Dyed Fabrics of Tea and Tea Stem Based on Kansei Engineering
Authors: Yang Li , Dai Xudong , Meng Yuke , Zhou Lin , Yue Xinyu
Published: January 2023

(1) Objective: This paper conducts a comparative study on the perceptual value of fabrics dyed with tea leaves and tea stems and explores the changes and differences in the Kansei image of the dyed fabrics to provide practical guidance for the product design dyed of tea leaves and tea stems based on the experimental results. (2) Methods: firstly, an effective dyeing method was selected through literature research to dye the samples. Secondly, Kansei words were collected and screened out, and the SD scale was established for a perceptual experiment. Thirdly, a factor analysis was performed on the quantified perceptual evaluation data to compare the changes in the fabric perceptual value before and after dyeing. A T-test and cluster analysis were used to study the difference between them. Finally, according to the fabric perceptual experience results, the product design was put into practice. (3) Conclusion: the perceptual value of all the fabrics dyed with Oolong tea leaves and tea stems were improved. Except for silk chiffon and Tencel, there was no significant difference between tea stems dyeing and tea leaves dyeing in other fabrics, which shows that tea stems dyeing has great perceptual value and reuse value.
Assessing and Managing the Direct and Indirect Emissions from Electric and Fossil-Powered Vehicles
Authors: Mofolasayo Adekunle
Published: January 2023

Efforts to improve air quality and concerns about global warming make transportation mediums that do not produce emissions more attractive to end users. Meanwhile, some of these transportation mediums are powered by an electricity grid that generates a great deal of emissions. This study compared the greenhouse gas GHG emissions for both electric and fossil-powered vehicles using estimates of tailpipe emissions of fossil-powered vehicles and the indirect emissions from the electricity grid. Furthermore, a system dynamic model was developed for a more holistic review of the GHG emissions for both electric and fossil-powered vehicles. The result indicated that in terms of associated emissions from the grid, electric-powered vehicles are not always better than fossil-powered vehicles when the electricity is not from a renewable source. The GHG emissions for electric-powered vehicles are dependent on both the electricity usage rate of the vehicle and the GHG emissions that are associated with the production of that amount of electricity. Further opportunities exist in renewable and clean energy technologies for various operations. Based on reports from previous works, this report also presented potential strategies to achieve a significant reduction in GHG emissions for both the electricity grid and fossil fuel refining processes.
The Impact of Degradation on a Building’s Energy Performance in Hot-Humid Climates
Authors: Taki Ahmad , Zakharanka Anastasiya
Published: January 2023

To date, energy consumption in buildings accounts for a significant part of the total amount of energy consumed worldwide. The effect of ageing and degradation of various building components is one of the least studied reasons for the possible increase in energy consumed in buildings over time. In addition, there is a clear lack of practical guidelines that would help specialists take this factor into account. In this paper, an attempt is made to assess a possible change in the energy performance of buildings due to the degradation of their various components (insulated glass units, thermal insulation, airtightness, solar reflectivity of the building envelope, and photovoltaic modules). Detached and apartment buildings in hot-humid climates with reference to the United Arab Emirates (UAE) were considered. The study was based on simulation research using EnergyPlus, in which the initially collected data on the possible deterioration of the properties of various building components was used for dynamic thermal simulation of selected buildings. The results showed an increase in energy consumption for cooling in detached houses might reach up to 9.53–38.4% over 25 years for more airtight and insulated buildings and 12.28–34.93% for less airtight and insulated buildings. As a result, certain patterns of changes in energy consumption for cooling buildings were established, based on which a set of guidelines was developed. These guidelines can help specialists in various fields better understand the trends in the energy performance of buildings under the influence of degradation processes and take appropriate measures.
Performance Analysis of Classification and Detection for PV Panel Motion Blur Images Based on Deblurring and Deep Learning Techniques
Authors: Al-Dulaimi Abdullah Ahmed , Guneser Muhammet Tahir , Hameed Alaa Ali , Márquez Fausto Pedro García , Fitriyani Norma Latif , Syafrudin Muhammad
Published: January 2023

Detecting snow-covered solar panels is crucial as it allows us to remove snow using heating techniques more efficiently and restores the photovoltaic system to proper operation. This paper presents classification and detection performance analyses for snow-covered solar panel images. The classification analysis consists of two cases, and the detection analysis consists of one case based on three backbones. In this study, five deep learning models, namely visual geometry group-16 (VGG-16), VGG-19, residual neural network-18 (RESNET-18), RESNET-50, and RESNET-101, are used to classify solar panel images. The models are trained, validated, and tested under different conditions. The first case of classification is performed on the original dataset without preprocessing. In the second case, extreme climate conditions are simulated by generating motion noise; furthermore, the dataset is replicated using the upsampling technique to handle the unbalancing issue. For the detection case, a region-based convolutional neural network (RCNN) detector is used to detect the three categories of solar panels, which are all_snow, no_snow, and partial. The dataset of these categories is taken from the second case in the classification approach. Finally, we proposed a blind image deblurring algorithm (BIDA) that can be a preprocessing step before the CNN (BIDA-CNN) model. The accuracy of the models was compared and verified; the accuracy results show that the proposed CNN-based blind image deblurring algorithm (BIDA-CNN) outperformed other models evaluated in this study.
Characterization of Sterile Mining Dumps by the ICP-OES Analytical Method: A Case Study from Baia Mare Mining Area (Maramures, Romania)
Authors: Petrean Ioana Andreea , Micle Valer , Sur Ioana Monica , Șenilă Marin
Published: January 2023

This paper describes a former sterile dump site that is the result of mining and ore processing. A large site located in the Baia Mare mining area (Romania) with a significant amount of Suior-type mining concentrate deposits was selected for this research. The method of analysis used in this study is inductively coupled plasma optical emission spectrometry (ICP-OES). To characterize the contaminated area, a total of 27 sterile samples and one soil sample were collected from the studied site, which was affected by the mining activity. The samples were mineralized by a mix of hydrochloric acid and nitric acid. The disaggregation of the samples took place on a sand bath, and the concentrations of nine heavy metals were determined using an inductively coupled plasma optical emission spectrometer. The investigations provided the information for a detailed analysis allowing the assessment of trace element concentrations to establish whether the area requires remediation. This paper aims to highlight the importance of obtaining quantitative analysis data when characterizing heavy metal contaminated areas that need to undergo the remediation processes, utilizing accurate and fast systems such as modern multispectral analytical devices. The objective of this paper consists of the characterization of an area in the Baia Mare municipality, Romania, affected by high heavy metal concentrations due to sterile mining material being deposited on its surface in order to determine if the area requires remediation.
Research on the Theoretical Framework, Spatio-temporal Laws, and Driving Mechanism of Beautiful Human Settlements—A Case Study of the 14 Prefecture-Level Cities in Liaoning Province
Authors: Tian Shenzhen , Jin Biyan , Li Hang , Li Xueming , Yang Jun
Published: January 2023

The existing research on Beautiful China focuses on the major strategic research that is horizontal and comprehensive, and it is urgent to conduct a vertical and in-depth study from the important focus of human settlements. This paper proposes the theoretical framework of “five-sphere integrated plan”, “three-state entirety”, and “binary fusion” of beautiful human settlements, and integrates the entropy power method, kernel density estimation method, geographic probe, and spatial analysis to study the spatio-temporal Laws and the driving mechanism of beautiful human settlements in Liaoning Province. The results show that: (1) In terms of time course, from 2009 to 2018, the beautiful human settlement in Liaoning showed a fluctuating upward trend, and there were more obvious stage divergence characteristics and discrete characteristics; over time, they clustered from low level to high level. (2) In terms of spatial pattern, beautiful human settlements in general showed regional heterogeneous characteristics. The construction in western Liaoning is relatively stable, while northern Liaoning has changed greatly. There is an obvious inverted “U” spatial structure in the province, and it was both higher in the north and south and lower in the east and west, specifically decreasing from southeast to northwest. The distribution pattern is a “dicaryon” dominated by Shenyang and Dalian, and a “triad” trend of core area, development area, and starting area. (3) System properties, such as environmental, support, and social systems show fluctuating upward trends, while systems such as population show downward trends with different discrete characteristics. (4) Driving mechanisms, social systems, and support systems are the main driving systems, and it is also driven by a combination of urban economic strength, population quantity and quality, infra-structure development such as housing, and emerging technology development. The purpose of studying the beautiful human settlements is to promote the integration and development of the sciences of human settlements and other cross disciplines and to clarify the focus of Liaoning local government on building a Beautiful China.
Research on the Sustainable Development of Enterprises That Evoke Industrial Heritage—A Case Study of Taoxichuan
Authors: Ni Zebo , Ouyang Taohua , Xu Jianxiong
Published: January 2023

This paper takes Taoxichuan Cultural and Creative Street as a case study. It explores how enterprises activate the value of “industrial heritage” resources and achieve sustainable development from the perspective of affordance theory. Research findings indicated that: (1) the creation of a culturally recognized context performs a vital role in activating the industrial heritage; (2) the evocation of industrial heritage resources is a dynamic process from the realization of fundamental values to the actualization of high-level values; and (3) the evoked industrial heritage resources can achieve sustainable corporate development. Additionally, the research findings provide reference for enterprises to realize high-level values of industrial heritage resources by creating contexts to transform them into sources of innovation in the post-pandemic era.
Study on the Effect of Non-Linear Ventilation Pipe Composite Measures on the Slope Permafrost Subgrade
Authors: Cheng Zhe , Zhang Zhilong , Liu Guang , Wu Ying
Published: January 2023

In the alpine mountain area, the stability of the steep-slope permafrost subgrade is mainly affected by the temperature variation in the frozen soil layer at the base of the road. Under the conditions of climate warming and engineering-related disturbance, the cooling of the subgrade is an urgent problem to be solved in the field of construction. In this paper, the numerical calculation method, combined with data monitored in situ, is used to study the cooling effects of several subgrade cooling measures, in which the non-linear ventilation pipe and rubble layer are combined. The results show the following: (1) the temperature field of the steep-slope subgrade is clearly different in lateral terms—after 20 years of operation, the maximum difference in the melting depth between the left shoulder and the subgrade center is 3 m; (2) the maximum melting depth of the gravel subgrade center is 3.85 m, while the maximum difference in the melting depth between the left shoulder and the subgrade center is 2.3 m; (3) the cooling effect of the composite measures is noteworthy, and a −2.2 °C freezing area appears under the subgrade.
The Assessment of Greyfields in Relation to Urban Resilience within the Context of Transect Theory: Exemplar of Kyrenia–Arapkoy
Authors: Akansu Vedia , Karaman Aykut
Published: January 2023

Greyfields are construction sites that emerge from the expansion of cities towards rural settings. They are unused structures in settlement areas that negatively impact the habitats and lead to ecologically, economically, and socially problematic zones. This study aims to examine the Greyfield problem, which emerges as one of the outcomes of urban sprawl, within the context of Transect Theory and urban resilience. We analyze the Greyfield problem in the Arapkoy rural settlement, which is located along the north coastline of Kyrenia, Cyprus. This study presents the impact of Greyfield sites on environmental, social, and economic values within the framework of Transect Theory. Thus, a road map for the redevelopment of Greyfields into public use is put forward to be used for future planning activities, which is a necessity in enabling urban resilience.
A Customizable No-Code Realistic Motion Editor for VRM-Based Avatars
Authors: Cheng Po-Hsun , Chen Li-Wei , Lin Chia-Hsuan
Published: January 2023

Avatar actions can be captured using certain gesture sensors or can be predefined by game designers through desktop applications. In other words, developing an online avatar editor could be necessary to specify the detailed actions for use by people who are not game creators. Our research team proposed a web-based toolset, myKLA, to construct and design avatar actions with editor and player features. The goal of myKLA is to help users define the required behaviors of avatars within a set time frame without codes. We used cyber–physical system theory in a software reconstruction initiative. Additionally, an exchangeable JSON file format for predefining the avatar actions was opened and shared here. Furthermore, the cyclomatic complexity of the main code blocks in our toolset was measured and changed using the McCabe approach to fine-tune the performance. An algorithm was proposed for quickly calculating an integrated activity diagram from several sub-activity diagrams. Our research showed that it is easy to create an avatar head and embed it in other web-based applications for additional interaction utilization. Therefore, our findings will be useful in creating and designing new educational tools.
Innovative and Competitive: A Systematic Literature Review on New Tourism Destinations and Products for Tourism Supply
Authors: Azmi Ezwani , Che Rose Rosniza Aznie , Awang Azahan , Abas Azlan
Published: January 2023

New tourism destinations and product supply are increasingly popular strategies among industry players to create competitiveness. The tourism industry has become more vibrant since globalization merged with technological changes, thus influencing human travel movements, lifestyles, and current trends. The purpose of the study was to systematically review and analyse the elements of new tourism destination products and the importance of sustaining the tourism industry. The following five primary methodological steps were used in the review processes: review protocol; formulation of research questions; systematic searching strategies based on identification, screening, and eligibility on Web of Science (WoS) and Scopus databases; quality appraisal and data extraction; analysis. Seven major themes were discovered, based on the thematic analysis: (a) Responsibilities and involvement, (b) Geography and resources, (c) Innovation, (d) Diversification, (e) Trend and travel pattern, (f) Sustainability, and (g) Marketing. The findings provide academics with a basic reference in scientific and design-related frameworks for examining new destinations and tourism products. The study also offers a guide for destination operators and industry stakeholders to be adopted for future destination development and management.
How Does Usage of Robot Affect Corporate Carbon Emissions?—Evidence from China’s Manufacturing Sector
Authors: Li Xiaoyi , Tian Qibo
Published: January 2023

Robot usage has become an intrinsic requirement to drive the intelligence transformation of the manufacturing industry, providing a key driver for carbon emission reduction in China’s manufacturing industry. This paper examines the carbon emission reduction effect of robot usage at three levels: theoretical, empirical, and decomposition. On the basis of the pollution emission data of segments of China’s manufacturing industry from 2006 to 2020, the paper takes matching robot stock and incremental data from the International Federation of Robotics statistics, and applies the instrumental variable method to identify and estimate the role played by industry robot stock and incremental improvement in reducing pollution emissions. The empirical results show that the usage of robots does significantly reduce the carbon emissions of the manufacturing industry in China. Further, mechanism testing revealed that robot use reduces corporate pollution emissions mainly through channels such as R&D investment and manual substitution. The research provides microscopic evidence for objectively assessing the impact of robot use on environmental pollution emissions from the perspective of promoting robot applications, and suggests policy recommendations for reducing pollution emissions from China’s manufacturing sector, which can help achieve harmonious economic and environmental development.
The Role of Connectedness in Pro-Environmental Consumption of Fashionable Commodities
Authors: Areias Salomé , Disterheft Antje , Gouveia João Pedro
Published: January 2023

A call for human-nature reconnection echoes among scholars to move consumers towards pro-environmental consumption. When addressing products that are deeply entangled with unconscious human desires and addictive behaviour and that are also part of one of the most toxic industries—such as fashionables—the need for consumer awareness is key. Studies both on connectedness to nature and moral emotions like guilt have consistently shown linkages with pro-environmental behaviour. However, deeper scrutiny regarding this pro-environmental behaviour is needed to grasp these variables’ sphere of action. This research aims to explore the first linkages between connectedness and pro-environmental consumption. We present findings from a literature review on the impact of connectedness in consumption, particularly fashionables, following an integrative approach of a semi-systematic keyword search and snowball sampling. We present a first indication of possible drivers for connectedness and their impact on pro-environmental choices.
A Model for the Assignment of Emergency Rescuers Considering Collaborative Information
Authors: Cao Pingping , Zheng Jin , Li Mingyang , Fu Yu
Published: January 2023

Emergency rescue is a critical decision for emergency response, and the assignment of rescuers is crucial to the sustainable development of emergency rescue. Therefore, how to effectively assign rescuers to carry out rescue tasks, so as to achieve the best rescue effect, is a research problem with practical value. In this paper, a model for the assignment of emergency rescuers considering collaborative information is proposed. Firstly, the synergy degrees of rescuers are calculated based on the synergy effect between rescuers and the synergy ability of rescuers. Secondly, according to the evaluation values of the skill level of rescuers, the competence degrees of rescuers are calculated and the overall ability of each rescuer is obtained. Then, the satisfaction degrees of rescuers are calculated according to the subjective preferences of rescuers. Furthermore, the task fitness degrees are obtained, and the satisfaction of rescue time is calculated. Afterwards, a model for assignment of emergency rescuers is constructed with the satisfaction of rescue time and the task fitness degrees maximization as the objectives, and the optimal assignment scheme can be obtained through solving the model. Finally, an illustrative example on the rescuer assignment under public health emergencies is given to illustrate the use of the proposed model.
Biochar as a Soil Amendment for Restraining Greenhouse Gases Emission and Improving Soil Carbon Sink: Current Situation and Ways Forward
Authors: Mosa Ahmed , Mansour Mostafa M. , Soliman Enas , El-Ghamry Ayman , El Alfy Mohamed , El Kenawy Ahmed M.
Published: January 2023

The global exponential rise in greenhouse gas (GHG) emissions over the last few decades has triggered an urgent need to contextualize low-cost and evergreen technologies for restraining GHG production and enhancing soil carbon sink. GHGs can be mitigated via incorporating biochar into soil matrix to sequestrate the mineralized carbon in a stable form upon organic matter decomposition in soil. However, the efficiency of using biochar to offset GHG emissions from soil and terrestrial ecosystems is still debatable. Moreover, in the literature, biochar shows high functionality in restraining GHG emissions in short-term laboratory studies, but it shows minimal or negative impacts in field-scale experiments, leading to conflicting results. This paper synthesizes information on the ability of biochar to mitigate carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) emissions from soil and organic biomass, with an emphasis on cropland soils. The feedstock type, pyrolysis temperature, and application rate factors showed significant effects on controlling the effectiveness of biochar in restraining GHG emissions. Our study demonstrates that biochar, taken as a whole, can be seen as a powerful and easy-to-use tool for halting the rising tide of greenhouse gas emissions. Nonetheless, future research should focus on (i) identifying other indirect factors related to soil physicochemical characters (such as soil pH/EH and CaCO3 contents) that may control the functionality of biochar, (ii) fabricating aged biochars with low carbon and nitrogen footprints, and (iii) functionalizing biologically activated biochars to suppress CO2, CH4, and N2O emissions. Overall, our paradoxical findings highlight the urgent need to functionalize modern biochars with a high capacity to abate GHG emissions via locking up their release from soil into the carbonaceous lattice of biochar.
Sustainable Legacies of a Climate Positive Olympic Games: An Assessment of Carbon Offsets and Renewable Energy for Brisbane 2032
Authors: Heynen Anthony P. , Vanaraja Ambeth Prabhakaran
Published: January 2023

Brisbane, Australia will host the Olympic and Paralympic Games in 2032—the first to be contractually obliged to be Climate Positive. This commitment can be achieved through a combination of two levers: emission reduction measures and carbon offsets. The objective of this study is to determine which combination of these levers is likely to maximise sustainability and its social, economic, and ecological dimensions. Based on these dimensions and the perspective of technology determinism, a novel sustainability assessment model is developed. Then, through a document analysis, this study uses emissions data to analyse and evaluate three different combinations of carbon offsets and renewable energy. Results showed that a higher reliance on carbon offsets resulted in poorer sustainability outcomes for this mega-event. The most sustainable scenario, involving large-scale investment in renewable energy infrastructure, involved significant cost implications but is likely to create greater legacy outcomes. Key recommendations include improving the governance and socialisation of Climate Positive delivery, and increasing partnerships with the private sector. Doing so will help enhance the authenticity and legacy of Climate Positive commitments for host regions.
Understanding Digital Identity during the Pandemic: An Investigation of Two Chinese Spanish Teachers
Authors: Li Shikun , Wu Junjie Gavin , Bian Jing , Ding Zhishuo , Sun Yuliang
Published: January 2023

During combatting the COVID-19 pandemic, the most widespread change in Spanish as a foreign language instruction is imperative online teaching. It demands that language teachers move all teaching activities to virtual platforms, facilitating the construction of their digital identities. However, there is scarce attention on Spanish teachers’ professional development, given the necessity of understanding the evolvement of their identities across virtual learning platforms. Through the lens of a case study, this research explores the digital identities of Spanish as a foreign language teachers during the school lockdown in 2022. The data includes semi-structured interviews, virtual classroom discourse, lesson plans, and reflective writing. The results show that Spanish teachers formed multiple digital identities, including curriculum innovators, vulnerable actors, involuntary team workers, overseas returnees, and academic researchers. Among them, the first three are core identities, while overseas returnees and academic researchers are peripheral identities. Regardless, they were formed and negotiated under the influence of teachers’ past experiences, the exercise of agency, emotional vulnerability, and social context. In addition, a contradictory belief in teaching was also identified during the formation of Chinese Spanish teachers’ digital identities.