bluuebunny/crossref_metadata_2025 huggingface dataset:
“Digitalisation” and “Greening” as Components of Technology Upgrading and Sustainable Economic Performance
Authors: Bruno Randolph , Matusiak Monika , Osaulenko Kirill , Radosevic Slavo
Published: January 2023

This paper explores the pace and direction of technological development by using a technology upgrade conceptual and measurement framework. This approach is applied to a sample of 164 economies worldwide between 2002 and 2019. Within the framework of technology upgrading, the paper focuses on digitalisation and “greening” as its two significant structural features. We explore their relationship with different components of technology upgrading and the relationship between technology upgrading components and different indicators of macroeconomic productivity. We have adopted a longitudinal fixed effects regression method with control for unobserved heterogeneity, clustered standard errors, and time dummies. Our results show that the growth of research and development (R&D) capabilities does not translate into aggregate productivity growth. There is a lack of unconditional relationship between aggregate productivity growth, digitalisation and greening. However, there are “latecomer advantages” to basic digitalisation for lower middle- and low-income economies and “latecomer liabilities” in the greening of the economy for upper-middle-income economies. In addition, levels of digitalisation and greening do not correlate, suggesting these two transformation processes are not yet integrated into ‘ICT-assisted greening’. When we control for income levels, the impact of components of technology upgrading on productivity is isolated to specific components and significant only for some income groups. The absence of a significant simultaneous effects of several components of technology upgrading on productivity points to large transformation failures. We conclude that the role of science and technology systems in spurring sustainable development would require a broad scope for science and technology (S&T) policies, their coordination, and integration with non-innovation policies.
The KAC-CSR Model in the Tourism Sector
Authors: Peña-Miranda David Daniel , Serra-Cantallops Antoni , Ramón-Cardona José
Published: January 2023

This article carries out, for the first time in the scientific literature, an integrated analysis of the variables of knowledge, application, and communication of CSR in an economic sector (in this case, tourism), through the application of a novel model called KAC-CSR (knowledge, application, and communication of corporate social responsibility); this model interrelates the three concepts and the possible factors causing them. The objective is to identify the possible causal relationships among these CSR variables and their respective determining factors. In practice, this implies carrying out a first empirical verification of the proposed model, seeking to determine its viability as an explanatory tool. Applying the structural equation modeling (SEM) approach, using partial least squares (PLS), to a sample of 224 hotels in the Colombian Caribbean region, this analysis verifies the proposed model and specifies its characteristics. This study finds that a greater degree of advanced CSR knowledge lends itself to a greater degree of CSR application. This, in turn, positively influences CSR communication. Likewise, motivations have a positive influence on CSR application, particularly in economic and social activities, while obstacles have a negative influence on CSR application. Moreover, different characteristics of the manager and the hotels determine the levels of knowledge, application, and communication of CSR. The paper also provides evidence on the determining factors influencing the ‘knowledge–application–communication’ sequence of CSR, an aspect not studied until now. Future research should consider more stakeholders and replicate the KAC-CSR model in other economic sectors and geographical areas.
Assessment of an Optimal Design Method for a High-Energy Ultrasonic Igniter Based on Multi-Objective Robustness Optimization
Authors: Di Liming , Sun Zhuogang , Zhi Fuxiang , Wan Tao , Yang Qixin
Published: January 2023

The current deterministic optimization design method ignores uncertainties in the material properties and potential machining error which could lead to unreliable or unstable designs. To improve the design efficiency and anti-jamming ability of a high-energy ultrasonic igniter, a Six Sigma multi-objective robustness optimization design method based on the response surface model and the design of the experiment has been proposed. In this paper, the initial structural dimensions of a high-energy ultrasonic igniter have been obtained by employing one-dimensional longitudinal vibration theory. The finite element simulation method of COMSOL Multiphysics software has been verified by the finite element simulation results of ANSYS Workbench software. The optimal igniter design has been achieved by using the proposed method, which is based on the finite element method, the Optimal Latin Hypercube Design method, Grey Relational Analysis, the response surface model, the non-dominated sorting genetic algorithm, and the mean value method. Considering the influence of manufacturing errors on the igniter’s performance, the Six Sigma method was used to optimize the robustness of the igniter. The Eigenfrequency analysis and the vibration velocity ratio calculation were conducted to verify the design’s effectiveness. The results reveal that the longitudinal resonant frequency of the deterministic optimization scheme and the robustness optimization scheme are closer to the design’s target frequency. The relative error is less than 0.1%. Compared with the deterministic optimization scheme, the vibration velocity ratio of the robustness optimization scheme is 2.8, which is about 15.7% higher than that of the deterministic optimization scheme, and the quality level of the design targets is raised to above Six Sigma. The proposed method can provide an efficient and accurate optimal design for developing a new special piezoelectric transducer.
Towards the Human Circular Tourism: Recommendations, Actions, and Multidimensional Indicators for the Tourist Category
Authors: Nocca Francesca , Bosone Martina , De Toro Pasquale , Fusco Girard Luigi
Published: January 2023

As underlined by OECD and United Nations, as cities are growing in size, they will face challenges in becoming climate neutral, reducing their environmental footprint, and meeting the growing needs of their populations. In cities, the main challenges of sustainable development are concentrated. So, there is a need to identify a new development model in order to make cities more sustainable. This necessity concerns all sectors, including the tourism one, which represents the third largest socio-economic activity in Europe. The tourism sector puts pressure on the city, increasing waste generation, noise and air pollution, and congestion in infrastructure and public areas. In addition, it is organized according to the linear economy model. This linearity is particularly visible in cities as people here tend to choose comfort over sustainability. In this framework, new approaches, strategies, and tools are required in order to make the tourism sector more sustainable, thus reducing its negative impacts on cities. In this perspective, the Human Circular Tourism (HCT) model is proposed. The aim of this study is to provide an operational framework consisting of recommendations, actions, and indicators to effectively operationalize the Human Circular Tourism model and to support public authorities (and other tourism stakeholders) in the identification of efficient policies in the tourism sector.
Urban Waste: Visualizing the Academic Literature through Bibliometric Analysis and Systematic Review
Authors: Mayes-Ramírez Martha María , Gálvez-Sánchez Francisco Jesús , Ramos-Ridao Ángel Fermín , Molina-Moreno Valentín
Published: January 2023

The management of solid urban waste is one of the biggest problems currently faced by society and the economy. It can be considered a negative externality that arises as a consequence of the production and consumption processes of industry and society. This study consists of a bibliometric analysis to recognize the articles published and included in high-impact scientific journals, as well as a systematic review of the literature. We have collected 1897 research articles from the Scopus database that have been published between 1981 and 2021. We have identified the main subject areas, authors, institutions, and countries of these publications, as well as research trends in terms of resource management. Our findings show that since the 20th century, there has been quantitative and qualitative growth in this line of research, especially since 2006, and that four main trends have been defined: environment, society, technical aspects, and economic aspects. The economic field makes reference to the circular economy and its link to the objectives and sustainable development goals of the 2030 agenda, in which there is an important need to provide solutions to the problems generated as a consequence of the inadequate management of solid waste.
Subjective Well-Being of Historical Neighborhood Residents in Beijing: The Impact on the Residential Environment
Authors: Jiang Yazhuo , Chen Li , Xie Yangyang , Li Yang , Li Ting
Published: January 2023

The protection of historical neighborhood blocks is the key to maintaining Beijing’s historical and cultural significance. These districts in Beijing carry the history and culture of the city, however, their increasingly crowded environments and lack of infrastructure significantly affects the quality of life for residents. A regression analysis model is constructed in this paper based on data from a 2019 urban physical examination questionnaire deployed in Beijing. Beijing’s historical districts are taken as the research unit to analyze current residents’ satisfaction with the living environment, supporting further discussion on residents’ subjective well-being. Residents report low satisfaction overall with air pollution, service facilities, parking facilities, childcare facilities, daily shopping facilities, and other factors, suggesting that targeted improvements thereto may significantly improve residents’ subjective well-being. Analysis of different groups with different attributes reveals that the older residents of these areas tend to have higher education and income levels. It is believed that improvement in various factors of the living environment may improve subjective well-being; further, dissatisfaction with the living environment has a significant negative effect on the subjective well-being of, particularly, women and people with children in the family.
The Effects of Corruption and Innovation on Sustainability: A Firm-Level Analysis
Authors: Troisi Roberta , Nese Annamaria , Blanco-Gregory Rocío , Giovanniello Monica Anna
Published: January 2023

In recent years, analysts’ interest in understanding sustainability as a new and exclusive economic paradigm has been matched by the research for tools that might both promote and hinder it. In particular, innovation has been widely regarded for its beneficial effects on sustainability, whereas corruption has been regarded for its negative implications. This study adds to our understanding of these linkages by revealing that, depending on the nature of the sustainability targets, these important drivers can have varying effects. Therefore, using a sample of Italian firms, through SEM analysis, we estimate two latent variables representing innovation and corruption for their relationship with sustainability in two models, covering two sets of indicators (sustainable industrialization and sustainable employment and labour). Whereas both models’ results indicate that innovation and sustainability have a substantial positive link, the relationship between corruption and sustainability yields contradictory results. Furthermore, the findings show a negative relationship between innovation and corruption. As a result, the distinction between types of sustainability leads to a different interpretation of how their driving factors operate. This approach suggests the establishment of more tailored sustainability strategies, in line with the diverse consequences that may arise when corruption, innovation, and sustainability are at play.
Factors Affecting the Sustainability of Halal Product Performance: Malaysian Evidence
Authors: Mabkhot Hashed
Published: January 2023

The purpose of this research is to examine the impact of supply chain integration (SCI), demand for halal products (DHP), halal marketing (HM), process quality improvement (PQI), food safety concerns (FSCs), and health consciousness (HC) on sustainable product performance (SPP) in the halal food industry in Malaysia. A survey was conducted with 212 respondents from Malaysian halal-certified companies, and the partial least squares (PLS-SEM) method was used for the data analysis. The findings indicate a positive and significant link between SCPI, HC, PQI, and SPP. In contrast, the findings show no significant link between HM, FSC, and SPP. DHP was found to have a negative, non-significant association with SPP. This paper concludes by discussing the implications of the findings and opportunities for future research.
Investigation of Vehicular Pollutant Emissions at 4-Arm Intersections for the Improvement of Integrated Actions in the Sustainable Urban Mobility Plans (SUMPs)
Authors: Mądziel Maksymilian , Campisi Tiziana
Published: January 2023

Sustainable urban mobility planning is a strategic and integrated approach that aims to effectively address the complexities of urban transportation. Additionally, vehicle emissions are still a significant problem found in cities. Its greatest concentration involves intersections, as they have the highest number of stop-and-go operations, resulting in the highest engine load. Although electrification of vehicles is underway, the coming years and the energy crisis may cause the full transformation and fulfillment of the European Green Deal to be postponed. This state of affairs means that much effort should still go into possibly modifying the current infrastructure to make it more environmentally friendly. The article addresses the use of vertical road markings such as “stop”, “give way”, and also signal controllers signs, at four-arm X intersections. The modeling of intersection variants was carried out in the traffic microsimulation software VISSIM. The created model was calibrated according to real world data. The actual part of the work concerns the assumption of specific traffic flow scenarios, for which measurements of delay and emissions of harmful exhaust components such as NOx and PM10 were made. The results obtained can have practical application in proposals for creating unequal intersections. Based on the results, it can be concluded that below the traffic volume value of 1200 vehicles/h, an intersection can be considered with a yield sign and stop sign for two directions of traffic. However, for traffic volumes from 1200 vehicles/h to 2000 vehicles/h, an intersection with stop signs can be used for all traffic directions. The results may also provide some information on the location of the crosswalks and the improvement of strategies to be introduced into the SUMPs.
Love More and Buy More? Behavioral Economics Analysis of Travel Preference and Travel Consumption
Authors: Wei Xiang , Taivan Ariuna , Hua Gang
Published: January 2023

This study examined the interaction between travel preference and travel consumption from the perspectives of traditional and behavioral economics and analyzed the impact of travel preference on travel consumption using survey data. The WLS regression model was adopted to examine the influence of travel preference on travel consumption and the mediating role of travel demand in the relationship between travel Preference and travel consumption. The results showed that: (1) for domestic travel, the travel preference has a positive impact on travel consumption through the mediating role of travel demand; and (2) for outbound travel, the travel preference has a positive impact on outbound travel consumption through the mediating role of outbound travel demand under the transaction utility and loss aversion effects. Thus, our findings confirm previous evidence on the relevance of tourists’ preferences as a good predictor of travel consumption in the case of Chinese travelers.
Smart and Automated Infrastructure Management: A Deep Learning Approach for Crack Detection in Bridge Images
Authors: Inam Hina , Islam Naeem Ul , Akram Muhammad Usman , Ullah Fahim
Published: January 2023

Artificial Intelligence (AI) and allied disruptive technologies have revolutionized the scientific world. However, civil engineering, in general, and infrastructure management, in particular, are lagging behind the technology adoption curves. Crack identification and assessment are important indicators to assess and evaluate the structural health of critical city infrastructures such as bridges. Historically, such critical infrastructure has been monitored through manual visual inspection. This process is costly, time-consuming, and prone to errors as it relies on the inspector’s knowledge and the gadgets’ precision. To save time and cost, automatic crack and damage detection in bridges and similar infrastructure is required to ensure its efficacy and reliability. However, an automated and reliable system does not exist, particularly in developing countries, presenting a gap targeted in this study. Accordingly, we proposed a two-phased deep learning-based framework for smart infrastructure management to assess the conditions of bridges in developing countries. In the first part of the study, we detected cracks in bridges using the dataset from Pakistan and the online-accessible SDNET2018 dataset. You only look once version 5 (YOLOv5) has been used to locate and classify cracks in the dataset images. To determine the main indicators (precision, recall, and mAP (0.5)), we applied each of the YOLOv5 s, m, and l models to the dataset using a ratio of 7:2:1 for training, validation, and testing, respectively. The mAP (Mean average precision) values of all the models were compared to evaluate their performance. The results show mAP values for the test set of the YOLOv5 s, m, and l as 97.8%, 99.3%, and 99.1%, respectively, indicating the superior performance of the YOLOv5 m model compared to the two counterparts. In the second portion of the study, segmentation of the crack is carried out using the U-Net model to acquire their exact pixels. Using the segmentation mask allocated to the attribute extractor, the pixel’s width, height, and area are measured and visualized on scatter plots and Boxplots to segregate different cracks. Furthermore, the segmentation part validated the output of the proposed YOLOv5 models. This study not only located and classified the cracks based on their severity level, but also segmented the crack pixels and measured their width, height, and area per pixel under different lighting conditions. It is one of the few studies targeting low-cost health assessment and damage detection in bridges of developing countries that otherwise struggle with regular maintenance and rehabilitation of such critical infrastructure. The proposed model can be used by local infrastructure monitoring and rehabilitation authorities for regular condition and health assessment of the bridges and similar infrastructure to move towards a smarter and automated damage assessment system.
Can Digital Inclusive Finance Improve the Financial Performance of SMEs?
Authors: Yu Wei , Huang Huiqin , Kong Xinyan , Zhu Keying
Published: January 2023

Our paper takes the sample of listed companies from Shanghai and Shenzhen A-share SMEs and then theoretically analyzes and empirically tests the impact of digital inclusive finance on the financial performance of SMEs. The results show that financial performance of SMEs located in areas with a higher level of digital inclusive finance is significantly higher. Digital inclusive finance can play a role in expanding the scale of innovative investment, reducing the cost of debt financing and improving the ability of risk-taking, thereby strengthening the financial performance of SMEs. Our findings enrich the academic research on the topic of digital inclusive finance from the perspective of SMEs and provide suggestions to the government, banks and SMEs to continually implement the digital inclusive finance policy.
Understanding Intention to Use Conditionally Automated Vehicles in Thailand, Based on an Extended Technology Acceptance Model
Authors: Sakuljao Phakphum , Satiennam Wichuda , Satiennam Thaned , Kronprasert Nopadon , Jaensirisak Sittha
Published: January 2023

Automated vehicles (AVs) provide several advantages in solving issues of road traffic; including enhanced safety, reduced greenhouse gas emissions, and reduced traffic congestion. As AVs are still relatively new developments in developing countries, AV adoption faces challenges from both technological and psychological issues. Therefore, our initial research focus is on identifying the factors that influence the intention to use conditionally automated vehicles (CAVs; SAE Level 3). An extended technology acceptance model (TAM), which includes Trust, Perceived Risks, and Environmental concerns, is proposed as the predictor model in this study. The 299 participants gathered through online surveys in Thailand were examined using the Structural Equation Model (SEM) technique. In this study, Trust was shown to be the strongest predictor of Intention, followed by Perceived Ease of Use, whereas Perceived Usefulness had no impact on intention to use the SAE Level 3. The results of this study will be able to guide the forming of future policies that aim at promoting the use of AVs and helping technology developers create systems to better meet the needs of users in developing nations.
Validation of the Sun Exposure and Protection Index (SEPI) in Greek: An Instrument for Measuring Children’s Sun Protection Propensity
Authors: Theodosi Sotiroula , Nicolaidou Iolie
Published: January 2023

Skin cancer, the most common type of cancer worldwide, has been linked to overexposure to ultraviolet radiation (UVR) without protection. As skin cancer is a preventable type of cancer, there is a pressing need to adopt health-promoting behaviors early in life. The Sun Exposure and Protection Index (SEPI) is an instrument for evaluating adults’ sun exposure habits and the propensity to increase sun protection with widely accepted validity and reliability in Swedish, English, and German. The present study aims to validate SEPI with children in Greek. Data was collected from 127 primary school students in Cyprus who completed the instrument twice within two weeks. Internal consistency calculated by Cronbach’s alpha was 0.69 for all 13 items included in SEPI. A statistically significant (p < 0.01) strong and positive correlation coefficient (Pearson’s r = 0.63) was measured between the total scores for parts 1 and 2. Test–retest stability was high and significant (ρ > 0.5, p < 0.01) for all items but one. In conclusion, the Greek version of SEPI demonstrates reasonable internal consistency, as Cronbach’s alpha is at a relatively acceptable level. It can be used for evaluating prevention interventions assessing sun exposure habits, and the propensity to increase sun protection among primary school students.
Geo-Environmental Factors’ Influence on the Prevalence and Distribution of Dental Fluorosis: Evidence from Dali County, Northwest China
Authors: Yang Min , Zhao Aning , Ke Hailing , Chen Huaqing
Published: January 2023

Residents living in areas with high fluorine environmental background will ingest excessive fluorine from the atmosphere, drinking water, food and other ways. Long-term effects of fluorine on the human body could cause people suffering from dental fluorosis and influence the sustainable development of the severe fluorosis areas. Previous studies have independently discussed the high fluoride environment in Dali County from the aspects of natural environment, drinking water quality and endemic fluorosis. This study carried out a detail investigation on dental fluorosis population in seven selected villages of Dali County, Shaanxi province, northwest China. The highest dental fluorosis index of 1.9 was found in Lianjia village located near the Anren depression, while the lowest dental fluorosis index of 0.0 was found in Jiaxi village near the Yellow River alluvium. Groundwater fluorine contents the range was 0.01 mg/L to 11.80 mg/L, with the highest value (2.6 mg/L) being observed in the 2nd terrace of Weihe River. The lowest groundwater fluorine content (0.8 mg/L) was observed in the Yellow River alluvium. Soil fluorine contents ranged from 1.18 mg/kg to 13.70 mg/kg, with its highest value (13.70 mg/kg) observed in Xinfeng village near the Anren depression. The lowest value of fluorine (1.18 mg/kg) was found in soil from the 1st terrace of Weihe River. As for the fluorine contents of corn, they ranged from 4.04 mg/kg to 7.72 mg/kg. The highest value (7.72 mg/kg) appeared in the 3rd terrace of Weihe River and the lowest value (4.04 mg/kg) in the 2nd terrace of Weihe River. The soil leaching was the dominant fluorine source of groundwater environment. Areas with severe dental fluorosis are located at the edge of the depression and the conjunction between steep slope and gentle slope. A poor correlation was found between the dental fluorosis index from the seven investigated villages and the corn fluorine content contrarily to the groundwater fluorine content, which positively correlated to the dental fluorosis index. Based on the obtained results, two recommendations were done to prevent and control dental fluorosis and accelerate the sustainable development in Dali County: to strengthen the use of low fluorine groundwater for drinking water supply, and to widely install the public water purifiers in the rural communities for purifying high-fluorine water to reduce the incidence of dental fluorosis in the population.
Evaluating the Impact of COVID-19 on the Behaviour of Pedestrians
Authors: Paul Deborah , Moridpour Sara , Nguyen Le Andrew
Published: January 2023

The COVID-19 pandemic has considerably impacted pedestrians’ perceived comfort in a public setting. The virus’s transmissibility and social distancing restrictions have resulted in a shift in pedestrians’ perceived comfort, with more pedestrians becoming more conscious of other pedestrians and the distance between pedestrians. The changes in pedestrians’ perception have resulted in the Pedestrian Level Of Service (PLOS) models becoming outdated. The models may not accurately portray the actual status of pedestrians’ Level Of Service (LOS) according to the pedestrian needs during a pandemic, which generally lasts for a couple of years. These pandemics will happen in the future; hence, their impact on pedestrian comfort on sidewalks is worth considering. This research aims to analyse the effect of COVID-19 on PLOS by compiling data using a face-to-face questionnaire survey in the Melbourne Central Business District (CBD). From the 445 completed surveys, 72% of respondents extensively considered social distancing due to COVID-19 when commuting in the CBD, and 49% preferred a 1–1.5 m distance between pedestrians. In conjunction with an in-depth analysis of the data, an ordinal regression model has been used to analyse the factors that influence the perceived comfort of the pedestrians and estimate the PLOS. The model results show that pedestrian density, COVID-19 social distancing, continuous footpath, and pedestrian flow in opposite directions on the sidewalk greatly impacted the walking comfort of pedestrians during the pandemic.
Empirical Study of the Effect of Thermal Loading on the Heating Efficiency of Variable-Speed Air Source Heat Pumps
Authors: Marsik Tom , Stevens Vanessa , Garber-Slaght Robbin , Dennehy Conor , Strunk Robby Tartuilnguq , Mitchell Alan
Published: January 2023

Heating buildings with air source heat pumps (ASHPs) has the potential to save energy compared to utilizing conventional heat sources. Accurate understanding of the efficiency of ASHPs is important to maximize the energy savings. While it is well understood that, in general, ASHP efficiency decreases with decreasing outdoor temperature, it is not well understood how the ASHP efficiency changes with different levels of thermal loading, even though it is an important consideration for sizing and controlling ASHPs. The goal of this study was to create an empirical model of the ASHP efficiency as a function of two independent variables–outside temperature and level of thermal loading. Four ductless mini-split ASHPs were evaluated in a cold chamber where the temperature (representing the outdoor temperature) was varied over a wide range. For each temperature, the ASHP performance data were collected at several levels of thermal loading. The data for all four ASHPs were combined and approximated with an analytical function that can be used as a general model for the ASHP steady-state efficiency as a function of the outside temperature and level of thermal loading. To the knowledge of the authors, no such empirical model that is solely based on third-party test data has been published before. While limitations exist, the model can be used to help guide future selection and operation of ASHPs.
SCKPISec: A KPI-Guided Model-Based Approach to Realize Security by Design for Smart City Systems
Authors: Ye Tong , Zhuang Yi , Qiao Gongzhe
Published: January 2023

This paper focuses on security by design for smart city systems. Insecure smart city systems may cause serious losses to the social, environmental and economic development of smart cities. Therefore, it is essential to ensure security by design for smart city systems. For large-scale, hyper-connected smart city systems consisting of a large number of interconnected devices of different types, analyzing the impact of security threats on the whole system as well as the various aspects of smart cities at the early design stage of the system is an important and difficult problem that remains unsolved. To address this problem, this paper proposes a KPI-guided model-based approach and accompanying prototype tool, named SCKPISec (Smart City KPI-guided Security). By applying the techniques of UML modeling, formal modeling and verification, and KPIs evaluation, SCKPISec provides an effective way to realize KPI-guided security by design for smart city systems. We evaluated SCKPISec through case studies. The results show that SCKPISec can efficiently detect the potential problems of smart city systems under security threats and has high feasibility and applicability in ensuring KPI-guided security by design for smart city systems. Compared with existing model-based security approaches, the advantage of SCKPISec is that it has a highly automated verification process and provides an effective and efficient solution to evaluate the potential KPI losses of smart cities under security threats at the early design stage of smart city systems.
Understanding Antecedents of Learning Management System Usage among University Lecturers Using an Integrated TAM-TOE Model
Authors: Sulaiman Twana , Mahomed Anuar , Rahman Azmawani , Hassan Mazlan
Published: January 2023

Even after the COVID-19 pandemic, the use of the learning management system (LMS) is still low among university lecturers in the Kurdistan Region of Iraq. The objective of the current study is to understand the factors influencing LMS usage in universities using indicators from Technology Acceptance Model (TAM) and Technology–Organisation–Environment (TOE) framework. This study examined system quality, service quality, information quality, technical support, and government policies as essential variables for affecting LMS usage using perceived ease of use (PEOU) and perceived usefulness (PU) as mediating variables. To reach the aim of this study, the conceptual model was proposed based on TAM integrated with external factors adapted from TOE framework. Quantitative research using a questionnaire was conducted on a sample of 393 lecturers. The study used a structural equation modelling technique, and the results were analysed by SmartPLS 4.0 software. The findings show that information quality significantly correlates with PU and PEOU. Service quality, system quality, and government policy show a significant relationship with either PU or PEOU. However, technical support shows an insignificant relationship with PU and PEOU. Inside the TAM itself, PU and PEOU significantly correlate with LMS usage. Finally, the current study demonstrated the role of PU and POEU as mediators between external factors and LMS usage. These study findings have implications for research and practice to guide university leaders and policymakers in understanding the factors that must be addressed.
Spatialized Life Cycle Assessment of Fluid Milk Production and Consumption in the United States
Authors: Henderson Andrew D. , Asselin-Balençon Anne , Heller Martin C. , Burek Jasmina , Kim Daesoo , Lessard Lindsay , Margni Manuele , Saad Rosie , Matlock Marty D. , Thoma Greg , Wang Ying , Jolliet Olivier
Published: January 2023

Purpose: Understanding the main factors affecting the environmental impacts of milk production and consumption along the value chain is key towards reducing these impacts. This paper aims to present detailed spatialized distributions of impacts associated with milk production and consumption across the United States (U.S.), accounting for locations of both feed and on-farm activities, as well as variations in impact intensity. Using a Life Cycle Analysis (LCA) approach, focus is given to impacts related to (a) water consumption, (b) eutrophication of marine and freshwater, (c) land use, (d) human toxicity and ecotoxicity, and (e) greenhouse gases. Methods: Drawing on data representing regional agricultural practices, feed production is modelled for 50 states and 18 main watersheds and linked to regions of milk production in a spatialized matrix-based approach to yield milk produced at farm gate. Milk processing, distribution, retail, and consumption are then modelled at a national level, accounting for retail and consumer losses. Custom characterization factors are developed for freshwater and marine eutrophication in the U.S. context. Results and discussion: In the overall life cycle, up to 30% of the impact per kg milk consumed is due to milk losses that occur during the retail and consumption phases (i.e., after production), emphasizing the importance of differentiating between farm gate and consumer estimates. Water scarcity is the impact category with the highest spatial variability. Watersheds in the western part of the U.S. are the dominant contributors to the total water consumed, with 80% of water scarcity impacts driven by only 40% of the total milk production. Freshwater eutrophication also has strong spatial variation, with high persistence of emitted phosphorus in Midwest and Great Lakes area, but high freshwater eutrophication impacts associated with extant phosphorus concentration above 100 µg/L in the California, Missouri, and Upper Mississippi water basins. Overall, normalized impacts of fluid milk consumption represent 0.25% to 0.8% of the annual average impact of a person living in the U.S. As milk at farm gate is used for fluid milk and other dairy products, the production of milk at farm gate represents 0.5% to 3% of this annual impact. Dominant contributions to human health impacts are from fine particulate matter and from climate change, whereas ecosystem impacts of milk are mostly due to land use and water consumption. Conclusion: This study provides a systematic, national perspective on the environmental impacts of milk production and consumption in the United States, showing high spatial variation in inputs, farm practices, and impacts.
School-Based Interventions for Migrant Students in the Framework of the Health Promoting Whole-School Approach: An Umbrella Review
Authors: Meroni Claudia , Velasco Veronica
Published: January 2023

Health and school achievement play a crucial role in the integration of migrant students. This study aims to conduct an umbrella review of the effectiveness of school-based strategies on the academic and health outcomes of migrant school-aged children and youth and to link these intervention typologies to the Health Promoting School (HPS) approach. The study was conducted according to the PRISMA statement. Twenty-one reviews were analyzed, and 18 strategies were identified and categorized according to the six components of the HPS whole-school approach: individual skills, the school physical environment, school social environment, school policies, health and social services, and community links. Strategies related to five of the six components were identified, demonstrating that the HPS approach is a fitting framework to address migrant students’ needs. Moreover, evidence about the effects on both health and learning was shown; however, the integration of these two areas should be further explored. Finally, significant conditions that enhance or hinder implementation are described. Multi-component interventions and stakeholder engagement improve intervention impacts, while the relevance of cultural adaptation needs to be clarified. These results contribute to understanding the complexity of the challenges faced by migrant students and of the effective school-based strategies to promote their health and learning.
Multi-Step Ahead Forecasting of the Energy Consumed by the Residential and Commercial Sectors in the United States Based on a Hybrid CNN-BiLSTM Model
Authors: Chen Yifei , Fu Zhihan
Published: January 2023

COVID-19 has continuously influenced energy security and caused an enormous impact on human life and social activities due to the stay-at-home orders. After the Omicron wave, the economy and the energy system are gradually recovering, but uncertainty remains due to the virus mutations that could arise. Accurate forecasting of the energy consumed by the residential and commercial sectors is challenging for efficient emergency management and policy-making. Affected by geographical location and long-term evolution, the time series of the energy consumed by the residential and commercial sectors has prominent temporal and spatial characteristics. A hybrid model (CNN-BiLSTM) based on a convolution neural network (CNN) and bidirectional long short-term memory (BiLSTM) is proposed to extract the time series features, where the spatial features of the time series are captured by the CNN layer, and the temporal features are extracted by the BiLSTM layer. Then, the recursive multi-step ahead forecasting strategy is designed for multi-step ahead forecasting, and the grid search is employed to tune the model hyperparameters. Four cases of 24-step ahead forecasting of the energy consumed by the residential and commercial sectors in the United States are given to evaluate the performance of the proposed model, in comparison with 4 deep learning models and 6 popular machine learning models based on 12 evaluation metrics. Results show that CNN-BiLSTM outperforms all other models in four cases, with MAPEs ranging from 4.0034% to 5.4774%, improved from 0.1252% to 49.1410%, compared with other models, which is also about 5 times lower than that of the CNN and 5.9559% lower than the BiLSTM on average. It is evident that the proposed CNN-BiLSTM has improved the prediction accuracy of the CNN and BiLSTM and has great potential in forecasting the energy consumed by the residential and commercial sectors.
An Approach to Progress Learning Outcomes: International Graduate Students’ Engagement in Reflective Practice and Reflective Journal Writing during Pandemic
Authors: Zafeer Hafiz Muhammad Ihsan , Li Yanping , Maqbool Samra
Published: January 2023

Reflective practice (RP) and reflective journal writing (RJW) are considered the most important ways to enhance students’ learning progress. During the pandemic, offline learning has replaced online learning to keep students safe and healthy. This research solely examined reflective practice during online learning, which is significant as online education is less effective and students carry the full study load. However, this study’s core purpose was to determine international graduate students’ perceptions regarding RP and RJW during online learning in the pandemic period. It also investigated whether student engagement in RP enhances their critical reflection and learning progress. The mixed-method (QUAN-QUAL) approach was utilized in this study. The sample consisted of 123 international graduate students who were enrolled in various disciplines and majors in China and at least attended two consecutive semesters (24 weeks) online. The survey questionnaire was based on 28 items to collect the quantitative data. The questionnaire was categorized into four variables: self-education, learning progress, critical reflection, and engagement. While semi-structured interviews were conducted with 5 participants for qualitative data collection, the quantitative results indicated that all of the statements received good ranks and could be used to study how reflective journals helped students improve their self-education, critical reflection, writing skills, learning progress, and engagement. In addition, the results revealed a statistically significant beneficial association between engagement, self-education, critical reflection, and learning progress. Qualitative findings corroborated the quantitative results that participation in RP and RJW boosted students’ critical thinking skills and facilitated their learning and development. Based on the results, this study concluded that RP or RJW enhance success ratios as well as critical reflection, which is effective not only in learning but also in professional and practical settings.
Design of a Standard and Programmatically Accessible Interface for Smart Meters to Allow Monitoring Automation of the Energy Consumed by the Execution of Computer Software
Authors: Ortega Alberto , Cano-Delgado Abel Miguel , Prieto Beatriz , González Jesús
Published: January 2023

Software has become more computationally demanding nowadays, turning out high-performance software in many cases, implying higher energy and economic expenditure. Indeed, many studies have arisen within the IT community to mitigate the environmental impact of software. Collecting and measuring software’s power consumption has become an essential task. This paper proposes the design of a standard interface for any currently available smart meter, which is programmatically accessible from any software application and can collect consumption data transparently while a program is executed. This interface is structured into two layers. The former is a driver that provides an OS-level standard interface to the meter, while the latter is a proxy offering higher-level API for a concrete programming language. This design provides many benefits. It makes it possible to substitute the meter for a different device without affecting the proxy layer. It also allows the presence of multiple proxy implementations to offer a programmatic interface to the meter for several languages. A prototype of the proposed interface design has been implemented for a concrete smart meter and OS to demonstrate its feasibility. It has been tested with two experiments. Firstly, its correct functioning has been validated. Later, the prototype has been applied to monitor the execution of a high-performance program, a machine learning application to select the most relevant features of electroencephalogram data.
Infrared Small-Target Detection Using Multidirectional Local Difference Measure Weighted by Entropy
Authors: Yao Huang , Liu Liping , Wei Yantao , Chen Di , Tong Mingwen
Published: January 2023

Detecting small targets from infrared remote sensing images is still a challenging task. In this research, we propose a multidirectional local difference measure weighted by entropy (MDLDE) to detect small targets from infrared images with messy backgrounds. First, a new multidirectional local difference measure is proposed to suppress the clutter background. Then, the entropy, which captures the overall heterogeneity between the target and the background, is utilized to enhance the target. Lastly, an adaptive threshold was adopted to segment the target region from the background. The designed MDLDE could effectively enhance the target and simultaneously suppress the background clutter. Experimental results on six datasets indicate that the proposed method outperformed other state-of-the-art methods in terms of the signal-to-clutter ratio gain (SCRG), background suppression factor (BSF), and receiver operating characteristic (ROC) curves.
The Spatial Effect of Industrial Intelligence on High-Quality Green Development of Industry under Environmental Regulations and Low Carbon Intensity
Authors: Fatima Taqdees , Li Bingxiang , Malik Shahab Alam , Zhang Dan
Published: January 2023

In order to thoroughly investigate how industrial intelligence influences green industrial development through direct, indirect, and spatial spillover effects in China and fill in the gaps left by earlier studies, the study combines industrial intelligence and green industrial development into a single analytical framework. The findings show that implementing industrial intelligence can proactively encourage high-quality green industrial development; additionally, a strong spatial correlation is shown between industrial intelligence and high-quality green industrial development. According to spatial spillover analysis, industrial intelligence fosters the development of green industries both inside and between regions. When regional heterogeneity is analyzed, it is revealed that the eastern part of China experiences industrial intelligence effects more strongly than the central region, while the western areas are unaffected. Environmental regulations are a crucial mediating mechanism for the operation of industrial intelligence; in particular, public-participation environmental regulation and market base environmental regulations strengthen the baseline relationship; however, industrial intelligence does not impact high-quality green industrial development through administrative environmental regulation. The partial mediating effect of carbon intensity was also observed. The findings could be used as a guide for decision-making by experts and policymakers in China and other developing nations to use industrial intelligence and support the green development of the sector during economic transformation.
On the Internal Synergistic Mechanism of Operating System of Beijing’s High-Technology Industry Chain: Evidence from Science and Technology Service Industry
Authors: Yang Li , Wang Dawei , Ji Yuanpeng , Xing Lizhi
Published: January 2023

Based on the then high-tech industry policy documents issued by Beijing in 2017, this paper builds a complex network model to reflect the internal structure of Beijing’s High-Technology Industry Chain (BHIC), and then analyzes the coevolutionary mechanisms of ten top high-technology industries and their detailed sectors. Especially for the science and technology service (S&T) industry, this paper measures its function and status in the system and studies its concrete approach to stabilize the development of the industry chain. Finally, policy suggestions to promote the development of the S&T service industry in specialization, networking, and scale are put forward.