bluuebunny/crossref_metadata_2025 huggingface dataset:
An Expert-Opinion-Based Evaluation Framework for Sustainable Technology-Enhanced Learning Using Z-Numbers and Fuzzy Logarithm Methodology of Additive Weights
Authors: Štilić Anđelka , Puška Edisa , Puška Adis , Božanić Darko
Published: August 2023

As technology continues to shape the landscape of education, the need for effective evaluation frameworks for sustainable technology-enhanced learning (TEL) becomes increasingly vital. This study presents an expert-opinion-based evaluation framework, utilizing Z-numbers and the fuzzy logarithm methodology of additive weights (LMAW), to assess the sustainability of TEL approaches. This framework focuses on four main criteria: cloud services compliance, cloud M-Learning essentials, system and technological advancement, and organizations management readiness. Additionally, it incorporates 17 sub-criteria to provide a comprehensive evaluation of the system. Drawing on the expertise of subject matter specialists, the evaluation framework utilizes Z-numbers to account for the inherent uncertainty and imprecision in expert judgments. The fuzzy LMAW is applied to calculate the overall scores for each criterion and sub-criterion, enabling a quantitative measure of their importance in the evaluation process. The findings of this study will contribute to the development of a robust and scientifically rigorous evaluation framework for sustainable TEL. By incorporating expert opinions and employing Z-LMAW, decision-makers and stakeholders can objectively assess the sustainability of TEL systems. This framework holds promise for informing the design and implementation of strategies to enhance the quality, compliance, and technological advancements in TEL environments.
Impacts of Red-Light Enforcement Cameras on Start-Up Lost Time at Urban Signalized Intersections
Authors: Mohamed Alshabibi Nawaf
Published: August 2023

Red-light cameras (RLCs) are used extensively in numerous countries as a tool to regulate traffic and enhance safety at signalized urban intersections. In this regard, a case study conducted in the Dammam metropolitan area has uncovered a potential unintended consequence of RLC usage. The presence of RLCs can lead to an increase in first-vehicle reaction time (FVRT), resulting in a higher start-up lost time (SLT) at these intersections. To investigate this phenomenon, data were collected from two distinct types of locations wherein three intersections were equipped with RLCs and three were without RLCs. A total of 311 observations or cycles were recorded, with 72 belonging to the first type and 239 belonging to the second type. The analysis revealed that the average FVRT for the intersections with RLCs was 4.27 s. For those without RLCs, it was slightly lower, at 3.68 s. Similarly, the average SLT for the RLC-equipped intersections was 3.63 s, while it measured 2.73 s at the non-RLC intersections. These findings highlighted a noticeable disparity in SLT between the two types of intersections. Further statistical analysis confirmed the existence of significant differences in the means of SLT and FVRT for the two categories of intersections. Specifically, for every 1-second delay in FVRT per location, the total SLT at intersections with RLCs increased by 7.5 s. These results underscored the potential impact of RLCs on traffic efficiency and supported the recommendation for implementing a red-light countdown system at intersections with RLCs. Such a system has the potential to reduce the FVRT and enhance traffic flow. These findings emphasize a careful consideration of the implications of RLC implementation and provide valuable insights for traffic management authorities.
Evaluation of Tropical Cyclone Disaster Loss Using Machine Learning Algorithms with an eXplainable Artificial Intelligence Approach
Authors: Liu Shuxian , Liu Yang , Chu Zhigang , Yang Kun , Wang Guanlan , Zhang Lisheng , Zhang Yuanda
Published: August 2023

In the context of global warming, tropical cyclones (TCs) have garnered significant attention as one of the most severe natural disasters in China, particularly in terms of assessing the disaster losses. This study aims to evaluate the TC disaster loss (TCDL) using machine learning (ML) algorithms and identify the impact of specific feature factors on the prediction of model with an eXplainable Artificial Intelligence (XAI) approach, SHapley Additive exPlanations (SHAP). The results show that LightGBM outperforms Random Forest (RF), Support Vector Machine (SVM), and Naive Bayes (NB) for estimating the TCDL grades, achieving the highest accuracy value of 0.86. According to the SHAP values, the three most important factors in the LightGBM classifier model are proportion of stations with rainfall exceeding 50 mm (ProRain), maximum wind speed (MaxWind), and maximum daily rainfall (MaxRain). Specifically, in the estimation of high TCDL grade, events characterized with MaxWind exceeding 30 m/s, MaxRain exceeding 200 mm, and ProRain exceeding 30% tend to exhibit a higher susceptibility to TC disaster due to positive SHAP values. This study offers a valuable tool for decision-makers to develop scientific strategies in the risk management of TC disaster.
Learning in Citizen Science: The Effects of Different Participation Opportunities on Students’ Knowledge and Attitudes
Authors: Berndt Josephine , Nitz Sandra
Published: August 2023

Citizen science (CS) projects are becoming increasingly popular in schools. They promise to expand knowledge, promote scientific literacy, as well as improve environmental attitudes and behavior. However, studies on the educational potential of CS projects show varying results. These inconsistent findings can be attributed to differences in the design of CS projects. It is assumed that participants who are involved in more phases of the scientific process show greater learning outcomes than participants who are involved in fewer phases. Various models about participation in CS have been developed but have not been thoroughly empirically tested. Therefore, the research question of this study is as follows: How do different participation opportunities influence the educational outcome of CS projects for students? To answer this question, a CS project was carried out with three experimental groups, whereby the participation opportunities were varied, and 199 students were included. The students’ knowledge, attitudes toward science, as well as their environmental attitudes and behavior were evaluated three times (before, shortly after, and 2–3 months after the intervention). The analyses show only minor or no statistically significant influences of the participation opportunities on participants. These results are consistent with studies that also expressed doubts about whether the level of participation determines the educational potential of CS projects.
Study on the Spatial and Temporal Distribution of the High–Quality Development of Urbanization and Water Resource Coupling in the Yellow River Basin
Authors: Huang Xin , Shen Juqin , Sun Fuhua , Wang Lunyan , Zhang Pengchao , Wan Yu
Published: August 2023

China is facing a critical period of high–speed development and a transition to high–quality development. The purpose of this study is to investigate the spatial and temporal distribution of the coupling and coordination of high–quality development of urbanization and water resources in the Yellow River Basin (YRB). Firstly, we propose the concept of “High–Quality Development of Urbanization–Water Resources Coupling” and construct a high–quality development of urbanization (HQDU) system consisting of five sub–systems: innovation, coordination, greenness, openness and sharing, and a water resources system (WRS) consisting of four sub–systems: water resources background conditions, utilization capacity, management level, and pollution control. The improved coupling coordination degree model combined with the barrier degree model and clustering model is used to study the spatial and temporal distribution of the two systems in the YRB. The results show that the coupling coordination state of HQDU and WRS in the YRB improves to some extent, from “mild imbalance” to “barely coordination” in general; Henan and Ningxia are characterized by “low and fluctuating (levels) in early years and fast development in recent years”; Shanxi and Inner Mongolia develop steadily during the study period; Sichuan, Shandong, Shaanxi, and Qinghai are characterized by “low (levels) which lasted for a long time in the early stage and accelerated development in the later stage”; and Gansu Province is characterized by “high level in the early stage but insufficient momentum in later stage”. The Coordination Index of Urbanization Economic Growth Speed and the Total Wastewater Discharge are the most important obstacle factors in HQDU and WRS. This study explores the level of coordination development of HQDU and WRS as well as finds the obstacle factors in the development process of the two systems, which is an important reference value for the high–quality development of urbanization under the constraint of water resources.
E-Waste Management in Rwanda: A Situational and Capacity Need Assessment
Authors: Kabera Telesphore , Nishimwe Honorine , Mukurarinda Juvenal
Published: August 2023

This study analyzed e-waste management and capacity need assessment for both the city of Kigali and secondary cities in Rwanda. Questionnaires were used to obtain primary data. Data collected during this study have been analyzed using the Statistical Package for Social Sciences (SPSS v.2020). Using qualitative and quantitative data on e-waste management, this study showed that a large number of respondents used repair and reuse (38.1%) and the main environmental concerns were found to be waste management problems (reported by 77.3% of respondents), water pollution (36.2%), and air pollution (20%), whereas regarding health effects, chronic diseases were the major concern (21.6%). Results showed a significant association between education levels and awareness and dissemination, with respect to Rwanda’s e-waste legislation and general e-waste knowledge. This study showed a need for urgency to introduce an extended producer responsibility (EPR) approach. It recommends the introduction of a disposal fee for every sale of electrical and electronic equipment (EEE).
Exploring the Impact of Corporate Philanthropy on Brand Authenticity in the Luxury Industry: Scale Development and Empirical Studies
Authors: Léo Trespeuch , Élisabeth Robinot
Published: August 2023

The objective of this study was to investigate the concept of perceived corporate philanthropy (PCP) among consumers of luxury goods and examine the differences these consumers perceive in terms of philanthropic actions, particularly within the luxury sector. To address this question, we adopted the following approach: (1) Defining the concept of PCP through an extensive analysis of 2590 articles using GEPHI methodology. (2) Developing a measurement scale for the PCP construct. (3) Exploring the impact of PCP on perceived brand authenticity by comparing consumers of luxury hotels and standard hotels. The results of our multigroup analysis indicated a significant difference among consumers. Corporate philanthropic strategies had a notably stronger influence on the perception of PCP among luxury hotel consumers. This finding underscores the substantial divergence within the luxury marketing literature. These consumers seek brands that align with their desire to associate themselves with robust and authentic brands that carry symbolic significance, which allows them to identify and connect with these brands. By consuming these brands, they are able to attain their desired status. This study sheds light on a significant variable in contemporary marketing, namely, PCP, which provides new avenues for differentiation and leverage within the luxury goods industry. As a result, this study provides valuable managerial recommendations to companies and NGOs, aiming to assist them in tailoring their philanthropic strategies to effectively resonate with their target audiences and bolster their brand reputation.
Human Impact on Water Circulation Patterns in Raised Bogs of the Baltic Type, Northern Poland
Authors: Lipińska Zuzanna , Cieśliński Roman , Pawłowska Marlena , Chlost Izabela , Pietruszyński Łukasz
Published: August 2023

Raised bogs of the Baltic type are unique because of their geomorphologic structure and hydrologic conditions. There are about 80 bogs of this type in Poland. All are affected by human impact, and their water circulation patterns are disrupted by artificial outflows. The aim of the study was to show the effects of human impact on water circulation patterns in raised bog on an example of the Wielkie Bagno peat bog. The main work consisted of field studies, during which measurements of groundwater fluctuations, flows at main outflows, and hydrographic mapping were performed. Data on precipitation and evaporation were also obtained from state institutions. Research has shown that fluctuations in groundwater levels in the Wielkie Bagno bog average 78 cm per year (hydrological years 2018–2019) and the bog is in poor condition. This is mainly due to climate change, which manifests itself in too little precipitation in summer and an increase in evaporation, a too dense drainage network causing the lowering of the groundwater level in the peat bog, and the close proximity of a peat mine causing significant drainage of water from the examined peat bog, as well as too large fluctuations of groundwater during the year and in individual months. In some areas, a near-surface layer of the bog was also detected, about 30 cm thick, which is a sign of bog desiccation (especially in summer). Water balance data were used to show that the quantity of water available in the bog is determined by atmospheric precipitation, which is too small in the warm period. As a consequence, there are months with a negative climatic balance. It was also observed that factors such as physical location in different parts of the bog and the degree of degradation also affect water circulation patterns in the study area. At the moment, the most important task in the peat bog is to raise the groundwater level, reduce its fluctuations, and reduce human pressure on the bog.
Monitoring Intertidal Habitats for Effects from Biosolids Applications onto an Adjacent Forestry Plantation
Authors: Campos Carlos J. A. , Berthelsen Anna , MacLean Fiona , Floerl Lisa , Morrisey Don , Gillespie Paul , Clarke Nathan
Published: August 2023

Stabilised organic solids derived from sewage sludge (“biosolids”) are applied to land as an alternative to disposal as landfill. This study evaluated the long-term effects of biosolids applied to forestry plantations on the adjacent intertidal habitats of Rabbit Island (New Zealand). On this island, biosolids are applied to enhance the growth of trees (Pinus radiata). Shoreline topography, macroalgal cover, sediment grain size, the concentrations of nutrients, trace metals, and faecal indicator bacteria, and benthic infaunal communities were studied in 2008, 2014, and 2019 at twelve intertidal transect sites (four “reference” and eight “application”) adjacent to forestry blocks where biosolids have been applied over a period of 24 years. The sediment composition did not differ significantly between the survey years or between the reference and application sites. Total nitrogen concentrations in the sediments increased over time at some transects, but such increases were not consistent among the application transects. No symptoms of excessive algal growth, sediment anoxia, and hydrogen sulphide odours were observed at most sites. Key infaunal taxa were similar between the reference and application transects. Overall, no long-term adverse changes to intertidal habitats attributed to biosolids application were detected between the reference and application sites. This study shows that biosolids application can co-occur without detectable adverse effects on nearby intertidal environments. In a global context of rising concern over climate change, environmental pollution, and resource scarcity, forest fertilisation with biosolids can facilitate biomass production and soil development while protecting valued coastal ecosystems.
Business Environment, Attitudes and Entrepreneurial Intentions as Antecedents of Entrepreneurial Inclination among University Students
Authors: Vargas-Martínez Maira Rafaela , Tavarez-De Henríquez Joselina Caridad , Colón-Flores Nirda de Jesús , Domínguez-Valerio Cándida María
Published: August 2023

Entrepreneurship education has become increasingly relevant. For some years now, the business environment for starting a new company in the Dominican Republic has been considered very propitious. This has caused many universities to incorporate training in entrepreneurship into their study plans. This study aims to analyse whether the cognitive and affective components, the country’s business environment, university training in entrepreneurship and attitudes towards entrepreneurship are antecedents of the entrepreneurial intention of university students. It also seeks to investigate the relationship between entrepreneurial intention and entrepreneurial behaviour of students. Data were collected through a structured questionnaire from a sample of 523 students who had taken courses on entrepreneurship. The data have been analysed through the SPSS and Smart-PLS programs. The results of this research highlight the importance of the affective component and attitudes towards entrepreneurship in the formation of students’ entrepreneurial intentions. This reinforces the importance of cultivating positive attitudes through educational interventions. It is also worth noting the influence of students’ entrepreneurial intentions on entrepreneurial inclinations. Finally, it is worth highlighting the high predictive power of the entrepreneurial intentions variable and more specifically the attitudes towards entrepreneurship variable as responsible for 35.38% of the variability of entrepreneurial intentions. These results contribute to the understanding of the factors that drive entrepreneurial intentions among university students and provide a foundation for future research.
Combining Data-Driven and Model-Driven Approaches for Optimal Distributed Control of Standalone Microgrid
Authors: Ahangar Parvaiz Ahmad , Lone Shameem Ahmad , Gupta Neeraj
Published: August 2023

This paper focuses on the comprehensive restoration of both voltage and frequency in a standalone microgrid (SAMG). In a SAMG, the power balance is achieved through traditional methods such as droop control for power sharing among distributed generators (DGs). However, when such microgrids (MGs) are subjected to perturbations coming from stochastic renewables, the frequency and voltage parameters deviate from their specified values. In this paper, a novel hybrid-type consensus-based distributed controller is proposed for voltage and frequency restoration. Data-based communication is ensured among the DGs for controlling voltage and frequency parameters. Different parameters such as voltage, frequency, and active and reactive power converge successfully to their nominal values using the proposed algorithms, thereby ensuring smooth operation of inverter-dominated DGs. Additionally, the machine-learning-based long short-term memory (LSTM) algorithm is implemented for renewable power forecasting using historical data from the proposed location for visualising the insolation profile. The effectiveness of our approach is demonstrated through a SAMG, which consists of four inverters, showing that the proposed approach can improve system stability, increase efficiency and reliability, and reduce costs compared to traditional methods. The complete study is performed in Python and MATLAB environments. Our results highlight the potential of data-driven approaches to revolutionise power system operation and control.
The Impact of Restoration and Protection Based on Sustainable Development Goals on Urban Wetland Health: A Case of Yinchuan Plain Urban Wetland Ecosystem, Ningxia, China
Authors: Wu Xiaolan , Bu Xiaoyan , Dong Suocheng , Ma Yushuang , Ma Yan , Ma Yarong , Liu Yulian , Wang Haixian , Wang Xiaomin , Wang Jiarui
Published: August 2023

Drawing heavily upon the Sustainable Development Goals (SDGs), an SDG–pressure–state–response (PSR)–ecological–economic–social (EES) model and an index system for wetland ecosystem health assessment were constructed from the three dimensions of environment, economy, and society. By using the Yinchuan Plain urban wetlands in the Yellow River Basin of China as a case study, their ecological health status from 2000 to 2020 was systematically evaluated by integrating information from remote sensing technology, geographic information technology, field sampling, information entropy (IE), a landscape index, and a Comprehensive Evaluation Index. The results show that the restoration and protection of wetland ecosystems have achieved remarkable results in the Yinchuan Plain. The wetland ecological health index has significantly increased from 0.26 to 0.67, which is an increase of 157.7%, and the health level increased from poor (II) to sub-healthy (IV). Factors restricting the healthy development of wetland ecology in the Yinchuan Plain include wetland construction, investment, population density, the number of tourists, and fertilizer use. The research results show that the wetland restoration and protection have achieved specific environmental, economic, and social results in the Yinchuan Plain. However, we also need to pay attention to increasing the investment in wetland environmental governance, strictly controlling the intensity of land use and the total amount of chemical fertilizer applied in various regions, scientifically carrying out wetland restoration and protection, reasonably coordinating the relationship between environment and society, and providing technical and decision-making support for wetland management and protection. This study provides a reference for the ecological governance and sustainable development of wetlands in large river basins worldwide.
Jointly Reducing Food Waste—The Experiences of the German Discussion Forum for Wholesale and Retail
Authors: Orr Lia , Goossens Yanne , Heinrich Marco , Brüggemann Nora
Published: August 2023

The global food system faces the challenge of food waste, which has significant environmental, social, and economic implications. In line with Sustainable Development Goal 12.3, the German food wholesale and retail sector has recognised the urgency of reducing food waste by 50% by 2030. However, limited scientific research exists on food waste in this sector. This study presents the implementation of a Discussion Forum as a three year project aiming to measure and reduce food waste in the German food wholesale and retail sectors. Collaboration among stakeholders played a crucial role, leading to the development of a voluntary agreement and ambitious reduction targets. The findings highlight the success of the Discussion Forum in generating high-quality data, fostering collaboration, and guiding reduction actions. Lessons learned include the practicality of data collection methods, the importance of data security and confidentiality, and the value of open discussions. The research contributes to filling the research gap in food waste studies and provides valuable insights for achieving SDG 12.3 in the wholesale and retail sectors.
Eco-Capabilities: Arts-in-Nature for Supporting Nature Visibilisation and Wellbeing in Children
Authors: Walshe Nicola , Perry Joy , Moula Zoe
Published: August 2023

Estimates of mental health disorders and poor wellbeing among children and young people in England are escalating. While maintaining a positive relationship with nature is thought to promote personal and collective wellbeing, children and young people are spending less time outdoors, exhibiting a lack of appreciation for the environment and degrees of ‘plant blindness’. As such, there is a pressing need on behalf of schools to address these issues, and to adapt to students’ needs for a deeper and more purposeful connection with nature. This study aimed to explore the potential of one avenue to achieving this: arts-in-nature practice. This involved utilising arts-based research methods, through which 97 children aged 7–10 drew their ‘happy place’, alongside participatory observations, and interviews and focus groups with artists and teachers, as part of the wider Eco-Capabilities project. Findings suggest that following the arts-in-nature sessions there was a significant increase in the number of children’s drawings which featured nature as a main focus. This was achieved in three ways: by drawing newfound attention to nature; by attributing increased value to nature; and by explicitly placing nature within the purview of wellbeing. As such, we argue that creative pedagogies outdoors likely enhance what we term ‘nature visibilisation’ in children, an outcome necessary for their personal wellbeing and sustainability of the environment. This has significant implications for school practice in relation to how to support children’s mental health and wellbeing, alongside boosting interest in environmental sustainability and pro-environmental behaviour.
Phenotypic, Geological, and Climatic Spatio-Temporal Analyses of an Exotic Grevillea robusta in the Northwestern Himalayas
Authors: Dabral Aman , Shankhwar Rajeev , Martins-Ferreira Marco Antonio Caçador , Pandey Shailesh , Kant Rama , Meena Rajendra K. , Chandra Girish , Ginwal Harish S. , Thakur Pawan Kumar , Bhandari Maneesh S. , Sahu Netrananda , Nayak Sridhara
Published: August 2023

The last five decades (since 1980) have witnessed the introduction of exotic trees as a popular practice in India to fulfill the demand of forest-based products for utilization in afforestation programmes. This study examines the distribution and habitat suitability of exotic Grevillea robusta trees in the northwestern Himalayas (state: Uttarakhand), focusing on the interaction between G. robusta and abiotic factors, such as climate, soil, and habitat suitability. This multipurpose agroforestry species is mainly grown by farmers as a boundary tree, windbreak, or shelterbelt and among intercrops on small farms in agroforestry systems worldwide. The results indicate that phenotypic plasticity is determined by tree height and diameter, indicating a higher frequency of young and adult trees. The study also highlights spatio-temporal modeling coupled with geological analysis to address the current distribution pattern and future habitat suitability range through MaxEnt modeling. The AUC ranged from 0.793 ± 3.6 (RCP 6.0_70) to 0.836 ± 0.008 (current) with statistical measures, such as K (0.216), NMI (0.240), and TSS (0.686), revealing the high accuracy of the model output. The variables, which include the minimum temperature of the coldest month (Bio 6), the slope (Slo), the mean temperature of the driest quarter (Bio 9), and the precipitation of the driest quarter (Bio 17), contribute significantly to the prediction of the distribution of the species in the Himalayan state. The model predicts a significant habitat suitability range for G. robusta based on bio-climatic variables, covering an area of approximately ~1641 km2 with maximal occurrence in Pauri (~321 km2) and Almora (~317 km2). Notably, the future prediction scenario corroborates with the regions of Tons (Upper Yamuna, Uttarkashi), Kalsi (Mussoorie, Dehradun), the Kedarnath Wildlife Sanctuary, and the Badrinath Forest Division for the potentially suitable areas. The climate was found to have a strong influence on the species’ distribution, as evidenced by its correlation with the Köppen–Geiger climate classification (KGCC) map. While the species demonstrated adaptability, its occurrence showed a high correlation with bedrocks containing an elevated iron content. Furthermore, the study also provides the first trees outside forests (TOF) map of G. robusta in the region, as well as insight into its future habitat suitability.
Identifying the Distribution and Frequency of Dust Storms in Iran Based on Long-Term Observations from over 400 Weather Stations
Authors: Mahmoudi Leila , Ikegaya Naoki
Published: August 2023

Middle Eastern countries suffer from dust events due to extended arid areas. Among them, Iran is a country experiencing a high record of dust events each year causing major environmental challenges. Although there are previous studies of the present situations of dust storm occurrences in Iran, most studies have analyzed the meteorological dataset in limited weather stations and areas in Iran. To understand the nationwide trends of the distributions and frequencies of dust storm events, comprehensive statistical evaluations of dust storm events, based on different dust categories, are required. Therefore, this study analyzes 12-year meteorological databases obtained at 427 stations in Iran to clarify the distribution of dust events and occurrence frequencies of the dust in a recent decade by classifying the dust events into suspended dust, rising dust, and dust storm. The highest record of the days belongs to rising dust, which surpassed 150 days per year, followed by suspended dust with over 100 days per year, and, finally, dust storms with a frequency of 30 days per year as annual statistics of dust events. In contrast, there were some stations that recorded minimal occurrences of dust events during the observation periods. To prove the spatial nonuniformity of the dust events, suspended dust events showed a distinct concentration in the western regions of the country, while rising dust tended to occur more frequently in the southern, eastern, and central parts of Iran. Accordingly, seasonal analyses indicate that the highest number of dust events occurred during the spring season, with the number of stations experiencing dust events being greater than during other seasons in all three categories. Nonetheless, annual analyses of dust events do not demonstrate any significant trends, with only 2012 having the highest record of dust events across all three categories. In terms of monthly analyses, dust events tended to increase from late spring to early summer in the suspended dust and rising dust categories. These analyses demonstrate the importance of studying numerous weather station datasets to clarify spatial trends of dust events with long-term variations.
Analysis of Consumers’ Green Consumption Behavior against the Background of “Carbon Peak, Carbon Neutrality”—Based on Survey Data from Anhui Province
Authors: Hu Fagang , Zhang Shufen , Yang Yaliu , Wang Kun
Published: August 2023

With the proposal of the goal of “carbon peak, carbon neutrality”, the concept of environmental protection has become increasingly popular. To explore the characteristics and influencing factors of consumers’ green consumption behavior against a dual-carbon background, this study proposed research variables and hypotheses about green consumption behavior and influencing factors. With the research purpose, research variables, and hypotheses, a questionnaire was designed. Consumers in Anhui Province were chosen as research samples. SPSS26.0 was employed to conduct reliability and validity analysis, correlation analysis, and stepwise linear regression analysis of the questionnaire data to evaluate the factors affecting consumers’ green consumption behavior; through these measures, it was verified that there existed a significant relationship between green consumption behavior and the influencing factors of purchase motivation, channel factor, consumer innovation, and price factor. And it was also verified that the influence of incentive factors and psychological factors was not significant. Based on this, the current study proposes countermeasures and suggestions for setting up environmental awareness, reducing the price of green products, expanding green consumption channels, and stimulating consumer innovation.
The Impact of the COVID-19 Pandemic on the Tourism Sector in the Autonomous Region of Madeira
Authors: Rita Paulo , António Nuno , Neves João
Published: August 2023

The highly regarded and award-winning tourism destination that is the autonomous region of Madeira (ARM), in the Madeira and Porto Santo islands, has suffered the consequences that the COVID-19 pandemic has brought to tourism through the mobility limitations as well as the fear faced by travelers. From data collected on tourism, COVID-19, and demography in ARM from the years 2019 to 2020, this study makes use of data science techniques, including statistics, data mining, and data visualization, to analyze the direct and indirect effects of the coronavirus outbreak as well as the weight of population density in the propagation of the virus. The results validate a direct effect and show evidence of dense regions having aggravated virus propagation, but they do not corroborate the idea that an indirect effect was significant.
Selecting an Optimal Approach to Reduce Drivers of Climate Change in a Complex Intuitionistic Fuzzy Environment
Authors: Razzaque Asima , Razaq Abdul , Khalid Afifa , Masmali Ibtisam , Shuaib Umer , Alhamzi Ghaliah
Published: August 2023

The sustainability of the climate is a critical concern in the modern world. A variety of acts are included in sustainability that strive to lessen our carbon footprint and maintain the fragile balance of our world. To preserve a sustainable future for future generations, we must cooperate in adopting renewable energy sources, supporting green transportation, and implementing responsible land use. In this article, we propose the concepts of complex intuitionistic fuzzy Dombi hybrid averaging (CIFDHA) and complex intuitionistic fuzzy Dombi hybrid geometric (CIFDHG) operators within the framework of a complex intuitionistic fuzzy environment. Furthermore, we explore several additional important features of these operators. To overcome the limitations of the existing score function within the CIF knowledge context, we present a new and improved score function. Additionally, we apply the proposed score function and newly defined operators to select an optimal strategy for mitigating the drivers of climate change and saving the planet’s valuable resources for a more livable and resilient planet. In order to demonstrate the validity and practicality of the suggested strategies, we conducted a comparative study of these novel techniques with existing methods.
A Microservices-Based Approach to Designing an Intelligent Railway Control System Architecture
Authors: Atanasov Ivaylo , Vatakov Vasil , Pencheva Evelina
Published: August 2023

The symmetry between customer expectations and operator goals, on one hand, and the digital transition of the railways, on the other hand, is one of the main factors affecting green transport sustainability. The European Train Control System (ETCS) was created to improve interoperability between different railway signaling systems and increase safety and security. While there are a lot of ETCS Level 2 deployments all over the world, the specifications of ETCS Level 3 are under development. ETCS Level 3 is expected to have a significant impact on automatic train operation, protection, and supervision. In this paper, we present an innovative control system architecture that allows the incorporation of artificial intelligence (AI)/machine learning (ML) applications. The architecture features control function virtualization and programmability. The concept of an intelligent railway controller (IRC) is introduced as being a piece of cloud software responsible for the control and optimization of railway operations. A microservices-based approach to designing the IRC’s functionality is presented. The approach was formally verified, and some of its performance metrics were identified.
Multiple Axes of Visual Symmetry: Detection and Aesthetic Preference
Authors: Pombo Maria , Aleem Hassan , Grzywacz Norberto M.
Published: August 2023

Little is known about the detection of and preference for multiple simultaneous parallel axes of symmetry. Neuroscientists have suggested that the detection of symmetry occurs in extrastriate brain areas with large receptive fields. Such large receptive fields may potentially hinder the simultaneous detection of more than one axis of symmetry. In contrast, psychophysicists have found that symmetry detection occurs within small spatial windows, allowing for the concurrent detection of multiple axes of symmetry. Using psychophysical and computational methods, we aim to test whether multiple axes of symmetry can be detected in parallel and to understand the role of multiple axes of symmetry on aesthetic valence. Experiment 1 provides evidence that multiple axes of symmetry cannot be detected simultaneously. However, with relatively long temporal integration, people can detect them. Experiment 2 suggests that multiple axes of symmetry tend to increase preference. However, the preference for symmetry is not universal because, although most people prefer symmetry, others prefer complex images without axes of symmetry. We present and test a computational model that explains the results of these experiments.
Symmetric Enhancement of Visual Clarity through a Multi-Scale Dilated Residual Recurrent Network Approach for Image Deraining
Authors: Bhutto Jameel Ahmed , Zhang Ruihong , Rahman Ziaur
Published: August 2023

Images captured during rainy days present the challenge of maintaining a symmetrical balance between foreground elements (like rain streaks) and the background scenery. The interplay between these rain-obscured images is reminiscent of the principle of symmetry, where one element, the rain streak, overshadows or disrupts the visual quality of the entire image. The challenge lies not just in eradicating the rain streaks but in ensuring the background is symmetrically restored to its original clarity. Recently, numerous deraining algorithms that employ deep learning techniques have been proposed, demonstrating promising results. Yet, achieving a perfect symmetrical balance by effectively removing rain streaks from a diverse set of images, while also symmetrically restoring the background details, is a monumental task. To address this issue, we introduce an image-deraining algorithm that leverages multi-scale dilated residual recurrent networks. The algorithm begins by utilizing convolutional activation layers to symmetrically process both the foreground and background features. Then, to ensure the symmetrical dissemination of the characteristics of rain streaks and the background, it employs long short-term memory networks in conjunction with gated recurrent units across various stages. The algorithm then incorporates dilated residual blocks (DRB), composed of dilated convolutions with three distinct dilation factors. This integration expands the receptive field, facilitating the extraction of deep, multi-scale features of both the rain streaks and background information. Furthermore, considering the complex and diverse nature of rain streaks, a channel attention (CA) mechanism is incorporated to capture richer image features and enhance the model’s performance. Ultimately, convolutional layers are employed to fuse the image features, resulting in a derained image. An evaluation encompassing seven benchmark datasets, assessed using five quality metrics against various conventional and modern algorithms, confirms the robustness and flexibility of our approach.
Geraghty–Pata–Suzuki-Type Proximal Contractions and Related Coincidence Best Proximity Point Results
Authors: Saleem Naeem , Raazzia Maneesha Tur , Hussain Nawab , Asiri Asim
Published: August 2023

The objective of this research paper is to establish the existence and uniqueness of the best proximity and coincidence with best proximity point results, specifically focusing on Geraghty–Pata–Suzuki-type proximal mappings. To achieve this, we introduce three types of mappings, all within the context of a complete metric space: an α-θ-Geraghty–Pata–Suzuki-type proximal contraction; an α-θ-generalized Geraghty–Pata–Suzuki-type proximal contraction; and an α-θ-modified Geraghty–Pata–Suzuki-type proximal contraction. These new results generalize, extend, and unify various results from the existing literature. Symmetry plays a crucial role in solving nonlinear problems in operator theory, and the variables involved in the metric space are symmetric. Several illustrative examples are provided to showcase the superiority of our results over existing approaches.
Analyzing Project Complexity, Its Dimensions and Their Impact on Project Success
Authors: Azmat Zeeshan , Siddiqui Mubashir Ali
Published: August 2023

Projects are undertaken in all science, engineering, and technology fields to achieve strategic and tactical goals. It is evident from the literature that projects are becoming more complex day by day, making project complexity a domain for current research. The objective of this study is to evaluate project complexity using a systematic, comprehensive, and widely accepted definition that can capture the multidimensional nature of project complexity and its impact on project success. Therefore, an integrative systemic framework has been selected to define project complexity considering seven key dimensions: context, size, diversity, autonomy, connectivity, emergence, and belonging. The study employed structural equation modeling to analyze project complexity, its dimensions and their relationship with project success for complex engineering projects. After an extensive literature review, a validated questionnaire was developed and used to obtain responses from different countries (Pakistan, China, UAE, UK, USA, and others) in the engineering fields of aerospace, design, manufacturing, oil and gas, IT, and construction. The work shows that project complexity has a negative impact on project success for complex engineering projects. Further, analyses examined the relationship between project success and the seven dimensions of project complexity. The significance of this study lies in its evaluation of project complexity using a systematic and comprehensive definition which is different from previous studies and brings more clarity and understanding of the underlying mechanisms and causal relationships between project complexity, project success and their related factors. The findings suggest that careful consideration of these dimensions and their factors can help project managers better understand and navigate project complexity and ultimately improve project success rates.
Spillover Effects and Performance Optimization of Air Pollution Control Policies: Evidence from the Yangtze River Delta Region, China
Authors: Sun Yanming , Xu Binkai
Published: August 2023

Government policy is crucial to control air pollution, while industrial structure upgrading and green technology progress are needed to optimize air pollution control performance (APCP). Meanwhile, policy spillovers from one region to another affect the APCP. This study applied systems theory to explain the mechanisms that drive both environmental policy spillover and APCP. We evaluated the APCPs of 41 cities in the Yangtze River Delta region from 2006 to 2020 using a super-efficiency SBM-DEA model. We then analyzed the paths by which industry and technology drive APCP using a spatial Durbin model (SDM) and investigated heterogeneity across different regional governance groups. The effects generated by the regulatory spillover of air pollutants were decomposed into four subsystems: chain transmission effect, vibration effect, ripple effect, and halo effect. The results show the following: (1) Throughout the study period, the APCP of most of the regional governance groups in the Yangtze River Delta region showed a fluctuating trend with continuous improvement. The APCP was higher and more stable in the Zhejiang Province in the southeast, and lower and more drastic in the Jiangsu and Anhui Provinces in the north, and shows a significant positive spatial correlation. (2) Industrial structure upgrading and green technology progress had different impact paths on the APCP. Industrial structure upgrading had a significant indirect contribution to the APCP, but the direct effect was not significant. Green technology progress had a significant direct inhibitory effect and an indirect promoting effect on the APCP. (3) In the optimization path of the APCP, industrial structure upgrading played a more important role than green technology progress, but they did not reinforce each other’s enhancement of the APCP. (4) There was regional heterogeneity in the impacts of industry and technology on the APCP. The paths and actual effects of industry and technology on the APCP varied greatly among different regional governance groups.
Structural Relationship between Attributes of Technology Acceptance for Food Delivery Application System: Exploration for the Antecedents of Perceived Usefulness
Authors: Moon Joonho , Lee Wonseok , Shim Jimin , Hwang Jinsoo
Published: August 2023

The aim of this research is to explore the antecedents of usefulness in the technology acceptance model for a food delivery application system and to confirm the accountability of the technology acceptance model in the area of food delivery application systems. The determinants of usefulness are information quality, swiftness, and food quality. For data collection, this research employs Amazon Mechanical Turk. The number of valid observations is 379. For the data analysis, confirmatory factor analysis and structural equation modeling were primarily implemented. The results indicate that usefulness is positively impacted by information quality, swiftness, and ease of use. Additionally, it is found that attitude is positively influenced by usefulness. Moreover, intention to use is positively affected by usefulness and attitude. This research is worthwhile in that it provides service providers with information for constructing better systems.
Inter-Organizational Partnering Strategies in Disaster Response: A Complex Network Perspective
Authors: Liu Chenyu , Shi Qian
Published: August 2023

Establishing appropriate inter-organizational partnership in disaster response is of great help to the improvement of disaster relief performance. However, the selection of proper disaster response organizations for government agencies to build partnerships among the numerous relief organizations remains to be addressed. To fill the gap, this paper adopted a complex network modeling method to explain the formation mechanism of inter-organizational partnership in disaster response. Then, based on a numerical simulation method, the paper compared different inter-organizational partnering strategies, and explored the optimal inter-organizational partnering strategy in the disaster response process. Results demonstrate that the optimal partnering strategy is contingent on disaster response conditions, with accurate disaster information and abundant relief materials to choose the material difference principle, and vague disaster information to choose the organizational influence principle. At the same time, frequent information communication and material cooperation allocation can be transformed into low-frequency information communication and government-led material allocation. This study provides practical guidance for disaster relief organizations to choose inter-organizational partnering strategies, and enriches the disaster organization management theory.