bluuebunny/crossref_metadata_2025 huggingface dataset:
How Social Impressions Affect Public Acceptance of Nuclear Energy: A Case Study in China
Authors: Yang Jie , Wang Jie , Zhang Xiaofeng , Shen Chunqi , Shao Zhijuan
Published: September 2022

Expanding the proportion of nuclear energy to shift the current energy structure and reduce carbon emission has been acknowledged by the China National Energy Administration. As a typical NIMBY facility, nuclear power plants are faced with a dilemma. Increasing the public acceptance of nuclear power is important for its development. Although multiple studies have shown the factors affecting the public acceptance, few of them focused on the effects of social impression brought about by nuclear power on public attitudes. In this study, a theoretical model was established to examine the impact of social impression (including impression management and stigmatization), knowledge, social trust, perceived risk, and perceived benefit on the public acceptance of nuclear energy. The data in this study were obtained through a questionnaire survey (N = 577) of residents near the Fangchenggang Nuclear Power Plant in China. The results showed that impression management did not directly affect the acceptance but had a positive effect on knowledge. Knowledge and perceived risk or perceived benefit play roles as chain intermediaries between impression management and public acceptance. Stigmatization negatively affects the social trust and public acceptance of nuclear energy. Social trust and perceived risk or perceived benefit act as chain intermediaries between stigmatization and public acceptance. The path “impression management affects knowledge, and knowledge affects perceived risk, then perceived risk finally affects public acceptance” is optimal among all the paths. Moreover, knowledge has no significant effect on public acceptance but negatively affects perceived risk. Social trust positively affects perceived benefit and public acceptance. It is also indicated that perceived benefit has a stronger effect on public acceptance than perceived risk. The findings in this study could inform the government regarding potential social management and recommendations on policy making.
University Students’ Perceptions of Food Waste in the UAE
Authors: Yagoub Mohamed M. , Al Hosani Naeema , AlSumaiti Tareefa , Kortbi Othmane , Alshehhi Aaesha A. , Aldhanhani Sarah R. , Albedwawi Shamma A.
Published: September 2022

This study examines the relationship between food waste and gender, income, and where students live. The research aligns with the United Nations Sustainable Development Goals 2, 11, and 12; moreover, the massive global food shortage in 2022 due to the conflict between Russia and Ukraine makes saving food a priority. A questionnaire was used to collect data from 201 students at the United Arab Emirates University (UAEU). A large proportion of the respondents were female (71.6%). The most common reasons cited by the respondents for food waste were over purchasing (31% of respondents), attitude (26.5%), and poor management (24%), while the most common reasons for having extra-cooked food were expecting guests (46%) and wanting to eat the food that had been prepared (35%). The majority of the respondents (57%) agreed that young people waste more food than older people. The methodology used in this study could be adopted by other researchers around the globe, and the output may help in developing policies and designing educational material for food waste intervention programs. Beneficiaries may therefore include food producers/consumers, environmental departments, and charitable organizations. The research contributes to the knowledge about food waste, perception, and intervention programs.
Customer Profiling Using Internet of Things Based Recommendations
Authors: Mohamed Shili , Sethom Kaouthar , Namoun Abdallah , Tufail Ali , Kim Ki-Hyung , Almoamari Hani
Published: September 2022

The digital revolution caused major changes in the world because not only are people increasingly connected, but companies are also turning more to the use of intelligent systems. The large amount of information about each product provided by the e-commerce websites may confuse the customers in their choices. The recommendations system and Internet of Things (IoT) are being used by an increasing number of e-commerce websites to help customers find products that fit their profile and to purchase what they had already chosen. This paper proposes a novel IoT based system that would serve as the foundation for creating a profile, which will store all the contextual data, personalize the content, and create a personal profile for each user. In addition, customer segmentation is used to determine which items the client wants. Next, statistical analysis is performed on the extracted data, where feelings, state of mind, and categorization play a critical role in forecasting what customers think about products, services, and so on. We will assess the accuracy of the forecasts to identify the most appropriate products based on the multi-source data thanks to the IoT, which assigns a digital footprint linking customers, processes, and things through identity-based information and recommendations, which is applied by using Raspberry Pi and other sensors such as the camera. Moreover, we perform experiments on the recommendation system to gauge the precision in predictions and recommendations.
The Impact of the Neighborhood Built Environment on the Commuting Patterns and Health of Patients with Chronic Diseases: A Case Study of Changshu, China
Authors: Wu Hao , Wang Hongbin , Liu Duanyang , Cao Yang , Qu Yawei
Published: September 2022

The health of patients with chronic diseases is affected not only by factors such as eating and living habits, but also by the neighborhood built environment, and by travel conditions. Using 18 blocks in the main urban area of Changshu, China, we performed structural equation modelling, to explore the relationships between the neighborhood built environment, the commuting patterns of patients with chronic diseases, and patient health. We first divided the commuting patterns into four categories—walking/biking, public transportation, electric vehicles/motorcycles, and cars—and conducted a street-scale questionnaire survey. Secondly, we divided ‘health’ into three latent variables—physical health, mental health, and healthy behavior—and analyzed the factors influencing the street environment. Finally, we verified our theoretical framework through a mathematical statistical analysis model. We found that: (1) service facility, environmental quality, and community safety perception in the neighborhood built environment significantly impacted commuting patterns; (2) the patient’s physical health was significantly correlated with healthy behaviors and daily commuting patterns; and (3) socioeconomic attributes directly affected neighborhood environmental satisfaction, and indirectly affected the patient’s health. Neighborhood environmental satisfaction also directly affected the patient’s health, and there was a cross-influence relationship between these factors. We propose strengthening the walkability and connectivity of the neighborhood built environment, and improving the health awareness of patients, and their willingness to participate in healthy behaviors.
A Comprehensive Review on Recent Advancements in Thermochemical Processes for Clean Hydrogen Production to Decarbonize the Energy Sector
Authors: Das Arnob , Peu Susmita Datta
Published: September 2022

Hydrogen is a source of clean energy as it can produce electricity and heat with water as a by-product and no carbon content is emitted when hydrogen is used as burning fuel in a fuel cell. Hydrogen is a potential energy carrier and powerful fuel as it has high flammability, fast flame speed, no carbon content, and no emission of pollutants. Hydrogen production is possible through different technologies by utilizing several feedstock materials, but the main concern in recent years is to reduce the emission of carbon dioxide and other greenhouse gases from energy sectors. Hydrogen production by thermochemical conversion of biomass and greenhouse gases has achieved much attention as researchers have developed several novel thermochemical methods which can be operated with low cost and high efficiency in an environmentally friendly way. This review explained the novel technologies which are being developed for thermochemical hydrogen production with minimum or zero carbon emission. The main concern of this paper was to review the advancements in hydrogen production technologies and to discuss different novel catalysts and novel CO2-absorbent materials which can enhance the hydrogen production rate with zero carbon emission. Recent developments in thermochemical hydrogen production technologies were discussed in this paper. Biomass gasification and pyrolysis, steam methane reforming, and thermal plasma are promising thermochemical processes which can be further enhanced by using catalysts and sorbents. This paper also reviewed the developments and influences of different catalysts and sorbents to understand their suitability for continuous clean industrial hydrogen production.
From Linear to Circular Ideas: An Educational Contest
Authors: Deda Denner , Barros Murillo Vetroni , Rigueiro Constança , Ribau Teixeira Margarida
Published: September 2022

This work proposes a framework with which to analyse Higher Education Institution (HEI) students’ knowledge and understanding of circular economy (CE) concepts and the potential of the CE to promote sustainability, using a contest. The framework integrates CE principles and business models with sustainable indicators, and it was applied to the accepted projects by the contest jury. The contest was launched in 2021 by the CE Working Group of the Portuguese Sustainable Campus Network to encourage creativity and the development of CE projects at HEIs. HEIs can play an essential role in promoting environmental education and creating partners with new visions for society and the economy concerning sustainability, developing knowledge, values, attitudes, and behaviours regarding the CE. The projects were mostly based on the recovery of secondary raw materials/by-products, the CE business model, and the CE principle of value optimisation. In addition, a strong relationship with environmental indicators was observed, but social and economic indicators of the CE were only marginally considered by the students. Therefore, students considered the CE as mostly mainly being related to product recovery/optimisation; thus, the CE concepts and principles and their relationship to sustainability implementation require reinforcement and transversal approaches to increase this knowledge and its dissemination.
Optimal Reconfiguration of Distribution Network Considering Stochastic Wind Energy and Load Variation Using Hybrid SAMPSO Optimization Method
Authors: Sellami Raida , Khenissi Imene , Guesmi Tawfik , Alshammari Badr M. , Alqunun Khalid , Alshammari Ahmed S. , Tlijani Kamel , Neji Rafik
Published: September 2022

Due to the stochastic characteristics of wind power generation and following varying demands for load consumption over a planning period, the optimal reconfiguration (OR) of the radial distribution network (RDN) represents a complex problem of a combinatorial nature. This paper evaluates two types of optimal reconfiguration searching for an optimal solution and considering time-varying changes. The first one is a static reconfiguration of RDN (SRRDN) made at a fixed load consumption point and during constant generated renewable power integration. The second one is a dynamic reconfiguration of RDN (DRRDN) made following a stochastic integration of wind energy (WTDG) and/or variation in load demand characteristics. In total, five scenarios are investigated in order to evaluate optimal reconfiguration of RDN (ORRDN) with the aim of reducing total active power losses (TAPL), improving the voltage profile (VP), and minimizing switches’ change costs (SCC). To deal with this, a hybrid optimization technique (SAMPSO) combining the simulated annealing algorithm (SA) with a modified particle swarm optimization (MPSO) is undertaken. This hybrid method coupled with the MATPOWER toolbox is tested on the standard IEEE 69-bus RDN through both SRRDN and DRRDN. The results show the effectiveness of this improved reconfiguration procedure for enhancing the test system performance. A comparison between the proposed optimization method and previous findings’ methods is undertaken in this work. The obtained results proved the superiority and effectiveness of the SAMPSO method in solving the SRRDN and DRRDN problems.
Performance Assessment of a Sensor-Based Variable-Rate Real-Time Fertilizer Applicator for Rice Crop
Authors: Mirzakhaninafchi Hasan , Singh Manjeet , Dixit Anoop Kumar , Prakash Apoorv , Sharda Shikha , Kaur Jugminder , Nafchi Ali Mirzakhani
Published: September 2022

Variable-rate technology (VRT) may reduce input costs, increase crop productivity and quality, and help to protect the environment. The present study was conducted to evaluate the performance of a variable-rate fertilizer applicator for rice (Oryza sativa L.). Three replications were conducted, each of which was divided into four plots. Field performance of the system was assessed at different nitrogen levels (N1 to N4, i.e., 75, 125, 175, 225 kg ha−1), growth stages (tillering, panicle initiation, heading), and heights (40, 60, 80, 100 cm) of the sensor from the crop canopy. Fertilizer rate was at minimum 12.59 kg ha−1 at 10 rpm of drive-shaft rotational speed and at maximum 50.41 kg ha−1 at 40 rpm. The system response time was within the range of 3.53 to 4.93 s, with overall error ranging between 0.83% to 4.92%. Across different growth stages, when fertilizer rate was increased from N1 to N4, NDVI increased from 0.49 to 0.69. Hence, drive-shaft rotational speed is decreased from 25 to 7 rpm to shift the application rate from 30.83 to 9.15 kg ha−1. There was a 45% reduction in total fertilizer rate applied by the system, with respect to the recommended rate.
A Conflict Measures-Based Extreme Value Theory Approach to Predicting Truck Collisions and Identifying High-Risk Scenes on Two-Lane Rural Highways
Authors: Geng Zhaoshi , Ji Xiaofeng , Cao Rui , Lu Mengyuan , Qin Wenwen
Published: September 2022

Collision risk identification and prediction is an effective means to prevent truck accidents. However, most existing studies focus only on highways, not on two-lane rural highways. To predict truck collision probabilities and identify high-risk scenes on two-lane rural highways, this study first calculated time to collision and post-encroachment time using high-precision trajectory data and combined them with extreme value theory to predict the truck collision probability. Subsequently, a traffic feature parameter system was constructed with the driving behavior risk parameter. Furthermore, machine learning algorithms were used to identify critical feature parameters that affect truck collision risk. Eventually, extreme value theory based on time to collision and post-encroachment time incorporated a machine learning algorithm to identify high-risk truck driving scenes. The experiments showed that bivariate extreme value theory integrates the applicability of time to collision and post-encroachment time for different driving trajectories of trucks, resulting in significantly better prediction performances than univariate extreme value theory. Additionally, the horizontal curve radius has the most critical impact on truck collision; when a truck is driving on two-lane rural highways with a horizontal curve radius of 227 m or less, the frequency and probability of collision will be higher, and deceleration devices and central guardrail barriers can be installed to reduce risk. Second is the driving behavior risk: the driving behavior of truck drivers on two-lane rural highways has high-risk, and we recommend the installation of speed cameras on two-lane rural roads to control the driving speed of trucks and thus avoid dangerous driving behaviors. This study extends the evaluation method of truck collisions on two-lane rural highways from univariate to bivariate and provides a basis for the design of two-lane rural highways and the development of real-time dynamic warning systems and enforcement for trucks, which will help prevent and control truck collisions and alleviate safety problems on two-lane rural highways.
Supervised Machine Learning Algorithms to Predict Provenance of Archaeological Pottery Fragments
Authors: Anglisano Anna , Casas Lluís , Queralt Ignasi , Di Febo Roberta
Published: September 2022

Code and data sharing are crucial practices to advance toward sustainable archaeology. This article explores the performance of supervised machine learning classification methods for provenancing archaeological pottery through the use of freeware R code in the form of R Markdown files. An illustrative example was used to show all the steps of the new methodology, starting from the requirements to its implementation, the verification of its classification capability and finally, the production of cluster predictions. The example confirms that supervised methods are able to distinguish classes with similar features, and provenancing is achievable. The provided code contains self-explanatory notes to guide the users through the classification algorithms. Archaeometrists without previous knowledge of R should be able to apply the novel methodology to similar well-constrained classification problems. Experienced users could fully exploit the code to set up different combinations of parameters, and they could further develop it by adding other classification algorithms to suit the requirements of diverse classification strategies.
Characteristics of Phytoplankton Production in Wet and Dry Seasons in Hyper-Eutrophic Lake Taihu, China
Authors: Wei Jin , Ji Xiaonan , Hu Wei
Published: September 2022

Primary productivity plays a key role in aquatic lake ecosystems. This study addresses the characteristics of primary phytoplankton productivity and its relationship with environmental factors in a large, shallow, and eutrophic lake (Lake Taihu, China). Surface water samples were collected in wet and dry seasons from eight lake areas to investigate physicochemical factors and primary productivity. The results show obvious seasonal differences in phytoplankton primary productivity and physicochemical factors in Lake Taihu. The primary productivity in the wet season is about five times larger than that in the dry season, and the spatial distribution of primary productivity is obviously inhomogeneous in the wet season, while in the dry season, there are no significant differences in different lake areas. Most of the lake areas are in the middle eutrophic state regardless of the season; the northwest region has the heaviest degree of eutrophication, while the southeast region has the lightest degree of eutrophication. Pearson correlation indicated that nutrients are the main factors affecting primary productivity in the wet season, while temperature is the most important factor affecting primary productivity in the dry season. Multiple stepwise regression suggested that chlorophyll-a (Chl-a), temperature (T), and water transparency (SD) can be used to estimate the phytoplankton primary productivity in Lake Taihu in different seasons, and the main influencing factors for primary productivity are Chl-a, nutrients, and SD/total suspended solids (TSS) in the wet season and T, Chl-a, and SD/TSS in the dry season.
Carbon Stock Estimation of Selected Subtropical Broad-Leaved Evergreen Scrub Forest
Authors: Sajjad Aisha , Begum Shaheen , Adnan Muhammad , Chaudhry Gul-e-Saba , Ibrahim Muhammad , Jamil Noor Mehwish , Jabeen Asma , Khalid Sofia , Iram Shazia , Yik Sung Yeong , Muhammad Tengku Sifzizul Tengku
Published: September 2022

This research estimates the carbon stock of the subtropical broad-leaved evergreen scrub forest of Lehtrar, a revenue estate of Kotli Sattian, Rawalpindi, Punjab, Pakistan. A total of six nested co-centric plots of 17.84 m2 each were laid out in the forest, having two sub-plots of 5.64 m2 and 1 m2 each, for shrubs and litter, respectively. Stem density, tree height, diameter at breast height (DBH), total tree biomass, and total carbon stock were calculated. In each plot, parameters like latitude, longitude, aspect, slope, elevation, tree count, etc., were catalogued. The carbon value was calculated in pools such as aboveground biomass (AGB), belowground biomass (BGB), litter, shrubs, etc. The tree height was measured using Abney’s level and the diameter at breast height (DBH) with diameter tape, while factors such as volume, shrub mass, litter mass, total tree biomass, and total carbon stock were calculated by using standard formulas. Results showed Olea ferrugineae to be the most abundant tree species in the study area, followed by Acacia modesta. The total average DBH and height were calculated as 17.03 and 16.79, respectively, with the species Dalbergia sissoo having the greatest DBH value. The mean carbon stock came out to be 47.75 tons/ha, with plot number 3 having the highest value of carbon stock, owing to the greatest stem count. The results of the study were significant and reflected a rich stem density, rich biomass, and an adequate carbon stocking capacity. The scrub forests of the study area, being important carbon sinks, are prone to deforestation and forest degradation activities that need to be controlled by using proper forest management practices to keep their carbon sequestration ability intact, as suggested under various reducing emissions from deforestation and forest degradation (REDD initiatives of UNFCCC.
Floating Population, Housing Security and Family Medical Economic Risk
Authors: Li Tao , Zhang Yi-Tong , Zhu He-Wen , Liu Peng-Ju
Published: September 2022

With the rapid development of China’s economy and the acceleration of urbanization, the country’s housing security system is constantly improving. To address the housing difficulties experienced by low- and middle-income populations, China has formulated the housing provident fund system and the affordable housing system. However, especially for the floating population, housing and medical security have not resulted in an equalization of services. We thus analyze data from Chinese Family Panel Studies (CFPS) to describe the influence of housing security on the family medical economic risk of the floating population. According to the results, the payment of housing provident fund can effectively reduce the incidence of catastrophic health expenditures. In contrast, per capita financial expenditure on affordable housing will significantly increase family medical economic risk. Heterogeneity tests based on the household register and income levels show that the impacts of housing security vary across populations. In addition, the influence mechanism analysis shows that the impact is mediated through housing mortgage loans. Based on the conclusions drawn, three policy recommendations of optimizing the guarantee function of the housing provident fund system, expanding the coverage of affordable housing policy, and promoting the coordinated development of housing and medical security are proposed. This research not only has theoretical and practical significance for the establishment of the security system for the floating population in China but also provides an effective reference for the development of housing and medical security systems in other countries.
Structural Behavior of LC-GFRP Confined Waste Aggregate Concrete Square Columns with Sharp and Round Corners
Authors: Parichatprecha Rattapoohm , Rodsin Kittipoom , Chaiyasarn Krisada , Ali Nazam , Suthasupradit Songsak , Hussain Qudeer , Khan Kaffayatullah
Published: September 2022

Reusing construction brick waste to fabricate new concrete is an economical and sustainable solution for the ever-increasing quantity of construction waste. However, the substandard mechanical properties of the concrete made using recycled crushed brick aggregates (RBAC) have limited its use mainly to non-structural applications. Several studies have shown that the axial compressive performance of the concrete is a function of the lateral confining pressure. Therefore, this study proposes to use low-cost glass fiber-reinforced polymer (LC-GFRP) wraps to improve the substandard compressive strength and ductility of RBAC. Thirty-two rectilinear RBAC specimens were constructed in this study and tested in two groups. The specimens in Group 1 were tested without the provision of a corner radius, whereas a corner radius of 26 mm was provided in the Group 2 specimens. Specimens in both groups demonstrated improved compressive behavior. However, the premature failure of LC-GFRP wraps near the sharp corners in Group 1 specimens undermined its efficacy. On the contrary, the stress concentrations were neutralized in almost all Group 2 specimens with a 26 mm corner radius, except low-strength specimen with six layers of LC-GFRP. As a result, Group 2 specimens demonstrated a more significant improvement in peak compressive strength and ultimate strain than Group 1 specimens. An analytical investigation was carried out to assess the efficiency of existing compressive stress–strain models to predict the peak compressive stress and ultimate of LC-GFRP-confined RBAC. Existing FRP models were found unreliable in predicting the key parameters in the stress–strain curves of LC-GFRP-confined RBAC. Equations were proposed by using nonlinear regression analysis, and the predicted values of the key parameters were found in good agreement with the corresponding experimental values.
Classification of Industrial Heat Source Objects Based on Active Fire Point Density Segmentation and Spatial Topological Correlation Analysis in the Beijing–Tianjin–Hebei Region
Authors: Ma Caihong , Sui Xin , Zeng Yi , Yang Jin , Xie Yanmei , Li Tianzhu , Zhang Pengyu
Published: September 2022

The development of industrial infrastructure in the Beijing–Tianjin–Hebei(BTH) region has been accompanied by a disorderly expansion of industrial zones and other inappropriate development. Accurate industrial heat source classification data become important to evaluate the policies of industrial restructuring and air quality improvement. In this study, a new classification of industrial heat source objects model based on active fire point density segmentation and spatial topological correlation analysis in the BTH Region was proposed. First, industrial heat source objects were detected with an active fire point density segmentation method using NPP-VIIRS active fire/hotspot data. Then, industrial heat source objects were classified into five categories based on a spatial topological correlation analysis method using POI data. Then, identification and classification results were manually validated based on Google Earth imagery. Finally, we evaluated the factors influencing the number of industrial heat sources based on an OLS regression model. A total of 493 industrial heat source objects were identified in this study with an identification accuracy of 96.14%(474/493). Compared with results for nighttime fires, the number of industrial heat source objects that were identified was higher, and the spatial coverage was greater; the minimum size of the detected objects was also smaller. Based on the function of the identified industrial heat source objects, the objects in the BTH region were then divided into five categories: cement plants (21.73%), steel plants (53.80%), coal and chemical industry (12.66%), oil and gas developments (7.81%), and other (4.01%). An analysis of their operations showed that the number of industrial heat source objects in operation in the BTH region tended to first rise and then decline during the 2012–2021 period, with the peak being reached in 2013. The results of this study will aid the rationalization of industrial infrastructure in the BTH region and, by extension, in China as a whole.
An Improved Innovation Adaptive Kalman Filter for Integrated INS/GPS Navigation
Authors: Sun Bo , Zhang Zhenwei , Qiao Dianju , Mu Xiaotong , Hu Xiaochen
Published: September 2022

The performance of transportation systems has been greatly improved by the rapid development of connected and autonomous vehicles, of which high precision and reliable positioning is a key technology. An improved innovation adaptive Kalman filter (IAKF) is proposed to solve the vulnerability of Kalman filtering (KF) in challenging urban environments during integrated navigation. First, the algorithm uses the innovation to construct a chi-squared test to determine the abnormal measurement noise; on this basis, the update method of the measurement noise variance matrix is improved, and the measurement noise variance matrix is adaptively updated by the difference between the current innovation and the mean value of the innovation when the measurement data is abnormal so as to reflect the impact degree of the current abnormal measurement data, thus suppressing the filtering divergence and improving the positioning accuracy. The experimental results show that the proposed algorithm can well suppress the filtering divergence when the measurement data are disturbed. The results demonstrate that the algorithm in this paper has improved adaptiveness and stability and provides a novel idea for the development of an intelligent traffic positioning system.
Pedestrian Single and Multi-Risk Assessment to SLODs in Urban Built Environment: A Mesoscale Approach
Authors: Salvalai Graziano , Blanco Cadena Juan Diego , Sparvoli Gessica , Bernardini Gabriele , Quagliarini Enrico
Published: September 2022

Pedestrians are increasingly exposed to slow-onset disasters (SLODs), such as air pollution and increasing temperatures in urban built environments (BEs). Pedestrians also face risks that arise from the combination of the BE features, the effects of SLODs on the microclimate, their own characteristics (e.g., health and ability), and the way they move and behave in indoor and outdoor BE areas. Thus, the effectiveness of sustainable risk-mitigation solutions for the health of the exposed pedestrians should be defined by considering the overlapping of such factors in critical operational scenarios in which such emergency conditions can appear. This work provides an innovative method to define a BE-oriented pedestrian risk index through a dynamic meso-scale approach that considers the daily variation of risk conditions. The method is ensured by a quick-to-apply approach, which also takes advantage of open-source repositories and tools to collect and manage input data, without the need for time-consuming in situ surveys. The resulting risk conditions are represented through meso-scale maps, which highlight the risk differences between BEs by focusing on their open spaces as fundamental parts of the urban road network. The method is applied to a significant case study (in Milan, Italy). The results demonstrate the ability of the approach to identify key input scenarios for risk assessment and mapping. The proposed methodology can: (1) provide insights for simulation activities in critical BE conditions, thanks to the identification of critical daily conditions for each of the factors and for single and multiple risks and (2) support the development of design and regeneration strategies in SLOD-prone urban BEs, as well as the identification of priority areas in the urban BE.
Remaining Fatigue Life Predictions of Railway Prestressed Concrete Sleepers Considering Time-Dependent Surface Abrasion
Authors: Li Dan , Kaewunruen Sakdirat , You Ruilin
Published: September 2022

One of the safety-critical components of ballasted track systems is railway sleepers whose main functions are to (i) transfer vertical load, (ii) maintain rail gauge, and (iii) restrain longitudinal rail movement. Railway sleepers can be manufactured using timber, concrete, steel, composite, and any other engineered materials. Prestressed concrete sleepers are the most commonly used type worldwide because of their superior value-for-money performance. In practice, railway sleepers experience thousands of cycles of aggressive wheel–rail dynamic loads and wear deterioration can be observed over their service life. Not only does the deterioration affect track quality and geometries, but it also undermines the structural integrity of the track structures. The wear and abrasion directly decrease the capacity of railway sleepers, resulting in the reduction in service life. In this paper, the emphasis is placed on the assessment of the fatigue life of prestressed concrete railway sleepers with imperfect geometry. This study is the world’s first to establish a new fatigue simulation of railway concrete sleepers considering accumulative non-constant amplitudes, which has been validated using full-scale experimental results and empirical analyses. Parametric studies have been conducted to obtain new insights into the fatigue performance of the worn sleepers. The new findings will improve railway sleeper maintenance and inspection criteria, and will provide a new guideline on track-condition monitoring networks.
Threat Perception, Emotions and Social Trust of Global Bat Experts before and during the COVID-19 Pandemic
Authors: Straka Tanja M. , Voigt Christian C.
Published: September 2022

Speculations about the origin of SARS-CoV-2 have catapulted bats into the spotlight of scientific and societal attention, with unforeseen consequences for bat conservation. In two global surveys with bat experts before and during the COVID-19 pandemic, we assessed their (i) threat perceptions, emotions towards bats and social trust in decision makers and (ii) the predictive potential of emotions, social trust and socio-demographic variables on threat perceptions. We also discuss (iii) the potential influence of the pandemic on threat perception and antecedents (emotions and social trust). We received 495 responses from 65 countries in September 2019 and 320 responses in June 2020 from 77 countries. We identified three major threat categories (indirect, direct and prejudice). Comparing threat perception, emotions and social trust between both surveys, we found that indirect threats (e.g., habitat modification) were considered as crucial, yet less so during the pandemic. During the pandemic, experts rated indirect threats lower and the perceived threat through prejudice (e.g., myths) higher than before the pandemic. During the pandemic, bat experts also expressed more compassion and sadness related to bats and trust in researchers and NGOs, but less trust in laypeople than before the pandemic. Emotions were particularly important predictors for threats through prejudice besides social trust. Socio-demographic variables (e.g., cultural and professional background) had predictive potential predominantly for direct threats (e.g., hunting and trade, wind turbines) and threats through prejudice. Our study highlights the role of emotions and social trust on threat perception among bat experts who remained relatively invisible during the pandemic despite their key role for bat conservation. More importantly, we echo previous calls to be more attentive to ecological grief also within the scientific community; especially as discussions around zoonotic spillover with valued study animals intensify.
Research on Deformation and Failure Control Technology of a Gob-Side Roadway in Close Extra-Thick Coal Seams
Authors: Zhao Bin , He Shengquan , He Xueqiu , Gao Le , Li Zhenlei , Song Dazhao , Shen Feng
Published: September 2022

Close extra-thick coal seams are subject to the broken overburden of mined coal seams, and the deformation and damage of the roadways is serious, which affects the safe operation of the mine. To reduce the deformation and damage of the roadways, this paper studied the deformation and damage law of the gob-side roadway in close extra-thick coal seams through numerical simulation and field monitoring, compared and analyzed the deformation and damage characteristics of the roadway under different reinforcement support methods, determined the optimal reinforcement support method, and carried out field verification. The obtained results indicated that the deformation and damage of the gob-side roadway showed asymmetric characteristics. The large deformation of the coal body in the deep part of the roadway wall is an important reason for the continuous occurrence of roadway wall heave in the coal pillar. Under the action of unbalanced support pressure, the floor is subject to the coupling effect of horizontal extrusion pressure and vertical stress that cause extrusion mobility floor heave. The horizontal and vertical displacement of the coal pillar side of the roadway under different support methods is much larger than that of the solid coal side. Increasing the anchor cable length and fan-shaped arrangement can improve the support effect. Grouting at the coal pillar side can significantly improve the bearing capacity and stability of the coal pillar. The effect of floor grouting is much better than the anchor cable in controlling the floor heave. The integrated reinforcement method of anchor cable + coal pillar side grouting + floor grouting has the best effect with the least horizontal and vertical deformation. The research results are of great significance for ensuring the stability of similarly endowed roadways.
Research on the Impact of Ambidextrous Innovation on Sustainable Entrepreneurial Performance from a Policy-Oriented Perspective
Authors: Zhu Tao , Peng Huatao
Published: September 2022

Based on the theory of dynamic capability theory, this study takes 671 listed companies in China’s ICT industry from 2010 to 2021 as a sample to explore the impact mechanism of policy-oriented ambidextrous innovation on sustainable entrepreneurial performance. The study found that exploratory innovation can promote sustainable entrepreneurial performance, but both government subsidy and environmental tax will weaken the relationship between exploratory innovation and sustainable entrepreneurial performance. Exploitative innovation can promote sustainable entrepreneurial performance, but environmental tax will weaken the relationship between exploitative innovation and sustainable entrepreneurial performance. The main contributions of this study include the following. (1) Unlike previous studies that focus on the impact of ambidextrous innovation on corporate financial performance, this study is forward-looking in pointing out the importance of sustainable entrepreneurial performance, and explores the impact of ambidextrous innovation on sustainable entrepreneurial performance. (2) This study proposes a theoretical framework for government policy analysis, arguing that government policy should not only focus on its support policies (government subsidy), but also on regulatory policies (environmental tax). (3) The conclusions of this study have certain reference significance for enterprises to correctly use government policies, construct appropriate ambidextrous innovation strategies, and improve sustainable entrepreneurial performance.
The Effect of Perceived Usefulness, Reliability, and COVID-19 Pandemic on Digital Banking Effectiveness: Analysis Using Technology Acceptance Model
Authors: Ghani Erlane K. , Ali Mazurina Mohd , Musa Muhammad Nazmy Rezzaimy , Omonov Akrom A.
Published: September 2022

This study examined the digital banking effectiveness of a bank. This study specifically explored the effect of perceived usefulness, banking system reliability, and COVID-19 pandemic on the digital banking effectiveness of a bank in Malaysia based on the technology acceptance model (TAM). Data collection was undertaken using a questionnaire survey involving 228 clients of the bank. The findings indicated that two of the chosen factors, namely, perceived usefulness and reliability of the banking system, significantly influenced digital banking effectiveness. On the other hand, the findings also showed that the COVID-19 pandemic did not influence digital banking effectiveness, per the bank clients’ perspective. The study’s findings provide insight into the future financial direction and addresses consumers’ financial needs. In addition, the findings help develop an overview of the industry based on one of the prominent financial institutions in Malaysia.
Antecedents of Residential Satisfaction in Resettlement Housing in Ellembelle: A PLS-SEM Approach
Authors: Boadi Emmanuel Bosompem , Chen Shaojun , Amponsah Ebenezer Impriam , Appiah Ruth
Published: September 2022

Compensation for land expropriation due to development projects such as mining is shifting from cash to physical assets like housing. Therefore, empirical studies are required to assess the residential satisfaction of project-affected families (PAFs) living in these houses and the factors which can enhance their satisfaction and quality of life in the long term. This study, therefore, assesses the antecedents of PAFs’ satisfaction with their current residence as an outcome of a mining-induced displacement and resettlement (MIDR) in Ellembelle, Ghana. The study adopted SPSS and PLS-SEM to assess the data retrieved from the heads or representatives of the PAFs. The study’s outcome reveals that the neighborhood environment plays the most significant role in predicting the PAFs’ satisfaction, followed by the public facilities and dwelling unit. The study has numerous implications for the resettlement stakeholders, housing policy, and mining development.
Programmable Electronic Load Prototype for the Power Quality Analysis of an Experimental Microgrid
Authors: Medina-Ortega Cristhian E. , Patiño-Noguera Martín A. , Revelo-Fuelagán Javier , Candelo-Becerra John E.
Published: September 2022

Microgrids have been widely adopted in many countries because they provide more reliable electricity service to those users connected to the power grid. These systems comprise various power sources, energy storage devices, and loads. However, detailed studies require considering linear and nonlinear loads, which are now used in this type of network. In addition, experimental tests require devices that emulate loads, represent different topologies, and construct assemblies for better identification, validation, and theoretical approximations of the power grid. Therefore, this paper presents a programmable electronic load to emulate linear and nonlinear loads of a microgrid, based on the control of a single-phase voltage source converter that considers rectification and power dissipation stages. Furthermore, a control stage allows power consumption variations, controlling the current demanded by the load, according to the reference current waveform programmed through a user interface. A synchronous reference frame phase-locked loop is implemented on a microcontroller. Thus, the programmable electronic load enables studying power quality in microgrids. Finally, the operation of the programmable electronic load is validated through experimental and simulation tests, considering different case studies.
The Impact of a Proposed Mathematics Enrichment Program on UAE Students’ Mathematical Literacy Based on the PISA Framework
Authors: Almarashdi Hanan Shaher , Jarrah Adeeb M.
Published: September 2022

The main objective of this study is to investigate the impact of a proposed mathematical enrichment program based on the Programme for International Student Assessment (PISA) framework for mathematical literacy. Mathematical literacy is essential because it helps students understand and use real-world mathematics frequently tested in many international assessments. PISA has received special attention because of its place on the national agenda of the United Arab Emirates (UAE), which aspires to become a globally preeminent nation. This quantitative research employed a non-equivalent pre- and post-test quasi-experimental method. A mathematical literacy test was used to collect data from a sample of 102 students of 10th grade in the UAE. The findings revealed a statistically significant difference between the experimental and control groups and an effect size above the mean according to the covariate analysis. The female students recorded greater improvement than the males. Overall, the results obtained from this study revealed that implementing mathematics enrichment programs based on the PISA framework might be one of the solutions to enhance students’ mathematical literacy.
Exploring the Relationship between Chinese Urban Residents’ Perceptions of Sustainable Consumption and Their Efficiency Behavior: A Mediation and Moderation Analysis Based on the Social Practice Approach
Authors: Liang Jianfang , Wang Ruiwen , Li Jingjun
Published: September 2022

There exists a problem of insufficient perception of sustainable consumption and the “perception–action paradox” among Chinese urban residents. To address this problem, we construct a holistic research framework, integrating micro and macro levels based on the “Social Practice Approach”, with lifestyle as the mediating variable and supply conditions as the moderating variable. This study aims to reveal the relationship between the sustainable consumption perception and efficiency behaviors of Chinese urban residents, as well as the associated influence mechanisms. Our results show that a sustainable consumption perception exerts a significantly positive influence on four dimensions of lifestyle and efficiency behaviors. Significant differences are explicitly identified among the four dimensions of lifestyle on efficiency behavior, and the mediating effect between sustainable consumption perception and efficiency behaviors, especially the development concern and price concern. Product sustainability perception and product facility availability conditions significantly positively moderate the relationship between sustainable consumption perception and efficiency behavior. Exploring the four dimensions of lifestyle and their deep-seated mediation effect on efficiency behavior will broaden the theoretical perspective of efficiency behavior research and guide sustainable consumption practices in China.
Saving CO2 Emissions by Reusing Organic Growing Media from Hydroponic Tomato Production as a Source of Nutrients to Produce Ethiopian Kale (Brassica carinata)
Authors: Vollmer Adrian , Geilfus Christoph-Martin , Nerlich Annika , Dannehl Dennis
Published: September 2022

Large quantities of growing media residues that are rich in nutrients are disposed of after their use in hydroponics. The objective of this study was to investigate the benefits of different organic growing media (wood fibers, hemp fibers, sphagnum moss) residues from hydroponic tomato production as a nutrient source to produce Ethiopian kale. The amount of nutrients that can be reused as fertilizer and the associated CO2 savings have been calculated. Kale was cultivated in sand-residue mixtures, either with 25 or 50 vol% of the mentioned growing media residues. Control treatments with sand with or without nutrient addition were cultivated too. The incorporation of all growing media residues to sand increased the field capacity and growth. Plants that were supplemented with hemp fiber residues showed the strongest growth and highest yields. However, the hemp fiber residues that are used are not suitable for use in the open field due to its excessive content of certain nutrients, which restrict the output quantity. Regarding the fertilization effect of growing media residues, it was calculated that 11–300 kg nutrients ha−1 (N, P, K, Mg, Ca, S), with an average primary energy demand of 90–3435 MJ and 6–317 kg CO2 eq, could potentially be saved when different crops were considered.