bluuebunny/crossref_metadata_2025 huggingface dataset:
Holiday Internet Usage Time and the Risk of Internet Addiction Tendency among Working Adults in their 30s in Japan
Authors: Matsuo Keitaro , Tateno Masaru , Katsuki Ryoko , Nakao Tomohiro , Kato Takahiro A.
Published: July 2023

Introduction: A positive association between Internet usage time and Internet addiction among adolescents and adults has been frequently reported; however, studies of working adults focusing on weekdays and holidays are limited. Therefore, this study aimed to elucidate the association between Internet usage time and psychometric tests among working adults in their 30s, focusing on weekdays and holidays. Methods: A total of 129 workers aged 30–39 years participated in this study. Participants completed a questionnaire and interview regarding psychometric tests, including Internet usage time, Internet addiction tendency, smartphone addiction tendency, depression tendency, and personality traits. A correlation analysis focusing on differences between weekdays and holidays was conducted. Results: The scores on Internet addiction scales are weakly positively correlated with holiday Internet usage time. The scores of smartphone addiction scales are also weakly positively correlated with the holiday Internet time. No correlation was found between weekdays Internet usage time and scores on Internet addiction scales. Conclusions: Internet usage time during holidays is associated with Internet addiction tendency among the working adult samples. Holiday Internet usage time could be a useful indicator of risk of Internet addiction. Our pilot findings provide clues to the mental health affected by the Internet, especially among adults.
Toward a Buddhist Ecological Ethic of Care
Authors: Simonds Colin Harold
Published: July 2023

This article thinks alongside the feminist ethic of care tradition to articulate a Tibetan Buddhist ethical approach to the more-than-human world. It begins by unpacking the characterization of Tibetan Buddhist ethics as a moral phenomenology before highlighting the major parallels between Buddhist moral phenomenology and the ethic of care tradition. Having made these parallels evident, this article then looks at how the ethic of care tradition has been applied to issues in animal ethics and environmental ethics to similarly think through how a Buddhist moral phenomenology might function in these more-than-human contexts. To further nuance this ecological application of Buddhist ethics, this article then takes up the question of veganism and argues that a Tibetan Buddhist care ethic would ideally adopt the positions of ethical veganism while also recognizing the socio-economic barriers to doing so in certain contexts. Ultimately, this article argues that when Buddhist moral phenomenology is applied to the more-than-human world, it presents as a Buddhist ecological ethic of care which recognizes the interconnected nature of duhkha, the necessity of approaching situations with care as one’s primary conative mode, and an emphasis on context, relationships, and positionality.
Ground-Based Remote Sensing of Atmospheric Water Vapor Using High-Resolution FTIR Spectrometry
Authors: Wu Peng , Shan Changgong , Liu Chen , Xie Yu , Wang Wei , Zhu Qianqian , Zeng Xiangyu , Liang Bin
Published: July 2023

Understanding the distribution of atmospheric water vapor (H2O) is crucial for global warming studies and climate change mitigation. In this study, we retrieved the ground layer, tropospheric and total columns of H2O using ground-based high-resolution Fourier transform infrared spectrometry (FTIR). The H2O total columns are obtained from near-infrared (NIR) and mid-infrared (MIR) spectra, and the ground layer and tropospheric H2O columns are retrieved from the MIR spectrum. The total columns of H2O retrieved from NIR and MIR have a good consistency (R = 0.989). Additionally, the ground layer H2O columns have a similar seasonal variation to total columns and tropospheric columns but have a higher seasonal amplitude. The ground layer H2O columns are close to the total columns and tropospheric columns in winter; however, in summer, the average difference between the ground layer and total columns and the value between the ground layer and tropospheric columns are large. This is mostly due to temperature variation. The temperature has a linear response to H2O, and the relationship between surface temperature and ln(XH2O) values in the ground layer, the entire atmosphere and the troposphere show a significantly positive correlation, and the correlation coefficient R is 0.893, 0.882 and 0.683, respectively. Furthermore, we selected the HYSPLIT model to simulate the back trajectories of air parcels in the four seasons in Hefei and find that the air mass transport has a significant impact on the local H2O change. These results demonstrate that ground-based high-resolution FTIR technology has high accuracy and precision in observing the vertical distribution and seasonal changes of H2O in different atmospheres.
The Application of CNN-Based Image Segmentation for Tracking Coastal Erosion and Post-Storm Recovery
Authors: Kang Byungho , Duran Vinent Orencio
Published: July 2023

Coastal erosion due to extreme events can cause significant damage to coastal communities and deplete beaches. Post-storm beach recovery is a crucial natural process that rebuilds coastal morphology and reintroduces eroded sediment to the subaerial beach. However, monitoring the beach recovery, which occurs at various spatiotemporal scales, presents a significant challenge. This is due to, firstly, the complex interplay between factors such as storm-induced erosion, sediment availability, local topography, and wave and wind-driven sand transport; secondly, the complex morphology of coastal areas, where water, sand, debris and vegetation co-exists dynamically; and, finally, the challenging weather conditions affecting the long-term small-scale data acquisition needed to monitor the recovery process. This complexity hinders our understanding and effective management of coastal vulnerability and resilience. In this study, we apply Convolutional Neural Networks (CNN)-based semantic segmentation to high-resolution complex beach imagery. This model efficiently distinguishes between various features indicative of coastal processes, including sand texture, water content, debris, and vegetation with a mean precision of 95.1% and mean Intersection of Union (IOU) of 86.7%. Furthermore, we propose a new method to quantify false positives and negatives that allows a reliable estimation of the model’s uncertainty in the absence of a ground truth to validate the model predictions. This method is particularly effective in scenarios where the boundaries between classes are not clearly defined. We also discuss how to identify blurry beach images in advance of semantic segmentation prediction, as our model is less effective at predicting this type of image. By examining how different beach regions evolve over time through time series analysis, we discovered that rare events of wind-driven (aeolian) sand transport seem to play a crucial role in promoting the vertical growth of beaches and thus driving the beach recovery process.
First Ocean Wave Retrieval from HISEA-1 SAR Imagery through an Improved Semi-Automatic Empirical Model
Authors: Sun Haiyang , Geng Xupu , Meng Lingsheng , Yan Xiao-Hai
Published: July 2023

The HISEA-1 synthetic aperture radar (SAR) minisatellite has been orbiting for over two years since its launch in 2020, acquiring numerous high-resolution images independent of weather and daylight. A typical and important application is the observation of ocean waves, essential ocean dynamical phenomena. Here, we proposed a new semi-automatic empirical method to retrieve ocean wave parameters from HISEA-1 images. We first applied some automated processing methods to remove non-wave information and artifacts, which largely improves the efficiency and robustness. Then, we developed an empirical model to retrieve significant wave height (SWH) by considering the dependence of SWH on azimuth cut-off, wind speed, and information extracted from the cross-spectrum. Comparisons with the Wavewatch III (WW3) data show that the performance of the proposed model significantly improved compared to the previous semi-empirical model; the root mean square error, correlation, and scattering index are 0.45 m (0.63 m), 0.87 (0.75), and 18% (26%), respectively. Our results are also consistent well with those from the altimeter measurements. Further case studies show that this new ocean wave model is reliable even under typhoon conditions. This work first provides accurate ocean-wave products from HISEA-1 SAR data and demonstrates its ability to perform high-resolution observation of coasts and oceans.
Variations of Remote-Sensed Forel-Ule Index in the Bohai and Yellow Seas during 1997–2019
Authors: Zhang Baohua , Guo Junting , Rong Zengrui , Lv Xianqing
Published: July 2023

Water color, often quantified using the Forel-Ule Index (FUI), is a crucial parameter for assessing the water quality and ecological health of coastal waters. However, there is limited research on the spatiotemporal variations of FUI and the associated influencing factors in the Bohai and Yellow Seas. In this study, we utilized multi-sensor satellite datasets to retrieve monthly FUI products for the Bohai and Yellow Seas spanning the period from September 1997 to December 2019. Subsequently, we examined significant spatial disparities and variations across multiple timescales in the remotely sensed FUI time series. The climatological annual mean FUI map reveals a decreasing trend from nearshore to offshore regions, with similar spatial patterns observed in terms of overall and interannual FUI variability. The annual variations in wind field, sea surface temperature (SST), and ocean stratification play a key role in the seasonal dynamics of FUI by modulating the sediment resuspension process, resulting in low FUI values in summer and high FUI values in winter. Linear regression analysis of FUI anomaly indicates a long-term decreasing trend in FUI for the three bays of the Bohai Sea, while upward trends in FUI predominantly prevail in the central Yellow Sea. Factors related to interannual FUI variations, such as surface winds, SST, river outflow, rainfall, and anthropogenic activities, are qualitatively discussed. The findings of this study provide the first comprehensive evaluation of water color variations and their underlying mechanisms in the Bohai and Yellow Seas.
Wetland Mapping in Great Lakes Using Sentinel-1/2 Time-Series Imagery and DEM Data in Google Earth Engine
Authors: Mohseni Farzane , Amani Meisam , Mohammadpour Pegah , Kakooei Mohammad , Jin Shuanggen , Moghimi Armin
Published: July 2023

The Great Lakes (GL) wetlands support a variety of rare and endangered animal and plant species. Thus, wetlands in this region should be mapped and monitored using advanced and reliable techniques. In this study, a wetland map of the GL was produced using Sentinel-1/2 datasets within the Google Earth Engine (GEE) cloud computing platform. To this end, an object-based supervised machine learning (ML) classification workflow is proposed. The proposed method contains two main classification steps. In the first step, several non-wetland classes (e.g., Barren, Cropland, and Open Water), which are more distinguishable using radar and optical Remote Sensing (RS) observations, were identified and masked using a trained Random Forest (RF) model. In the second step, wetland classes, including Fen, Bog, Swamp, and Marsh, along with two non-wetland classes of Forest and Grassland/Shrubland were identified. Using the proposed method, the GL were classified with an overall accuracy of 93.6% and a Kappa coefficient of 0.90. Additionally, the results showed that the proposed method was able to classify the wetland classes with an overall accuracy of 87% and a Kappa coefficient of 0.91. Non-wetland classes were also identified more accurately than wetlands (overall accuracy = 96.62% and Kappa coefficient = 0.95).
Analysis of PlanetScope Dove Digital Surface Model Accuracy Using Geometrically Simulated Images
Authors: Noh Myoung-Jong , Howat Ian M.
Published: July 2023

Many objectives in geoscience and engineering require Earth surface elevations at greater temporospatial resolution and coverage than are currently available. This may be achieved with stereo imagery from large constellations of “small sats”, such as PlanetScope Doves. Obtaining Digital Surface Models (DSMs) of sufficient quality from these images is challenging due to their lower resolution and weaker stereo geometry relative to stereo mode satellites such as WorldView. The quality can be improved by utilizing their much larger numbers of repeat images, but this requires effective stereopair selection. To determine the stereo geometries required for obtaining quality DSMs from PlanetScope Dove imagery, we apply a new methodology for generating simulated stereo images of varying geometries using adjusted orientation parameters obtained by a self-calibrating bundle adjustment and validated by comparing the resulting rigorous sensor and rational function models. The accuracies of simulated stereo and multi-pair DSMs are then assessed through comparison to a reference DSM, providing the relationship between specific imaging geometries and DSM quality. Our results provide a basis for automated stereo imagery selection to enable large-scale DSM production from PlanetScope Dove imagery. Our methodology can be applied to other sources of stereo imagery and designing future satellite missions. In the future, we will further develop multi-pair matching algorithms for generating DSMs with Dove Classic images to improve both accuracy and quality that are otherwise limited by the weak stereo geometry of single stereo pairs.
Inertial Sensor Technologies—Their Role in Equine Gait Analysis, a Review
Authors: Crecan Cristian Mihăiță , Peștean Cosmin Petru
Published: July 2023

Objective gait analysis provides valuable information about the locomotion characteristics of sound and lame horses. Due to their high accuracy and sensitivity, inertial measurement units (IMUs) have gained popularity over objective measurement techniques such as force plates and optical motion capture (OMC) systems. IMUs are wearable sensors that measure acceleration forces and angular velocities, providing the possibility of a non-invasive and continuous monitoring of horse gait during walk, trot, or canter during field conditions. The present narrative review aimed to describe the inertial sensor technologies and summarize their role in equine gait analysis. The literature was searched using general terms related to inertial sensors and their applicability, gait analysis methods, and lameness evaluation. The efficacy and performance of IMU-based methods for the assessment of normal gait, detection of lameness, analysis of horse–rider interaction, as well as the influence of sedative drugs, are discussed and compared with force plate and OMC techniques. The collected evidence indicated that IMU-based sensor systems can monitor and quantify horse locomotion with high accuracy and precision, having comparable or superior performance to objective measurement techniques. IMUs are reliable tools for the evaluation of horse–rider interactions. The observed efficacy and performance of IMU systems in equine gait analysis warrant further research in this population, with special focus on the potential implementation of novel techniques described and validated in humans.
An Improved Pig Counting Algorithm Based on YOLOv5 and DeepSORT Model
Authors: Huang Yigui , Xiao Deqin , Liu Junbin , Tan Zhujie , Liu Kejian , Chen Miaobin
Published: July 2023

Pig counting is an important task in pig sales and breeding supervision. Currently, manual counting is low-efficiency and high-cost and presents challenges in terms of statistical analysis. In response to the difficulties faced in pig part feature detection, the loss of tracking due to rapid movement, and the large counting deviation in pig video tracking and counting research, this paper proposes an improved pig counting algorithm (Mobile Pig Counting Algorithm with YOLOv5xpig and DeepSORTPig (MPC-YD)) based on YOLOv5 + DeepSORT model. The algorithm improves the detection rate of pig body parts by adding two different sizes of SPP networks and using SoftPool instead of MaxPool operations in YOLOv5x. In addition, the algorithm includes a pig reidentification network, a pig-tracking method based on spatial state correction, and a pig counting method based on frame number judgment on the DeepSORT algorithm to improve pig tracking accuracy. Experimental analysis shows that the MPC-YD algorithm achieves an average precision of 99.24% in pig object detection and an accuracy of 85.32% in multitarget pig tracking. In the aisle environment of the slaughterhouse, the MPC-YD algorithm achieves a correlation coefficient (R2) of 98.14% in pig counting from video, and it achieves stable pig counting in a breeding environment. The algorithm has a wide range of application prospects.
Assessment of Sea-Surface Wind Retrieval from C-Band Miniaturized SAR Imagery
Authors: Wang Yan , Li Yan , Xie Yanshuang , Wei Guomei , He Zhigang , Geng Xupu , Shang Shaoping
Published: July 2023

Synthetic aperture radar (SAR) has been widely used for observing sea-surface wind fields (SSWFs), with many scholars having evaluated the performance of SAR in SSWF retrieval. Due to the large systems and high costs of traditional SAR, a tendency towards the development of smaller and more cost-effective SAR systems has emerged. However, to date, there has been no evaluation of the SSWF retrieval performance of miniaturized SAR systems. This study utilized 1053 HiSea-1 and Chaohu-1 miniaturized SAR images covering the Southeast China Sea to retrieve SSWFs. After a quality control procedure, the retrieved winds were subsequently compared with ERA5, buoy, and ASCAT data. The retrieved wind speeds demonstrated root mean square errors (RMSEs) of 2.42 m/s, 1.64 m/s, and 3.29 m/s, respectively, while the mean bias errors (MBEs) were found to be −0.44 m/s, 1.08 m/s, and −1.65 m/s, respectively. Furthermore, the retrieved wind directions exhibited RMSEs of 11.5°, 36.8°, and 41.7°, with corresponding MBEs of −1.3°, 2.4°, and −8.8°, respectively. The results indicate that HiSea-1 and Chaohu-1 SAR satellites have the potential and practicality for SSWF retrieval, validating the technical indicators and performance requirements implemented during the satellites’ design phase.
A Low-Cost Radar-Based IoT Sensor for Noncontact Measurements of Water Surface Velocity and Depth
Authors: Catsamas Stephen , Shi Baiqian , Wang Miao , Xiao Jieren , Kolotelo Peter , McCarthy David
Published: July 2023

We designed an out-of-water radar water velocity and depth sensor, which is unique due to its low cost and low power consumption. The sensor is a first at a cost of less than USD 50, which is well suited to previously cost-prohibited high-resolution monitoring schemes. This use case is further supported by its out-of-water operation, which provides low-effort installations and longer maintenance-free intervals when compared with in-water sensors. The inclusion of both velocity and depth measurement capabilities allows the sensor to also be used as an all-in-one solution for flowrate measurement. We discuss the design of the sensor, which has been made freely available under open-hardware and open-source licenses. The design uses commonly available electronic components, and a 3D-printed casing makes the design easy to replicate and modify. Not before seen on a hydrology sensor, we include a 3D-printed radar lens in the casing, which boosts radar sensitivity by 21 dB. The velocity and depth-sensing performance were characterised in laboratory and in-field tests. The depth is accurate to within ±6% and ±7 mm and the uncertainty in the velocity measurements ranges from less than 30% to 36% in both laboratory and field conditions. Our sensor is demonstrated to be a feasible low-cost design which nears the uncertainty of current, yet more expensive, velocity sensors, especially when field performance is considered.
Sensor Placement in an Irregular 3D Surface for Improving Localization Accuracy Using a Multi-Objective Memetic Algorithm
Authors: Graça Paula A. , Alves José C. , Ferreira Bruno M.
Published: July 2023

Accurate localization is a critical task in underwater navigation. Typical localization methods use a set of acoustic sensors and beacons to estimate relative position, whose geometric configuration has a significant impact on the localization accuracy. Although there is much effort in the literature to define optimal 2D or 3D sensor placement, the optimal sensor placement in irregular and constrained 3D surfaces, such as autonomous underwater vehicles (AUVs) or other structures, is not exploited for improving localization. Additionally, most applications using AUVs employ commercial acoustic modems or compact arrays, therefore the optimization of the placement of spatially independent sensors is not a considered issue. This article tackles acoustic sensor placement optimization in irregular and constrained 3D surfaces, for inverted ultra-short baseline (USBL) approaches, to improve localization accuracy. The implemented multi-objective memetic algorithm combines an evaluation of the geometric sensor’s configuration, using the Cramer-Rao Lower Bound (CRLB), with the incidence angle of the received signal. A case study is presented over a simulated homing and docking scenario to demonstrate the proposed optimization algorithm.
Learning-Based IRS-Assisted Secure Transmission for Mine IoTs
Authors: Min Minghui , Xiao Jiayang , Zhang Peng , Song Jinling , Li Shiyin
Published: July 2023

Mine Internet of Things (MIoT) devices in intelligent mines often face substantial signal attenuation due to challenging operating conditions. The openness of wireless communication also makes it susceptible to smart attackers, such as active eavesdroppers. The attackers can disrupt equipment operations, compromise production safety, and exfiltrate sensitive environmental data. To address these challenges, we propose an intelligent reflecting surface (IRS)-assisted secure transmission system for an MIoT device which enhances the security and reliability of wireless communication in challenging mining environments. We develop a joint optimization problem for the IRS phase shifts and transmit power, with the goal of enhancing legitimate transmission while suppressing eavesdropping. To accommodate time-varying channel conditions, we propose a reinforcement learning (RL)-based IRS-assisted secure transmission scheme that enables MIoT device to optimize both the IRS reflecting coefficients and transmit power for optimal transmission policy in dynamic environments. We adopt the deep deterministic policy gradient (DDPG) algorithm to explore the optimal transmission policy in continuous space. This can reduce the discretization error caused by traditional RL methods. The simulation results indicate that our proposed scheme achieves superior system utility compared with both the IRS-free (IF) scheme and the IRS randomly configured (IRC) scheme. These results demonstrate the effectiveness and practical relevance of our contributions, proving that implementing IRS in MIoT wireless communication can enhance safety, security, and efficiency in the mining industry.
Basic Research on Selective Extraction of Iron from Titanium Dioxide Waste Acid to Prepare Iron Phosphate Precursors
Authors: Cao Xuejiao , Chen Yang , Liang Xinxing , Li Yibing , Zhang Weiguang , Cai Zhenlei , Zhang Ting’an
Published: July 2023

In view of the current situation wherein acid resources and valuable components in titanium dioxide waste acid cannot be effectively extracted and are prone to secondary pollution, our research team proposed a new technique consisting of step extraction and the comprehensive utilization of titanium dioxide waste acid. In this paper, the thermodynamics of selective precipitation and the preparation of doped iron phosphate from waste acid were studied. The thermodynamics results show that the content of Al3+, Mn2+, Mg2+, and Ca2+ in the reaction system can be tuned by adjusting the pH during the pre-precipitation process. In the first step, these impurity ions should be settled as much as possible; then, Fe2+ should be oxidized to Fe3+ so as to obtain iron phosphate with higher purity in the next step of the precipitation process. The effects of the reaction temperature, seed crystals, pH value, and P/M on the precipitation process were investigated in detail. The experimental results show that in the reduced state, the optimal precipitation conditions are a temperature of 75 °C, an initial pH value of 4.5, and an optimal P/M molar ratio of 1.1. In the oxidized state, the optimal precipitation conditions are a temperature of 60 °C, a solution pH = 2.5, and a reaction time of 25 min. After calcination, the precipitate mainly consists of iron phosphate, which basically meets the requirements of an iron phosphate precursor.
The Impact of Digital Economy Development on Industrial Restructuring: Evidence from China
Authors: Li Qingjun , Zhao Shuliang
Published: July 2023

This paper aims to analyze how the digital economy affects industrial restructuring and examine the mediating role of the relevant factors. Based on the analysis of the effect mechanism of the digital economy development on industrial restructuring, this paper constructs an improved measuring index system of digital economy covering digital infrastructure, digital industrialization, and industrial digitalization, and measures regional digital economic growth based on provincial panel data in China from 2013 to 2020 by using the entropy TOPSIS method, empirical analyses on the impact of the digital economy on industrial restructuring, and verifies the mediating effect of human capital, technological innovation, and financial development in this process. Research findings are as follows: (i) Digital economic growth demonstrates a considerable positive effect of the speed, efficiency of industrial restructuring, and industrial structure rationalization. (ii) Digital economy indirectly boosts industrial restructuring by affecting human capital, technological innovation, and financial development. The findings in this study are of theoretical significance to interpret the effect of digital economic growth on industrial restructuring, facilitating relevant economies in the decision-making of industrial restructuring and upgrading.
In Search of the Niche—Targeting Lamb Meat Consumers in North-East Germany to Communicate the Ecosystem Services of Extensive Sheep Farming Systems
Authors: Wiedemann Anne , Lauterbach Josephine , Häring Anna Maria
Published: July 2023

Extensive sheep farming systems provide numerous ecosystem services, most of which consumers are not aware of. Consumers’ subjective quality perception relates to intrinsic and extrinsic quality attributes. Extrinsic quality attributes, like animal welfare, conservation of biodiversity, and regional and sustainable lamb meat production, meet the expectations of meat consumers. Communication of quality attributes can support consumers’ willingness to buy and pay a premium price, as well as producers’ economic viability. Previous studies focused on consumers’ perception of intrinsic quality attributes, while it is our objective to analyse the target group-specific communication of extrinsic quality attributes of extensive sheep farming. An online survey with 387 valid respondents included lamb meat consumers in Berlin-Brandenburg and revealed their consumption patterns. The sample is representative of Berlin-Brandenburg in net household income, population division and gender, while academics and respondents over 50 years were overrepresented. The survey addressed demographics, meat consumption and purchasing behaviour, preferences for different lamb meat products, purchasing motives and barriers, perception of communication messages and personal initiative for the purchase of regional lamb. Via Principal Component Analysis (PCA) and Cluster Analysis, we identified two key target groups for regionally produced lamb meat: “Foodies” and “Cooking enthusiasts”. Guided by Alphabet theory with its specific focus on Knowledge, Information seeking behaviour and purchasing Habit, we derive recommendations for target-group-specific communication of regionally produced lamb meat. “Foodies” showed a high potential for direct marketing and personal storytelling of sheep farmers. “Cooking enthusiasts” are best addressed through print and online marketing with a focus on cooking and personal health.
No Cow? Understanding US Consumer Preferences for Plant-Based over Regular Milk-Based Products
Authors: Rombach Meike , Lucock Xiaomeng , Dean David L.
Published: July 2023

Dairy products such as cheese, butter, and yoghurt are popular staples in American households; however, alternative plant-based products are gaining increasing popularity. An online survey was conducted to investigate the factors that determine US consumers’ preferences for plant-based and regular milk-based products before and since the occurrence of food price inflation. The study used descriptive statistics and partial least square structural equation modelling for the analysis. The accessibility of plant-based substitutes, the perceived impact of food price inflation and associated consumer behaviour, engagement with food-related activities, and environmental concerns were important factors in both scenarios. Recommendations to marketers on how to target different consumer groups are offered.
Just Energy Transition of South Africa in a Post-COVID Era
Authors: Bohlmann Heinrich R. , Bohlmann Jessika A. , Chitiga-Mabugu Margaret , Inglesi-Lotz Roula
Published: July 2023

The impacts of the COVID-19 pandemic have sparked global debate over how green economic recovery may and should be, and if the pandemic has accelerated the present energy transition while assuring a just transition for vulnerable populations such as unskilled workers and women. This study investigates the socioeconomic impact of South Africa’s planned green energy transition, with a focus on the Mpumalanga province—the country’s largest coal mining region with many coal-fired power plants. Using a regional-dynamic computable general equilibrium (CGE) model, the study analyses the economy-wide effects of different policy scenarios related to a changing electricity generation mix, investment financing costs, and international action against non-compliant industries, amongst others, with a specific focus on the vulnerable industries and population groups in Mpumalanga. Key results from the study highlights that (1) the structure of the Mpumalanga economy will be affected in the medium to long run regardless of the domestic transition path, (2) the Mpumalanga economy is indeed in danger of shrinking relative to the baseline, unless the Just Energy Transition (JET) is quickly and carefully managed, and (3) at a national level, at least, there is the strong possibility of a double dividend when greening the South African economy with overall economic growth and environmental outcomes expected to improve in the long run.
A Score Index System for a Semi-Quantitative Assessment of Inhalation Risks at Contaminated Sites
Authors: Mangiapia Maria Dalma , Verginelli Iason , Baciocchi Renato , Bogliolo Maria Paola , Berardi Simona
Published: July 2023

Risk assessment of contaminated sites is typically applied following a tiered approach with increasing levels of complexity. In the standard risk-based corrective action (RBCA) procedure issued by the American Society for Testing and Materials (ASTM), the site-specific evaluation is carried out using fate and transport models that require a relatively large amount of input data. In this work, we introduce a site-specific score index system for a preliminary assessment of the inhalation risks related to contaminants in soil or groundwater that resembles the modeling approaches typically adopted for chemical risk assessment in the field of industrial hygiene. In the developed system, a risk index for the outdoor and indoor volatilization pathways is calculated as the ratio between the calculated concentration at the point of exposure for the contaminant of concern and the corresponding acceptable concentration in air. The concentration at the point of exposure for each contaminant of concern is estimated through simple algorithms that involve a limited number of indexes that depend on the parameters that affect the exposure scenario. This qualitative assessment is then converted into a semi-quantitative approach by introducing scaling factors that were calibrated using the ASTM RBCA fate and transport models. The procedure was validated against the standard RBCA procedure by performing a simple Monte Carlo analysis with 10,000 simulations with randomly varying site-specific parameters. The developed score index system resulted in a conservative estimate of the risks, with percentages of false negatives lower than 1% and false positives lower than 15%. This means that the developed system allows one to screen out sites from further evaluations in more than 80% of cases, while ensuring a conservative estimate of the expected risks. The application to a real case study of a contaminated site confirmed the suitability of the developed approach.
A Random Parameters Multinomial Logit Model Analysis of Median Barrier Crash Injury Severity on Wyoming Interstates
Authors: Moomen Milhan , Molan Amirarsalan Mehrara , Ksaibati Khaled
Published: July 2023

This paper investigated factors influencing injury severity of crashes involving median traffic barriers, including the impact of barrier characteristics and their geometric features in Wyoming. Combining field data of inventoried median barriers with crash data on Wyoming interstates highways, a random parameters multinomial logit (mixed logit) model of injury severity was estimated. This methodological approach allowed for the possibility of estimated model parameters to vary randomly across crash observations to account for heterogeneity with respect to driver characteristics, roadway attributes, and vehicle characteristics. The estimation results indicated concrete barriers installed on front side-slopes and box beam barriers were associated with severe injury crashes. It was also found that median barrier crashes involving sports utility vehicles, pickups, and improperly restraint vehicle occupants are complex and vary significantly across observations. Other statistically significant variables found to increase the likelihood of severe injury crashes were rural interstate roads, concrete barriers installed on a front side-slope, box beam barriers with lateral offset less than 2 feet, and rollover crashes. These parameters were fixed across observations. The findings of this research point to the need to further investigate the impacts of sport utility vehicles, pickups, and rollover crashes on median barrier crash injury severity.
Comprehensive Performance of Green Infrastructure through a Life-Cycle Perspective: A Review
Authors: Wang Mo , Zhong Xu , Sun Chuanhao , Chen Tong , Su Jin , Li Jianjun
Published: July 2023

Climate change represents a paramount challenge for humanity in the 21st century. Green infrastructure (GI), due to its myriad environmental and societal benefits, has emerged as an essential natural life support system and a pivotal strategy to combat climate change-induced risks. Consequently, GI has garnered considerable global interest. As of now, comprehensive and systematic environmental impact assessments of GI are underway worldwide. Nonetheless, there remains a conspicuous scarcity of life-cycle approaches to delineate the evolutionary trajectory of this domain. Employing three bibliometric software tools—the R language “Bibliometrix” package (version 4.0.1), CiteSpace (version 6.2.R2 Basic), and “VOSviewer” (version 1.6.18)—this study scrutinizes the progression of the GI paradigm until 2022. An exhaustive review of 1124 documents published on the Web of Science between 1995 and 2022 facilitates an overarching evaluation of GI, encompassing environmental, economic, and social facets from a life-cycle standpoint. The analysis results reveal that (1) the majority of current studies accentuate the economic and environmental efficacy of GI throughout its life cycle, with the social performance receiving comparatively less focus, potentially due to the difficulties in formulating a social life-cycle-assessment database; (2) contemporary research predominantly concentrates on the life-cycle carbon footprint of GI, warranting further exploration into its water and carbon footprints; and (3) multi-objective optimization emerges as a promising avenue for future GI investigations. This review thus furnishes a comprehensive understanding of the performance of GI from a life-cycle perspective.
Dynamic Reconfiguration to Optimize Energy Production on Moving Photovoltaic Panels
Authors: Merino Salvador , Martinez Javier , Guzman Francisco , Lara Juan de Dios , Guzman Rafael , Sanchez Francisco , Heredia Juan Ramon , Sidrach de Cardona Mariano
Published: July 2023

Urban transport systems play a major role in the development of today’s societies, but they require technological changes to reduce their environmental impact. The problem lies in their level of autonomy, which is why electrical energy production systems are proposed for self-consumption, efficiently feeding their accumulators. As the energy provided by photovoltaic installations has lower recharge speeds, conventional systems with high transfer amperage and higher voltage are required. For this reason, solar installations are used for additional services and to support their autonomy. The present work tries to find the best solution for both constant voltage and peak current systems. Once found, these solutions will be applied in real time for the dynamic recharging of battery packs, trying to achieve vehicles that are progressively more energetically autonomous. To solve these situations, a new computational method for calculating voltage and amperage has been developed in this work, based on Dijkstra’s minimum path search algorithm on graph theory, adapted to electrical circuits. Once this algorithm has been established, the panel performance analysis sensors, developed at the University of Malaga, are combined with different electronic solutions described in this article (Wi-Fi relay devices using esp8266 chips or feeding these relays through panels and establishing the voltage drop to switch the connection), achieving precise and sufficiently fast solutions at very low cost. Both series and parallel transitions are possible, depending on the type of energy generation required. The theoretical solutions using Minkowski paths, analyzed in the past, have been simulated and subsequently constructed in this paper, indicating the diagrams necessary for their realization.
Analysis of the Quality and Quantity of Antiepileptic Drugs Required in Communities during Large-Scale Disasters: Focused on a Small Local City in Japan
Authors: Morisaki Yuma , Fujiu Makoto , Takayama Junichi
Published: July 2023

The Tohoku earthquake off the Pacific coast in March 2011 led to massive medical requirements. Although the availability of drugs is essential in the disaster-affected area, a shortage of drugs and a lack of supply of drugs were reported. Moreover, in Japan, there are concerns regarding the occurrence of a large-scale earthquake, such as the Nankai Trough megathrust earthquake, in the near future. Therefore, drug requirements in a disaster-affected area need to be determined in advance. This study uses national health insurance data (KDB), which are medical big data, to determine the drug requirements in the region from insurance claim information. This study focuses on epilepsy as the target disease and determines the quantity and quality of antiepileptic drugs required in the region via analysis.
Building Sustainable Creative Economy in Society through the Mediation Role of Innovation Behavior
Authors: Widodo Widodo , Triyono Mochamad Bruri , Sudira Putu , Mutohhari Farid
Published: July 2023

This study measures the level of influence of digital competence (DC), green behavior (GB), psychological well-being (PWB), and innovation behavior (IB) in building a sustainable creative economy (SCE). In more depth, the role of IB mediation is tested against the influence of DC, GB, and PWB in building SCE. This study adopts an ex post facto design that involves 294 participating creative industry communities. A Likert scale questionnaire instrument with validated items was used to collect data. Structural Equation Modeling (SEM) analysis was used to test the hypothesis of direct influence between variables and the mediating role through path analysis and the bootstrap method. The results of the direct effect test stated that DC, GB, PWB, and IB played significant roles in building SCE. The mediating role of IB was shown to be significant in the influence of DC, GB, and PWB on SCE development. This result provides a signal for the government and society to strive for the growth of DC and GB, which PWB offsets, to boost SCE. The most important thing is to grow IB through these three aspects to build SCE. These results provide specific conveniences for the community to participate in building SCE through the encouragement of the studied aspects.
Research on Multi-Channel Supply Chain Decisions Considering Carbon Emission Cost and Consumer Loyalty
Authors: Chen Haodong , Zhang Hengyi , Humdan Eias Al , Alharithi Mohammed , Gong Yu
Published: July 2023

Considering carbon emission cost and consumer loyalty, this paper establishes a three-level multi-channel supply chain composed of the leading manufacturer, the retailer, and the consumer and builds a multi-channel supply chain with centralized decision-making and decentralized decision-making modes, and the optimal decision-making under both decision-making modes is solved. The study found that the carbon emission reduction level of multi-channel centralized decision-making is better than that of decentralized decision-making under the same carbon emission cost, and centralized decision-making can improve the carbon emission reduction level. Manufacturers open a direct channel to help reduce carbon emissions and need to consider the cost of emission reduction in their channel decisions. Consumer loyalty also directly impacts channel decisions. Only when carbon emission costs and consumer loyalty are within a reasonable range can new direct sales channels be opened to bring in new profits. Simultaneously, the total profit of the supply chain is greater than that of decentralized decision-making, but the double marginal utility of both parties decreases with the increase in carbon emission costs.
Investigation of the Microenvironment, Land Cover Characteristics, and Social Vulnerability of Heat-Vulnerable Bus Stops in Knoxville, Tennessee
Authors: Lee Sangwon , First Jennifer M.
Published: July 2023

The urban heat island is a climate, public health, and environmental justice issue. Sustainable urban infrastructure needs improvements in public transport to protect citizens’ health from the urban heat island. This case study investigates the local microenvironment and social vulnerability of heat-vulnerable bus stops in Knoxville, Tennessee, using publicly available data from a variety of sources. These included ground and satellite measurements of heat and humidity from the Knoxville Heat Mapping Campaign, characteristics of land surface from the National Land Cover Dataset 2019 of the United States Geological Survey, and the 2018 Social Vulnerability Index from the U.S. Centers for Disease Control and Prevention. A geographic information system and a principal component analysis were used to identify social vulnerability in areas where the bus stops are located. The results show that most heat-vulnerable bus stops are poor microenvironments without trees and shelters. The hottest bus stops are concentrated in the highly developed and densely populated areas of West Knoxville and downtown Knoxville and in South, North, Northeast, and Northwest Knoxville, which are relatively high vulnerability clustered and have poor public infrastructure. The findings provide the foundation for mitigation strategies to better prepare local communities for climate change by identifying public transportation areas negatively impacted by the urban heat island.
Customer Experience in Open Banking and How It Affects Loyalty Intention: A Study from Saudi Arabia
Authors: Mutambik Ibrahim
Published: July 2023

The concept of open banking has emerged only recently within the fintech sector, and it is rapidly becoming popular in many regions across the world. Currently, there are very few studies on the relationship between customer experience and intention to use fintech apps, none of which focus on open banking. This relationship is significant for a number of reasons, one of which is the emerging importance of the connection between fintech and an environmentally sustainable economy. This paper seeks to add to our understanding of the factors that shape the customer experience and that determine loyalty levels toward open banking brands and apps. We propose a model in which a number (six) of affective and cognitive factors influence customer experience, which ultimately determines loyalty intention. The model is tested using data collected via a quantitative (survey) methodology involving open banking users in Saudi Arabia. The results show that customer experience is affected by all of the proposed factors (ease of use, perceived value, quality of support, reliability, perceived risk and ability to innovate). These factors, in turn, actively influence the level of customer loyalty. The study contributes to the current literature by identifying the various cognitive and affective determinants of customer experience, which therefore influences loyalty intention in open banking, and provides valuable insights into how both new and established brands should integrate customer experience into promotional and development strategies.
General Fundraising Trends among University Patrons and Entrepreneurs to Promote the Sustainability of Universities
Authors: Kundzina Laila , Rivza Baiba , Grinevica Liva , Rivza Peteris
Published: July 2023

One of the most important issues for higher education institutions is achieving financial viability and sustainability by expanding revenue sources, as the costs associated with ensuring the operation of higher education institutions is increasing. Therefore, raising funds through donations for universities means new challenges. Within the framework of this study, the authors have drawn attention to attracting funds to universities from patrons of universities and companies, providing a detailed analysis of trends in this field. The purpose of this study was to analyze the general trends in fundraising among university patrons and businessmen, and to identify possible solutions that could help in attracting donations to universities and promote their sustainability in the future. The research methodology applied in this research included analysis of the literature, conducting surveys, and analysis using statistical methods such as the correlation method, chi-squared test, and ANOVA. This study provides an insight into the situation in Latvia regarding the trends of patrons and entrepreneurs donating to universities. The results of this study show that philanthropic organizations should work on building a feedback relationship with patrons to promote as much fundraising as possible.