bluuebunny/crossref_metadata_2025 huggingface dataset:
UAV Multisensory Data Fusion and Multi-Task Deep Learning for High-Throughput Maize Phenotyping
Authors: Nguyen Canh , Sagan Vasit , Bhadra Sourav , Moose Stephen
Published: February 2023

Recent advances in unmanned aerial vehicles (UAV), mini and mobile sensors, and GeoAI (a blend of geospatial and artificial intelligence (AI) research) are the main highlights among agricultural innovations to improve crop productivity and thus secure vulnerable food systems. This study investigated the versatility of UAV-borne multisensory data fusion within a framework of multi-task deep learning for high-throughput phenotyping in maize. UAVs equipped with a set of miniaturized sensors including hyperspectral, thermal, and LiDAR were collected in an experimental corn field in Urbana, IL, USA during the growing season. A full suite of eight phenotypes was in situ measured at the end of the season for ground truth data, specifically, dry stalk biomass, cob biomass, dry grain yield, harvest index, grain nitrogen utilization efficiency (Grain NutE), grain nitrogen content, total plant nitrogen content, and grain density. After being funneled through a series of radiometric calibrations and geo-corrections, the aerial data were analytically processed in three primary approaches. First, an extended version normalized difference spectral index (NDSI) served as a simple arithmetic combination of different data modalities to explore the correlation degree with maize phenotypes. The extended NDSI analysis revealed the NIR spectra (750–1000 nm) alone in a strong relation with all of eight maize traits. Second, a fusion of vegetation indices, structural indices, and thermal index selectively handcrafted from each data modality was fed to classical machine learning regressors, Support Vector Machine (SVM) and Random Forest (RF). The prediction performance varied from phenotype to phenotype, ranging from R2 = 0.34 for grain density up to R2 = 0.85 for both grain nitrogen content and total plant nitrogen content. Further, a fusion of hyperspectral and LiDAR data completely exceeded limitations of single data modality, especially addressing the vegetation saturation effect occurring in optical remote sensing. Third, a multi-task deep convolutional neural network (CNN) was customized to take a raw imagery data fusion of hyperspectral, thermal, and LiDAR for multi-predictions of maize traits at a time. The multi-task deep learning performed predictions comparably, if not better in some traits, with the mono-task deep learning and machine learning regressors. Data augmentation used for the deep learning models boosted the prediction accuracy, which helps to alleviate the intrinsic limitation of a small sample size and unbalanced sample classes in remote sensing research. Theoretical and practical implications to plant breeders and crop growers were also made explicit during discussions in the studies.
Enhanced Root-MUSIC Algorithm Based on Matrix Reconstruction for Frequency Estimation
Authors: Zhu Yingjie , Zhang Wuxiong , Yi Huiyue , Xu Hui
Published: February 2023

In recent years, frequency-modulated continuous wave (FMCW) radar has been widely used in automatic driving, settlement monitoring and other fields. The range accuracy is determined by the estimation of the signal beat frequency. The existing algorithms are unable to distinguish between signal components with similar frequencies. To address this problem, this study proposed an enhanced root-MUSIC algorithm based on matrix reconstruction. Firstly, based on the sparsity of a singular value vector, a convex optimization problem was formulated to identify a singular value vector. Two algorithms were proposed to solve the convex optimization problem according to whether the standard deviation of noise needed to be estimated, from which an optimized singular value vector was obtained. Then, a signal matrix was reconstructed using an optimized singular value vector, and the Hankel structure of the signal matrix was restored by utilizing the properties of the Hankel matrix. Finally, the conventional root-MUSIC algorithm was utilized to estimate the signal beat frequency. The simulation results showed that the proposed algorithm improved the frequency resolution of multi-frequency signals in a noisy environment, which is beneficial to improve the multi-target range accuracy and resolution capabilities of FMCW radar.
Solution-Processed Functionalized Graphene Film Prepared by Vacuum Filtration for Flexible NO2 Sensors
Authors: Dieng Mbaye , Sankar Siva , Ni Pingping , Florea Ileana , Alpuim Pedro , Capasso Andrea , Yassar Abderrahim , Bouanis Fatima Zahra
Published: February 2023

Large-scale production of graphene nanosheets (GNSs) has led to the availability of solution-processable GNSs on the commercial scale. The controlled vacuum filtration method is a scalable process for the preparation of wafer-scale films of GNSs, which can be used for gas sensing applications. Here, we demonstrate the use of this deposition method to produce functional gas sensors, using a chemiresistor structure from GNS solution-based techniques. The GNS suspension was prepared by liquid-phase exfoliation (LPE) and transferred to a polyvinylidene fluoride (PVDF) membrane. The effect of non-covalent functionalization with Co-porphyrin and Fe-phthalocyanines on the sensor properties was studied. The pristine and functionalized GNS films were characterized using different techniques such as Raman spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM), X-ray diffraction (XRD), and electrical characterizations. The morphological and spectroscopic analyses both confirm that the molecules (Co-porphyrin and Fe-phthalocyanine) were successfully adsorbed onto the GNSs surface through π-π interactions. The chemiresistive sensor response of functionalized GNSs toward the low concentrations of nitrogen dioxide (NO2) (0.5–2 ppm) was studied and compared with those of the film of pristine GNSs. The tests on the sensing performance clearly showed sensitivity to a low concentration of NO2 (5 ppm). Furthermore, the chemical modification of GNSs significantly improves NO2 sensing performance compared to the pristine GNSs. The sensor response can be modulated by the type of adsorbed molecules. Indeed, Co-Por exhibited negative responsiveness (the response of Co-Por-GNS sensors and pristine GNS devices was 13.1% and 15.6%, respectively, after exposure to 0.5 ppm of NO2). Meanwhile, Fe-Phc-GNSs induced the opposite behavior resulting in an increase in the sensor response (the sensitivity was 8.3% and 7.8% of Fe-Phc-GNSs and pristine GNSs, respectively, at 0.5 ppm NO2 gas).
Magnetoelastic Monitoring System for Tracking Growth of Human Mesenchymal Stromal Cells
Authors: Skinner William S. , Zhang Sunny , Garcia Jasmine R. , Guldberg Robert E. , Ong Keat Ghee
Published: February 2023

Magnetoelastic sensors, which undergo mechanical resonance when interrogated with magnetic fields, can be functionalized to measure various physical quantities and chemical/biological analytes by tracking their resonance behaviors. The unique wireless and functionalizable nature of these sensors makes them good candidates for biological sensing applications, from the detection of specific bacteria to tracking force loading inside the human body. In this study, we evaluate the viability of magnetoelastic sensors based on a commercially available magnetoelastic material (Metglas 2826 MB) for wirelessly monitoring the attachment and growth of human mesenchymal stromal cells (hMSCs) in 2D in vitro cell culture. The results indicate that the changes in sensor resonance are linearly correlated with cell quantity. Experiments using a custom-built monitoring system also demonstrated the ability of this technology to collect temporal profiles of cell growth, which could elucidate key stages of cell proliferation based on acute features in the profile. Additionally, there was no observed change in the morphology of cells after they were subjected to magnetic and mechanical stimuli from the monitoring system, indicating that this method for tracking cell growth may have minimal impact on cell quality and potency.
Multi-Annual Evaluation of Time Series of Sentinel-1 Interferometric Coherence as a Tool for Crop Monitoring
Authors: Villarroya-Carpio Arturo , Lopez-Sanchez Juan M.
Published: February 2023

Interferometric coherence from SAR data is a tool used in a variety of Earth observation applications. In the context of crop monitoring, vegetation indices are commonly used to describe crop dynamics. The most frequently used vegetation indices based on radar data are constructed using the backscattered intensity at different polarimetric channels. As coherence is sensitive to the changes in the scene caused by vegetation and its evolution, it may potentially be used as an alternative tool in this context. The objective of this work is to evaluate the potential of using Sentinel-1 interferometric coherence for this purpose. The study area is an agricultural region in Sevilla, Spain, mainly covered by 18 different crops. Time series of different backscatter-based radar vegetation indices and the coherence amplitude for both VV and VH channels from Sentinel-1 were compared to the NDVI derived from Sentinel-2 imagery for a 5-year period, from 2017 to 2021. The correlations between the series were studied both during and outside the growing season of the crops. Additionally, the use of the ratio of the two coherences measured at both polarimetric channels was explored. The results show that the coherence is generally well correlated with the NDVI across all seasons. The ratio between coherences at each channel is a potential alternative to the separate channels when the analysis is not restricted to the growing season of the crop, as its year-long temporal evolution more closely resembles that of the NDVI. Coherence and backscatter can be used as complementary sources of information, as backscatter-based indices describe the evolution of certain crops better than coherence.
Multimodal Sensor-Input Architecture with Deep Learning for Audio-Visual Speech Recognition in Wild
Authors: He Yibo , Seng Kah Phooi , Ang Li Minn
Published: February 2023

This paper investigates multimodal sensor architectures with deep learning for audio-visual speech recognition, focusing on in-the-wild scenarios. The term “in the wild” is used to describe AVSR for unconstrained natural-language audio streams and video-stream modalities. Audio-visual speech recognition (AVSR) is a speech-recognition task that leverages both an audio input of a human voice and an aligned visual input of lip motions. However, since in-the-wild scenarios can include more noise, AVSR’s performance is affected. Here, we propose new improvements for AVSR models by incorporating data-augmentation techniques to generate more data samples for building the classification models. For the data-augmentation techniques, we utilized a combination of conventional approaches (e.g., flips and rotations), as well as newer approaches, such as generative adversarial networks (GANs). To validate the approaches, we used augmented data from well-known datasets (LRS2—Lip Reading Sentences 2 and LRS3) in the training process and testing was performed using the original data. The study and experimental results indicated that the proposed AVSR model and framework, combined with the augmentation approach, enhanced the performance of the AVSR framework in the wild for noisy datasets. Furthermore, in this study, we discuss the domains of automatic speech recognition (ASR) architectures and audio-visual speech recognition (AVSR) architectures and give a concise summary of the AVSR models that have been proposed.
Explaining Personal and Public Pro-Environmental Behaviors
Authors: Yang Philip Q. , Wilson Michaela LaNay
Published: February 2023

A global crisis generated by human-made climate change has added urgency to the need to fully understand human pro-environmental behaviors (PEBs) that may help slow down the crisis. Factors influencing personal and public PEBs may or may not be the same. Only a few studies have empirically investigated the determinants of personal and public PEBs simultaneously, but they contain major limitations with mixed results. This study develops a conceptual model for explaining both personal and public PEBs that incorporate demographic, socioeconomic, political, and attitudinal variables, and their direct and indirect effects. Using the latest available data from the 2010 General Social Survey and structural equation modeling (SEM), we tested the determinants of both personal and public PEBs in the United States. The results reveal that environmental concerns, education, and political orientation demonstrate similar significant impacts on both personal and public PEBs, but income, gender, race, urban/rural residency, region, and party affiliation have differential effects on these behaviors. Age, cohort, and religion have no significant effect on both types of behaviors. Our results confirm some existing findings; however, they challenge the findings of much of the literature.
Litter Decomposition Is Not Affected by Perfluorobutane Sulfonate (PFBS) in Experimental Soil Microcosms
Authors: Xie Qiaoling , Xu Baile , Rillig Matthias C.
Published: February 2023

Perfluorobutane sulfonate (PFBS) has been found in increasing concentrations in the environment. However, its effect on litter decomposition in soils is still unclear. Therefore, the effect of PFBS on the decomposition of various litter types was tested, as well as on selected aspects of soil quality. Soil samples were treated with different concentrations of PFBS (0, 1, and 10 µg g–1) and five organic litter materials were used with various C:N ratios. A soil microcosm experiment was performed at 20 °C for 6 weeks. Litter decomposition, soil respiration, enzyme activities, soil pH, water-stable aggregates (WSA), and soil total C and N contents were measured. PFBS treatments were observed to have negligible effects on litter decomposition as well as on other soil properties. This means that in the concentration range examined, this substance has no observable effects on the key soil parameters examined. The present result was inconsistent with the findings of a previous study with similar experimental microcosms but different soils. This study suggests that the effects of PFBS may be less pronounced in the tested soil, but it cannot be concluded that PFBS is harmless in soil ecosystems. A wider range of soil types and PFBS levels should be tested in future studies.
Exploring the Well-Being of Slovenian and Serbian Sport Science Students during the COVID-19 Pandemic of Summer 2022
Authors: Banjac Brigita , Milovanović Ivana M. , Pišot Saša , Matić Radenko M. , Popović Stevo , Radenović Sandra S. , Drid Patrik
Published: February 2023

The COVID-19 pandemic profoundly changed everyday life of social actors, which inferred mental health and well-being concerns. As students of health-related studies tend to adapt better to difficult circumstances, in this study, we explored the effect of the pandemic on sports science students’ well-being during the summer of 2022. The research was conducted in Slovenia and Serbia. The sample comprised n = 350 students. The PERMA-Profiler, a 15-item self-reported questionnaire, was adapted to assess well-being across five elements: positive emotions, engagement, relationships, meaning, and accomplishment. Data were collected with a questionnaire through the summer of 2022 (from May to July) and analyzed in SPSS, AMOS 26.0. The results revealed normal functioning (M = 7.72, SD ± 1.38) for the overall well-being of the students. Although all dimensions indicated high scores, relationships (M = 7.95, SD ± 1.63), meaning (M = 7.76, SD ± 1.69), and engagement (M = 7.73, SD ± 1.36) rated the highest. Furthermore, the instrument was acceptable, as the confirmatory factor analysis showed adequate reliability based on Cronbach’s alpha (15 items, α = 0.94) and strong internal correlations between the PERMA dimensions. This study contributes to the previously published research, emphasizing the positive responses and successful coping of sports science students in times of complex situations, such as the COVID-19 pandemic.
Souvenirs Development Related to Cultural Heritage: A Thematic Review
Authors: Zhu Qiuxia , Rahman Rizal , Alli Hassan , Effendi Raja Ahmad Azmeer Raja Ahmad
Published: February 2023

Previous souvenir research has generally supported the use of heritage arts and crafts as a design inspiration, which both arouses visitors’ interest in the destination and enhances the local cultural identity. The increasing concern about souvenirs and cultural heritage has led to a proliferation of studies on this topic. However, few review articles discuss their inevitable connection and the process of transforming cultural heritage resources into souvenirs. Therefore, this review aims to analyze the literature on souvenirs related to cultural heritage from 2018 to July 2022. A criterion for inclusion and exclusion is presented to search and screen articles from three leading databases (i.e., WOS, Mendeley, and Scopus). Ultimately, 27 articles meeting the eligibility criteria were selected for synthesis analysis. ATLAS.ti 9, as the analysis software, yielded quantitative results showing trends in research on cultural heritage-related souvenirs. At the same time, from the qualitative analysis emerged four main themes about the topic: (1) significance of souvenirs, (2) customer’s purchase intention, (3) transformation, and (4) sustainability. Finally, the findings are expected to be beneficial in addressing the relationship between souvenirs and cultural heritage and provide insights for future research and practice of cultural product sustainability.
NA-DGRU: A Dual-GRU Traffic Speed Prediction Model Based on Neighborhood Aggregation and Attention Mechanism
Authors: Tian Xiaoping , Zou Changkuan , Zhang Yuqing , Du Lei , Wu Song
Published: February 2023

Traffic prediction is an important part of the Intelligent Transportation System (ITS) and has broad application prospects. However, traffic data are affected not only by time, but also by the traffic status of other nearby roads. They have complex temporal and spatial correlations. Developing a means for extracting specific features from them and effectively predicting traffic status such as road speed remains a huge challenge. Therefore, in order to reduce the speed prediction error and improve the prediction accuracy, this paper proposes a dual-GRU traffic speed prediction model based on neighborhood aggregation and the attention mechanism: NA-DGRU (Neighborhood aggregation and Attention mechanism–Dual GRU). NA-DGRU uses the neighborhood aggregation method to extract spatial features from the neighborhood space of the road, and it extracts the correlation between speed and time from the original features and neighborhood aggregation features through two GRUs, respectively. Finally, the attention model is introduced to collect and summarize the information of the road and its neighborhood in the global time to perform traffic prediction. In this paper, the prediction performance of NA-DGRU is tested on two real-world datasets, SZ-taxi and Los-loop. In the 15-, 30-, 45- and 60-min speed prediction results of NA-DGRU on the SZ-taxi dataset, the RMSE values were 4.0587, 4.0683, 4.0777 and 4.0851, respectively, and the MAE values were 2.7387, 2.728, 2.7393 and 2.7487; on the Los-loop dataset, the RMSE values for the speed prediction results were 5.1348, 6.1358, 6.7604 and 7.2776, respectively, and the MAE values were 3.0281, 3.6692, 4.0567 and 4.4256, respectively. On the SZ-taxi dataset, compared with other baseline methods, NA-DGRU demonstrated a maximum reduction in RMSE of 6.49% and a maximum reduction in MAE of 6.17%; on the Los-loop dataset, the maximum reduction in RMSE was 31.01%, and the maximum reduction in MAE reached 24.89%.
Research on Integrated Scheduling of Multi-Mode Emergency Rescue for Flooding in Chemical Parks
Authors: Guo Bowen , Zhan Wei
Published: February 2023

As the scale of the chemical park industry continues to expand, the impact of flooding on the park’s people and surrounding environment increases. This paper uses project scheduling theory to optimize the emergency rescue process in order to alleviate the suffering of affected people, promote the sustainable development of society and the environment, and take into account the characteristics of the dynamic evolution of flooding in chemical parks and the periodic renewal of emergency resources. We constructed a proactive–reactive multi-mode emergency rescue integrated scheduling model that aims to minimize the loss of affected people in the early stage of flooding and minimize the sum of the total deviation of the start time and end time of activities before and after reactive scheduling in the later stages of flooding. Furthermore, an ant colony algorithm was designed to solve the constructed model. Next, the effectiveness of the proposed model and solution algorithm was verified using simulations of actual cases. The calculation results show that using proactive–reactive integrated scheduling can improve the efficiency of emergency rescue and reduce the loss of affected people. Moreover, if a multi-mode rescue strategy is adopted, emergency rescue scheduling under four different resource combinations can reduce rescue duration and loss of affected people. The model can provide a decision reference for sustainable emergency rescue scheduling in chemical parks during a flood.
Understanding Consumers’ Barriers to Using FinTech Services in the United Arab Emirates: Mixed-Methods Research Approach
Authors: Bouteraa Mohamed , Chekima Brahim , Lajuni Nelson , Anwar Ayesha
Published: February 2023

The cutting-edge development known as FinTech is now fast replacing traditional financial services all over the world. Despite that, UAE consumers are still not embracing FinTech services at the expected rate. This study hence suggests expanded research based on the unified theory of acceptance and use of technology (UTAUT) to deeply examine the obstacles preventing consumers from using FinTech services. This research utilised an exploratory sequential mixed-method approach. Preliminary semi-structured interviews involving ten banking experts were undertaken to explore the barriers preventing consumers from using FinTech services. To get additional empirical support for the research concept, the study sequentially examined numerous components using a quantitative cross-sectional online survey involving 332 bank customers. The qualitative investigation highlighted six new barriers that consumers face when using FinTech. Through quantitative data analysis, the preliminary qualitative findings were largely verified. As far as the authors are concerned, this inquiry is the first to put forth a thorough model that takes into account organisational, technological, individual, and environmental aspects for addressing the problem of low FinTech usage. By incorporating several new factors, this study also expands the UTAUT. Additionally, it is one of the first studies to examine FinTech adoption employing a mixed-approach methodology.
Identifying, Monitoring, and Evaluating Sustainable Ecotourism Management Criteria and Indicators for Protected Areas in Türkiye: The Case of Camili Biosphere Reserve
Authors: Aydin Inci Zeynep , Öztürk Atakan
Published: February 2023

Although many criteria and indicator sets have been developed for sustainable ecotourism management in many countries around the world, such a set of criteria and indicators has not been developed in Türkiye yet. The aim of this study was to develop sustainable ecotourism management criteria and indicators specific to Türkiye’s social, economic, and ecological differences and to investigate the possibilities of using this developed set in the sustainable management of the Camili Biosphere Reserve Area. The set that consisted of 12 criteria and 68 indicators prepared based on WTO and UNWTO criteria and indicator sets was used as a starting point. Within the scope of the Delphi method, as a result of three stages of repeated questionnaires, a set of criteria and indicators consisting of 11 criteria and 101 indicators was reached, based on the suggestions and consensus of four expert groups. In the next step, the adaptation and prioritization of the national sustainable ecotourism management criteria and indicator set for the Camili Biosphere Reserve Area were realized using the Analytical Hierarchy Process method, depending on the opinions of four local expert groups. As a result, it was concluded that the ecotourism activities carried out in the Camili Biosphere Reserve received a total score of 95.4 and that the ecotourism activities in the area were positively sustainable, with an average of 69.1%. It was determined that ecotourism activities in the Camili Biosphere Reserve are positively sustainable in terms of “level of awareness and perception of the field”, “socio-economic benefits to the local people”, “local participation”, “financial structure”, “environmental education and practices“, and “visitor satisfaction” criteria. However, in order to ensure the sustainability of ecotourism activities both at the country level and at the local level, studies should be carried out with a participatory approach by establishing a balance between the expectations of the local people and the income obtained from ecotourism, by providing a central authority, and by making improvements in the financing structure.
Proposal of a Disrupted Road Detection Method in a Tsunami Event Using Deep Learning and Spatial Data
Authors: Sakamoto Jun
Published: February 2023

Tsunamis generated by undersea earthquakes can cause severe damage. It is essential to quickly assess tsunami-damaged areas to take emergency measures. In this study, I employ deep learning and develop a model using aerial photographs and road segment data. I obtained data from the aerial photographs taken after the Great East Japan Earthquake; the deep learning model used was YOLOv5. The proposed method based on YOLOv5 can determine damaged roads from aerial pictures taken after a disaster. The feature of the proposed method is to use training data from images separated by a specific range and to distinguish the presence or absence of damage related to the tsunami. The results show that the proposed method is more accurate than a comparable traditional method, which is constructed by labeling and learning the damaged areas. The highest F1 score of the traditional method was 60~78%, while the highest F1 score of the proposed method was 72~83%. The traditional method could not detect locations where it is difficult to determine the damage status from aerial photographs, such as where houses are not completely damaged. However, the proposed method was able to detect them.
Bioethanol Production from Waste and Nonsalable Date Palm (Phoenix dactylifera L.) Fruits: Potentials and Challenges
Authors: Castillo Azenith B. , Cortes Dan Jerry D. , Sorino Caesar F. , Soriño Christian Kim P. , El-Naas Muftah H. , Ahmed Talaat
Published: February 2023

Balancing the needs of current and future generations stimulates investment for sustainable development such as converting waste biomass into biorenewables. Sugar-based ethanol production is a well-investigated and established process, and researchers are now focusing on the transformation of cellulosic biomass to sugar and the application of non-conventional methods for ethanol production. The State of Qatar generates date palm fruit waste of approximately 4505 tons annually, excluding ornamental palms and palms outside the farms that bear nonmarketable date fruits. Date fruit molasses contains fermentable sugars, representing 75% of the total fruit mass, which can offer a good source for bioethanol production through anaerobic fermentation and distillation. On this basis, the valorization of waste date fruits can be an effective zero-waste strategy via biotransformation into bio-renewable materials, hence, contributing to the achievement of sustainable development goals. This paper reviews the potentials and challenges for the utilization of waste date fruits as a bioethanol source and assesses the abundance of waste date fruits as raw material for the conventional bioethanol conversion process. The review also identified conventional and nonconventional processes for bioethanol production and their applicability to Qatar. Finally, this confirmed ample demand for bioethanol ranging from fuel and industrial chemicals to pharmaceutical alcohol.
The Spatio-Temporal Pattern of Regional Coordinated Development in the Common Prosperity Demonstration Zone—Evidence from Zhejiang Province
Authors: Xu Binkai , Liu Lei , Sun Yanming
Published: February 2023

Achieving common prosperity is the essential requirement of socialism and promoting regional coordinated development (RCD) is an important path to achieving common prosperity. This study uses data from Zhejiang Province from 2011 to 2020, a demonstration zone of common prosperity, to construct an evaluation model of RCD, assess the regional development level and coordinated development degree, and then analyze the regional differences and spatial correlation pattern of RCD. The following results were obtained: (1) The economic, social, and ecological subsystems of all cities or counties show a continuous or fluctuating rise, and the regional coordinated development level of each study unit also shows a rising trend. This shows that steady regional development is the fundamental material basis for common prosperity. (2) The level of economic and social development shows a pattern of high in the north and low in the south, while the level of ecological development shows a pattern of high in the south and low in the north. The level of RCD evolves from a very uneven spatial distribution to a good level of coordinated development in most cities. It shows that the equalization of development among regions is a realistic manifestation of common prosperity. (3) The level of RCD in Zhejiang Province has greater intra-regional than inter-regional differences, and the differences in RCD in the north are greater than those in the south. The differences between regions have been narrowing. It shows a significant positive spatial correlation, with high-value regions tending to be adjacent to high-value regions and low-value regions tending to be adjacent to low-value regions. In sum, the development of Zhejiang Province in the last decade provides evidence of its role as a demonstration zone for common prosperity. It confirms that coordinated regional development is the fundamental way to achieve common prosperity.
A Meta-Analysis and Systematic Review of the Effect of Chatbot Technology Use in Sustainable Education
Authors: Deng Xinjie , Yu Zhonggen
Published: February 2023

The development of artificial intelligence in recent years has promoted the use of chatbot technology in sustainable education. Many studies examined the effect of chatbots on learning outcomes. However, scant studies summarized the effectiveness of chatbots in education. The aim of the study is to investigate the effect of chatbot-assisted learning on various components and how different moderator variables influenced the effectiveness. This study, through a meta-analysis, reviewed 32 empirical studies with 2201 participants published between 2010 and 2022. The results showed that chatbot technology exerted a medium-to-high effect on overall learning outcomes regardless of moderator variables, i.e., intervention duration, chatbot roles, and learning content. In terms of learning components, chatbots could significantly improve explicit reasoning, learning achievement, knowledge retention, and learning interest despite negative findings in critical thinking, learning engagement, and motivation. Future research could expand chatbot research by including different learning components.
Valuing in the Agrifood System: The Case of Fresh Grain Legumes in Denmark
Authors: Aare Ane Kirstine , Hansen Stine Rosenlund , Kristensen Niels Heine , Hauggaard-Nielsen Henrik
Published: February 2023

Transitioning towards more sustainable food products, such as plant proteins, requires a change in practice by several actors in the agrifood system. Change of this kind involves everyday choices about what food to produce, sell, prepare, and eat. Inspired by science and technology studies (STS) thinking, we investigate how such choices are influenced by socio-material practices of valuing. We use the case of fresh grain legumes for human consumption to explore how valuing is simultaneously affected by and shapes the agrifood system. Through interviews with 24 actors in the Danish agrifood system, we identify valuing parameters ranging from taste, nitrogen fixation, durability, and nutrition to price. The study reveals differences regarding what and how actors value depending on the actors’ position in the agrifood system and how the fresh grain legumes travel from field to plate. Where values conflict, we observe how some valuing practices have the power to exclude others and thereby prevent specific enactments of the fresh grain legumes. We argue that looking for valuing practices can help us understand how agrifood systems come into being, and that valuing differently can represent active involvement, both academically and practically, in encouraging change in the agrifood system. By using STS-thinking, the study brings novel insights about barriers towards more plant-based diets and contributes to the diversification of theoretical perspectives on sustainable transitions.
From Sport Policy to National Federation Sport Policy: An Integrative Literature Review and Conceptualisation Attempt
Authors: Viollet Bastien , Scelles Nicolas , Peng Qi
Published: February 2023

The notion of sport policy is a relatively recent subject of study, but it has been frequently used over the last 20 years, particularly referring to governmental sport policies. However, less research has been conducted in the field of national sport federations (NSFs), which are key non-governmental structures in governing, organising and sustaining the development of sports. The objective of this article is to propose a conceptualisation of the notion of sport policy adapted to NSFs. The proposed approach consists of two steps: first, we conducted an extensive integrative literature review around the notion of sport policy. Second, based on the literature review, we developed a model that conceptualises what an NSF sport policy is. This conceptual model is intended to be a useful analytical tool to design, implement and assess the success of a sport policy for both researchers and practitioners working in the field of NSFs.
Missing Structural Health Monitoring Data Recovery Based on Bayesian Matrix Factorization
Authors: Sun Shouwang , Jiao Sheng , Hu Qi , Wang Zhiwen , Xia Zili , Ding Youliang , Yi Letian
Published: February 2023

The exposure of bridge health-monitoring systems to extreme conditions often results in missing data, which constrains the health monitoring system from working. Therefore, there is an urgent need for an efficient data cleaning method. With the development of big data and machine-learning techniques, several methods for missing-data recovery have emerged. However, optimization-based methods may experience overfitting and demand extensive tuning of parameters, and trained models may still have substantial errors when applied to unseen datasets. Furthermore, many methods can only process monitoring data from a single sensor at a time, so the spatiotemporal dependence among monitoring data from different sensors cannot be extracted to recover missing data. Monitoring data from multiple sensors can be organized in the form of matrix. Therefore, matrix factorization is an appropriate way to handle monitoring data. To this end, a hierarchical probabilistic model for matrix factorization is formulated under a fully Bayesian framework by incorporating a sparsity-inducing prior over spatiotemporal factors. The spatiotemporal dependence is modeled to reconstruct the monitoring data matrix to achieve the missing-data recovery. Through experiments using continuous monitoring data of an in-service bridge, the proposed method shows good performance of missing-data recovery. Furthermore, the effect of missing data on the preset rank of matrix is also investigated. The results show that the model can achieve higher accuracy of missing-data recovery with higher preset rank under the same case of missing data.
Institutional Pressures and Circular Economy Target Performance: Are Zero Waste Practices and Enviropreneurship Worth Pursuing?
Authors: Nassani Abdelmohsen A. , Isac Nicoleta , Rosak-Szyrocka Joanna , Yousaf Zahid , Haffar Mohamed
Published: February 2023

The continuous worsening environmental pollution and rapid depletion of natural resources exerts pressures on the economies to adopt circular economy principles in order to improve and protect the natural environment. Given the importance to humanity and social responsibility, this study examines how CETP is achieved through zero waste practices and IP. Zero waste practices are also tested as a mediator between IP and CETP. Furthermore, we also tested the moderating role of enviropreneurship on the relationship between zero waste practices and CETP. Data were collected from 273 front-line managers of manufacturing concerns and analyzed through SPSS 25.0 and SEM. Results proved that IP plays an essential role in explaining CETP and zero waste practices. Zero waste practices directly affectCETP, and also act as a mediator between IP and CETP.
A Novel Desert Vegetation Extraction and Shadow Separation Method Based on Visible Light Images from Unmanned Aerial Vehicles
Authors: Lu Yuefeng , Song Zhenqi , Li Yuqing , An Zhichao , Zhao Lan , Zan Guosheng , Lu Miao
Published: February 2023

Owing to factors such as climate change and human activities, ecological and environmental problems of land desertification have emerged in many regions around the world, among which the problem of land desertification in northwestern China is particularly serious. To grasp the trend of land desertification and the degree of natural vegetation degradation in northwest China is a basic prerequisite for managing the fragile ecological environment there. Visible light remote sensing images taken by a UAV can monitor the vegetation cover in desert areas on a large scale and with high time efficiency. However, as there are many low shrubs in desert areas, the shadows cast by them are darker, and the traditional RGB color-space-based vegetation index is affected by the shadow texture when extracting vegetation, so it is difficult to achieve high accuracy. For this reason, this paper proposes the Lab color-space-based vegetation index L2AVI (L-a-a vegetation index) to solve this problem. The EXG (excess green index), NGRDI (normalized green-red difference index), VDVI (visible band difference vegetation index), MGRVI (modified green-red vegetation index), and RGBVI (red-green-blue vegetation index) constructed based on RGB color space were used as control experiments in the three selected study areas. The results show that, although the extraction accuracies of the vegetation indices constructed based on RGB color space all reach more than 70%, these vegetation indices are all affected by the shadow texture to different degrees, and there are many problems of misdetection and omission. However, the accuracy of the L2AVI index can reach 99.20%, 99.73%, and 99.69%, respectively, avoiding the problem of omission due to vegetation shading and having a high extraction accuracy. Therefore, the L2AVI index can provide technical support and a decision basis for the protection and control of land desertification in northwest China.
Innovative Development and Practice of Digital Rural Governance Model Based on Green Ecology
Authors: Lv Lujun , Shi Danni
Published: February 2023

Rural governance is an important issue that cannot be ignored in China’s modernization drive. It is not only related to the stability and development of grassroots society, but also to the rise and fall of a nation. The modernization and evolution of rural governance is the foundation of understanding rural social governance, and it is also an important part of current rural social management. Based on the simplification of the current rural traditional governance model, this paper conducts research on its innovative development based on the theory of green ecology. After more than 30 years of practice, the current rural governance model has greatly promoted the democratization of grassroots society. After profound adjustment and changes in the economic and social structure, the existing rural governance model is also faced with problems that urgently need to be solved. Rural grassroots informatization management takes the village as the center and uses modern information technology and communication technology for management. On the basis of the analysis, it can be concluded that the efficiency of rural information through digital display was as high as 60%, and the information could be conveyed to everyone more intuitively and clearly. The rural governance model would also receive a qualitative leap forward. Therefore, the work of rural governance has a long way to go. It is necessary to mobilize the masses, publicize to the masses, give full play to the enthusiasm and initiative of the masses, ensure that farmers exercise their right to participate in the environment according to the law, and implement a new model of government investment, joint participation among farmers, and the linkage of government and farmers, in order to promote rural ecological civilization, and promote the construction of beautiful countryside.
Democracy and Human Rights in the Management of Small-Scale Fisheries in England
Authors: Gray Tim , Korda Rebecca , Stead Selina Margaret
Published: February 2023

Small-scale fisheries (SSF) in England face several challenges to their viability. We argue that the source of these challenges can be traced to the more dominant large-scale fisheries (LSF) sector which has more influence than SSF over government policies. A recent attempt to mitigate the impact of these challenges has been made by the Future of Inshore Fisheries initiative whose main prescription is co-management, i.e., giving SSF a participatory role with the government and LSF in the decision-making in English fisheries management. Co-management is a form of democracy and it may help the SSF to deal with their problems. However, in our view, the English SSF also require an acknowledgement of their human rights to a fair quota and protected access to productive inshore waters. In making this case, we draw on normative arguments to assert that human rights are prior to democratic processes. Our conclusion is that both democratic decision-making and human rights principles are needed to secure the English SSF from the real threat of extinction.
Challenges of Higher Education in Turbulent Environments
Authors: Bernardo Ana B. , Castro-Lopez Adrian , Almeida Leandro S. , Fernandez-Rivas Silvia
Published: February 2023

New technologies will change personal and social life as we know it today [...]
Mechanical and Microstructural Properties of a Stabilized Sand Using Geopolymer Made of Wastes and a Natural Pozzolan
Authors: Nabizadeh Mashizi Mahsa , Bagheripour Mohammad Hossein , Jafari Mohammad Mostafa , Yaghoubi Ehsan
Published: February 2023

In this study, a combination of geopolymers including Rafsanjan Natural Pozzolan (RNP), Cement Kiln Dust (CKD), and an activator such as Calcium Carbide Residue (CCR) or NaOH was used to stabilize and improve the poorly graded sandy soil. Factors such as the activator type, activator concentration, CKD and RNP content were studied. Chemical compounds of the soil and abovementioned materials were investigated using X-ray Diffraction (XRD) and X-ray Fluorescence (XRF) detection tests. Unconfined Compressive Strength (UCS) tests were carried out to evaluate the mechanical behavior of the specimens. The findings revealed that CKD, which is a hazardous byproduct, could be turned into an eco-friendly construction material through geopolymerization. The presence of CKD along with NaOH significantly increased the UCS of the samples compared to unstabilized specimens (control 1). Microstructural analyses using Scanning Electron Microscopy (SEM) confirmed the desirable distribution of the geopolymer gel in the stabilized soil. According to the SEM images, it was observed that the samples stabilized with CKD had a higher strength than those stabilized with CKD combined with RNP due to the formation of a greater amount of gel and a stable microstructure. The findings of this research promote sustainable ground improvement techniques using waste by-products.
Incorporating Vehicle-Routing Problems into a Closed-Loop Supply Chain Network Using a Mixed-Integer Linear-Programming Model
Authors: Pedram Ali , Sorooshian Shahryar , Mulubrhan Freselam , Abbaspour Afshin
Published: February 2023

In recent years, there has been a tremendous increase in environmental awareness, due to concerns about sustainability. Designing an efficient supply chain network that fulfills the expectation of both business owners and customers and, at the same time, pays attention to environmental protection is becoming a trend in the commercial world. This study proposes a theoretical model incorporating vehicle routing problems (VRPs) into the typical CLSC (closed-loop supply chain) network architecture. This combination assists all operators to act more efficiently in terms of environmental protection and profitability. A mixed-integer-linear-programming model for CLSC network design with fuzzy and random uncertain data is developed to achieve the goals. The parameters of the CLSC network are also programmed using hybrid fuzzy-stochastic mathematical programming. The model is for a single product and a single timeframe. Several numerical examples are provided to demonstrate the validity of the proposed mixed-integer-linear-programming (MILP) model. This study also investigated probabilistic possibilities for recourse variables with a trapezoidal fuzzy number using a problem size of four cases. The result indicates that the model performed well in the numerical test, suggesting it can help the operation to be more profitable if this model is implemented in their daily routines.