bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Analysis of Dropout and Student Permanence in Rural Higher Education
Authors: Guzmán Alfredo , Barragán Sandra , Cala-Vitery Favio
Published: July 2022

The growing dropout and low permanence of rural students in higher education has become a central problem in the education system, both affecting the quality conditions of training programmes and preventing the materialisation of the benefits that achieving this educational level entails for society. However, the study of these events in rural populations is scarce, resulting in an inadequate treatment of dropout and, consequently, the impossibility of consolidating student permanence. Thus, the aim of this article is to identify which individual, academic, socio-economic, and institutional variables influence the dropout and the retention of the rural student population in higher education. To achieve this purpose, a cross-sectional study was defined. The sample used was a non-probabilistic sample with an n of 269 rural Colombian students who were administered a self-report questionnaire that assessed 59 variables. Data analysis was based on means comparison and cluster modelling. The results show that dropout and permanence in rural students is related to the educational level of the father, family and work obligations, the need to move from their place of residence, the academic average in higher education, satisfaction with the choice of programme, communication with the institution, and the attention of teachers, among other things.
Does Online Ride-Hailing Service Improve the Efficiency of Taxi Market? Evidence from Shanghai
Authors: Ma Yiyuan , Chen Ke , Xiao Youzhi , Fan Rong
Published: July 2022

Online ride-hailing services, which are characterized by online matching, are generally considered improving the work efficiency of taxi drivers and bring disruptive changes to the taxi market. We use the historical and contemporaneous trip-level big data of Shanghai online ride-hailing drivers and traditional cruising taxi drivers, structure the data into shift and hour levels, and compare the two types in terms of efficiency. The comparison results indicate that the overall capacity utilization rate of online ride-hailing drivers is slightly higher than that of cruising taxi drivers, but it is mainly driven by part-time drivers. We confirm the role of flexible work and market scale in improving capacity utilization, but do not find the impact of online matching mechanisms. From the perspective of the drivers’ work efficiency, the similar capacity utilization of the two types of full-time workers is consistent with Cramer and Krueger’s (2016) evidence in New York. Online matching and street searching achieve almost equal efficiency in densely populated urban areas. However, from the perspective of supply and demand matching, online ride-hailing creates a more flexible supply and is more adaptable to the changes in demand, which improves the overall taxi market efficiency.
Five Guidelines for Adopting Smartwatches in Construction: A Novel Approach for Understanding Workers’ Efficiency Based on Travelled Distances and Locations
Authors: Pérez Cristina Toca , Salling Stephanie , Wandahl Søren
Published: July 2022

This study is part of an ongoing research project aiming to develop a method for understanding workers’ efficiency (workers’ time spent in value-adding activities) by measuring new indexes, such as workers’ travelled distances and workers’ locations collected by smartwatches. To achieve the objective of the study, a Design Science Research (DSR) strategy was adopted. The first cycle consists of understanding which types of information smartwatches can collect and how this data can be employed for measuring workers’ efficiency. This paper reports a case study as part of the first Cycle of the DSR. The object studied were the activities carried out by a carpenter trade in a housing renovation project. The authors used the geographic coordinates obtained by smartwatches worn by the carpenter trade connected to two Global Navigations Satellite Systems. The primary contribution of this research consists of proposing a set of five guidelines for the application of smartwatches, using data gathered from the case study. The guidelines are: (1) adopt a stratified sampling approach for selecting the workers involved according to their tasks conducted; (2) set up the smartwatches considering workers’ physical features; (3) carefully consider the job site location for delivering the smartwatch to workers; (4) establish assumptions for the data cleaning process regarding construction project features and the study’s goal; and (5) use individual participant data in the analysis according to each participant’s characteristics and role.
Eye-SCOR: A Supply Chain Operations Reference-Based Framework for Smart Eye Status Monitoring Using System Dynamics Modeling
Authors: Pourreza Saba , Faezipour Misagh , Faezipour Miad
Published: July 2022

This work is a unique integration of three different areas, including smart eye status monitoring, supply chain operations reference (SCOR), and system dynamics, to explore the dynamics of the supply chain network of smart eye/vision monitoring systems. Chronic eye diseases such as glaucoma affect millions of individuals worldwide and, if left untreated, can lead to irreversible vision loss. Nearly half of the affected population is unaware of the condition and can be informed with frequent, accessible eye/vision tests. Tonometry is the conventional clinical method used in healthcare settings to determine the intraocular pressure (IOP) level for evaluating the risk of glaucoma. There are currently very few (under development) non-contact and non-invasive methods using smartphones to determine the risk of IOP and/or the existence of other eye-related diseases conveniently at home. With the overall goal of improving health, well-being, and sustainability, this paper proposes Eye-SCOR: a supply chain operations reference (SCOR)-based framework to evaluate the effectiveness of smartphone-based eye status monitoring apps. The proposed framework is designed using system dynamics modeling as a subset of a new causal model. The model includes interaction/activities between the main players and enablers in the supply chain network, namely suppliers/service providers, smartphone app/device factors, customers, and healthcare professionals, as well as cash and information flow. The model has been tested under various scenarios and settings. Simulation results reveal the dynamics of the model and show that improving the eye status monitoring device/app factors directly increases the efficiency/Eye-SCOR level. The proposed framework serves as an important step towards understanding and improving the overall performance of the supply chain network of smart eye/vision monitoring systems.
Deep Model-Based Security-Aware Entity Alignment Method for Edge-Specific Knowledge Graphs
Authors: Kim Jongmo , Kim Kunyoung , Sohn Mye , Park Gyudong
Published: July 2022

This paper proposes a deep model-based entity alignment method for the edge-specific knowledge graphs (KGs) to resolve the semantic heterogeneity between the edge systems’ data. To do so, this paper first analyzes the edge-specific knowledge graphs (KGs) to find unique characteristics. The deep model-based entity alignment method is developed based on their unique characteristics. The proposed method performs the entity alignment using a graph which is not topological but data-centric, to reflect the characteristics of the edge-specific KGs, which are mainly composed of the instance entities rather than the conceptual entities. In addition, two deep models, namely BERT (bidirectional encoder representations from transformers) for the concept entities and GAN (generative adversarial networks) for the instance entities, are applied to model learning. By utilizing the deep models, neural network models that humans cannot interpret, it is possible to secure data on the edge systems. The two learning models trained separately are integrated using a graph-based deep learning model GCN (graph convolution network). Finally, the integrated deep model is utilized to align the entities in the edge-specific KGs. To demonstrate the superiority of the proposed method, we perform the experiment and evaluation compared to the state-of-the-art entity alignment methods with the two experimental datasets from DBpedia, YAGO, and wikidata. In the evaluation metrics of Hits@k, mean rank (MR), and mean reciprocal rank (MRR), the proposed method shows the best predictive and generalization performance for the KG entity alignment.
Effects of Intrinsic and Extrinsic Motivational Factors on Employee Participation in Internal Crowdsourcing Initiatives in China
Authors: Suen Ted Y. T. , Cheung Simon K. S. , Wang Fu Lee , Hui John Y. K.
Published: July 2022

The concept of crowdsourcing, categorized into internal and external crowdsourcing, emerged relatively recently. Internal crowdsourcing gained increasing popularity in Chinese organizations. Based on the self-determination theory (SDT), this study advances the theoretical understanding of the effects of employee motivation antecedents (the three basic psychological needs: autonomy, competence, and relatedness) on participation effort in internal crowdsourcing activities. Through an online survey, 435 employees in information technology organizations in southern China completed the questionnaires which used for statistical analysis and hypotheses testing. It was found that the three basic psychological needs significantly positively impacted employees’ intrinsic motivation, with autonomy having the most significant effect. Furthermore, only the needs for autonomy and competence were significantly positively associated with extrinsic motivation. A positive relation was observed between intrinsic motivation and employee participation effort in internal crowdsourcing. Although no direct relationship was revealed between extrinsic motivation and employee participation effort, an indirect effect of extrinsic motivation on employee participation via intrinsic motivation was observed, which aligned with one of the main concepts of SDT, the internalization process of extrinsic to intrinsic motivation. Accordingly, the SDT model is applicable to information technology organizations in China based on the findings of this study.
An Agricultural Supply Chain Coordination Model: The Case of Trinity Comprehensive Cooperation Organization in China
Authors: Shi Jia , Zhang Jiacheng , Xie Naiyan , Yang Zhuodong , Luo Jianli
Published: July 2022

Farmer cooperatives play a significant role in increasing farmers’ income, ensuring food security, and maintaining supply chain stability. While the number of cooperatives in China has increased rapidly in recent years, it is challenge for many small-scale cooperatives in China to achieve high performance due to resource and scale constraints. Taking Rui’an Meiyu’s Trinity Comprehensive Cooperation Organization as an example, this paper makes improvement to the original Trinity Comprehensive Cooperation Model and innovatively proposes a new practicable model called “three areas of cooperation with multiple bodies” for small-scale cooperatives to adopt. According to our research, the following features have been identified: first, the formation motivations of the new model include four different aspects, and the formation process of it includes three specific steps. Second, the resource integration mechanism of the new model is composed of production coordination optimization, supply and marketing platform restructuring, and credit capital guarantees. Third, the new cooperative model can increase economic benefits and simultaneously promote sustainable agricultural development. This study further complements the literature on the Trinity Comprehensive Cooperation Model and offers many managerial and academic implications for cooperative members and policy-makers.
An Interpretable Framework for an Efficient Analysis of Students’ Academic Performance
Authors: Gligorea Ilie , Yaseen Muhammad Usman , Cioca Marius , Gorski Hortensia , Oancea Romana
Published: July 2022

Recent technological advancements in e-learning platforms have made it easy to store and manage students’ related data, such as personal details, initial grade, intermediate grades, final grades, and many other parameters. These data can be efficiently processed and analyzed by intelligent techniques and algorithms to generate useful insights into the students’ performance, such as to identify the factors impacting the progress of successful students or the performance of the students who are struggling in their courses and are at risk of failing. Such a framework is scarce in the current literature. This study proposes an interpretable framework to generate useful insights from the data produced by e-learning platforms using machine learning algorithms. The proposed framework incorporates predictive models, as well as regression and classification models to analyze multiple factors of student performance. Classification models are used to systematize normal and at-risk students based on their academic performance, with high precision and accuracy. Regression analysis is performed to determine the inherent linear and nonlinear relationships between the academic outcomes of the students acting as the target or independent variables and the performance indicative features acting as dependent variables. For further analysis, a predictive modeling problem is considered, where the performance of the students is anticipated based on their commitment to a specific course, their performance for the whole course, and their final grades. The efficiency of the proposed framework is also optimized by reliably tuning the algorithmic parameters. Furthermore, the performance is accelerated by empowering the system with a GPU-based infrastructure. Results reveal that the proposed interpretable framework is highly accurate and precise and can identify factors that play a vital role in the students’ success or failure.
A Frequency–Pressure Cooperative Control Strategy of Multi-Microgrid with an Electric–Gas System Based on MADDPG
Authors: Fan Peixiao , Hu Jia , Ke Song , Wen Yuxin , Yang Shaobo , Yang Jun
Published: July 2022

With the development of micro gas turbines (MT) and power-to-gas (P2G) technology, the electric–gas system plays an important role in maintaining the stable, economical, and flexible operation of the microgrid. When subjected to power load disturbance and natural gas load disturbance, the system controller needs to coordinately control the frequency of the microgrid and the gas pressure at the natural gas pipeline nodes. Additionally, the reliability and stability of a multi-microgrid system are much higher than that of a single microgrid, but its control technology is more complicated. Thus, a frequency–pressure cooperative control strategy of a multi-microgrid oriented to an electric–gas system is proposed in this paper. Firstly, based on the analysis of the operating characteristics of the natural gas network and the coupling equipment, the dynamic model of natural gas transmission is built. Secondly, a multi-microgrid load frequency control model including MT, P2G equipment, electric vehicles (EVs), distributed power sources and loads has been established. In addition, according to the three control objectives of microgrid frequency, node pressure and system coordination and stability, the structure of a Muti-Agent Deep Deterministic Policy Gradient (MADDPG) controller is designed, then the definition of space and reward functions are completed. Finally, different cases are set up in the multi-microgrid, and the simulation results are compared with PI control and fuzzy control. The simulation results show that, the proposed MADDPG controller can greatly suppress the frequency deviation caused by wind power and load disturbances and the air pressure fluctuations caused by natural gas network load fluctuations. Additionally, it can coordinate well the overall stability between the sub-microgrids of multi-microgrid.
RETRACTED: Evaluation of a Microbial Consortium and Selection of a Support in an Anaerobic Reactor Directed to the Bio-Treatment of Wastewater of the Textile Industry
Authors: Heredia-R Marco , Layedra-Almeida Andrea , Torres Yenny , Toulkeridis Theofilos
Published: July 2022

The dyeing processes of the textile industry generate waste products such as unfixed dyes, phenolic surfactants and heavy metals. These constitute an environmental problem for the bodies receiving their wastewater due to the interruption of the lighting in the aquatic environment and the release of toxic molecules by the decomposition of the dyes. There are several treatment methods, of which biological methods are the most feasible. In the current study, the I5-ESPE microbial consortium was obtained and evaluated on the components of textile wastewater, in addition to the selection of a support for an anaerobic reactor that is directed to the treatment of effluents from the textile industry. Two microbial consortia were achieved by exposure to air in Pseudomonas culture medium modified with direct dyes Red 23 and Blue 106, evaluating their removal capacity of the reactive dyes Navy 171, Red 141 and Yellow 84. The consortium I5-ESPE was selected for its greatest action, yielding approximately 95% removal. Its tolerance to phenol was also determined; we reached 98% removal of chromium(VI) and 67% of total chromium under anaerobic conditions and some 25% zinc in aerobiosis. The reduction in the chemical oxygen demand (COD) was evaluated with (57.03%) and without (31.47%) aeration. The species Staphylococcus xylosus, Saccharomyces cerevisiae and Candida tropicalis were identified prior to treatment of textile wastewater, as well as Enterobacter cloacae and Bacillus megaterium after treatment. Bacillus subtilis was present throughout the process. We evaluated coconut shell as a support for an anaerobic reactor, and it demonstrated better physical characteristics than plastic and common rock, in addition to similar results in the reduction in COD of 50%, volatile suspended solids of 2545.46 mg/L and total suspended solids of 282.82 mg/L.
Socio-Environmental Responsive Strategy and Sustainable Development of Traditional Tianshui Dwellings
Authors: Shi Jiayi , Zhang Tao , Fukuda Hiroatsu , Zhang Qun , Bai Lujian
Published: July 2022

The comprehensive and coordinated sustainable development of residential dwellings requires a response to the multidimensional environment. In this study, typical traditional Tianshui dwellings are selected as research objects, through the methods of field investigation, in-depth conversations, and on-site monitoring, in order to investigate the potential of traditional Tianshui dwellings reacting to natural conditions as well as social environment. The performance of traditional dwellings in the process of regional adaptation expounded and discussed based on seven elements under the conditions of two dimensions: (1) an objective regional response to the natural environment, namely, site selection, courtyard layout, orientation, structure, and envelop enclosure; and (2) a subjective regional response to social environment, namely, spatial order, construction technology, and decorative arts. The results show that traditional Tianshui dwellings are well adapted to local natural conditions and the social background, and that they meet both the physical and psychological needs of residents. In conclusion, this paper summarizes the features of the sustainable development of traditional dwellings learning from the principles obtained from the process of socio-environment responsive strategy analysis. These valuable experiences and design principles can provide references and guidelines for the long-term development of modern architecture not to only reduce energy consumption, but also to increase local social influence.
Changes of Microbial Diversity in Rhizosphere of Different Cadmium-Gradients Soil under Irrigation with Reclaimed Water
Authors: Cui Jiaxin , Li Ping , Qi Xuebin , Rahman Shafeeq Ur , Zhang Zulin
Published: July 2022

Water scarcity and the uneven distribution of water resources in China have resulted in water shortages for agricultural irrigation in arid and semi-arid areas. Reclaimed water used for agricultural irrigation has become an effective solution in the context of the global water shortage. In order to improve soil productivity and solve the shortage of water resources, we carried out reclaimed water irrigation experiments on polluted soil. Compared with full irrigation treatments, the EC value of reclaimed water under deficit irrigation treatments decreased by 2.89–42.90%, and the content of organic matter increased by 6.31–12.10%. The proportion of Acidobacteria community in soils with different cadmium concentration gradients irrigated with reclaimed water ranged from 13.6% to 30.5%, its relative abundance decreased with the increase of soil cadmium concentration. In particular, the relative abundance of Pseudomonas pathogens in deficit irrigation treatments was lower than that of the full irrigation treatments. RDA analysis showed that the environmental factors that played a leading role in the change of microbial community structure were organic matter and pH. Furthermore, the metabolic function potential of the rhizosphere soil bacterial community in deficit irrigation treatments was higher than that of full irrigation treatments with reclaimed water. This study proved that reclaimed water irrigation for cadmium contaminated soil did not aggravate the pollution level and promoted the soil ecological environment with better microbial community diversity.
Biological Concepts as a Source of Inspiration for Efficiency, Consistency, and Sufficiency
Authors: Speck Olga , Möller Martin , Grießhammer Rainer , Speck Thomas
Published: July 2022

Sustainable development is a global challenge addressed by the 2030 Agenda with internationally adopted goals. The consideration of the three major sustainability strategies of efficiency, consistency, and sufficiency can guide us toward more sustainable policy approaches, product manufacturing, service offers, and consumption lifestyles. We select the growth form “liana”, which has evolved several times independently, to identify traits of lianas and general biological concepts derived therefrom. Even though sustainability is an anthropocentric approach and does not exist in biology, we can attribute biological concepts to sustainability strategies. The biological concepts of lightweight construction, modularity, function-related tissue formation, and trade-off can be attributed to efficiency; the concepts of zero waste, best fit, and damage repair to consistency; and the change of growth form and the concept of less is more and good enough to sufficiency. We discuss the analogies between parasitic architecture and the “structural parasitism” of lianas on host trees and between polymers with switchable autonomous properties and ontogenetic changes in the lianescent growth form. Efficiency can be analyzed quantitatively and consistency qualitatively, whereas sufficiency, as an aspect of human consumption patterns, cannot be mathematically measured. Biological concepts can thus serve as a source of inspiration for improving sustainability in the technosphere.
Research on Chlorophyll-a Concentration Retrieval Based on BP Neural Network Model—Case Study of Dianshan Lake, China
Authors: Zhu Wei-Dong , Qian Chu-Yi , He Nai-Ying , Kong Yu-Xiang , Zou Zi-Ya , Li Yu-Wei
Published: July 2022

The Chlorophyll-a (Chl-a) concentration is an important indicator of water environmental conditions; thus, the simultaneous monitoring of large-area water bodies can be realized through the remote sensing-based retrieval of the Chl-a concentrations. The back propagation (BP) neural network learning method has been widely used for the remote sensing retrieval of water quality in first and second-class water bodies. However, many Chl-a concentration measurements must be used as learning samples with this method, which is constrained by the number of samples, due to the limited time and resources available for simultaneous measurements. In this paper, we conduct correlation analysis between the Chl-a concentration data measured at Dianshan Lake in 2020 and 2021 and synchronized Landat-8 data. Through analysis and study of the radiative transfer model and the retrieval method, a BP neural network retrieval model based on multi-phase Chl-a concentration data is proposed, which allows for the realization of remote sensing-based Chl-a monitoring in third-class water bodies. An analysis of spatiotemporal distribution characteristics was performed, and the method was compared with other constructed models. The research results indicate that the retrieval performance of the proposed BP neural network model is better than that of models constructed using multiple regression analysis and curve estimation analysis approaches, with a coefficient of determination of 0.86 and an average relative error of 19.48%. The spatial and temporal Chl-a distribution over Dianshan Lake was uneven, with high concentrations close to human production and low concentrations in the open areas of the lake. During the period from 2020 to 2021, the Chl-a concentration showed a significant upward trend. These research findings provide reference for monitoring the water environment in Dianshan Lake.
Learning Outcomes of Educational Usage of Social Media: The Moderating Roles of Task–Technology Fit and Perceived Risk
Authors: Sabah Nasser M. , Altalbe Ali A.
Published: July 2022

This study aims to explore the moderating roles of task–technology fit (TTF) and perceived risk (PR) in the relationships between the educational usage of social media (SM) platforms and its use outcomes. This is to better understand the potential benefits of using SM for educational purposes and to provide thorough insights on how SM usage would influence students’ use outcomes. We conceptualize the potential use outcomes through three-dimensional factors: perceived satisfaction, perceived academic performance, and perceived impact on learning. We further hypothesize that TTF and PR have negative moderation effects on the relationships between SM usage and the variables of use outcomes. In addition, we examine gender differences using multi-group analysis. Data were collected from a state college in Palestine using a self-administered survey, and Smart-PLS was used for data analysis and model testing using partial least square–structural equation modeling. The findings reveal that TTF has significant negative effects on the relationships between SM usage and its outcomes, whereas PR has insignificant negative moderation effects. Despite the significant negative interaction effects of TTF, the educational usage of SM has a positive impact on use outcomes. Furthermore, the findings only indicate significant gender differences in three variables: information sharing, TTF, and PR.
Life Cycle Assessment and Life Cycle Cost of an Innovative Carbon Paper Sensor for 17α-Ethinylestradiol and Comparison with the Classical Chromatographic Method
Authors: Martins Florinda , Torrinha Álvaro , Delerue-Matos Cristina , Morais Simone
Published: July 2022

Nowadays there is a growing concern with the environment and sustainability, which means that better methods, including pollutants analysis, with less consumption of materials, organic solvents, and energy, need to be developed. Considering the almost inexistent information about the topic, the main goal of this work was to compare the environmental impacts of two analytical methods, a traditional one based on liquid chromatography with fluorescence detection and a newly developed carbon paper sensor. The selected analyte was 17α-ethinylestradiol, which is a contaminant of emergent concern in aquatic ecosystems due to its endocrine disruptor behavior. The life cycle assessment data showed that the sensor detection presents an almost negligible environmental impact when compared with the extraction step (the same for both methods) and the liquid chromatographic determination (roughly 80 times higher than with the sensor). The sensor values for all categories of damage are below 3% of the total method impacts, i.e., 1.6, 1.9, 2.4, and 2.9% for resources, climate change, human health, and ecosystem quality. The extraction represents 98.1% of the sensor environmental impacts (and 99.6% of its life cycle costing) and 38.8% of the chromatographic method. This study evidences the need of developing and applying greener analytical (detection and extraction) strategies.
Interprovincial Metal and GHG Transfers Embodied in Electricity Transmission across China: Trends and Driving Factors
Authors: Han Yawen , Xing Wanli , Hao Hongchang , Du Xin , Liu Chongyang
Published: July 2022

With the increasing proportion of low-carbon power in electricity generation mix, power generation will be transformed from carbon-intensive to metal-intensive. In this context, metal and GHG transfers embodied in electricity transmission of China from 2015 to 2019 are quantified by the Quasi-Input-Output model. Combined with complex network theory, we have distinguished whether metal and GHG transfers show different trends as electricity trade changes. Driving factors contributing to forming the metal and GHG transfers are also explored based on the Quadratic Assignment Procedure. The results show that the electricity trade change has strengthened the metal transfer network significantly, while several key links in the GHG transfer network have weakened. Moreover, we find provincial differences in low-carbon electricity investment contributing to the metal transfer while affecting the GHG transfer little. The above facts imply an expanding embodied metal transfer in the future and shed light on policy making for power system decarbonization.
Online Engagement with Memes and Comments about Climate Change
Authors: Kovacheva Aleksandra , Wiener Hillary J. D. , Kareklas Ioannis , Muehling Darrel
Published: July 2022

Social media posts, and memes in particular, offer important opportunities for social media users and organizations to disseminate information about climate change. However, as this topic remains controversial, memes often elicit comments that may oppose (rather than support) the existence of climate change. In three studies, we find that the position of the comments influences users’ engagement with the main post: when the user’s and the meme’s positions on climate change align, comments opposing the claim of the meme decrease users’ readiness to “like” the meme. We also examine social media users’ attitudes toward different comment moderating options, including disabling, deleting, hiding, or responding to comments.
Corn Starch-Based Sandstone Sustainable Materials: Sand Type and Water Content Effect on Their Structure and Mechanical Properties
Authors: Zoumaki Maria , Tsongas Konstantinos , Tzetzis Dimitrios , Mansour Gabriel
Published: July 2022

A new biodegradable, sustainable and environmentally friendly building material is introduced and studied in this work, which can be applied to lightweight architectural structures, aiming for the reduction of the greenhouse gas emissions and mitigation of the climate change effects. The focus was to investigate the effect of water concentration and different types of sand on the mechanical properties of corn starch-based artificial sandstone. A series of cubic, cylindrical and disk specimens were prepared by varying the concentration of water and using different sources of commercial quartz sand. The quasi-static and cyclic compressive properties of starch-based artificial sandstone samples were measured as a function of water concentration and sand type, while the structure of the artificial sandstone specimens was examined by scanning electron microscopy (SEM) and optical microscopy. Moreover, the Brazilian Test was employed as the indirect method to determine the tensile strength of the samples based on the type of the commercial sand they contained. The experimental results showed that the homogeneous grading of sand grains and the latter’s chemical composition have a significant effect on the mechanical properties of the sandstone samples. The highest compression values were obtained using the microwave heating method at a water concentration of about 12 wt%, while the cyclic compression and Brazilian Tests have shown that the granulometric grading of the sand particles and the chemical composition of the sand influence the compressive and tensile strength of the material.
Motivation and Engagement of Final-Year Students When Using E-learning: A Qualitative Study of Gamification in Pandemic Situation
Authors: Rahayu Flourensia Sapty , Nugroho Lukito Edi , Ferdiana Ridi , Setyohadi Djoko Budiyanto
Published: July 2022

The COVID-19 pandemic has changed how the education system operates. The shift from face-to-face learning to online learning generated many problems, including decreasing students’ motivation and engagement. Gamification has been used as one of the solutions to overcome the problem of low motivation and engagement in learning. The current study aims to examine students’ behavioral change when using e-learning with gamification, investigate gamification elements that are important to students and how it influences students’ motivation and engagement, and investigate whether population characteristics may influence students’ motivation and engagement. Qualitative methods were employed to gather and analyze the data. The thematic analysis resulted in six main themes. The findings revealed that there were behavioral changes in students during gamification implementation, i.e., from negative to positive and from positive to negative. Four gamification elements were found to be the most important gamification elements to students, i.e., points, leaderboard, badges, and gamified test. The mechanism of how these elements influenced motivation and engagement was discussed. The population characteristics of final-year students also had an impact on gamification effectiveness. Despite gamification’s capabilities to influence motivation and engagement, there are some concerns related to negative impacts that must be addressed in the future.
How Live Streaming Interactions and Their Visual Stimuli Affect Users’ Sustained Engagement Behaviour—A Comparative Experiment Using Live and Virtual Live Streaming
Authors: Lv Jie , Cao Cong , Xu Qianwen , Ni Linyao , Shao Xiuyan , Shi Yangyan
Published: July 2022

With the massive expansion in live streaming, enhancing the sustained engagement of users has become a key issue in ensuring its success. This study examines the relationship between real-time interaction, user perceptions, user intention to keep using live streaming, and whether this relationship differs between a live and a virtual live streaming environment. Using partial least squares (PLS) structural equation modelling (SEM), this paper analyses 240 valid questionnaire responses and finds that there is a link between real-time interactions, visual stimuli, and users’ sustained engagement. This shows that users’ active interactions while watching live streaming videos significantly affect their perceptions of social presence and trust, which in turn, affect their sustained engagement behaviour. These effects were found to vary with differences in the live streaming environment. The findings of this paper will play a positive role in understanding the differences between various live streaming environments, in optimizing the design of live streaming content and in improving the perceptions of emotional warmth by live streaming users.
Changes in and Patterns of the Tradeoffs and Synergies of Production-Living-Ecological Space: A Case Study of Longli County, Guizhou Province, China
Authors: Gao Shunqian , Yang Liu , Jiao Hongzan
Published: July 2022

Production-living-ecological space (PLES) constitutes territorial space, and how to scientifically optimize PLES has become the core issue of territorial spatial planning in China. This paper constructs a spatial classification system for PLES based on merge classification. Taking Longli County, Guizhou Province, China, as an example, this paper studies the spatial patterns in 2015 and 2019, the driving factors of the changes in the spatial patterns, and the interrelationships of production space (PS), living space (LS) and ecological space (ES) and proposes a new scheme for dominant functional zoning. The results show that: (1) The high-scoring areas of PS and LS in Longli County are mainly located near the center of each town, with obvious consistency in the spatial distribution. The high-scoring areas of ES are located in the suburbs far from the towns, conflicting with PS and LS; (2) In the five-year period, PS and LS in Longli County continuously expanded. Specifically, LS expanded the most from the perspective of the rate of change, and ES shrunk continuously; (3) Socioeconomic factors are the dominant factor affecting the changes in PLES, among which the distance to town has the greatest influence; (4) Based on the correlation coefficient, PS and LS have a significant positive correlation, but they have a significant negative correlation with ES. In terms of spatial relationships, PS and LS mainly have synergistic relationships, but their relationships with ES mainly involve tradeoffs; (5) In the spatial functional areas of PLES in Longli County, the single dominant functional area is the main area, among which the ecological-dominant functional area is the largest. The results of this study provide a reference for territorial spatial planning and sustainable regional development.
Combined Effect of Biochar and Fertilizers on Andean Highland Soils before and after Cropping
Authors: Garcia-Perez Tsai , Pelaez-Samaniego Manuel Raul , Delgado-Noboa Jorge , Chica Eduardo J.
Published: July 2022

Although a number of works present biochar as a promising material for improving the quality of degraded soils, only a few show the effect of this material in soils from the Andean highlands. The objective of this work was twofold: (a) to study the effect of two types of biochars on two agricultural soils commonly found in the Andean highlands (Andisol and Inceptisol) and the corresponding soil–biochar–fertilizer interactions, and, (b) to assess the response to biochar of two vegetable crops (lettuce and radish) grown in succession in a simulated double-cropping system. Biochar was produced at 400 °C and 500 °C, for 1 h (B400 and B500, respectively), using hardwood residues. Properties of biochar that could potentially affect its interaction with soil and water (e.g., functional groups, surface area, elemental composition) were assessed. Experiments were conducted to test for main and interaction effects of biochar type, soil type, and the addition of NPK fertilizer on the soils’ characteristics. Bulk density and water content at field capacity and permanent wilting point were affected by two-way interactions between biochar and soil type. Biochar impacted bulk density and water retention capacity of soils. Higher available water content was found in soils amended with B400 than with B500, which is a consequence of the higher hydrophilicity of B400 compared to B500. After the lettuce crop was planted and harvested, the soil pH was unaffected by the biochar addition. However, after the second crop, the pH in the Inceptisol slightly decreased, whereas the opposite was detected in the Andisol. The CEC of the Inceptisol decreased (e.g., from 36.62 to 34.04 and from 41.16 to 39.11 in the control and in the Inceptisol amended with B400 only) and the CEC of the Andisol increased (e.g., from 74.25 to 90.41 in the control and from 79.61 to 90.80 in the Andisol amended with B400 only). Inceptisol amended only with biochar showed decrease of radish weight, while a large increase was found in B400 + fertilizer Inceptisol (i.e., from 22.9 g to 40.4 g). In Andisol, the weight of radish after the second crop increased in less proportion (i.e., from 43 g in the control to 59.7 g in the B400 + fertilizer Andisol), showing a visible positive impact of B400. The results suggest that biochar produced at 400 °C performs better than biochar produced at 500 °C because B400 apparently promotes a better environment for bacteria growth in the soils, as a consequence of more OH available groups in B400 and its better interaction with water and the fertilizer.
The Efficiency of Document and Border Procedures for International Trade
Authors: Hiraide Takashi , Hanaoka Shinya , Matsuda Takuma
Published: July 2022

In many countries, document and border procedures create trading barriers, thereby impairing economic growth. These can range from insufficient transshipment facilities to unsupportive institutional arrangements. To address this, countries have taken reforms to improve their procedures by introducing electronic documentation systems, strengthening border infrastructure, and enhancing customs procedures. However, the efficiency of the document and border procedures in each country remains unclear, as well as how new reforms can affect these. This study investigated the efficiency of document and border procedures in each country, defined as the trade volume and value per required cost, time, and documents in the trading procedures. The efficiencies were calculated through a data envelopment analysis with cross-sectional data from 2019 and a window analysis with panel data from 2014 to 2019. The study found a positive change in export procedure efficiency after all three types of reforms were instituted in a country, but a positive change in import efficiency only after the introduction of electronic documentation. All countries were classified according to their document and border procedure strengths and weaknesses.
Smart Tourist Village—An Entrepreneurial Necessity for Maramures Rural Area
Authors: Ciolac Ramona , Iancu Tiberiu , Popescu Gabriela , Adamov Tabita , Feher Andrea , Stanciu Sorin
Published: July 2022

The necessity of entrepreneurship in rural area is an actual one. A smart entrepreneurial variant of contemporary village’s development could be “the smart tourist village”, to capitalize rural resources. Thus, in this research we come to a variant of contemporary village’s development, respectively “smart tourist village”, which is the basic idea of the work. To demonstrate that the notion of “smart tourist village” can be a future idea of sustainable rural entrepreneurship the steps undertaken were: the identification of the representative aspects of the villages from Maramures and of their specific resources presentation of the specific aspects; the study also made a quantitative presentation of the rural tourism infrastructure from Maramures by localities; and identifies the perception and “vision” of tourists and owners of tourist structures about Maramures tourist village as an innovative solution with benefits for tourists and locals. The information collected by using the method of qualitative case study served to sketch a possible projection such as “smart tourist village” taking into account the possible costs, return on investment, possible design and advantages.
Image Encryption Algorithm Using 2-Order Bit Compass Coding and Chaotic Mapping
Authors: Chen Jinlin , Wu Yiquan , Sun Yeguo , Yang Chunzhi
Published: July 2022

This paper proposes a novel image encryption algorithm based on an integer form of chaotic mapping and 2-order bit compass diffusion technique. Chaotic mapping has been widely used in image encryption. If the floating-point number generated by chaotic mapping is applied to image encryption algorithm, it will slow encryption and increase the difficulty of hardware implementation. An innovative pseudo-random integer sequence generator is proposed. In chaotic system, the result of one-iteration is used as the shift value of two binary sequences, the original symmetry relationship is changed, and then XOR operation is performed to generate a new binary sequence. Multiple iterations can generate pseudo-random integer sequences. Here integer sequences have been used in scrambling of pixel positions. Meanwhile, this paper demonstrates that there is an inverse operation in the XOR operation of two binary sequences. A new pixel diffusion technique based on bit compass coding is proposed. The key vector of the algorithm comes from the original image and is hidden by image encryption. The efficiency of our proposed method in encrypting a large number of images is evaluated using security analysis and time complexity. The performance evaluation of algorithm includes key space, histogram differential attacks, gray value distribution(GDV),correlation coefficient, PSNR, entropy, and sensitivity. The comparison between the results of coefficient, entropy, PSNR, GDV, and time complexity further proves the effectiveness of the algorithm.
An Authentication Protocol for the Medical Internet of Things
Authors: El-Meniawy Nagwa , Rizk Mohamed R. M. , Ahmed Magdy A. , Saleh Mohamed
Published: July 2022

The progress in biomedical sensors, Internet of Things technologies, big data, cloud computing, and artificial intelligence is leading the development of e-health medical systems, offering a range of new and innovative services. One such service is remote patient monitoring, where medical professionals are able to collect and examine a patient’s medical data remotely. Of course, in these systems, security and privacy are of utmost importance and we need to verify the identities of system users before granting them access to sensitive patient-related data. To this end, several authentication protocols have been recently designed specifically for e-health systems. We survey several of these protocols and report on flaws and shortcomings we discovered. Moreover, we propose an authentication protocol that enables a medical professional and the network of sensors used by a patient to authenticate each other and share a cryptographic key to be used for security in a communication session. The protocol also enables the dynamic assignment of patients to doctors in order to control access to patients’ data. We perform a security analysis of the protocol both formally, using the ProVerif protocol analysis tool, and informally, demonstrating its security features. We show that our protocol achieves mutual authentication, secret key establishment, forward secrecy, and anonymity. In terms of performance, the protocol is computationally lightweight, as it relies on symmetric key cryptography. This is demonstrated by comparing the computational cost of our protocol (in terms of execution time) with that of other similar protocols.
Implementation of Two-Mode Gaussian States Whose Covariance Matrix Has the Standard Form
Authors: Cariolaro Gianfranco , Corvaja Roberto
Published: July 2022

This paper deals with the covariance matrix (CM) of two-mode Gaussian states, which, together with the mean vector, fully describes these states. In the two-mode states, the (ordinary) CM is a real symmetric matrix of order 4; therefore, it depends on 10 real variables. However, there is a very efficient representation of the CM called the standard form (SF) that reduces the degrees of freedom to four real variables, while preserving all the relevant information on the state. The SF can be easily evaluated using a set of symplectic invariants. The paper starts from the SF, introducing an architecture that implements with primitive components the given two-mode Gaussian state having the CM with the SF. The architecture consists of a beam splitter, followed by the parallel set of two single–mode real squeezers, followed by another beam splitter. The advantage of this architecture is that it gives a precise non-redundant physical meaning of the generation of the Gaussian state. Essentially, all the relevant information is contained in this simple architecture.