bluuebunny/crossref_metadata_2025 huggingface dataset:
Weighted Information Models for the Quantitative Prediction and Evaluation of the Geothermal Anomaly Area in the Plateau: A Case Study of the Sichuan–Tibet Railway
Authors: Zhao Wenbo , Dong Qing , Chen Zhe , Feng Tao , Wang Dong , Jiang Liangwen , Du Shihui , Zhang Xiaoyu , Meng Deli , Bian Min , Chen Jianping
Published: April 2021

The prediction of geothermal high-temperature anomalies along the plateau railway will be helpful in the construction of the project and its later management. Taking the Sichuan–Tibet railway as the study area and based on Landsat8 thermal infrared images, map data, and measured data regarding the cause and distribution of geothermal high-temperature anomalies, through correlation analysis, we selected six impact factors including the LST, combined entropy of geological formation, fault density, buffer distance to rivers, magnetic anomaly, and earthquake peak acceleration as the input maps of the model. The index-overlay information model, the weights of the entropy information model, and the weights of the evidence information model were established to quantitatively predict the geothermal anomaly in the study area, and the prediction maps were divided into four classes. The results show that the weights of the evidence information model achieved a high prediction accuracy; the success index and the ratio of the high anomaly area reached 0.0053% and 0.872, respectively, and the spatial distribution of the geothermal points is basically consistent with the prediction results. This research can act as a reference for the design and construction of the Sichuan–Tibet railway.
A Multi-Frequency SDR-Based GBSAR: System Overview and First Results
Authors: Amézaga Adrià , López-Martínez Carlos , Jové Roger
Published: April 2021

This work describes a system-level overview of a multi-frequency GBSAR built around a high performance software defined radio (SDR). The main goal of the instrument is to be employed as a demonstrator and experimental platform for multi-frequency GBSAR campaigns. The system is capable of operating in P, L, C and X-bands, and signal generation and digital signal processing are customizable and reconfigurable through software. An overview of the software and hardware and implementations of the system are presented. The operation of the system is demonstrated with two measuring campaigns showing focused amplitude images at different frequencies. It is shown how the usage of SDR for GBSAR systems is a viable design option.
How Can We Realize Sustainable Development Goals in Rocky Desertified Regions by Enhancing Crop Yield with Reduction of Environmental Risks?
Authors: Liang Boyi , Quine Timothy A. , Liu Hongyan , Cressey Elizabeth L. , Bateman Ian
Published: April 2021

To meet the sustainable development goals in rocky desertified regions like Guizhou Province in China, we should maximize the crop yield with minimal environmental costs. In this study, we first calculated the yield gap for 6 main crop species in Guizhou Province and evaluated the quantitative relationships between crop yield and influencing variables utilizing ensembled artificial neural networks. We also tested the influence of adjusting the quantity of local fertilization and irrigation on crop production in Guizhou Province. Results showed that the total yield of the selected crops had, on average, reached over 72.5% of the theoretical maximum yield. Increasing irrigation tended to be more consistently effective at increasing crop yield than additional fertilization. Conversely, appropriate reduction of fertilization may even benefit crop yield in some regions, simultaneously resulting in significantly higher fertilization efficiency with lower residuals in the environment. The total positive impact of continuous intensification of irrigation and fertilization on most crop species was limited. Therefore, local stakeholders are advised to consider other agricultural management measures to improve crop yield in this region.
Assessment of Rangeland Degradation in New Mexico Using Time Series Segmentation and Residual Trend Analysis (TSS-RESTREND)
Authors: Gedefaw Melakeneh G. , Geli Hatim M. E. , Abera Temesgen Alemayehu
Published: April 2021

Rangelands provide significant socioeconomic and environmental benefits to humans. However, climate variability and anthropogenic drivers can negatively impact rangeland productivity. The main goal of this study was to investigate structural and productivity changes in rangeland ecosystems in New Mexico (NM), in the southwestern United States of America during the 1984–2015 period. This goal was achieved by applying the time series segmented residual trend analysis (TSS-RESTREND) method, using datasets of the normalized difference vegetation index (NDVI) from the Global Inventory Modeling and Mapping Studies and precipitation from Parameter elevation Regressions on Independent Slopes Model (PRISM), and developing an assessment framework. The results indicated that about 17.6% and 12.8% of NM experienced a decrease and an increase in productivity, respectively. More than half of the state (55.6%) had insignificant change productivity, 10.8% was classified as indeterminant, and 3.2% was considered as agriculture. A decrease in productivity was observed in 2.2%, 4.5%, and 1.7% of NM’s grassland, shrubland, and ever green forest land cover classes, respectively. Significant decrease in productivity was observed in the northeastern and southeastern quadrants of NM while significant increase was observed in northwestern, southwestern, and a small portion of the southeastern quadrants. The timing of detected breakpoints coincided with some of NM’s drought events as indicated by the self-calibrated Palmar Drought Severity Index as their number increased since 2000s following a similar increase in drought severity. Some breakpoints were concurrent with some fire events. The combination of these two types of disturbances can partly explain the emergence of breakpoints with degradation in productivity. Using the breakpoint assessment framework developed in this study, the observed degradation based on the TSS-RESTREND showed only 55% agreement with the Rangeland Productivity Monitoring Service (RPMS) data. There was an agreement between the TSS-RESTREND and RPMS on the occurrence of significant degradation in productivity over the grasslands and shrublands within the Arizona/NM Tablelands and in the Chihuahua Desert ecoregions, respectively. This assessment of NM’s vegetation productivity is critical to support the decision-making process for rangeland management; address challenges related to the sustainability of forage supply and livestock production; conserve the biodiversity of rangelands ecosystems; and increase their resilience. Future analysis should consider the effects of rising temperatures and drought on rangeland degradation and productivity.
Estimating Plant Nitrogen Concentration of Rice through Fusing Vegetation Indices and Color Moments Derived from UAV-RGB Images
Authors: Ge Haixiao , Xiang Haitao , Ma Fei , Li Zhenwang , Qiu Zhengchao , Tan Zhengzheng , Du Changwen
Published: April 2021

Estimating plant nitrogen concentration (PNC) has been conducted using vegetation indices (VIs) from UAV-based imagery, but color features have been rarely considered as additional variables. In this study, the VIs and color moments (color feature) were calculated from UAV-based RGB images, then partial least square regression (PLSR) and random forest regression (RF) models were established to estimate PNC through fusing VIs and color moments. The results demonstrated that the fusion of VIs and color moments as inputs yielded higher accuracies of PNC estimation compared to VIs or color moments as input; the RF models based on the combination of VIs and color moments (R2 ranging from 0.69 to 0.91 and NRMSE ranging from 0.07 to 0.13) showed similar performances to the PLSR models (R2 ranging from 0.68 to 0.87 and NRMSE ranging from 0.10 to 0.29); Among the top five important variables in the RF models, there was at least one variable which belonged to the color moments in different datasets, indicating the significant contribution of color moments in improving PNC estimation accuracy. This revealed the great potential of combination of RGB-VIs and color moments for the estimation of rice PNC.
Robust Multipath-Assisted SLAM with Unknown Process Noise and Clutter Intensity
Authors: Dan Zesheng , Lian Baowang , Tang Chengkai
Published: April 2021

In multipath-assisted simultaneous localization and mapping (SLAM), the geometric association of specular multipath components based on radio signals with environmental features is used to simultaneously localize user equipment and map the environment. We must contend with two notable model parameter uncertainties in multipath-assisted SLAM: process noise and clutter intensity. Knowledge of these two parameters is critically important to multipath-assisted SLAM, the uncertainty of which will seriously affect the SLAM accuracy. Conventional multipath-assisted SLAM algorithms generally regard these model parameters as fixed and known, which cannot meet the challenges presented in complicated environments. We address this challenge by improving the belief propagation (BP)-based SLAM algorithm and proposing a robust multipath-assisted SLAM algorithm that can accommodate model mismatch in process noise and clutter intensity. Specifically, we describe the evolution of the process noise variance and clutter intensity via Markov chain models and integrate them into the factor graph representing the Bayesian model of the multipath-assisted SLAM. Then, the BP message passing algorithm is leveraged to calculate the marginal posterior distributions of the user equipment, environmental features and unknown model parameters to achieve the goals of simultaneous localization and mapping, as well as adaptively learning the process noise variance and clutter intensity. Finally, the simulation results demonstrate that the proposed approach is robust against the uncertainty of the process noise and clutter intensity and shows excellent performances in challenging indoor environments.
Measuring Gait Velocity and Stride Length with an Ultrawide Bandwidth Local Positioning System and an Inertial Measurement Unit
Authors: Singh Pratham , Esposito Michael , Barrons Zach , Clermont Christian A. , Wannop John , Stefanyshyn Darren
Published: April 2021

One possible modality to profile gait speed and stride length includes using wearable technologies. Wearable technology using global positioning system (GPS) receivers may not be a feasible means to measure gait speed. An alternative may include a local positioning system (LPS). Considering that LPS wearables are not good at determining gait events such as heel strikes, applying sensor fusion with an inertial measurement unit (IMU) may be beneficial. Speed and stride length determined from an ultrawide bandwidth LPS equipped with an IMU were compared to video motion capture (i.e., the “gold standard”) as the criterion standard. Ninety participants performed trials at three self-selected walk, run and sprint speeds. After processing location, speed and acceleration data from the measurement systems, speed between the last five meters and stride length in the last stride of the trial were analyzed. Small biases and strong positive intraclass correlations (0.9–1.0) between the LPS and “the gold standard” were found. The significance of the study is that the LPS can be a valid method to determine speed and stride length. Variability of speed and stride length can be reduced when exploring data processing methods that can better extract speed and stride length measurements.
Studying Collaboration Dynamics in Physical Learning Spaces: Considering the Temporal Perspective through Epistemic Network Analysis
Authors: Vujovic Milica , Amarasinghe Ishari , Hernández-Leo Davinia
Published: April 2021

The role of the learning space is especially relevant in the application of active pedagogies, for example those involving collaborative activities. However, there is limited evidence informing learning design on the potential effects of collaborative learning spaces. In particular, there is a lack of studies generating evidence derived from temporal analyses of the influence of learning spaces on the collaborative learning process. The temporal analysis perspective has been shown to be essential in the analysis of collaboration processes, as it reveals the relationships between students’ actions. The aim of this study is to explore the potential of a temporal perspective to broaden understanding of the effects of table shape on collaboration when different group sizes and genders are considered. On-task actions such as explanation, discussion, non-verbal interaction, and interaction with physical artefacts were observed while students were engaged in engineering design tasks. Results suggest that table shape influences student behaviour when taking into account different group sizes and different genders.
Face Recognition on a Smart Image Sensor Using Local Gradients
Authors: Valenzuela Wladimir , Soto Javier E. , Zarkesh-Ha Payman , Figueroa Miguel
Published: April 2021

In this paper, we present the architecture of a smart imaging sensor (SIS) for face recognition, based on a custom-design smart pixel capable of computing local spatial gradients in the analog domain, and a digital coprocessor that performs image classification. The SIS uses spatial gradients to compute a lightweight version of local binary patterns (LBP), which we term ringed LBP (RLBP). Our face recognition method, which is based on Ahonen’s algorithm, operates in three stages: (1) it extracts local image features using RLBP, (2) it computes a feature vector using RLBP histograms, (3) it projects the vector onto a subspace that maximizes class separation and classifies the image using a nearest neighbor criterion. We designed the smart pixel using the TSMC 0.35 μm mixed-signal CMOS process, and evaluated its performance using postlayout parasitic extraction. We also designed and implemented the digital coprocessor on a Xilinx XC7Z020 field-programmable gate array. The smart pixel achieves a fill factor of 34% on the 0.35 μm process and 76% on a 0.18 μm process with 32 μm × 32 μm pixels. The pixel array operates at up to 556 frames per second. The digital coprocessor achieves 96.5% classification accuracy on a database of infrared face images, can classify a 150×80-pixel image in 94 μs, and consumes 71 mW of power.
Obituary for Prof. Dr. Alexander Gaskov
Authors: Rumyantseva Marina N. , Vasiliev Roman B.
Published: April 2021

Professor Alexander Gaskov, our dear colleague, friend and teacher, passed away on January 18, 2021 from COVID-19 [...]
Improved Light Field Compression Efficiency through BM3D-Based Denoising Using Inter-View Correlation
Authors: Jin You-Na , Rhee Chae-Eun
Published: April 2021

Multi-view or light field images have recently gained much attraction from academic and commercial fields to create breakthroughs that go beyond simple video-watching experiences. Immersive virtual reality is an important example. High image quality is essential in systems with a near-eye display device. The compression efficiency is also critical because a large amount of multi-view data needs to be stored and transferred. However, noise can be easily generated during image capturing, and these noisy images severely deteriorate both the quality of experience and the compression efficiency. Therefore, denoising is a prerequisite to produce multi-view-based image contents. In this paper, the structural characteristics of linear multi-view images are fully utilized to increase the denoising speed and performance as well as to improve the compression efficiency. Assuming the sequential processes of denoising and compression, multi-view geometry-based denoising is performed keeping the temporal correlation among views. Experimental results show the proposed scheme significantly improves the compression efficiency of denoised views up to 76.05%, maintaining good denoising quality compared to the popular conventional denoise algorithms.
A Novel Method of Fault Detection and Identification in a Tightly Coupled, INS/GNSS-Integrated System
Authors: Zhang Fan , Wang Ye , Gao Yanbin
Published: April 2021

Fault detection and identification are vital for guaranteeing the precision and reliability of tightly coupled inertial navigation system (INS)/global navigation satellite system (GNSS)-integrated navigation systems. A variance shift outlier model (VSOM) was employed to detect faults in the raw pseudo-range data in this paper. The measurements were partially excluded or included in the estimation process depending on the size of the associated shift in the variance. As an objective measure, likelihood ratio and score test statistics were used to determine whether the measurements inflated variance and were deemed to be faulty. The VSOM is appealing because the down-weighting of faulty measurements with the proper weighting factors in the analysis automatically becomes part of the estimation procedure instead of deletion. A parametric bootstrap procedure for significance assessment and multiple testing to identify faults in the VSOM is proposed. The results show that VSOM was validated through field tests, and it works well when single or multiple faults exist in GNSS measurements.
An Improved Sensing Method of a Robotic Ultrasound System for Real-Time Force and Angle Calibration
Authors: Wang Kuan-Ju , Chen Chieh-Hsiao , Chen Jia-Jin (Jason) , Ciou Wei-Siang , Xu Cheng-Bin , Du Yi-Chun
Published: April 2021

An ultrasonic examination is a clinically universal and safe examination method, and with the development of telemedicine and precision medicine, the robotic ultrasound system (RUS) integrated with a robotic arm and ultrasound imaging system receives increasing attention. As the RUS requires precision and reproducibility, it is important to monitor the real-time calibration of the RUS during examination, especially the angle of the probe for image detection and its force on the surface. Additionally, to speed up the integration of the RUS and the current medical ultrasound system (US), the current RUSs mostly use a self-designed fixture to connect the probe to the arm. If the fixture has inconsistencies, it may cause an operating error. In order to improve its resilience, this study proposed an improved sensing method for real-time force and angle calibration. Based on multichannel pressure sensors, an inertial measurement unit (IMU), and a novel sensing structure, the ultrasonic probe and robotic arm could be simply and rapidly combined, which rendered real-time force and angle calibration at a low cost. The experimental results show that the average success rate of the downforce position identification achieved was 88.2%. The phantom experiment indicated that the method could assist the RUS in the real-time calibration of both force and angle during an examination.
An Incentive Based Dynamic Ride-Sharing System for Smart Cities
Authors: Bakibillah Abu Saleh Md , Paw Yi Feng , Kamal Md Abdus Samad , Susilawati Susilawati , Tan Chee Pin
Published: April 2021

Connected and automated vehicle (CAV) technology, along with advanced traffic control systems, cannot ensure congestion-free traffic when the number of vehicles exceeds the road capacity. To address this problem, in this paper, we propose a dynamic ride-sharing system based on incentives (for both passengers and drivers) that incorporates travelers of similar routes and time schedules on short notice. The objective is to reduce the number of private vehicles on urban roads by utilizing the available seats properly. We develop a mobile-cloud architecture-based system that enables real-time ride-sharing. The effectiveness of the proposed system is evaluated through microscopic traffic simulation using Simulation of Urban Mobility (SUMO) considering the traffic flow behavior of a real smart city. Moreover, we develop a lab-scale experimental prototype in the form of Internet of Things (IoT) network. The simulation results show that the proposed system reduces fuel consumption, CO2 and CO emissions, and average waiting time of vehicles significantly, while increasing the vehicle’s average speed. Remarkably, it is found that only 2–10% ride-sharing can improve the overall traffic performance.
Evaluating the Relationship between Park Features and Ecotherapeutic Environment: A Comparative Study of Two Parks in Istanbul, Beylikdüzü
Authors: Kara Didem , Oruç Gülden Demet
Published: April 2021

The impacts of problems related to dense, unplanned, and irregular urbanization on the natural environment, urban areas, and humankind have been discussed in many disciplines for decades. Because of the circular relationship between humans and their environment, human health and psychology have become both agents and patients in interactions with nature. The field of ecopsychology investigates within this reciprocal context the relationship between human psychology and ecological issues and the roles of human psychology and society in environmental problems based on deteriorated nature–human relationships in urbanized areas. This approach has given rise to ecotherapy, which takes a systemic approach to repairing this disturbed nature–human relationship. This study aims to uncover the relationship between the physical attributes of urban green areas and their potential for providing ecotherapy service to users, first by determining the characteristics of ecotherapeutic urban space and urban green areas given in studies in the ecopsychology and ecotherapy literature, and then by conducting a case study in two urban parks from the Beylikdüzü District of the Istanbul Metropolitan Area. The impacts of these parks’ changing physical characteristics on user experiences are determined through a comparison of their physical attributes and the user experiences related to their ecotherapy services.
Purchasing Eco-Sustainable Products: Interrelationship between Environmental Knowledge, Environmental Concern, Green Attitude, and Perceived Behavior
Authors: Rusyani Erni , Lavuri Rambabu , Gunardi Ardi
Published: April 2021

Due to eco-sustainable marketing practices, customer consciousness has increased the use of eco-sustainable goods in India. This provides new opportunities for businesses and researchers in terms of eco-sustainable behavior; however, the market analysis in India is weak. This study examines the factors that trigger consumers to purchase eco-sustainable products and the interrelationship between environmental knowledge (EK), environmental concern (EC), green attitude (GA), and perceived behavior control (PB) among Indian consumers. The data were collected from 514 respondents, using purposive and snowball sampling. Using IBM SPSS 23.0 software, we employed exploratory factor analysis, a homogeneity test, Pearson’s correlation, and multiple regression for a multicollinearity test for data analysis. The results revealed that EK, EC, and GA are positively related and strongly influence eco-friendly purchasing behavior. Moreover, EK and EC are the strongest determinants of PB for eco-friendly products. This research will help green marketers to develop new green strategies to increase sales volumes and build relationships with target green customers.
The Heterogeneous Public Debt–Growth Relationship: The Role of the Expenditure Multiplier
Authors: Butkus Mindaugas , Cibulskiene Diana , Garsviene Lina , Seputiene Janina
Published: April 2021

Currently countries are facing a new crisis caused by the COVID-19, which leads to the rise of government expenditures and additional borrowing. This situation highlights the importance of examine factors which determine the level of public debt that still sustains economic growth. A growing body of research supports the idea of a non-linear debt–growth relationship and estimates the threshold level above which debt becomes unsustainable and has a negative effect on output. The empirical evidence points out that there is no single sustainable debt threshold level that holds for all countries. This research complements scarce empirical evidence on the heterogeneous debt–growth relationship and provides some insights on the publicly available statistical indicators that might signal a relatively low/high expenditure multiplier and, at the same time, potentially unsustainable/sustainable growth stimulus through the use of borrowed funds. We test the hypothesis that the expenditure multiplier is shaping the impact of public debt on growth. Our empirical examination is based on panel data analysis in the groups of countries with expected relatively high and low expenditure multiplier. Research results show that a statistically significant negative marginal effect of debt on growth starts to manifest at a lower debt-to-GDP ratio when the expenditure multiplier is lower and vice-versa. The study shed some light on the sources of heterogeneity in a debt–growth relationship. We can conclude that countries with a high expenditure multiplier level can borrow more and sustain growth. In contrast, in countries with a lower expenditure multiplier, a relatively low debt level becomes unsustainable for growth.
Response of Different Band Combinations in Gaofen-6 WFV for Estimating of Regional Maize Straw Resources Based on Random Forest Classification
Authors: Mou Huawei , Li Huan , Zhou Yuguang , Dong Renjie
Published: April 2021

Maize straw is a valuable renewable energy source. The rapid and accurate determination of its yield and spatial distribution can promote improved utilization. At present, traditional straw estimation methods primarily rely on statistical analysis that may be inaccurate. In this study, the Gaofen 6 (GF-6) satellite, which combines high resolution and wide field of view (WFV) imaging characteristics, was used as the information source, and the quantity of maize straw resources and spatial distribution characteristics in Qihe County were analyzed. According to the phenological characteristics of the study area, seven classification classes were determined, including maize, buildings, woodlands, wastelands, water, roads, and other crops, to explore the influence of sample separation and test the responsiveness to different land cover types with different waveband combinations. Two supervised classification methods, support vector machine (SVM) and random forest (RF), were used to classify the study area, and the influence of the newly added band of GF-6 WFV on the classification accuracy of the study area was analyzed. Furthermore, combined with field surveys and agricultural census data, a method for estimating the quantity of maize straw and analyzing the spatial distribution based on a single-temporal remote sensing image and random forests was proposed. Finally, the accuracy of the measurement results is evaluated at the county level. The results showed that the RF model made better use of the newly added bands of GF-6 WFV and improved the accuracy of classification, compared with the SVM model; the two red-edge bands improved the accuracy of crop classification and recognition; the purple and yellow bands identified non-vegetation more effectively than vegetation, thus minimizing the “salt-and-pepper noise” of classification results. However, the changes to total classification accuracy were not obvious; the theoretical quantity of maize straw in Qihe County in 2018 was 586.08 kt, which reflects an error of only 2.42% compared to the statistical result. Hence, the RF model based on single-temporal GF-6 WFV can effectively estimate regional maize straw yield and spatial distribution, which lays a theoretical foundation for straw recycling.
Prioritization of the Best Sustainable Supply Chain Risk Management Practices Using a Structural Analysis Based-Approach
Authors: Elmsalmi Manel , Hachicha Wafik , Aljuaid Awad M.
Published: April 2021

Companies attempt to improve the performance of their supply chain (SC) by distinguishing and presenting feasible sustainable development practices (SDP). Considering SDP without focusing on sustainability risks may disturb the company’s future. Very few studies in the extant literature have dealt with the impact of (SDP) on the supply chain risk management (SCRM). In fact, the aim of this paper is to classify and prioritize SDPs according to their priority for better risk management and effective SC performance. The proposed approach comprises two phases. First, 14 SDPs are identified and selected from the literature. Second, MICMAC (Matrice d’impacts croisés multiplication appliquée à un classement) method as a structural analysis method applies to identify and assess sustainable supply chain risk management (SSCRM) practices which reduce risk in the SC. The input data for each phase are based on Delphi technique, which is a process group used to collect the opinions of experts in the field. The aim of the proposed approach is to prioritize SSCRM practices and classify them into influential, non-influential, independent and dependent practices and their mutual relationships. The six key findings SSCRM practices from direct and indirect classification include the following elements: (1) Delayed differentiation, (2) Information sharing with upstream and/or downstream partners, (3) Simplification of product dismantling/anticipation of product end of life, (4) Supplier/subcontractor’s performance assessment, (5) establishing shared supply management and (6) establishment of contracts with transporters.
Talking about Sustainability: How the Media Construct the Public’s Understanding of Sustainable Food in Romania
Authors: Marinescu Valentina , Fox Bianca , Cristea Darie , Roventa-Frumusani Daniela , Marinache Ramona , Branea Silvia
Published: April 2021

Decades of medical research have focused on analysing the effects of sustainable eating on health and well-being; yet, less attention has been devoted to this subject in communication and media studies research. Recently, however, scholarly attention has shifted towards the way sustainable food is covered in the media. Nevertheless, previous studies analyse sustainable food together with other sustainability challenges, such as climate change. In this article, we focus our attention on analysing media reporting of sustainable food. Relying theoretically on the framing analysis approach coupled with Goody’s five-phase analytical framework in building sustainable food-related behaviours (production, distribution, preparation, consumption and disposal) and by applying the rationale of content analysis, this article examines media coverage of sustainable food with a focus on sustainable food production, distribution, preparation, consumption and disposal. Therefore, the article identifies trends and patterns of media coverage of sustainable food in Romania between 2014 and 2017. Interesting results emerge, showing that Romanian journalists reporting on food-related topics do not have a solid understanding of the field and contribute to the spread of inaccurate information often, resulting from insufficient research or inadequate use of sources. As a result of the lack of in-depth knowledge of those involved in writing about food, the media coverage of sustainable food is strictly reduced to reporting on aspects related to the consumption of fresh fruit and vegetables, framed as the only healthy foods, and recommended diets for specific underlying health conditions (such as obesity, diabetes, hypertension and associated diseases).
The Challenge of Communication in Pandemic
Authors: Kim Sangkyun
Published: April 2021

COVID-19, the first cases of which were reported at the beginning of 2020, has significantly impacted the world [...]
Legal Issues Concerning the Impact of Anthropogenic Underwater Noise in the Marine Environment
Authors: Chang Yen-Chiang , Zhang Xu
Published: April 2021

Anthropogenic underwater noise has an adverse effect on the marine environment. Therefore, it is of essential importance to establish the problem consciousness regarding this issue and then regulate it by the application of laws. In order to achieve the aim of protecting the marine environment through solving the problem of anthropogenic underwater noise, this article will comb through the existing domestic legislation and international agreements for potential solutions. At the same time, lessons can be drawn from major developed countries in order to lay down the rules which can in turn improve the law-making procedure in dealing with anthropogenic underwater noise. In brief, restricting underwater noise is indispensable from the joint efforts of the international community. To solve the noise problem, it is deemed necessary to clarify the precautionary principle, make full use of the existing legal framework, and promote targeted law-making more effectively through different channels and mechanisms. Moreover, adopting government supervision as a necessary guarantee can also help to hit the target. Meanwhile, paying close attention to science and technology progress is also vital for solving anthropogenic underwater noise issues.
Geosites and Geotourism in the Local Development of Communities of the Andes Mountains. A Case Study
Authors: Carrión-Mero Paúl , Borja-Bernal César , Herrera-Franco Gricelda , Morante-Carballo Fernando , Jaya-Montalvo María , Maldonado-Zamora Alfonso , Paz-Salas Nataly , Berrezueta Edgar
Published: April 2021

The inventory and assessment of a geosite in a territory provides a sound basis for the protection and use of its geological heritage. This article aims to evaluate the most relevant geosites in the province of Chimborazo (Ecuador), applying the Spanish Inventory of Sites of Geological Interest (IELIG, in Spanish) method, and proposing alternatives for geotourism development in the studied area. The methodological process was based on: (i) the inventory and preliminary selection of geosites; (ii) a semi-quantitative geosite assessment and proposal of travel itineraries for geotourism; and (iii) the application of the strengths, weaknesses, opportunities, and threats (SWOT) matrix to establish geotourism development strategies within a framework of sustainability. The global assessment of scientific, tourist, and academic interests demonstrates that 25% of the 20 evaluated geosites have very high interest and 75% have high interest. The top three geosites with the highest degrees of interest are the Chimborazo Volcano, known as ‘Earth’s Closest Point to the Sun’, the Pallatanga geological fault, and the geosite named Comunidad Cacha. The SWOT analysis reveals that travel itineraries that combine cultural heritage elements and geosites could offer a real alternative for the region’s sustainable development through geotourism.
Mindfulness for Sustainable Internet Use in Chinese Junior Secondary School Students: A Dual-Path Mediation Model
Authors: Wu Jianfen , Li Hui
Published: April 2021

Mindfulness training can reduce Internet addiction and promote sustainable development, but the possible mediators of this impact have not been thoroughly explored. This study explored the mediating roles of self-control and maladaptive cognitions in the association between mindfulness and Internet addiction to fill this gap. Altogether, 771 Chinese adolescents (M = 13.87 years, SD = 0.78 years) were surveyed about their mindfulness, self-control, maladaptive cognitions, and Internet addiction. The confirmed model presented a good model fit and revealed that (i) mindfulness, self-control, maladaptive cognitions, and Internet addiction were significantly correlated; (ii) mindfulness had indirect negative effects on Internet addiction, mediated by self-control; (iii) mindfulness had an indirect negative impact on Internet addiction, mediated by the path of self-control to maladaptive cognitions; and (iv) this dual-path mediation model might apply to male and female adolescents. The results of the present study suggest that both self-control and maladaptive cognitions are key factors in the association between mindfulness and Internet addiction.
Multimetric Index to Evaluate Water Quality in Lagoons: A Biological and Geomorphological Approach
Authors: Hernández-Mira Frank Aangel , Rosas-Acevedo José Luis , Reyes-Umaña Maximino , Violante-González Juan , Sigarreta-Almira José María , Vakhania Nodari
Published: April 2021

In recent years, Multimetric Indices (MMIs) have received a lot of attention thanks to their ability to develop integrative evaluations of water quality, particularly in lagoons. In this article, we propose a new MMI for determining the water quality in lagoons. The proposed index is composed of biotic and abiotic indicators, in particular macroinvertebrates, macrophytes and morphological indicators. The proposed index is based on a geometric representation of a phenomenon associated with an ecological system, the ecosystem elements are mapped as vertices of a network and the relationship between them is represented by the corresponding edges. We classify the status of water bodies, from very low to very high using the ecological quality ratio. We compare our index with different different indices that measure water quality, such as General Biotic Index (JP(G)), Macrophyte Index for River (MIR) and Shannon diversity index (H’) and validate our index with Pearson’s correlation coefficient. A strong correlation with the JP(G) and MIR indices (R2 = 0.8605 and R2=0.7661, respectively) is obtained. Although the proposed index is composed of other indices, the independence of the proposed index with respect to its component indices is proven and the structure of the geometric model associated to the proposed network is studied. A close relationship between the measure called medium articulation and the geometric model associated with the proposed index is highlighted, which allows to determine the missing relationships in the network using structural analysis. The proposed index presents a more comprehensive measure than most indices currently used and has the advantage in the scalability, since other existing indicators can be integrated into our model.
Biophysical Accounting of Forests’ Value under Different Management Regimes: Conservation vs. Exploitation
Authors: Vassallo Paolo , Turcato Claudia , Rigo Ilaria , Scopesi Claudia , Costa Andrea , Barcella Matteo , Dapueto Giulia , Mariotti Mauro , Paoli Chiara
Published: April 2021

Forest ecosystems are important providers of ecosystem functions and services belonging to four categories: supporting, provisioning, regulating and cultural ecosystem services. Forest management, generally focused on timber production, has consequences on the ability of the system to keep providing services. Silviculture, in fact, may affect the ecological structures and processes from which services arise. In particular, the removal of biomass causes a radical change in the stocks and flows of energy characterizing the system. Aiming at the assessment of differences in stored natural capital and ecosystem functions and services provision, three differently managed temperate forests of common beech (Fagus sylvatica) were considered: (1) a forest in semi-natural condition, (2) a forest carefully managed to get timber in a sustainable way and (3) a forest exploited without management. Natural capital and ecosystem functions and services are here accounted in biophysical terms. Specifically, all the resources used up to create the biomass (stock) and maintain the production (flow) of the different components of the forest system were calculated. Both stored emergy and empower decrease with increasing human pressure on the forest, resulting in a loss of natural capital and a diminished ability of the natural system to contribute to human well-being in terms of ecosystem services provision.
A Systematic Review of AR and VR Enhanced Language Learning
Authors: Huang Xinyi , Zou Di , Cheng Gary , Xie Haoran
Published: April 2021

This paper provided a systematic review of previous Augmented Reality (AR) and Virtual Reality (VR) studies on language learning. A total of 88 articles were selected and analyzed from five perspectives: their ways of integrating AR or VR tools in language learning; main users of AR and VR technologies; major research findings; why AR and VR tools are effective in promoting language learning; and the implications. It was found that (1) immersing learners into virtual worlds is the main approach to language learning in AR and VR studies; (2) university students were the main users of AR/VR technologies; (3) the major research findings concerning the benefits of AR and VR included improvement of students’ learning outcomes, enhancement of motivation, and positive perceptions towards using AR and VR; (4) AR and VR tools promoted language learning through providing immersive learning experience, enhancing motivation, creating interaction, and reducing learning anxiety; and (5) implications identified from previous research include the need of providing training for teachers, enlarging sample sizes, and exploring learner factors such as learner engagement and satisfaction.
Knowledge Acquisition and Representation for High-Performance Building Design: A Review for Defining Requirements for Developing a Design Expert System
Authors: Choi Seung Yeoun , Kim Sean Hay
Published: April 2021

New functions and requirements of high performance building (HPB) being added and several regulations and certification conditions being reinforced steadily make it harder for designers to decide HPB designs alone. Although many designers wish to rely on HPB consultants for advice, not all projects can afford consultants. We expect that, in the near future, computer aids such as design expert systems can help designers by providing the role of HPB consultants. The effectiveness and success or failure of the solution offered by the expert system must be affected by the quality, systemic structure, resilience, and applicability of expert knowledge. This study aims to set the problem definition and category required for existing HPB designs, and to find the knowledge acquisition and representation methods that are the most suitable to the design expert system based on the literature review. The HPB design literature from the past 10 years revealed that the greatest features of knowledge acquisition and representation are the increasing proportion of computer-based data analytics using machine learning algorithms, whereas rules, frames, and cognitive maps that are derived from heuristics are conventional representation formalisms of traditional expert systems. Moreover, data analytics are applied to not only literally raw data from observations and measurement, but also discrete processed data as the results of simulations or composite rules in order to derive latent rule, hidden pattern, and trends. Furthermore, there is a clear trend that designers prefer the method that decision support tools propose a solution directly as optimizer does. This is due to the lack of resources and time for designers to execute performance evaluation and analysis of alternatives by themselves, even if they have sufficient experience on the HPB. However, because the risk and responsibility for the final design should be taken by designers solely, they are afraid of convenient black box decision making provided by machines. If the process of using the primary knowledge in which frame to reach the solution and how the solution is derived are transparently open to the designers, the solution made by the design expert system will be able to obtain more trust from designers. This transparent decision support process would comply with the requirement specified in a recent design study that designers prefer flexible design environments that give more creative control and freedom over design options, when compared to an automated optimization approach.
Spanish Adaptation and Validation of the Child Adjustment and Parent Efficacy Scale
Authors: Seijo Dolores , Tomé David , Sanmarco Jessica , Morawska Alina , Fariña Francisca
Published: April 2021

(1) Background: The aim of this study is to obtain an instrument, with robust psychometric properties validated with a Spanish sample, that allows for the evaluation of the emotional and behavioural adjustment of children, as well as the perceived ability of parents to manage their children’s problems. (2) Methods: Data from 2618 Spanish parents of 2–12-year-old children were used to evaluate the psychometric properties of the Child Adjustment and Parent Efficacy Scale. In order to develop the intensity scale, exploratory and confirmatory analyses were carried out, and the reliability, validity, and invariance of the measurement model were estimated. (3) Results: A structure of 25 items grouped into two factors are shown, which allows for the evaluation of emotional and behavioural problems and children’s competencies. The model adjustment indicators were satisfactory. Favourable evidence was obtained for the reliability of the measurement model from two perspectives, internal consistency and composite reliability. The discriminant validity was satisfactory, as was the homogeneity of the measurement model based on child gender. Regarding the self-efficacy scale, confirmatory analysis procedures were also carried out, verifying a good factorial structure. (4) Conclusions: Results support a scale with robust psychometric properties that measure child adjustment and parent self-efficacy. The instrument can help to improve family effectiveness and be useful for schools and teachers to promote the well-being of children. The instrument could also be good to evaluate in special contexts, like custody evaluations in a legal or forensic context.
Old but Not Old Fashioned: Agricultural Landscapes as European Heritage and Basis for Sustainable Multifunctional Farming to Earn a Living
Authors: Slámová Martina , Kruse Alexandra , Belčáková Ingrid , Dreer Johannes
Published: April 2021

Today, farmers are multioptional entrepreneurs, demanding far more skills than only those of agricultural production. The awareness of European agricultural landscape (EAL) values should enable farmers to create new business strategies. Open education repositories (OERs) based on online vocational education and training (VET) are still not widespread. The project FEAL (multifunctional farming for the sustainability of EALs) has brought interactive material online based on results of two questionnaire surveys performed in Germany, Italy, Slovakia, Slovenia, and Spain. A survey of 31 experts confirmed that VET activities are very much needed for farmers. A survey of 28 farmers had different aims and content. Data collected from farmers were used to evaluate basic farm attributes, farmers’ characteristics, and keywords indicating the farms’ activities, multifunctionality and sustainability, and EALs, specifying the presence of nature- and landscape-protected areas. A decision-making schema, applying a collection of terms from literature analysis and the questionnaire’s results, is a support tool to develop a model of a farm that contributes to the preservation of the landscape’s character, strengthening the landscape’s quality, and sustainable business. The model presents the interactions of the farm (its territory and ancestral heritage, control of natural resources, tourism services and cultural events, public goods provision, and quality guarantees); socioeconomic strategies regarding quality, marketing, communication, business operation, and monitoring are proposed.