bluuebunny/crossref_metadata_2025 huggingface dataset:
Urbanization-Driven Changes in Land-Climate Dynamics: A Case Study of Haihe River Basin, China
Authors: Li Zhouyuan , Xu Yanjie , Sun Yingbao , Wu Mengfan , Zhao Bin
Published: August 2020

Urbanization changes the land surface environment, which alters the regional climate system. In this study, we took the Haihe River Basin in China as a case study area, as it is highly populated and experienced rapid urbanization from 2000–2015. We investigated how land use and cover change (LUCC) was driven by urban land development affects land-climate dynamics. From 2000–2015, we collected data from the land use and cover database, the remote sensing database of the Moderate Resolution Imaging Spectroradiometer (MODIS) series, and the meteorological database to process and generate regional datasets for LUCC maps. We organized data by years aligned with the selected indicators of land surface, normalized difference vegetation index (NDVI), albedo, and land surface temperature (LST), as well as of regional climate, cloud water content (CWC), and precipitation (P). The assembled datasets were processed to perform statistical analysis and conduct structural equation modelling (SEM). Based on eco-climatology principles and the biophysical process in the land-climate dynamics, we made assumptions on how the indicators connected to each other. Moreover, we testified and quantified them in SEM. LUCC results found that from 2000–2015 the urban area proportion increased by 214% (2.20–6.91%), while the agricultural land decreased by 7.2% (53.05–49.25%) and the forest increased by 4.3% (10.02–10.45%), respectively. This demonstrated how cropland intensification and afforestation happened in the urbanizing basin. SEM results showed that the forest had both positive and negative effects on the regional hydrological cycle. The agricultural land, grassland, and shrub had indirect effects on the P via different biophysical functions of LST. The overall effects of urbanization on regional precipitation was positive (pathway correlation coefficient = 0.25). The interpretation of how urbanization drives LUCC and alters regional climate were herein discussed in different aspects of socioeconomic development, biophysical processes, and urbanization-related atmospheric effects. We provided suggestions for further possible research on monitoring and assessment, putting forth recommendations to advance sustainability via land planning and management, including agricultural land conservation, paying more attention to the quality growth of forest rather than the merely area expansion, integrating the interdisciplinary approach, and assessing climatic risk for extreme precipitation and urban flooding.
Ultraviolet Camera Measurements of Passive and Explosive (Strombolian) Sulphur Dioxide Emissions at Yasur Volcano, Vanuatu
Authors: Ilanko Tehnuka , Pering Tom D , Wilkes Thomas Charles , Woitischek Julia , D’Aleo Roberto , Aiuppa Alessandro , McGonigle Andrew J S , Edmonds Marie , Garaebiti Esline
Published: August 2020

Here, we present the first ultraviolet (UV) camera measurements of sulphur dioxide (SO2) flux from Yasur volcano, Vanuatu, for the period 6–9 July 2018. These data yield the first direct gas-measurement-derived calculations of explosion gas masses at Yasur. Yasur typically exhibits persistent passive gas release interspersed with frequent Strombolian explosions. We used compact forms of the “PiCam” Raspberry Pi UV camera system powered through solar panels to collect images. Our daily median SO2 fluxes ranged from 4 to 5.1 kg s−1, with a measurement uncertainty of −12.2% to +14.7%, including errors from the gas cell calibration drift, uncertainties in plume direction and distance, and errors from the plume velocity. This work highlights the use of particle image velocimetry (PIV) for plume velocity determination, which was preferred over the typically used cross-correlation and optical flow methods because of the ability to function over a variety of plume conditions. We calculated SO2 masses for Strombolian explosions ranging 8–81 kg (mean of 32 kg), which to our knowledge is the first budget of explosive gas masses from this target. Through the use of a simple statistical measure using the moving minimum, we estimated that passive degassing is the dominant mode of gas emission at Yasur, supplying an average of ~69% of the total gas released. Our work further highlights the utility of UV camera measurements in volcanology, and particularly the benefit of the multiple camera approach in error characterisation. This work also adds to our inventory of gas-based data, which can be used to characterise the spectrum of Strombolian activity across the globe.
IM2ELEVATION: Building Height Estimation from Single-View Aerial Imagery
Authors: Liu Chao-Jung , Krylov Vladimir A. , Kane Paul , Kavanagh Geraldine , Dahyot Rozenn
Published: August 2020

Estimation of the Digital Surface Model (DSM) and building heights from single-view aerial imagery is a challenging inherently ill-posed problem that we address in this paper by resorting to machine learning. We propose an end-to-end trainable convolutional-deconvolutional deep neural network architecture that enables learning mapping from a single aerial imagery to a DSM for analysis of urban scenes. We perform multisensor fusion of aerial optical and aerial light detection and ranging (Lidar) data to prepare the training data for our pipeline. The dataset quality is key to successful estimation performance. Typically, a substantial amount of misregistration artifacts are present due to georeferencing/projection errors, sensor calibration inaccuracies, and scene changes between acquisitions. To overcome these issues, we propose a registration procedure to improve Lidar and optical data alignment that relies on Mutual Information, followed by Hough transform-based validation step to adjust misregistered image patches. We validate our building height estimation model on a high-resolution dataset captured over central Dublin, Ireland: Lidar point cloud of 2015 and optical aerial images from 2017. These data allow us to validate the proposed registration procedure and perform 3D model reconstruction from single-view aerial imagery. We also report state-of-the-art performance of our proposed architecture on several popular DSM estimation datasets.
First Insights on Soil Respiration Prediction across the Growth Stages of Rainfed Barley Based on Simulated MODIS and Sentinel-2 Spectral Indices
Authors: Cicuéndez Víctor , Rodríguez-Rastrero Manuel , Recuero Laura , Huesca Margarita , Schmid Thomas , Inclán Rosa , Litago Javier , Sánchez-Girón Víctor , Palacios-Orueta Alicia
Published: August 2020

Rainfed agriculture occupies the majority of the world’s agricultural surface and is expected to increase in the near future causing serious effects on carbon cycle dynamics in the context of climate change. Carbon cycle across several temporal and spatial scales could be studied through spectral indices because they are related to vegetation structure and functioning and hence with carbon fluxes, among them soil respiration (Rs). The aim of this work was to assess Rs linked to crop phenology of a rainfed barley crop throughout two seasons based on spectral indices calculated from field spectroscopy data. The relationships between Rs, Leaf Area Index (LAI) and spectral indices were assessed by linear regression models with the adjusted coefficient of determination (Radj2). Results showed that most of the spectral indices provided better information than LAI throughout the studied period and that soil moisture and temperature were relevant variables in specific periods. During vegetative stages, indices based on the visible (VIS) region showed the best relationship with Rs. On the other hand, during reproductive stages indices containing the near infrared-shortwave infrared (NIR-SWIR) spectral region and those related to water content showed the highest relationship. The inter-annual variability found in Mediterranean regions was also observed in the estimated ratio of carbon emission to carbon fixation between years. Our results show the potential capability of spectral information to assess soil respiration linked to crop phenology across several temporal and spatial scales. These results can be used as a basis for the utilization of other remote information derived from satellites or airborne sensors to monitor crop carbon balances.
Spatiotemporal Variation of Snow Depth in the Northern Hemisphere from 1992 to 2016
Authors: Xiao Xiongxin , Zhang Tingjun , Zhong Xinyue , Li Xiaodong
Published: August 2020

A comprehensive and hemispheric-scale snow cover and snow depth analysis is a prerequisite for all related processes and interactions investigation on regional and global surface energy and water balance, weather and climate, hydrological processes, and water resources. However, such studies were limited by the lack of data products and/or valid snow retrieval algorithms. The overall objective of this study is to investigate the variation characteristics of snow depth across the Northern Hemisphere from 1992 to 2016. We developed long-term Northern Hemisphere daily snow depth (NHSnow) datasets from passive microwave remote sensing data using the support vector regression (SVR) snow depth retrieval algorithm. NHSnow is evaluated, along with GlobSnow and ERA-Interim/Land, for its accuracy across the Northern Hemisphere against meteorological station snow depth measurements. The results show that NHSnow performs comparably well with a relatively high accuracy for snow depth with a bias of −0.6 cm, mean absolute error of 16 cm, and root mean square error of 20 cm when benchmarked against the station snow depth measurements. The analysis results show that annual average snow depth decreased by 0.06 cm per year from 1992 to 2016. In the three seasons (autumn, winter, and spring), the areas with a significant decreasing trend of seasonal maximum snow depth are larger than those with a significant increasing trend. Additionally, snow cover days decreased at the rate of 0.99 day per year during 1992–2016. This study presents that the variation trends of snow cover days are, in part, not consistent with the variation trends of the annual average snow depth, of which approximately 20% of the snow cover areas show the completely opposite variation trends for these two indexes over the study period. This study provides a new perspective in snow depth variation analysis, and shows that rapid changes in snow depth have been occurring since the beginning of the 21st century, accompanied by dramatic climate warming.
A Feature-Enhanced Anchor-Free Network for UAV Vehicle Detection
Authors: Yang Jianxiu , Xie Xuemei , Shi Guangming , Yang Wenzhe
Published: August 2020

Vehicle detection based on unmanned aerial vehicle (UAV) images is a challenging task. One reason is that the objects are small size, low-resolution, and large scale variations, resulting in weak feature representation. Another reason is the imbalance between positive and negative examples. In this paper, we propose a novel architecture for UAV vehicle detection to solve above problems. In detail, we use anchor-free mechanism to eliminate predefined anchors, which can reduce complicated computation and relieve the imbalance between positive and negative samples. Meanwhile, to enhance the features for vehicles, we design a multi-scale semantic enhancement block (MSEB) and an effective 49-layer backbone which is based on the DetNet59. The proposed network offers appropriate receptive fields that match the small-sized vehicles, and involves precise localization information provided by the contexts with high resolution. The MSEB strengthens discriminative feature representation at various scales, without reducing the spatial resolution of prediction layers. Experiments show that the proposed method achieves the state-of-the-art performance. Particularly, the main part of vehicles, much smaller ones, the accuracy is about 2% higher than other existing methods.
Emotion Assessment Using Feature Fusion and Decision Fusion Classification Based on Physiological Data: Are We There Yet?
Authors: Bota Patrícia , Wang Chen , Fred Ana , Silva Hugo
Published: August 2020

Emotion recognition based on physiological data classification has been a topic of increasingly growing interest for more than a decade. However, there is a lack of systematic analysis in literature regarding the selection of classifiers to use, sensor modalities, features and range of expected accuracy, just to name a few limitations. In this work, we evaluate emotion in terms of low/high arousal and valence classification through Supervised Learning (SL), Decision Fusion (DF) and Feature Fusion (FF) techniques using multimodal physiological data, namely, Electrocardiography (ECG), Electrodermal Activity (EDA), Respiration (RESP), or Blood Volume Pulse (BVP). The main contribution of our work is a systematic study across five public datasets commonly used in the Emotion Recognition (ER) state-of-the-art, namely: (1) Classification performance analysis of ER benchmarking datasets in the arousal/valence space; (2) Summarising the ranges of the classification accuracy reported across the existing literature; (3) Characterising the results for diverse classifiers, sensor modalities and feature set combinations for ER using accuracy and F1-score; (4) Exploration of an extended feature set for each modality; (5) Systematic analysis of multimodal classification in DF and FF approaches. The experimental results showed that FF is the most competitive technique in terms of classification accuracy and computational complexity. We obtain superior or comparable results to those reported in the state-of-the-art for the selected datasets.
Neuromorphic Vision Based Contact-Level Classification in Robotic Grasping Applications
Authors: Huang Xiaoqian , Muthusamy Rajkumar , Hassan Eman , Niu Zhenwei , Seneviratne Lakmal , Gan Dongming , Zweiri Yahya
Published: August 2020

In recent years, robotic sorting is widely used in the industry, which is driven by necessity and opportunity. In this paper, a novel neuromorphic vision-based tactile sensing approach for robotic sorting application is proposed. This approach has low latency and low power consumption when compared to conventional vision-based tactile sensing techniques. Two Machine Learning (ML) methods, namely, Support Vector Machine (SVM) and Dynamic Time Warping-K Nearest Neighbor (DTW-KNN), are developed to classify material hardness, object size, and grasping force. An Event-Based Object Grasping (EBOG) experimental setup is developed to acquire datasets, where 243 experiments are produced to train the proposed classifiers. Based on predictions of the classifiers, objects can be automatically sorted. If the prediction accuracy is below a certain threshold, the gripper re-adjusts and re-grasps until reaching a proper grasp. The proposed ML method achieves good prediction accuracy, which shows the effectiveness and the applicability of the proposed approach. The experimental results show that the developed SVM model outperforms the DTW-KNN model in term of accuracy and efficiency for real time contact-level classification.
Illumination Adaptation in a Multi-Wavelength Opto-Electronic Patch Sensor
Authors: Yan Liangwen , Yu Yue , Hu Sijung , Mulvaney David , Blanos Panagiotis , Alharbi Samah , Hayes Matthew
Published: August 2020

In capturing high-quality photoplethysmographic signals, it is crucial to ensure that appropriate illumination intensities are used. The purpose of the study was to deliver controlled illumination intensities for a multi-wavelength opto-electronic patch sensor that has four separate arrays each consisting of four light-emitting diodes (LEDs), the wavelength of the light generated by each array being different. The study achieved the following: (1) a linear constant current source LED driver incorporating series negative feedback using an integrated operational amplifier circuit; (2) the fitting of a linear regression equation to provide rapid determination of the LEDs driver voltage; and (3) an algorithm for the automatic adjustment of the output voltage to ensure suitable LED illumination. The data from a single centrally-located photo detector, which is capable of capturing all four channels of back-light in a time-multiplexed manner, were used to monitor heart rate and blood oxygen saturation. This paper provides circuitry for driving the LEDs and describes an adaptive algorithm implemented on a microcontroller unit that monitors the quality of the photo detector signals received in order to control each of the individual currents being supplied to the LED arrays. The study demonstrated that the operation of the new circuitry in its ability to adapt LED illumination to the strength of the signal received and the performance of the adaptive system was compared with that of a non-adaptive approach.
Improved FBAM and GO/PO Method for EM Scattering Analyses of Ship Targets in a Marine Environment
Authors: Li Jinxing , Zhang Min , Jiang Wangqiang , Wei Pengbo
Published: August 2020

The combination of the fact-based asymptotic method (FBAM) and the geometrical optics and physical optics (GO/PO) hybrid method is an effective way to analyze the electromagnetic (EM) scattering from electrically large ship targets in a marine environment because it takes the multiple scattering of the ship targets into consideration as well as the coupling scattering field between the targets and the sea surface. However, regarding an electrically large marine scene that contains a large target, the occlusion judgement process for calculating the multiple scattering field and the coupling field makes it inefficient. To solve this problem, this paper proposes a physical mechanism-based improved method to reduce the invalid occlusion judgment between different patches on the composite ship–ocean scene, and this operation enhances the computational efficiency significantly. With the proposed method, radar cross section (RCS) results of different targets and composite ship–ocean scenes were calculated and compared with the original FBAM and GO/PO method. Numerical results showed that the proposed method had higher efficiency compared with the original method with the same good accuracy. In addition, synthetic aperture radar (SAR) images of a composite ship–ocean scene with different radar parameters and sea conditions were simulated with the proposed method for detection purpose. Finally, the proposed method was used to analyze the EM scattering characteristic of a marine environment with multiple ships.
Improving Congestion Control of TCP for Constrained IoT Networks
Authors: Lim Chansook
Published: August 2020

For smooth integration with middleboxes on the Internet, TCP (Transmission Control Protocol) is favorably considered as a transport-layer protocol for IoT (Internet of Things) networks. In constrained networks, TCP tends to perform well with a small window size. For example, the uIP (micro IP) TCP/IP stack sets the TCP window size to one segment by default. In such a case, managing the retransmission timer is a primary approach to congestion control. In this paper, we examine the congestion control mechanism of TCP in the uIP stack using grid topology networks. In the preliminary test using the Cooja network simulator, the results show that the original uIP TCP causes lots of retransmissions when a radio duty cycling mechanism such as ContikiMAC is used. One main reason is that, once retransmission is deemed to be necessary, the original uIP TCP sets the retransmission timer based on the fixed RTO (retransmission timeout) before performing a retransmission. Since ContikiMAC may cause large RTT (round-trip time) variations due to the hidden terminal problem, the retransmission timer based on the fixed RTO value may cause lots of retransmissions. To address the problem, we propose a new scheme for managing the retransmission timer which adopts the notion of weak RTT estimation of CoCoA, exponential backoffs with variable limits, and dithering. Simulation results show that our proposed scheme reduces retransmissions while enhancing throughput and fairness when an RDC (radio duty cycling) mechanism is used.
Reliability of the Polar Vantage M Sports Watch when Measuring Heart Rate at Different Treadmill Exercise Intensities
Authors: Climstein Mike , Alder Jessica L. , Brooker Alyce M. , Cartwright Elissa J. , Kemp-Smith Kevin , Simas Vini , Furness James
Published: August 2020

Background: Usage of wrist-worn activity monitors has rapidly increased in recent years, and these devices are being used by both fitness enthusiasts and in clinical populations. We, therefore, assessed the test–retest reliability of the Polar Vantage M (PVM) watch when measuring heart rate (HR) during various treadmill exercise intensities. Methods: HR was measured every 30 s (simultaneous electrocardiography (ECG) and PVM). Test–retest reliability was determined using an intraclass correlation coefficient (ICC) with 95% confidence intervals (CIs). Standard error of measurement (SEM) and smallest real difference (SRD) were used to determine measurement variability. Results: A total of 29 participants completed the trials. ICC values for PVM during stages 1, 2 and 5 demonstrated good to excellent test–retest reliability (0.78, 0.78 and 0.92; 95% CI (0.54–0.90, 0.54–0.9, 0.79–0.97)). For PVM during stages 0 (rest), 3 and 4, the ICC values indicated poor to good reliability (0.42, 0.68 and 0.58; 95% CI (−0.27–0.73, 0.32–0.85, 0.14–0.80)). Conclusion: This study identified that the test–retest reliability of the PVM was comparable at low and high exercise intensities; however, it revealed a poor to good test–retest reliability at moderate intensities. The PVM should not be used in a clinical setting where monitoring of an accurate HR is crucial to the patients’ safety.
Using Visualization to Build Transparency in a Healthcare Blockchain Application
Authors: Peral Jesús , Gallego Eduardo , Gil David , Tanniru Mohan , Khambekar Prashant
Published: August 2020

With patients demanding services to control their own health conditions, hospitals are looking to build agility in delivering care by extending their reach into patient and partner ecosystems and sharing relevant patient data to support care continuity. However, sharing patient data with several external stakeholders outside a hospital network calls for the development of a digital platform that is trusted by both hospitals and stakeholders, given that there is often no single entity supporting such coordination. In this paper, we propose a methodology that uses a blockchain architecture to address the technical challenge of linking disparate systems used by multiple stakeholders and the social challenge of engendering trust by using visualization to bring about transparency in the way in which data are shared. We illustrate this methodology using a pilot implementation. The paper concludes with a discussion and directions for future research and makes some concluding comments.
Fuzzy Bi-Objective Closed-Loop Supply Chain Network Design Problem with Multiple Recovery Options
Authors: Zhou Jian , Xia Wenying , Wang Ke , Li Hui , Zhang Qianyu
Published: August 2020

A network design of a closed-loop supply chain (CLSC) with multiple recovery modes under fuzzy environments is studied in this article, in which all the cost coefficients (e.g., for facility establishment, transportation, manufacturing and recovery), customer demands, delivery time, recovery rates and some other factors that cannot be precisely estimated while designing are modeled as triangular fuzzy numbers. To handle these uncertain factors and achieve a compromise between the two conflicting objectives of maximizing company profit and improving customer satisfaction, a fuzzy bi-objective programming model and a corresponding two-stage fuzzy interactive solution method are presented. Applying the fuzzy expected value operator and fuzzy ranking method, the fuzzy model is transformed into a deterministic counterpart. Subsequently, Pareto optimal solutions are determined by employing the fuzzy interactive solution method to deal with the conflicting objectives. Numerical experiments address the efficiency of the proposed model and its solution approach. Furthermore, by comparing these results with the CLSC network design in deterministic environments, the benefits of modeling the CLSC network design problem with fuzzy information are highlighted.
Design Principles of Wiki System for Knowledge Transfer and Sharing in Organizational Education and Training
Authors: Hung Wei-Hsi , Wang Wen-Hsin
Published: August 2020

Due to rapid technological advancements, firms are paying more attention to the importance of knowledge creation and sharing. Effective knowledge management can be utilized to enhance employee performance, as well as an organization’s competitiveness. Staff training is crucial to the internal knowledge transfer within an organization. Through education and training, an organization can transfer its internal knowledge to its employees. Furthermore, the use of information systems to assist in training and management has been widely adopted by organizations. This study, through action research, attempted to understand how organizations can build a Wiki system to assist in the training of new staff. When employees can obtain work knowledge from more sources, it is easier for the knowledge to be shared and transferred during training. The results show that in the process of implementing Wiki system, providing support for Wiki software design, management skill, and a knowledge sharing environment can enable employees to create and exchange knowledge. The organization itself can rapidly accumulate knowledge capital and enhance the quality of staff through such system in order to enhance its competitiveness.
Landscape Conflicts—A Theoretical Approach Based on the Three Worlds Theory of Karl Popper and the Conflict Theory of Ralf Dahrendorf, Illustrated by the Example of the Energy System Transformation in Germany
Authors: Kühne Olaf
Published: August 2020

On the basis of Karl Popper’s Three Worlds Theory, a theoretical approach to landscape can be derived, which includes the physical foundations of landscape (Landscape 1), the individual construction and emotions drawn from and placed upon landscape (Landscape 2), and social conventions regarding landscape (Landscape 3). These three landscape dimensions are connected via Landscape 2, which also provides an approach for the systematic investigation of the relations between the dimensions. Ralf Dahrendorf’s conflict theory in turn serves as a theoretical framework for when the different connections develop in a conflictual way and how these can be regulated. Dahrendorf sees a principled productivity of conflicts, providing they are settled fairly. On the basis of the conditions he has developed for just such a conflict settlement, the implementation of the energy system transformation is examined against the background of its consequences for the landscape, with the result that essential conditions for an orderly settlement of conflicts are not fulfilled, thereby contributing to the polarization of society.
Sustainable Risk Management of Rural Road Networks Exposed to Natural Hazards: Application to Volcanic Lahars in Chile
Authors: Chamorro Alondra , Echaveguren Tomás , Allen Eduardo , Contreras Marta , Dagá Joaquín , de Solminihac Hernan , Lara Luis E.
Published: August 2020

Natural hazards may temporarily or permanently interrupt the normal operation of rural road networks. The potential social, economic, environmental and physical impacts of natural events on rural road infrastructures empirically evidence the need to incorporate a sustainable risk approach to manage rural road networks exposed to natural hazards. Available risk management systems are applied to major networks emphasizing the physical risk of road infrastructure in terms of expected economic losses and travel time delays, without considering a systemic approach and other dimensions of risk, such as social vulnerability and the consequent socio-economic effects. The study proposes a sustainable risk management framework for rural roads that accounts for the social vulnerability of rural population, the physical vulnerability of rural roads and the environmental context in terms of natural hazards. The proposed framework is applicable to rural road networks exposed to major natural events that permanently or temporarily disrupt accessibility and mobility in the system. A case study is selected from a developing country, due to the socio-economic condition of the rural population and high vulnerability in the context of natural events. The proposed risk management framework is scaled at the network level rather than an element based analysis, or project level approach, considering the interdependencies between road links, the variability of road infrastructure types in the rural context, and the impacts on network accessibility and mobility due to natural events. The proposed framework is applied to a rural road network exposed to volcanic hazard, specifically lahar flows that are usually the most recurrent and disruptive process in terms of road infrastructure. Outcomes demonstrate that rural population present high social vulnerability levels, resulting in a slower recovery when exposed to the effects of infrastructure disruptions. Therefore, considering social vulnerability under a sustainable risk management approach depicts the sustainable role of rural road networks, which commonly are managed only under a physical vulnerability perspective. The proposed methodology will allow road agencies and municipalities to design sustainable mitigation and recovery strategies by incorporating dimensions such as social vulnerability, probability of failure of road links and their impacts on road accessibility and mobility due to natural hazards.
Is Awareness on Plastic Pollution Being Raised in Schools? Understanding Perceptions of Primary and Secondary School Educators
Authors: Dalu Mwazvita T. B. , Cuthbert Ross N. , Muhali Hulisani , Chari Lenin D. , Manyani Amanda , Masunungure Current , Dalu Tatenda
Published: August 2020

Plastic pollution is a major global issue and its impacts on ecosystems and socioeconomic sectors lack comprehensive understanding. The integration of plastics issues into the educational system of both primary and secondary schools has often been overlooked, especially in Africa, presenting a major challenge to environmental awareness. Owing to the importance of early age awareness, this study aims to investigate whether plastic pollution issues are being integrated into South African primary and secondary education school curriculums. Using face-to-face interviews with senior educators, we address this research problem by investigating (i) the extent to which teachers cover components of plastic pollution, and (ii) educator understandings of plastic pollution within terrestrial and aquatic environments. The results indicate that plastic pollution has been integrated into the school curriculum in technology, natural science, geography, life science, life skills and life orientation subjects. However, there was a lack of integration of management practices for plastics littering, especially in secondary schools, and understanding of dangers among different habitat types. This highlights the need for better educational awareness on the plastic pollution problem at both primary and secondary school level, with increased environmental programs needed to educate schools on management practices and impacts.
Localizing Sustainable Development Goal 6: An Assessment of Equitable Access to Sanitation in a Brazilian Metropolitan Region
Authors: Carvalho Rodrigo Coelho de , Nahas Maria Inês Pedrosa , Heller Léo
Published: August 2020

In order for the goals and targets of the 2030 Agenda to be achieved, it is essential to “localize” the Sustainable Development Goals (SDGs), since it is only at the local level that it is possible to move towards their effective implementation. This article seeks to contribute to the development of evaluation and monitoring strategies for target 6.2 at the local level, adapting the official SDG indicator 6.2.1a and the international criteria established by the Joint Monitoring Programme for Water Supply, Sanitation and Hygiene (coordinated by the World Health Organization (WHO) and the United Nations Children’s Fund (UNICEF)) at the municipal scale. Using the Belo Horizonte Metropolitan Region (RMBH) as a case study, a series of methodological procedures is proposed to assess and monitor equitable access to sanitation services. Inequalities in access to services between different population subgroups and between the municipalities that make up the RMBH are explored in different ways, including the evaluation of intersecting forms of inequality, the mapping of a synthetic index of inequality based on multiple criteria and the projection of the time needed to achieve universal access to services according to international criteria. The procedures applied demonstrated the existence of significant inequalities among the municipalities and population subgroups of the RMBH, which are not evident in the analysis of the aggregated data by municipality.
A Hybrid Multi-Criteria Methodology for Solving the Sustainable Dispatch Problem
Authors: Martins Andréa Camila dos Santos , Balbo Antonio Roberto , Jones Dylan , Nepomuceno Leonardo , Soler Edilaine Martins , Baptista Edméa Cássia
Published: August 2020

Wind energy is becoming an increasingly substantial component of many nations’ energy portfolios. The intermittent nature of wind energy is traded off in a multi-objective sense against its environmental benefits when compared to conventional thermal energy sources. This gives rise to the multi-criteria sustainable dispatch problem considered in this paper. A relevant multi-objective model is formulated considering both environmental and economic criteria as well as ensuring adequate production levels. The techniques of weighted goal programming (WGP) and the progressive bounded constraint method (PBC) are combined in a novel manner in order to overcome computational challenges associated with the sinusoidal nature of the model. This allows the generation of a representative set of Pareto efficient solutions. The proposed methodology is demonstrated on a test set of relevant examples, and conclusions are drawn from both methodological and application perspectives. The results provide a quantification of the economic and environmental benefits of added wind power to a solely thermal system. However, a trade-off between the levels of economic versus environmental benefits gained is also demonstrated.
Resources Confirmation for Tourism Destinations Marketing Efforts Using PLS-MGA: The Moderating Impact of Semirural and Rural Tourism Destination
Authors: Chin Chee Hua , Lo May Chiun , Razak Zaidi bin , Pasbakhsh Pooria , Mohamad Abang Azlan
Published: August 2020

This study presents a framework to empirically validate the relationship between the tangible and intangible measures on tourism destination marketing efforts. Uniquely, a case study was developed involving two different nature of tourism destinations (semirural and rural) and is incorporated into the framework to assess its moderating effect on the relationships among the predictors and destination marketing efforts. Two hundred and ninety-three usable responses were collected using a questionnaire survey. Partial least squares structural equation modelling was utilized to perform latent variable and multi-group analyses (MGA). The findings revealed that destination appeal was found to be the biggest concern among tourists visiting semirural and rural tourism destinations in Sarawak. For intangible components, both service quality and destination image were found to be significantly related to destination marketing efforts at a semirural tourism destination. Interestingly, for MGA results, it was worthwhile to learn that the relationship between service quality and destination marketing efforts happened to have a stronger impact on semirural than rural tourism destination. Hence, the proposed framework and research findings from this case study have provided significant insights that help various tourism stakeholders to better strategize and position semirural and rural tourism, particularly in the scenario of Sarawak, Malaysia. Future studies can examine this framework and test at other tourism destinations in Malaysia or in some other countries.
Analysis of China’s Importance in “Belt and Road Initiative” Trade Based on a Gravity Model
Authors: Li Enkang , Lu Mengqiu , Chen Yu
Published: August 2020

This study used a gravity model to analyze the importance of China within the “Belt and Road Initiative” (BRI) trade pattern based on different regression methods, including pooled ordinary least squares (POLS), fixed effects (FE), and the Heckman two-step calculation. The results show that from 2000 to 2018, China’s position in the BRI trade pattern constantly rose in both exports and imports. After removing zero trade flow, POLS and FE analyses showed GDP and a common language had more influence on national exports than population or common religion. The Heckman two-step results with zero trade flows are similar to the other regression results, showing that both a country’s economic aggregate of a country and a common language between two countries were important during trade exchanges. China is one of Eurasia’s most attractive trading partners; while China provides more goods for BRI countries to export, it also provides a huge market for other BRI countries’ goods while promoting their economic development. Thus, China plays a very important role in the BRI trade pattern. Its huge export/import growth potential is a key economic foundation for further promoting Eurasia’s economic and trade integration.
International Trade and Sustainability: Bibliometric and Cluster Analysis
Authors: Jiménez-Almazán Manuel , Uribe-Toril Juan , Ruiz-Real José Luis
Published: August 2020

This article studies the scientific research literature that focuses on the terms related to international trade and sustainability. For this, a bibliometric analysis using the Web of Science database and a cluster analysis on the results obtained carried out. With regard to the results, it can be pointed out that, despite being closely linked, the terms have opposing characteristics and are included in a wide variety of research trends such as those related to agriculture, industry or carbon footprint. This article is of special importance for researchers who want to have a holistic view of international trade and sustainability by identifying its main indicators in the scientific literature.
Perspectives of Circular Economy in Romanian Space
Authors: Vermeșan Horațiu , Mangău Alexandrina , Tiuc Ancuța-Elena
Published: August 2020

The circular economy (CE) is a popular concept in the European Union (EU) space, which has been the subject of numerous research and substantiation activities. In the last years, there has been a growing interest in Romania regarding the characteristics of this new economic model and the principles on which it works. Referring to Romanian specialized literature currently available regarding the submitted topic, we consider that the theoretical part is insufficiently structured. In addition, by pointing out the applicability of the circular economy in Romanian space, we consider this to be represented mainly by the fragility of its effective and practical implementation. The examples of Romanian successes in the field of circular economy are limited, a fact that can be explained—from our perspective—through the aspect that in other EU countries, the process of development of CE has some precedents, a stronger background and a ”self-constructed” history in the topic. There is undoubtedly a necessity for adopting this new economic model, considering that, for the most part, Romanian economy is still dependent on the linear economic system. Starting from these arguments, the proposed article uses a thematic debate of the notion of circular economy, presenting, at the beginning, an incursion into the predominantly European variety of theoretical approaches. The selection of definitions and conceptualization is continued with an analysis of the stage of implementation of CE in Romania. The purpose of this approach is to investigate a niche identified in the Romanian space, not covered in the specialized scientific research and to expose the specificity of the process of transition of Romania to a circular economy, of the barriers encountered—namely, the problem related to the attitude and mentality regarding this new concept. We also point out that the intention of the study is to integrate a ”different” contemporary and very current economic concept into a real economy, and at the same time, to increase the visibility of its application at the level of a member country of the EU. The challenges encountered in the context of the increasingly present tendency in Romania of assimilating and complying with the precepts of the circular economy are also detailed, proposing, at the end of the study suggestions for improving the gaps identified at this level. The most realistic implementation of the circular model in Romania represents a qualitative plus for the human-society factor, as well as for the environment. In conclusion, we note that, despite the evolution of the number of theoretical approaches and concerns, the field of circular economy and the perspectives it proposes, continues to offer a favorable ground for further research.
Student Engagement for Sustainability of Chinese International Education: The Case of International Undergraduate Students in China
Authors: Tian Mei , Lu Genshu , Yin Hongbiao , Li Lijie
Published: August 2020

Student engagement has been attracting attention in the discussion of higher education (HE) quality. Despite the rapid increase of international students in China, little understanding has been gained for quality management on these students’ engagement in learning. This paper focuses on international undergraduate students in Chinese higher education institutions, exploring the nature and characteristics of their academic engagement and the environmental factors influencing the engagement. The discussion was based on a synthesis of the findings of two studies, i.e., an exploratory qualitative study following a small group of international students at a research university and a large-scale survey involving 1428 international students at 34 Chinese universities. The analyses revealed less than satisfactory levels of international students’ engagement, with a high proportion of the participants being passively or ineffectively involved in learning. The qualitative findings highlighted pedagogical and attitudinal factors that affected international students’ engagement. The survey results indicated six environmental factors, categorized into three groups, having significant effects on the respondents’ engagement. Although located in China, the analyses bear implications for practitioners striving for the sustainable development of international education in a broader range of contexts.
The Role of Agrotechnical Factors in Shaping the Protein Yield of Maize (Zea mays L.)
Authors: Szulc Piotr , Ambroży-Deręgowska Katarzyna , Mejza Iwona , Kobus-Cisowska Joanna , Ligaj Marta
Published: August 2020

The subject of the work was the evaluation of maize protein yield conditioned by various agrotechnical factors. The test results are derived from two different field experiments covering a total of seven years of observation. Protein yield was significantly dependent on changing weather conditions in the growing seasons. Protein yield was significantly lower in the dry and hot years. The sum of precipitation for the month of May was positively correlated with maize protein yield. However, there was no correlation between the average air temperature and the amount of protein yield. The sum of atmospheric precipitation for the entire growing season (IV–X) shaped maize protein yield in over 96%. A non-linear relationship of the 2nd degree was determined between these traits. Sowing maize into the soil cultivated traditionally (autumn tillage), “stay-green” type cultivars and row fertilization positively influenced maize protein yield. Initial fertilization (regardless of depth) with two-component NP fertilizer, in relation to broadcast fertilization, significantly increased maize protein yield from 11.4% to 18%, respectively. The type of nitrogen fertilizer did not differentiate the value of this trait. Pre-sowing nitrogen application was more effective compared to the top dressing, and significantly increased protein yield. Row fertilization with two-component NP fertilizer clearly affected the content protein in grain. The interdependence of genetic and agronomic progress is an important factor shaping the potential of maize protein yield and cannot be attributed to either breeding (cultivar) or agronomy.
Potential Impact of Meat Replacers on Nutrient Quality and Greenhouse Gas Emissions of Diets in Four European Countries
Authors: Mertens Elly , Biesbroek Sander , Dofková Marcela , Mistura Lorenza , D’Addezio Laura , Turrini Aida , Dubuisson Carine , Havard Sabrina , Trolle Ellen , Geleijnse Johanna M. , van ’t Veer Pieter
Published: August 2020

Meat replacers could play a role in achieving more plant-based diets, but their current consumption is limited. The present modelling study aimed to explore the nutritional and greenhouse gas emissions impacts of meat replacers. Using dietary surveys from Denmark, Czech Republic, Italy and France (~6500 adults), we composed alternative diets in which all the meat in the observed diet (in grams) was substituted by similar use meat replacers (with and without fortification). Starting from the observed diets and meat-replacement diets, diets with improved adherence to food-based dietary guidelines (FBDGs) were modelled using Data Envelopment Analysis. These improved diets were then further optimised for dietary preferences (MaxP, diet similarity index), nutrient quality (MaxH, Nutrient Rich Diet score, NRD15.3) or diet-related greenhouse gas emissions (GHGE) (MaxS, CO2 equivalents). In all optimised modelled diets, the total amount of meat was lower than in the observed diets, i.e., 30% lower in the MaxP, 50% lower in the MaxH, and 75% lower in the MaxS diets. In the MaxP diet, NRD15.3 was ~6% higher, GHGE was ~9% lower, and ~83% of food intake remained similar. In the MaxH diet, NRD15.3 was ~17% higher, GHGE was ~15% lower, and ~66% of food intake remained similar. In the MaxS diet, NRD15.3 was ~9% higher, GHGE was ~33% lower, and ~65% of food intake remained similar. When using fortified meat replacers, for all modelled diets, the diet similarity was on average 2% lower and the GHGE reduction was on average 3% higher as compared with the same scenarios without fortification. This analysis showed that meat replacers, provided their preference is similar to meat, can provide benefits for GHGE, without necessarily compromising nutrient quality.