bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep Learning Classification of Cheatgrass Invasion in the Western United States Using Biophysical and Remote Sensing Data
Authors: Larson Kyle B. , Tuor Aaron R.
Published: March 2021

Cheatgrass (Bromus tectorum) invasion is driving an emerging cycle of increased fire frequency and irreversible loss of wildlife habitat in the western US. Yet, detailed spatial information about its occurrence is still lacking for much of its presumably invaded range. Deep learning (DL) has demonstrated success for remote sensing applications but is less tested on more challenging tasks like identifying biological invasions using sub-pixel phenomena. We compare two DL architectures and the more conventional Random Forest and Logistic Regression methods to improve upon a previous effort to map cheatgrass occurrence at >2% canopy cover. High-dimensional sets of biophysical, MODIS, and Landsat-7 ETM+ predictor variables are also compared to evaluate different multi-modal data strategies. All model configurations improved results relative to the case study and accuracy generally improved by combining data from both sensors with biophysical data. Cheatgrass occurrence is mapped at 30 m ground sample distance (GSD) with an estimated 78.1% accuracy, compared to 250-m GSD and 71% map accuracy in the case study. Furthermore, DL is shown to be competitive with well-established machine learning methods in a limited data regime, suggesting it can be an effective tool for mapping biological invasions and more broadly for multi-modal remote sensing applications.
Extensive Evaluation of a Continental-Scale High-Resolution Hydrological Model Using Remote Sensing and Ground-Based Observations
Authors: Zhu Bowen , Xie Xianhong , Lu Chuiyu , Lei Tianjie , Wang Yibing , Jia Kun , Yao Yunjun
Published: March 2021

Extreme hydrologic events are getting more frequent under a changing climate, and a reliable hydrological modeling framework is important to understand their mechanism. However, existing hydrological modeling frameworks are mostly constrained to a relatively coarse resolution, unrealistic input information, and insufficient evaluations, especially for the large domain, and they are, therefore, unable to address and reconstruct many of the water-related issues (e.g., flooding and drought). In this study, a 0.0625-degree (~6 km) resolution variable infiltration capacity (VIC) model developed for China from 1970 to 2016 was extensively evaluated against remote sensing and ground-based observations. A unique feature in this modeling framework is the incorporation of new remotely sensed vegetation and soil parameter dataset. To our knowledge, this constitutes the first application of VIC with such a long-term and fine resolution over a large domain, and more importantly, with a holistic system-evaluation leveraging the best available earth data. The evaluations using in-situ observations of streamflow, evapotranspiration (ET), and soil moisture (SM) indicate a great improvement. The simulations are also consistent with satellite remote sensing products of ET and SM, because the mean differences between the VIC ET and the remote sensing ET range from −2 to 2 mm/day, and the differences for SM of the top thin layer range from −2 to 3 mm. Therefore, this continental-scale hydrological modeling framework is reliable and accurate, which can be used for various applications including extreme hydrological event detections.
AT2ES: Simultaneous Atmospheric Transmittance-Temperature-Emissivity Separation Using Online Upper Midwave Infrared Hyperspectral Images
Authors: Kim Sungho , Shin Jungsub , Kim Sunho
Published: March 2021

This paper presents a novel method for atmospheric transmittance-temperature-emissivity separation (AT2ES) using online midwave infrared hyperspectral images. Conventionally, temperature and emissivity separation (TES) is a well-known problem in the remote sensing domain. However, previous approaches use the atmospheric correction process before TES using MODTRAN in the long wave infrared band. Simultaneous online atmospheric transmittance-temperature-emissivity separation starts with approximation of the radiative transfer equation in the upper midwave infrared band. The highest atmospheric band is used to estimate surface temperature, assuming high emissive materials. The lowest atmospheric band (CO2 absorption band) is used to estimate air temperature. Through onsite hyperspectral data regression, atmospheric transmittance is obtained from the y-intercept, and emissivity is separated using the observed radiance, the separated object temperature, the air temperature, and atmospheric transmittance. The advantage with the proposed method is from being the first attempt at simultaneous AT2ES and online separation without any prior knowledge and pre-processing. Midwave Fourier transform infrared (FTIR)-based outdoor experimental results validate the feasibility of the proposed AT2ES method.
Snow Depth Fusion Based on Machine Learning Methods for the Northern Hemisphere
Authors: Hu Yanxing , Che Tao , Dai Liyun , Xiao Lin
Published: March 2021

In this study, a machine learning algorithm was introduced to fuse gridded snow depth datasets. The input variables of the machine learning method included geolocation (latitude and longitude), topographic data (elevation), gridded snow depth datasets and in situ observations. A total of 29,565 in situ observations were used to train and optimize the machine learning algorithm. A total of five gridded snow depth datasets—Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) snow depth, Global Snow Monitoring for Climate Research (GlobSnow) snow depth, Long time series of daily snow depth over the Northern Hemisphere (NHSD) snow depth, ERA-Interim snow depth and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) snow depth—were used as input variables. The first three snow depth datasets are retrieved from passive microwave brightness temperature or assimilation with in situ observations, while the last two are snow depth datasets obtained from meteorological reanalysis data with a land surface model and data assimilation system. Then, three machine learning methods, i.e., Artificial Neural Networks (ANN), Support Vector Regression (SVR), and Random Forest Regression (RFR), were used to produce a fused snow depth dataset from 2002 to 2004. The RFR model performed best and was thus used to produce a new snow depth product from the fusion of the five snow depth datasets and auxiliary data over the Northern Hemisphere from 2002 to 2011. The fused snow-depth product was verified at five well-known snow observation sites. The R2 of Sodankylä, Old Aspen, and Reynolds Mountains East were 0.88, 0.69, and 0.63, respectively. At the Swamp Angel Study Plot and Weissfluhjoch observation sites, which have an average snow depth exceeding 200 cm, the fused snow depth did not perform well. The spatial patterns of the average snow depth were analyzed seasonally, and the average snow depths of autumn, winter, and spring were 5.7, 25.8, and 21.5 cm, respectively. In the future, random forest regression will be used to produce a long time series of a fused snow depth dataset over the Northern Hemisphere or other specific regions.
Comparative Evaluation of Microwave L-Band VOD and Optical NDVI for Agriculture Drought Detection over Central Europe
Authors: Afshar Mehdi H. , Al-Yaari Amen , Yilmaz M. Tugrul
Published: March 2021

Agricultural droughts impose many economic and social losses on various communities. Most of the effective tools developed for agricultural drought assessment are based on vegetation indices (VIs). The aim of this study is to compare the response of two commonly used VIs to meteorological droughts—Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and Soil Moisture and Ocean Salinity (SMOS) vegetation optical depth (VOD). For this purpose, meteorological droughts are calculated by using a standardized precipitation index over more than 24,000 pixels at 0.25° × 0.25° spatial resolution located in central Europe. Then, to evaluate the capability of VIs in the detection of agricultural droughts, the average values of VIs anomalies during dry and wet periods obtained from meteorological droughts are statistically compared to each other. Additionally, to assess the response time of VIs to meteorological droughts, a time lag of one to six months is applied to the anomaly time series of VIs during their comparison. Results show that over 35% of the considered pixels NDVI, over 22% of VOD, and over 8% of both VIs anomalies have a significant response to drought events, while the significance level of these differences and the response time of VIs vary with different land use and climate conditions.
Modeling and Performance Analysis of Satellite Network Moving Target Defense System with Petri Nets
Authors: Shi Leyi , Du Shanshan , Miao Yifan , Lan Songbai
Published: March 2021

With the development of satellite communication networks and the increase of satellite services, security problems have gradually become some of the most concerning issues. Researchers have made great efforts, including conventional safety methods such as secure transmission, anti-jamming, secure access, and especially the new generation of active defense technology represented by MTD. However, few scholars have theoretically studied the influence of active defense technique on the performance of satellite networks. Formal modeling and performance analysis have not been given sufficient attention. In this paper, we focus on the performance evaluation of satellite network moving target defense system. Firstly, two Stochastic Petri Nets (SPN) models are constructed to analyze the performance of satellite network in traditional and active defense states, respectively. Secondly, the steady-state probability of each marking in SPN models is obtained by using the isomorphism relation between SPN and Markov Chains (MC), and further key performance indicators such as average time delay, throughput, and the utilization of bandwidth are reasoned theoretically. Finally, the proposed two SPN models are simulated based on the PIPE platform. In addition, the effect of parameters on the selected performance indexes is analyzed by varying the values of different parameters. The simulation results prove the correctness of the theoretical reasoning and draw the key factors affecting the performance of satellite network, which can provide an important theoretical basis for the design and performance optimization of the satellite network moving target defense system.
Vertical Structures of Meteorological Elements and Black Carbon at Mt. Tianshan Using an Unmanned Aerial Vehicle System
Authors: Wang Honglei , Liu Ankang , Zhen Zhongxiu , Yin Yan , Li Bin , Li Yuanyuan , Chen Kui , Xu Jiaping
Published: March 2021

As the largest independent east–west-trending mountain in the world, Mt. Tianshan exerts crucial impacts on climate and pollutant distributions in central Asia. Here, the vertical structures of meteorological elements and black carbon (BC) were first derived at Mt. Tianshan using an unmanned aerial vehicle system (UAVS). Vertical changes in meteorological elements can directly affect the structure of the planet boundary layer (PBL). As such, the influences of topography and meteorological elements’ vertical structure on aerosol distributions were explored from observations and model simulations. The mass concentrations of BC changed slightly with the increasing height below 2300 m above sea level (a.s.l.), which significantly increased with the height between 2300–3500 m a.s.l. and contrarily decreased with ascending altitude higher than 3500 m. Topography and mountain–valley winds were found to play important roles in the distributions of aerosols and BC. The prevailing valley winds in the daytime were conducive to pollutant transport from surrounding cities to Mt. Tianshan, where the aerosol number concentration and BC mass concentration increased rapidly, whereas the opposite transport pattern dominated during nighttime.
Unsupervised Adversarial Domain Adaptation with Error-Correcting Boundaries and Feature Adaption Metric for Remote-Sensing Scene Classification
Authors: Ma Chenhui , Sha Dexuan , Mu Xiaodong
Published: March 2021

Unsupervised domain adaptation (UDA) based on adversarial learning for remote-sensing scene classification has become a research hotspot because of the need to alleviating the lack of annotated training data. Existing methods train classifiers according to their ability to distinguish features from source or target domains. However, they suffer from the following two limitations: (1) the classifier is trained on source samples and forms a source-domain-specific boundary, which ignores features from the target domain and (2) semantically meaningful features are merely built from the adversary of a generator and a discriminator, which ignore selecting the domain invariant features. These issues limit the distribution matching performance of source and target domains, since each domain has its distinctive characteristic. To resolve these issues, we propose a framework with error-correcting boundaries and feature adaptation metric. Specifically, we design an error-correcting boundaries mechanism to build target-domain-specific classifier boundaries via multi-classifiers and error-correcting discrepancy loss, which significantly distinguish target samples and reduce their distinguished uncertainty. Then, we employ a feature adaptation metric structure to enhance the adaptation of ambiguous features via shallow layers of the backbone convolutional neural network and alignment loss, which automatically learns domain invariant features. The experimental results on four public datasets outperform other UDA methods of remote-sensing scene classification.
Ground Penetrating Radar Survey of the Floor of the Accademia Gallery (Florence, Italy)
Authors: Miccinesi Lapo , Beni Alessandra , Monchetti Silvia , Betti Michele , Borri Claudio , Pieraccini Massimiliano
Published: March 2021

This paper reports the results of a ground penetrating radar (GPR) survey of the ground-floor of Academia Gallery (Florence, Italy) where the Michelangelo’s David is exhibited to the public. The equipment used was a step-frequency GPR operating in the 100 MHz-1 GHz band, named ORFEUS. The survey covered an area of 13 m × 7.3 m, and the scans were performed along two orthogonal directions. Acquisitions in the same direction were separated by 0.25 m from each other. The GPR was able to confirm the underground structure, as it can be deducted by planimetry and historical documentation. In particular, the radar clearly detected the air-conditioning ducts under the floor and an approximately circular foundation below the basement of the statue.
Step Length Is a Promising Progression Marker in Parkinson’s Disease
Authors: Welzel Julius , Wendtland David , Warmerdam Elke , Romijnders Robbin , Elshehabi Morad , Geritz Johanna , Berg Daniela , Hansen Clint , Maetzler Walter
Published: March 2021

Current research on Parkinson’s disease (PD) is increasingly concerned with the identification of objective and specific markers to make reliable statements about the effect of therapy and disease progression. Parameters from inertial measurement units (IMUs) are objective and accurate, and thus an interesting option to be included in the regular assessment of these patients. In this study, 68 patients with PD (PwP) in Hoehn and Yahr (H&Y) stages 1–4 were assessed with two gait tasks—20 m straight walk and circular walk—using IMUs. In an ANCOVA model, we found a significant and large effect of the H&Y scores on step length in both tasks, and only a minor effect on step time. This study provides evidence that from the two potentially most important gait parameters currently accessible with wearable technology under supervised assessment strategies, step length changes substantially over the course of PD, while step time shows surprisingly little change in the progression of PD. These results show the importance of carefully evaluating quantitative gait parameters to make assumptions about disease progression, and the potential of the granular evaluation of symptoms such as gait deficits when monitoring chronic progressive diseases such as PD.
Distance Measurements in UWB-Radio Localization Systems Corrected with a Feedforward Neural Network Model
Authors: Krapež Peter , Vidmar Matjaž , Munih Marko
Published: March 2021

An ultra-wideband (UWB) localization system is an alternative in a GPS-denied environment. However, a distance measurement with UWB modules using a two-way communication protocol induces an orientation-dependent error. Previous research studied this error by looking at parameters such as the received power and the channel response signal. In this paper, the neural network (NN) method for correcting the orientation-induced distance error without the need to calculate the signal strength, obtain the channel response or know any parameters of the antenna and the UWB modules is presented. The NN method utilizes only the measured distance and the tag orientation, and implements an NN model obtained by machine learning, using measurements at different distances and orientations of the two UWB modules. The verification of the experimental setup with 12 anchors and a tag shows that with the proposed NN method, 5 cm better root mean square error values (RMSEs) are obtained for the measured distance between the anchors and the tag compared to the calibration method that did not include orientation information. With the least-square estimator, 14 cm RMSE in 3D is obtained with the NN model corrected distances, with a 9 cm improvement compared to when raw distances are used. The method produces better results without the need to obtain the UWB module’s diagnostics parameters that are required to calculate the received signal strength or channel response, and in this way maintain the minimum packet size for the ranging protocol.
Compensation for Lateral Misalignment in Litz Wire Based on Multilayer Coil Technology
Authors: Chang Hyungjun , Lim Taejun , Lee Yongshik
Published: March 2021

This study applies a multilayer coil technology that can compensate for a decrease in transfer efficiency due to a lateral misalignment in a practical 100 kHz-band wireless power transfer system and validates its effect on the efficiency of compensation. The effectiveness is investigated using coils fabricated with Litz wires. Three-turn rectangular assistant coils 22.4 × 45.3 mm2 in size were stacked on a five-turn circular primary coil with a diameter of 45.3 mm in a 2 × 1 array. Transfer efficiency between two such coils was measured by producing lateral misalignment, while maintaining the vertical distance between the Tx and Rx coils at 7 mm. The experimental results showed that the transfer efficiency was compensated by approximately 46.1%P maximum in a misalignment state of 30 mm, which corresponded to 67% of the maximum size of the coil, compared to the transfer efficiency of the structure, in which the multilayer coil was not applied. Furthermore, transfer efficiency was compensated by 37.6%P, even in an asymmetric system in which the multilayer structure was applied only to the Tx coil, thereby confirming an excellent multilayer coil technology effect on compensation for lateral misalignment in practical cases.
Concept and Realization of a Novel Test Method Using a Dynamic Test Stand for Detecting Persons by Sensor Systems on Autonomous Agricultural Robotics
Authors: Meltebrink Christian , Ströer Tom , Wegmann Benjamin , Weltzien Cornelia , Ruckelshausen Arno
Published: March 2021

As an essential part for the development of autonomous agricultural robotics, the functional safety of autonomous agricultural machines is largely based on the functionality and robustness of non-contact sensor systems for human protection. This article presents a new step in the development of autonomous agricultural machine with a concept and the realization of a novel test method using a dynamic test stand on an agricultural farm in outdoor areas. With this test method, commercially available sensor systems are tested in a long-term test around the clock for 365 days a year and 24 h a day on a dynamic test stand in continuous outdoor use. A test over a longer period of time is needed to test as much as possible all occurring environmental conditions. This test is determined by the naturally occurring environmental conditions. This fact corresponds to the reality of unpredictable/determinable environmental conditions in the field and makes the test method and test stand so unique. The focus of the developed test methods is on creating own real environment detection areas (REDAs) for each sensor system, which can be used to compare and evaluate the autonomous human detection of the sensor systems for the functional safety of autonomous agricultural robots with a humanoid test target. Sensor manufacturers from industry and the automotive sector provide their sensor systems to have their sensors tested in cooperation with the TÜV.
Analysis of the Influence of Shrinkage Tensile Stress in Potting Material on the Anti-Overload Performance of the Circuit Board
Authors: Sun Lei , Yi Wenjun
Published: March 2021

In this article, the influence of shrinkage tensile stress in potting materials on the anti-overload performance of a circuit board was studied. Firstly, the phenomenon of shrinkage tensile stress in common potting materials was analyzed, and it was found that the commonly used potting adhesives displayed large shrinkage characteristics. Secondly, a small experiment was set up to verify that the shrinkage tensile stress of potting adhesives would lead to printed circuit board (PCB) deformation, and the shrinkage stress was contrary to the acceleration direction of overload. Thirdly, the influence of potting adhesives on the overload resistance of the PCB was analyzed. However, the shrinkage tensile stress in the potting adhesive weakened the anti-overload ability of the circuit board. When there was a small amount of expansion stress in the potting adhesive, the overload resistance of the circuit board could be partially increased. From the analysis, it is indicated that a material with a certain expansion property, elasticity, and dense structure should be selected as the potting adhesive. This article provides a reference for improving the overload resistance of electronic devices.
Collaborative Robotic Assistant Platform for Endonasal Surgery: Preliminary In-Vitro Trials
Authors: Muñoz Victor F. , Garcia-Morales Isabel , Fraile-Marinero Juan Carlos , Perez-Turiel Javier , Muñoz-Garcia Alvaro , Bauzano Enrique , Rivas-Blanco Irene , Sabater-Navarro Jose María , Fuente Eusebio de la
Published: March 2021

Endonasal surgery is a minimally invasive approach for the removal of pituitary tumors (sarcomas). In this type of procedure, the surgeon has to complete the surgical maneuvers for sarcoma resection with extreme precision, as there are many vital structures in this area. Therefore, the use of robots for this type of intervention could increase the success of the intervention by providing accurate movements. Research has focused on the development of teleoperated robots to handle a surgical instrument, including the use of virtual fixtures to delimit the working area. This paper aims to go a step further with a platform that includes a teleoperated robot and an autonomous robot dedicated to secondary tasks. In this way, the aim is to reduce the surgeon’s workload so that he can concentrate on his main task. Thus, the article focuses on the description and implementation of a navigator that coordinates both robots via a force/position control. Finally, both the navigation and control scheme were validated by in-vitro tests.
Examining the Relationship between Social Inefficiency and Financial Performance. Evidence from Wisconsin Dairy Farms
Authors: Skevas Theodoros , Skevas Ioannis , Cabrera Victor E.
Published: March 2021

Although social sustainability is an important component of sustainable agricultural production, little research has been conducted to assess social sustainability performance at the farm level. This study measures farmers’ social sustainability performance using (in)efficiency measures derived from a non-parametric dynamic directional distance function approach. It further examines the relationship between social (in)efficiency and financial performance measured by profitability, which is crucial to understand the financial impact of engaging in socially responsible activities. The empirical application focuses on a sample of Wisconsin dairy farms over the period 2007–2017. Results show that sample farms could have (decreased/)increased their social (in)efficiency by an average of 14%. Social (in)efficiency was found to be (negatively/)positively related to farm profitability, implying that social objectives can be achieved in tandem with economic goals.
Parents’ Perspectives on Remote Learning in the Pandemic Context
Authors: Daniela Linda , Rubene Zanda , Rūdolfa Arta
Published: March 2021

In the spring of 2020, when the entire education system worldwide switched to distance learning, parents became key learning agents, helping students to understand how to continue learning, how to use digital solutions and how to support students in this process. This article summarizes parents’ views on the distance learning process and the challenges they faced. This is part of a larger study carried out within the project “Life with COVID-19: Evaluation of the overcoming coronavirus crisis in Latvia and recommendations for social resilience in the future” (CoLife), which was launched in Latvia in the summer of 2020 and analyzed what digital learning tools schools can use to support students in their learning. Parents’ views on 738 school-age children (313 responses about 1st–4th graders; 362 responses for 5th–9th graders and 63 responses for 10th–12th graders) were obtained, and the main conclusions were that after parents became learning agents, they would have liked more support from educators to understand how to support their children in the learning process. Parents would also have liked schools to be interested in how their children are doing and whether everything necessary is available. Overall, it can be concluded that in this crisis, parents tried to support their children, and in most cases, it was the mothers of the students who provided this support, but it was primarily based on the need to use digital technologies, which means that children whose parents do not use digital technologies may be more exposed to the danger of falling into a risk group with larger educational gaps.
The Effect of Financial Materiality on ESG Performance Assessment
Authors: Madison Nicolas , Schiehll Eduardo
Published: March 2021

The effect of considering the financial materiality of ESG (environmental, social and governance) issues on firms’ ESG performance scores and rankings is investigated using Morgan Stanley Capital International (MSCI) ESG Ratings and the financial Materiality Map® developed by the Sustainability Accounting Standard Board (SASB). Results show that when financial materiality is applied, firms’ ESG performance scores change significantly. Further corroboration is provided by significant changes in firms’ ESG rankings when ESG performance assessment is based on SASB-adjusted ESG performance scores. Environmental pillar issues, and particularly natural resource use, are predominantly responsible for the changes. Overall, the results suggest that financial materiality affects the informative value of ESG scores and rankings, allowing the identification of investment opportunities in firms with high scores on business-critical ESG issues. We argue that consideration of financial materiality can better inform investment decisions based on ESG performance. This study adds to the understanding and assessment of ESG performance and its information content.
Early Childhood and Lockdown: The Challenge of Building a Virtual Mutual Support Network between Children, Families and School for Sustainable Education and Increasing Their Well-Being
Authors: Cano-Hila Ana Belén , Argemí-Baldich Rafel
Published: March 2021

The COVID-19 pandemic is questioning the achievement of main challenges we face as a society, for instance, to ensure a free, equitable, and good quality compulsory education for all children or to reduce social inequality. During the spring lockdown, particularly in Spain, schools were closed for six months and a process of virtualization of teaching was total; that context generated important educational challenges. This paper presents and analyses forms of digital reciprocity and solidarity among pre-primary education children, families, and teachers, by presenting a case study of the parents’ WhatsApp class groups and a collaborative YouTube channel. The procedure developed was netnography and the data analysis followed the model of grounded theory. Both digital spaces created by parents have become a network of mutual support. It has had multiple positive impacts: (i) providing and receiving social support; (ii) generating dynamics of reciprocity and empowerment; and (iii) activating values that generate a sense of community (feeling of belonging, trust, etc.). The case study shows how virtual networks increase the subjective well-being of participants in a difficult context and also invites reflection about the key role of cultural capital of the parents as a key element in the conditions of educability of children, especially in e-learning of pre-primary education.
Estimation of Carbon Dioxide Emissions from a Traditional Nutrient-Rich Cambodian Diet Food Production System Using Life Cycle Assessment
Authors: Hor Rathna , Ly Phanna , Putra Agusta Samodra , Ishizaki Riaru , Ahamed Tofael , Noguchi Ryozo
Published: March 2021

Traditional Cambodian food has higher nutrient balances and is environmentally sustainable compared to conventional diets. However, there is a lack of knowledge and evidence on nutrient intake and the environmental greenness of traditional food at different age distributions. The relationship between nutritional intake and environmental impact can be evaluated using carbon dioxide (CO2) emissions from agricultural production based on life cycle assessment (LCA). The objective of this study was to estimate the CO2 equivalent (eq) emissions from the traditional Cambodian diet using LCA, starting at each agricultural production phase. A one-year food consumption scenario with the traditional diet was established. Five breakfast (BF1–5) and seven lunch and dinner (LD1–7) food sets were consumed at the same rate and compared using LCA. The results showed that BF1 and LD2 had the lowest and highest emissions (0.3 Mt CO2 eq/yr and 1.2 Mt CO2 eq/yr, respectively). The food calories, minerals, and vitamins met the recommended dietary allowance. The country’s existing food production system generates CO2 emissions of 9.7 Mt CO2 eq/yr, with the proposed system reducing these by 28.9% to 6.9 Mt CO2 eq/yr. The change in each food item could decrease emissions depending on the type and quantity of the food set, especially meat and milk consumption.
The Evolutionary Trend and Impact of Global Plastic Waste Trade Network
Authors: Zhao Changping , Liu Mengru , Du Huanzheng , Gong Yu
Published: March 2021

Marine plastic waste, global warming, and ozone holes have become global environmental problems that need to be resolved urgently. With the promulgation of plastic bans in many countries, the global plastic waste trade will undergo tremendous change. In order to explore the future evolutionary trend of the global plastic waste trade network, this paper focuses on the analysis of the import and export of plastic waste from major trading countries around the world. Based on the bilateral trade volume of plastic waste from 1990 to 2019, a global plastic waste trade network is constructed, and the structure and characteristics of the network are studied. The results show that the global plastic waste trade network has shifted its center of gravity, and the import center has gradually shifted from China to Southeast Asia. The global plastic waste trade network presents a sparse state. Moreover, the dependence of related countries on plastic waste trade decreases, whilst the closeness of trade links also decreases. Sudden factors such as plastic waste import bans have a disruptive impact on plastic waste management.
Looking Deeper: Using the Mobile Microscope to Support Young Children’s Scientific Inquiries
Authors: Chou Pao-Nan , Wang Ping-Jhen
Published: March 2021

This study adopted a quasi-experimental design with the support of qualitative information to investigate the impact of the mobile microscope on students’ science learning outcomes in a laboratory setting. The duration of the educational experiment was 5 weeks. Research participants comprised 56 third graders from two different classes at a public elementary school in Taiwan. Two classes with an equal number of students formed the experimental and control groups. Students in the experimental group employed mobile microscopes to support their scientific inquiries, whereas students in the control group used only tablet computers to facilitate their science learning. A standardized test was developed to measure students’ basic understanding of botany. Additionally, semi-structured concept mapping was employed as an alternative non-standardized test to evaluate students’ natural science learning. The quantitative findings indicated a significant instructional effect in the students’ concept mapping but not in the standardized test. The qualitative results revealed that mobile microscopes might motivate students to actively engage in knowledge discussion and sharing during plant observation.
The Role of Online Brand Community Engagement on the Consumer–Brand Relationship
Authors: Martínez-López Francisco J. , Aguilar-Illescas Rocío , Molinillo Sebastián , Anaya-Sánchez Rafael , Coca-Stefaniak J. Andres , Esteban-Millat Irene
Published: March 2021

The purpose of this study is to analyze the effects of online brand community (OBC) engagement on strategic aspects for the brand supporting the community. A total of 628 valid responses were collected through a self-administered questionnaire. The authors tested the proposed model using structural equation modeling. The results show that OBC engagement directly favors participation in the community, willingness to co-create with the brand, and positive sord-of-mouth (WOM); it also has an indirect positive influence on brand loyalty. At the same time, OBC engagement is directly influenced by OBC identification and, through this, indirectly influenced by brand identification. Likewise, brand trust directly influences brand co-creation, loyalty, and positive WOM. However, OBC participation has been shown to have no significant effect on brand co-creation and positive WOM.
Creating Transdisciplinary Teaching Spaces. Cooperation of Universities and Non-University Partners to Design Higher Education for Regional Sustainable Transition
Authors: Hoinle Birgit , Roose Ilka , Shekhar Himanshu
Published: March 2021

Teaching formats involving non-university partners are increasingly gaining importance to deliver key competencies needed in higher education for sustainable development. Such teaching formats may also create new transdisciplinary spaces that allow different actors to impact regional transition towards sustainable development. Against this background, this article focuses on how universities foster regional transition through teaching, particularly in collaboration with local non-university. Using the interdisciplinary certificate programs on sustainable development offered by the German Universities of Tübingen and Duisburg-Essen as case studies, we analyze the potentials and challenges of teaching programs on sustainable development for promoting regional transition. Leaning on the multi-level-perspective-approach, we have used qualitative interviews to shed light on the design of cooperation between the university and regional partners as well as the creation and integration of transdisciplinary learning spaces. This paper shows that the impact of such teaching formats on the regional transition consists primarily of awareness and network building. One of the most fundamental challenges faced is unequal power relations in terms of access to resources, financing, and doing the course planning. Simultaneously, co-design, mutual understanding, and collective decisions on roles and responsibilities and—especially—empathy and trust are crucial factors for successfully teaching cooperation towards regional sustainability.
A Study on Sustainable Design for Indigo Dyeing Color in the Visual Aspect of Clothing
Authors: Lai Chih-Chun , Chang Ching-Erh
Published: March 2021

Various colors of clothing originating from synthetic dyes are presently causing serious environmental pollution problems, whereas natural dyes extracted from indigo plants help to reduce harm to the environment and extend the sustainable use of clothing. This study focuses on the difference between indigo dyeing colors and the environment on the basis of sustainable design. This study surveyed 105 postgraduates and college students through repeated measurements of ANOVA. The results reveal that light colors are considered to conform to the sustainable spirit more than dark colors in different indigo shades. In fact, a recyclable light-colored indigo-dyed t-shirt is beneficial due to its reusability. Indigo-dyed fabric can be decomposed by a variety of microorganisms; however, light-colored indigo dyeing takes a shorter amount of time. Light-colored indigo dyeing is more resource-saving when considering dye, water and electricity costs. The results of the relationship between colors and environmental protection provide scheme references to consumers or industries for clothing collocation of different indigo dyeing colors for a series of blue clothing, and carry out the idea of sustainability and co-existence between clothing and natural resources.
New Plant Breeding Technologies: An Assessment of the Political Economy of the Regulatory Environment and Implications for Sustainability
Authors: Smith Vincent , Wesseler Justus H. H. , Zilberman David
Published: March 2021

This perspective discusses the impact of political economy on the regulation of modern biotechnology. Modern biotechnology has contributed to sustainable development, but its potential has been underexplored and underutilized. We highlight the importance of the impacts of regulations for investments in modern biotechnology and argue that improvements are possible via international harmonization of approval processes. This development is urgently needed for improving sustainable development. Policy makers in the European Union (EU) in particular are challenged to rethink their approach to regulating modern biotechnology as their decisions have far ranging consequences beyond the boundaries of the EU and they have the power to influence international policies.
The Hidden Potential of Informal Urban Greenspace: An Example of Two Former Landfills in Post-Socialist Cities (Central Poland)
Authors: Długoński Andrzej , Dushkova Diana
Published: March 2021

The present study described analyses of two similar informal recreational green areas (former constructional waste disposal landfills) in two large cities (Warsaw city and Łódź city). On the basis of local society’s opinions, the land use conditions related to current accessibility, management, safety, cleanliness, variety and diversity of facility and vegetation, neighbourhood and connections with the urban green infrastructure of the given sites were studied. Overall feedback posted by the site users indicated that, despite temporary land use, both sites are good leisure areas that provide cultural ecosystem services to the citizens. However, their undefined development makes them to varying degrees neglected and risky spaces, especially for the local community. The reflection of the results of the present study may help the local authorities to manage the spaces of former landfills in accordance with the needs of the local society as well as define new functions of informal urban green space in the sustainable spatial policy in post-socialist cities in Poland and Eastern Europe.
Investigations on Biogas Recovery from Anaerobic Digestion of Raw Sludge and Its Mixture with Agri-Food Wastes: Application to the Largest Industrial Estate in Oman
Authors: Jellali Salah , Charabi Yassine , Usman Muhammad , Al-Badi Abdullah , Jeguirim Mejdi
Published: March 2021

This work is intended to evaluate the technical, environmental, and economic feasibility of converting the sludge produced at an industrial estate’s wastewater treatment plant (WWTP) in Oman into energy through anaerobic digestion (AD). In this study, three different scenarios were analyzed. They concerned the digestion of the total amount of the produced sludge alone (240 m3 day−1) (scenario 1), and its co-digestion with wet agri-food wastes (AFW) at rates of two tonnes day−1 (scenario 2) and ten tonnes day−1 (scenario 3). Based on the analyses of sludge samples, an intensive literature review regarding sludge and AFW Physico-chemical and energetic characteristics and the use of the cost–benefit analysis (CBA) approach, it was found that, for the overall duration of the project (20 years), the AD of the sludge alone (scenario 1) permitted the production of 43.9 GWh of electricity, the reduction of greenhouse gas (GHG) emissions (more than 37,000 tonnes equivalent CO2 (TCO2)) and exhibited positive net present value (NPV: $393,483) and an internal return rate (IRR) of 19.4%. Co-digesting sludge with AFW significantly increased all of these key performance indicators. For instance, scenario 3 results in the recovery of electrical energy of 82.2 GWh and avoids the emission of 70,602 tCO2. Moreover, a higher NPV and IRR of $851,876 and 21.8%, respectively, and a payback period (PBP) of only seven years were calculated. The sensitivity analysis revealed that a decrease in total expenses by 15% results in a significant increase of the NPV and the IRR to $1,418,704 and 33.9%, respectively, for scenario 3. Considering a pessimistic assumption (an increase of the total expenses by 15%), all studied scenarios remain attractive. For instance, for scenario 3, the NPV, IRR, and PBP were evaluated to $285,047, 13.5%, and 9 years, respectively. Therefore, the co-digestion of sludge with agri-food wastes for energy recovery purposes could be considered a promising, eco-friendly, and economically viable approach in the Omani industrial estates.
The Management of Polymer and Biodegradable Composite Waste in Relation to Petroleum-Based Thermoplastic Polymer Waste—In Terms of Energy Consumption and Processability
Authors: Stachowiak Tomasz , Łukasik Katarzyna
Published: March 2021

The article presents a comparative analysis of the flow and utilisation of biodegradable polymer waste in relation to the waste of petroleum-based thermoplastic polymers. It compares energy expenditures and the costs of the reutilisation of both types of plastics in industrial applications. The performed studies and an analysis of the yielded results enabled the acquisition of real data involving the subject of managing petroleum-based plastic waste after the end of its life cycle, as well as biodegradable plastic waste, over the recent years, which is the main purpose of the study. So far, this subject has not been analysed very frequently, and, considering climate change, the predatory economy and the growing population of our planet, it is becoming an important topic, within the scope of which it is necessary to develop a new approach and new solutions regarding legal regulations and social awareness, as well as the technological possibilities of their implementation. The authors’ own research will indicate factual results related to managing various types of waste, based on the example of data acquired from a company involved in the retreatment of plastics and give answers to bothering questions such as: Is there an impact of retreatment on technological indicators defined by means of the mass flow rate? Is the retreatment of biodegradable plastics justified in terms of economy, energy and ecology? Is the retreatment of biodegradable plastics efficient?
A Model for Developing Existing Ports Considering Economic Impact and Network Connectivity
Authors: Riaventin Veterina Nosadila , Cahyo Sofyan Dwi , Singgih Ivan Kristianto
Published: March 2021

This study discusses the problem of determining which container port should be developed within an existing network and when this should be carried out. A case study of Indonesia’s port network is presented, where several new ports are to be improved to ensure smooth interisland transportation flows of goods. The effects of the investment on economic consequences and increased network connectivity are assessed. When improving the ports, we consider that the available budget limits the investment. The network connectivity is evaluated by considering the number of reachable ports from the developed ports or transportation time required from other ports within the same port cluster. Based on our knowledge, our study is the first one that discusses the investment problem in multiple container ports under single management, as well as its effects regarding the increase in container flows. The problem is introduced and three mathematical models are proposed and used to solve a real problem. The results show that different models have different improved aspects of container transportation flows—e.g., a balanced improvement of the whole port network (Model 2) and appropriate investment priority for port clusters (Model 3).
The Value of CSR in Acquisitions: Evidence from China
Authors: Li Kun , He Chaohua , Dbouk Wassim , Zhao Ke
Published: March 2021

In this paper, we aim to test whether and how corporate social responsibility (CSR) is valued in merger and acquisition (M&A) transactions. Employing multiple regression and logistic regression methods to examine the CSR in China’s domestic M&A market from 2007 to 2018, we reveal the following: (i) acquisition targets with higher social performance can attain higher acquisition valuation, especially when the acquirers are also socially responsible; (ii) high-CSR acquirers are inclined to choose equity payments, while high-CSR acquisition targets prefer to be paid in cash; (iii) high CSR performance boosts M&A success rate. The findings are robust, due to adopting two-stage least squares method to tackle endogeneity, substituting variable measures and data sources, and winsorizing variables at high levels to eliminate outliers. The value of CSR in M&As possibly results from the role of CSR in reducing information frictions, agency concerns, and corporate risks and is primarily associated with activities which are friendly to suppliers, customers, shareholders, public welfare, and natural environment, as well as being higher in developed regions and irrelevant to corporate ownership and nature. The study is of vital significance to the valuation and decision making in M&A deals.