bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of GPM IMERG and TRMM 3B43 Products over Cyprus
Authors: Retalis Adrianos , Katsanos Dimitris , Tymvios Filippos , Michaelides Silas
Published: October 2020

Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) high-resolution product and Tropical Rainfall Measuring Mission (TRMM) 3B43 product are validated against rain gauges over the island of Cyprus for the period from April 2014 to June 2018. The comparison performed is twofold: firstly, the Satellite Precipitation (SP) estimates are compared with the gauge stations’ records on a monthly basis and, secondly, on an annual basis. The validation is based on ground data from a dense and well-maintained network of rain gauges, available in high temporal (hourly) resolution. The results show high correlation coefficient values, on average reaching 0.92 and 0.91 for monthly 3B43 and IMERG estimates, respectively, although both IMERG and TRMM tend to underestimate precipitation (Bias values of −1.6 and −3.0, respectively), especially during the rainy season. On an annual basis, both SP estimates are underestimating precipitation, although IMERG estimates records (R = 0.82) are slightly closer to that of the corresponding gauge station records than those of 3B43 (R = 0.81). Finally, the influence of elevation of both SP estimates was considered by grouping rain gauge stations in three categories, with respect to their elevation. Results indicated that both SP estimates underestimate precipitation with increasing elevation and overestimate it at lower elevations.
An Integrated Geologic Map of the Rembrandt Basin, on Mercury, as a Starting Point for Stratigraphic Analysis
Authors: Semenzato Andrea , Massironi Matteo , Ferrari Sabrina , Galluzzi Valentina , Rothery David A. , Pegg David L. , Pozzobon Riccardo , Marchi Simone
Published: October 2020

Planetary geologic maps are usually carried out following a morpho-stratigraphic approach where morphology is the dominant character guiding the remote sensing image interpretation. On the other hand, on Earth a more comprehensive stratigraphic approach is preferred, using lithology, overlapping relationship, genetic source, and ages as the main discriminants among the different geologic units. In this work we produced two different geologic maps of the Rembrandt basin of Mercury, following the morpho-stratigraphic methods and symbology adopted by many authors while mapping quadrangles on Mercury, and an integrated geo-stratigraphic approach, where geologic units were distinguished also on the basis of their false colors (derived by multispectral image data of the NASA MESSENGER mission), subsurface stratigraphic position (inferred by crater excavation) and model ages. We distinguished two different resurfacing events within the Rembrandt basin, after the impact event, and four other smooth plains units outside the basin itself. This provided the basis to estimate thicknesses, volumes, and ages of the smooth plains inside the basin. Results from thickness estimates obtained using different methodologies confirm the presence of two distinct volcanic events inside the Rembrandt basin, with a total thickness ranging between 1–1.5 km. Furthermore, model ages suggest that the volcanic infilling of the Rembrandt basin is among the ones that extended well into the mid-Calorian period, when Mercury’s effusive volcanism was previously thought to be largely over.
Image Collection Simulation Using High-Resolution Atmospheric Modeling
Authors: Kalukin Andrew , Endo Satoshi , Crook Russell , Mahajan Manoj , Fennimore Robert , Cialella Alice , Gregory Laurie , Yoo Shinjae , Xu Wei , Cisek Daniel
Published: October 2020

A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes.
A Software Architecture for the Industrial Internet of Things—A Conceptual Model
Authors: Ungurean Ioan , Gaitan Nicoleta Cristina
Published: September 2020

The Internet of Things (IoT) is an emerging concept that has revolutionized the use of new technologies in everyday life. The economic impact of IoT becoming very important, and it began to be used in the industrial environment under the name of the Industrial Internet of Things (IIoT) concept, which is a sub-domain of IoT. The IIoT changes the way industrial processes are controlled and monitored, increasing operating efficiency. This article proposes a software architecture for IIoT that has a low degree of abstraction compared to the reference architectures presented in the literature. The architecture is organized on four-layer and it integrates the latest concepts related to fog and edge computing. These concepts are activated through the use of fog/edge/gateway nodes, where the processing of data acquired from things is performed and it is the place where things interact with each other in the virtual environment. The main contributions of this paper are the proposal and description of a complete IIoT software architecture, the use of a unified address space, and the use of the computing platform based on SoC (System on Chip) with specialized co-processors in order to be able to execute in real-time certain time-critical operations specific to the industrial environment.
Novel Ensemble Approach of Deep Learning Neural Network (DLNN) Model and Particle Swarm Optimization (PSO) Algorithm for Prediction of Gully Erosion Susceptibility
Authors: Band Shahab S. , Janizadeh Saeid , Chandra Pal Subodh , Saha Asish , Chakrabortty Rabin , Shokri Manouchehr , Mosavi Amirhosein
Published: October 2020

This study aims to evaluate a new approach in modeling gully erosion susceptibility (GES) based on a deep learning neural network (DLNN) model and an ensemble particle swarm optimization (PSO) algorithm with DLNN (PSO-DLNN), comparing these approaches with common artificial neural network (ANN) and support vector machine (SVM) models in Shirahan watershed, Iran. For this purpose, 13 independent variables affecting GES in the study area, namely, altitude, slope, aspect, plan curvature, profile curvature, drainage density, distance from a river, land use, soil, lithology, rainfall, stream power index (SPI), and topographic wetness index (TWI), were prepared. A total of 132 gully erosion locations were identified during field visits. To implement the proposed model, the dataset was divided into the two categories of training (70%) and testing (30%). The results indicate that the area under the curve (AUC) value from receiver operating characteristic (ROC) considering the testing datasets of PSO-DLNN is 0.89, which indicates superb accuracy. The rest of the models are associated with optimal accuracy and have similar results to the PSO-DLNN model; the AUC values from ROC of DLNN, SVM, and ANN for the testing datasets are 0.87, 0.85, and 0.84, respectively. The efficiency of the proposed model in terms of prediction of GES was increased. Therefore, it can be concluded that the DLNN model and its ensemble with the PSO algorithm can be used as a novel and practical method to predict gully erosion susceptibility, which can help planners and managers to manage and reduce the risk of this phenomenon.
Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural Networks
Authors: Burduja Mihail , Ionescu Radu Tudor , Verga Nicolae
Published: October 2020

In this paper, we present our system for the RSNA Intracranial Hemorrhage Detection challenge, which is based on the RSNA 2019 Brain CT Hemorrhage dataset. The proposed system is based on a lightweight deep neural network architecture composed of a convolutional neural network (CNN) that takes as input individual CT slices, and a Long Short-Term Memory (LSTM) network that takes as input multiple feature embeddings provided by the CNN. For efficient processing, we consider various feature selection methods to produce a subset of useful CNN features for the LSTM. Furthermore, we reduce the CT slices by a factor of 2×, which enables us to train the model faster. Even if our model is designed to balance speed and accuracy, we report a weighted mean log loss of 0.04989 on the final test set, which places us in the top 30 ranking (2%) from a total of 1345 participants. While our computing infrastructure does not allow it, processing CT slices at their original scale is likely to improve performance. In order to enable others to reproduce our results, we provide our code as open source. After the challenge, we conducted a subjective intracranial hemorrhage detection assessment by radiologists, indicating that the performance of our deep model is on par with that of doctors specialized in reading CT scans. Another contribution of our work is to integrate Grad-CAM visualizations in our system, providing useful explanations for its predictions. We therefore consider our system as a viable option when a fast diagnosis or a second opinion on intracranial hemorrhage detection are needed.
A Deformable Configuration Planning Framework for a Parallel Wheel-Legged Robot Equipped with Lidar
Authors: Guo Fei , Wang Shoukun , Yue Binkai , Wang Junzheng
Published: October 2020

The wheel-legged hybrid robot (WLHR) is capable of adapting height and wheelbase configuration to traverse obstacles or rolling in confined space. Compared with legged and wheeled machines, it can be applied for more challenging mobile robotic exercises using the enhanced environment adapting performance. To make full use of the deformability and traversability of WHLR with parallel Stewart mechanism, this paper presents an optimization-driven planning framework for WHLR with parallel Stewart mechanism by abstracting the robot as a deformable bounding box. It will improve the obstacle negotiation ability of the high degree-of-freedoms robot, resulting in a shorter path through adjusting wheelbase of support polygon or trunk height instead of using a fixed configuration for wheeled robots. In the planning framework, we firstly proposed a pre-calculated signed distance field (SDF) mapping method based on point cloud data collected from a lidar sensor and a KD -tree-based point cloud fusion approach. Then, a covariant gradient optimization method is presented, which generates smooth, deformable-configuration, as well as collision-free trajectories in confined narrow spaces. Finally, with the user-defined driving velocity and position as motion inputs, obstacle-avoidancing actions including expanding or shrinking foothold polygon and lifting trunk were effectively testified in realistic conditions, demonstrating the practicability of our methodology. We analyzed the success rate of proposed framework in four different terrain scenarios through deforming configuration rather than bypassing obstacles.
Incorporating a Ferrous Polymer Target into Elastomeric Liners for Socket Fit Sensing in Prosthesis Users
Authors: Carter Ryan V. , Larsen Brian G. , McLean Jake B. , Garbini Joseph L. , Sanders Joan E.
Published: October 2020

Liner-to-socket distance measurement using inductive sensing may be an effective means to continuously monitor socket fit in people using trans-tibial prostheses. A practical limitation, however, is a means to incorporate a thin uniform-thickness layer of conductive or magnetically permeable target material into the wide range of prosthetic liner products that people with limb amputation commonly use. In this paper, a method is presented whereby a 0.50-mm thickness ferrous polymer made from a SEEPS polymer and iron powder that is formed adjacent to a 0.25-mm thick non-ferrous layer of SEEPS polymer is assembled between two sheets of elastic fabric material. Bench testing showed that the fabrication procedure achieved a root-mean-square error in the thickness of this construct of 58 μm, helping to create a consistent calibration result over the entire surface. The original fabric backing of an off-the-shelf prosthetic liner was removed and replaced with the developed construct. When worn in the shoe of an able-bodied participant for 7.5 h per day for 28 days, the sensor well maintained the shape of its calibration curve at the start of wear, but a distance offset (shifting of the y-intercept) was introduced that increased during the initial approximately 12 days of wear. When the distance offset was corrected, for the primary distance range of clinical interest for this application (0.00–5.00 mm), the sensor maintained its calibration within 4.4%. Before being used in clinical application for liner-to-socket distance monitoring, new ferrous liners may need to be pre-worn so as to achieve a consistent distance reference.
Recognition of Non-Manual Content in Continuous Japanese Sign Language
Authors: Brock Heike , Farag Iva , Nakadai Kazuhiro
Published: October 2020

The quality of recognition systems for continuous utterances in signed languages could be largely advanced within the last years. However, research efforts often do not address specific linguistic features of signed languages, as e.g., non-manual expressions. In this work, we evaluate the potential of a single video camera-based recognition system with respect to the latter. For this, we introduce a two-stage pipeline based on two-dimensional body joint positions extracted from RGB camera data. The system first separates the data flow of a signed expression into meaningful word segments on the base of a frame-wise binary Random Forest. Next, every segment is transformed into image-like shape and classified with a Convolutional Neural Network. The proposed system is then evaluated on a data set of continuous sentence expressions in Japanese Sign Language with a variation of non-manual expressions. Exploring multiple variations of data representations and network parameters, we are able to distinguish word segments of specific non-manual intonations with 86% accuracy from the underlying body joint movement data. Full sentence predictions achieve a total Word Error Rate of 15.75%. This marks an improvement of 13.22% as compared to ground truth predictions obtained from labeling insensitive towards non-manual content. Consequently, our analysis constitutes an important contribution for a better understanding of mixed manual and non-manual content in signed communication.
A Dual-Padded, Protrusion-Incorporated, Ring-Type Sensor for the Measurement of Food Mass and Intake
Authors: Hong Wonki , Lee Jungmin , Lee Won Gu
Published: October 2020

Dietary monitoring is vital in healthcare because knowing food mass and intake (FMI) plays an essential role in revitalizing a person’s health and physical condition. In this study, we report the development of a highly sensitive ring-type biosensor for the detection of FMI for dietary monitoring. To identify lightweight food on a spoon, we enhance the sensing system’s sensitivity with three components: (1) a first-class lever mechanism, (2) a dual pad sensor, and (3) a force focusing structure using a ring surface having protrusions. As a result, we confirmed that, as the food arm’s length increases, the force detected at the sensor is amplified by the first-class lever mechanism. Moreover, we obtained 1.88 and 1.71 times amplification using the dual pad sensor and the force focusing structure, respectively. Furthermore, the ring-type biosensor showed significant potential as a diagnostic indicator because the ring sensor signal was linearly proportional to the food mass delivered in a spoon, with R2 = 0.988, and an average F1 score of 0.973. Therefore, we believe that this approach is potentially beneficial for developing a dietary monitoring platform to support the prevention of obesity, which causes several adult diseases, and to keep the FMI data collection process automated in a quantitative, network-controlled manner.
Wastewater Quality Estimation through Spectrophotometry-Based Statistical Models
Authors: Carreres-Prieto Daniel , García Juan T. , Cerdán-Cartagena Fernando , Suardiaz-Muro Juan
Published: October 2020

Local administrations are increasingly demanding real-time continuous monitoring of pollution in the sanitation system to improve and optimize its operation, to comply with EU environmental policies and to reach European Green Deal targets. The present work shows a full-scale Wastewater Treatment Plant field-sampling campaign to estimate COD, BOD5, TSS, P, TN and NO3−N in both influent and effluent, in the absence of pre-treatment or chemicals addition to the samples, resulting in a reduction of the duration and cost of analysis. Different regression models were developed to estimate the pollution load of sewage systems from the spectral response of wastewater samples measured at 380–700 nm through multivariate linear regressions and machine learning genetic algorithms. The tests carried out concluded that the models calculated by means of genetic algorithms can estimate the levels of five of the pollutants under study (COD, BOD5, TSS, TN and NO3−N), including both raw and treated wastewater, with an error rate below 4%. In the case of the multilinear regression models, these are limited to raw water and the estimate is limited to COD and TSS, with less than a 0.5% error rate.
Method for Fault Diagnosis of Temperature-Related MEMS Inertial Sensors by Combining Hilbert–Huang Transform and Deep Learning
Authors: Gao Tong , Sheng Wei , Zhou Mingliang , Fang Bin , Luo Futing , Li Jiajun
Published: October 2020

In this paper, we propose a novel method for fault diagnosis in micro-electromechanical system (MEMS) inertial sensors using a bidirectional long short-term memory (BLSTM)-based Hilbert–Huang transform (HHT) and a convolutional neural network (CNN). First, the method for fault diagnosis of inertial sensors is formulated into an HHT-based deep learning problem. Second, we present a new BLSTM-based empirical mode decomposition (EMD) method for converting one-dimensional inertial data into two-dimensional Hilbert spectra. Finally, a CNN is used to perform fault classification tasks that use time–frequency HHT spectrums as input. According to our experimental results, significantly improved performance can be achieved, on average, for the proposed BLSTM-based EMD algorithm in terms of EMD computational efficiency compared with state-of-the-art algorithms. In addition, the proposed fault diagnosis method achieves high accuracy in fault classification.
Supply Chain Uncertainties of Small-Scale Coffee Husk-Biochar Production for Activated Carbon in Vietnam
Authors: Flammini Alessandro , Brundin Erik , Grill Rikard , Zellweger Hannes
Published: September 2020

Between 2014 and 2019, an innovative small-pyrolysis system (the PPV300) using agrowaste as feedstock was transferred and adapted from Switzerland to Vietnam by a United Nations Industrial Development Organization (UNIDO) project. The coffee husk resulting from the processing of coffee beans is usually disposed of in Vietnam or burned inefficiently to dry coffee beans. Small-scale pyrolysis of coffee husk using the PPV300 avoids smoke emissions and local air pollution while providing an energy source for coffee drying and biochar as a by-product. This paper investigates the uncertainties in the “coffee husk to activated carbon” supply chain in Vietnam and discusses the pros and cons of different supply chain setups using a framework derived by Chopra and Meindl (2013). According to the analysis, a number of actors (an intermediary without previous direct involvement in the coffee supply chain, a coffee processor, or a hybrid between farm and processor), each with advantages and disadvantages, would be suitable from a supply chain perspective to attain an efficient strategy that would keep the price of the biochar low. However, in order to be attractive for one activated carbon producer, several PPV300 systems are needed to reach a significant economy of scale. Sufficient husk sourcing and storage capacity is also needed. If the purpose is simply to produce biochar for activated carbon, processors and intermediaries could consider a simpler and cheaper design than the PPV300. In conclusion, supply chain uncertainties and economic viability can be optimized when the PPV300 is used by coffee processors or intermediaries, who are able to make use of the co-products generated (biochar, heat, and wood vinegar). In addition to its financial viability, all of the other co-benefits of this technology should be taken into consideration (reduced smoke and environmental pollution, avoided health costs, greenhouse gas savings, etc.) for a proper assessment of its economic attractiveness.
Digital Information Tools for Urban Regeneration: Capital’s Approach in Theory and Practice
Authors: Bratuškins Uģis , Zaleckis Kęstutis , Treija Sandra , Koroļova Alisa , Kamičaitytė Jūratė
Published: October 2020

Urban regeneration, which includes renovation of decaying urban structures as well as renovation of dilapidated buildings, is an important economic, aesthetic and cultural factor for sustainable development planning worldwide. The revitalization of urban structures is a complex challenge, influenced by various interdisciplinary aspects, like urban socio-economic development, integrated transport and mobility solutions and others. And it requires involvement of different stakeholders at different levels in identifying and finding solutions. Technological innovations offer a variety of digital tools to address modern urban governance and modelling issues, identifying problem areas with public involvement and participation that allow relevant services to respond quickly, thus improving the urban environment and the quality of life of people. With the help of digital tools, it is also possible to promote the availability of public services, model and forecast environmental risks, as well as perform other functions integral to the organization and management of modern society. However, the wide range of these tools and their mutually asynchronous use often make it difficult to choose the right tool, thus creating the risk of fragmented implementation. The aim of this paper is to propose theoretical approach for modelling of complex interactions affecting urban regeneration as well as summarize and systematize the existing digital information tools which might empower the process of regeneration. The analysis of the use and impact of digital and smart tools allows to identify urban problems, as well as to outline ways to solve them. The results of the research will form the basis for further research stages.
Measurement of Fairness Perceptions in Energy Transition Research: A Factorial Survey Approach
Authors: Liebe Ulf , Dobers Geesche M.
Published: October 2020

Justice and fairness are increasingly popular concepts in energy research and comprise several justice dimensions, including distributive and procedural justice, related to energy production and consumption. In this paper, we used factorial survey experiments—a method employed in sociological justice research—for energy transition research. In a factorial survey, respondents evaluated one or more situations described by several attributes, which varied in their levels. The experimental setup of factorial surveys is one of its advantages over simple survey items, as based on this, the relative importance of each attribute for justice evaluations can be determined. We employed the method in a study on the perceived fairness of renewable energy expansion projects related to wind energy, solar energy, and biomass in Germany, and considered aspects of procedural and distributive justice. We show that the effects of these justice dimensions can be separated and the heterogeneity in justice evaluations can be explained. Compared to previous studies applying factorial survey experiments to explain the acceptance of renewable energy projects, we employed the method to directly measure justice concerns and asked respondents to evaluate the vignettes in terms of perceived fairness. This is important because acceptance and fairness as well as inequality and injustice are different phenomena.
A Participatory Geospatial Toolkit for Science Integration and Knowledge Transfer Informing SDGs Based Governance and Decision Making
Authors: Sajeva Maurizio , Maidell Marjo , Kotta Jonne
Published: October 2020

While the specialisation of science is important for understanding specific systems, the isolation of scientific schools in their disciplinary silos makes it harder to understand the interactions within and between systems and limits the wisdom about the whole systems’ sustainability. Science integration and its practical implementation is a key factor of success for sustainable development. The aim of this paper is to present a participatory geospatial toolkit developed during the BONUS MARES project that enables science integration and knowledge transfer informing SDGs based governance and decision making. This was realized through the Eco-GAME (Governance Assessment Matrix Exercise) framework, trans-disciplinary social learning for the meta-evaluation of existing knowledge about human-nature systems interaction—manifested through ecosystem services. The Eco-GAME was applied to a participatory geospatial toolkit that translates complex ecological knowledge on ecosystems, ecosystem functions, and services produced into more usable forms to inform evidence-based decision-making in pursuit of the Sustainable Development Goals (SDGs). This is the first attempt, in the context of geospatial applications, to support dynamic interaction, trans-disciplinary social-learning, and multi-dimensional appreciation of ecosystem services for integrating ecological, non-economic and economic knowledge and methods. The toolkit is being implemented in the MAREA project.
GIS-Based Material Stock Analysis (MSA) of Climate Vulnerabilities to the Tourism Industry in Antigua and Barbuda
Authors: Bradshaw Johnella , Jit Singh Simron , Tan Su-Yin , Fishman Tomer , Pott Kristen
Published: October 2020

In the past decades, the Caribbean economy has transformed to rely primarily on tourism with a vast amount of infrastructure dedicated to this sector. At the same time, the region is subject to repeated crises in the form of extreme weather events that are becoming more frequent, deadly, and costly. Damages to buildings and infrastructure (or the material stocks) from storms disrupt the local economy by an immediate decline in tourists and loss of critical services. In Antigua and Barbuda (A&B), tourism contributes 80% to the GDP and is a major driver for adding new material stocks to support the industry. This research analyzes A&B’s material stocks (MSs) in buildings (aggregates, timber, concrete, and steel) using geographic information systems (GIS) with physical parameters such as building size and footprint, material intensity, and the number of floors. In 2004, the total MSs of buildings was estimated at 4.7 million tonnes (mt), equivalent to 58.5 tonnes per capita, with the share of non-metallic minerals to be highest (2.9 mt), followed by aggregates (1.2 mt), steel (0.44 mt), and timber (0.18 mt). Under the National Oceanic and Atmospheric Administration’s (NOAA’s) 2 meter (m) sea level rise scenario, an estimated 4% of the island’s total MSs would be exposed. The tourism sector would disproportionately experience the greatest exposure of 19% of its MSs. By linking stocks to services, our research contributes to the understanding of the complexities between the environmental and economic vulnerability of island systems, and the need for better infrastructure planning as part of resilience building.
Electrical Longboard for Everyday Urban Commuting
Authors: Ciocan Alexandru , Ungureanu Cosmin , Chitu Alin , Carcadea Elena , Darie George
Published: October 2020

This paper addresses the possibility of using an electric longboard in daily travel. A conventional longboard was transformed into an electric one and tested in ICSI Rm. Valcea labs. A series of tests were performed both at the laboratory level and, under normal running conditions, outdoors. Nevertheless, two possible scenarios have been taken into consideration. First, when the electric longboard is running on a flat road with a cruise speed, while the second scenario considered was that of climbing a hill with a 10% slope. The results confirmed the expectations and showed that a full charge of the batteries allows a trip over a distance of almost 50 km on a flat route having a consumption of about 10 Wh/km. However, there are some things to keep in mind when making travel distance predictions. The quality and the profile of the road, the weight of the rider, the rider position, all of these are factors which can significantly influence the predictions regarding the travel distance. Moreover, if the optimization is taken into account, several adjustments can be done in choosing the size and wheel model, whether or not to equip the skateboard with suspensions as well as a compromise between power and energy densities when choosing battery type is essential.
The Environment and Populist Radical Right in Eastern Europe: The Case of National Alliance 2010–2018
Authors: Timofejevs Péteris F
Published: October 2020

Although the literature on populist radical right parties (PRRP) in Western and Eastern Europe has expanded considerably in the last two decades, relatively little is known about the views on nature and the environment of the PRRP in Eastern Europe. This study focuses on the Latvian PRRP “National Alliance” (NA), which has not only been a coalition government partner since 2011, but occupied a ministerial post tasked with environmental policy from 2014 to 2019. This article examines how the NA viewed nature, the environment, and governance for sustainability in the period 2010–2018, and more specifically, whether and to what extent the NA’s vision of nature and the environment was compatible with its sustainable development position. The study employs qualitative content analysis examining the official party literature. The results indicate that the party’s vision embraced the sustainable development position in its declaratory statements on nature and environmental policy. The NA’s views on governance for sustainability demonstrate a strong statist preference, downplaying more participatory approaches, thus departing from the sustainable development governance position.
Temporary Uses of Urban Brownfields for Creative Activities in a Post-Socialist City. Case Study: Timișoara (Romania)
Authors: Marian-Potra Alexandra-Camelia , Ișfănescu-Ivan Ramona , Pavel Sorin , Ancuța Cătălina
Published: October 2020

The linking (in terms of functional use) of brownfield sites with creative spaces is a frequently encountered phenomenon in western European, post-communist, and industrialized countries in general and is viewed as a way of revitalizing, repurposing, or simply making temporary use of them. It may also be seen in the municipality of Timișoara in Romania, where 12 creative spaces, each involving one or more kinds of functionalities (coworking space, maker space, community space, event space, incubator), are operating on such sites. A content analysis of interviews with those in charge of these 12 creative spaces brought to light, on the one hand, the opportunities represented by the existence of derelict industrial spaces, as represented by their large size, low rents, and innate flexibility, but on the other the reality of a number of long-term constraints on the use of these spaces, given the financial instability of cultural operators, the limited numbers of the public who are interested in creative activities of this kind, and, most seriously, the development pressure exerted by some real-estate developers on derelict industrial spaces.
Influential Factors Regarding Carbon Emission Intensity in China: A Spatial Econometric Analysis from a Provincial Perspective
Authors: Xue Li-Ming , Meng Shuo , Wang Jia-Xing , Liu Lei , Zheng Zhi-Xue
Published: October 2020

Emission reduction strategies based on provinces are key for China to mitigate its carbon emission intensity (CEI). As such, it is valuable to analyze the driving mechanism of CEI from a provincial view, and to explore a coordinated emission mitigation mechanism. Based on spatial econometrics, this study conducts a spatial-temporal effect analysis on CEI, and constructs a Spatial Durbin Model on the Panel data (SDPM) of CEI and its eight influential factors: GDP, urbanization rate (URB), industrial structure (INS), energy structure (ENS), energy intensity (ENI), technological innovation (TEL), openness level (OPL), and foreign direct investment (FDI). The main findings are as follows: (1) overall, there is a significant and upward trend of the spatial autocorrelation of CEI on 30 provinces in China. (2) The spatial spillover effect of CEI is positive, with a coefficient of 0.083. (3) The direct effects of ENI, ENS and TEL are significantly positive in descending order, while INS and GDP are significantly negative. The indirect effects of URB and ENS are significantly positive, while GDP, ENI, OPL and FDI are significantly negative in descending order. Economic and energy-related emission reduction measures are still crucial to the achievement of CEI reduction targets for provinces in China.
Small and Light Electric Vehicles: An Analysis of Feasible Transport Impacts and Opportunities for Improved Urban Land Use
Authors: Ewert Amelie , Brost Mascha , Eisenmann Christine , Stieler Sylvia
Published: October 2020

Improvements in battery technology have resulted in small and light electric vehicles (LEVs) appearing on the market in Europe since 2011—however, their market share is still comparatively low. Low energy requirements and small size can potentially contribute to sustainable mobility in terms of climate protection and reduced local emissions. Our study evaluates how three-wheeled and four-wheeled vehicles, categorised as L-Class according to Regulation (EU) No 168/2013, can contribute to more efficient use of space in urban areas. Evaluations of expert interviews, an extensive literature research, and analyses of the German national household travel survey (MiD) serve as the basis of the study. First, the substitution potential of trips through LEVs is explored using MiD data. Our findings show that between 17% and 49% of trips made and 6% to 30% of the distance covered by private trips can theoretically be substituted by LEVs. Thus, reorganisation of current land use offers potential and additionally, LEVs are an attractive and sustainable addition to other means of transport and contribute to achieving the climate protection goals of the transport sector. Due to the fact that technology application is restricted by travel behaviour and political support, our study discusses possible support by public bodies towards sustainable mobility. Here, the promotion of LEVs in combination with restrictive measures for cars is necessary.
Nursing as a Sustainability Factor of the Health System during the COVID-19 Pandemic: A Qualitative Study
Authors: Rojas-Ocaña María Jesús , Araujo-Hernández Miriam , Romero-Castillo Rocío , Román-Mata Silvia San , García-Navarro E. Begoña
Published: October 2020

Earlier this year, Spain took center stage in the emerging health crisis due to the SARS-CoV-2 pandemic. On 14 March 2020, a state of alarm was declared to manage this health crisis. The contribution of nursing professionals to sustainability of the system during this health crisis has been vital, not only in specialized care but, in a more understated way, in primary care. The objective of the present study was to describe the perceptions and lived experiences of primary care nurses during the COVID-19 health emergency. A qualitative study taking a phenomenological approach was carried out, triangulating data collected through non-participant observations, eight in-depth interviews, and two discussion groups with community nurses and case managers. A total sample of 20 key informants was obtained during the month of May, 2020. The key informants expressed strong positive perceptions of the recognition received from service users and satisfaction when acknowledging that they have been an important source of emotional support. Informants identify the importance of their work in sustaining the system, particularly outlining team cohesion and communication, whilst also evaluating the empowering position in which service users and society itself has put them.
Factors Influencing the Tourist’s Future Intentions in Small-Scale Sports Events
Authors: Vegara-Ferri José Miguel , López-Gullón José María , Valantine Irena , Díaz Suárez Arturo , Angosto Salvador
Published: October 2020

Small-scale sports events are a good strategy for communities seeking to attract visitors and are one of the major attractions of sustainable sports tourism. The aim of this study to determine which factors influence the future intentions of the tourist involved in small-scale sports events. The sample was composed of 236 subjects who participated in a half-marathon in Spain. The results of the Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) provide support for the applicability of the tourists’ perception questionnaire in the context of sports events. The results of both validity (convergent and discriminant) and reliability (internal consistency) analyses were satisfactory. The results indicated that this scale had 18 items distributed in six factors (communication, staff, electronic wordofmouth, destination image, satisfaction and future intentions). The proposal model revealed that satisfaction is a mediated factor between staff and destination image with future intentions of repeating the event. Electronic word of mouth and satisfaction were influencing factors that predicted the tourists’ future intentions. This finding suggests that this questionnaire can be a useful tool in measuring tourist perception on a small-scale sports events scale, allowing a better understanding of the reasons that lead a tourist to select a certain destination and sports event.
Phased Reverse Engineering Framework for Sustainable Cultural Heritage Archives Using Laser Scanning and BIM: The Case of the Hwanggungwoo (Seoul, Korea)
Authors: Ham Namhyuk , Bae Baek-Il , Yuh Ok-Kyung
Published: October 2020

This study proposed a phased reverse engineering framework to construct cultural heritage archives using laser scanning and a building information model (BIM). This framework includes acquisition of point cloud data through laser scanning. Unlike previous studies, in this study, a standard for authoring BIM data was established through comparative analysis of existing archives and point cloud data, and a method of building valuable BIM data as an information model was proposed. From a short-term perspective, additional archives such as member lists and drawings can be extracted from BIM data built as an information model. In addition, from a long-term perspective, a scenario for using the cultural heritage archive consisting of historical records, point cloud data, and BIM data was presented. These scenarios were verified through a case study. In particular, through the BIM data building and management method, relatively very light BIM data (499 MB) could be built based on point cloud data (more than 917 MB), which is a large amount of data.
Improvement of Memory and Motivation in Language Learning in Primary Education through the Interactive Digital Whiteboard (IDW): The Future in a Post-Pandemic Period
Authors: Bautista-Vallejo José M. , Hernández-Carrera Rafael M. , Moreno-Rodriguez Ricardo , Lopez-Bastias José Luis
Published: October 2020

This paper presents an analysis of the use of an interactive digital whiteboard (IDW) and a computer application called Action Manager (AM), with a sample of 158 sixth-grade students in primary education. Subsequently, a study was carried out with the main goal of testing the didactic functioning of AM and examining the validity of this application, in terms of motivation and the retention of both short and long-term memory when teaching foreign languages in primary education. In order to fulfil these objectives, we performed a positivist exploratory study based on a quantitative methodology combining qualitative aspects (qualitative evaluation) and quantitative aspects (questionnaires) as well as a descriptive method with a survey design. The data collection was performed using instruments, specifically the Extrinsic vs. Intrinsic Orientation Scale, to ascertain the motivational impressions of the students and two memory tests, the Test of Memory and Learning (TOMAL) and the Children’s Memory Scale (CMS). Forty-five days later, the two memory tests were repeated to compare the results with the previous ones. After this experience, the results allowed us to conclude that the students demonstrated optimal memorization from a conceptual point of view, in addition to having improved their motivational impressions.
Contribution of Roof Refurbishment to Urban Sustainability
Authors: Pitarch Ángel , Ruá María José , Reig Lucía , Arín Inés
Published: October 2020

Achieving sustainable urban environments is a challenging goal—especially in existing cities with high percentages of old and obsolete buildings. This work analyzes the contribution of roof refurbishment to sustainability, considering that most roofs are currently underused. Many potential benefits of refurbishment can be achieved, such as the improvement of the energy performance of the buildings and the use of a wasted space for increasing green areas or for social purposes. In order to estimate the degree of the improvement, a vulnerable area in Castellón (east Spain) was selected as a case study. A thorough analysis of the residential building stock was undertaken. Using georeferenced information from the Cadastral Office we classified them according to typology, year of construction and roof type. Some refurbishment solutions were proposed and their applicability to the actual buildings was analyzed under different criteria. The theoretical benefits obtained in the neighborhood such as energy and carbon emissions savings were evaluated, together with the increase of green areas. Moreover, other social uses were suggested for neglected urban spaces in the area. Finally, a more accurate analysis was performed combining different solutions in a specific building, according to its particular characteristics.
Board and Top Management Social Sustainability Work in Cluster Organizations
Authors: Sundström Agneta , Mickelsson Kristina
Published: October 2020

This case study aims to analyze how boards and top management in regional cluster organizations contribute to social sustainability commitment for themselves and their member organizations with specific focus on gender equality and diversity issues. The study adopts a case study research approach, where interviews, observations and secondary data constitute the basis for in-depth analysis. To deepen the case analysis, four theoretical perspectives are applied for pattern-matching: stakeholder, resource dependence, agency and institutional theory. Results of the study show that the boards are aware of stakeholder requirements, have necessary resources and expertise, and are well aware of the importance of social sustainability, but they act traditionally by focusing on economic incentives and responsibility. Board members act symbolically by transferring social responsibility to the top management of these cluster organizations through their applications for funds. From agency and stakeholder perspectives, the fund application regulates roles and responsibilities between the parties. Top management legitimates the responsibility by initiating projects and initiatives to strengthen social sustainability in a substantive way in member organizations. The study contribution shows that the board’s mission and role have symbolic significance for building social responsibility, while top management contributes substantively.
Contamination, Spatial Distribution and Source Analysis of Heavy Metals in Surface Soil of Anhui Chaohu Economic Development Zone, China
Authors: Pan Chang , Yu Fei , Tao Xiao , Guo Jiahuan , Yu Yuanchun
Published: October 2020

Anthropogenic activities may result in the accumulation of heavy metals in the soil, especially in economic development zones with frequent industrial activities. Therefore, the investigation and assessment of soil heavy metal pollution in economic development zones is one of the important measures for soil environmental management and sustainable development. This study used Nemero evaluation, Kriging interpolation, cluster analysis, and principal component analysis to investigate the contamination degree, spatial distribution, and origin of heavy metal in Anhui Chaohu Economic Development Zone (ACED), Anhui, East China. The result showed that different land use types can cause different levels and types of soil heavy metal pollution. The maximum concentrations of heavy metals in the study area all exceeded their background value but did not exceed the guide values. The highest average concentrations were found in Zn, followed by Cr and Ni. The concentrations of As in soils have the largest coefficient of variation (CV) at 38%. The concentration of heavy metals in different functional areas was varied, the areas with higher Ni, As, Cd, Zn, and Cr concentrations were mainly distributed in Hot Springs Resort (HSR), the relatively higher concentrations of Pb, Hg, and Cu were mainly distributed in Integrated Zone (IZ), while all heavy metal (except for Ni) have relatively higher content in the surface soil of Huashan Industrial Zone (HIZ). Origin analysis showed that soil As, Cd, and Zn in HSR surface soil were predominantly influenced by agricultural activities, while Ni and Cr were mainly controlled by parent material. Pb and Hg in IZ surface soil were predominantly originated from the vehicle and domestic exhaust, and Cu was mainly controlled by industrial pollutants. Industrial activity was the main source of soil heavy metals in HIZ. Although heavy metal in ACED surface soil did not reach pollution levels, the concentration of Cd, Hg, Pb, and Cu was significantly affected by anthropogenic activities, especially in HIZ, which the necessary attention of heavy metals needs to be given.