bluuebunny/crossref_metadata_2025 huggingface dataset:
An Improved Cloud Detection Method for GF-4 Imagery
Authors: Lu Ming , Li Feng , Zhan Bangcheng , Li He , Yang Xue , Lu Xiaotian , Xiao Huachao
Published: May 2020

Clouds are significant barriers to the application of optical remote sensing images. Accurate cloud detection can help to remove contaminated pixels and improve image quality. Many cloud detection methods have been developed. However, traditional methods either rely heavily on thermal infrared bands or clear-sky images. When traditional cloud detection methods are used with Gaofen 4 (GF-4) imagery, it is very difficult to separate objects with similar spectra, such as ice, snow, and bright sand, from clouds. In this paper, we propose a new method, named Real-Time-Difference (RTD), to detect clouds using a pair of images obtained by the GF-4 satellite. The RTD method has four main steps: (1) data preprocessing, including transforming digital value (DN) to Top of Atmosphere (TOA) reflectance, and orthographic and geometric correction; (2) the computation of a series of cloud indexes for a single image to highlight clouds; (3) the calculation of the difference between a pair of real-time images in order to obtain moved clouds; and (4) confirming the clouds and background by analyzing their physical and dynamic features. The RTD method was validated in three sites located in the Hainan, Liaoning, and Xinjiang areas of China. The results were compared with those of a popular classifier, Support Vector Machine (SVM). The results showed that RTD outperformed SVM; for the Hainan, Liaoning, and Xinjiang areas, respectively, the overall accuracy of RTD reached 95.9%, 94.1%, and 93.9%, and its Kappa coefficient reached 0.92, 0.88, and 0.88. In the future, we expect RTD to be developed into an important means for the rapid detection of clouds that can be used on images from geostationary orbit satellites.
Secular Changes in Atmospheric Turbidity over Iraq and a Possible Link to Military Activity
Authors: Chudnovsky Alexandra , Kostinski Alexander
Published: May 2020

We examine satellite-derived aerosol optical depth (AOD) data during the period 2000–2018 over the Middle East to evaluate the contribution of anthropogenic pollution. We focus on Iraq, where US troops were present for nearly nine years. We begin with a plausibility argument linking anthropogenic influence and AOD signature. We then calculate the percent change in AOD every two years. To pinpoint the causes for changes in AOD on a spatial basis, we distinguish between synoptically “calm” periods and those with vigorous synoptic activity. This was done on high-resolution 10 km AOD retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (Terra satellite). We found spatiotemporal variability in the intensity of the AOD and its standard deviation along the dust-storm corridor during three studied periods: before Operation Iraqi Freedom (OIF) (1 March 2000–19 March 2003), during OIF (20 March 2003–1 September 2010), and Operation New Dawn (OND; 1 September 2010–18 December 2011), and after the US troops’ withdrawal (19 December 2011–31 December 2018). Pixels of military camps and bases, major roads and areas of conflict, and their corresponding AOD values, were selected to study possible effects. We found that winter, with its higher frequency of days with synoptically “calm” conditions compared to spring and summer, was the best season to quantitatively estimate the impact of these ground-based sources. Surprisingly, an anthropogenic impact on the AOD signature was also visible during vigorous synoptic activity. Meteorological conditions that favor detection of these effects using space imagery are discussed, where the effects are more salient than in surrounding regions with similar meteorological conditions. This exceeds expectations when considering synoptic variations alone.
Mapping Fragmented Impervious Surface Areas Overlooked by Global Land-Cover Products in the Liping County, Guizhou Province, China
Authors: Zhao Jing , Tsutsumida Narumasa
Published: May 2020

Imperviousness is an important indicator for monitoring urbanization and environmental changes, and is evaluated widely in urban areas, but not in rural areas. An accurate impervious surface area (ISA) map in rural areas is essential to achieve environmental conservation and sustainable rural development. Global land-cover products such as MODIS MCD12Q1, ESA CCI-LC, and Global Urban Land are common resources for environmental practitioners to collect land-cover information including ISAs. However, global products tend to focus on large ISA agglomerations and may not identify fragmented ISA extents in less populated regions. Land-use planners and practitioners have to map ISAs if it is difficult to obtain such spatially explicit information from local governments. A common and consistent approach for rural ISA mapping is yet to be established. A case study of the Liping County, a typical rural region in southwest China, was undertaken with the objectives of assessing the global land-cover products in the context of rural ISA mapping and proposing a simple and feasible approach for the mapping. This approach was developed using Landsat 8 imagery and by applying a random forests classifier. An appropriate number of training samples were distributed to towns or villages across all townships in the study area for classification. The results demonstrate that the global land-cover products identified major ISA agglomerations, specifically at the county seat; however, other fragmented ISAs over the study area were overlooked. In contrast, the map created using the developed approach inferred ISAs across all townships with an overall accuracy of 91%. A large amount of training samples together with geographic information of towns or villages is the key suggestion to identify and map ISAs in rural areas.
Research on the Weld Position Detection for the T-Joints in Web-Core Sandwich Panels Based on Eddy Current Technology
Authors: Wei Angang , Chang Baohua , Meng Fanyue , Du Dong , Han Zandong
Published: May 2020

Web-core sandwich panels have gained the popularity in various fields, especially aviation and shipbuilding, etc. Penetration welding was considered as an effective process to manufacture such a structure through a T-joint. To ensure the formation quality and mechanical properties of weld, the welding torch needs to be aligned with the T-joint position. However, it is difficult to locate the T-joint position (i.e., the position of core panel) because of the shielding of the face panels. This paper investigated the detection of T-joint position from the face panel side in web-core sandwich panels based on eddy current technology. First, we designed an experimental system for the weld position detection of T-joints from the face panel side. The relationships are investigated between the characteristics of the eddy current detection signal and the primary parameters of the detection system (including excitation frequency, coil outer diameter, and lift off distance) and the T-joint (including thickness of the core panel, gap distance, and thickness of the cover panel). Corresponding experiments were carried out with variable primary parameters, and the influence mechanism of the primary parameters on the detection results in terms of sensitivity and dynamic performance was elaborated to set up the theoretical basis for the detection. Finally, weld position detection experiments were carried out on TC4 titanium alloy T-joint specimens with 3 mm-thick face panel and 5 mm-thick core panel. Results showed that the maximum detection error was 0.482 mm, and the average error was 0.234 mm. This paper provided a possible technical solution to the automatic tracking problem for the welding of T-joints in the web-core sandwich panels.
Modeling of Magnetic Field and Transients in a Novel Permanent Magnet Valve Actuator
Authors: Waindok Andrzej , Tomczuk Bronisław , Koteras Dariusz
Published: May 2020

This paper concerns mathematical modelling of dynamic performances to a new permanent magnet electromagnetic valve actuator (PMEVA). Both static and transient characteristics were simulated by using the finite element method (FEM) and field-circuit approach. The magnetic force values versus the excitation current and the position of the valve actuator movable part have been determined. Our concept of the mover positioning relative to the radial magnets is quite novel. PMEVA parameters are satisfied for implementation in combustion engines. Transients in the device have also been analyzed for no-load and for the nominal burden of the actuator. The indications of the position sensors and the excitation current waves were simulated and measured for the step voltage supply. The calculation results were verified experimentally, and a good conformity has been observed. The advantages of our actuator are simple construction, short time of the switching, the current supplying being needed only at the runner extreme positions, and simple controlling. Additionally, PMEVA design can be extended to support the simultaneous operation of four valves.
Deep Binary Classification via Multi-Resolution Network and Stochastic Orthogonality for Subcompact Vehicle Recognition
Authors: Shin Joongchol , Koo Bonseok , Kim Yeongbin , Paik Joonki
Published: May 2020

To encourage people to save energy, subcompact cars have several benefits of discount on parking or toll road charge. However, manual classification of the subcompact car is highly labor intensive. To solve this problem, automatic vehicle classification systems are good candidates. Since a general pattern-based classification technique can not successfully recognize the ambiguous features of a vehicle, we present a new multi-resolution convolutional neural network (CNN) and stochastic orthogonal learning method to train the network. We first extract the region of a bonnet in the vehicle image. Next, both extracted and input image are engaged to low and high resolution layers in the CNN model. The proposed network is then optimized based on stochastic orthogonality. We also built a novel subcompact vehicle dataset that will be open for a public use. Experimental results show that the proposed model outperforms state-of-the-art approaches in term of accuracy, which means that the proposed method can efficiently classify the ambiguous features between subcompact and non-subcompact vehicles.
A Novel Chemical Gas Vapor Sensor Based on Photoluminescence Enhancement of Rugate Porous Silicon Filters
Authors: Zhou Zicheng , Sohn Honglae
Published: May 2020

In this study, an innovative rugate filter configuration porous silicon (PSi) with enhanced photoluminescence intensity was fabricated. The fabricated PSi exhibited dual optical properties with both sharp optical reflectivity and sharp photoluminescence (PL), and it was developed for use in organic vapor sensing. When the wavelength of the resonance peak from the rugate PSi filters is engineered to overlap with the emission band of the PL from the PSi quantum dots, the PL intensity is amplified, thus reducing the full width at half maximum (FWHM) of the PL band from 154 nm to 22 nm. The rugate PSi filters samples were fabricated by electrochemical etching of highly doped n-type silicon under illumination. The etching solution consisted of a 1:1 volume mixture of 48% hydrofluoric acid and absolute ethanol and photoluminescent rugate PSi filter was fabricated by etching while using a periodic sinusoidal wave current with 10 cycles. The obtained samples were characterized by scanning electron microscopy (SEM), and both reflection redshift and PL quenching were measured under exposure to organic vapors. The reflection redshift and PL quenching were both affected by the vapor pressure and dipole moment of the organic species.
A Proposed Method to Assess the Mechanical Properties of Treadmill Surfaces
Authors: Colino Enrique , Garcia-Unanue Jorge , Van Hooren Bas , Gallardo Leonor , Meijer Kenneth , Lucia Alejandro , Felipe Jose Luis
Published: May 2020

The aim of this study was to define a reliable and sensitive test method for assessing Shock Absorption (SA), Vertical Deformation (VD), and Energy Restitution (ER) in treadmill surfaces. A total of 42 treadmills belonging to four different models were included in the study: (a) Technogym Jog700 Excite (n = 10), (b) Technogym Artis Run (n = 12), (c) LifeFitness Integrity Series 97T (n = 11), and (d) LifeFitness Integrity Series DX (n = 9). An advanced artificial athlete (AAA) device was used to assess SA, VD, and ER at three different locations along the longitudinal axis of each treadmill and in the support area of the athletes’ feet. For each location, our results show that the error assumed when performing one impact with the AAA instead of three (SA ≤ |0.1|%, VD ≤ |0.0| mm, and ER ≤ |0.2|%) is lower than the smallest changes that can be detected by the measuring device (SA = 0.4%, VD = 0.2 mm, and ER = 0.9%). Also, our results show the ability of the test method to detect meaningful differences between locations once the one-impact criterium is adopted, since absolute minimum differences between zones (SA: |0.6|%, VD: |0.3| mm, and ER: |1.2|%) were above the uncertainty of the measuring device. Therefore, performing a single impact with the AAA in each of the three locations described in this study can be considered a representative and reliable method for assessing SA, VD, and ER in treadmill surfaces.
Identifying Informal Settlements Using Contourlet Assisted Deep Learning
Authors: Ansari Rizwan Ahmed , Malhotra Rakesh , Buddhiraju Krishna Mohan
Published: May 2020

As the global urban population grows due to the influx of migrants from rural areas, many cities in developing countries face the emergence and proliferation of unplanned and informal settlements. However, even though the rise of unplanned development influences planning and management of residential land-use, reliable and detailed information about these areas is often scarce. While formal settlements in urban areas are easily mapped due to their distinct features, this does not hold true for informal settlements because of their microstructure, instability, and variability of shape and texture. Therefore, detecting and mapping these areas remains a challenging task. This research will contribute to the development of tools to identify such informal built-up areas by using an integrated approach of multiscale deep learning. The authors propose a composite architecture for semantic segmentation using the U-net architecture aided by information obtained from a multiscale contourlet transform. This work also analyzes the effects of wavelet and contourlet decompositions in the U-net architecture. The performance was evaluated in terms of precision, recall, F-score, mean intersection over union, and overall accuracy. It was found that the proposed method has better class-discriminating power as compared to existing methods and has an overall classification accuracy of 94.9–95.7%.
Identification of Risk Factors Associated with Obesity and Overweight—A Machine Learning Overview
Authors: Chatterjee Ayan , Gerdes Martin W. , Martinez Santiago G.
Published: May 2020

Social determining factors such as the adverse influence of globalization, supermarket growth, fast unplanned urbanization, sedentary lifestyle, economy, and social position slowly develop behavioral risk factors in humans. Behavioral risk factors such as unhealthy habits, improper diet, and physical inactivity lead to physiological risks, and “obesity/overweight” is one of the consequences. “Obesity and overweight” are one of the major lifestyle diseases that leads to other health conditions, such as cardiovascular diseases (CVDs), chronic obstructive pulmonary disease (COPD), cancer, diabetes type II, hypertension, and depression. It is not restricted within the age and socio-economic background of human beings. The “World Health Organization” (WHO) has anticipated that 30% of global death will be caused by lifestyle diseases by 2030 and it can be prevented with the appropriate identification of associated risk factors and behavioral intervention plans. Health behavior change should be given priority to avoid life-threatening damages. The primary purpose of this study is not to present a risk prediction model but to provide a review of various machine learning (ML) methods and their execution using available sample health data in a public repository related to lifestyle diseases, such as obesity, CVDs, and diabetes type II. In this study, we targeted people, both male and female, in the age group of >20 and <60, excluding pregnancy and genetic factors. This paper qualifies as a tutorial article on how to use different ML methods to identify potential risk factors of obesity/overweight. Although institutions such as “Center for Disease Control and Prevention (CDC)” and “National Institute for Clinical Excellence (NICE)” guidelines work to understand the cause and consequences of overweight/obesity, we aimed to utilize the potential of data science to assess the correlated risk factors of obesity/overweight after analyzing the existing datasets available in “Kaggle” and “University of California, Irvine (UCI) database”, and to check how the potential risk factors are changing with the change in body-energy imbalance with data-visualization techniques and regression analysis. Analyzing existing obesity/overweight related data using machine learning algorithms did not produce any brand-new risk factors, but it helped us to understand: (a) how are identified risk factors related to weight change and how do we visualize it? (b) what will be the nature of the data (potential monitorable risk factors) to be collected over time to develop our intended eCoach system for the promotion of a healthy lifestyle targeting “obesity and overweight” as a study case in the future? (c) why have we used the existing “Kaggle” and “UCI” datasets for our preliminary study? (d) which classification and regression models are performing better with a corresponding limited volume of the dataset following performance metrics?
Array Diagnosis and DOA Estimation for Coprime Array under Sensor Failures
Authors: Sun Bing , Wu Chenxi , Ruan Huailin
Published: May 2020

A coprime array of N sensors can achieve O ( N 2 ) degrees of freedom (DOFs) by possessing a uniform linear array segment of size O ( N 2 ) in the difference coarray. However, the structure of difference coarray is sensitive to sensor failures. Once the sensor fails, the impact of failure sensors on the coarray structure may decrease the DOFs and cause direction finding failure. Therefore, the direction of arrival (DOA) estimation of coprime arrays with sensor failures is a significant but challenging topic for investigation. Driven by the need for remedial measures, an efficient detection strategy is developed to diagnose the coprime array. Furthermore, based on the difference coarray, we divide the sensor failures into two scenarios. For redundant sensor failure scenarios, the structure of difference coarray remains unchanged, and the coarray MUSIC (CO-MUSIC) algorithm is applied for DOA estimation. For non-redundant sensor failure scenarios, the consecutive lags of the difference coarray will contain holes, which hinder the application of CO-MUSIC. We employ Singular Value Thresholding (SVT) algorithm to fill the holes with covariance matrix reconstruction. Specifically, the covariance matrix is reconstructed into a matrix with zero elements, and the SVT algorithm is employed to perform matrix completion, thereby filling the holes. Finally, we employ root-MUSIC for DOA estimation. Simulation results verify the effectiveness of the proposed methods.
A PCB Alignment System Using RST Template Matching with CUDA on Embedded GPU Board
Authors: Le Minh-Tri , Tu Ching-Ting , Guo Shu-Mei , Lien Jenn-Jier James
Published: May 2020

The fiducial-marks-based alignment process is one of the most critical steps in printed circuit board (PCB) manufacturing. In the alignment process, a machine vision technique is used to detect the fiducial marks and then adjust the position of the vision system in such a way that it is aligned with the PCB. The present study proposed an embedded PCB alignment system, in which a rotation, scale and translation (RST) template-matching algorithm was employed to locate the marks on the PCB surface. The coordinates and angles of the detected marks were then compared with the reference values which were set by users, and the difference between them was used to adjust the position of the vision system accordingly. To improve the positioning accuracy, the angle and location matching process was performed in refinement processes. To overcome the matching time, in the present study we accelerated the rotation matching by eliminating the weak features in the scanning process and converting the normalized cross correlation (NCC) formula to a sum of products. Moreover, the scanning time was reduced by implementing the entire RST process in parallel on threads of a graphics processing unit (GPU) by applying hash functions to find refined positions in the refinement matching process. The experimental results showed that the resulting matching time was around 32× faster than that achieved on a conventional central processing unit (CPU) for a test image size of 1280 × 960 pixels. Furthermore, the precision of the alignment process achieved a considerable result with a tolerance of 36.4 μm.
Lead-Wire-Resistance Compensation Technique Using a Single Zener Diode for Two-Wire Resistance Temperature Detectors (RTDs)
Authors: Li Wei , Xiong Shusheng , Zhou Xiaojun
Published: May 2020

In remote measurement systems, the lead wire resistance of the resistance sensor will produce a large measurement error. In order to ensure the accuracy of remote measurement, a novel lead-wire-resistance compensation technique is proposed, which is suitable for a two-wire resistance temperature detector. By connecting a zener diode in parallel with the resistance temperature detector (RTD) and an interface circuit specially designed for it, the lead-wire-resistance value can be accurately measured by virtue of the constant voltage characteristic of the zener diode when reverse breakdown occurs, and compensation can thereby be made when calculating the resistance of RTD. Through simulation verification and practical circuit testing, when the sensor resistance is in 848–2120 Ω scope and the lead wire resistance is less than 50 Ω, the proposed technology can ensure the measuring error of the sensor resistance within ±1 Ω and the temperature measurement error within ±0.3 °C for RTDs performing 1000 Ω at 0 °C. Therefore, this method is able to accurately compensate the measurement error caused by the lead wire resistance in two-wire RTDsand is suitable for most applications.
Entrepreneurial Governance and Local Growth
Authors: Olsson Amy Rader , Westlund Hans , Larsson Johan P.
Published: May 2020

Do local development policies influence local employment growth? Based on a survey to municipal managers in all Swedish municipalities, this is one of the first studies to empirically assess the relationship between reported local development initiatives (entrepreneurial governance (EG)) and growth of local employment. We find a weak but significant association between EG and employment growth for urban municipalities. This suggests that EG is more effective in larger, growing municipalities than in smaller, declining rural areas. Urban municipalities may of course have more resources for entrepreneurial governance than rural ones as they have grown substantially faster for a long period of time. The result thus indicates that EG and growth are in a positive interplay of interaction. When the EG index was divided into three sub-indexes after the entrepreneurial process (discover or create opportunities, collect resources and exploit opportunities) the analyses also showed positive correspondence between some sub-indexes and employment growth for the rural municipalities, indicating that EG is not solely a phenomenon connected to growth in urban, growing municipalities. In sum, the article indicates several avenues through which entrepreneurial governance at local level might be linked to local growth.
Flat Glass or Crystal Dome Aperture? A Year-Long Comparative Analysis of the Performance of Light Pipes in Real Residential Settings and Climatic Conditions
Authors: Sibley Magda , Peña-García Antonio
Published: May 2020

This paper presents the first comparative study of its type of the performance of light pipes with different types of apertures: a flat glass versus a bohemian crystal dome. Measurements were taken at 20-minute intervals over a period of one year in the bathrooms of two newly built identical houses of the same orientation located in Manchester, UK. The comparative analysis of the data collected for both light pipes types reveals that the crystal domed aperture consistently outperforms the flat glass one. Furthermore, the difference in the recorded horizontal illuminance is most marked during the winter months and at the end of the one-year experiment, indicating that the crystal dome has better performance for low incident winter light and higher resistance for the long term effect of weathering and pollution. This study provides strong evidence based on long term real measurements. Such evidence informs architects’ decisions when weighing up the aesthetic considerations of a flat glass aperture versus the higher illumination levels afforded by a crystal dome aperture with higher resistance to weathering and pollution.
Land-Use/Land-Cover Changes and Its Contribution to Urban Heat Island: A Case Study of Islamabad, Pakistan
Authors: Sadiq Khan Muhammad , Ullah Sami , Sun Tao , Rehman Arif , Chen Liding
Published: May 2020

One of the essential anthropogenic influences on urban climate is land-use/land-cover (LULC) change due to urbanization, which has a direct impact on land surface temperature (LST). However, LULC changes affect LST, and further, urban heat island (UHI) still needs to be investigated. In this study, we estimated changes in LULC from 1993 to 2018, its warming (positive) and cooling (negative) effect, and their contribution to relative LST (RLST) in the city of Islamabad using satellite remote-sensing data. The LULC was classified using a random forest (RF) classifier, and LST was retrieved by a standardized radiative transfer equation (RTE). Our results reveal that the impervious surfaces has increased by 11.9% on the cost of declining barren land, forest land, grass/agriculture land, and water bodies in the last 26 years. LULC conversion contributed warming effects such as forest land, water bodies, and grass/agriculture land transformed into impervious surfaces, inducing a warming contribution of 1.52 °C. In contrast, the replacement of barren land and impervious surfaces by forest land and water bodies may have a cooling contribution of −0.85 °C to RLST. Furthermore, based on the standardized scale (10%) of LULC changes, the conversion of forest land into impervious surfaces contributed 1% compared to back conversion by −0.2%. The positive contribution to UHI due to the transformation of a natural surface to the human-made surface was found higher than the negative (cooler) contribution due to continued anthropogenic activities. The information will be useful for urban managers and decision makers in land-use planning to control the soaring surface temperature for a comfortable living environment and sustainable cities.
Understanding the Transit Market: A Persona-Based Approach for Preferences Quantification
Authors: Eldeeb Gamal , Mohamed Moataz
Published: May 2020

The study aims at utilizing a persona-based approach in understanding, and further quantifying, the preferences of the key transit market groups and estimating their willingness to pay (WTP) for service improvements. The study adopted an Error Component (EC) interaction choice model to investigate personas’ preferences in a bus service desired quality choice experiment. Seven personas were developed based on four primary characteristics: travel behaviour, employment status, geographical distribution, and Perceived Behavioural Control (PBC). The study utilized a dataset of 5238 participants elicited from the Hamilton Street Railway Public Engagement Survey, Ontario, Canada. The results show that all personas, albeit significantly different in magnitude, are negatively affected by longer journey times, higher trip fares, longer service headways, while positively affected by reducing the number of transfers per trip and real-time information provision. The WTP estimates show that, in general, potential users are more likely to have higher WTP values compared to current users except for at-stop real-time information provision. Also, there is no consensus within current users nor potential users on the WTP estimates for service improvements. Finally, shared and unique preferences for service attributes among personas were identified to help transit agencies tailor their marketing/improvement plans based on the targeted segments.
Impact of Future Time Perspective on Entrepreneurial Career Intention for Individual Sustainable Career Development: The Roles of Learning Orientation and Entrepreneurial Passion
Authors: Kiani Ataullah , Liu Jingjiang , Ghani Usman , Popelnukha Anastasia
Published: May 2020

This study addressed the underlying mechanisms through which future time perspective (FTP) motivates entrepreneurial career intention. By focusing on entrepreneurship as an important career decision for individual sustainable career development, we argued that the generic use of a learning orientation approach mediates the effect of the presence of an extended FTP on individual entrepreneurial career intention. We also posited that entrepreneurial passion for founding moderates the relationship between learning orientation and individual entrepreneurial career intention. Using a survey data of 416 students attending a Chinese public sector university, we found that FTP enhanced learning orientation, which, in turn, stimulated entrepreneurial career intention. Moreover, the positive relationship between learning orientation and entrepreneurial career intention became strong as entrepreneurial passion for founding increased. Results were discussed in terms of implications for theory and practice.
Environmental Policy Stringency, Technical Progress and Pollution Haven Hypothesis
Authors: Sadik-Zada Elkhan Richard , Ferrari Mattia
Published: May 2020

The present inquiry provides a common ground for the analysis of two strands of literature, the environmental Kuznets curve (EKC) and the pollution haven hypothesis (PHH). To this end, the study sets out a simple variational model, which identifies the structural composition of the economy and the level of economic development as the primary determinants of the magnitude of the domestic environmental degradation. The juxtaposition of the mentioned literature strands undermines the optimistic view that economic growth, in the long run, leads to the reduction of atmospheric pollution. To assess the empirical validity of the pollution haven conjecture, the study employs the OECD Environmental Policy Stringency Index and the refined data on carbon emissions embodied in imports for the dataset of 26 OECD countries in the time interval between 1995 and 2011. By employing pooled mean group (PMG) estimators, the study, for the first time, accounts for a number of issues mentioned in the literature as factors that confine the inferential power of existing empirical studies on the EKC. The strong and robust confirmation of the pollution haven conjecture indicates that at least in the context of global common pool resources, a purely national perspective of the EKC is not satisfactory.
Sustainability of Both Pecking Order and Trade-Off Theories in Chinese Manufacturing Firms
Authors: Nguyen Huu Manh , Vuong Thi Huong Giang , Nguyen Thi Huong , Wu Yang-Che , Wong Wing-Keung
Published: May 2020

Our study investigates Chinese manufacturing firms listed on both the Shanghai and the Shenzhen Stock Exchanges. These firms follow the pecking order or trade-off theories in their capital structure choices. Using panel data from the Taiwan Economic Journal and quantile regression, we construct three models to compare the two theories. Our first model tests the impact of profitability, tangible asset, firm size, and investment opportunities on leverage; our second model adds the dividend payout ratio to test the robustness of the first model; and our third model tests how leverage, profitability, firm size, and dividend variables affect a firm’s investments. From the results of all the models used in our study, we find a negative relationship between leverage and both profitability and the dividend payout ratio and a positive relationship between leverage and growth in a firm’s investments. We also find a negative relationship between dividends, firm size, and growth in a firm’s investments and a positive relationship between investment capital and profitability. The overall results indicate that the capital structure decisions of Chinese manufacturing firms are best explained by the pecking order theory.
Data Usage and Access Control in Industrial Data Spaces: Implementation Using FIWARE
Authors: Munoz-Arcentales Andres , López-Pernas Sonsoles , Pozo Alejandro , Alonso Álvaro , Salvachúa Joaquín , Huecas Gabriel
Published: May 2020

In recent years, a new business paradigm has emerged which revolves around effectively extracting value from data. In this scope, providing a secure ecosystem for data sharing that ensures data governance and traceability is of paramount importance as it holds the potential to create new applications and services. Protecting data goes beyond restricting who can access what resource (covered by identity and Access Control): it becomes necessary to control how data are treated once accessed, which is known as data Usage Control. Data Usage Control provides a common and trustful security framework to guarantee the compliance with data governance rules and responsible use of organizations’ data by third-party entities, easing and ensuring secure data sharing in ecosystems such as Smart Cities and Industry 4.0. In this article, we present an implementation of a previously published architecture for enabling access and Usage Control in data-sharing ecosystems among multiple organizations using the FIWARE European open source platform. Additionally, we validate this implementation through a real use case in the food industry. We conclude that the proposed model, implemented using FIWARE components, provides a flexible and powerful architecture to manage Usage Control in data-sharing ecosystems.
Establishing a Sustainable Waste Management System in a Transitional Economic Context: Analysis of the Socio-Economic Dynamics
Authors: Fehr Andreas , Urushadze Teo , Zöller Nikolas , Knerr Béatrice , Ploeger Angelika , Vogtmann Hartmut
Published: May 2020

Establishing a sustainable waste management system concerns multiple aspects of the prospected geo-locations. Among them, the dynamics of the socio-economy play a crucial role. Based on the idea of circular economy (CE), the amount of waste, in general, should be reduced and the process of social involvement is embedded. This study aims to examine the social willingness towards a sustainable waste management system at a local level in Georgia. The research study was conducted with waste management analyses in Marneuli city in the South-Eastern Georgian district of Kvemo Kartli, as well as a survey in 510 households in Marneuli. A descriptive statistical analysis and a narrative analysis were used to evaluate the results of the survey. In Georgia, as a transitional country, local participation is still not well developed. However, this research study shows that the potentiality and the social request for the environmental actions at a local level exist. The key results of this study are that the robust connection with the locals is a fundamental factor in implementing a sustainable waste management plan at a local level.
Long-Term Monitoring of Soil Carbon Sequestration in Woody and Herbaceous Bioenergy Crop Production Systems on Marginal Lands in Southern Ontario, Canada
Authors: Bazrgar Amir Behzad , Ng Aeryn , Coleman Brent , Ashiq Muhammad Waseem , Gordon Andrew , Thevathasan Naresh
Published: May 2020

Enhancement of terrestrial carbon (C) sequestration on marginal lands in Canada using bioenergy crops has been proposed. However, factors influencing system-level C gain (SLCG) potentials of maturing bioenergy cropping systems, including belowground biomass C and soil organic carbon (SOC) accumulation, are not well documented. This study, therefore, quantified the long-term C sequestration potentials at the system-level in nine-year-old (2009–2018) woody (poplar clone 2293–29 (Populus spp.), hybrid willow clone SX-67 (Salix miyabeana)), and herbaceous (miscanthus (Miscanthus giganteus var. Nagara), switchgrass (Panicum virgatum)) bioenergy crop production systems on marginal lands in Southern Ontario, Canada. Results showed that woody cropping systems had significantly higher aboveground biomass C stock of 10.02 compared to 7.65 Mg C ha−1 in herbaceous cropping systems, although their belowground biomass C was not significantly different. Woody crops and switchgrass were able to increase SOC significantly over the tested period. However, when long term soil organic carbon (∆SOC) gains were compared, woody and herbaceous biomass crops gained 11.0 and 9.8 Mg C ha−1, respectively, which were not statistically different. Results also indicate a significantly higher total C pool [aboveground + belowground + soil organic carbon] in the willow (103 Mg ha−1) biomass system compared to other bioenergy crops. In the nine-year study period, woody crops had only 1.35 Mg C ha−1 more SLCG, suggesting that the influence of woody and herbaceous biomass crops on SLCG and ∆SOC sequestrations were similar. Further, among all tested biomass crops, willow had the highest annual SLCG of 1.66 Mg C ha−1 y−1.
Millennials’ Sleep and Unethical Behavior: Testing the Relationship between Sleep and Academic Dishonesty of Millennials in a Korean University
Authors: Ha Seongwook
Published: May 2020

This study empirically examined the impact of sleep quantity and sleep quality on academic dishonesty as a kind of unethical behavior with a sample of 237 millennials in a Korean university. Sleep quantity was calculated by subtracting bedtime, sleep latency, and wake after sleep onset (WASO) from wake-up time. Sleep quality was measured with the Insomnia Scale developed by Jenkins et al. (1988), and all items are reverse coded. Plagiarism and attitudes toward academic dishonesty (ATAD) were selected as unethical behaviors of millennials at the university. The results of this study are as follows: (1) sleep quantity and sleep quality have negative relationships with ego depletion; (2) ego depletion has no significant relationship with plagiarism or ATAD; (3) sleep quantity has no relationship with plagiarism or ATAD; (4) sleep quality has negative relationships with plagiarism and ATAD; (5) all four indirect effects of sleep quantity and sleep quality on plagiarism and ATAD through ego depletion are not significant. Based on the results, theoretical and practical implications are discussed, and the limitations of this study and recommendations for future research are provided.
Study on the Impact of Residential Outdoor Environments on Mood in the Elderly in Guangzhou, China
Authors: Chen Chongxian , Luo Weijing , Kang Ning , Li Haiwei , Yang Xiaohao , Xia Yu
Published: May 2020

Understanding the relationship between mood and the environment among the elderly is important for the healthy aging agenda. This study aimed to investigate the relationship between residential outdoor environments of different qualities and mood in the elderly. Nine residential neighborhoods across three different quality levels of the outdoor environment in Guangzhou, China, were surveyed. Measures included demographic characteristics, assessment of the residential outdoor environment, and mood status of the elderly. We constructed a group of multiple regression models to investigate influencing environmental factors of participants’ mood. Results revealed that the environmental factors influencing mood in the elderly are different across the three types of residential outdoor environments: function and cleanliness of the site showed a significant correlation with mood in high-quality residences, while pavement was significantly correlated with mood in medium-quality residences. In contrast, transparency, enclosure, greenness, temperature, and humidity were significantly correlated with mood in poor-quality residences. To promote mental health in the elderly, we recommend that different qualities of residential outdoor environments should be considered individually rather than aggregated as simply “outdoor space.” The findings of this study are expected to contribute to create age-friendly communities for an aging society.
Individual Green Certificates on Blockchain: A Simulation Approach
Authors: Zhao Fangyuan , Guo Xin , Chan Wai Kin (Victor)
Published: May 2020

Distributed renewable energy offers an exciting opportunity for sustainable transition and climate change mitigation. However, it is overlooked in most of the conventional tradable green certificates programs. Blockchain shows an advantage of incorporating a galaxy of distributed prosumers in a transparent and low-cost manner. This paper proposes I-Green, a blockchain-based individual green certificates system for promoting voluntary adoption of distributed renewable energy. Combing the features of blockchain technology and the theories of social norm and peer effects, the novel green ratio incentive scheme and proof of generation consensus protocol are designed for I-Green. A blockchain simulator is constructed to evaluate the effectiveness and efficiency of I-Green system. The simulation results present its potential for facilitating widespread adoption of distributed generation, and confirm the feasibility of blockchain as the information communication technology (ICT).
The Endless Challenges of Arboviral Diseases in Brazil
Authors: Magalhaes Tereza , Chalegre Karlos Diogo M. , Braga Cynthia , Foy Brian D.
Published: May 2020

In this Editorial, we list and discuss some of the main challenges faced by the population and public health authorities in Brazil concerning arbovirus infections, including the occurrence of concurrent epidemics like the ongoing SARS-CoV-2/COVID-19 pandemic.
Description of a Novel Mycovirus in the Phytopathogen Fusarium culmorum and a Related EVE in the Yeast Lipomyces starkeyi
Authors: Mahillon Mathieu , Romay Gustavo , Liénard Charlotte , Legrève Anne , Bragard Claude
Published: May 2020

A new mycovirus was found in the Fusarium culmorum strain A104-1 originally sampled on wheat in Belgium. This novel virus, for which the name Fusarium culmorum virus 1 (FcV1) is suggested, is phylogenetically related to members of the previously proposed family ‘’Unirnaviridae’’. FcV1 has a monopartite dsRNA genome of 2898 bp that harbors two large non-overlapping ORFs. A typical -1 slippery motif is found at the end of ORF1, advocating that ORF2 is translated by programmed ribosomal frameshifting. While ORF2 exhibits a conserved replicase domain, ORF1 encodes for an undetermined protein. Interestingly, a hypothetically transcribed gene similar to unirnaviruses ORF1 was found in the genome of Lipomyces starkeyi, presumably resulting from a viral endogenization in this yeast. Conidial isolation and chemical treatment were unsuccessful to obtain a virus-free isogenic line of the fungal host, highlighting a high retention rate for FcV1 but hindering its biological characterization. In parallel, attempt to horizontally transfer FcV1 to another strain of F. culmorum by dual culture failed. Eventually, a screening of other strains of the same fungal species suggests the presence of FcV1 in two other strains from Europe.
Eco-Epidemiological Evidence of the Transmission of Avian and Human Influenza A Viruses in Wild Pigs in Campeche, Mexico
Authors: Maya-Badillo Brenda Aline , Ojeda-Flores Rafael , Chaves Andrea , Reveles-Félix Saul , Orta-Pineda Guillermo , Martínez-Mercado María José , Saavedra-Montañez Manuel , Segura-Velázquez René , Sanvicente Mauro , Sánchez-Betancourt José Iván
Published: May 2020

Influenza, a zoonosis caused by various influenza A virus subtypes, affects a wide range of species, including humans. Pig cells express both sialyl-α-2,3-Gal and sialyl-α-2,6-Gal receptors, which make them susceptible to infection by avian and human viruses, respectively. To date, it is not known whether wild pigs in Mexico are affected by influenza virus subtypes, nor whether this would make them a potential risk of influenza transmission to humans. In this work, 61 hogs from two municipalities in Campeche, Mexico, were sampled. Hemagglutination inhibition assays were performed in 61 serum samples, and positive results were found for human H1N1 (11.47%), swine H1N1 (8.19%), and avian H5N2 (1.63%) virus variants. qRT-PCR assays were performed on the nasal swab, tracheal, and lung samples, and 19.67% of all hogs were positive to these assays. An avian H5N2 virus, first reported in 1994, was identified by sequencing. Our results demonstrate that wild pigs are participating in the exposure, transmission, maintenance, and possible diversification of influenza viruses in fragmented habitats, highlighting the synanthropic behavior of this species, which has been poorly studied in Mexico.
Safety Profile of a Virus-Like Particle-Based Vaccine Targeting Self-Protein Interleukin-5 in Horses
Authors: Jonsdottir Sigridur , Fettelschoss Victoria , Olomski Florian , Talker Stephanie C. , Mirkovitch Jelena , Rhiner Tanya , Birkmann Katharina , Thoms Franziska , Wagner Bettina , Bachmann Martin F. , Kündig Thomas M. , Marti Eliane , Fettelschoss-Gabriel Antonia
Published: May 2020

Background: Insect bite hypersensitivity (IBH) is an eosinophilic allergic dermatitis of horses caused by type I/IVb reactions against mainly Culicoides bites. The vaccination of IBH-affected horses with equine IL-5 coupled to the Cucumber mosaic virus-like particle (eIL-5-CuMVTT) induces IL-5-specific auto-antibodies, resulting in a significant reduction in eosinophil levels in blood and clinical signs. Objective: the preclinical and clinical safety of the eIL-5-CuMVTT vaccine. Methods: The B cell responses were assessed by longitudinal measurement of IL-5- and CuMVTT-specific IgG in the serum and plasma of vaccinated and unvaccinated horses. Further, peripheral blood mononuclear cells (PBMCs) from the same horses were re-stimulated in vitro for the proliferation and IFN-γ production of specific T cells. In addition, we evaluated longitudinal kidney and liver parameters and the general blood status. An endogenous protein challenge was performed in murine IL-5-vaccinated mice. Results: The vaccine was well tolerated as assessed by serum and cellular biomarkers and also induced reversible and neutralizing antibody titers in horses and mice. Endogenous IL-5 stimulation was unable to re-induce anti-IL-5 production. The CD4+ T cells of vaccinated horses produced significantly more IFN-γ and showed a stronger proliferation following stimulation with CuMVTT as compared to the unvaccinated controls. Re-stimulation using E. coli-derived proteins induced low levels of IFNγ+CD4+ cells in vaccinated horses; however, no IFN-γ and proliferation were induced following the HEK-eIL-5 re-stimulation. Conclusions: Vaccination using eIL-5-CuMVTT induces a strong B-cell as well as CuMVTT-specific T cell response without the induction of IL-5-specific T cell responses. Hence, B-cell unresponsiveness against self-IL-5 can be bypassed by inducing CuMVTT carrier-specific T cells, making the vaccine a safe therapeutic option for IBH-affected horses.