bluuebunny/crossref_metadata_2025 huggingface dataset:
An Investigation on the Use by Academic Researchers of Knowledge from Scientific Social Networking Sites
Authors: Corvello Vincenzo , Chimenti Maria Cristina , Giglio Carlo , Verteramo Saverino
Published: November 2020

Scientific social networking sites like ResearchGate or Academia.edu have become part of the work practice of academic researchers. These digital platforms have been designed precisely to encourage the exchange of knowledge between scholars and to help the expansion of collaborative networks among them. Even if studies on this topic have multiplied in recent years, there is a dearth of research on the actual impact of these platforms on scientific production. The goal of this study is to investigate the relationship between the attitude of researchers towards scientific social networks and the use of knowledge in their scientific work. Data from users of the scientific social networking site ResearchGate were collected. A total of 143 valid responses were received and structural equation modeling was applied for data analysis. Findings of this study confirmed that researchers use knowledge obtained from scientific social networking sites both incorporating it within their research products and to acquire new competences. In particular approaching the platform as a scientific community with a shared language and a shared vision was found to have a positive impact on knowledge use. To the best knowledge of the authors this is the first study investigating the actual use of knowledge from scientific social networking sites by academic researchers. Results help us to understand the impact of these platforms on the work practice of a strategic sector like scientific research.
Social Entrepreneurship Education as an Innovation Hub for Building an Entrepreneurial Ecosystem: The Case of the KAIST Social Entrepreneurship MBA Program
Authors: Kim Moon Gyu , Lee Ji-Hwan , Roh Taewoo , Son Hosung
Published: November 2020

As social problems become more extensive and diverse, one of the most critical capabilities of social entrepreneurs is connecting and aligning various stakeholders. Social entrepreneurs can solve problems better through collaboration with stakeholders, and this leads to sustainable innovation of society. Accordingly, social entrepreneurship education (SEE) programs should be designed and operated to cultivate social entrepreneurs’ abilities to enhance connectivity with all relevant entities of the social enterprise ecosystem. Consequently, SEE can form ever-growing communities of social entrepreneurs while functioning as innovation hubs for entrepreneurial ecosystems (EEs) evolving on their own. To this end, this study proposes a design and assessment framework for SEE. The framework emphasizes strengthening internal connectivity among SEE program members and external connectivity with outside entities, including universities, firms, government agencies, civil societies, and natural environments. This framework clarifies how and to whom social entrepreneurs should connect throughout the SEE process. This paper analyzes the case of an MBA degree SEE program in Korea using this framework and identifies directions for further improvement of SEE, contributing to the social entrepreneurship and entrepreneurship education literatures by integrating SEE’s key features with social theories of learning and the quintuple helix model for sustainable innovation ecosystems. Practically, our findings provide a useful benchmark to find isolated internal and external entities that need more active interactions to achieve SEE’s purposes.
The Impact of Corruption, Economic Freedom and Urbanization on Economic Development: Western Balkans versus EU-27
Authors: Feruni Nerajda , Hysa Eglantina , Panait Mirela , Rădulescu Irina Gabriela , Brezoi Alina
Published: November 2020

The topic of economic development has been addressed in recent decades from more and more points of view in order to identify the factors with significant impact on this phenomenon. Identifying the factors and measuring their impact on economic development are essential starting points for adopting the necessary public policies. Similar types of research for the Western Balkan countries and comparative analyses between the Western Balkans and the European Union countries are limited in number. Hence, the main purpose of this paper is to empirically test the impact of corruption, economic freedom, and urbanization on the economic development for both the Western Balkan countries and the EU countries for the period 2009–2018 to provide a comparative analysis for these two groups. The corruption perception index, economic freedom index, and urban population growth are chosen as independent variables, whereas the dependent variable of the human development index (HDI) represents economic development. Using the Random Effects model, which falls under the Panel Generalized Least Square method, the empirical analysis suggests that corruption has a negative impact on economic development, while economic freedom and urbanization have a positive impact on the economic development for both groups of countries. However, the impact of corruption is more destructive in the Western Balkans, and they appear to benefit more from economic freedom and urbanization as compared to the EU countries. Whether the impact of the chosen independent variables is restricted to any component of the HDI in particular is left open for further studies in the future, though the results of this paper are highly significant and in accordance with the reviewed literature.
Design of Isolated Microgrid System Considering Controllable EV Charging Demand
Authors: Chae Sang Heon , Kim Gi Hoon , Choi Yeong-Jun , Kim Eel-Hwan
Published: November 2020

Microgrid construction is promoted globally to solve the problems of energy inequality in island regions and the use of fossil fuels. In the application of a microgrid system, it is important to calculate the capacities of renewable energy sources and storage systems (ESSs) to ensure economic feasibility. In some microgrids that have recently had environmental challenges, there are island regions where the policy is to consider both the installation of the microgrid system and the supplement of electric vehicles (EV). However, an EV load pattern that does not match the solar radiation pattern may increase the required ESS capacity. Therefore, in this study, we designed and analyzed a method for reducing the microgrid system cost using a controllable EV charging load without the requirements of vehicle-to-grid technology and real-time pricing. The power system operations at similar capacities of photovoltaic and ESS were shown by applying EV charging control steps in 10% increments to analyze the effect of EV charging demand control on the microgrid. As a result of the proposed simulation, the amount of renewable power generation increased by 2.8 GWh over 20 years only by moving the charging load under the same conditions. This is an effect that can reduce CO2 by about 2.1 kTon.
Effect of The Physical Characteristics of a Dwelling on Energy Consumption and Emissions: The Case of Castellón And Valencia (Spain)
Authors: Martínez-Llorens Ana-María , de La Paz Paloma Taltavull , Mora-Garcia Raul-Tomas
Published: November 2020

This research analyses the relation between building and housing attributes and energy consumption and CO2 emissions, considering the spatial dependence present on the Spanish residential market and the different climatic areas. The paper uses a hedonic model with spatial correlation. To measure the spatial dependence, we have combined the Lag Model and the Error Model. The data has been obtained from three different sources and merged in a complex geolocated database, for the provinces of Castellón and Valencia. The results of both regressions indicate that there is a spatial dependence in the sample and a relation between some building attributes and energy consumption and CO2 emissions. The regressions show the existence of low consumption and low emission clusters in the metropolitan area of Valencia and Castellón. Moreover, the endogenous variables indicate that characteristics such as the age, the size, the typology of the house building or dwelling, the use of the surface, or the climatic area have an effect in the energy consumption and the CO2 emissions of the houses in Castellón and Valencia.
Current (2020) and Long-Term (2035 and 2050) Sustainable Potentials of Wood Fuel in Switzerland
Authors: Erni Matthias , Burg Vanessa , Bont Leo , Thees Oliver , Ferretti Marco , Stadelmann Golo , Schweier Janine
Published: November 2020

Wood fuel has become central in environmental policy and decision-making processes in cross-sectoral areas. Proper consideration of different types of woody biomass is fundamental in forming energy transition and decarbonization strategies. We quantified the development of theoretical (TPs) and sustainable (SPs) potentials of wood fuel from forests, trees outside forests, wood residues and waste wood in Switzerland for 2020, 2035 and 2050. Ecological and economic restrictions, timber market situations and drivers of future developments (area size, tree growth, wood characteristics, population growth, exporting/importing (waste wood)) were considered. We estimated a SP of wood fuel between 26.5 and 77.8 PJ/a during the three time points. Results demonstrate that the SP of wood fuel could be significantly increased already in the short term. This, as a moderate stock reduction (MSR) strategy in forests, can lead to large surpluses in SPs compared to the wood fuel already used today (~36 PJ/a), with values higher by 51% (+18.2 PJ) in 2020 and by 59% (+21.3 PJ) in 2035. To implement these surpluses (e.g., with a cascade approach), a more circular economy with sufficient processing capacities of the subsequent timber industries and the energy plants to convert the resources is required.
The Influence of Cleaning Frequency of Photovoltaic Modules on Power Losses in the Desert Climate
Authors: Shah Ali Hasan , Hassan Ahmed , Laghari Mohammad Shakeel , Alraeesi Abdulrahman
Published: November 2020

Dust accumulation on the photovoltaic (PV) surface decreases the solar radiation penetration to the PV cells and, eventually, the power production from the PV system. To prevent dust-based power losses, PV systems require frequent cleaning, the frequency of which depends on the geographical location, PV integration scheme, and scale of the PV power plant. This study aims to measure the drop-in radiation intensity, as well as power output, due to dust and to determine the optimal time interval for PV cleaning in the United Arab Emirates (UAE) climate. In this research, a dusting study experiment was carried out at the Renewable Energy Laboratory, Falaj Hazza Campus, UAE University, Al Ain, UAE, for 3.5 months, from 22 April 2018 to 7 August 2018. To measure the pure radiation losses caused by the dust, four transparent glasses were used to mimic the top glass cover of the PV modules. The dusting induced power losses were measured for four selected PV cleaning frequencies (10 days, 20 days, 1 month, and 3 months). This study revealed that up to 13% of power losses occurred in PV panels that remained dusty for 3 months, compared to panels that were cleaned daily. PV cleaning after 15 days brought the losses down to 4%, which was found the most feasible time for PV cleaning in this study, considering a reasonable balance between the cleaning cost and energy wasted due to soiling.
Decolonizing Methodologies, Situated Resilience, and Country: Insights from Tayal Country, Taiwan
Authors: Chen Yayut Yishiuan
Published: November 2020

This paper addresses the methodological challenges of working with Indigenous peoples in the Anthropocene. Drawing from the author’s geographical fieldwork with Tayal people, one of sixteen nationally recognized Indigenous groups in Taiwan, it argues that ontological shift is required in the dominant ways of thinking about resilience research. After reviewing a well-adopted Australian custom called ‘Acknowledgement of Country’, the paper addresses the concept of Indigenizing methodology and mobilizing the concepts of ‘Country’ and ‘situated resilience’ in Tayal settings. Finally, the paper proposes methodological principles for better engaging Indigenous knowledge in a more-than-human world on an ethical and constructive basis, as well as its implications for resilience research.
Linkages among Soil Properties and Litter Quality in Agroforestry Systems of Southeastern Brazil
Authors: Matos Priscila S. , Fonte Steven J. , Lima Sandra S. , Pereira Marcos G. , Kelly Courtland , Damian Júnior M. , Fontes Marcelo A. , Chaer Guilherme M. , Brasil Felipe C. , Zonta Everaldo
Published: November 2020

Agroforestry systems have been promoted as a solution to address trade-offs between environmental conservation efforts and the need for increased agricultural productivity on smallholder farms in Brazil. However, the impact of land use change from degraded pasture to agroforestry on soil properties remains unclear. The objectives of this research were to: (1) assess soil chemical, physical and biological properties across distinct land uses (degraded pasture, agroforestry and secondary forest); and (2) understand relationships between litter quality, soil organic matter (SOM) and key soil quality parameters in the Brazilian Atlantic Rainforest. Soils, macroinvertebrates and litter were collected in April and September of 2018 under five land uses, including: three types of agroforestry systems, a degraded pasture and a secondary forest in Sapucaia, Rio de Janeiro, Brazil. Our results showed that soil properties clearly separated the three agroforestry systems plots (AS1, AS2, AS3) from the forest and pasture plots. Moreover, litter quality and SOM likely influence multiple biological and physiochemical soil properties under agroforestry systems and secondary forest. Our findings suggest that agroforestry systems can help support soil biological, chemical and physical properties and that the litter quality may be an important driver of their effects and potential contributions to soil restoration in the region.
Implications of Network Diversity for Venture Growth: The Mediation Effect of Entrepreneurial Alertness
Authors: Zhao Wu , Li Jizhen , Li Xiaohua , Schøtt Thomas
Published: November 2020

This paper extends the conventional wisdom of social networks and entrepreneurship by clarifying the relationship between network diversity and venture growth as well as by studying the mediation effect of entrepreneurial alertness on network diversity. It highlights the importance of diverse networks for providing heterogeneous information and resources, which is the antecedent of entrepreneurial alertness. In this paper, Global Entrepreneurship Monitor (GEM) data from 44 countries are used in our analysis, considering the country’s impact. Overall, we concluded that network diversity can significantly predict entrepreneurial alertness, and a venture’s growth. Furthermore, an entrepreneur’s educational level and entrepreneurial experience have positive moderating effects on the relationship between network diversity and entrepreneurial alertness.
Sustainable Tourism and Facilities Preferences: The Sustainable Tourist Stay Scale (STSS) Validation
Authors: Fermani Alessandra , Sergi Maria Rita , Carrieri Angelo , Crespi Isabella , Picconi Laura , Saggino Aristide
Published: November 2020

This study aims to start the development of the Sustainable Tourist Stay Scale (STSS), a self-report instrument designed to measure tourists’ preferences regarding the degree to which they accept accommodation and programs in tourism facilities with sustainable characteristics. The research involved a total sample of 621 participants aged 18 to 74 (m = 41.75%; f = 58.25%). According to the literature and the available data, we considered the possibility that young people (millennials) and adults within the same sample may show peculiarities concerning the sustainability issues. We carried out three subsequent analyses: (1) an explorative factor analysis; (2) a confirmatory factor analysis via structural equation modelling; (3) the test of the structural invariance between young people and adults. The results supported a three-factor scale solution and they are discussed with reference to their potential practical applications to better understanding the preference for a sustainable stay.
On the Settlement of the Floating Population in the Pearl River Delta: Understanding the Factors of Permanent Settlement Intention versus Housing Purchase Actions
Authors: Wang Yuqu , Wang Zehong , Zhou Chunshan , Liu Ying , Liu Song
Published: November 2020

Previous investigations of the settlement intentions of China’s floating population have been undermined by an oversimplification of the concepts and measurements related to settlement intentions. More attention should be paid to influencing factors from the theoretical framework of “place utility” in new periods. Based on this framework, we use a multinormal logistic regression model to explore the impact of economic, human capital, and social factors on migration intentions and housing purchase actions of the floating population in the Pearl River Delta. The results revealed that the floating population’s purchasing ability is generally lower than its willingness to settle down, and this population experiences an incomplete citizenization problem. Among the economic and human capital factors, family economic factors have become an important basis for the housing purchase actions of the floating population and may even be more important than their own economic income and education level. After the State Council implemented the “Notice of Further Promoting the Reform of the Hukou System”, the decision of whether to pass restrictions of urban hukou (household registration) acquisition threshold has played an important role in the settlement decisions of the floating population. The government should formulate settlement policies according to the characteristics of the floating population.
Reflecting on Partnerships of Sustainability Learning: Enacting a Lewin–Deleuze–Guattari Rhizome
Authors: Tillmanns Tanja , Salomão Filho Alfredo
Published: November 2020

This paper works towards the enactment of a Lewin–Deleuze–Guattari rhizome. We assemble Deleuze and Guattari’s principles of the rhizome, Lewin’s idea of re-education, and reflections on the performance of one of the authors in the lecture hall, bringing into being what could be a rhizomatic partnership approach to sustainability learning in a higher education setting. The reflections are based on experiences delivering a sustainability module within a business education context, mainly for international students in Germany. The purpose of this paper is to illuminate possibilities of student–teacher partnership assemblages, aiming to motivate sustainability change agency on “people-yet-to-come”: those who are open to enacting difference, or multifaceted, heterogeneous, and often partial transformations addressing the current plethora of contemporary crises.
Citizen Scientists Showed a Four-Fold Increase of Lynx Numbers in Lithuania
Authors: Balčiauskas Linas , Balčiauskienė Laima , Litvaitis John A. , Tijušas Eugenijus
Published: November 2020

By the early 2000s, Eurasian lynx (Lynx lynx) were nearly extirpated in Lithuania. To determine their status, we used snow-track counts in 2006–2012 and volunteer monitoring in 1999–2005 and 2015–2018. Using simple questionnaires, we collected incidental observations from hunters, foresters, and other interested citizens to estimate lynx distribution, abundance and extent of breeding. Citizen scientists provided 206 reports of 278 individual lynx that suggested expanding lynx distributions in central, western, southwestern, and southern parts of Lithuania. A decrease in range fragmentation has also been observed since 2015. Nationwide, the lynx population quadrupled from 2010 to 162 individuals in 2018. The number of breeding individuals reported was just seven in both 2007 and 2008, limited to two forests in the very north and central part of the country. This increased to 46 in 2015–2018. Our results indicate that the lynx population in Lithuania has increased and its conservation status should be reconsidered.
Influence of Characteristics of Metropolitan Areas on the Logistics Sprawl: A Case Study for Metropolitan Areas of the State of Paraná (Brazil)
Authors: Sousa Luísa Tavares Muzzi de , Oliveira Leise Kelli de
Published: November 2020

The concentration of warehouses in peripheral regions of metropolitan areas in a time period is called logistics sprawl (LS). Identifying this phenomenon could help to reduce externalities related to urban freight transport, mainly, the distance traveled. This paper examines the contribution of the characteristics of metropolitan areas on the logistics sprawl indicator. A case study was carried out considering data from eight metropolitan areas of the state of Paraná (Brazil). The research method is based on the data collection procedure proposed, centrographic method, and linear regression. The results of the centrographic method reveal a positive LS in four metropolitan areas and a negative LS in three metropolitan areas. In general, the warehouses are close to the highways that cross the metropolitan area. In addition, the size of the metropolitan area has a negative relationship with the number of warehouses and the logistics sprawl indicator. The findings highlight the importance of public policies relating to urban freight transport and land use at a metropolitan level.
Measurement and Verification of Zero Energy Settlements: Lessons Learned from Four Pilot Cases in Europe
Authors: Mavrigiannaki Angeliki , Gobakis Kostas , Kolokotsa Dionysia , Kalaitzakis Kostas , Pisello Anna Laura , Piselli Cristina , Gupta Rajat , Gregg Matt , Laskari Marina , Saliari Maria , Assimakopoulos Margarita-Niki , Synnefa Afroditi
Published: November 2020

Measurement and verification (M&V) has become necessary for ensuring intended design performance. Currently, M&V procedures and calculation methods exist for the assessment of Energy Conservation Measures (ECM) for existing buildings, with a focus on reliable baseline model creation and savings estimation, as well as for reducing the computation time, uncertainties, and M&V costs. There is limited application of rigorous M&V procedures in the design, delivery and operation of low/zero energy dwellings and settlements. In the present paper, M&V for four pilot net-zero energy settlements has been designed and implemented. The M&V has been planned, incorporating guidance from existing protocols, linked to the project development phases, and populated with lessons learned through implementation. The resulting framework demonstrates that M&V is not strictly linked to the operational phase of a project but is rather an integral part of the project management and development. Under this scope, M&V is an integrated, iterative process that is accompanied by quality control in every step. Quality control is a significant component of the M&V, and the proposed quality control procedures can support the preparation and implementation of automated M&V. The proposed framework can be useful to project managers for integrating M&V into the project management and development process and explicitly aligning it with the rest of the design and construction procedures.
MultiDefectNet: Multi-Class Defect Detection of Building Façade Based on Deep Convolutional Neural Network
Authors: Lee Kisu , Hong Goopyo , Sael Lee , Lee Sanghyo , Kim Ha Young
Published: November 2020

Defects in residential building façades affect the structural integrity of buildings and degrade external appearances. Defects in a building façade are typically managed using manpower during maintenance. This approach is time-consuming, yields subjective results, and can lead to accidents or casualties. To address this, we propose a building façade monitoring system that utilizes an object detection method based on deep learning to efficiently manage defects by minimizing the involvement of manpower. The dataset used for training a deep-learning-based network contains actual residential building façade images. Various building designs in these raw images make it difficult to detect defects because of their various types and complex backgrounds. We employed the faster regions with convolutional neural network (Faster R-CNN) structure for more accurate defect detection in such environments, achieving an average precision (intersection over union (IoU) = 0.5) of 62.7% for all types of trained defects. As it is difficult to detect defects in a training environment, it is necessary to improve the performance of the network. However, the object detection network employed in this study yields an excellent performance in complex real-world images, indicating the possibility of developing a system that would detect defects in more types of building façades.
Nonadiabatic Atomic-Like State Stabilizing Antiferromagnetism and Mott Insulation in MnO
Authors: Krüger Ekkehard
Published: November 2020

This paper reports evidence that the antiferromagnetic and insulating ground state of MnO is caused by a nonadiabatic atomic-like motion, as is evidently the case in NiO. In addition, it is shown that experimental findings on the displacements of the Mn and O atoms in the antiferromagnetic phase of MnO corroborate the presented suggestion that the rhombohedral-like distortion in antiferromagnetic MnO, as well as in antiferromagnetic NiO is an inner distortion of the monoclinic base-centered Bravais lattice of the antiferromagnetic phases.
An Efficient Parallel Extragradient Method for Systems of Variational Inequalities Involving Fixed Points of Demicontractive Mappings
Authors: Jolaoso Lateef Olakunle , Aphane Maggie
Published: November 2020

Herein, we present a new parallel extragradient method for solving systems of variational inequalities and common fixed point problems for demicontractive mappings in real Hilbert spaces. The algorithm determines the next iterate by computing a computationally inexpensive projection onto a sub-level set which is constructed using a convex combination of finite functions and an Armijo line-search procedure. A strong convergence result is proved without the need for the assumption of Lipschitz continuity on the cost operators of the variational inequalities. Finally, some numerical experiments are performed to illustrate the performance of the proposed method.
Optimization by Context Refinement for Development of Incremental Granular Models
Authors: Lee Myung-Won , Kwak Keun-Chang
Published: November 2020

Optimization by refinement of linguistic contexts produced from an output variable in the construction of an incremental granular model (IGM) is presented herein. In contrast to the conventional learning method using the backpropagation algorithm, we use a novel method to learn both the cluster centers of Gaussian fuzzy sets representing the symmetry in the premise part and the contexts of the consequent part in the if–then fuzzy rules. Hence, we use the fundamental concept of context-based fuzzy clustering and design with an integration of linear regression (LR) and granular fuzzy models (GFMs). This GFM is constructed based on the association between the triangular membership function produced both in the input–output variables. The context can be established by the system user or using an optimization method. Hence, we can obtain superior performances based on the combination of simple linear regression and local GFMs optimized by context refinement. Experimental results pertaining to coagulant dosing in a water purification plant and automobile miles per gallon prediction revealed that the presented method performed better than linear regression, multilinear perceptron, radial basis function networks, linguistic model, and the IGM.
Best Approximations by Increasing Invariant Subspaces of Self-Adjoint Operators
Authors: Lopushansky Oleh , Tłuczek-Piȩciak Renata
Published: November 2020

The paper describes approximations properties of monotonically increasing sequences of invariant subspaces of a self-adjoint operator, as well as their symmetric generalizations in a complex Hilbert space, generated by its positive powers. It is established that the operator keeps its spectrum over the dense union of these subspaces, equipped with quasi-norms, and that it is contractive. The main result is an inequality that provides an accurate estimate of errors for the best approximations in Hilbert spaces by these invariant subspaces.
Multi-Parameter Optimization of an InP Electro-Optic Modulator
Authors: Stepanenko Mikhail , Yunusov Igor , Arykov Vadim , Troyan Pavel , Zhidik Yury
Published: November 2020

In this article, a method for indium phosphide (InP) electro-optic modulator (EOM) optimization is introduced. The method can be used for the design and analysis of an EOM based on the Mach-Zehnder interferometer (MZI) design. This design is based on the division of the input optical signal into two optical paths and then, after processing, it combines the light into a single waveguide. The symmetry of the structure can provide state-of-the-art EOM characteristics with a push-pull control signal. Using a traveling wave electrode (TWE) design as a starting point, the authors varied the heterostructure design and optical waveguide parameters to obtain the optimal values of initial optical loss, evenness of the initial optical loss in the operating wavelength range, and the extinction ratio and length of the modulator arm. The key features of the proposed optimization method include the following: all independent input parameters are linked into a single system, where the relationship between the electrical and optical parameters of the modulator is realized; all physically realizable combinations of the input parameters are available for analysis; and EOM optimization is possible for one target parameter or for a group of target parameters. The results of the EOM optimization using the described method are presented.
Ontology-Based Decision Support Tool for Automatic Sleep Staging Using Dual-Channel EEG Data
Authors: Zhang Bingtao , Yang Zhifei , Cai Hanshu , Lian Jing , Chang Wenwen , Zhang Zhonglin
Published: November 2020

Sleep staging has attracted significant attention as a critical step in auxiliary diagnosis of sleep disease. To avoid subjectivity of doctor’s manual sleep staging, and to realize scientific management of massive physiological data, an ontology-based decision support tool is proposed. The tool implements an automated procedure for sleep staging using dual-channel electroencephalogram (EEG) signals. First of all, it encodes EEG features, sleep-related concepts and other contextual information to “EEG-Sleep ontology”. Secondly, a rule-set is constructed based on a data mining technique. Finally, the first two steps are processed in a reasoning engine which is automatically assign each 30 s epoch (segment) sleep stage to one of five possible sleep stages: WA, NREM1, NREM2, SWS and REM. The rule set is obtained using EEG data taken from the Sleep-EDF database [EXPANDED] according to the random forest algorithm (RF), we prove that the performance of the proposed method with 89.12% accuracy, and 0.81 Kappa statistics is superior to other algorithms such as Bayesian network, C4.5, support vector machine, and multilayer perceptron. Additionally, our proposed approach improved performance when compared to other studies using a small subset of the Sleep-EDF database [EXPANDED].
Performance Evaluation of Keyword Extraction Methods and Visualization for Student Online Comments
Authors: Liu Feng , Huang Xiaodi , Huang Weidong , Duan Sophia Xiaoxia
Published: November 2020

Topic keyword extraction (as a typical task in information retrieval) refers to extracting the core keywords from document topics. In an online environment, students often post comments in subject forums. The automatic and accurate extraction of keywords from these comments are beneficial to lecturers (particular when it comes to repeatedly delivered subjects). In this paper, we compare the performance of traditional machine learning algorithms and two deep learning methods in extracting topic keywords from student comments posted in subject forums. For this purpose, we collected student comment data from a period of two years, manually tagging part of the raw data for our experiments. Based on this dataset, we comprehensively compared the five typical algorithms of naïve Bayes, logistic regression, support vector machine, convolutional neural networks, and Long Short-Term Memory with Attention (Att-LSTM). The performances were measured by the four evaluation metrics. We further examined the keywords by visualization. From the results of our experiment and visualization, we conclude that the Att-LSTM method is the best approach for topic keyword extraction from student comments. Further, the results from the algorithms and visualization are symmetry, to some degree. In particular, the extracted topics from the comments posted at the same stages of different teaching sessions are, almost, reflection symmetry.
Automated Sustainable Multi-Object Segmentation and Recognition via Modified Sampling Consensus and Kernel Sliding Perceptron
Authors: Rafique Adnan Ahmed , Jalal Ahmad , Kim Kibum
Published: November 2020

Object recognition in depth images is challenging and persistent task in machine vision, robotics, and automation of sustainability. Object recognition tasks are a challenging part of various multimedia technologies for video surveillance, human–computer interaction, robotic navigation, drone targeting, tourist guidance, and medical diagnostics. However, the symmetry that exists in real-world objects plays a significant role in perception and recognition of objects in both humans and machines. With advances in depth sensor technology, numerous researchers have recently proposed RGB-D object recognition techniques. In this paper, we introduce a sustainable object recognition framework that is consistent despite any change in the environment, and can recognize and analyze RGB-D objects in complex indoor scenarios. Firstly, after acquiring a depth image, the point cloud and the depth maps are extracted to obtain the planes. Then, the plane fitting model and the proposed modified maximum likelihood estimation sampling consensus (MMLESAC) are applied as a segmentation process. Then, depth kernel descriptors (DKDES) over segmented objects are computed for single and multiple object scenarios separately. These DKDES are subsequently carried forward to isometric mapping (IsoMap) for feature space reduction. Finally, the reduced feature vector is forwarded to a kernel sliding perceptron (KSP) for the recognition of objects. Three datasets are used to evaluate four different experiments by employing a cross-validation scheme to validate the proposed model. The experimental results over RGB-D object, RGB-D scene, and NYUDv1 datasets demonstrate overall accuracies of 92.2%, 88.5%, and 90.5% respectively. These results outperform existing state-of-the-art methods and verify the suitability of the method.
In-Situ Observation of Pouring a High-Viscosity Liquid
Authors: Miyazawa Chisa , Sakagami Koichi , Konno Naoki , Nonomura Yoshimune
Published: November 2020

The rheology of liquids affects their ease of pouring. In this study, the subjects evaluated the feeling of pouring liquids with various viscosities. The situation was recorded with a high-speed camera and force plate. The score for ease of pouring water and 5 wt% thickened aqueous solution was 8.9 ± 1.5 and 2.1 ± 1.6 respectively, demonstrating that the score decreased with increasing viscosity. The three stages of the pouring process, namely the flowing state in which the liquid flows out vigorously (I), the yarning state in which the liquid flows out to stretch (II), and the dripping state in which the liquid flows out as droplets (III) were observed. The duration of state II extended as the viscosity increased. These findings can be useful for the development of characteristic containers and beverages.
Trends of Polychlorinated Compounds in the Surroundings of a Municipal Solid Waste Incinerator in Mataró (Catalonia, Spain): Assessing Health Risks
Authors: Nadal Martí , Marquès Montse , Mari Montse , Rovira Joaquim , Domingo José L.
Published: November 2020

Since 2008, the environmental levels of polychlorinated compounds near a municipal solid waste incinerator in Mataró (Catalonia, Spain) have been periodically monitored. The present study aimed at updating the data regarding the temporal changes occurred between 2015 and 2017, when air and soil samples were collected again, and the concentrations of the same chemical pollutants (i.e., polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), and polychlorinated biphenyls (PCBs)) were analysed. Furthermore, the health risks associated with their human exposure were also evaluated. The levels of all the contaminants in soil were far below the threshold established by regional and national legislations, also being lower than those observed in previous surveys. A similar trend was also noted for PCDD/Fs in air samples, while airborne PCBs were the only group of chemicals whose levels significantly increased. In any case, the global assessment of the data regarding the different pollutants and matrices indicates that there has not been a general increase in the environmental pollution around the facility. In addition, the environmental exposure to PCDD/Fs and PCBs by the population living nearby is still clearly lower than the dietary intake of these same chemical pollutants.
Epigenetic Modifications, and Alterations in Cell Cycle and Apoptosis Pathway in A549 Lung Carcinoma Cell Line upon Exposure to Perfluoroalkyl Substances
Authors: Jabeen Musarrat , Fayyaz Muhammad , Irudayaraj Joseph
Published: November 2020

Per- and polyfluoroalkyl substances (PFAS) are a group of human-made compounds with strong C-F bonds, and have been used in various manufacturing industries for decades. PFAS have been reported to deleterious effect on human health, which has led to studies identifying the possible toxicity and toxicity routes of these compounds. We report that these compounds have the potential to cause epigenetic modifications, and to induce dysregulation in the cell proliferation cycle as well as apoptosis in A549 lung cancer cells when exposed to 10-, 200- and 400 μM concentrations of each compound. Our studies show that exposure to perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) may cause hypomethylation in the epigenome, but changes in the epigenetic makeup are not evident upon exposure to GenX. We establish that exposure to lower doses of these compounds causes the cells’ balance to shift to cell proliferation, whereas exposure to higher concentrations shifts the balance more towards apoptosis. Furthermore, the apoptosis pathway upon exposure to GenX, PFOA, and PFOS has also been identified. Our findings suggest that exposure to any of these compounds may have profound effects in patients with pre-existing lung conditions or could trigger lung cancinogenesis.
Diversity Assessment of Toxic Cyanobacterial Blooms during Oxidation
Authors: Moradinejad Saber , Trigui Hana , Guerra Maldonado Juan Francisco , Shapiro Jesse , Terrat Yves , Zamyadi Arash , Dorner Sarah , Prévost Michèle
Published: November 2020

Fresh-water sources of drinking water are experiencing toxic cyanobacterial blooms more frequently. Chemical oxidation is a common approach to treat cyanobacteria and their toxins. This study systematically investigates the bacterial/cyanobacterial community following chemical oxidation (Cl2, KMnO4, O3, H2O2) using high throughput sequencing. Raw water results from high throughput sequencing show that Proteobacteria, Actinobacteria, Cyanobacteria and Bacteroidetes were the most abundant phyla. Dolichospermum, Synechococcus, Microcystis and Nostoc were the most dominant genera. In terms of species, Dolichospermum sp.90 and Microcystis aeruginosa were the most abundant species at the beginning and end of the sampling, respectively. A comparison between the results of high throughput sequencing and taxonomic cell counts highlighted the robustness of high throughput sequencing to thoroughly reveal a wide diversity of bacterial and cyanobacterial communities. Principal component analysis of the oxidation samples results showed a progressive shift in the composition of bacterial/cyanobacterial communities following soft-chlorination with increasing common exposure units (CTs) (0–3.8 mg·min/L). Close cyanobacterial community composition (Dolichospermum dominant genus) was observed following low chlorine and mid-KMnO4 (287.7 mg·min/L) exposure. Our results showed that some toxin producing species may persist after oxidation whether they were dominant species or not. Relative persistence of Dolichospermum sp.90 was observed following soft-chlorination (0.2–0.6 mg/L) and permanganate (5 mg/L) oxidation with increasing oxidant exposure. Pre-oxidation using H2O2 (10 mg/L and one day contact time) caused a clear decrease in the relative abundance of all the taxa and some species including the toxin producing taxa. These observations suggest selectivity of H2O2 to provide an efficient barrier against toxin producing cyanobacteria entering a water treatment plant.
Toxicity and Sublethal Effects of Autumn Crocus (Colchicum autumnale) Bulb Powder on Red Imported Fire Ants (Solenopsis invicta)
Authors: Lin Sukun , Qin Deqiang , Zhang Yue , Zheng Qun , Yang Liupeng , Cheng Dongmei , Huang Suqing , Chen Jianjun , Zhang Zhixiang
Published: November 2020

Autumn crocus (Colchicum autumnale L.) is a medicinal plant as it contains high concentrations of colchicine. In this study, we reported that the ground powder of autumn crocus bulb is highly toxic to invasive Solenopsis invicta Buren, commonly referred to as red imported fire ants (RIFAs). Ants fed with sugar water containing 5000 mg/L of bulb powder showed 54.67% mortality in three days compared to 45.33% mortality when fed with sugar water containing 50 mg/L of colchicine. Additionally, the effects of short-term feeding with sugar water containing 1 mg/L of colchicine and 100 mg/L of autumn crocus bulb powder were evaluated for RIFAs’ colony weight, food consumption, and aggressiveness, i.e., aggregation, grasping ability, and walking speed. After 15 days of feeding, the cumulative colony weight loss reached 44.63% and 58.73% due to the sublethal concentrations of colchicine and autumn crocus bulb powder, respectively. The consumption of sugar water and mealworm (Tenebrio molitor L.) was substantially reduced. The aggregation rates decreased 48.67% and 34.67%, grasping rates were reduced to 38.67% and 16.67%, and walking speed decreased 1.13 cm/s and 0.67 cm/s as a result of the feeding of the two sublethal concentrations of colchicine and autumn crocus bulb powder, respectively. Our results for the first time show that powder derived from autumn crocus bulbs could potentially be a botanical pesticide for controlling RIFAs, and application of such a product could be ecologically benign due to its rapid biodegradation in the environment.
X-ray Properties of 3C 111: Separation of Primary Nuclear Emission and Jet Continuum
Authors: Fedorova Elena , Hnatyk B.I. , Zhdanov V.I. , Del Popolo A.
Published: November 2020

3C111 is BLRG with signatures of both FSRQ and Sy1 in X-ray spectrum. The significant X-ray observational dataset was collected for it by INTEGRAL, XMM-Newton, SWIFT, Suzaku and others. The overall X-ray spectrum of 3C 111 shows signs of a peculiarity with the large value of the high-energy cut-off typical rather for RQ AGN, probably due to the jet contamination. Separating the jet counterpart in the X-ray spectrum of 3C 111 from the primary nuclear counterpart can answer the question is this nucleus truly peculiar or this is a fake “peculiarity” due to a significant jet contribution. In view of this question, our aim is to estimate separately the accretion disk/corona and non-thermal jet emission in the 3C 111 X-ray spectra within different observational periods. To separate the disk/corona and jet contributions in total continuum, we use the idea that radio and X-ray spectra of jet emission can be described by a simple power-law model with the same photon index. This additional information allows us to derive rather accurate values of these contributions. In order to test these results, we also consider relations between the nuclear continuum and the line emission.
Host Range and Coding Potential of Eukaryotic Giant Viruses
Authors: Sun Tsu-Wang , Yang Chia-Ling , Kao Tzu-Tong , Wang Tzu-Haw , Lai Ming-Wei , Ku Chuan
Published: November 2020

Giant viruses are a group of eukaryotic double-stranded DNA viruses with large virion and genome size that challenged the traditional view of virus. Newly isolated strains and sequenced genomes in the last two decades have substantially advanced our knowledge of their host diversity, gene functions, and evolutionary history. Giant viruses are now known to infect hosts from all major supergroups in the eukaryotic tree of life, which predominantly comprises microbial organisms. The seven well-recognized viral clades (taxonomic families) have drastically different host range. Mimiviridae and Phycodnaviridae, both with notable intrafamilial genome variation and high abundance in environmental samples, have members that infect the most diverse eukaryotic lineages. Laboratory experiments and comparative genomics have shed light on the unprecedented functional potential of giant viruses, encoding proteins for genetic information flow, energy metabolism, synthesis of biomolecules, membrane transport, and sensing that allow for sophisticated control of intracellular conditions and cell-environment interactions. Evolutionary genomics can illuminate how current and past hosts shape viral gene repertoires, although it becomes more obscure with divergent sequences and deep phylogenies. Continued works to characterize giant viruses from marine and other environments will further contribute to our understanding of their host range, coding potential, and virus-host coevolution.
Plant Virology Delivers Diverse Toolsets for Biotechnology
Authors: Wang Mo , Gao Shilei , Zeng Wenzhi , Yang Yongqing , Ma Junfei , Wang Ying
Published: November 2020

Over a hundred years of research on plant viruses has led to a detailed understanding of viral replication, movement, and host–virus interactions. The functions of vast viral genes have also been annotated. With an increased understanding of plant viruses and plant–virus interactions, various viruses have been developed as vectors to modulate gene expressions for functional studies as well as for fulfilling the needs in biotechnology. These approaches are invaluable not only for molecular breeding and functional genomics studies related to pivotal agronomic traits, but also for the production of vaccines and health-promoting carotenoids. This review summarizes the latest progress in these forefronts as well as the available viral vectors for economically important crops and beyond.
LysSAP26, a New Recombinant Phage Endolysin with a Broad Spectrum Antibacterial Activity
Authors: Kim Shukho , Jin Jong-Sook , Choi Yoon-Jung , Kim Jungmin
Published: November 2020

Multidrug-resistant (MDR) bacteria are a major threat to public health. Bacteriophage endolysins (lysins) are a promising alternative treatment to traditional antibiotics. However, the lysins currently under development are still underestimated. Herein, we cloned the lysin from the SAP-26 bacteriophage genome. The recombinant LysSAP26 protein inhibited the growth of carbapenem-resistant Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa, oxacillin-resistant Staphylococcus aureus, and vancomycin-resistant Enterococcus faecium with minimum inhibitory concentrations of 5~80 µg/mL. In animal experiments, mice infected with A. baumannii were protected by LysSAP26, with a 40% survival rate. Transmission electron microscopy analysis confirmed that LysSAP26 treatment resulted in the destruction of bacterial cell walls. LysSAP26 is a new endolysin that can be applied to treat MDR A. baumannii, E. faecium, S. aureus, K. pneumoniae, P. aeruginosa, and E. coli infections, targeting both Gram-positive and Gram-negative bacteria.