bluuebunny/crossref_metadata_2025 huggingface dataset:
Temperature-Dependent Synergistic Effect of Multi-Walled Carbon Nanotubes and Graphene Nanoplatelets on the Tensile Quasi-Static and Fatigue Properties of Epoxy Nanocomposites
Authors: Jen Yi-Ming , Chang Hao-Huai , Lu Chien-Min , Liang Shin-Yu
Published: December 2020

Even though the characteristics of polymer materials are sensitive to temperature, the mechanical properties of polymer nanocomposites have rarely been studied before, especially for the fatigue behavior of hybrid polymer nanocomposites. Hence, the tensile quasi-static and fatigue tests for the epoxy nanocomposites reinforced with multi-walled carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs) were performed at different temperatures in the study to investigate the temperature-dependent synergistic effect of hybrid nano-fillers on the studied properties. The temperature and the filler ratio were the main variables considered in the experimental program. A synergistic index was employed to quantify and evaluate the synergistic effect of hybrid fillers on the studied properties. Experimental results show that both the monotonic and fatigue strength decrease with increasing temperature significantly. The nanocomposites with a MWCNT (multi-walled CNT): GNP ratio of 9:1 display higher monotonic modulus/strength and fatigue strength than those with other filler ratios. The tensile strengths of the nanocomposite specimens with a MWCNT:GNP ratio of 9:1 are 10.0, 5.5, 12.9, 23.4, and 58.9% higher than those of neat epoxy at −28, 2, 22, 52, and 82 °C, respectively. The endurance limits of the nanocomposites with this specific filler ratio are increased by 7.7, 26.7, 5.6, 30.6, and 42.4% from those of pristine epoxy under the identical temperature conditions, respectively. Furthermore, the synergistic effect for this optimal nanocomposite increases with temperature. The CNTs bridge the adjacent GNPs to constitute the 3-D network of nano-filler and prevent the agglomeration of GNPs, further improve the studied strength. Observing the fracture surfaces reveals that crack deflect effect and the bridging effect of nano-fillers are the main reinforcement mechanisms to improve the studied properties. The pullout of nano-fillers from polymer matrix at high temperatures reduces the monotonic and fatigue strengths. However, high temperature is beneficial to the synergistic effect of hybrid fillers because the nano-fillers dispersed in the softened matrix are easy to align toward the directions favorable to load transfer.
Experimental and Numerical Analysis of a Low Environmental Impact Pyro-Gasification System for the Energetic Valorization of Waste through a Biomass Steam Power Plant
Authors: Gimelli Alfredo , Muccillo Massimiliano , Sannino Raniero , Braccio Giacobbe , Capone Vincenzo , Cornacchia Giacinto , Manganiello Matteo , Mongiello Carmine , Sharma Vinod Kumar
Published: December 2020

This paper addresses the study of a pyro-gasification plant designed, built, and operated to recover inert metals from different types of solid waste. Experimental tests were carried out using pulper as the solid waste. However, while a reliable composition analysis of the produced syngas was carried out, a precise composition evaluation of the pulper used during the experimental activities was not performed and the related data were characterized by unacceptable uncertainty. Therefore, with the aim of reliably characterizing the plant operation, a thermochemical model of the gasification process was setup to simulate the equilibrium operation of the plant and a vector optimization methodology was used to calibrate the numerical model. Then, a decision-making problem was solved to identify the most suitable optimal solution between those belonging to the Pareto optimal front, thus obtaining reliable composition data for the adopted pulper waste. In particular, four different identification criteria were applied for the selection of small subset of solutions over the 3138 dominant solutions found. Among them, the solution (i.e., set of calibration parameters) that minimizes the experimental-numerical difference between the lower heating value of the produced syngas seemed to provide the most reliable approximation of the real plant operation. Finally, a possible plant configuration is proposed for the energetic valorization of the pulper waste and its overall conversion process efficiency is estimated.
Building Robust Closed-Loop Supply Networks against Malicious Attacks
Authors: Deng Ding-Shan , Long Wei , Li Yan-Yan , Shi Xiao-Qiu
Published: December 2020

With recent industrial upgrades, it is essential to transform the current forward supply networks (FSNs) into closed-loop supply networks (CLSNs), which are formed by the integration of forward and reverse logistics. The method chosen in this paper for building reverse logistics is to add additional functions to the existing forward logistics. This process can be regarded as adding reverse edges to the original directed edges in an FSN. Due to the limitation of funds and the demand for reverse flow, we suppose that a limited number of reverse edges can be built in a CLSN. To determine the transformation schemes with excellent robustness against malicious attacks, this paper proposes a multi-population evolutionary algorithm with novel operators to optimize the robustness of the CLSN, and this algorithm is abbreviated as MPEA-RSN. Then, both the generated and realistic SNs are taken as examples to validate the effectiveness of MPEA-RSN. The simulation results show that the index R, introduced to evaluate the robustness of CLSNs, can be improved by more than 95%, and this indicates that (1) the different schemes for adding reverse routes to an FSN can lead to different robustness values, and (2) the robustness of the transformed CLSN to malicious attacks can be significantly improved after optimization by MPEA-RSN. When an FSN is to be transformed into a CLSN, this paper can provide a frame of reference for building a CLSN that is robust to malicious attacks from a network structural perspective.
Living with Time: Spirituality and Denis Villeneuve’s Arrival
Authors: van Dijk Mathilde
Published: December 2020

At first sight, Denis Villeneuve’s 2016 Arrival seems to provide a fairly standard science fiction narrative about the landing of aliens on earth and the panic that ensues, featuring aggressive soldiers, a suspicious CIA man, brilliant scientists and rioting populaces. The film could be read as propaganda for the humanities as it is a linguist rather than a natural scientist who saves the world. The second narrative is more important, as acknowledged by the director: the main character Dr. Louise Banks’s mourning for her deceased daughter, Hannah. In contact with the aliens, she learns how to cope with this disastrous event, by acquiring a different perspective on how life proceeds and how time works. This is also where the film, subtly, tells a deeply spiritual narrative, in which Louise acquires tender competence to deal with what life brings, including Hannah’s death.
Optimal Grasping Pose Synthesis in a Constrained Environment
Authors: Altobelli Alessandro , Tokatli Ozan , Burroughes Guy , Skilton Robert
Published: December 2020

In the last few decades, several approaches have been presented to accomplish tasks with robots or autonomous systems in a glovebox; nevertheless, in nuclear facilities, risky operations are still executed by humans that guarantee a high manipulation capability and dexterity. Inside the gloveboxes, robotic devices have to operate in cluttered environments, or environments with limited space for movement; therefore, it is of significant interest to identify grasping poses that are feasible within such constrained environments. In this paper, we present and experimentally evaluate a strategy to synthesise optimal grasps considering geometric primitives for a manipulation systems in a constrained environment. The novel strategy has been experimentally evaluated in a cluttered environment (as a glovebox mock-up) with realistic objects, and the efficacy of the proposed grasping algorithm is proposed.
RSCNN: A CNN-Based Method to Enhance Low-Light Remote-Sensing Images
Authors: Hu Linshu , Qin Mengjiao , Zhang Feng , Du Zhenhong , Liu Renyi
Published: December 2020

Image enhancement (IE) technology can help enhance the brightness of remote-sensing images to obtain better interpretation and visualization effects. Convolutional neural networks (CNN), such as the Low-light CNN (LLCNN) and Super-resolution CNN (SRCNN), have achieved great success in image enhancement, image super resolution, and other image-processing applications. Therefore, we adopt CNN to propose a new neural network architecture with end-to-end strategy for low-light remote-sensing IE, named remote-sensing CNN (RSCNN). In RSCNN, an upsampling operator is adopted to help learn more multi-scaled features. With respect to the lack of labeled training data in remote-sensing image datasets for IE, we use real natural image patches to train firstly and then perform fine-tuning operations with simulated remote-sensing image pairs. Reasonably designed experiments are carried out, and the results quantitatively show the superiority of RSCNN in terms of structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) over conventional techniques for low-light remote-sensing IE. Furthermore, the results of our method have obvious qualitative advantages in denoising and maintaining the authenticity of colors and textures.
HRCNet: High-Resolution Context Extraction Network for Semantic Segmentation of Remote Sensing Images
Authors: Xu Zhiyong , Zhang Weicun , Zhang Tianxiang , Li Jiangyun
Published: December 2020

Semantic segmentation is a significant method in remote sensing image (RSIs) processing and has been widely used in various applications. Conventional convolutional neural network (CNN)-based semantic segmentation methods are likely to lose the spatial information in the feature extraction stage and usually pay little attention to global context information. Moreover, the imbalance of category scale and uncertain boundary information meanwhile exists in RSIs, which also brings a challenging problem to the semantic segmentation task. To overcome these problems, a high-resolution context extraction network (HRCNet) based on a high-resolution network (HRNet) is proposed in this paper. In this approach, the HRNet structure is adopted to keep the spatial information. Moreover, the light-weight dual attention (LDA) module is designed to obtain global context information in the feature extraction stage and the feature enhancement feature pyramid (FEFP) structure is promoted and employed to fuse the contextual information of different scales. In addition, to achieve the boundary information, we design the boundary aware (BA) module combined with the boundary aware loss (BAloss) function. The experimental results evaluated on Potsdam and Vaihingen datasets show that the proposed approach can significantly improve the boundary and segmentation performance up to 92.0% and 92.3% on overall accuracy scores, respectively. As a consequence, it is envisaged that the proposed HRCNet model will be an advantage in remote sensing images segmentation.
A Rapid and High-Precision Mountain Vertex Extraction Method Based on Hotspot Analysis Clustering and Improved Eight-Connected Extraction Algorithms for Digital Elevation Models
Authors: Zheng Zhenqi , Xiao Xiongwu , Zhong Zhi-Chao , Zang Yufu , Yang Nan , Tu Jianguang , Li Deren
Published: December 2020

Digital Elevation Model (DEM)-based mountain vertex extraction is one of the most useful DEM applications, providing important information to properly characterize topographic features. Current vertex-extraction techniques have considerable limitations, such as yielding low-accuracy results and generating false mountain vertices. To overcome these limitations, a new approach is proposed that combines Hotspot Analysis Clustering and the Improved Eight-Connected Extraction algorithms that would quickly and accurately provide the location and elevation of mountain vertices. The use of the elevation-based Hotspot Analysis Clustering Algorithm allows the fast partitioning of the mountain vertex area, which significantly reduces data and considerably improves the efficiency of mountain vertex extraction. The algorithm also minimizes false mountain vertices, which can be problematic in valleys, ridges, and other rugged terrains. The Eight-Connected Extraction Algorithm also hastens the precise determination of vertex location and elevation, providing a better balance between accuracy and efficiency in vertex extraction. The proposed approach was used and tested on seven different datasets and was compared against traditional vertex extraction methods. The results of the quantitative evaluation show that the proposed approach yielded higher efficiency, considerably minimized the occurrence of invalid points, and generated higher vertex extraction accuracy compared to other traditional methods.
The Magic of Optics—An Overview of Recent Advanced Terahertz Diffractive Optical Elements
Authors: Siemion Agnieszka
Published: December 2020

Diffractive optical elements are well known for being not only flat but also lightweight, and are characterised by low attenuation. In different spectral ranges, they provide better efficiency than commonly used refractive lenses. An overview of the recently invented terahertz optical structures based on diffraction design is presented. The basic concepts of structure design together with various functioning of such elements are described. The methods for structure optimization are analysed and the new approach of using neural network is shown. The paper illustrates the variety of structures created by diffractive design and highlights optimization methods. Each structure has a particular complex transmittance that corresponds to the designed phase map. This precise control over the incident radiation phase changes is limited to the design wavelength. However, there are many ways to overcome this inconvenience allowing for broadband functioning.
Vision-Based Suture Tensile Force Estimation in Robotic Surgery
Authors: Jung Won-Jo , Kwak Kyung-Soo , Lim Soo-Chul
Published: December 2020

Compared to laparoscopy, robotics-assisted minimally invasive surgery has the problem of an absence of force feedback, which is important to prevent a breakage of the suture. To overcome this problem, surgeons infer the suture force from their proprioception and 2D image by comparing them to the training experience. Based on this idea, a deep-learning-based method using a single image and robot position to estimate the tensile force of the sutures without a force sensor is proposed. A neural network structure with a modified Inception Resnet-V2 and Long Short Term Memory (LSTM) networks is used to estimate the suture pulling force. The feasibility of proposed network is verified using the generated DB, recording the interaction under the condition of two different artificial skins and two different situations (in vivo and in vitro) at 13 viewing angles of the images by changing the tool positions collected from the master-slave robotic system. From the evaluation conducted to show the feasibility of the interaction force estimation, the proposed learning models successfully estimated the tensile force at 10 unseen viewing angles during training.
An Effective BERT-Based Pipeline for Twitter Sentiment Analysis: A Case Study in Italian
Authors: Pota Marco , Ventura Mirko , Catelli Rosario , Esposito Massimo
Published: December 2020

Over the last decade industrial and academic communities have increased their focus on sentiment analysis techniques, especially applied to tweets. State-of-the-art results have been recently achieved using language models trained from scratch on corpora made up exclusively of tweets, in order to better handle the Twitter jargon. This work aims to introduce a different approach for Twitter sentiment analysis based on two steps. Firstly, the tweet jargon, including emojis and emoticons, is transformed into plain text, exploiting procedures that are language-independent or easily applicable to different languages. Secondly, the resulting tweets are classified using the language model BERT, but pre-trained on plain text, instead of tweets, for two reasons: (1) pre-trained models on plain text are easily available in many languages, avoiding resource- and time-consuming model training directly on tweets from scratch; (2) available plain text corpora are larger than tweet-only ones, therefore allowing better performance. A case study describing the application of the approach to Italian is presented, with a comparison with other Italian existing solutions. The results obtained show the effectiveness of the approach and indicate that, thanks to its general basis from a methodological perspective, it can also be promising for other languages.
Investigating Possible Effects from a One-Year Coach-Education Program
Authors: Moen Frode , Olsen Maja , Bjørkøy John Anders
Published: December 2020

The main purpose of the current study was to examine possible effects from a coach education program over one year, in which each coach was supervised by a mentor who facilitated their learning based on coach-centered values. The current study was designed as an experiment with a control group, where the coaches in the experiment group received mentoring by a mentor over one year, whereas the coaches in the control group did not. Ninety-four coaches completed the study over one year from a variety of sports (n > 30), where cross-country skiing, soccer, biathlon, handball and swimming were the most represented sports. Among the coaches in the sample, 87% were coaches for athletes who competed or had ambitions to compete at an international level. The results from self-reported questionnaires at the pre-test and post-test show that the coach education program had a significant effect on the bond dimension in the coach–athlete working alliances and the coaches’ perceived coach performances. The analysis did not find any effects from the coach education program on the goal and task dimension in the coach–athlete working alliances. The findings are discussed in terms of applied implications and possible future research.
Analysis of Rotational Stiffness of the Timber Frame Connection
Authors: Johanides Marek , Kubíncová Lenka , Mikolášek David , Lokaj Antonín , Sucharda Oldřich , Mynarčík Petr
Published: December 2020

Initially, timber was considered only as an easily accessible and processable material in nature; however, its excellent properties have since become better understood. During the discovery of new building materials and thanks to new technological development processes, industrial processing technologies and gradually drastically decreasing forest areas, wood has become an increasingly neglected material. Load-bearing structures are made mostly of reinforced concrete or steel elements. However, ecological changes, the obvious problems associated with environmental pollution and climate change, are drawing increasing attention to the importance of environmental awareness. These factors are attracting increased attention to wood as a building material. The increased demand for timber as a building material offers the possibility of improving its mechanical and physical properties, and so new wood-based composite materials or new joints of timber structures are being developed to ensure a better load capacity and stiffness of the structure. Therefore, this article deals with the improvement of the frame connection of the timber frame column and a diaphragm beam using mechanical fasteners. In common practice, bolts or a combination of bolts and pins are used for this type of connection. The subject of the research and its motivation was to replace these commonly used fasteners with more modern ones to shorten and simplify the assembly time and to improve the load capacity and rigidity of this type of frame connection.
Baikal Region (Russia) Development Prospects Based on the Green Economy Principles
Authors: Bilgaev Alexey , Dong Suocheng , Li Fujia , Cheng Hao , Tulohonov Arnold , Sadykova Erzhena , Mikheeva Anna
Published: December 2020

The problems of preserving the natural environment are relevant for unique natural complexes of territories, such as the Baikal region (Russia). There are few studies devoted to forecasting the green economic development of the eco-socio-economic system of the Baikal region. The previous studies are mainly dedicated to the theory of forming the green economy in the Baikal region. This study aimed to forecast and determine future trends in the Baikal region’s eco-socio-economic development based on the green economy. The methodological approach to assess the Baikal region development prospects is based on determining the factors affecting the relationship between various eco-socio-economic components using multiple regression models. We constructed the forecast using the artificial neural networks method, and we assessed the possible impact of anthropogenic factors on the Baikal region’s eco-socio-economic system in the future. Based on the obtained forecast, we proposed a mechanism for regulating the green economy formation in the region. The regional governments of the Baikal region should perform the management function. This requires establishing a special interregional Green Development Fund to restructure incoming public funds by redistributing financial flows from contaminating brown to green industries and develop a state program for the Green Development of the Baikal region. The constructed forecast is informational support for decision making for the long-term development of the economy during the transition to the green economy, the development and justification of program activities, and the future’s main strategic priorities.
Sustainable Additive Manufacturing: Mechanical Response of Polypropylene over Multiple Recycling Processes
Authors: Vidakis Nectarios , Petousis Markos , Tzounis Lazaros , Maniadi Athena , Velidakis Emmanouil , Mountakis Nicolaos , Papageorgiou Dimitrios , Liebscher Marco , Mechtcherine Viktor
Published: December 2020

The recycling of polymeric materials has received a steadily growing scientific and industrial interest due to the increase in demand and production of durable and lightweight plastic parts. Recycling of such materials is mostly based on thermomechanical processes that significantly affect the mechanical, as well as the overall physicochemical properties of polymers. The study at hand focuses on the recyclability of Fused Filament Fabrication (FFF) 3D printed Polypropylene (PP) for a certain number of recycling courses (six in total), and its effect on the mechanical properties of 3D printed parts. Namely, 3D printed specimens were fabricated from non-recycled and recycled PP material, and further experimentally tested regarding their mechanical properties in tension, flexion, impact, and microhardness. Comprehensive dynamic scanning calorimetry (DSC), thermogravimetric analysis (TGA), Raman spectroscopy, and morphological investigations by scanning electron microscopy (SEM) were performed for the different 3D printed PP samples. The overall results showed that there is an overall slight increase in the material’s mechanical properties, both in tension and in flexion mode, while the DSC characterization indicates an increase in the polymer crystallinity over the recycling course.
Effects of Verbal Interactions between Students on Skill Development, Game Performance and Game Involvement in Soccer Learning
Authors: Ben Khalifa Wissam , Zouaoui Mehrzia , Zghibi Makrem , Azaiez Fairouz
Published: December 2020

The purpose of the study was to examine the effects of verbal interaction between students on skill development and soccer game performance within a socio-constructivist perspective and a cooperative learning model in team-sport teaching. In addition, the usefulness of open verbalization was manifested as follows: (1) a social tool for both actors (teachers and students) to collect and manage reports on their thought processes; (2) a tool to stimulate reflection and critical reflection on performance to induce transformation during game action projects. Participants were 18 boys and 12 girls aged (15 ± 0.4 years) from a Tunisian school (ninth grade). They were placed in either the experimental group (with verbal interaction) or the comparison group (without verbal interaction) and then were tested before and after a 12-lesson soccer unit (approximately two hours/week). Skill competence was assessed using three tests: a 15 m ball dribbling test, the Loughborough Soccer Passing Test (LSPT) and a shooting accuracy test. Game performance was measured using the Game Performance Assessment Instrument (GPAI) in which the outcome variables assessed included (a) decision-making (DM), (b) skill execution (SE), (c) support (S), (d) game performance (GP), and (e) game involvement (GI). While both groups showed significant improvements in their short-passing ability, no such improvements were found in dribbling and shooting. In contrast, only the verbal interaction group produced significant improvements in overall game performance. In conclusion, if the objectives of the physical education curriculum are to promote team-sport teaching methods and quality game play, and create a reflexive learner, verbal interaction may be an effective tool for developing tactical understanding through cooperative learning.
Trade Facilitation and Its Impacts on the Economic Welfare and Sustainable Development of the ECOWAS Region
Authors: Safaeimanesh Shahrzad , Jenkins Glenn P.
Published: December 2020

The facilitation of trade is a principal objective in the context of increasing regional trade integration for the achievement of sustainable development goals. The purpose of this study is to estimate the potential annual economic gain to be had from trade facilitation by the coastal countries of the Economic Community of West African States (ECOWAS). These measures would decrease border and documentary compliance time and costs of the administration of international trade. A partial equilibrium welfare economics framework is used that employs sets of export supply and import demand elasticities for each country that are derived using a general equilibrium estimation method. The annual economic welfare gains resulting from the reduction of excessive trade compliance costs for the region are estimated to between US$1.6 billion to US$2.7 billion (2019 prices). This is between 0.24% and 0.42% of the combined GDPs of these countries. The welfare gain is between 6% and 10% of the combined governments’ budgets assigned for education, and is between 33% and 58% of their budgets allocated for health. In the absence of reform, these inefficient practices waste an amount equal to between 15% and 26% of the annual net official development assistance these countries receive.
The Effects of Product Monetary Value, Product Evaluation Cost, and Customer Enjoyment on Customer Intention to Purchase and Reuse Vendors: Institutional Trust-Based Mechanisms
Authors: Masri Ni Wayan , Ruangkanjanases Athapol , Chen Shih-Chih
Published: December 2020

This study develops a model based on perceived effectiveness of e-commerce institutional mechanisms (PEEIM) and trust-based mechanisms to explain how PEEIM, product monetary value (MV), product evaluation cost (PEC), and enjoyment influence trust online vendor (TV) and how they affect purchase intention (IP) and reuse intention (IR) in e-shopping. The study is based on a survey of 293 online shoppers in Taiwan. Results show that monetary value, product evaluation cost, and customer enjoyment have a positive relationship with trust in online vendors, and a positive indirect and significant relationship on intention to purchase and reuse the products or service in the e-shopping environment. However, PEEIM does not have indirect effects on the customer’s intention to purchase and reuse the products or services through the influence of trust online vendor if the influence of PEEIM on customer trust online vendor is low and no significant effects, but PEEIM does have significant direct effects on a customer’s purchase and reuse intention. In addition, PEEIM has two constantly indirect relationships with a customer to purchase and reuse intention the product or services through the influence of customer enjoyment and customer trust in online vendor relationships. The study contributes important theoretical and practical implications for scholars and e-commerce providers.
Reforming Housing Policies for the Sustainability of Historic Cities in the Post-COVID Time: Insights from the Atlas World Heritage
Authors: Shirvani Dastgerdi Ahmadreza , De Luca Giuseppe , Francini Carlo
Published: December 2020

In recent years, finding affordable housing has been a notable challenge for the residents of historic cities in Europe. This paper aims to develop a novel vision for improving housing policies in the post-COVID time to moderate the long-lasting issue of affordable housing in historic cities. The research was developed based on the findings of the Atlas World Heritage in 2019. In this project, five European Art Cities, namely Florence, Edinburgh, Bordeaux, Porto, and Santiago de Compostela, discussed their common management challenges through the shared learning method. Focusing on the case study of Florence and using a mixed-method, we collected data through the municipality of Florence, map analysis, and distribution of a questionnaire among the city residents. Then, we used inductive reasoning to explain how reforming housing policies in the post-COVID time could moderate the long-lasting issue of affordable housing in historic cities. The findings suggest that housing policies need to be supported simultaneously at both international and local levels. From the international perspective, associated cultural heritage organizations, like United Nations Educational, Scientific and Cultural Organization (UNESCO) and its advisory bodies and the World Tourism Organization (UNWTO), need to develop restriction policies that manage tourism flows in historic cities like increasing the airline taxation. At the local level, Florence needs decisive housing policies that ban the growth of illegal tourist accommodation in the city. However, the privilege of establishing new hotels can be awarded in suburban or rural areas to support sustainable tourism goals.
Sustainability and Resilience in Smart City Planning: A Review
Authors: Ramirez Lopez Leonardo Juan , Grijalba Castro Angela Ivette
Published: December 2020

Urban planning is recognized as an interaction between the state and society, which aims to articulate public policies in the territory, facilitating their administration in favor of greater development and well-being of society. However, this interaction becomes complex because consumption demands increase, and the carrying capacity of the urban ecosystem to supply them is exceeded, hindering its sustainable functionality. With this overview, it becomes relevant to study urban planning from a sustainable environmental planning perspective, based on four topics: urban planning, sustainability, resilience, and smart cities, which are developed throughout the document by means of a chronological study. A bibliometric study was used through a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) adjustment to 87 articles, supported by VOSviewer®, which allowed for the construction and visualization of the co-occurrence networks of key words extracted from the selected articles. Likewise, 16 documents more were used for the co-occurrence analysis. The main result is to consider cities with a complex systems approach that works like a gear; the relationship between inter-urban and intra-urban processes is the key factor that allows for an understanding of their synchronization; therefore, deepening of each of these topics is crucial to the ideal of a territorial administration involving time scales and adaptive cycles, allowing for the provision of new tools for concepts such as carrying capacity and the measurement of the ecological footprint.
Hysteretic Behavior of Reinforced Concrete Coupling Beams According to Volume Fraction of Steel Fiber
Authors: Chung Joo-Hong , Son Dong-Hee , Kim Su-Yong , Bae Baek-Il , Choi Chang-Sik
Published: December 2020

The purpose of this study was to evaluate the structural performance of steel fiber reinforced concrete (SFRC) coupling beams. Reversed cyclic loading tests were performed with full-scale specimens. The main variable for the tests was the volume fraction ratio of the steel fibers. The results showed that the maximum strength was increased by about 11% with 1% of steel fibers incorporated, and about 24% when the ratio of mixed fibers was doubled to 2%. Because numerous microcracks occurred, decreased crack width due to the bridge effect was observed with the steel fiber reinforcement. Increased diagonal tension crack angles and energy dissipation also appeared as the volume fraction of steel fibers increased. The contribution of shear to the total deformation was decreased while the contribution of rocking was increased as steel fibers were added. Considering the results of these experiments, it can be concluded that steel fiber reinforcement affects the deformation of coupling beams in various ways, and should be considered when estimating the effective stiffness of such beams when SFRC is introduced.
Modelling VOC Emissions from Building Materials for Healthy Building Design
Authors: D’Amico Alessandro , Pini Agnese , Zazzini Simone , D’Alessandro Daniela , Leuzzi Giovanni , Currà Edoardo
Published: December 2020

The profound qualitative changes of indoor air and the progressive increase in the absolute number of pollutants, combined with the scientific awareness of the health impacts deriving from spending more than 90% of one’s time inside confined spaces, have increased the attention onto the needs of well-being, hygiene, and the health of users. This scientific attention has produced studies and analyses useful for evidence-based insights into building performance. Among the main pollutants in the indoor environment, Volatile Organic Compounds (VOCs) play a central role, and the use of box-models using the mass balance approach and Computational Fluid Dynamics (CFD) models are now consolidated to study their concentrations in an indoor environment. This paper presents the use of both types of modelling for the prediction of the VOC concentration in the indoor environment and the proposal of a guide value for the Indoor Air Quality (IAQ)-oriented building design, specifically related to the indoor VOC concentration due to building materials. Methodologically, the topic is addressed through environmental sampling, the definition of the parameters necessary for the numerical models, the simulations with the box-model and the CFD, and the comparison between the results. They show a good correspondence between the modelling tools used, highlighting the central role of ventilation and allowing a discussion of the relationship between regulatory limits of emissivity of materials and Indoor Air Guide Values for the concentration of pollutants.
Sustainability in the Beverage Industry: A Research Agenda from the Demand Side
Authors: Rodriguez-Sanchez Carla , Sellers-Rubio Ricardo
Published: December 2020

Sustainability has become one of the most important challenges for the beverage industry over the last few decades. In fact, many producers have implemented environmental, social, or economic aspects of sustainability at several stages of their production process. One of the reasons that might explain this interest in sustainability is that consumers are changing their behavior to integrate sustainable and environmental considerations into their purchase behavior. Accordingly, some consumers’ purchasing decisions are based not only on how well products satisfy their needs but also on how these products affect the environment or society at large. Within this context, designing appropriate interventions to fostering sustainable consumption requires deeper knowledge about its underlying determinants. In this paper, we focus on some of the most important challenges that might drive future research within this area.
Customer Behavior as an Outcome of Social Media Marketing: The Role of Social Media Marketing Activity and Customer Experience
Authors: Wibowo Ardy , Chen Shih-Chih , Wiangin Uraiporn , Ma Yin , Ruangkanjanases Athapol
Published: December 2020

Social media has been playing an important role in marketing strategy. As a part of social media, social networking sites (SNS) can be utilized by enterprises to create direct communication and good relationships with their customers. Therefore, enterprises using SNS have to select the right marketing content to enhance strong customer relationships, which lead to their behavior generating sustainable performance for enterprises. This research considered social media marketing activity (SMMA) and Customer Experience (CX) to measure the customer’s relationship quality, which can impact customer behavioral outcomes, which are purchase intention, loyalty intention, and participation intention. The 413 online questionnaire surveys were measured and analyzed using SmartPLS 3. The results show that SMMA and CX have a significant influence on the customer relationship quality, which also leads to a positive impact on customer behavioral outcomes. This research guides enterprises that SNS’s marketing content has to follow SMMA and CX dimensions to achieve the marketing objective and generate sustainable performance for enterprises.
A Note on the Periodic Solutions for a Class of Third Order Differential Equations
Authors: Diab Zouhair , Guirao Juan L. G. , Vera Juan A.
Published: December 2020

The aim of the present work is to study the necessary and sufficient conditions for the existence of periodic solutions for a class of third order differential equations by using the averaging theory. Moreover, we use the symmetry of the Monodromy matrix to study the stability of these solutions.
Ethylenediaminetetraacetic Acid Disodium Salt Acts as an Antifungal Candidate Molecule against Fusarium graminearum by Inhibiting DON Biosynthesis and Chitin Synthase Activity
Authors: Song Xiu-Shi , Gu Kai-Xin , Gao Jing , Wang Jian-Xin , Ding Shao-Chen , Zhou Mingguo
Published: December 2020

Fusarium fungi are the cause of an array of devastating diseases affecting yield losses and accumulating mycotoxins. Fungicides can be exploited against Fusarium and deoxynivalenol (DON) production. However, Fusarium resistance to common chemicals has become a therapeutic challenge worldwide, which indicates that new control agents carrying different mechanisms of action are desperately needed. Here, we found that a nonantibiotic drug, ethylenediaminetetraacetic acid disodium salt (EDTANa2), exhibited various antifungal activities against Fusarium species and DON biosynthesis. The infection of wheat seeding caused by F. graminearum was suppressed over 90% at 4 mM EDTANa2. A similar control effect was observed in field tests. Mycotoxin production assays showed DON production was significantly inhibited, 47% lower than the control, by 0.4 mM EDTANa2. In vitro experiments revealed a timely inhibition of H2O2 production as quickly as 4 h after amending cultures with EDTANa2 and the expression of several TRI genes significantly decreased. Chitin synthases of Fusarium were Mn2+-containing enzymes that were strongly inhibited by Mn2+ deficiency. EDTANa2 inhibited chitin synthesis and destroyed the cell wall and cytomembrane integrity of Fusarium, mainly via the chelation of Mn2+ by EDTANa2, and thus led to Mn deficiency in Fusarium cells. Taken together, these findings uncover the potential of EDTANa2 as a fungicide candidate to manage Fusarium head blight (FHB) and DON in agricultural production.
Emergence of Novel Reassortant H1N1 Avian Influenza Viruses in Korean Wild Ducks in 2018 and 2019
Authors: Trinh Thuy-Tien Thi , Duong Bao Tuan , Nguyen Anh Thi Viet , Tuong Hien Thi , Hoang Vui Thi , Than Duong Duc , Nam SunJeong , Sung Haan Woo , Yun Ki-Jung , Yeo Seon-Ju , Park Hyun
Published: December 2020

Influenza A virus subtype H1N1 has caused global pandemics like the “Spanish flu” in 1918 and the 2009 H1N1 pandemic several times. H1N1 remains in circulation and survives in multiple animal sources, including wild birds. Surveillance during the winter of 2018–2019 in Korea revealed two H1N1 isolates in samples collected from wild bird feces: KNU18-64 (A/Greater white-fronted goose/South Korea/KNU18-64/2018(H1N1)) and WKU19-4 (A/wild bird/South Korea/WKU19-4/2019(H1N1)). Phylogenetic analysis indicated that M gene of KNU18-64(H1N1) isolate resembles that of the Alaskan avian influenza virus, whereas WKU19-4(H1N1) appears to be closer to the Mongolian virus. Molecular characterization revealed that they harbor the amino acid sequence PSIQRS↓GLF and are low-pathogenicity influenza viruses. In particular, the two isolates harbored three different mutation sites, indicating that they have different virulence characteristics. The mutations in the PB1-F2 and PA protein of WKU19-4(H1N1) indicate increasing polymerase activity. These results corroborate the kinetic growth data for WKU19-4 in MDCK cells: a dramatic increase in the viral titer after 12 h post-inoculation compared with that in the control group H1N1 (CA/04/09(pdm09)). The KNU18-64(H1N1) isolate carries mutations indicating an increase in mammal adaptation; this characterization was confirmed by the animal study in mice. The KNU18-64(H1N1) group showed the presence of viruses in the lungs at days 3 and 6 post-infection, with titers of 2.71 ± 0.16 and 3.71 ± 0.25 log10(TCID50/mL), respectively, whereas the virus was only detected in the WKU19-4(H1N1) group at day 6 post-infection, with a lower titer of 2.75 ± 0.51 log10(TCID50/mL). The present study supports the theory that there is a relationship between Korea and America with regard to reassortment to produce novel viral strains. Therefore, there is a need for increased surveillance of influenza virus circulation in free-flying and wild land-based birds in Korea, particularly with regard to Alaskan and Asian strains.
Palmitoylation of the Bovine Foamy Virus Envelope Glycoprotein Is Required for Viral Replication
Authors: Chai Keli , Wang Zhaohuan , Xu Yali , Zhang Junshi , Tan Juan , Qiao Wentao
Published: December 2020

Membrane proteins of enveloped viruses have been reported to undergo palmitoylation, a post-translational modification often having a critical role in the function of these viral proteins and hence viral replication. In this study, we report that the foamy virus (FV) envelope (Env) glycoprotein is palmitoylated. Specifically, we found that bovine foamy virus (BFV) Env (BEnv) is palmitoylated at amino acid positions C58 and C59 by BDHHC3 and BDHHC20 in a DHHC motif-dependent manner. In addition, mutations C58S and C58/59S significantly decrease cell surface expression of BEnv, subviral particle (SVP) egress, and its membrane fusion activity, thus ultimately inhibiting BFV replication. The C59S mutation exerts a minor effect in this regard. Taken together, these data demonstrate that the function of BEnv in the context of BFV replication is under the regulation of palmitoylation.
Invasive Alien Plants in Africa and the Potential Emergence of Mosquito-Borne Arboviral Diseases—A Review and Research Outlook
Authors: Agha Sheila B. , Alvarez Miguel , Becker Mathias , Fèvre Eric M. , Junglen Sandra , Borgemeister Christian
Published: December 2020

The emergence of arthropod-borne viruses (arboviruses) as linked to land-use changes, especially the growing agricultural intensification and expansion efforts in rural parts of Africa, is of growing health concern. This places an additional burden on health systems as drugs, vaccines, and effective vector-control measures against arboviruses and their vectors remain lacking. An integrated One Health approach holds potential in the control and prevention of arboviruses. Land-use changes favour invasion by invasive alien plants (IAPs) and investigating their impact on mosquito populations may offer a new dimension to our understanding of arbovirus emergence. Of prime importance to understand is how IAPs influence mosquito life-history traits and how this may affect transmission of arboviruses to mammalian hosts, questions that we are exploring in this review. Potential effects of IAPs may be significant, including supporting the proliferation of immature and adult stages of mosquito vectors, providing additional nutrition and suitable microhabitats, and a possible interaction between ingested secondary plant metabolites and arboviruses. We conclude that aspects of vector biology are differentially affected by individual IAPs and that while some plants may have the potential to indirectly increase the risk of transmission of certain arboviruses by their direct interaction with the vectors, the reverse holds for other IAPs. In addition, we highlight priority research areas to improve our understanding of the potential health impacts of IAPs.
Altered NKp46 Recognition and Elimination of Influenza B Viruses
Authors: Duev-Cohen Alexandra , Isaacson Batya , Berhani Orit , Charpak-Amikam Yoav , Friedman Nehemya , Drori Yaron , Mandelboim Michal , Mandelboim Ofer
Published: December 2020

Every year, millions of people worldwide are infected with influenza, causing enormous health and economic problems. The most common type of influenza is influenza A. It is known that Natural Killer (NK) cells play an important role in controlling influenza A infection, mostly through the recognition of the viral protein hemagglutinin (HA) by the activating receptor, NKp46. In contrast, little is known regarding NK cell recognition of influenza B viruses, even though they are responsible for a third of all pediatric influenza deaths and are therefore included in the seasonal vaccine each year. Here we show that NKp46 also recognizes influenza B viruses. We show that NKp46 binds the HA protein of influenza B in a sialic acid-dependent manner, and identified the glycosylated residue in NKp46, which is critical for this interaction. We discovered that this interaction has a binding affinity approximately seven times lower than NKp46 binding of influenza A’s HA. Finally, we demonstrated, using mice deficient for the mouse orthologue of NKp46, named NCR1, that NKp46 is not important for influenza B elimination. These findings enable us to better understand the interactions between the different influenza viruses and NK cells that are known to be crucial for viral elimination.
Safety of Newer Disease Modifying Therapies in Multiple Sclerosis
Authors: Jalkh Georges , Abi Nahed Rachelle , Macaron Gabrielle , Rensel Mary
Published: December 2020

In the past decade, the therapeutic arsenal for multiple sclerosis has expanded greatly. Newer more potent disease modifying therapies (DMTs) with varying mechanisms of actions are increasingly used early in the disease course. These newer DMTs include oral therapies (teriflunomide, dimethyl fumarate, fingolimod, siponimod, ozanimod, and cladribine) and infusion therapies (natalizumab, alemtuzumab, and ocrelizumab), and are associated with better control of disease activity and long-term outcomes in patients with MS compared to older injectable therapies (interferon beta and glatiramer acetate). However, they are associated with safety concerns and subsequent monitoring requirements. Adverse events are initially observed in phase 2 and 3 clinical trials, and further long-term data are collected in phase 3 extension studies, case series, and post-marketing reports, which highlight the need to periodically re-evaluate and adjust monitoring strategies to optimize treatment safety in an individualized approach.