bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial Distribution and Geographical Mechanism of Natural Resources in China under the Orientation of the New Economic Demands
Authors: Zhang Xiangmin , Yu Bin , Yu Hailong , Li Zhuofan , Luo Shen , Sun Jianwu , Fan Yong
Published: July 2021

The demand structure of resources for new economy is different from the traditional one in that its development may significantly change China’s economic location map and spatial pattern. Based on 343 administrative units of prefecture-level cities in China, this research constructs the measurement index system of terrestrial surface natural resources under the orientation of the new economic demands; this research mainly analyses the spatial distribution characteristics and geographical mechanism of natural resources by means of the spatial autocorrelation and spatial similarity calculation methods. The results show that: (1) The structure and endowment of natural resources under the orientation of the new economic demands need to be reexamined. The significance of a good environment and ecological resources has been highlighted. The coupling of resource elements better reveals the availability of natural resources. (2) The natural resources decrease from southeast to northwest, showing a pattern of “abundant in the south and east and scarce in the north and west”. Natural resources have a significant positive correlation in spatial distribution with two types of agglomeration: high-high agglomeration and low-low agglomeration, showing the local agglomeration feature of “high in the south and low in the north”. (3) Natural factors such as temperature, precipitation and altitude affect the spatial distribution of natural resources, with the temperature being the most significant. This indicates that the original natural environment and its role are the geographical mechanism for the formation and distribution of natural resources. The results could provide a reference for the development and the optimization of China’s new economy.
Sustainable Teacher Training via Distance Education: The Effect of Study Centers, Gender and Economic Demographics on Academic Performance
Authors: Zhang Hong , Apeanti Wilson Osafo , Georgescu Paul , Harvim Prince , Lu Dianchen , Li Tan , Zhang Bing
Published: July 2021

We examine the effectiveness and sustainability of the distance teacher education program established by the University of Education, Winneba, Ghana, by investigating the differences in the academic performance of students who are trained in the teacher education program via traditional and distance education modes, respectively, from 2011 to 2015. Close attention is paid to the factors that affect the academic performance of students in the distance mode. Our findings confirm that traditional mode students perform better than their distance mode counterparts in terms of cumulative GPAs. Gender and economic demographics of distance study centers are found to affect the academic performance of distance education students significantly. The policy implications of these findings are discussed and directions of further action are outlined.
Measuring Egyptian Farmers’ Attitude towards Staying Organic
Authors: Rota Cosimo , Pugliese Patrizia , Elnady Mai , Zanasi Cesare
Published: July 2021

Organic agriculture (OA) in Egypt is well-developed and still fast growing. Improving the relation between organic farmers and the other agents in the chain can provide a positive contribution to the whole organic chain competitiveness. One possible approach to investigate the farmers’ perceived role and satisfaction within the organic system is to explore the factors influencing their decision to stay organic. In particular, the aim of the present study was to measure the farmers’ attitude towards staying organic. Organic agricultural experts and institutional stakeholders were interviewed to complete a literature review and to obtain information about the Egyptian context. The survey questionnaire was pre-tested (n = 13) and then administered to a different sample (n = 232). A split-half validation procedure was used to evaluate and then confirm the factor structure. Explorative and confirmatory factor analysis yielded a final 29-item measure consisting of 8 distinct factors showing how organic agriculture influences a broad range of farmers’ life dimensions (environmental, economic, social, psychological). The significant role played by psychological and social factors in defining the farmers’ decision to stay organic emerged as a relatively unexpected outcome. The study supports the sustainable development of small family farmers, providing a useful tool to support the growth of organic production and consumption, mostly in developing countries. By monitoring farmers’ attitudes and perception towards OA, the instrument proposed in the present study can support policy makers, farmers’ organizations, civil society organizations (NGOs) and organic chains focal companies when defining policies, advocating campaigns, and chain coordination strategies for farmers involved in the organic food system development.
The Effects of Transformational Leadership on Organizational Performance: Testing the Mediating Effects of Knowledge Management
Authors: Kılıç Mahmut , Uludağ Orhan
Published: July 2021

Transformational leadership is a sustainable and exemplary form of leadership that liberates subordinates’ ideas, enables subordinates to view problems from a different perspective, helps adaptation to changing environments, and increases Human Resources Management effectiveness in public and service institutions. The effects of transformational leadership on organizational performance by means of knowledge management have been examined in this study on the northern Cyprus Security Forces. In addition, the study aims to analyze the relationships between transformational leadership, knowledge management, organizational performance, job satisfaction, organizational learning, and knowledge creation processes. The questionnaire was conducted in three different periods using a time-lag method, and data were collected from 1229 employees for this study. The collected data were analyzed using structural equation modeling (Lisrel 8.54). The findings of the research include 17 hypotheses that were supported, and 1 hypothesis that was not. In addition, it was determined that organizational learning, knowledge management, and job satisfaction mediate the effect of transformational leadership on organizational performance.
Impacts of Erosion on the Sustainability of Organic Olive Groves: A Case Study (Estepa Region, Southwestern Spain)
Authors: Rodríguez Sousa Antonio Alberto , Parra-López Carlos , Sayadi-Gmada Samir , Barandica Jesús M. , Rescia Alejandro J.
Published: July 2021

Spain has more than 2.5 M ha of olive groves, with 60% of this area (i.e., 1.5 M ha) concentrated in the region of Andalusia (Southern Spain). Assuming the socio-ecological characteristics of these crops, of which their contribution to ecosystemic services (ES) is fundamental for society, it is highly relevant to direct their management towards practices that guarantee their durability. Organic management of olive groves constitutes a multifunctional model that contributes to ensuring its sustainability and represents 2.4–3.5% of the olive grove area in Spain. Taking the Protected Designation of Origin (PDO) Estepa (Southwestern Spain) as a study model, where organic olive groves are novel, a study of the impacts of erosion on the economic, social, and environmental factors associated with this management was carried out in addition to estimating its impacts. The results showed how organic management promotes edaphic fertility, keeping the levels of diffuse pollution under the legislative limits. Although the increase in erosion has negative effects on the sustainability/durability of agricultural holdings, organic management consolidates a sustainable model that satisfies farmers’ demands. Therefore, organic farming is a model that focuses on the correct use of natural resources associated with the geographical region of study, and contributes to increasing the sustainability of olive groves.
Knowledge Management and Business Education
Authors: Bratianu Constantin
Published: July 2021

Knowledge management emerged as a direct result of developing the knowledge economy and the information technology that enables complex data and information processing [...]
On the Legal Status of Marine Genetic Resources in Areas beyond National Jurisdiction
Authors: Wang Chuanliang
Published: July 2021

The question of how to define the legal status of marine genetic resources (hereinafter MGRs) in areas beyond national jurisdiction (hereinafter ABNJ) is one of the important issues in the negotiation of the International Legally Binding Instrument under United Nations Convention on the Law of the Sea on the Conservation and Sustainable Use of Marine Biodiversity of Areas beyond National Jurisdiction. According to the theory of the order and justice value of the law, in combining the experiences of the international community in handling global ocean problems and characteristics of MGRs in ABNJ, it can be said that MGRs in ABNJ have the legal attribute of being the common heritage of mankind (hereinafter CHM). From the perspective of the principle of CHM, in applying the subject, object and content elements of legal relations as the research approach, the legal status of MGRs in ABNJ should be defined as follows: Firstly, an international management body should be established and the scope of actual resource developers should be defined in terms of subject elements. Secondly, the temporal scope, geographical scope and material scope of MGRs in ABNJ should be clarified in terms of object elements. Thirdly, the disposition of rights and obligations in the process of development and utilization of MGRs in ABNJ should be defined in terms of content elements.
The Effect of the Characteristics and Activities of the Board of Directors on Sustainable Development Goal (SDG) Disclosures: Empirical Evidence from Southeast Asia
Authors: Sekarlangit Lintang D. , Wardhani Ratna
Published: July 2021

This study aimed to analyze the board of directors’ commitment to the Sustainable Development Goals (SDGs) by looking at the influence of the characteristics and activities of the board of directors and the existence of Corporate Social Responsibility (CSR) committees on disclosures regarding the SDGs. The directors’ characteristics that were analyzed in this research included the board size, the proportion of independent directors, the presence of female directors, and the presence of foreign directors. The activities analyzed included the number of board meetings held in one year and the percentage of directors in meetings. The context of this study was companies in five Southeast Asian countries—Indonesia, Malaysia, Singapore, Thailand, and the Philippines—during the 2016 and 2017 reporting years. This study was an initial research work aiming to empirically examine the effect of the board of directors on SDG disclosures in public companies from five countries in Southeast Asia. The study shows that the percentage of attendance of board directors’ meetings and the existence of CSR committees positively affected SDG disclosures. It also indicates that the presence of the board at the meeting can encourage more intensive SDG disclosures. Companies with a high commitment to sustainability, as shown by their forming of CSR committees, also tended to have a higher level of SDG disclosures.
Prognostication of Shortwave Radiation Using an Improved No-Tuned Fast Machine Learning
Authors: Ebtehaj Isa , Soltani Keyvan , Amiri Afshin , Faramarzi Marzban , Madramootoo Chandra A. , Bonakdari Hossein
Published: July 2021

Shortwave radiation density flux (SRDF) modeling can be key in estimating actual evapotranspiration in plants. SRDF is the result of the specific and scattered reflection of shortwave radiation by the underlying surface. SRDF can have profound effects on some plant biophysical processes such as photosynthesis and land surface energy budgets. Since it is the main energy source for most atmospheric phenomena, SRDF is also widely used in numerical weather forecasting. In the current study, an improved version of the extreme learning machine was developed for SRDF forecasting using the historical value of this variable. To do that, the SRDF through 1981–2019 was extracted by developing JavaScript-based coding in the Google Earth Engine. The most important lags were found using the auto-correlation function and defined fifteen input combinations to model SRDF using the improved extreme learning machine (IELM). The performance of the developed model is evaluated based on the correlation coefficient (R), root mean square error (RMSE), mean absolute percentage error (MAPE), and Nash–Sutcliffe efficiency (NSE). The shortwave radiation was developed for two time ahead forecasting (R = 0.986, RMSE = 21.11, MAPE = 8.68%, NSE = 0.97). Additionally, the estimation uncertainty of the developed improved extreme learning machine is quantified and compared with classical ELM and found to be the least with a value of ±3.64 compared to ±6.9 for the classical extreme learning machine. IELM not only overcomes the limitation of the classical extreme learning machine in random adjusting of bias of hidden neurons and input weights but also provides a simple matrix-based method for practical tasks so that there is no need to have any knowledge of the improved extreme learning machine to use it.
Contributions of Smart City Solutions and Technologies to Resilience against the COVID-19 Pandemic: A Literature Review
Authors: Sharifi Ayyoob , Khavarian-Garmsir Amir Reza , Kummitha Rama Krishna Reddy
Published: July 2021

Since its emergence in late 2019, the COVID-19 pandemic has swept through many cities around the world, claiming millions of lives and causing major socio-economic impacts. The pandemic occurred at an important historical juncture when smart solutions and technologies have become ubiquitous in many cities. Against this background, in this review, we examine how smart city solutions and technologies have contributed to resilience by enhancing planning, absorption, recovery, and adaptation abilities. For this purpose, we reviewed 147 studies that have discussed issues related to the use of smart solutions and technologies during the pandemic. The results were synthesized under four themes, namely, planning and preparation, absorption, recovery, and adaptation. This review shows that investment in smart city initiatives can enhance the planning and preparation ability. In addition, the adoption of smart solutions and technologies can, among other things, enhance the capacity of cities to predict pandemic patterns, facilitate an integrated and timely response, minimize or postpone transmission of the virus, provide support to overstretched sectors, minimize supply chain disruption, ensure continuity of basic services, and offer solutions for optimizing city operations. These are promising results that demonstrate the utility of smart solutions for enhancing resilience. However, it should be noted that realizing this potential hinges on careful attention to important issues and challenges related to privacy and security, access to open-source data, technological affordance, legal barriers, technological feasibility, and citizen engagement. Despite this, this review shows that further development of smart city initiatives can provide unprecedented opportunities for enhancing resilience to the pandemic and similar future events.
The Impacts of Area-Based Policies on Essential Retail in Vulnerable Areas
Authors: Mateos-Mora Cristina , Herrera-Gutiérrez María Rosa , González-Benítez Cristina
Published: July 2021

Since the 1990s, urban regeneration has emerged as the main initiative of the European Territorial Development Strategy. A series of integrated urban regeneration policies have subsequently been implemented to redress the socio-territorial imbalance in urban areas by improving the structure of opportunities available to inhabitants. The aim of the current paper is to evaluate the effect of such policies of proximity on the “essential retail trade” in neighborhoods in Andalusia. A quasi-experimental methodology was applied using the Difference in Differences (DiD) technique in order to ascertain the changes attributed to the intervention of the projects. In addition, change trends were analyzed using repeat measurements models for each calculated indicator and in the different considered contexts. The findings show an increase in the density and diversity of essential retail businesses in experimental and control areas. We found that in general, intervention had no significant effect on essential retail trade. However, the results do indicate that the impact of these plans is conditioned by the possible effect of different contexts and their specific dynamics (historical districts of large cities or towns on the one hand or peripheral suburbs on the other). The study may contribute to improving the design of integrated policies by controlling for the specificities of urban areas targeted by intervention.
Images of Nature, Nature-Self Representation, and Environmental Attitudes
Authors: Ambrose Lauren E. , Wiezel Adi , Pages Erika B. , Shiota Michelle N.
Published: July 2021

Prior work suggests that feeling small relative to nature (Nature-Self Size; NSS) and inclusion of nature in the self-concept (INS) are both associated with more pro-environmental attitudes. The present experiment asked whether exposure to stimuli eliciting awe—an emotion often evoked by extraordinary panoramic views of nature, characterized by subjective experience of “small self” and modulation of reliance on stored concepts—leads to increased NSS and/or INS, thereby promoting pro-environmental policy attitudes. Participants in this online experiment were randomly assigned to view photographs of extraordinary panoramic nature scenes, prosaic nature images, desirable foods, or neutral scenes before completing measures of INS, NSS, and support for environmental conservation policies. Analyses revealed that INS significantly mediated the effects of exposure to panoramic nature scenes (versus a neutral control) on pro-environmental policy attitudes; however, the same effect was observed for the prosaic nature and tasty foods images. Results suggest that exposure to awe-eliciting stimuli can promote pro-environmental attitudes via modulation of the self-concept, but this may be due to pleasant affect rather than awe per se. Future research with real-life stimuli and longitudinal designs is needed to further examine the lasting effects of awe and other emotional states on the self-concept and associated environmental attitudes.
Assessment of Soil Pollution Levels in North Nile Delta, by Integrating Contamination Indices, GIS, and Multivariate Modeling
Authors: Abowaly Mohamed E. , Belal Abdel-Aziz A. , Abd Elkhalek Enas E. Abd , Elsayed Salah , Abou Samra Rasha M. Abou , Alshammari Abdullah S. , Moghanm Farahat S. , Shaltout Kamal H. , Alamri Saad A. M. , Eid Ebrahem M.
Published: July 2021

The proper assessment of trace element concentrations in the north Nile Delta of Egypt is needed in order to reduce the high levels of toxic elements in contaminated soils. The objectives of this study were to assess the risks of contamination for four trace elements (nickel (Ni), cobalt (Co), chromium (Cr), and boron (B)) in three different layers of the soil using the geoaccumulation index (I-geo) and pollution load index (PLI) supported by GIS, as well as to evaluate the performance of partial least-square regression (PLSR) and multiple linear regression (MLR) in estimating the PLI based on data for the four trace elements in the three different soil layers. The results show a widespread contamination of I-geo Ni, Co, Cr, and B in the three different layers of the soil. The I-geo values varied from 0 to 4.74 for Ni, 0 to 6.56 for Co, 0 to 4.11 for Cr, and 0 to 4.57 for B. According to I-geo classification, the status of Ni, Cr, and B ranged from uncontaminated/moderately contaminated to strongly/extremely contaminated. Co ranged from uncontaminated/moderately contaminated to extremely contaminated. There were no significant differences in the values of I-geo for Ni, Co, Cr, and B in the three different layers of the soil. According to the PLI classification, the majority of the samples were very highly polluted. For example, 4.76% and 95.24% of the samples were unpolluted and very highly polluted, respectively, in the surface layer of the soil profiles. Additionally, 14.29% and 85.71% of the samples were unpolluted and very highly polluted, respectively, in the subsurface layer of the soil profiles. Both calibration (Cal.) and validation (Val.) models of the PLSR and MLR showed the highest performance in predicting the PLI based on data for the four studied trace elements, as an alternative method. The validation (Val.) models performed the best in predicting the PLI, with R2 = 0.89–0.93 in the surface layer, 0.91–0.96 in the subsurface layer, 0.89–0.94 in the lowest layers, and 0.92–0.94 across the three different layers. In conclusion, the integration of the I-geo, PLI, GIS technique, and multivariate models is a valuable and applicable approach for the assessment of the risk of contamination for trace elements, and the PLSR and MLR models could be used through applying chemometric techniques to evaluate the PLI in different layers of the soil.
Risk Management in Seaports: A Community Analysis at the Port of Hamburg
Authors: Nagi Ayman , Schroeder Meike , Kersten Wolfgang
Published: July 2021

The aim of this work is to detect communities of stakeholders at the port of Hamburg regarding their communication intensity in activities related to risk management. An exploratory mixed-method design is chosen as a methodology based on a compact survey and semi-structured interviews, as well as secondary data. A compact survey at the port of Hamburg is utilized to address the communication intensity values among stakeholders. Based on 28 full responses, the data is extracted, cleansed, and prepared for the network analysis using the software “Gephi”. Thereafter, the Louvain community detection algorithm is used to extract the communities from the network. A plausibility check is carried out using 15 semi-structured interviews and secondary data to verify and refine the results of the community analysis. The results have revealed different communities for the following risk categories: (a) natural disasters and (b) operational and safety risks. The focus of cooperation is on the reactive process and emergency plans. For instance, emergency plans play an important role in the handling of natural disasters such as floods or extreme winds.
Building Cohesive Teams—The Role of Leaders’ Bottom-Line Mentality and Behavior
Authors: Riisla Katrin , Wendt Hein , Babalola Mayowa T. , Euwema Martin
Published: July 2021

Team cohesiveness plays a crucial role in effective teamwork, innovation, and improved performance, and as such, its development among team members is an essential part of team management. However, it may be disregarded by leaders with a high bottom-line mentality (BLM; a single-minded focus on the bottom line at the expense of other values or priorities). These leaders may show little interest in other priorities, such as ethical, social, or environmental considerations, and may be tempted to push their followers to go above and beyond what is expected, even if it means bending the rules, cutting corners, or engaging in other ethically problematic behaviors. We argue that although a team leader’s BLM may motivate followers to come together around the pursuit of a common goal, it may come at the expense of nurturing healthy interpersonal relationships, trust, and other important social resources within the team. Specifically, we argue that the way leaders with a high BLM approach their goals may affect team cohesiveness, and that it is particularly negative for female leaders. Using a large multi-national study, we found that this happens through increased directive and lowered participative leader behaviors.
Corporate Social Responsibility in South Europe during the Financial Crisis and Its Relation to the Financial Performance of Greek Companies
Authors: Ziogas Ioannis , Metaxas Theodore
Published: July 2021

This paper aims at presenting the notion of corporate social responsibility in Europe by examining its application in Southern European countries, Greece, Italy, Spain and Portugal. These major Mediterranean countries, beside the geographical proximity and common features, were at the center of the financial crisis in Europe in 2009. The aforementioned countries are under evaluation on the one hand as a European region and on the other hand as independent ones. Considering the complexity of CSR, its aspects through time, its diversity depending on the geographical position and the necessity of ethical CSR as part of business activity, this paper presents a new categorization of existing quantitative indicators and a method of evaluation that covers the multidimensional notion of CSR. The new model, which combines quantitative indicators, is used to measure CSR during the period from 2009 until 2016 and reflects companies’ ethical policy, the degree of understanding their moral obligations. The longitudinal comparative analysis is the starting point for further improvement as the countries, except for Portugal, are fluctuating within low levels and the Mediterranean region as a whole in average ones. Furthermore, having estimate CSR index, the examination of the financial performance of Greek companies within the period 2015–2016 confirms the majority of the literature that the adoption of CSR’s good practices, is not only a moral rule, but contributes at least partly, to the development of their effectiveness. As a conclusion, the structure of a commonly acceptable measurement model of the National Social Responsibility and the longitudinal measurement will be a useful tool for all involved institutions, with immediate results to both the society and the companies.
Reducing Topdressing N Fertilization with Variable Rates Does Not Reduce Maize Yield
Authors: Schillaci Calogero , Tadiello Tommaso , Acutis Marco , Perego Alessia
Published: July 2021

Proximal sensing represents a growing avenue for precision fertilization and crop growth monitoring. In the last decade, precision agriculture technology has become affordable in many countries; Global Positioning Systems for automatic guidance instruments and proximal sensors can be used to guide the distribution of nutrients such as nitrogen (N) fertilization using real-time applications. A two-year field experiment (2017–2018) was carried out to quantify maize yield in response to variable rate (VR) N distribution, which was determined with a proximal vigour sensor, as an alternative to a fixed rate (FR) in a cereal-livestock farm located in the Po valley (northern Italy). The amount of N distributed for the FR (140 kg N ha−1) was calculated according to the crop requirement and the regional regulation: ±30% of the FR rate was applied in the VR treatment according to the Vigour S-index calculated on-the-go from the CropSpec sensor. The two treatments of N fertilization did not result in a significant difference in yield in both years. The findings suggest that the application of VR is more economically profitable than the FR application rate, especially under the hypothesis of VR application at a farm scale. The outcome of the experiment suggests that VR is a viable and profitable technique that can be easily applied at the farm level by adopting proximal sensors to detect the actual crop N requirement prior to stem elongation. Besides the economic benefits, the VR approach can be regarded as a sustainable practice that meets the current European Common Agricultural Policy.
Analysis of Human Behavior by Mining Textual Data: Current Research Topics and Analytical Techniques
Authors: Gutierrez Edgar , Karwowski Waldemar , Fiok Krzysztof , Davahli Mohammad Reza , Liciaga Tameika , Ahram Tareq
Published: July 2021

The goal of this study was to conduct a literature review of current approaches and techniques for identifying, understanding, and predicting human behaviors through mining a variety of sources of textual data with a focus on enabling classification of psychological behaviors regarding emotion, cognition, and social empathy. This review was performed using keyword searches in ISI Web of Science, Engineering Village Compendex, ProQuest Dissertations, and Google Scholar. Our findings show that, despite recent advancements in predicting human behaviors based on unstructured textual data, significant developments in data analytics systems for identification, determination of interrelationships, and prediction of human cognitive, emotional and social behaviors remain lacking.
Estimation of Electricity Generation by an Electro-Technical Complex with Photoelectric Panels Using Statistical Methods
Authors: Turysheva Anna , Voytyuk Irina , Guerra Daniel
Published: July 2021

This paper presents a computational tool for estimating energy generated by low-power photovoltaic systems based on the specific conditions of the study region since the characteristic energy equation can be obtained considering the main climatological factors affecting these systems in terms of the symmetry or skewness of the random distribution of the generated energy. Furthermore, this paper is aimed at determining any correlation that exists between meteorological variables with respect to the energy generated by 5-kW solar systems in the specific climatic conditions of the Republic of Cuba. The paper also presents the results of the influence of each climate factor on the distribution symmetry of the generated energy of the solar system. Studying symmetry in statistical models is important because they allow us to establish the degree of symmetry (or skewness), which is the probability distribution of a random variable, without having to make a graphical representation of it. Statistical skewness reports the degree to which observations are distributed evenly and proportionally above and below the center (highest) point of the distribution. In the case when the mentioned distribution is balanced, it is called symmetric.
Generalized Lie Triple Derivations of Lie Color Algebras and Their Subalgebras
Authors: Asif Sania , Wu Zhixiang
Published: July 2021

Consider a Lie color algebra, denoted by L. Our aim in this paper is to study the Lie triple derivations TDer(L) and generalized Lie triple derivations GTDer(L) of Lie color algebras. We discuss the centroids, quasi centroids and central triple derivations of Lie color algebras, where we show the relationship of triple centroids, triple quasi centroids and central triple derivation with Lie triple derivations and generalized Lie triple derivations of Lie color algebras L. A classification of Lie triple derivations algebra of all perfect Lie color algebras is given, where we prove that for a perfect and centerless Lie color algebra, TDer(L)=Der(L) and TDer(Der(L))=Inn(Der(L)).
Symmetry of Dressed Photon
Authors: Ochiai Hiroyuki
Published: July 2021

Motivated by describing the symmetry of a theoretical model of dressed photons, we introduce several spaces with Lie group actions and the morphisms between them depending on three integer parameters n≥r≥s on dimensions. We discuss the symmetry on these spaces using classical invariant theory, orbit decomposition of prehomogeneous vector spaces, and compact reductive homogeneous space such as Grassmann manifold and flag variety. Finally, we go back to the original dressed photon with n=4,r=2,s=1.
Estimating the Variance of Estimator of the Latent Factor Linear Mixed Model Using Supplemented Expectation-Maximization Algorithm
Authors: Angraini Yenni , Notodiputro Khairil Anwar , Folmer Henk , Saefuddin Asep , Toharudin Toni
Published: July 2021

This paper deals with symmetrical data that can be modelled based on Gaussian distribution, such as linear mixed models for longitudinal data. The latent factor linear mixed model (LFLMM) is a method generally used for analysing changes in high-dimensional longitudinal data. It is usual that the model estimates are based on the expectation-maximization (EM) algorithm, but unfortunately, the algorithm does not produce the standard errors of the regression coefficients, which then hampers testing procedures. To fill in the gap, the Supplemented EM (SEM) algorithm for the case of fixed variables is proposed in this paper. The computational aspects of the SEM algorithm have been investigated by means of simulation. We also calculate the variance matrix of beta using the second moment as a benchmark to compare with the asymptotic variance matrix of beta of SEM. Both the second moment and SEM produce symmetrical results, the variance estimates of beta are getting smaller when number of subjects in the simulation increases. In addition, the practical usefulness of this work was illustrated using real data on political attitudes and behaviour in Flanders-Belgium.
Identifying the Attack Sources of Botnets for a Renewable Energy Management System by Using a Revised Locust Swarm Optimisation Scheme
Authors: Lin Hsiao-Chung , Wang Ping , Lin Wen-Hui , Chao Kuo-Ming , Yang Zong-Yu
Published: July 2021

Distributed denial of service (DDoS) attacks often use botnets to generate a high volume of packets and adopt controlled zombies for flooding a victim’s network over the Internet. Analysing the multiple sources of DDoS attacks typically involves reconstructing attack paths between the victim and attackers by using Internet protocol traceback (IPTBK) schemes. In general, traditional route-searching algorithms, such as particle swarm optimisation (PSO), have a high convergence speed for IPTBK, but easily fall into the local optima. This paper proposes an IPTBK analysis scheme for multimodal optimisation problems by applying a revised locust swarm optimisation (LSO) algorithm to the reconstructed attack path in order to identify the most probable attack paths. For evaluating the effectiveness of the DDoS control centres, networks with a topology size of 32 and 64 nodes were simulated using the ns-3 tool. The average accuracy of the LS-PSO algorithm reached 97.06 for the effects of dynamic traffic in two experimental networks (number of nodes = 32 and 64). Compared with traditional PSO algorithms, the revised LSO algorithm exhibited a superior searching performance in multimodal optimisation problems and increased the accuracy in traceability analysis for IPTBK problems.
The Skewed-Elliptical Log-Linear Birnbaum–Saunders Alpha-Power Model
Authors: Martínez-Flórez Guillermo , Bolfarine Heleno , Gómez Yolanda M.
Published: July 2021

In this paper, the skew-elliptical sinh-alpha-power distribution is developed as a natural follow-up to the skew-elliptical log-linear Birnbaum–Saunders alpha-power distribution, previously studied in the literature. Special cases include the ordinary log-linear Birnbaum–Saunders and skewed log-linear Birnbaum–Saunders distributions. As shown, it is able to surpass the ordinary sinh-normal models when fitting data sets with high (above the expected with the sinh-normal) degrees of asymmetry. Maximum likelihood estimation is developed with the inverse of the observed information matrix used for standard error estimation. Large sample properties of the maximum likelihood estimators such as consistency and asymptotic normality are established. An application is reported for the data set previously analyzed in the literature, where performance of the new distribution is shown when compared with other proposed alternative models.
The Impact of the Course of Disease before Botulinum Toxin Therapy on the Course of Treatment and Long-Term Outcome in Cervical Dystonia
Authors: Hefter Harald , Schomaecker Isabelle , Schomaecker Max , Rosenthal Dietmar , Samadzadeh Sara
Published: July 2021

This study analyses the influence of the course of the disease of idiopathic cervical dystonia (CD) before botulinum toxin (BoNT) therapy on long-term outcomes. 74 CD-patients who were treated on a regular basis in the botulinum toxin outpatient department of the University of Düsseldorf and had received at least 3 injections were consecutively recruited after written informed consent. Patients were asked to rate the amount of change of CD in relation to the severity of CD at begin of BoNT therapy (IMPQ). Then they had to draw the course of disease of CD from onset of symptoms until initiation of BoNT therapy (CoDB-graph) on a sheet of paper into a square of 10 × 10 cm2 size. Remaining severity of CD was estimated by the treating physician using the TSUI-score. Demographical and treatment related data were extracted from the charts of the patients. Depending on the curvature four different types of CoDB-graphs could be distinguished. Time to BoNT therapy, increase of dose and improvement during BoNT treatment were significantly (p < 0.05) different when patients were split up according to CoDB-graph types. The lower the age at onset of symptoms, the shorter was the time to therapy (p < 0.02). Initial dose (p < 0.04) and actual dose (p < 0.009) were negatively correlated with the age of the patients at recruitment. The course of disease of CD before BoNT therapy has influence on long-term outcome. This has implications on patient management and information on the efficacy of BoNT treatment.
New Advancements in AdS/CFT in Lower Dimensions
Authors: Lozano Yolanda , Ramirez Anayeli
Published: July 2021

We review recent developments in the study of the AdS/CFT correspondence in lower dimensions. We start by summarising the classification of AdS3×S2 solutions in massive type IIA supergravity with (0, 4) supersymmetries and the construction of their 2D dual quiver CFTs. These theories are the seed for further developments that we review next. First, we construct a new class of AdS3 solutions in M-theory that describe M-strings in M5-brane intersections. Second, we generate a new class of AdS2×S3 solutions in massive IIA with four supercharges that we interpret as describing backreacted baryon vertices within the 5D N=1 QFT living in D4-D8 branes. Third, we construct two classes of AdS2 solutions in Type IIB. The first are dual to discrete light-cone quantised quantum mechanics living in null cylinders. The second class is interpreted as dual to backreacted baryon vertices within 4D N=2 QFT living in D3-D7 branes. Explicit dual quiver field theories are given for all classes of solutions. These are used to compute the central charges of the CFTs that are shown to agree with the holographic expressions.
Potential Phosphorylation of Viral Nonstructural Protein 1 in Dengue Virus Infection
Authors: Dechtawewat Thanyaporn , Roytrakul Sittiruk , Yingchutrakul Yodying , Charoenlappanit Sawanya , Siridechadilok Bunpote , Limjindaporn Thawornchai , Mangkang Arunothai , Prommool Tanapan , Puttikhunt Chunya , Songprakhon Pucharee , Kongmanas Kessiri , Kaewjew Nuttapong , Avirutnan Panisadee , Yenchitsomanus Pa-thai , Malasit Prida , Noisakran Sansanee
Published: July 2021

Dengue virus (DENV) infection causes a spectrum of dengue diseases that have unclear underlying mechanisms. Nonstructural protein 1 (NS1) is a multifunctional protein of DENV that is involved in DENV infection and dengue pathogenesis. This study investigated the potential post-translational modification of DENV NS1 by phosphorylation following DENV infection. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS), 24 potential phosphorylation sites were identified in both cell-associated and extracellular NS1 proteins from three different cell lines infected with DENV. Cell-free kinase assays also demonstrated kinase activity in purified preparations of DENV NS1 proteins. Further studies were conducted to determine the roles of specific phosphorylation sites on NS1 proteins by site-directed mutagenesis with alanine substitution. The T27A and Y32A mutations had a deleterious effect on DENV infectivity. The T29A, T230A, and S233A mutations significantly decreased the production of infectious DENV but did not affect relative levels of intracellular DENV NS1 expression or NS1 secretion. Only the T230A mutation led to a significant reduction of detectable DENV NS1 dimers in virus-infected cells; however, none of the mutations interfered with DENV NS1 oligomeric formation. These findings highlight the importance of DENV NS1 phosphorylation that may pave the way for future target-specific antiviral drug design.
The Role of Coinfections in the EBV–Host Broken Equilibrium
Authors: Sánchez-Ponce Yessica , Fuentes-Pananá Ezequiel M.
Published: July 2021

The Epstein–Barr virus (EBV) is a well-adapted human virus, and its infection is exclusive to our species, generally beginning in the childhood and then persisting throughout the life of most of the affected adults. Although this infection generally remains asymptomatic, EBV can trigger life-threatening conditions under unclear circumstances. The EBV lifecycle is characterized by interactions with other viruses or bacteria, which increases the probability of awakening its pathobiont capacity. For instance, EBV infects B cells with the potential to alter the germinal center reaction (GCR)—an adaptive immune structure wherein mutagenic-driven processes take place. HIV- and Plasmodium falciparum-induced B cell hyperactivation also feeds the GCR. These agents, along with the B cell tropic KSHV, converge in the ontogeny of germinal center (GC) or post-GC lymphomas. EBV oral transmission facilitates interactions with local bacteria and HPV, thereby increasing the risk of periodontal diseases and head and neck carcinomas. It is less clear as to how EBV is localized in the stomach, but together with Helicobacter pylori, they are known to be responsible for gastric cancer. Perhaps this mechanism is reminiscent of the local inflammation that attracts different herpesviruses and enhances graft damage and chances of rejection in transplanted patients. In this review, we discussed the existing evidence suggestive of EBV possessing the potential to synergize or cooperate with these agents to trigger or worsen the disease.
Impact of HCV Eradication on Lipid Metabolism in HIV/HCV Coinfected Patients: Data from ICONA and HepaICONA Foundation Cohort Study
Authors: Spaziante Martina , Taliani Gloria , Marchetti Giulia , Tavelli Alessandro , Lichtner Miriam , Cingolani Antonella , Cicalini Stefania , Biliotti Elisa , Girardi Enrico , Antinori Andrea , Puoti Massimo , d’Arminio Monforte Antonella , Cozzi-Lepri Alessandro
Published: July 2021

Objectives: HCV shows complex interactions with lipid metabolism. Our aim was to examine total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) changes in HIV/HCV coinfected patients, after achieving sustained virological response (SVR), according to different HCV genotypes and specific antiretroviral use. Methods: HIV/HCV coinfected patients, enrolled in the ICONA and HepaICONA cohorts, who achieved DAA-driven SVR were included. Paired t-tests were used to examine whether the pre- and post-SVR laboratory value variations were significantly different from zero. ANCOVA regression models were employed to estimate the causal effect of SVR and of PI/r use on lipid changes. The interaction between the effect of eradication and HCV genotype was formally tested. Results: six hundred and ninety-nine HIV/HCV coinfected patients were enrolled. After HCV eradication, a significant improvement in liver function occurred, with a significant decrease in AST, ALT, GGT, and total plasmatic bilirubin. TC and LDL-C significantly increased by 21.4 mg/dL and 22.4 mg/dL, respectively (p < 0.001), after SVR, whereas there was no evidence for a change in HDL-C (p = 0.45) and triglycerides (p = 0.49). Notably, the TC and LDL-C increase was higher for participants who were receiving darunavir/ritonavir, and the TC showed a more pronounced increase among HCV genotype 3 patients (interaction-p value = 0.002). Conclusions: complex and rapid changes in TC and LDL-C levels, modulated by HCV genotype and PI/r-based ART combinations, occurred in HIV/HCV coinfected patients after SVR. Further studies are needed to evaluate the clinical impact of these changes on the long-term risk of cardiovascular disease.
Young Adults’ Intentions and Rationales for COVID-19 Vaccination Participation: Evidence from a Student Survey in Ho Chi Minh City, Vietnam
Authors: Khuc Quy Van , Nguyen Trang , Nguyen Thuy , Pham Linh , Le Dang-Trung , Ho Hong-Hai , Truong Tien-Binh , Tran Quoc-Khai
Published: July 2021

The COVID-19 pandemic, a source of fear and anxiety worldwide, has caused many adverse impacts. Collaborative efforts to end COVID-19 have included extensive research on vaccines. Many vaccination campaigns have been launched in many countries, including Vietnam, to create community immunization. However, citizens’ willingness to participate is a prerequisite for effective vaccination programs and other related policies. Among all demographic groups, participation rates among young adults are of interest because they are an important workforce and are a source of high infection risk in the community. In March 2021, a pool of approximately 6000 participants in Ho Chi Minh City were randomly polled using an email-based online survey. The exploratory results of 398 valid observations show that students’ perceptions of the dangers of COVID-19 and the importance of vaccination were both relatively high (4.62/5 and 4.74/5, respectively). Furthermore, 83.41 percent of students polled (n = 332) chose vaccination, while 16.59 percent chose hesitation (n = 64) and not to be vaccinated (n = 2). More importantly, our estimated results of the Bayesian regression model (BRM) show that the perceived importance of the vaccine, concerns about the vaccine’s side effects, and a lack of access to information are the top three reasons for their reluctance and/or refusal to get vaccinated. These findings are a valuable resource for politicians, researchers, and those interested in COVID-19 vaccinations to devise and execute campaigns to effectively combat this terrifying pandemic.
Bioinformatics Prediction of SARS-CoV-2 Epitopes as Vaccine Candidates for the Colombian Population
Authors: Montes-Grajales Diana , Olivero-Verbel Jesus
Published: July 2021

Coronavirus disease (COVID-19) pandemic caused by the coronavirus SARS-CoV-2 represents an enormous challenge to global public health, with thousands of infections and deaths in over 200 countries worldwide. The purpose of this study was to identify SARS-CoV-2 epitopes with potential to interact in silico with the alleles of the human leukocyte antigen class I (HLA I) and class II (HLA II) commonly found in the Colombian population to promote both CD4 and CD8 immune responses against this virus. The generation and evaluation of the peptides in terms of HLA I and HLA II binding, immune response, toxicity and allergenicity were performed by using computer-aided tools, such as NetMHCpan 4.1, NetMHCIIpan 4.0, VaxiJem, ToxinPred and AllerTop. Furthermore, the interaction between the predicted epitopes with HLA I and HLA II proteins frequently found in the Colombian population was studied through molecular docking simulations in AutoDock Vina and interaction analysis in LigPlot+. One of the promising peptides proposed in this study is the HLA I epitope YQPYRVVVL, which displayed an estimated coverage of over 82% and 96% for the Colombian and worldwide population, respectively. These findings could be useful for the design of new epitope-vaccines that include Colombia among their population target.