bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comparative Study on the Reduction Effect in Greenhouse Gas Emissions between the Combined Heat and Power Plant and Boiler
Authors: Kim Dahye , Kim Kyung-Tae , Park Young-Kwon
Published: June 2020

The purpose of this study is to compare the effect of a reduction in greenhouse gas (GHG) emissions between the combined heat and power (CHP) plant and boiler, which became the main energy-generating facilities of “anaerobic digestion” (AD) biogas produced in Korea, and analyze the GHG emissions in a life cycle. Full-scale data from two Korean “wastewater treatment plants” (WWTPs), which operated boilers and CHP plants fueled by biogas, were used in order to estimate the reduction potential of GHG emissions based on a “life cycle assessment” (LCA) approach. The GHG emissions of biogas energy facilities were divided into pre-manufacturing stages, production stages, pretreatment stages, and combustion stages, and the GHG emissions by stages were calculated by dividing them into Scope1, Scope2, and Scope3. Based on the calculated reduction intensity, a comparison of GHG reduction effects was made by assuming a scenario in which the amount of biogas produced at domestic sewage treatment plants used for boiler heating is replaced by a CHP plant. Four different scenarios for utilizing biogas are considered based on the GHG emission potential of each utilization plant. The biggest reduction was in the scenario of using all of the biogas in CHP plants and heating the anaerobic digester through district heating. GHG emissions in a life cycle were slightly higher in boilers than in CHP plants because GHG emissions generated by pre-treatment facilities were smaller than other emissions, and lower Scope2 emissions in CHP plants were due to their own use of electricity produced. It was confirmed that the CHP plant using biogas is superior to the boiler in terms of GHG reduction in a life cycle.
Consumer Behavior towards Regional Eco-Labels in Slovakia
Authors: Jaďuďová Jana , Badida Miroslav , Badidová Anna , Marková Iveta , Ťahúňová Miriam , Hroncová Emília
Published: June 2020

Slovakia, as part of the European Union, participates in all forms of regional development and sustainability. A transparent form of regional development and sustainability is regional labeling, which has a 10-year tradition. Our regions represent excellent potential for the development of domestic products. Acceptance of essential requirements for regional products (domestic raw materials, manual work share, respect for the environment) opens up opportunities for the labor market, promotes tourism, and increases citizens’ purchase ability, none of which are clearly demonstrable in Slovak regions. Residents of individual regions have specific approaches in relation to regional brands depending on the region studied. For the purpose of the survey, four regions of southern Slovakia (with common environmental morphology and different industrial development) were selected. Indicators of age, gender, education, monthly income, and location relative to regional product preferences were studied. The results obtained were processed by cluster analysis (as a way of segmenting consumers). An average conscious purchaser of regional products is a local productive middle-aged person with a secondary or tertiary education, either male or female, and from a more economically advanced region. The results show regional branding as a mobilizing function for connecting inhabitants and the subsequent joint presentation of regional activities.
A Taxonomy of Crisis Management Functions
Authors: Tagarev Todor , Ratchev Valeri
Published: June 2020

The management of crises triggered by natural or manmade events requires a concerted effort of various actors crossing institutional and geographic boundaries. Technological advances allow to make crisis management more effective, but innovation is hindered by dispersed and often disconnected knowledge on the lessons learned, gaps, and solutions. Taxonomies enable the search for information of potential interest. This article presents a taxonomy of crisis management functions, designed on the basis of a conceptual model integrating the concepts of hazard, vulnerability, risk, and community, and the main consequence- and management-based concepts. At its highest level, the taxonomy includes ten functional areas: preparatory (mitigation, capability development, and strategic adaptiveness), operational (protection, response, and recovery), and common (crisis communications and information management; command, control, and coordination; logistics; and security management). The taxonomy facilitates the navigation of online platforms and the matching of needs and solutions. It has broader applications, e.g., for structuring the assessment of the societal impact of crisis management solutions and as a framework for a comprehensive assessment of disaster risk reduction measures. While the taxonomy was developed within a research and innovation project supported by the European Union, it reflects and is compatible with established international concepts and classification schemes, and is thus applicable by a wider international community.
Entrepreneurship Through Open Data: An Opportunity for Sustainable Development
Authors: Corrales-Garay Diego , Mora-Valentín Eva-María , Ortiz-de-Urbina-Criado Marta
Published: June 2020

Entrepreneurship and open data are key elements in the sustainable development field, improving economic, social, and environmental dimensions. However, entrepreneurship and open data are barely studied together in the literature from a theoretical perspective. Therefore, this study identifies the main themes in the previous studies and proposes a conceptual model for analyzing entrepreneurship through open data. For this purpose, a descriptive analysis and a co-word analysis were performed. Results show that the subject is multidisciplinary, and the main theme of study is how different agents reuse information released by public administrations to generate new entrepreneurial initiatives, especially novel business models associated with new mobile applications. Open data sources, innovation, and business models are studied as critical factors for analyzing entrepreneurship through open data. Likewise, a conceptual model is presented and emerging themes for future research are proposed. Among them, the importance of encouraging collaboration between different agents in the open data ecosystem for service development and improvement is emphasized. Our study identifies an emerging theme that is still in an early phase: The study of sustainable entrepreneurship through open data as a value creation initiative to address global sustainable development.
Calculation of Potential Radiation Doses Associated with Predisposal Management of Dismantled Steam Generators from Nuclear Power Plants
Authors: Chun Ga Hyun , Park Jin-ho , Cheong Jae Hak
Published: June 2020

Although the generation of large components from nuclear power plants is expected to gradually increase in the future, comprehensive studies on the radiological risks of the predisposal management of large components have been rarely reported in open literature. With a view to generalizing the assessment framework for the radiological risks of the processing and transport of a representative large component—a steam generator—12 scenarios were modeled in this study based on past experiences and practices. In addition, the general pathway dose factors normalized to the unit activity concentration of radionuclides for processing and transportation were derived. Using the general pathway dose factors, as derived using the approach established in this study, a specific assessment was conducted for steam generators from a pressurized water reactor (PWR) or a pressurized heavy water reactor (PHWR) in Korea. In order to demonstrate the applicability of the developed approach, radiation doses reported from actual experiences and studies are compared to the calculated values in this study. The applicability of special arrangement transportation of steam generators assumed in this study is evaluated in accordance with international guidance. The generalized approach to assessing the radiation doses can be used to support optimizing the predisposal management of large components in terms of radiological risk.
Scheduling Charging of Electric Vehicles in a Secured Manner by Emphasizing Cost Minimization Using Blockchain Technology and IPFS
Authors: Javed Muhammad Umar , Javaid Nadeem , Aldegheishem Abdulaziz , Alrajeh Nabil , Tahir Muhammad , Ramzan Muhammad
Published: June 2020

In this work, Electric Vehicles (EVs) are charged using a new and improved charging mechanism called the Mobile-Vehicle-to-Vehicle (M2V) charging strategy. It is further compared with conventional Vehicle-to-Vehicle (V2V) and Grid-to-Vehicle (G2V) charging strategies. In the proposed work, the charging of vehicles is done in a Peer-to-Peer (P2P) manner; the vehicles are charged using Charging Stations (CSs) or Mobile Vehicles (MVs) in the absence of a central entity. CSs are fixed entities situated at certain locations and act as charge suppliers, whereas MVs act as prosumers, which have the capability of charging themselves and also other vehicles. In the proposed system, blockchain technology is used to tackle the issues related with existing systems, such as privacy, security, lack of trust, etc., and also to promote transparency, data immutability, and a tamper-proof nature. Moreover, to store the data related to traffic, roads, and weather conditions, a centralized entity, i.e., Transport System Information Unit (TSIU), is used. It helps in reducing the road congestion and avoids roadside accidents. In the TSIU, an Inter-Planetary File System (IPFS) is used to store the data in a secured manner after removing the data’s redundancy through data filtration. Furthermore, four different types of costs are calculated mathematically, which ultimately contribute towards calculating the total charging cost. The shortest distance between a vehicle and the charging entities is calculated using the Great-Circle Distance formula. Moving on, both the time taken to traverse this shortest distance and the time to charge the vehicles are calculated using real-time data of four EVs. Location privacy is also proposed in this work to provide privacy to vehicle users. The power flow and the related energy losses for the above-mentioned charging strategies are also discussed in this work. An incentive provisioning mechanism is also proposed on the basis of timely delivery of credible messages, which further promotes users’ participation. In the end, simulations are performed and results are obtained that prove the efficiency of the proposed work, as compared to conventional techniques, in minimizing the EVs’ charging cost, time, and distance.
Impact of Samarkand’s Destination Attributes on International Tourists’ Revisit and Word-of-Mouth Intention
Authors: Jumanazarov Sanjar , Kamilov Alisher , Kiatkawsin Kiattipoom
Published: June 2020

Samarkand, Uzbekistan is a relatively unknown but emerging tourism destination. The city was once a major trading hub along the Great Silk Road. The once great city of Samarkand was hidden from the world tourism market, only to emerge after the country gained its independence in 1991. Since then, the artistically beautiful and historically-rich monuments have been attracting tourists from around the world. However, Samarkand has not been gaining much research attention at the same rate as international tourist arrivals. Thus, this study aims to comprehensively assess the city’s destination attributes and their impact on international visitor loyalty behaviors. The literature review process identified 16 destination attribute dimensions. Additionally, cognitive and affective evaluation, satisfaction, revisit intention, and word-of-mouth intention were identified and added to form the study model. A total of 223 international tourist samples were collected in Samarkand to validate the proposed model. The findings revealed 10 attributes to be consistently rated by the samples. Subsequently, the attributes were significantly influencing all subsequent hypothesized relationships. Both theoretical and practical implications are also discussed.
Environmental Risk Management for Museums in Historic Buildings through an Innovative Approach: A Case Study of the Pinacoteca di Brera in Milan (Italy)
Authors: Lucchi Elena
Published: June 2020

In the contemporary age, museums are dealing with unexpected challenges, related to the transformation of social structures, educative methods and cultural diffusion. The conversion of heritage buildings into exhibition halls and the renovation of existent exhibits involve a series of environmental risks and preservation issues. The study aims to demonstrate that conservation and human comfort are mutually compatible, when based on rational planning, interdisciplinary cooperation, and extensive knowledge of the features of buildings and collections. This study carries out an operative strategy for assessing and managing the environmental risks in museum buildings. To validate its suitability, it is applied to the Pinacoteca di Brera in Milan (Italy), an old palace completely reshaped in the 20th century following the typical design concepts of the “Modern Movement of Architecture” (e.g., rational planning, use of innovative technologies and materials, profusion of natural light integrated with artificial lighting, etc.). Several solutions adopted in these years caused both heritage decay and human discomfort. In addition, the insertion of new functions required a complete modification of the original design project. For this reason, the proposed tool supports the environmental risk management connected with these transformations, also defining clear maintenance guidelines, and planning low-engineering and low-impact solutions to satisfy, in a practical way, the daily needs of conservators, heritage authorities and designers. Furthermore, technical skills and the awareness of museum staff has been improved.
Synergies of Cutting Air Pollutants and CO2 Emissions by the End-of-Pipe Treatment Facilities in a Typical Chinese Integrated Steel Plant
Authors: Tang Haoyue , Jiang Ping , He Jia , Ma Weichun
Published: June 2020

Reducing industrial emissions has become increasingly important, given China’s ongoing industrialization. In this study, the reduction in CO2 emissions and air pollutants due to end-of-pipe treatment in a typical integrated steel plant in China was assessed. The emissions were subdivided into sector levels, including main production and auxiliary departments. The synergies of reducing air pollutants and CO2 emissions using end-of-pipe treatment technologies were quantified, including direct and indirect effects. The results show that (1) using the carbon balance method is more suitable for the greenhouse gas (GHG) emissions of the steel plants in China at the enterprise and sector levels. The carbon-related parameters adopted in the carbon balance method strongly impact the accuracy of the emission calculation. (2) Compared with the direct synergistic CO2 emissions caused by chemical reactions, the indirect emissions due to the power consumption of the end-of-pipe facilities is more significant. (3) To achieve the control of local air pollutants and CO2 emissions, the negative effects of CO2 emissions caused by the end-of-pipe treatment technologies should be considered.
Time and Mobility after the Anthropocene
Authors: Heikkurinen Pasi , Ruuska Toni , Valtonen Anu , Rantala Outi
Published: June 2020

The Special Issue on ‘After the Anthropocene: Time and Mobility’ is published. It discusses the geological time to follow the human-dominated epoch and ways to move there. In addition to this editorial, a total of five articles are published in the issue. The articles engage with a variety of social science disciplines—ranging from economics and sociology to philosophy and political science—and connect to the natural science insights on the Anthropocene. The issue calls for going beyond anthropocentrism in sustainability theory and practice in order to exit the Anthropocene with applications and insights in the contexts of politics (Ruuska et al., 2020), energy (Mohorčich, 2020), tourism (Rantala et al., 2020), food (Mazac and Tuomisto, 2020) and management (Küpers, 2020). We hope that you will find this Special Issue interesting and helpful in contributing to sustainable change.
Reinforcement Learning in Blockchain-Enabled IIoT Networks: A Survey of Recent Advances and Open Challenges
Authors: Jameel Furqan , Javaid Uzair , Khan Wali Ullah , Aman Muhammad Naveed , Pervaiz Haris , Jäntti Riku
Published: June 2020

Blockchain is emerging as a promising candidate for the uberization of Internet services. It is a decentralized, secure, and auditable solution for exchanging, and authenticating information via transactions, without the need of a trusted third party. Therefore, blockchain technology has recently been integrated with industrial Internet-of-things (IIoT) networks to help realize the fourth industrial revolution, Industry 4.0. Though blockchain-enabled IIoT networks may have the potential to support the services and demands of next-generation networks, the gap analysis presented in this work highlights some of the areas that need improvement. Based on these observations, the article then promotes the utility of reinforcement learning (RL) techniques to address some of the major issues of blockchain-enabled IIoT networks such as block time minimization and transaction throughput enhancement. This is followed by a comprehensive case study where a Q-learning technique is used for minimizing the occurrence of forking events by reducing the transmission delays for a miner. Extensive simulations have been performed and the results have been obtained for the average transmission delay which relates to the forking events. The obtained results demonstrate that the Q-learning approach outperforms the greedy policy while having a reasonable level of complexity. To further develop the blockchain-enabled IIoT networks, some future research directions are also documented. While this article highlights the applications of RL techniques in blockchain-enabled IIoT networks, the provided insights and results could pave the way for rapid adoption of blockchain technology.
Intergroup Comparison of Personalities in the Preferred Pricing of Public Transport in Rush Hours: Data Revisited
Authors: Pavlíček Antonín , Sudzina František
Published: June 2020

Public authorities and administrations in the developed world are trying to reduce air pollution through the introduction and promotion of public transport. Typically, passengers are charged flat fares. However, with passenger numbers rising, this flat rate pricing model ceases to be sustainable, and a new trend arises—to charge more during traffic peaks as an incentive to even the load and travel outside of rush hours. However, it can be also argued that prices should be lower during rush hours due to poorer service quality—public transportation tends to be crowded and slow. Our on-line questionnaire did not discuss the logic of pricing models, having only measured the preferences of Czech university students (N = 256). The objective was to investigate whether there is a difference in demographic factors or in personality traits between respondents preferring a lower, flat, or higher pricing model. One-way analysis of variance was used for the intergroup comparison. The majority of respondents prefer flat pricing; higher pricing was the least preferred of the three considered models. The main findings were that men, narcissists and people who tend to find fault with others (i.e. lower in one facet of agreeableness) were in favor of higher prices during rush hours. In particular, the latter finding may be useful for policy makers, as it suggests that there ought to be no or only a little tension after higher rush hours prices are introduced.
Safety Science, a Systems Thinking Perspective: From Events to Mental Models and Sustainable Safety
Authors: Blokland Peter , Reniers Genserik
Published: June 2020

In the past one hundred years, concepts such as risk, safety and security have become ever more important and they represent a growing concern in our society. These concepts are also important subjects of study to enhance sustainability. During the past fifty years, safety science has gradually developed as an independent field of science. In this period, different concepts, theories, models and research traditions have emerged, each with its specific perspective. Safety science is now focused on finding ways to proactively achieve safety versus reaching safety in a reactive way. We think this increasing awareness and search for proactiveness can be found and presented when viewed in light of the systems thinking iceberg model, where increasing awareness and proactiveness can be seen as digging deeper into this systems thinking iceberg, discovering the levels of systems, structures and ultimately the mental models that are “below the waterline”. It offers a way forward in understanding, and proactively managing, risk, safety, security and sustainable performance, in organizations and ultimately in society as a whole.
How to Improve the Diffusion of Climate-Smart Agriculture: What the Literature Tells us
Authors: Fusco Giulio , Melgiovanni Marta , Porrini Donatella , Ricciardo Traci Michelle
Published: June 2020

Climate-smart agriculture (CSA) is a technologically innovative response to the challenges faced by agriculture due to climate change. Its implementation needs a change of mentality in the direction of an approach that takes into account how the increase in technologically induced productivity affects climate change. In the belief that the in-depth analysis conducted by scientific research plays a fundamental role, we explore the characteristics, actors, and pillars of CSA, examining both the scientific literature and financed projects. Specifically, through a systematic review of the literature we address both the application and barriers to implementation at a global level, and then we focus on a case study of the geographical distribution of CSA projects in Europe. Our results show a heterogeneous framework in which we can note discrepancies among countries. Finally, as conclusive remarks, we consider the type of policies that could be implemented to improve the diffusion of CSA in the near future.
Categorizing Organic Grain Buyers in the Midwestern United States
Authors: Torres Ariana P. , Lancaster Nicholas A. , Vilas Boas Luiz H. B.
Published: June 2020

Though the demand for organic grains is increasing, domestic supply is falling short. One of the major barriers to entry in the organic grain market for producers is the inability to identify an appropriate buyer, as well as a lack of understanding buyer perceptions, assistance offered, and contracting strategies. While classifications of organic producers exist, and have helped researchers and policymakers develop incentives, no such classification exists for organic grain buyers. Previous works have identified communication gaps between buyers and producers of organic grains, yet buyers’ beliefs and requirements regarding organic grain are not well documented in literature. Drawing from the personal values theory, this study proposes the categorization of organic grain buyers based on their commitment to the organic industry, with categories such as committed organic and pragmatic organic. We profiled grain purchases, buying arrangements, grain requirements, relationships, and business characteristics by buyer type. Means comparisons among groups showed that committed organic buyers seem to be primarily driven by social focus values, while pragmatic organic buyers tend to show values related to personal focus. A principal component analysis suggested the existence of three components constructed by contract-, perceptions-, and relationship-oriented characteristics in buyers. Our results allowed us to identify potential marketing opportunities by providing insight regarding types of assistance offered by buyers, how to build and maintain a relationship with buyers, types of purchasing agreements used, and purchasing agreement characteristics and requirements. Industry stakeholders can use this information to identify appropriate buyers based on times contracts are signed, payment timing, storage and transportation requirements, and the amount of organic practice documentation buyers require. Our categorization can provide the foundation for further research in the organic grain industry.
Empirical Research on the Fama-French Three-Factor Model and a Sentiment-Related Four-Factor Model in the Chinese Blockchain Industry
Authors: Ji Ziyang , Chang Victor , Lan Hao , Robert Hsu Ching-Hsien , Valverde Raul
Published: June 2020

As one of the most significant components of financial technology (FinTech), blockchain technology arouses the interests of numerous investors in China, and the number of companies engaged in this field rises rapidly. The emotion of investors has an effect on stock returns, which is a hot topic in behavioral finance. Blockchain is an essential part of FinTech, and with the fast development of this technology, investors’ sentiment varies as well. The online information that directly reflects investors’ mood could be utilized for mining and quantifying to construct a sentiment index. For a better understanding of how well some factors adequately explain the return of stocks related to blockchain companies in the Chinese stock market, the Fama-French three-factor model (FFTFM) will be introduced in this paper. Furthermore, sentiment could be a new independent variable to enhance the explanatory power of the FFTFM. A comparison between those two models reveals that the sentiment factor could raise the explanatory power. The results also indicate that the Chinses blockchain industry does not own the size effect and book-to-market effect.
Scientometric Analysis of Research in Energy Efficiency and Citizen Science through Projects and Publications
Authors: De Filippo Daniela , Lascurain María Luisa , Pandiella-Dominique Andres , Sanz-Casado Elias
Published: June 2020

Energy efficiency is part of the commitment to environmental sustainability made by the organizations that promote and finance research and by the researchers that make this field their subject of study. Although there is growing interest in the subject, it is worth asking whether the research has been approached considering citizens’ needs or citizens’ participation. The main objective of this study is to analyse whether energy efficiency research has adopted a citizen science perspective. Using scientometric methods, the SCOPUS and CORDIS databases were consulted and a document search strategy was developed to gather information on publications and projects. The analysis revealed that, out of 265 projects under the Seventh Framework Programme on Energy Efficiency, only seven (3%) were related to citizen science. Although there is a large volume of publications on energy efficiency (over 200,000) and a considerable number of publications on citizen science (>30,000 articles), only 336 documents were identified that deal with both topics. The number of projects and publications on these topics has increased in recent years, with universities being the institutions that have published the most. Content analysis found that the most frequent topics are public perception of the use of renewable energies; citizen participation in measures to address climate change and global warming; and the involvement of different stakeholders in the use and responsible consumption of energy. Finally, information was collected on the impact of these publications on social media and altmetric tools. It was revealed that 33% of the 336 papers have had a presence in different sources, especially Twitter. This is a high figure compared with the dissemination achieved by papers from other disciplines.
An Extended Analysis on Robust Dissipativity of Uncertain Stochastic Generalized Neural Networks with Markovian Jumping Parameters
Authors: Humphries Usa , Rajchakit Grienggrai , Sriraman Ramalingam , Kaewmesri Pramet , Chanthorn Pharunyou , Lim Chee Peng , Samidurai Rajendran
Published: June 2020

The main focus of this research is on a comprehensive analysis of robust dissipativity issues pertaining to a class of uncertain stochastic generalized neural network (USGNN) models in the presence of time-varying delays and Markovian jumping parameters (MJPs). In real-world environments, most practical systems are subject to uncertainties. As a result, we take the norm-bounded parameter uncertainties, as well as stochastic disturbances into consideration in our study. To address the task, we formulate the appropriate Lyapunov–Krasovskii functional (LKF), and through the use of effective integral inequalities, simplified linear matrix inequality (LMI) based sufficient conditions are derived. We validate the feasible solutions through numerical examples using MATLAB software. The simulation results are analyzed and discussed, which positively indicate the feasibility and effectiveness of the obtained theoretical findings.
Concrete Based Jeffrey Nanofluid Containing Zinc Oxide Nanostructures: Application in Cement Industry
Authors: Sheikh Nadeem Ahmad , Chuan Ching Dennis Ling , Khan Ilyas , Ahmad Afnan , Ammad Syed
Published: June 2020

Concrete is a non-Newtonian fluid which is a counterexample of Jeffrey fluid. The flow of Jeffrey fluid is considered containing nanostructures of zinc oxide in this study. The flow of the nanofluid is modeled in terms of partial fractional differential equations via Atangana–Baleanu (AB) fractional derivative approach and then solved using the integral transformation. Specifically, the applications are discussed in the field of concrete and cement industry. The variations in heat transfer rate and skin friction have been observed for different values of volume fractions of nanoparticles. The results show that by adding 4% Z n O nanoparticles increase skin friction up to 15%, ultimately enhancing the adhesion capacity of concrete. Moreover, Z n O increase the density of concrete, minimizing the pores in the concrete and consequently increasing the strength of concrete. The solutions are simplified to the corresponding solutions of the integer ordered model of Jeffrey-nanofluid. Applications of this work can be found in construction engineering and management such as buildings, roads, tunnels, bridges, airports, railroads, dams, and utilities.
Ordered Gyrovector Spaces
Authors: Kim Sejong
Published: June 2020

The well-known construction scheme to define a partial order on a vector space is to use a proper convex cone. Applying this idea to the gyrovector space we construct the partial order, called a gyro-order. We also give several inequalities of gyrolines and cogyrolines in terms of the gyro-order.
Effect of Zinc Oxide Nano-Additives and Soybean Biodiesel at Varying Loads and Compression Ratios on VCR Diesel Engine Characteristics
Authors: S. Gavhane Rakhamaji , M. Kate Ajit , Pawar Abhay , Safaei Mohammad Reza , M. Soudagar Manzoore Elahi , Mujtaba Abbas Muhammad , Muhammad Ali Hafiz , R Banapurmath Nagaraj , Goodarzi Marjan , Badruddin Irfan Anjum , Ahmed Waqar , Shahapurkar Kiran
Published: June 2020

The present investigation is directed towards synthesis of zinc oxide (ZnO) nanoparticles and steady blending with soybean biodiesel (SBME25) to improve the fuel properties of SBME25 and enhance the overall characteristics of a variable compression ratio diesel engine. The soybean biodiesel (SBME) was prepared using the transesterification reaction. Numerous characterization tests were carried out to ascertain the shape and size of zinc oxide nanoparticles. The synthesized asymmetric ZnO nanoparticles were dispersed in SBME25 at three dosage levels (25, 50, and 75 ppm) with sodium dodecyl benzene sulphonate (SDBS) surfactant using the ultrasonication process. The quantified physicochemical properties of all the fuels blends were in symmetry with the American society for testing and materials (ASTM) standards. Nanofuel blends demonstrated enhanced fuel properties compared with SBME25. The engine was operated at two different compression ratios (18.5 and 21.5) and a comparison was made, and best fuel blend and compression ratio (CR) were selected. Fuel blend SBME25ZnO50 and compression ratio (CR) of 21.5 illustrated an overall enhancement in engine characteristics. For SBME25ZnO50 and CR 21.5 fuel blend, brake thermal efficiency (BTE) increased by 23.2%, brake specific fuel consumption (BSFC) were reduced by 26.66%, and hydrocarbon (HC), CO, smoke, and CO2 emissions were reduced by 32.234%, 28.21% 22.55% and 21.66%, respectively; in addition, the heat release rate (HRR) and mean gas temperature (MGT) improved, and ignition delay (ID) was reduced. In contrast, the NOx emissions increased for all the nanofuel blends due to greater supply of oxygen and increase in the temperature of the combustion chamber. At a CR of 18.5, a similar trend was observed, while the values of engine characteristics were lower compared with CR of 21.5. The properties of nanofuel blend SBME25ZnO50 were in symmetry and comparable to the diesel fuel.
An Upper Bound of the Third Hankel Determinant for a Subclass of q-Starlike Functions Associated with k-Fibonacci Numbers
Authors: Shafiq Muhammad , Srivastava Hari M. , Khan Nazar , Ahmad Qazi Zahoor , Darus Maslina , Kiran Samiha
Published: June 2020

In this paper, we use q-derivative operator to define a new class of q-starlike functions associated with k-Fibonacci numbers. This newly defined class is a subclass of class A of normalized analytic functions, where class A is invariant (or symmetric) under rotations. For this function class we obtain an upper bound of the third Hankel determinant.
Symmetry-Adapted Machine Learning for Information Security
Authors: Park Jong Hyuk
Published: June 2020

Nowadays, data security is becoming an emerging and challenging issue due to the growth in web-connected devices and significant data generation from information and communication technology (ICT) platforms. Many existing types of research from industries and academic fields have presented their methodologies for supporting defense against security threats. However, these existing approaches have failed to deal with security challenges in next-generation ICT systems due to the changing behaviors of security threats and zero-day attacks, including advanced persistent threat (APT), ransomware, and supply chain attacks. The symmetry-adapted machine-learning approach can support an effective way to deal with the dynamic nature of security attacks by the extraction and analysis of data to identify hidden patterns of data. It offers the identification of unknown and new attack patterns by extracting hidden data patterns in next-generation ICT systems. Therefore, we accepted twelve articles for this Special Issue that explore the deployment of symmetry-adapted machine learning for information security in various application areas. These areas include malware classification, intrusion detection systems, image watermarking, color image watermarking, battlefield target aggregation behavior recognition models, Internet Protocol (IP) cameras, Internet of Things (IoT) security, service function chains, indoor positioning systems, and cryptoanalysis.
Estimation of Natural Radionuclides’ Concentration of the Plutonic Rocks in the Sakarya Zone, Turkey Using Multivariate Statistical Methods
Authors: Yalcin Fusun , Ilbeyli Nurdane , Demirbilek Mehmet , Yalcin Mustafa Gurhan , Gunes Alper , Kaygusuz Abdullah , Ozmen Suleyman Fatih
Published: June 2020

The study aimed to determine the natural radioactivity levels of 226Ra, 232Th, and 40K by the Gamma-Ray spectrometry method, and radiological hazard parameters of the plutonic rocks in the Western and Central Sakarya Zone and to analyze the data using multivariate statistical methods. The average radiological values of samples were determined as 40K (1295.3 Bq kg−1) > 232Th (132.1 Bq kg−1) > 226Ra (119.7 Bq kg−1). According to the skewness values of the distributions of the examined radionuclides, 226Ra (2.1) and 232Th (0.7) seemed to be positively right-skewed while 40K (−0.2) had a negatively right-skewed histogram. On the other hand, the following kurtosis values were calculated for the distributions: 226Ra (5.8 > 3), 232Th (−0.7), and 40K (−0.8). Kolmogorov–Smirnov and Shapiro–Wilk tests were applied to the data to test their normality. Therefore, Spearman’s correlation coefficient method was performed. The radionuclides of 226Ra and 232Th were found to have a positive correlation with radiological hazard parameters of the samples. 2 (two)-related factors identified, and the cumulative value was calculated to be 98.7% on the basis of the Scree Plot. According to the hierarchical cluster analysis, the samples that are grouped with those from Camlik region are prominent. The average radioactivity values of Camlik, Sogukpinar, Karacabey, and Sogut (except for 232Th) regions were detected to be higher than the world averages while the value of 40K was also found to be higher than the average values of various countries in the world.
Monaural Singing Voice and Accompaniment Separation Based on Gated Nested U-Net Architecture
Authors: Geng Haibo , Hu Ying , Huang Hao
Published: June 2020

This paper proposes a separation model adopting gated nested U-Net (GNU-Net) architecture, which is essentially a deeply supervised symmetric encoder–decoder network that can generate full-resolution feature maps. Through a series of nested skip pathways, it can reduce the semantic gap between the feature maps of encoder and decoder subnetworks. In the GNU-Net architecture, only the backbone not including nested part is applied with gated linear units (GLUs) instead of conventional convolutional networks. The outputs of GNU-Net are further fed into a time-frequency (T-F) mask layer to generate two masks of singing voice and accompaniment. Then, those two estimated masks along with the magnitude and phase spectra of mixture can be transformed into time-domain signals. We explored two types of T-F mask layer, discriminative training network and difference mask layer. The experiment results show the latter to be better. We evaluated our proposed model by comparing with three models, and also with ideal T-F masks. The results demonstrate that our proposed model outperforms compared models, and it’s performance comes near to ideal ratio mask (IRM). More importantly, our proposed model can output separated singing voice and accompaniment simultaneously, while the three compared models can only separate one source with trained model.
Quantum Key Distillation Using Binary Frames
Authors: Lizama-Perez Luis A. , López J. Mauricio
Published: June 2020

We introduce a new integral method for Quantum Key Distribution to perform sifting, reconciliation and amplification processes to establish a cryptographic key through the use of binary matrices called frames which are capable to increase quadratically the secret key rate. Since the eavesdropper has no control on Bob’s double matching detection events, our protocol is not vulnerable to the Intercept and Resend (IR) attack nor the Photon Number Splitting (PNS) attack. The method can be implemented with the usual optical Bennett–Brassard ( B B 84 ) equipment allowing strong pulses in the quantum regime.
Listeria monocytogenes Interferes with Host Cell Mitosis through Its Virulence Factors InlC and ActA
Authors: Costa Ana Catarina , Pinheiro Jorge , Reis Sandra A. , Cabanes Didier , Sousa Sandra
Published: June 2020

Listeria monocytogenes is among the best-characterized intracellular pathogens. Its virulence factors, and the way they interfere with host cells to hijack host functions and promote the establishment and dissemination of the infection, have been the focus of multiple studies over the last 30 years. During cellular infection, L. monocytogenes was shown to induce host DNA damage and delay the host cell cycle to its own benefit. However, whether the cell cycle stage would interfere with the capacity of Listeria to infect human cultured cell lines was never assessed. We found here that L. monocytogenes preferentially infects cultured cells in G2/M phases. Inside G2/M cells, the bacteria lead to an increase in the overall mitosis duration by delaying the mitotic exit. We showed that L. monocytogenes infection causes a sustained activation of the spindle assembly checkpoint, which we correlated with the increase in the percentage of misaligned chromosomes detected in infected cells. Moreover, we demonstrated that chromosome misalignment in Listeria-infected cells required the function of two Listeria virulence factors, ActA and InlC. Our findings show the pleiotropic role of Listeria virulence factors and their cooperative action in successfully establishing the cellular infection.
Toxicokinetics of Hydrolyzed Fumonisin B1 after Single Oral or Intravenous Bolus to Broiler Chickens Fed a Control or a Fumonisins-Contaminated Diet
Authors: Antonissen Gunther , De Baere Siegrid , Novak Barbara , Schatzmayr Dian , den Hollander Danica , Devreese Mathias , Croubels Siska
Published: June 2020

The toxicokinetics (TK) of hydrolyzed fumonisin B1 (HFB1) were evaluated in 16 broiler chickens after being fed either a control or a fumonisins-contaminated diet (10.8 mg fumonisin B1, 3.3 mg B2 and 1.5 mg B3/kg feed) for two weeks, followed by a single oral (PO) or intravenous (IV) dose of 1.25 mg/kg bodyweight (BW) of HFB1. Fumonisin B1 (FB1), its partially hydrolyzed metabolites pHFB1a and pHFB1b, and fully hydrolyzed metabolite HFB1, were determined in chicken plasma using a validated ultra-performance liquid chromatography–tandem mass spectrometry method. None of the broiler chicken showed clinical symptoms of fumonisins (FBs) or HFB1 toxicity during the trial, nor was an aberration in body weight observed between the animals fed the FBs-contaminated diet and those fed the control diet. HFB1 was shown to follow a two-compartmental pharmacokinetic model with first order elimination in broiler chickens after IV administration. Toxicokinetic parameters of HFB1 demonstrated a total body clearance of 16.39 L/kg·h and an intercompartmental flow of 8.34 L/kg·h. Low levels of FB1 and traces of pHFB1b were found in plasma of chickens fed the FBs-contaminated diet. Due to plasma concentrations being under the limit of quantification (LOQ) after oral administration of HFB1, no toxicokinetic modelling could be performed in broiler chickens after oral administration of HFB1. Moreover, no phase II metabolites, nor N-acyl-metabolites of HFB1 could be detected in this study.
Biomonitoring of Enniatin B1 and Its Phase I Metabolites in Human Urine: First Large-Scale Study
Authors: Rodríguez-Carrasco Yelko , Narváez Alfonso , Izzo Luana , Gaspari Anna , Graziani Giulia , Ritieni Alberto
Published: June 2020

Enniatins (Enns) are mycotoxins produced by Fusarium spp. which are a fungus widely spread throughout cereals and cereal-based products. Among all the identified enniatins, Enn B1 stands as one of the most prevalent analogues in cereals in Europe. Hence, the aim of this study was to evaluate for the first time the presence of Enn B1 and its phase I metabolites in 300 human urine samples using an ultrahigh-performance liquid chromatography high resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS) methodology. Enn B1 was detected in 94.3% of samples ranging from 0.007 to 0.429 ng/mL (mean value: 0.065 ng/mL). In accordance with previous in vitro and in vivo analysis, hydroxylated metabolites (78.0% samples) and carbonylated metabolites (66.0% samples) were tentatively identified as the major products. Results from this biomonitoring study point to a frequent intake of Enn B1 in the studied population, suggesting that in-depth toxicological studies are needed in order to understand the potential effects in humans.
PCR Detection and Phylogenetic Analysis of Megalocytivirus Isolates in Farmed Giant Sea Perch Lates calcarifer in Southern Taiwan
Authors: Tsai Jia-Ming , Huang Song-Lang , Yang Chung-Da
Published: June 2020

The Megalocytivirus genus includes three genotypes, red sea bream iridovirus (RSIV), infectious spleen and kidney necrosis virus (ISKNV), and turbot reddish body iridovirus (TRBIV), and has caused mass mortalities in various marine and freshwater fish species in East and Southeast Asia. Of the three genotypes, TRBIV-like megalocytivirus is not included in the World Organization for Animal Health (OIE)-reportable virus list because of its geographic restriction and narrow host range. In 2017, 39 cases of suspected iridovirus infection were isolated from fingerlings of giant sea perch (Lates calcarifer) cultured in southern Taiwan during megalocytivirus epizootics. Polymerase chain reaction (PCR) with different specific primer sets was undertaken to identify the causative agent. Our results revealed that 35 out of the 39 giant sea perch iridovirus (GSPIV) isolates were TRBIV-like megalocytiviruses. To further evaluate the genetic variation, the nucleotide sequences of major capsid protein (MCP) gene (1348 bp) from 12 of the 35 TRBIV-like megalocytivirus isolates were compared to those of other known. High nucleotide sequence identity showed that these 12 TRBIV-like GSPIV isolates are the same species. Phylogenetic analysis based on the MCP gene demonstrated that these 12 isolates belong to the clade II of TRBIV megalocytiviruses, and are distinct from RSIV and ISKNV. In conclusion, the GSPIV isolates belonging to TRBIV clade II megalocytiviruses have been introduced into Taiwan and caused a severe impact on the giant sea perch aquaculture industry.
Modelling PAHs Transfer from Polluted Soil to Herbaceous Species in Phytoremediation Attempts
Authors: Matsodoum Nguemté Pulchérie , Kengne Noumsi Ives Magloire , Djumyom Wafo Guy Valérie , Djocgoue Pierre François , Wanko Adrien
Published: June 2020

To address the soil–plant transfer modelling of 13 US-EPA Polycyclic Aromatic Hydrocarbons (PAHs), a mechanistic model—MM_19—has been developed based on the fugacity concept. For that, the Mackay_97 model has been improved in terms of reconsidering the losses related to the transport and transformation mechanisms taking place in the compartments—roots and aboveground shoots—of the three short-life species (Eleusine indica, Cynodon dactylon and Alternanthera sessilis). Model input parameters consist of both experimental and literature data, including the initial soil and air PAHs content, flowrates, PAHs physico-chemical properties, retention times and transport half-lives of PAHs inside plant species. Using in situ weather data and Penman’s law, xylem flows were estimated as the evapotranspiration for each plant. Model calibration was performed using a Generalized Reduced Gradient (GRG) nonlinear optimization solver method. Sensitivity analysis showed that the phloem flow was the most sensitive among all tested parameters. According to the Nash–Sutcliffe efficiency (NSE), the MM_19 model is more efficient than the Mackay_97 model for all three plant species. Finally, the impact of PAHs physico-chemical parameters on their sol-plant transfer was discussed in terms of slight, intermediate and high molecules weight. The NSE values showed that the MM_19 model is more efficient than the Mackay_97 model. Indeed, comparisons between experimental and simulated results in the MM_19 model showed similarities for each compartment of the plant species. Thus, the MM_19 model can be used to predict the soil–plant transfer of organic pollutants.