bluuebunny/crossref_metadata_2025 huggingface dataset:
Social Spider Algorithm for Training Artificial Neural Networks
Authors: Gülmez Burak , Kulluk Sinem
Published: January 2021

Artificial neural networks (ANNs) are one of the most widely used techniques for generalization, classification, and optimization. ANNs are inspired from the human brain and perform some abilities automatically like learning new information and making new inferences. Back-propagation (BP) is the most common algorithm for training ANNs. But the processing of the BP algorithm is too slow, and it can be trapped into local optima. The meta-heuristic algorithms overcome these drawbacks and are frequently used in training ANNs. In this study, a new generation meta-heuristic, the Social Spider (SS) algorithm, is adapted for training ANNs. The performance of the algorithm is compared with conventional and meta-heuristic algorithms on classification benchmark problems in the literature. The algorithm is also applied to real-world data in order to predict the production of a factory in Kayseri and compared with some regression-based algorithms and ANNs models. The obtained results and comparisons on classification benchmark datasets have shown that the SS algorithm is a competitive algorithm for training ANNs. On the real-world production dataset, the SS algorithm has outperformed all compared algorithms. As a result of experimental studies, the SS algorithm is highly capable for training ANNs and can be used for both classification and regression.
Efficient Approximation Algorithms for Minimum Dominating Sets in Social Networks
Authors: Truta Traian Marius , Campan Alina , Beckerich Matthew
Published: January 2021

Social networks are increasingly becoming an outlet that is more and more powerful in spreading news and influence individuals. Compared with other traditional media outlets such as newspaper, radio, and television, social networks empower users to spread their ideological message and/or to deliver target advertising very efficiently in terms of both cost and time. In this article, the authors focus on efficiently finding dominating sets in social networks for the classical dominating set problem as well as for two related problems: partial dominating sets and d-hop dominating sets. They will present algorithms for determining efficiently a good approximation for the social network minimum dominating sets for each of the three variants. The authors ran an extensive suite of experiments to test the presented algorithms on several datasets that include real networks made available by the Stanford Network Analysis Project and synthetic networks that follow the power-law and random models that they generated for this work. The performed experiments show that the selection of the algorithm that performs best to determine efficiently the dominating set is dependent of network characteristics and the order of importance between the size of the dominating set and the time required to determine such a set.
Intelligent Log Analysis Using Machine and Deep Learning
Authors: Yen Steven , Moh Melody
Published: January 2021

Computers generate a large volume of logs recording various events of interest. These logs are a rich source of information and can be analyzed to extract various insights about the system. However, due to its overwhelmingly large volume, logs are often mismanaged and not utilized effectively. The goal of this chapter is to help researchers and industrial professionals make more informed decisions about their logging solutions. It first lays the foundation by describing log sources and format. Then it describes all the components involved in logging. The remainder of the chapter provides a survey of different log analysis techniques and their applications, consisting of conventional techniques using rules and event correlators that can detect known issues, plus more advanced techniques such as statistical, machine learning, and deep learning techniques that can also detect unknown issues. The chapter concludes describing the underlying concepts of the techniques, their application to log analysis, and their comparative effectiveness.
Security Visualization Extended Review Issues, Classifications, Validation Methods, Trends, Extensions
Authors: Sönmez Ferda Özdemir , Günel Banu
Published: January 2021

Security visualization has been an issue, and it continues to grow in many directions. In order to give sufficient security visualization designs, information both in many different aspects of visualization techniques and the security problems is required. More beneficial designs depend on decisions that include use cases covering security artifacts and business requirements of the organizations, correct and optimal use of data sources, and selection of proper display types. To be able to see the big picture, the designers should be aware of available data types, possible use cases and different styles of displays. In this chapter, these properties of a large set of earlier security visualization work have been depicted and classified using both textual and graphical ways. This work also contains information related to trending topics of the domain, ways of user interaction, evaluation, and validation techniques that are commonly used for the security visualization designs.
A Resourceful Approach in Security Testing to Protect Electronic Payment System Against Unforeseen Attack
Authors: Behera Rajat Kumar , Sahoo Abhaya Kumar , Jena Ajay
Published: January 2021

This article describes how electronic payments are financial transactions made over the internet for goods or services. In the digital era, the e-commerce industry has gone beyond the traditional in-store service due to the wide spread of internet-based shopping. Developed countries are greatly relying on e-commerce business and a sizable number of countries have shown concern in regard to the online payment cards such as credit cards, debit cards, e-cash, e-cheques, e-wallets and smart card security. The main downsides are concerns over privacy or a malicious attack and hence safeguard mechanisms are required to protect personal information from falling into the hands of intruders. Before commercializing electronic payment systems (EPS), security tests play a significant role in the software development life cycle to check whether the system is secure and it is safe to use. A resourceful approach covering security policies, secure coding, security attack prevention methodology, security testing tool, security testing metrics, security test case prioritization techniques and a model for effective project management methodology are presented in this article. Early detection and resolution of security weaknesses can be achieved with the authors' proposed approach and would certainly reduce the time, effort and cost of a project. The proposed approach is likely the best-fit implementation of the payment industry, covering channels like B2C (Business to Consumer), C2C (Consumer to Consumer), C2B (Consumer to Business), B2B (Business to Business), People to People (P2P), G2C (Government to Citizen) and C2G (Citizen to Government).
A Proposal for Information Systems Security Monitoring Based on Large Datasets
Authors: Van Pham Hai , Moore Philip
Published: January 2021

This article describes how the objective of recent advances in soft computing and machine learning models is the resolution of issues related to security monitoring for information systems. Most current techniques and models face significant limitations, in the monitoring of information systems. To address these limitations, the authors propose a new model designed to detect potential security breaches at an early stage using logging data. The proposed model uses unsupervised training techniques with a rule-based system to analyse data file logs. The proposed approach has been evaluated using a case study based on the learning of data file logs to determine the effectiveness of the proposed approach. Experimental results show that the proposed approach performs well, the results demonstrate that the proposed approach performs better than other conventional security methods in the identification of the correct decisions related to potential security in information systems.
Machine Learning Techniques for Internet of Things
Authors: Priakanth P. , Gopikrishnan S.
Published: January 2021

The idea of an intelligent, independent learning machine has fascinated humans for decades. The philosophy behind machine learning is to automate the creation of analytical models in order to enable algorithms to learn continuously with the help of available data. Since IoT will be among the major sources of new data, data science will make a great contribution to make IoT applications more intelligent. Machine learning can be applied in cases where the desired outcome is known (guided learning) or the data is not known beforehand (unguided learning) or the learning is the result of interaction between a model and the environment (reinforcement learning). This chapter answers the questions: How could machine learning algorithms be applied to IoT smart data? What is the taxonomy of machine learning algorithms that can be adopted in IoT? And what are IoT data characteristics in real-world which requires data analytics?
Overview of Machine Learning Approaches for Wireless Communication
Authors: Ensari Tolga , Günay Melike , Nalçakan Yağız , Yildiz Eyyüp
Published: January 2021

Machine learning is one of the most popular research areas, and it is commonly used in wireless communications and networks. Security and fast communication are among of the key requirements for next generation wireless networks. Machine learning techniques are getting more important day-by-day since the types, amount, and structure of data is continuously changing. Recent developments in smart phones and other devices like drones, wearable devices, machines with sensors need reliable communication within internet of things (IoT) systems. For this purpose, artificial intelligence can increase the security and reliability and manage the data that is generated by the wireless systems. In this chapter, the authors investigate several machine learning techniques for wireless communications including deep learning, which represents a branch of artificial neural networks.
Recent Development in Big Data Analytics
Authors: Kumar M. Sandeep , Prabhu J.
Published: January 2021

This chapter describes how big data consist of an extreme volume of data, velocity, and more complex variable data that demands current technology changes in capturing, storage, distribution, management, analysis data. Business facing more struggles in identifying the pragmatic approach in capturing the data about customer, products, and services. Usage of big data mainly with the analytical method, but it specifically compares with features of an analytical method based on unstructured data contributed around 95% of big data. The analytical approach depends on heterogeneous data and unstructured data's like text, audio, video format. It demands new effective tool for predictive analysis for big data with the unstructured format. This chapter describes explanation of big data and characteristics of big data compress of Volume, Velocity, Variety, Variability, and Value. Recent trends in the development of big data that applies in real time application perspectives like health care agriculture, education etc.
Non-Compliant Mobile Device Usage and Information Systems Security: A Bystander Theory Perspective
Authors: Paravastu Narasimha , Simmers Claire A. , Anandarajan Murugan
Published: January 2021

This study tested the context of employees using their devices for both work and personal use, and non-compliant device usage of a person potentially resulting in Information Systems (IS) security threat to personal as well as work data and/or the devices. Integrating bystander and protection motivation theory (PMT) perspectives this paper studies bystanders' responses to IS security threats and the extent to which a perceived security threat motivates individual intention to act, in the context of non-compliant mobile device usage behaviors. It tests the role of an individual's threat perceptions to protect their own IS security, and as a bystander, protecting their peers or the IS security of their organization. Data collected from 431 individuals support the hypotheses that security awareness predicts perceived severity and protection motivation. Evaluation apprehension and diffusion of responsibility inhibit bystander's intentions to act against non-compliant mobile device usage behaviors, while awareness facilitates it. Theoretical contributions and practical implications of the research are discussed.
Where Do All My Keys Come From?
Authors: Sinnhofer Andreas Daniel , Steger Christian , Kreiner Christian , Oppermann Felix Jonathan , Potzmader Klaus , Orthacker Clemens
Published: January 2021

Nowadays, cyber-physical systems are omnipresent in our daily lives and are increasingly used to process confidential data. While the variety of portable devices we use excessively at home and at work is steadily increasing, their security vulnerabilities are often not noticed by the user. Therefore, portable devices such as wearables are becoming more and more interesting for adversaries. Thus, a robust and secure software design is required for the implementation of cryptographic communication protocols and encryption algorithms. While these topics are well discussed and subject to further research activities, the issue of provisioning the initial device setup is widely uncovered. However, the protection of the initial setup is as important as the protection of the confidential data during the time in use. In this work, the authors will present solutions for a secure initialization of security critical integrated circuits (ICs).
Complex Interdependency of IT Security Risk in B2B Supply Chain
Authors: Bandyopadhyay Tridib
Published: January 2021

Managers often decide to integrate supply chains of collaborating firms. Whether such decisions are for competitive posture, cost saving or operational efficiencies, it is important to understand that supply chains integrate not only the flow of goods but also the information processes and assets and more often than not, the IT networks of the firms. Thus two developments occur. First, IT security losses of one firm collocate at the other firm's servers as information assets like demand forecasts are shared. Second, the Intranets of both firms get connected with the help of VPN or similar technologies, making it possible that a breach can travel from one firm to the other. This in turn makes IT security risks of SC firms strategically interdependent. This chapter analyzes such interdependent IT security risks and provides insights for SC and IT managers who are poised to collaborate with other downstream or upstream partner firms.
Personalization With Digital Technology
Authors: Zheng Robert Z.
Published: January 2021

This chapter focuses on the challenges surrounding personalization and digital technology to promote learners' deep learning. The chapter examines the literature relating to deep cognitive processes and the cognitive functionality of digital technology that support learners' personalized deep cognitive processes in learning. Discussions on instructional design relating to digital technology and personalization were made with suggestions for future research.
Cognitive Deep Learning
Authors: Chowdhary Chiranji Lal , Darwish Ashraf , Hassanien Aboul Ella
Published: January 2021

Deep learning states the scientific algorithms that are accustomed to come through a particular assignment. Such tidy issues could also be meteorology or brain diagnosing wherever records are obtainable as text. In such a state of affairs, cognitive computing can help medical practitioners to diagnose patterns that they might not observe, and they will extend the flexibility to diagnose the brain with efficiency. Deep learning is additionally able to introduce new APIs.
Towards Deep Learning-Based Approach for Detecting Android Malware
Authors: Booz Jarrett , McGiff Josh , Hatcher William G. , Yu Wei , Nguyen James , Lu Chao
Published: January 2021

In this article, the authors implement a deep learning environment and fine-tune parameters to determine the optimal settings for the classification of Android malware from extracted permission data. By determining the optimal settings, the authors demonstrate the potential performance of a deep learning environment for Android malware detection. Specifically, an extensive study is conducted on various hyper-parameters to determine optimal configurations, and then a performance evaluation is carried out on those configurations to compare and maximize detection accuracy in our target networks. The results achieve a detection accuracy of approximately 95%, with an approximate F1 score of 93%. In addition, the evaluation is extended to include other machine learning frameworks, specifically comparing Microsoft Cognitive Toolkit (CNTK) and Theano with TensorFlow. The future needs are discussed in the realm of machine learning for mobile malware detection, including adversarial training, scalability, and the evaluation of additional data and features.
Tracing the Cultural Background of Lone-Wolf Terrorism
Authors: Korstanje Maximiliano Emanuel
Published: January 2021

The end of the Cold War, as well as the collapse of the Soviet Union, posed new greater challenges and risks for the “Global North.” Terrorism—doubtless—seems to be one of them. Over the recent years, and particularly after 9/11, terrorists changed the focus of their attacks. While classic terrorism targeted important persons such as politicians, chief police officers, or celebrities, modern terrorism planned attacks on leisure-spots spaces, tourist destinations, and lay-persons. This is particularly troublesome for policymakers (who are in charge of orchestrating all-pervading models to preserve homeland security) and for field-workers who are seriously punished when they are in contact with radicalized cells. For this reason, specialists traverse for many problems to understand the complexity of terrorism as well as the motivation of young lone-wolves to attack societies where they are native. The present conceptual research focuses not only on the borders of travel literature but also the colonial stereotypes forged during the European expansion to draw and model an “alterity” strictly limited to the ideals of the Enlightenment. In a nutshell, the allegories revolving around the “lone-wolf terrorism” continues the imprint of the “archetype of the noble savage” coined in 18th century.
Architecture Description Languages Taxonomies Review
Authors: Boutekkouk Fateh
Published: January 2021

Self-adaptive distributed embedded systems can automatically adjust their behavior and/or structure at run time to respond to some predictable or unpredictable events. On the other hand, architecture description languages (ADLs) are qualified to be a convenient solution to model systems architecture as a set of components with well-defined interfaces and links. ADLs have been well-studied and applied in many engineering areas beyond the software and hardware engineering. This research work reviews the most relevant ADLs taxonomies and surveys from 2000 till now, selects the most suitable ADLs for self-adaptive embedded systems, and compares between standard and non-standard ADLs based on some key criteria. To do this, a search methodology was followed enabling a systematic review. Results showed that only a few standard ADL have been accepted by the embedded industry favoring domain-specific ADLs with a proved support of adaptivity, real time, energy consumption and security.
Drying Kinetics, Desorption Isotherms and Apparent Diffusivity of Sage Leaves
Authors: Ouahida Bensebia
Published: January 2021

The use of fresh herb is limited in the food and pharmaceutical industry thats why the dry form of the herb is the one commonly used. To save the quality of medicinal and aromatic plants it is very important to provide optimum drying and storage conditions. The aim of this study is to determine and model the drying kinetics of sage leaves. Initially the desorption isotherms are determined for different temperatures (30, 45 and 60°C). The drying experiments were carried out in a convection oven at the same temperature range. For the desorption isotherms and the drying kinetics various models reported in the literature were used and from the statistical view, the Yanniotis and Blahovec and the Fick models fit well the results of desorption isotherms and the oven drying, respectively. The net isosteric heat of desorption of the sage leaves ranged from 6.86 to 63.45 kJ/mol. The total time of oven drying reduced substantially with an increase of the drying temperature. Effective moisture diffusivity values ranged from 1.1x10-12 to 3.7x10-12 m2/s and significantly affected by temperature. An Arrhenius relation with an activation energy value of 66.87 kJ/mol expressed effect of temperature on the diffusivity. Keywords: Desorption isotherms, Drying kinetics, Modelling, Effective diffusivity, Sage leaves
Study of the Structural, Dynamic and Thermodynamic Properties of the III- Antimonides Semiconductors
Authors: Bounab Sabrina , Bentabet Abdelouahb , Bouahadda Youssef
Published: January 2021

In the present contribution, structural, dynamic, and some thermodynamic properties of the III-Antimonides are studied using the density-functional perturbation theory (DFPT) within the local density approximation (LDA) in combination with the harmonic approximation Our results for the structural properties such as the lattice constant and the bulk modulus were found to agree well with the previous theoretical and experimental works. We have also calculated the phonon dispersion relation, and we found that our phonon calculations show that these compounds are dynamically stable in the zinc blende phase moreover our results of the optical and acoustic phonon frequencies at the high symmetry points Γ, X and L are in good agreement with the available theoretical and experimental data. In addition, the thermodynamic properties, including the free energy, internal energy, entropy, and the heat capacity at constant volume were predicted and discussed.
The Calcination Temperature Effect on the Phase Formation of the PZT Ceramic: How the same Calcination Temperature, Result in Different Phase’s Formation
Authors: Mahdi Mohammed , Kadri M.
Published: January 2021

First, the metallic oxides of PbO, TiO2 and ZrO2 were mixed following (2, 1, 1) molar mass respectively. Then 4 samples were separated (S1, S2, S3 and S4). the first one S1 was subjected to calcination treatments at 600, 700 and 800 °C however, the S2 was treated at 700 °C only, the S3 at 800 °C and S4 at 850 °C. The X ray diffraction of the samples reveals important difference in the phases obtained, at 600 °C the quadratic riche phase of PbTiO3 was mainly observed on sample S1, after the treatment at 700 °C and 800°C, the same XRD patterns were obtained with the same peaks positions and the relative intensity. However the S2 revels different pattern from S1 at 700 °C relative to the formation of the Pb(Zr0.75, Ti0.25)O3 Rhombohedral riche phase. The S3 XRD results reveal also different pattern from S1 at 800 °C relative to the formation of Pb (Zr0.58, Ti0.42) O3 near the Morphotropic phase boundary (MPB) and the S4 confirm these finding. Thin films grown from the S1 and S4 used as target in the RF sputtering system, show important difference in the PZT stoichiometry obtained which is relative to Pb (Zr0.44, Ti0.56) located in the quadratic riche phase and Pb (Zr0.52, Ti0.48) O3 near the MPB respectively.
Study of Natural Convection Melting of Phase Change Material inside a Rectangular Cavity with Non-Uniformly Heated Wall
Authors: Laouer Abdelghani , Boulaktout Nesrine , Mezaache El Hacene , Laouar Salah
Published: January 2021

In the present numerical study, the convection diffusion phenomena associated with solid-liquid phase transition processes during phase change material (PCM) melting within a rectangular cavity is studied. The cavity is heated from left wall with a sinusoidal temperature distribution. Initially the enclosure was filled by solid gallium at melting temperature 29.78°C. The enthalpy-based lattice Boltzmann method (LBM) with D2Q9 particle velocity model is used to solve density, velocity and temperature fields. Influence of Rayleigh number ranging from 103 to 4×105 on streamlines, isotherms and liquid fraction is analyzed. The results indicate that natural convection of liquid phase change material (PCM) plays a significant role in the melting heat transfer of PCM. It is found that the rate of the melting increases with the increase in the values of the Rayleigh number.
Microstructural and Mechanical Properties of Welding and Thermal Spraying Coatings on Ductile Cast Iron
Authors: Kellai Ahmed , Kahla Sami , Dehimi Said , Babes Badreddine
Published: January 2021

The subject of this work is to evaluate the influence and adhesion degree of different coating layers deposited on a ductile cast iron substrate by two different methods, thermal spraying and welding with and without use of an interlayer. Microstructures of different zones and interfaces of coated specimens are investigated using optical microscope and scanning electron microscope SEM. Also, the mechanical behavior was evaluated by tensile test. It is found that when stainless steel thermal spraying coating onto the ductile cast iron substrate, the use of the nickel-based interlayer Ni allowed us to mitigate the disadvantages of cracking at the interface. This is due to the mechanical effect of nickel plasticity. In the case of coating by welding, the use of nickel-based buttering ENi-CI allowed us to reduce the diffusion of graphite to stainless steel, resulting in a reduction in the formation of harder alloy carbides. Finally, the mechanicals tests in particular the tensile test shows that the coating by welding is effective but causes a structural hardening; on the other hand the coating realized by thermal spraying does not really present sufficient adhesion.
Mechanical and Tribological Behaviors of Nanocomposite Titanium Nitrides Coatings
Authors: Belgroune Ahlam , Aissani Linda , Salhi Faiza , Nouveau Corinne , Alhussein Akram
Published: January 2021

TiN coatings with a thickness of 2 μm were deposited using the magnetron sputtering has developed rapidly over the last decade in such a way that it has become an established process of choice for the deposition of a wide range in various applications for different domains as it gives excellent performance in many aspects. In view of this, we have deposited the TiN coatings by magnetron sputtering using Ti target at different nitrogen content to study the influence of the nitrogen content on the mechanical properties and tribological behaviors of the TiN coatings were systematically investigated using nanoindentation and a pin-on-disk tribometer. Nanoindentation results shows that the hardness and Young's modulus of the TiN coatings increase with increasing N content in the coatings.Wear test results indicate that the wear rate and friction coefficient of the XC100 steel substrate were significantly reduced by deposition of the TiN coatings, and the tribological behaviors of the TiN coatings are strongly dependent on the nitrogen content in the coatings.
Experimental Study of Tool Wear Evolution during Turning Operation Based on DWT and RMS
Authors: Zaida Hamid , Bouchelaghem Abdelaziz Mahmoud , Chehaidia Seif Eddine
Published: January 2021

In cutting process, the wear of the tool remains posed, it describes their progressive failure in regular operation. The tool wear phenomena is mainly caused by abrasion of hard particles, shearing of micro welds between tool and work-material and the exchange of particles between the tool and work material leading to a several forms of tool wear, however, we focused in this study on the frontal wear, also called wear on clearance surface or flank wear. For efficient use of cutting tool according to the technical requirement, the comprehension and the knowledge of the cutting tool wear evolution is necessary. In order to meet this indispensable need, the present paper proposes a two-step tool flank wear monitoring technique based on vibratory signals analysis during the turning operation using a P30 grade metal carbide tool and C45 (XC48) steel. Firstly, discrete wavelet transforms (DWT), has been used to decompose the signal and extract the information, then the scalar indicator Root Mean Square (RMS) value has been used to evaluate the cutting tool stability level. The proposed method offers the possibility to accurately predict break-in tool wear phase, accelerated tool wear phase and the stability period, in which a high quality machining process is guaranteed.
Heat Treatment Effect on the Microstructural, Hardness and Tribological Behavior of A105 Medium Carbon Steel
Authors: Gharbi Amel , Bouhamla Khedidja , Ghelloudj Oualid , Ramoul Chems Eddine , Berdjane Djamel , Chettouh Samia , Remili Saleh
Published: January 2021

The present work is a contribution in investigating the effect of heat treatment on microstructure, hardness and friction wear of A105N steel. Samples of 25x25 mm2 cross-section and 15mm thickness have been prepared from the as-received material and then heat-treated. The samples were austenitized at 1050°C for 60 minutes followed by water quenching, then tempered at 500 and 700°C for 120 minutes. Microstructural changes and their effect on the wear resistance and hardness were investigated according to the applied heat treatments. The main results show that after quenching the structure is mostly composed of quenched martensite, which confers high hardness and friction resistance to the steel. While the tempered structure is composed of tempered martensite and ferrite. As the temperature rises to 700°C, the tempered martensite decreases and is fully transformed to ferrite and cementite. A good wear resistance expressed by a low friction coefficient and a low wear rate is achieved by tempering at 500°C.
Study of Chemical and Physical Characterization of the Natural Dolomite of Ain Mlila-Algeria
Authors: Abdellaoui K. , Boumaza A. , Kamoun N.
Published: January 2021

Dolomite is one of the commonest minerals that abound in the formation of a number of geological conditions. And it is found in abundance in eastern Algeria, especially Ain Mlila-Wilaya of Oum El Bouaghi-Algeria. The analyzed sample of raw dolomite has been by various physical-chemical techniques. The constituents of these carbonates are Ca, Mg, C, O, Al, Si, Fe, Ba, F, and Sr, analysis by XRD, and Raman, show that in addition to CaMg(CO3)2, we may have calcium carbonate. The Photoluminescence analysis characterizes the intrinsic and extrinsic defects of this carbonate. Differential thermal analysis reveals the different transformations of this mineral during heating. Indeed several stages including the elimination of water, the departure of CO2, the formation of MgO, and finally the formation of CaO.
Conjugate Heat and Mass Transfer on Steady MHD Mixed Convection Flow along a Vertical Slender Hollow Cylinder with Heat Generation and Chemical Reaction Effects
Authors: Saidoune F. , Bouaziz M.N. , Aziz A.
Published: January 2021

This paper studies the effects of heat generation and chemical reaction on the coupled conjugate heat and mass transfer by MHD laminar mixed convective flow along a vertical slender hollow cylinder. The governing boundary layer equations along with the boundary conditions are first cast into a dimensionless form by a non similar transformation and the resulting equations are then solved by the finite difference method using Matlab@ following the code bvp4c. Numerical results of the velocity, temperature and concentration for different values of the conjugate heat transfer parameter p, the magnetic parameter M, the heat generation Q, and the chemical reaction K are studied. The local skin friction, Nusselt number and Sherwood number are also analyzed and presented graphically. In the numerical ranges of the main parameters, it is found mainly that working with strong conjugate heat transfer or/and all others parameters affects negatively the Nusselt and Sherwood numbers. The same trend is revealed for the skin friction factor.
Influence of Reactive Oxygen Gas on Sputtered-Vanadium Oxide Films under Post-Annealing in Vacuum
Authors: Khlayboonme S.Tipawan , Warawoot Thowladda
Published: January 2021

Vanadium oxide thin films were deposited on glass substrates by O2 reactive-RF magnetron sputtering from a vanadium (V) target without substrate-heating. The percentages of O2 gas were 10%, 7.5%, 6.0%, 5.0% and 2.5%. The total gas flow rate (O2/Ar) was kept at 25 sccm. As-deposited films were experienced post-annealing process at different temperatures and times. The crystallinity and chemical bonding states of films were examined by X-ray diffraction and Raman spectroscopy. The condition in annealing to active crystallinity depended on an earlier composition of the films. As O2-gas percentages were 10% and 7.5%, after annealing, the as-deposited VxOy films were transformed into crystalline V2O5 films. With decreasing in O2 percentage to 5.0% and 2.5%, the films were transformed into V2O3 and VO films, respectively. The films deposited with 6.0% O2 were crystallized to VO2 with phase B after annealing with 500 °C 15 h. By applying a longer time to 30 h at the high temperature 500 °C in annealing, VO2 films revealed only phase M formation.
The Method of Creating and Measuring the Printability of Fine-Grained Concrete
Authors: Lesovik Valery S. , Glagolev Evgeny S. , Elistratkin Michail Yu. , Pospelova Marina A. , Alfimova Natalia I.
Published: January 2021

One of the factors hindering the normal development of additive construction technologies is the lack of reasonable methods for evaluating the suitability of mixtures for printing. This makes it almost impossible to compare remotely the compositions of different developers, makes it difficult to develop equipment and regulatory documentation, without which it is impossible to complete industrial production. The paper considers the feasibility of introducing the concept of “printability” of compositions and “rheological technological index of mixtures” as a numerical indicator for its evaluation. The design of the device for determining the rheological technological index is described. The developed device has a low cost of production, is linked to standard equipment of construction laboratories and emulates the main types of effects on the mixture during the extrusion process. The effective method for ensuring the printability of fine-grained concretes is considered based on the joint use of traditional plasticizing additives with entrained agents – foaming agents for cellular concretes. The effect of these additives is realized at different scale levels (micro-and mesolevels (cement paste) – traditional superplasticizers; macro-level (fine aggregate) - entrained agents), which together provides high rheological technological indices and effectiveness of mixtures with increased amounts of sand, low W/C ratios and small dosages of these additives. The use of additional mineral or organic rheology modifiers that increase the cost of the mixture is not required in this case. The structural features and basic properties of the developed composites are studied, allowing making comparisons with the solutions of other developers, assessing the prospects of the proposed method of ensuring printability, and outlining directions for its further improvement.
Influence of Preliminary Heat Treatment and Ball Milling of Aluminum Powder on Cold Spray Process
Authors: Klinkov S.V. , Kosarev V.F. , Chesnokov A.E. , Smirnov A.V. , Shikalov V.S.
Published: January 2021

This paper presents the results of a study of the effect of preliminary heat treatment and ball milling of aluminum powder on the cold spraying process and the properties of the obtained coatings (porosity and microhardness). The ball milling of aluminum powder leads to an increase in specific surface area, a decrease in apparent density and a decrease in the value of the crystallite size, which indicates a decrease in grain size. It is shown that coatings deposited from ball milled powders have slightly higher coatings hardness averagely. The profilometry of aluminum coatings obtained under the same conditions from the initial and processed powders did not reveal significant changes in the form of coatings and their typical dimensions (width, thickness), which indicates the absence of significant changes in the deposition coefficient of the initial and processed aluminum powders. Ball milled powders on average correspond to slightly higher hardnesses of coatings.
Structure and Grain Boundaries of Ultrafine-Grained Nickel after Rolling and Forging at Cryogenic Temperature
Authors: Naydenkin Evgeny V. , Mishin Ivan P.
Published: January 2021

The structure and misorientations of grain boundaries of ultrafine-grained nickel subjected to rolling and forging at liquid nitrogen temperature are studied. It is shown that as a result of rolling in UFG nickel obtained by the ECAP the forming of a band fragmented structure with the formation of special twin boundaries Σ3 is observed. An increase in the strain rate (forging) leads to the appearance of localized deformation bands in which the formation of new small grains is observed through dynamic recrystallization. The development of recrystallization results in increase up to 7% in UFG nickel the fraction of special twin boundaries Σ3 which are similar in nature to annealing twins.
Inductor for Uniform Bulk Heat Treatment of Welded Butt Joints of Railway Rails
Authors: Prokof’iev O. , Gubatyuk R. , Rymar S. , Sydorets V. , Kostin Valery
Published: January 2021

To improve the structure of metal in welded butt joints of railway rails produced by flash-butt welding and increase the reliability of butt joints, it is advisable to carry out their induction heat treatment using high-frequency currents. Solving the problem of a uniform bulk heating of weld metal of railway rails in a narrow area during its heat treatment remains an urgent task. The work describes the principle of designing an inductor without magnetic cores for carrying out a uniform bulk heat treatment of welded butt joints of railway rails for realization of favorable phase transformations of metal and normalization of its structure. The principle is based on the physical laws of propagation of electromagnetic fields and electric currents in the inductor and a rail. Based on the carried out investigations, an inductor was designed that has a variable shape along the perimeter of a rail and a variable distance from it, as well as a partial splitting of the inductor busbar for current parallelization, which provides a uniform bulk heating of a rail butt joint. Splitting of the inductor busbar allowed adjusting the propagation of currents in the inductor and a rail in such a way as to avoid overheating of a rail in its particular areas without a significant increase in the distance between the inductor and a rail, and respectively without a significant increase in the reactive power of the “inductor-product” system. The carried out experiments on heating the welded butt joint of a rail by the designed inductor showed the indices of uniformity and rate of its bulk heating, which are acceptable for heat treatment of rails both on the surface as well as in the depth of a rail in a narrow heating zone with providing the required temperature levels.
Research of Technology for Repair of Heat Exchangers of Nuclear Power Plants by Laser Welding
Authors: Bernatskyi A. , Sydorets V. , Berdnikova Olena M. , Krivtsun I. , Kushnarova Olha
Published: January 2021

Extending the lifetime of energy facilities is extremely important today. This is especially true of nuclear power plants, the closure (or modernization) of which poses enormous financial and environmental problems. High-quality repair of reactors can significantly extend their service life. One of the critical parts is heat exchangers, the tubes of which quite often fail. Sealing, as a type of repair of heat exchanger tubes by the plugs, is promising provided that the joint quality is high. Practical experience in the use of welding to solve this problem has shown the need to search technological solutions associated with increasing the depth of penetration and reducing the area of thermal effect. The aim of the work was to develop a highly efficient technology for repair and extension of service life of heat exchangers of nuclear power plants based on the results of studying the technological features of laser welding of joints of dissimilar austenitic steels AISI 321 and AISI 316Ti in the vertical spatial position. Based on the results of the analysis of mechanical test data, visual and radiographic control, impermeability tests and metallographic studies of welded joints, the appropriate modes of laser welding of plugs have been determined. The principal causes of defects during laser welding of annular welded joints of dissimilar stainless steels are determined and techniques for their elimination and prevention of their formation are proposed. Based on the results of the research, technological recommendations for laser welding of plugs in the heat exchange tube of the collector are formulated, which significantly improves the technology of repair of steam generators of nuclear power plants and extends the service life of reactors.
Interstitial pneumonitis with autoimmune features: 2 case reports and review of literature
Authors: Laria Antonella , Lurati Alfredomaria , Mazzocchi Daniela , Marrazza Mariagrazia , Re Katia Angela , Faggioli Paola Maria , Mazzone Antonino
Published: January 2021

The classification of interstitial pneumonia with autoimmune features (IPAF) is used to categorize patients with an autoimmune substrate and pulmonary interstitial involvement, who do not meet the classification criteria for any specific connective tissue disease. These patients seem to have a better clinical course than patients with IPAF. The diagnosis of IPAF is of paramount importance and a window of opportunity to identify and to treat forms of early onset of pulmonary interstitial disease without any established damage and to recognize incomplete forms of connective diseases preventing complete clinical manifestation.
Spatial distribution and sociodemographic risk factors of malaria in Nigerian children less than 5 years old
Authors: Ugwu Chigozie Louisa J. , Zewotir Temesgen
Published: January 2021

Malaria remains a leading cause of morbidity and mortality among children in Nigeria less than 5 years old (under-5). This study utilized nationally representative secondary data extracted from the 2015 Nigeria Malaria Indicator Survey (NMIS) to investigate the spatial variability in malaria distribution in those under- 5 and to explore the influence of socioeconomic and demographic factors on malaria prevalence in this population group. To account for spatial correlation, a Spatially Generalized Linear Mixed Model (SGMM) was employed and predictive risk maps was developed using Kriging. Highly significant spatial variability in under-5 malaria distribution was observed (P<0.0001) with a higher likelihood of malaria prevalence in this group in the Northwest and North-east of the country. The number of malaria infections increased with age, children aged between 49-59 months were found to be at a higher risk (Odds Ratio=4.680, 95% CI=3.674 to 5.961 at P<0.0001). After accounting for spatial correlation, we observed a strong significant association between the non-availability or non-use of mosquito bed-nets, low household socioeconomic status, low level of mother’s educational attainment, family size, anaemia prevalence, rural type of residence and under-5 malaria prevalence. Faced with a high rate of under-5 mortality due to malaria in Nigeria, targeted interventions (which requires the identification of the child’s location) may reduce malaria prevalence, and we conclude that socioeconomic impediments need to be confronted to reduce the burden of childhood malaria infection.
The diagnostic and predictive accuracy of thyroglobulin to TSH ratio and TSH to thyroglobulin ratio in detecting differentiated thyroid carcinoma in normothyroid patients with thyroid nodules: A retrospective cohort study and systematic review of the literature
Authors: Karvounis Evangelos , Kappas Ioannis , Angelousi Anna , Makris George-Marios , Siamatras Thomas D. , Kassi Eva
Published: January 2021

The purpose of the present study is to examine the diagnostic and predictive accuracy of the thyroglobulin (Tg) to thyroid stimulating hormone (TSH) and TSH/Tg ratios in normothyroid patients with differentiated thyroid cancer (DTC). We conducted a retrospective cohort study evaluating the diagnostic accuracy of the serum Tg/TSH and TSH/Tg ratios in normothyroid patients with thyroid nodules. We also systematically searched the international literature using the Medline, Cochrane’s CENTRAL, Scopus, Clinicaltrials.gov, EMBASE, and Google Scholar databases for evidence concerning the diagnostic and predictive accuracy of these ratios. Overall, 374 patients were identified in our cohort study of whom 240 were treated for benign disease and 134 were treated for DTC. Significant differences were noted in the Tg/TSH and TSH/Tg values among cases with malignant and benign disease (P=0.020). However, the diagnostic ROC curve did not confirm these results (Tg/TSH=0.572 and TSH/Tg=0.428). After searching the international literature, we identified 8 studies. The majority of the included data reported significant differences among patients with benign/malignant disease and those with successful iodine therapy compared to those with disease relapse. However, the clinical relevance was clearer among studies that investigated the usefulness of these ratios in predicting recurrent disease. The findings of our study support that the Tg/TSH ratio increases in patients with DTC and can, thus, become useful in the future as a predictive marker of ablative 131I therapy success. However, given the significant variability of Tg its diagnostic accuracy remains to date minimal; thus, the actual cut-off value that can be used to discriminate cancer cases from benign disease has not been determined yet.
9-Hydroxy-6,7-dimethoxydalbergiquinol suppresses hydrogen peroxide-induced senescence in human dermal fibroblasts through induction of sirtuin-1 expression
Authors: Lim Seok-Hee , Li Bing Si , Zhu Ri Zhe , Choi Byung-Min
Published: January 2021

Objective:

To investigate the potential anti-aging mechanism of 9-hydroxy-6,7-dimethoxydalbergiquinol (HDDQ) on hydrogen peroxide (H2O2)-induced oxidative stress in human dermal fibroblasts (HDFs).

Methods:

The effect of HDDQ on cell viability was assessed by MTT assay, and the effects of HDDQ on senescence-like phenotypes were determined by senescence-associated β-galactosidase (SA-β-gal) staining, Western blotting analysis, and a cell proliferation assay. The expression level and activity of sirtuin-1 (SIRT1) induced by HDDQ were also measured.

Results:

HDDQ reversed senescence-like phenotypes in the oxidant-challenged model, through reducing SA-β-gal activity and promoting cell growth. Meanwhile, decreases in ac-p53, p21
Cip1/WAF1
, and p16
Ink4a
and an increase in pRb were observed. HDDQ induced the expression of SIRT1 in a concentration- and time-dependent manner. Moreover, HDDQ inhibited H2O2-induced phosphorylation of Akt by SIRT1 up-regulation and reduced SA-β-gal staining.

Conclusions:

HDDQ inhibits H2O2-induced premature senescence and upregulation of SIRT1 expression plays a vital role in the inhibition of the senescence phenotype in HDFs.