bluuebunny/crossref_metadata_2025 huggingface dataset:
A Survey on Denial of Service Attacks and Preclusions
Authors: Nagesh K.  , Sumathy R.  , Devakumar P.  , Sathiyamurthy K.
Published: September 2020

Security is concerned with protecting assets. The aspects of security can be applied to any situation- defense, detection and deterrence. Network security plays important role of protecting information, hardware and software on a computer network. Denial of service (DOS) attacks causes great impacts on the internet world. These attacks attempt to disrupt legitimate user's access to services. By exploiting computer's vulnerabilities, attackers easily consume victim's resources. Many special techniques have been developed to protest against DOS attacks. Some organizations constitute several defense mechanism tools to tackle the security problems. This paper has proposed various types of attacks and solutions associated with each layers of OSI model. These attacks and solutions have different impacts on the different environment. Thus the rapid growth of new technologies may constitute still worse impacts of attacks in the future.
DDoS Attacks and Defense Mechanisms Using Machine Learning Techniques for SDN
Authors: Swami Rochak , Dave Mayank , Ranga Virender
Published: September 2020

Distributed denial of service (DDoS) attack is one of the most disastrous attacks that compromises the resources and services of the server. DDoS attack makes the services unavailable for its legitimate users by flooding the network with illegitimate traffic. Most commonly, it targets the bandwidth and resources of the server. This chapter discusses various types of DDoS attacks with their behavior. It describes the state-of-the-art of DDoS attacks. An emerging technology named “Software-defined networking” (SDN) has been developed for new generation networks. It has become a trending way of networking. Due to the centralized networking technology, SDN suffers from DDoS attacks. SDN controller manages the functionality of the complete network. Therefore, it is the most vulnerable target of the attackers to be attacked. This work illustrates how DDoS attacks affect the whole working of SDN. The objective of this chapter is also to provide a better understanding of DDoS attacks and how machine learning approaches may be used for detecting DDoS attacks.
Security in IoT Devices
Authors: JEYANTHI N. , Banthia Shreyansh , Sharma Akhil
Published: September 2020

An attempt to do a comparison between the various DDoS attack types that exist by analysing them in various categories that can be formed, to provide a more comprehensive view of the problem that DDoS poses to the internet infrastructure today. Then DDoS and its relevance with respect to IoT (Internet of Things) devices are analysed where attack types have been explained and possible solutions available are analysed. This chapter does not propose any new solutions to mitigating the effects of DDoS attacks but just provides a general survey of the prevailing attack types along with analysis of the underlying structures that make these attacks possible, which would help researchers in understanding the DDoS problem better.
Malware Threat in Internet of Things and Its Mitigation Analysis
Authors: Yamaguchi Shingo , Gupta Brij
Published: September 2020

This chapter introduces malware's threat in the internet of things (IoT) and then analyzes the mitigation methods against the threat. In September 2016, Brian Krebs' web site “Krebs on Security” came under a massive distributed denial of service (DDoS) attack. It reached twice the size of the largest attack in history. This attack was caused by a new type of malware called Mirai. Mirai primarily targets IoT devices such as security cameras and wireless routers. IoT devices have some properties which make them malware attack's targets such as large volume, pervasiveness, and high vulnerability. As a result, a DDoS attack launched by infected IoT devices tends to become massive and disruptive. Thus, the threat of Mirai is an extremely important issue. Mirai has been attracting a great deal of attention since its birth. This resulted in a lot of information related to IoT malware. Most of them came from not academia but industry represented by antivirus software makers. This chapter summarizes such information.
Zero-Crossing Analysis of Lévy Walks and a DDoS Dataset for Real-Time Feature Extraction
Authors: Gonzalez Jesus David Terrazas , Kinsner Witold
Published: September 2020

A comparison between the probability similarities of a Distributed Denial-of-Service (DDoS) dataset and Lévy walks is presented. This effort validates Lévy walks as a model resembling DDoS probability features. In addition, a method, based on the Smirnov transform, for generating synthetic data with the statistical properties of Lévy-walks is demonstrated. The Smirnov transform is used to address a cybersecurity problem associated with the Internet-of-things (IoT). The synthetic Lévy-walk is merged with sections of distinct signals (uniform noise, Gaussian noise, and an ordinary sinusoid). Zero-crossing rate (ZCR) within a varying-size window is utilized to analyze both the composite signal and the DDoS dataset. ZCR identifies all the distinct sections in the composite signal and successfully detects the occurrence of the cyberattack. The ZCR value increases as the signal under analysis becomes more complex and produces steadier values as the varying window size increases. The ZCR computation directly in the time-domain is its most notorious advantage for real-time implementations.
The Improved LSTM and CNN Models for DDoS Attacks Prediction in Social Media
Authors: Alguliyev Rasim M. , Aliguliyev Ramiz M. , Abdullayeva Fargana J
Published: September 2020

Automatic identification of conversations related to DDoS events in social networking logs helps the organizations act proactively through early detection of negative and positive sentiments in cyberspace. In this article, the authors describe the novel application of a deep learning method to the automatic identification of negative and positive sentiments in large volumes of social networking texts. The authors present classifiers based on Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) to address this problem domain. The improved CNN and LSTM architecture outperform the classification techniques that are common in this domain including classic CNN and classic LSTM in terms of classification performance, which is measured by recall, precision, f-measure, train loss, train accuracy, test loss, and test accuracy. In order to predict the occurrence probability of the DDoS events the next day, the negative and positive sentiments in social networking texts are used. To verify the efficacy of the proposed method experiments is conducted on Twitter data.
An Overview of Recent Development in Privacy Regulations and Future Research Opportunities
Authors: Wang Tawei , Wang Yen-Yao
Published: September 2020

This chapter provides an overview of several recently proposed or passed privacy-related regulations, including General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), Illinois Video Interview Act, Data Broker Regulations in Vermont, and Privacy Bill of Rights Act, and related but very limited studies. Toward the end, several research opportunities are discussed. These research opportunities include (1) economic consequences of these new regulations and (2) the new research framework to capture novel features of these regulations to explain security compliance. The authors further discuss possible research designs to address the proposed research opportunities. This chapter provides both professionals and researchers additional insights on the regulation of privacy issues.
Challenges to Multimedia Privacy and Security Over Social Media
Authors: Chavan Pallavi , Jadhav Dipti , Borkar Gautam M.
Published: September 2020

With the rise in usage of social media, large quantities of data like pictures, videos, audio, and computer graphics are created. As the data is shared over the network, security and privacy become important concerns. Social networks are most popular and have become a medium for instant information sharing. Facebook, Instagram, WhatsApp are the most popular social networks. There has been extreme increase in the usage of audiovisual data over the social network. When multimedia data are stored in a networked environment, billions of users get connected to it for different purposes. The privacy challenges are personification, harassment, password sharing, location-oriented services, and privacy vs. marketing. The other challenges are data semantics, content management rights, and false information. There has been significant contribution by the researchers in development of security systems against these threats; still, the problems of clickjacking, short URL, phishing remain unresolved for some network architectures.
Computer Forensics and Cyber Attacks
Authors: Perilli Michele , De Bonis Michelangelo , Gallo Crescenzio
Published: September 2020

During investigative activities in the field of contrasting tax evasion and fraud, it is known that law enforcement agencies are increasingly encountering digital documents, which are slowly replacing the paper ones. The chapter has the purpose to explain as data, extracted from an electronic device, turns into evidence in court. The authors describe how hidden data (metadata) can become forensic evidence. In particular, the chapter examines the metadata contained in digital photos, which conceal a mass of data whose existence is not normally suspected. The second part of the chapter consists of miscellaneous cyber-attack descriptions in which computer forensics can be applied. It is finally described how one can protect systems against a cyber-attacks.
Forensic Readiness for Enhanced eDiscovery
Authors: Sule Dauda
Published: September 2020

To discover, uncover, and stamp out digital crime while ensuring information security and assurance, there is a need to investigate the crime once it has occurred. This will help trace the criminals and also secure an organization against future attacks. Forensic readiness entails organizations being at alert as per digital evidence collection and storage – that is collecting and storing such evidence constantly in a forensically sound manner, not just when the need for such evidence arises. In the event litigation arises or is anticipated, digital evidence may need to be reviewed by the opposing parties prior to court proceedings to assess quality of the evidence; this is eDiscovery. Digital evidence for eDiscovery needs to be forensically sound and provided in an efficient timely manner – forensic readiness helps to ensure this. This chapter is an update on the chapter on “Forensic Readiness and eDiscovery” in the previous edition and still seeks to establish how forensic readiness is relevant to the eDiscovery process, taking into consideration current developments in the field.
Mobile Device Forensics Investigation Process
Authors: Bernardo Bruno , Santos Vitor
Published: September 2020

One of the main topics that is discussed today is how can a person leverage technology in a positive and secure way in order to enhance their lives. However, with improvements in technology comes challenges; the concern that people have over their privacy and the safeguard of sensitive information being the greatest. In fact, one of the most used technologies is the mobile, which can take different forms, features, and shapes and create, store, delete, and transfer various types of data that can be evidence for the forensics fields. As such, this chapter proposes a different approach to this field by conglomerating and researching for all the information available and aiming at building a comprehensive systematic literature review on the topics of forensics, digital and mobile device forensics using the PRISMA methodology, with the intent of supporting and enhancing the mobile device forensics investigation process and allowing for a more robust and up-to-date knowledge base by breaking through the techniques available.
Fuzzy Rule-Based Layered Classifier and Entropy-Based Feature Selection for Intrusion Detection System
Authors: Sellappan Devaraju , Srinivasan Ramakrishnan
Published: September 2020

Intrusion detection systems must detect the vulnerability consistently in a network and also perform efficiently with the huge amount of traffic. Intrusion detection systems must be capable of detecting emerging and proactive threats in the networks. Various classifiers are used to classify the threats as normal or intrusive by supervising the system activity. In this chapter, layered fuzzy rule-based classifier is proposed to detect the various intrusions, and fuzzy entropy-based feature selection is proposed to identify the relevant features. Layered fuzzy rule-based classifier is proposed to improve the performance of the intrusion detection system. KDD dataset contains various attacks; these attacks are grouped into four classes, namely Denial-of-Service (DoS), Probe, Remote-to-Local (R2L), and User-to-Root (U2R). Real-time dataset is also considered in this research. Experimental result shows that the proposed method provides good detection rate, minimizes the false positive rate, and less computational time.
Learning With Differential Privacy
Authors: Sengupta Poushali , Paul Sudipta , Mishra Subhankar
Published: September 2020

The leakage of data might have an extreme effect on the personal level if it contains sensitive information. Common prevention methods like encryption-decryption, endpoint protection, intrusion detection systems are prone to leakage. Differential privacy comes to the rescue with a proper promise of protection against leakage, as it uses a randomized response technique at the time of collection of the data which promises strong privacy with better utility. Differential privacy allows one to access the forest of data by describing their pattern of groups without disclosing any individual trees. The current adaption of differential privacy by leading tech companies and academia encourages authors to explore the topic in detail. The different aspects of differential privacy, its application in privacy protection and leakage of information, a comparative discussion on the current research approaches in this field, its utility in the real world as well as the trade-offs will be discussed.
Limitation of COTS Antiviruses
Authors: Lima Sidney
Published: September 2020

Malware (amalgam between the words malicious and software) aims to access a device without the permission of its owner. Undoubtedly, antiviruses are the most popular mechanism in relation for information security. They are present on 95% of personal computers and are associated with combating malicious applications. Technically, the modus operandi of the COTS antiviruses is for the most part the identification of the executable malicious in their datasets nominated blacklist. The major problem with the strategy, adopted by COTS antiviruses, is that in order to detect a new malware, some machines must have already been infected. In order to demonstrate the inefficiency of COTS antiviruses, the authors evaluate the accuracy of conventional antiviruses. On average, the 86 main worldwide antiviruses were able to detect 54.84%, 34.95%, 42.17%, and 16.82% of Portable Executable (PE), Java, JavaScript, and PHP malwares, respectively. Thus, traditional antiviruses have severe limitations when dealing with cyber-pandemic caused by malware.
Preserving Information Security Using Fractal-Based Cryptosystem
Authors: Agarwal Shafali
Published: September 2020

The chapter intends to propose a hybrid cryptosystem based on a chaotic map and a fractal function. The sequential order of process execution provides a computationally less expensive and simple approach that still designed a secure cryptosystem. A one-dimensional Ricker map and its modified form are employed to initially shuffle the image pixels twice, and also a pseudo-random sequence is generated using both maps. The algorithm implemented a sequence of pixel confusion-diffusion steps using the image rotation and a transcendental anti-Mandelbrot fractal function (TAMFF) and its Mann-iterated fractal function (Sup-TAMFF). Finally, the pixel value of an image obtained in the last step and the recent two pixels of the encrypted image is XORed with the corresponding pseudo-random matrix value to get the cipher image. Subsequently, various performance tests are conducted to verify the suitability of the given method to be used in real-world information transmission.
User Authentication Into Electronic Health Record Based on Reliable Lightweight Algorithms
Authors: Al-Zubaidie Mishall , Zhang Zhongwei , Zhang Ji
Published: September 2020

Supporting a mechanism to authenticate members in electronic health record (EHR) is a fundamental procedure to prevent different threats from penetrating patients' identities/data. Existing authentication schemes still suffer from security drawbacks. Exchanging medical-related information/data between clients and the servers leaves them compromised to breakthrough by intruders as they can transmit over an unreliable environment. To guarantee the protection of patient records, this chapter proposes a new scheme that provides authentication of patients/providers in EHR depending on the legitimate member identities and the device information. The scheme utilizes an elliptic curve cryptography and lightweight hash function to accomplish robust security with satisfying performance. Moreover, it depends on a set of techniques such as multi-pseudonyms to authenticate legitimate members. Additionally, concentrated theoretical and experimental analysis proves that the proposed provides elevated performance and security compared to existing research.
Contribution to the Maximum Coverage Detection in a Heterogeneous Network
Authors: Chebi Hocine , Benaissa Abdelkader , Sayah Rafik
Published: September 2020

This article has addressed the problem of area coverage in surveillance camera networks using a minimum number of active sensors. The dense and random deployment of cameras creates many problems, among which the same portion of the area of interest is cited and monitored by several sensors. This redundancy of information generates unnecessary energy consumption, which increases the cost of installation. This work contributed to the extension of a surveillance algorithm, and the authors presented in this work a distributed algorithm of perimeter surveillance and made this contribution allowing the maintenance of total coverage in heterogeneous camera networks. The proposed solution is based on the search for minimum sets that completely cover a surface by scheduling the activity of the sensors. The proposed approach consists of calculating the distance between the center and the furthest point not covered and subtracting a fixed step from it; the coverage of these circles is done in the same way as the coverage of the first perimeter. The results of the simulations show that this approach ensures maximum coverage with a minimum number of cameras.
The Avatar as a Self-Representation Model for Expressive and Intelligent Driven Visualizations in Immersive Virtual Worlds
Authors: Demirdjian Colina , Demirdjian Hripsime
Published: September 2020

One could argue that the “self” as a human entity will be affected by the desire for more intelligence-driven products and creations. The avatar acts as an agent that unlocks the pathway to a better version of the human self. The true power of the avatar is beyond the comprehension of those that see it as a replica or a clone of a human. Rather, for those that look through the lens of the future, the avatar has the power(s) that mankind ultimately desires in their fulfilment of selfhood. To this end, the perception of the avatar needs to be reconsidered in order to appropriately recognise the avatar's multi-dimensional advantages and opportunities it holds for society and how it enhances the human condition. This paper creates a backdrop for understanding the avatar in the connected modalities of the real and virtual state of environments. This paper will also attempt to tackle the connected conditions that emerge as avatar-to-avatar interaction happens through the works of current research to understand the avatar more in-depth.
Microservice-Oriented Architecture in Distributed Artificial Intelligence Systems and the Language of AI in Bio-Neural Systems
Authors: Galiautdinov Rinat
Published: September 2020

This article describes the views on the architecture of distributed AI systems based on the simulated bio-neurons representing the basis for the bio-neural circuits, which represent distributed AI subsystems and serve as microservices for the AI client-side systems. The article also describes the interface and the demands to the protocol of communication with the distributed subsystems of the AI, the ways of tuning the synaptic contacts in the brand new neural circuits, which represent the distributed AI systems, and finally, the new approach to communication with such the systems based on the new computer language, which will be used in construction and tuning of such the AI systems.
Adaptive Parameter Estimation of IIR System-Based WSN Using Multihop Diffusion in Distributed Approach
Authors: Dash Meera , Panigrahi Trilochan , Sharma Renu , Mohanty Mihir Narayan
Published: September 2020

Distributed estimation of parameters in wireless sensor networks is taken into consideration to reduce the communication overhead of the network which makes the sensor system energy efficient. Most of the distributed approaches in literature, the sensor system is modeled with finite impulse response as it is inherently stable. Whereas in real time applications of WSN like target tracking, fast rerouting requires, infinite impulse response system (IIR) is used to model and that has been chosen in this work. It is assumed that every sensor node is equipped with IIR adaptive system. The diffusion least mean square (DLMS) algorithm is used to estimate the parameters of the IIR system where each node in the network cooperates themselves. In a sparse WSN, the performance of a DLMS algorithm reduces as the degree of the node decreases. In order to increase the estimation accuracy with a smaller number of iterations, the sensor node needs to share their information with more neighbors. This is feasible by communicating each node with multi-hop nodes instead of one-hop only. Therefore the parameters of an IIR system is estimated in distributed sparse sensor network using multihop diffusion LMS algorithm. The simulation results exhibit superior performance of the multihop diffusion LMS over non-cooperative and conventional diffusion algorithms.
Classification of Eyes Based on Fuzzy Logic
Authors: Fakir Mohamed , Hicham Hatimi , Chabi Mohamed , Sarfraz Muhammad
Published: September 2020

The systems of eye classification in an image are indispensable in several domains. To better find the class of membership of the eye in a minimal time, the classic methods of detection are inadequate. Fuzzy logic is considered to be an effective technique for solving an eye classification problem. This article proposes a fuzzy approach for eye classification. The tasks of classification are realized in two steps. In the first step, the characteristic points of the image are extracted in order to locate the eye. These characteristic points allow generating a representative model of the eye. In the second step, the detected eyes have to pass by a fuzzy controller containing several parts: Fuzzification, inference rules, and defuzzification. Finally, the system gives the degree of membership of the detected eyes to each class in the database.
Principles for Enhancing Earth System Governance and Sustainable Development Through Informality
Authors: Chirambo Dumisani
Published: September 2020

Even though the United Nations Framework Convention on Climate Change introduced the Nationally Determined Contributions (NDCs) framework as a novel mechanism for improving climate change governance and promoting sustainable development, some studies show that NDCs are still far from achieving the 2°C target. Non-state actors from the informal economy can potentially improve the implementation of the NDCs framework and Sustainable Development Goals framework as much of the urban population growth occurring in developing nations is taking place in slums/informal settlements. This paper is therefore an inductive inquiry to address knowledge gaps on how non-state actors can augment Earth System Governance and NDC implementation in the context of Global South cities. The paper highlights that Earth System Governance and climate change adaptation may be improved by increasing the use of South-South Climate Finance mechanisms in urban adaptation programmes and to facilitate institutional reforms that can lead to substantial increases in domestic tax collection.
Profit and Profitability and a Look Through the Lens of Smart Cities
Authors: Vaz do Vale Hamilcar
Published: September 2020

This study attempts to understand how the vision of the smart cities (SC) influences the way to understand profit and profitability in the practice of managers, where the context creates its interpretations of solutions and results. The research design throws light on narrative analysis and a discussion of the sense of profit and profitability in the context of the SC. The evidence found supports the construction of new meanings for profit and profitability, which on the one hand is reflecting on the way to share collective property assets, which are immobilized elements in the cities. On the other, it related to a sense that the quality of profitability is an extension of signifier of exploitation of resources. This study has its weakness in the multidisciplinary overlap that originated from the discussion of profit and profitability; innovation and urbanism is a promenade through complex themes that can only be an approximation of the challenges that can be materialized in the discussions about SC.
Difficulty in Transition
Authors: Saini Chand Prakash
Published: September 2020

The purpose of this article is to identify and study various risks that stop potential online shoppers to shop online. A total of 268 potential online shoppers were personally surveyed with a structured questionnaire. These respondents were from Gurgaon city. Exploratory factor analysis and regression analysis were used to assess the potential consumers' risk perception towards online retailing. It was found that potential online shoppers considered product risk, privacy risk, time risk, social risk, and security risk to be important while thinking of online shopping. Among all these risks security risks were found to be on potential online buyers' minds followed by product risk, social risk, privacy risk, and time risk. Online shopping behavior was the dependent variable in the study.
The Quality Amplification Challenge
Authors: Li Zhen , Rogers Pamela , Lau Wai Kwan
Published: September 2020

In dynamic production environments, positive business outcomes often require pursuing high quality, shorter throughput time, and low cost simultaneously. This research tries to track the timing effect of having undetected defects continue to progress through the supply chain. The purpose is to demonstrate the influence of throughput time on quality variance amplification and the effect of quality loss on manufacturing performance. A time series model is developed, and numerical analyses are conducted to understand how various parameters affect the quality variance fluctuation and quality loss amplification phenomena. The results show that the variance in quality increases as materials move down a supply chain, away from a supplier. In addition, the quality loss experienced by a manufacturer is greater than that faced by a supplier. Finally, both quality variability and quality loss amplification phenomena are larger when throughput time is longer.
Milk Supply Chain Network Design (SCND)
Authors: Pattnaik Monalisha
Published: September 2020

This study is based on a real-life case study of a SCND of a single milk product (premium milk) of a leading milk producing organization in Odisha. This product is highly perishable in nature; SCND implicates decision-making at a strategic level. Network design is the basis for the efficient operation of supply chain, and consequently, one of the most important problems a supply chain manager has to solve. This study conducts a real-life case-based modeling to address the gap in the area of supply chain network design. The author investigates the milk supply chain network design under preservation technology and propose a generic mathematical model for milk supply chain network design encompassing economic objective. A customized mathematical model is also developed for a leading milk producing organization in Odisha. Both of the models are formulated and solved by using piecewise nonlinear optimization.
Influence of Layer Parameters in Fused Deposition Modeling Three-Dimensional Printing on the Tensile Strength of a Product
Authors: Nguyen Vinh Du , Trinh Thai Xiem , Minh Pham Son , Nguyen Trong Huynh
Published: September 2020

Additive manufacturing (3D printing) is a hopeful technique that is used to produce complex geometry parts in a layer-by-layer method. Fused deposition modeling (FDM) is a popular 3D printing technology for producing components of thermoplastic polymers. In FDM process, the part quality is influenced strongly by the printing parameters. Until now, these parameters stil need to be investigated. Therefore, in this study, the influence of FDM 3D printing parameters on the tensile strength of product will be investigated. By experiment, three parameters, that is, layer height, solid layer top, and first-layer height, were studied. The investigation shows that the layer height is the only parameter impacted the tensile strength of the product.
A Comparative Study of Photodegradation Behavior Sodium Niobate Nanowires and Microcubes
Authors: Yan Chang Xu , Li Bo , Wang Jin
Published: September 2020

Sodium niobate catalysts with different morphologies of nanowires and microcubes have been prepared by hydrothermal method. The photocatalytic performance of NaNbO3 nanowires and microcubes was evaluated by degradation of rhodamine B (RhB) and cationic red X-GRL (CRX). The photodegradation reaction of organic dyes is shown to be kinetically first-order. The as-prepared NaNbO3 nanowires exhibit higher photo-catalytic activity for organic dyes degradation than NaNbO3 microcubes, which is attributed to the larger specific surface area and ferroelectric phase structure.
Ionic Diffusion and Dissociation in Room-Temperature Ionic Liquids
Authors: Ikeda Masahiro , Aniya Masaru
Published: September 2020

The clarification of the degree of ionic dissociation occurring in liquid-electrolyte systems such as those used in current lithium-ion batteries is important from both, fundamental and application points of views. In the present study, based on the bond strength–coordination number fluctuation (BSCNF) model proposed by the authors, we consider the relation between the ionic diffusion and dissociation in room-temperature ionic liquids. Specifically, we show firstly, that the molar conductivity Λ is well correlated with the degree of molecular cooperativity NB defined by the BSCNF model. This correlation enables to connect the cooperativity with the degree of ionic dissociation in ionic liquids. Through the comparison between the ionic diffusion coefficients and the molar conductivity, we discuss on a possible relation between these quantities.
First-Principles Study of Effects of Combined Ti Supervalent Cations and Lithium Ion Vacancies Doping on Crystal and Electronic Structures and Conductivity in LiFePO4
Authors: Cholsuk Chanaprom , Suwanna Sujin , Sukkabot Worasak , Busayaporn Wutthikrai , Suwanna Pimsiree
Published: September 2020

Olivine-type LiFePO4 is widely considered as a cathode for lithium-ion batteries owing to its environmental friendliness and low-cost, yet its applicability in the pristine state is limited due to poor electronic and ionic conductivity. To investigate the conductivity enhancement of LiFePO4, first-principles method under the GGA+U framework is implemented to study effects of doping with Ti4+ at Fe2+ sites under the lithium-deficient environment. LiFePO4 crystal and electronic structures as well as conductivity are investigated. Ti doping creates the impurity states at the acceptor level, which are normally degenerate states, but split into multiple states by the crystal field splitting. Doping under the lithium-deficient environment induces small hole polarons localizing at the Fe atoms and creates defect states located in the intermediate band. Both phenomena combine to facilitate charge carrier hopping. The climbing-image nudge elastic band (cNEB) calculation shows that Li hopping can be promoted by doping with high Ti concentration. This co-doping mechanism therefore can enhance both the electronic and ionic conductivities, which can be beneficial benchmark for cathode-material synthesis in the future.
The Research Progress of Fluorescent Probes for Detection of Selenols
Authors: Gao Yan , Han Li , Liu Jing Jing , Gao Xing , He Wen
Published: September 2020

Selenols (R-SeH) are similar to thiols , both of them are important reducing substance. Selenocysteine (Sec) and hydrogen selenide (H2Se) are two important selenols. They play a key role in cancer research and disease treatment. Recently, fluorescent probes and nanoprobes for detecting selenols have been developed rapidly because that fluorescent methods can be applied for biological imaging of cells or in vivo. Therefore, it is very important to the detect selenols. In this paper, we summarized the fluorescent probes for detecting the selenols in recent years.
Research Progress of Rare Earth-Based Hydrogen Storage Alloys
Authors: Jiang Zhao Jun , Wang Jun , Cao Dong Mei
Published: September 2020

As a clean and efficient renewable energy, hydrogen energy will play an important role in the future energy system. The utilization of hydrogen energy involves various fields including production, application, storage and transportation, and the storage of hydrogen has become the main technical bottleneck restricting the wide application of hydrogen energy. Rare earth-based hydrogen storage alloys are promising hydrogen storage medium and have been widely used as anode materials for commercial Ni/MH batteries because of the excellent hydrogen storage and electrochemical properties. In this paper, the research progress of AB5 and R-Mg-Ni-based rare earth-based hydrogen storage alloys is described in detail. The alloy composition, preparation process, heat treatment and surface treatment process have significant influence on the comprehensive properties of rare earth-based hydrogen storage alloys. The effects of element substitution on the hydrogen storage capacity, corrosion resistance, oxidation resistance and electrochemical properties of the alloys are emphasized. This paper provides a guidance and a theoretical basis for the development and application of rare earth-based hydrogen storage materials.
Development of Alginate Based Active Films Containing Turmeric Essential Oil
Authors: Phal Sophoan , Khan Muhammad Rafiullah , Leelaphiwat Pattarin , Chonhenchob Vanee
Published: September 2020

Sodium alginate based films containing turmeric oil (TEO) at different concentrations (1, 2 and 3%) were developed. The film with no TEO was used as control. Incorporation of TEO had the effects on the film properties. With increasing TEO concentrations, thickness, elongation at break, permeability of oxygen and water vapor of the films significantly (p ≤ 0.05) increased. Whereas moisture content, tensile strength and modulus of elasticity significantly (p ≤ 0.05) decreased. Scanning electron microscopy (SEM) analysis showed more numerous pores and rougher surface of the antifungal films than the control film.
Research on New Technology of Metal Powder-Plate Composite Rolling
Authors: Tian Yu Ting , Li Yan , Xia Lei , Man Ting Hui
Published: September 2020

The metal powder-plate composite rolling, which combines the Monel 400 metal powder and 45# steel plate, is a novel method to prepare composite strips. By using a new high-rigidity two-high metallurgical powder 350mm test mill designed and developed independently, the composite sheet is achieved by the process of “cold rolling+sintering+hot rolling”. Then the cross-section of the rolled composite sheet is analyzed. The results show that 0.9mm Monel 400 powder and 4.3mm 45# steel plate can be successfully rolled into a 4.4mm composite sheet after 4 passes of cold rolling, sintering at 1200°C and hot rolling at 900°C with furnace cooling. The detection analysis shows that transition layer of the composite sheet has obvious element diffusion without interface. The bonding surface has changed from physical bonding to metallurgical bonding, and the combination is excellent.
Research on Mix Proportion Design Method of Cement Concrete for Road Mixed with Antifreeze Admixtures Sealed in Capsules
Authors: Zhao Yang , Yu Hongfa , Wang Wei Dong , Li Yue
Published: September 2020

In order to explore the influence of a new mixed type antifreeze material on the flexural strength of concrete for road, the orthogonal design method was used to conduct experimental research on six factors including the water-binder ratio, the antifreeze material content, the fly ash content, the feeding process, the shape of the antifreeze material and the pre-absorption of antifreeze material. The influence degree of various factors on the flexural strength of concrete was studied, and the mixing ratio design method of concrete for road mixed with the antifreeze material was given. It was found that the water-binder ratio is the main factor affecting the strength of the concrete and that when the amount of antifreeze material is less than 15%, the effect on the strength is small. The influence of other factors on the strength is greatly influenced by the interaction of water-binder ratio. When it comes to the mix design, the content of gelling material is 500 kg/m3, and the water-binder ratio changes from 0.35 to 0.43 under different traffic levels. The recommended antifreeze material content and fly ash content is 10% and 15% respectively. It’s also suggested that the antifreeze material should be pre-absorbed, and the cement sand and stone be mixed before the antifreeze material is put into the mixing.
Vacancy Formation Energy of Metals
Authors: Starodubtsev Yuri N. , Tsepelev Vladimir S. , Wu Kai Ming , Kochetkova Yekaterina A. , Tsepeleva Nadezhda P.
Published: September 2020

In this work, we investigated and discussed the experimental and theoretical data of the vacancy formation energy Ev. The results of calculations in the continuum model of the solids and the model of interaction between a pair of neutral atoms, as well as the results of ab initio methods using various exchange – correlation functionals, are analyzed. It was found that the experimental and theoretical values of the vacancy formation energy have an adjusted coefficient of determination R2 close to 0.80. The relationship between the calculated vacancy formation energy and the sublimation enthalpy most closely corresponds to the relation Ev = ΔHs/3 for the results obtained on the basis of continuum model and model of interaction between a pair of atoms. The vacancy formation energy most closely correlates with the melting enthalpy ΔHm. The adjusting coefficient of determination R2 of this relation is 0.87 in comparison with 0.71 and 0.84 for the sublimation enthalpy and the evaporation enthalpy, respectively.
Numerical Simulation and Parameter Study of Radial Forging of Conical Tube
Authors: Zhao Xin Hai , Ren Xin Bo , Sun Xing Chen , Zheng Chao , Song Li Bin , Zhao Guo Qun
Published: September 2020

The cone tube is an important part of the circuit connector, which has high requirements for its forming quality. In this paper, the cone tube is taken as the object, the finite element model is established, the radial forging process of the cone tube is simulated, the influence of process parameters such as axial feed and friction on the thickness of the cone tube is studied, and the influence law is analyzed, which has certain reference value for the analysis of the forming law of the radial forging.
TIG Overlap Welding Affecting Hard-Faced Weld Metal Properties on JIS-S50C Carbon Steel
Authors: Kimapong Kittipong , Wattanajitsiri Voraya , Chantasri Sakchai , Triwanapong Surat
Published: September 2020

This paper aimed to study an overlap distance (OL) of hard-faced welding bead in a tungsten inert gas (TIG) welding on the JIS-S50C carbon steel surface. Hard-faced weld metal was produced on an outside surface of the cylinder, using TIG welding with a high chromium flux-cored wire electrode. Welding process parameters were a welding current of 150–210 A and a hard-faced layer of 1–3. The experimental results were summarized as follows. An increase in welding current increased the weld width and the penetration but decreased the weld convex. It also increased the hardness and wear resistance of hard-faced weld metal. The increase of a weld overlap distance resulted in a decrease in the dilution effect in weld metals and an increase in the hardness and wear resistance. An increase in the hard-faced weld metal layer also resulted in a decrease in the dilution effect, resulting in an increase in the hardness and wear resistance.
High-Temperature Oxidation Behaviors of 30Cr25Ni20Si Heat-Resistant Steel in Air
Authors: Yang You , Wang Xiao Dong
Published: September 2020

High temperature oxidation dynamic behaviors and mechanisms for 30Cr25Ni20Si heat-resistant steel were investigated at 800, 900 and 1000°C. The oxide layers were characterized by scanning electron microscopy (SEM-EDS), X-ray diffractometer (XRD). The results showed that the oxidation rate of test alloys is increased with increasing the oxidation time. The oxidation dynamic curves at 800 and 900°C follow from liner to parabolic oxidation law. The transition point is 10 h. At 1000°C, the steel exhibits a catastrophic oxidation, and the oxidation mass gain value at 50 h is 0.77 mg/cm2. This suggests that the steel at 900°C has formed a dense protective surface oxidation film, effectively preventing the diffusion of the oxygen atoms and other corrosive gas into the alloy. Therefore, at the first stage of oxidation, chemical adsorption and reaction determine the oxide film composition and formation process. At the oxide film growth stage, oxidation is controlled by migration of ions or electrons across the oxide film. When the spinel scale forms, it acts as a compact barrier for O element and improving the oxidation resistance.
Bedside wireless lung ultrasound for the evaluation of COVID-19 lung injury in senior nursing home residents
Authors: Dini Frank Lloyd , Bergamini Carlo , Allegrini Aldo , Scopelliti Massimo , Secco Gianmarco , Miccoli Mario , Boni Stefano , Brigada Raffaella , Perlini Stefano
Published: September 2020

Lung Ultrasound (LUS) is regarded to be potentially useful to diagnose lung injury in older adults living in nursing homes with suspected COVID-19 pneumonia. We aimed at evaluating presence lung injury among senior nursing home residents by LUS performed with portable wireless scanner echography. The study population consisted of 150 residents with a mean age of 88 years (85% female) residing in 12 nursing homes in Northern Italy. Subjects had to have a history of recent onset of symptoms compatible with COVID-19 pneumonia or have been exposed to the contagion of patients carrying the disease. COVID-19 testing was performed with SARS-CoV-2 nasal-pharyngeal (NP) swabs. Positive subjects to LUS scanning were considered those with non-coascelent B-lines in >3 zones, coalescent B-lines in >3 zones and with iperdensed patchy non-consolidated lungs. Sixty-three percent had positive NP testing and 65% had LUS signs of pulmonary injury. LUS had a sensitivity of 79% in predicting positive NP testing. Sixteen percent of residents tested negative for SARSCoV-2 carried the signs of COVID-19 lung injury at LUS. There were 92 patients (61%) with current or recent symptoms.Positivity to LUS scanning was reported in 73% of residents with symptoms, while it was 53% in those without (P=0.016). A positive NP testing was observed in 66% of residents with symptoms and in 57% of those without (P=0.27). We conclude that assessment of LUS by portable wireless scanner echography can be profitability utilized to diagnose lung injury among senior nursing home residents with or without symptoms compatible with COVID-19 pneumonia.
Role of Pain-Related Evoked Potential in the Diagnosis of Meralgia Paresthetica
Authors: Ahmed Shaikh Atif Iqbal , Das Monika , Roy Anupama , Baby Bini , Dhar Dolcy , Abigayil Jebalin , Varghese Vitty Susan , Mathew Vivek , Aaron Sanjith , Sivadasan Ajith , Premkumar Paul , Suresh Tharan , Prabhakar Appaswamy Thirumal
Published: September 2020

Introduction:

Entrapment of the lateral femoral cutaneous nerve (LFCN) of thigh results in meralgia paresthetica (MP). Standard electrophysiological tests for MP are technically demanding and unreliable. We aimed to study the role of pain-related evoked potentials (PREP) in the diagnosis of MP.

Methods:

Patients with MP and normal volunteers were included. PREP was recorded by stimulating the skin over the lateral thigh 20 cm below the anterior-superior iliac spine and recording from the cortex at Cz.

Results:

A total of 28 subjects and 56 LFCNs were studied. 36 nerves had MP and 20 were normal. The mean PREP latency was 118 (8) ms among normal controls and 164 (10.8) ms in MP. The optimal cut-off point for the diagnosis of MP was 134 ms. Area under receiver operator characteristic curve was 0.97; sensitivity was 91.7% and specificity was 100%.

Conclusion:

PREP is reliable and easy to use electrophysiological test in establishing the diagnosis of MP.
Extraaxial cerebellopontine angle medulloblastoma with multiple intracranial metastases in adult: A rare case report with a review of literature
Authors: Singh Saraj , Kumar Niraj
Published: September 2020

Medulloblastoma (MB) is very rare malignant primary brain tumor in adults and its location at cerebellopontine angle (CPA) is even rarer. There are only few case reports of CPA MBs in literature. Most of them are reported in pediatric age groups which are mostly intraaxial. Only 11 cases of extra-axial CPA MBs have been reported so far. The author is reporting a very rare case of adult extra-axial CPA MBs with multiple intracranial metastases. We are also reviewing clinical and radiological features and unusual way of its presentation along with surgical management. Keeping MBs as one of the differential diagnosis for extra-axial CPA tumors is going to increase our spectrum of diagnosis which can lead to alteration in management.
A rare case of an aneurysmal bone cyst of the temporal bone
Authors: Gotecha Sarang , Punia Prashant , Chugh Ashish , Patil Anil , Kashyap Dushyant , Raghu Vybhav , Chhabra Shobhit , Patel Ankit , Kotecha Megha
Published: September 2020

Aneurysmal bone cysts (ABCs) are benign bone lesions mainly occurring at the metaphyseal end of long bones and are a rarity in the calvarium. The reported incidence of this lesion in the skull is 1% of all the ABC. It is a benign condition that may extend intracranially. We report here a case of a 3½-year-old male child who presented with a bony hard, painless, and gradually enlarging swelling over his right temporal region. Radiological investigations and histology revealed that the lesion was an ABC. A total surgical excision was achieved despite its intracranial extension along with the involvement of dura. Prognosis is excellent with total removal as a total surgical removal of the lesion is considered curative. The rarity of the lesion along with a good surgical result despite an intracranial extension with dural involvement prompted this report.