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The past several decades have witnessed an increasing number of natural and manmade hazards with a dramatic impact on the normal operations of the society. The occurrences of these hazards manifest...

INTRODUCTION Heroin overdose is a leading cause of mortality among drug users. This paper aims to identify individual and contextual factors associated with lethal and non-lethal heroin-related overdoses on the basis of case reports and semi-structured proxy interviews. Typical patterns within these cases are determined by means of cluster analysis. METHODS Within the CaRe (Case Reports of heroin-related overdoses) study, case reports (100 proxy reports of overdose events from 36 different facilities) were gathered and evaluated as part of a nationwide survey of experts conducted in Germany in 2019. Following initial descriptive analyses a two-step cluster analysis with the four binary variables of gender, age, time and place was conducted to identify patterns within the reported cases. RESULTS The case reports grouped into five clusters: 1) Younger male drug users, found in a public space during the daytime; 2) Female drug users; 3) Older male drug users, found in a public space during the daytime; 4) Drug users found at home at night; 5) Drug users found outside at night. Overdoses by female drug users and those which occurred at home and/or at night were significantly more likely to have a fatal outcome. CONCLUSION Future prevention and intervention measures should aim to consider the context, i.e. typical constellations of risk, and attempt to inhibit this through appropriate counter measures.

PurposeWhile United States is among countries with the world’s highest coronavirus infections, its approaches and policies to reopen the economy vary by state. A lack of objective criteria and monitoring toward satisfying the criteria can lead to another COVID-19 outbreak and business closures. Considering the pressing need to return to normalcy without a rebound of COVID-19 infections and deaths, an index that provides a data-driven and objective insight is urgently needed. Hence, a method was devised to assess the severity of the COVID-19 pandemic and determine the degree of progress any state has made in containing the spread of COVID-19.Design/methodology/approachUsing measures such as the weekly averages of daily new deaths, ICU bed occupancy rates, positive cases and test positivity rates, two indexes were developed: COVID-19 reopening readiness and severity.FindingsA clear difference in the pandemic severity trends can be observed between states, which is possibly due to the disparity in the state’s response to coronavirus. A sharp upward trend in index values requires caution prior to moving to the next phase of reopening.Originality/valueThe composite indexes advanced in this study will provide a universal, standardized and unbiased view of each state’s readiness to reopen and allow comparisons between states. This in turn can help governments and health-care agencies take counter measures if needed as to the anticipated demand for future health-care services and minimize adverse consequences of opening.

Through the method of literature and online inquiry, this paper studies the connotation, harm and classification of bribery in competitive sports industry and puts forward countermeasures such as enhancing the sensitivity of judicial enforcement and strengthening the management of sports competitions, which provides the basis for the decision-making of competent departments.

Physical Unclonable Functions (PUFs) exploit the manufacturing process variations inherent in silicon-based chips to generate unique secret keys. Although PUFs are supposed to be unclonable or unbreakable, researchers have found that they are vulnerable to machine learning (ML) attacks. In this article, we analyze the vulnerability of different FPGA-based Ring Oscillator PUFs (ROPUFs) to machine learning attacks. The challenge-response pairs (CRPs) data obtained from different ROPUFs is trained using different machine learning algorithms. From the study, it is found that the Artificial Neural Network (ANN) models can be used to train the ROPUFs with a training accuracy of 99.9% and a prediction accuracy of 62% when 5,000 CRPs are used for a challenge-response ROPUF. In this article, we assume a realistic situation where a small set of the CRP dataset (approximately 15% maximum) is unscrupulously obtained by the hacker. A prediction accuracy of 62% makes the PUF vulnerable to machine learning attacks. Therefore, a secondary goal of this article is the design of a ROPUF capable of thwarting machine learning modeling attacks. The modified XOR-inverter ROPUF drastically reduces the prediction accuracy from 62% to 13.1%, thus making it increasingly difficult for hackers to attack the ROPUF.

The Antarctic environment is characterized by many of the same extreme stressors as long-duration space flight (LDSE), thereby providing a useful earth-based analog for examining changes in and predictors of mental health over time. At coastal (n = 88) and inland (n = 22) Antarctic stations we tracked mental health symptoms across a nine-month period including winter-over using the Mental Health Checklist (MHCL; Bower et al., 2019). Our monthly assessment battery also examined changes in physical complaints, biomarkers of stress, and the use of different emotion regulation strategies. MHCL positive adaptation scores showed linear decreases whereas MHCL poor self-regulation scores and severity of physical symptoms increased across the study period. During-mission use of emotion regulation strategies and dehydroepiandrosterone (DHEA) levels predicted end-of-study MHCL scores, whereas trait-based psychological measures collected at the start of the mission showed little predictive utility. Results suggest that interventions and counter measures aimed at enhancing positive affect/emotion during prolonged exposure to extreme environments may be useful in reducing psychological risk.

Objective:People with NCDs are particularly vulnerable to disasters. This research systematically reviewed reports describing studies on the status of patients with NCDs before, during and after disasters.Method:Relevant articles published from 1997 to 2019 were collected by searching the Scopus, PubMed, and Science Direct databases. We specifically examined reports describing NCDs and including the key words ‘Non-Communicable Disease and Disasters.’ NCDs include cardiovascular, respiratory, diabetes and cancer diseases.Results:The review identified 42 relevant articles. Most of the included studies were found to have described the conditions of patients with NCDs after disasters - 14 (13.3%), during disasters – 11 (26.2%), before disasters – 6 (14.3%), within all stages of disasters: before, during and after – 6 (14.3%), only during and after disasters – 4 (9.5%), and includes before and during disasters – 1 (2.4%).Conclusion:NCDs pose major health issues in disasters. Development of strong counter measures against the interruption of treatment, as well as surveillance systems to ascertain medical needs for NCDs are necessary as preparation for future disasters.

In recent times, the use of Chemical Warfare (CW) agents against civilian and military by terrorists and rogue countries are recurrent. The examples of such attacks are available in open literature. They are highly dangerous due to their acute toxicity nature. They tend to stimulate and paralyze nerve system of the body and cause other toxic side effects. Once these toxic chemicals are released into the atmosphere, timely detection and identification of the same at standoff distances will help the defensive forces to take proper counter measures. Detection techniques such as ion mobility spectrometry, infrared spectrometry, Raman spectrometry, FTIR, LIDAR, etc. have been used widely. Among all these techniques, Raman spectroscopy techniques and LIDAR (LIght Detection and Ranging) is the only active remote detection method that can detect and discriminate the chemical agents at standoff distances. Infrared DIAL (Differential Absorption Lidar) is a versatile technique for remote detection of various chemicals. DIAL technique can provide spatially resolved measurements of these agents with sufficient sensitivity (at few ppm levels) at ranges of several kilometers by exploiting the concept such as scattering and absorption from the atmosphere. The main objective of this review paper is to bring out the details of highly potential chemical warfare agents, their properties and laser based remote detection sensors. LIDAR technique is emphasized in more detail because of their long range detection capability, sensitivity and selectivity. An overview of existing R&D based and commercial systems is also discussed.

Construction is a demanding work environment. Many construction professionals experience workplace stress, leading to physiological, psychological and sociological strain effects. They adopt a vari...

Violence against women is a world-wide crisis of pandemic magnitude. The crime statistics in India show a steady increase in violence against women in urban areas.Different theories in Criminology have sought to explain violent crime in general and violence against women in particular.Violence inhibits harm both psychological and physical.The crime statistics is self explanatory and exhibits the scenario of violence against women in nineteen metropolitan cities of India which are smart cities. However it deserves mention that the level of literacy,development of the states, religious and cultural values,geographical and political location of the city can play provocative causes for the incidents of criminality. Collaborative effort of the people, NGOs and the urban police can foster sustainable urban society which are smart in the true sense of the term. Each city has its unique characteristics, issues of concern and distinct demographic and environmental conditions which influence people's life and crime trends. Thus each commissionerate should identify the lacunae, problems and prioritise accordingly and can thereby succeed in achieving success in combating crime. The present study analyses the trends of violence against women in smart cities of India and attempts to explore the counter measures that can be undertaken to eradicate the bane.

COVID-19, caused by SARS-CoV-2, is severe respiratory illnesses leading to millions of deaths worldwide in very short span. The high case fatality rate and the lack of medical counter measures emphasize for an urgent quest to develop safe and effective vaccine. Receptor-binding domain (RBD) of spike protein of SARS-CoV-2 binds to the ACE2 receptor on human host cell for the viral attachment and entry, hence considered as a key target to develop vaccines, antibodies and therapeutics. In this study, immunoinformatics approach was employed to design a novel multi-epitope vaccine using RBD of SARS-CoV-2 spike protein. The potential B- and T-cell epitopes were selected from RBD sequence using various bioinformatics tools to design the vaccine construct. The in silico designed multi-epitope vaccine encompasses 146 amino acids with an adjuvant (human beta-defensin-2), which was further computationally evaluated for several parameters including antigenicity, allergenicity and stability. Subsequently, three-dimensional structure of vaccine construct was modelled and then docked with various toll-like receptors. Molecular dynamics (MD) study of docked TLR3-vaccine complex delineated it to be highly stable during simulation time and the stabilization of interaction was majorly contributed by electrostatic energy. The docked complex also showed low deformation and increased rigidity in motion of residues during dynamics. Furthermore, in silico cloning of the multi-epitope vaccine was carried out to generate the plasmid construct for expression in a bacterial system. Altogether, our study suggests that the designed vaccine candidate containing RBD region could provide the specific humoral and cell-mediated immune responses against SARS-CoV-2. Communicated by Ramaswamy H. Sarma

Purpose Today, online shopping and online business has become a new norm especially in the current pandemic scenario. With more businesses running online, cyber criminals are coming up with different tactics to steal identity and sensitive information such as credit card and banking credentials either for personal monetary gain or to sell in the dark Web. One form of such attack that is seen in the recent times is formjacking attack. This paper aims to review the current scenario of formjacking attack and its modus operandi. The paper also provides certain counter measures that can be adopted by the users and website owners. Design/methodology/approach The paper mainly focuses on the modus operandi of formjacking attack to understand the severity of the problem. Based on the way the attack is carried out, some guidelines to be followed are provided. Later, a brief review of machine learning techniques is furnished to understand how it may help as secure defense mechanism. Findings Formjacking attacks are on a rise in the past two years, especially during the holiday season. Cyber criminals have been using smart tactics to carry out these attacks which are very difficult to detect. Machine learning techniques may prove to be effective in combating these attacks. Originality/value Formjacking attack is not just a concern of the customers who may lose their sensitive data, but the onus also lies on the companies itself to ensure they protect their customer’s data from theft. Not much research is found regarding formjacking attack, as it is relatively a new form of attack. The paper reviews this attack and provides some measure that can be followed. It also provides few guidelines which can be used for further research in devising a security tool to mitigate this problem.

This paper, by means of quantitative and qualitative analysis based on a vast investigation, talks about the anomie in China’s academic publishing from the following three aspects: first, disorders...

Although it has been proven that various volatile organic compounds (VOCs) are produced during surgery, there have been no studies focusing specifically on endoscopy. Therefore, we aimed to investigate VOCs produced during endoscopic submucosal dissection (ESD). Thirty-one patients scheduled for ESD were enrolled in this study. Sorbent tubes were installed to collect gas at two sites: one in a suction bottle and the other at the level of the endoscopists’ upper chest. Gas collections were performed for up to 30 min during submucosal dissection. Quantitative analysis of the VOCs in gas samples was performed using gas chromatography and mass spectrometry. Concentrations of fifteen VOCs were measured. The total concentration of volatile organic compounds (TVOC) was also calculated. Among the five carcinogens—benzene, ethylbenzene, formaldehyde, tetrachloroethylene, and trichloroethylene (TCE)—measured, excess life-time risks of cancer for benzene and TCE were interpreted as unacceptable based on the New Jersey Department of Environmental Protection Division of Air Quality and the Environmental Protection Agency guidelines (5 × 10–4 and 7 × 10–5, respectively). Among the non-carcinogenic VOCs, the mean concentration of toluene was much higher than the reference value (260 μg/m3) in the Japanese guidelines for indoor air quality (IAQ) (1323.7 ± 2884.0 μg/m3 from the air at the upper chest level of endoscopists and 540.9 ± 1345.4 μg/m3 from the suction bottle). Mean TVOCs were at least 10 times higher than the reference value (400 μg/m3) issued by the Japanese guidelines for IAQ. Various carcinogenic and non-carcinogenic VOCs were detected at levels higher than the reference “safe” values during the submucosal dissection step of ESD. Implementation of counter measures is essential to protect medical personnel who are involved in ESD surgeries.

Studies were carried out with the aim of analyzing blackouts in electric networks of 0.4 ... 10 kV and determining the main countermeasures to reduce their number. As an indicator of reliability, the failure rate of the main network elements is analyzed. The total number of outages considered included consumer outages, outages due to damage to 0.4 kV overhead power lines (transmission lines) and transformer substation (TS) equipment. The studies were carried out on the basis of the data of Mtsenskiy, Orloyskiy and Pokrovsky districts of electric networks of “Oreloenergo” – a branch of PJSC “MRSK Center” and JSC “Oreloblenergo” in the period from 2015 to 2017. Most of the causes of damage to power line equipment of 0.4 and transformer substations of 10/0.4 kV can be prevented by increasing the level of its maintenance and conducting timely diagnostics. The determination of quantitative indicators of the effectiveness of countermeasures to reduce the number of outages is difficult due to the lack of technical condition monitoring systems in electric networks. The main measures aimed at solving this problem in 0.4 kV networks are the transition to power lines with insulated wires; improving the design of switching devices, switches and transformer leads; the use of diagnostic tools; disaggregation of power lines. Replacing the equipment of electric grids with new types provides the economic effect of reducing the frequency of failures, as well as saving due to a reduction in maintenance costs. In particular, replacing transformers with hermetic ones allows reducing electricity shortfalls by 43.6%, and insulated wires by 95.3%

The research is talking about a virus spread across the world with her being taken from the government and MUI as the Islamic regime. The government itself has issued a hand-to-hand lockdown system and also a PSBB or social distaff to fight the spread of the virus covid-19, so is the counter measures done by MUI by canceling traditional player in the mosque and by reducing Friday prayer in regular. Even though this circular became a pro and cons for most of society especially at the rings of MUI. The purpose of this research is to help the public understand whether the government’s existence and MUI’s treatment of the plague corresponds to or even contradicts the Islamic regime. Research methods will be used with literature literature review with the normative approarch and supported by the historial approach. Research shows that the rule imposed by the government and MUI in handling the outbreak did not include an investigation into Islam.

This article presents a review and a synthesis of basic strategies and approaches, which constitute the basis of modern strategies for combating extremist and terrorist threats or their prevention. The approaches to the matter are defined, and their social consequences are considered. It summarizes the issues, concerning prior aspects of counter-terrorism strategies, which should be taken into consideration. It also presents some critical expert views whether any universal foundations for counter-terrorism strategies could be found. The author pays attention to the existing general difficulties at this scientific field, which directly affect the studys success. It focuses on the importance of careful approach to the issue from both by the general public and policy makers.

One of the most serious problems in modern society is that internet users are deceived by various fake information. In this paper, we analyse a scenario based on an actual incident of fraud called business email compromise (BEC). We suppose that each email, in the incident, step-wisely changes user’s thinking and makes him or her believe the emails. If fraud has such a step-by-step mechanism, it allows us to consider counter measures for dissuading a user from decision-making on the way. We discuss features and factors of the incident based on formulations of Channel theory. Our analysis revealed that each email message influenced user’s decision-making by what kind of logical trap. It can be fundamental knowledge that is capable of warning the user with predicting logical traps. This paper contributes to providing a novel viewpoint to develop systems for detecting deception of BEC.

Internet of Things (IoT) is undoubtedly a well-known research area. Security on IoT communication services is the major challenge with advanced technology and devices. This paper mainly focusing on Perceptron layer based attacks and counter measures based on Effective Authentication System (EAS). This paper is ordered as outlining IoT Architecture, Types of Threats ,Perceptron Layer based attacks, sensor based communication services ,RFID mechanism ,Tag identify and verification by back end server and Hash based Effective Authentication System (EAS) to avoid pseudonym attacks .This paper proposes EAS as security measure by preventing privacy attack, pseudonym attack, location tracking and asynchronous attack.

Internet of Things (IoT) technology is anticipated to pave the way for groundbreaking applications in a number of areas of current healthcare systems. Given the significant number of connected medical devices, the vital data generated by the patient is under several security threats. Selective Forwarding (SF) and Wormhole (WH) attacks are two critical threats that cause information deficit in the network. The SF attack drops critical data packets at compromised nodes while the WH attack creates fallacious routing tables due to the introduction of malicious routes in the network. In this paper, we focus on the security aspects of Healthcare-IoT and review the proposed counter-measures against the SF and WH attacks. We weigh the recently postulated counter-measures based on their significance and identify their limitations. Additionally, we propose a blockchain-based cryptographic framework for mitigating SF and WH attacks in H-IoT. We explore future research directions in mitigating these threats.

Automatic Speaker verification systems are vulnerable to spoofing attacks. We propose our anti-spoofing system. It uses some acoustic features. The set of binary classifiers includes XGBoost tree boosting algorithm. ASV Spoof 2015 corpus is utilized in the experiments as the main database for anti-spoofing systems training. The pretreatment of acoustic features is essential for better performance of the system. Obtained results demonstrate that the proposed system can provide a good accuracy. High evaluation performance can be obtained using the combination between MFCC, LogFBE and SSC features. The attained metrics values such 97.80% for the accuracy, 97.12% for the precision, 98.50% for the Recall and 97.81% for the F1-mesure validate the performance of the proposed technique.