The Dark Triad (i.e., narcissism, psychopathy, Machiavellianism) has garnered intense attention over the past 15 years. We examined the structure of these traits’ measure—the Dark Triad Dirty Dozen (DTDD)—in a sample of 11,488 participants from three W.E.I.R.D. (i.e., North America, Oceania, Western Europe) and five non-W.E.I.R.D. (i.e., Asia, Middle East, non-Western Europe, South America, sub-Saharan Africa) world regions. The results confirmed the measurement invariance of the DTDD across participants’ sex in all world regions, with men scoring higher than women on all traits (except for psychopathy in Asia, where the difference was not significant). We found evidence for metric (and partial scalar) measurement invariance within and between W.E.I.R.D. and non-W.E.I.R.D. world regions. The results generally support the structure of the DTDD.

Although results of animal research show that interactions between stress and sex hormones are implicated in the development of affective disorders in women, translation of these findings to patients has been scarce. As a basic step toward advancing this field of research, we analyzed findings of studies which reported circulating cortisol levels in healthy women in the follicular vs. luteal phase of the menstrual cycle. We deemed this analysis critical not only to advance our understanding of basic physiology, but also as an important contrast to the findings of future studies evaluating stress and sex hormones in women with affective disorders. We hypothesized that cortisol levels would be lower in the follicular phase based on the proposition that changes in levels of potent GABAergic neurosteroids, including allopregnanolone, during the menstrual cycle dynamically change in the opposite direction relative to cortisol levels. Implementing strict inclusion criteria, we compiled results of high-quality studies involving 778 study participants to derive a standardized mean difference between circulating cortisol levels in the follicular vs. luteal phase of the menstrual cycle. In line with our hypothesis, our meta-analysis found that women in the follicular phase had higher cortisol levels than women in the luteal phase, with an overall Hedges' g of 0.13 (p < 0.01) for the random effects model. No significant between-study difference was detected, with the level of heterogeneity in the small range. Furthermore, there was no evidence of publication bias. As cortisol regulation is a delicate process, we review some of the basic mechanisms by which progesterone, its potent metabolites, and estradiol regulate cortisol output and circulation to contribute to the net effect of higher cortisol in the follicular phase.

Objective: To explain the global between-countries variance in number of deaths per million citizens (nDpm) and case fatality rate (CFR) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Design: Systematic analysis. Data sources: Worldometer, European Centre for Disease Prevention and Control, United Nations Main outcome measures: The explanators of nDpm and CFR were mathematically hypothesised and tested on publicly-available data from 88 countries with linear regression models on May 1st 2020. The derived explanators - age-adjusted infection fatality rate (IFRadj) and case detection rate (CDR) - were estimated for each country based on a SARS-CoV-2 model of China. The accuracy and agreement of the models with observed data was assessed with R2 and Bland-Altman plots, respectively. Sensitivity analyses involved removal of outliers and testing the models at five retrospective and two prospective time points. Results: Globally, IFRadj estimates varied between countries, ranging from below 0.2% in the youngest nations, to above 1.3% in Portugal, Greece, Italy, and Japan. The median estimated global CDR of SARS-CoV-2 infections on April 16th 2020 was 12.9%, suggesting that most of the countries have a much higher number of cases than reported. At least 93% and up to 99% of the variance in nDpm was explained by reported prevalence expressed as cases per million citizens (nCpm), IFRadj, and CDR. IFRadj and CDR accounted for up to 97% of the variance in CFR, but this model was less reliable than the nDpm model, being sensitive to outliers (R2 as low as 67.5%). Conclusions: The current differences in SARS-CoV-2 mortality between countries are driven mainly by reported prevalence of infections, age distribution, and CDR. The nDpm might be a more stable estimate than CFR in comparing mortality burden between countries.

This paper investigates the relationship of information communication technology (ICT) and virtual reality (VR), and tourism, or specifically its interrelations and links to tourism sustainability. As a consumer technology, VR is still a relatively new concept, although it has been researched and used in the tourism industry for marketing purposes. The aim is to understand the different aspects of VR and ICTs and potentially link them to sustainability and perspectives on mass tourism, as well as to the potential future developments related to the ability of ICT and tourism to meet the tourists’ needs to a greater extent in the future. By use of the systematic mapping methodology, the insights into these concepts and their relations to each other are provided. The study reveals the evolution and links between the investigated concepts, the existing challenges and solutions, and the remaining gaps. The present findings indicate that VR as a trend in the tourism industry still needs significant work and improvement until it is ready to fully immerse itself into the tourism sector and especially involve itself into the issues concerning tourism and the potential of sustainability concept within the industry. Many of the concerns and conflicts still exist, but the potential of its right implementation is enormous.

Neural networks are important method of machine learning that can be used to predict air quality with high accuracy. Using NARX-SP neural network type, several neural network models are developed to predict concentration of air pollutants in Sarajevo for two prediction cases, for 24th and 48th hour ahead, with different combinations of inputs and outputs. The data used in this paper contain hourly values of meteorological parameters (air humidity, pressure and temperature, wind speed and direction) and concentrations of SO2, PM10, NO2, O3 and CO from 2016 to 2018. Optimal models are selected for both prediction cases. It is concluded that the optimal models have very good performances and can be used to predict concentration of pollutants in Sarajevo with great accuracy and contribute to improve quality of life. By adequate application of optimal models, concentration of air pollutants can be predicted for each hour over the next 48 hours.

Quantum computing has the power to break current cryptographic systems, disrupting online banking, shopping, data storage and communications. Quantum computing also has the power to support stronger more resistant technologies. In this paper, we describe a digital cash scheme created by Dmitry Gavinsky, which utilises the capability of quantum computing. We contribute by setting out the methods for implementing this scheme. For both the creation and verification of quantum coins we convert the algebraic steps into computing steps. As part of this, we describe the methods used to convert information stored on classical bits to information stored on quantum bits.

Abstract Assets such as gold, silver, government bonds are widely considered good hedges against adverse movements in the stock market. At times, market participants move between these markets in order to hedge against any immediate risks. The shifts from one market to another likely create a dynamic relationship between the stock market and other assets. We investigate short-run and long-run causality between the industry returns and the prices of the four assets: gold, silver, oil, and 10-year Treasury bonds. Using symmetric and asymmetric Granger causality, we try to identify different industries within the S&P500 that are caused by movement in the prices of these four assets. Although we were able to find short-run and long-run bidirectional causality between the four asset prices and share returns in many industries, our findings are industry-specific. We discover overwhelming and robust evidence of symmetric and asymmetric causality between 10-Year Treasury yield and returns of almost all 18 industries we considered.

Recent work has shown how predictive modeling can endow agents with rich knowledge of their surroundings, improving their ability to act in complex environments. We propose question-answering as a general paradigm to decode and understand the representations that such agents develop, applying our method to two recent approaches to predictive modeling -action-conditional CPC (Guo et al., 2018) and SimCore (Gregor et al., 2019). After training agents with these predictive objectives in a visually-rich, 3D environment with an assortment of objects, colors, shapes, and spatial configurations, we probe their internal state representations with synthetic (English) questions, without backpropagating gradients from the question-answering decoder into the agent. The performance of different agents when probed this way reveals that they learn to encode factual, and seemingly compositional, information about objects, properties and spatial relations from their physical environment. Our approach is intuitive, i.e. humans can easily interpret responses of the model as opposed to inspecting continuous vectors, and model-agnostic, i.e. applicable to any modeling approach. By revealing the implicit knowledge of objects, quantities, properties and relations acquired by agents as they learn, question-conditional agent probing can stimulate the design and development of stronger predictive learning objectives.

Noninvasive contactless methods for electric power line monitoring based on magnetic field measurement have become an interesting topic for researchers and the electric power industry since introduction of the Smart Grid concept. By measuring and analyzing magnetic field originating from currents in power line conductors, it is possible to detect faults in the network. In medium voltage distribution networks, where a variety of different pole geometries are present, different criteria for fault detection have to be employed for each geometry, which complicates detection and influences accuracy. This paper proposes a novel approach for fault detection in medium voltage distribution networks which is based on processing of signals measured by low cost contactless magnetic field sensors. In order to create a generalized method for fault detection, a sequence of mathematical transformations of the measured magnetic field components is applied. A novel geometric transformation which eliminates influence of pole geometry is introduced, providing signals from which steady-state symmetrical components of the rotating magnetic field are computed. Those components are used as general fault detection criteria. The proposed approach is confirmed to be applicable for different fault types by a set of experiments on three-phase overhead power line model scaled to laboratory conditions.

Probably in the history of medicine, doctors were not as united as they are today, in that fight against COVID-19, when the pandemic spread incredibly fast - from East to West, from North to South. The COVID-19 pandemic is likely to have unprecedented and unforeseeable consequences, from those on a worldwide/global level to those at the local level - at the level of local communities and families, and individuals (and not just humans, but all other living beings), of which the future will testify in various ways. The consequences will be political, economic, social, but probably to the greatest degree, the consequences of a health nature - systemic and individual. The death toll is high, despite the therapy being applied. We do not currently have a specific and effective therapy against COVID-19. In addition, we do not have a single clinical study that would support prophylactic therapy that could affect COVID-19. All of the therapeutic options now available to us are based on the experience we have gained in treating SARS and MERS. When the vaccine is discovered, at that moment we will be able to say that we have an appropriate and effective method in fighting against COVID-19. Some historians of medicine believe that voluntary vaccination against COVID-19 would be, not only less politically risky but also more effective in protecting the population from coronavirus. It remains to be seen what the new wave of the COVID-19 pandemic, announced by WHO experts these days, and which is expected in the fall of 2020, will bring us.

Introduction: COVID-19 is the disease caused by an infection of the SARS-CoV-2 virus, previously known as 2019 Novel Coronavirus (2019-nCoV) respiratory disease. World Health Organization (WHO) declared the official name as COVID-19 in February 2020 and in 11th March 2020 declared COVID-19 as Global Pandemic. In June 6th 2020, over 7 million cases registered in the world, recovered 3.4 million and death over 402.000. Aim: The aim of this study is to retreive published papers about COVID-19 infection deposited in PubMed data base and analyzed current results of investigations regarding morbidity and mortality rates as consequences of COVID-19 infection and opinions of experts about treatment of afected patients with COVID-19 who have Cardiovascular diseases (CVDs). Methods: It’s used method of descriptive analysis of the published papers with described studies about Corona virus connected with CVDs. Results: After searching current scientific literature (on PubMed till today is deposited more than 1.000 papers about COVID-19 with consequences in almost every medical disciplines), we have acknowledged that till today not any Evidence Based Medicine (EBM) study in the world. Also, there are no unique proposed ways of treatments and drugs to protect patients, especially people over 65 years old, who are very risk group to be affected with COVID-19, including patients with CVDs. Vaccine against COVID-19 is already produced and being in phases of testing in praxis in treatment of COVID-19 at affected patients, but the opinions of experts and common people whole over the world about vaccination are full of controversis. Conclusion: Frequent hand washing, avoiding crowds and contact with sick people, and cleaning and disinfecting frequently touched surfaces can help prevent coronavirus infections are the main proposal of WHO experts in current Guidelines, artefacts stored on a web site. Those preventive measures at least can help to everybody, including also the patients who have evidenced CVDs in their histories of illness. Authors analyzed most important dilemmas about all aspects of CVDs, including etipathogenesis, treatment with current drugs and use of potential discovered vaccines against COVID-19 infection, described in scientific papers deposited in PubMed data base.