Volatility spillovers among major tourism stock indices during Covid-19 pandemic

This paper examines the dynamics of volatility spillovers among five major tourism stock indices during the Covid-19 period. Our paper enriches the current literature as it is the first paper to investigate the volatility spillovers among major global tourism stock indices by adopting Diebold and Yilmaz (2012. Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66. ), and Barunik and Krehlik (2018. Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk. Journal of Financial Econometrics, 16(2), 271–296.) time and frequency domain methods. Results suggest that total spillovers of the tourism stock indices rose significantly during the pandemic. Turkey and Italy are net volatility spillover transmitters, and others are net volatility spillover receivers. Findings of this study also indicates that the effect of volatility transmission among tourism stock markets is temporary (short-lasting). The results suggest that short-term investors and portfolio managers should avoid investing in the tourism indices in the short term.

Radiological findings spectrum of asymptomatic coronavirus (COVID-19) patients

BackgroundRadiological examinations of COVID-19 positive patients play a vital role in early diagnosis and assessment of disease course, as most COVID-19 infected patients were diagnosed with pneumonia and characteristic CT imaging patterns. Asymptomatic infected individuals, called "asymptomatic carrier or transmitter”, who are the infectious sources of SARS-CoV-2, and some of them progress rapidly, even resulting in acute respiratory distress syndrome (ARDS) with a high case-fatality rate. Our study is a prospective study and aims to be familiar with the CT imaging features of asymptomatic cases with COVID-19 pneumonia.ResultsA total of 44 asymptomatic cases with COVID-19 pneumonia between March 20, 2020 and May 23, 2020 were enrolled. All patients had a history of exposure to SARS-CoV-2 or recent travel history. All patients had no symptoms. The predominant feature of CT findings in this cross-sectional study was ground-glass opacity (GGO) (41, 93%) with peripheral (34, 77.3%) distribution, bilateral location (20, 45.5%) with lower lobe predominance (left lower lobe 72% and right lower lobe 50%).ConclusionCT imaging of asymptomatic cases with COVID-19 pneumonia has highly characteristics findings. Since asymptomatic patients are the asymptomatic transmitter, and some patients can progress rapidly in the short term, it is essential to early diagnose asymptomatic patients with COVID-19. CT scan has great sensitivity in screening and detecting patients with COVID-19 pneumonia.

Non-contact sensing system based on GaN optoelectronic chip

As the global spread of COVID-19 becomes a rapidly evolving crisis, the development of contactless shared interactive displays is an urgent issue to reduce the risk of viral and bacterial cross contamination due to the use of touch-operated shared user terminals. Here, we experimentally demonstrate a contactless user terminal fabricated with a monolithic GaN Optoelectronic system (MGOS), which integrates the transmitter and receiver into a single chip. The inherent spectral emission-responsiveness overlap of GaN QW diodes gives the device a unique ability to detect light transmitted by diodes that share the same QW structure. When the GaN transmitter emits light to illuminate an external object, the integrated GaN receiver can detect the reflected light encoding the information and convert the optical signal into an electrical signal, so that the non-contact user terminal has the ability to use light for bidirectional data communication. Compared to traditional handwriting systems, these terminals operate as contactless information entry devices that can help reduce potential cross-contamination due to contact with handwriting terminals, provide precautions to keep the environment clean, and help prevent virus transmission. © 2023 IEEE.

Inflation Spillovers among Advanced and Emerging Economies: Evidence from the G20 Group

The influence of recent global shocks such as the COVID-19 pandemic and the Russian–Ukrainian war on the variability of major macroeconomic trends not only shows synchronized behavior across economies but also induces similar policy responses to counter these shocks. The purpose of this article is to explore the transmission of inflation among the G20 economies and evaluate its contribution to domestic inflation. To this end, we use the Diebold and Yilmaz spillover approach. The results that emerge from unconditional analysis reveal stark dissimilarities in inflation spillover patterns between advanced and emerging economies. Advanced economies are subject to higher spillover rates and thereby more exposed to global shocks compared to their emerging counterparts. Inflation in emerging countries is mainly derived from idiosyncratic shocks, while global shocks have only a modest influence on domestic inflation. In addition, bilateral spillovers among the G20 members show that the average pairwise directional spillovers between emerging economies are lower compared to advanced economies. The results pertaining to the spillover dynamics, on the other hand, show that total inflation spillover has a clear upward trend, indicating that the overall interconnectedness between G20 countries is increasing over time. Moreover, the estimates of spillover dynamics show a growing influence of received inflation spillovers from external shocks in both advanced and emerging economies. Policymakers in advanced economies are expected to respond to global shocks to mitigate the influence of spillovers, which is essential for economies that display high spillovers and turn out to be net receivers of shocks. However, public agencies in emerging economies should concentrate more on internal shocks to control inflation while not ignoring global shocks.

Covid-19 Vest for Social distancing and Monitoring

In recent years, due to the rise in the number of novel coronaviruses across the globe nations step forward to stop the crisis. With guidelines of the WHO many methodologies came into existence to prevent the spreading of coronavirus. My SD: A Smart Social distance and Monitoring System takes advantage of the features of the smartphone's hardware which usually has Bluetooth transmitter-receiver, like GPS to determine the safe distance and required level of compliance. Through artificial intelligence, this new smart device helps maintain uniform social distance and detect COVID 19 patients. In these COVID 19 environments, everyone knows how safe they are. In this paper, we have automated the process whereby the layman can control himself without any priming which makes the system more user-friendly for the public. The user himself or herself can monitor body temperature, social distancing and get an alert in abnormal selfisolation conditions using contactless thermometer, ultrasonic sensors, and GSM modules. © 2022 IEEE.

Measuring the frequency and quantile connectedness between policy categories and global oil price

This study explores the connectedness between various categories of economic policy uncertainty (EPU) and global crude oil prices in different frequencies and quantiles using the generalized forecast error variance decomposition and data in the US, China, and Japan from January 2000 to May 2022. The empirical results may be summarized as follows. First, total short and long term connectedness exhibits different patterns and is more sensitive to extreme positive and negative shocks than regular shocks. Second, fiscal policy uncertainty (FPU) and monetary policy uncertainty (MPU) tend to act as net transmitters of shocks, while the roles of trade policy uncertainty (TPU) are mixed in the short term, irrespective of the country. However, under extreme market conditions, no specific-category EPU features a clear net transmitter/recipient. Finally, the results are qualitatively and quantitatively unaffected by the chosen proxy of crude oil prices and are not altered by global real economic activity. © 2023 Elsevier Ltd

Risk Connectedness among International Stock Markets: Fresh Findings from a Network Approach

In this study, we analyze the upside and downside risk connectedness among international stock markets. We characterize the connectedness among international stock returns using the Diebold and Yilmaz spillover index approach and compute the upside and downside value-at-risk. We document that the connectedness level of the downside risk is higher than that of the upside risk and stock markets are more sensitive when the stock market declines. We also find that specific periods (e.g., the global financial crisis, the European debt crisis, and the COVID-19 turmoil) intensified the spillover effects across international stock markets. Our results demonstrate that DE, UK, EU, and US acted as net transmitters of dynamic connectedness;however, Japan, China, India, and Hong Kong acted as net receivers of dynamic connectedness during the sample period. These findings provide significant new information to policymakers and market participants.

Analysis of the dynamic return and volatility connectedness for non-ferrous industrial metals during the COVID-19 pandemic crisis

PurposeThis paper aims to examine the dynamic return and volatility connectedness for six major industrial metals (tin, lead, nickel, zinc, copper and aluminium) and the coronavirus media coverage index (MCI).Design/methodology/approachTo that purpose, this study applies the fresh time-varying parameter vector autoregression methodology (TVP–VAR model) during the sample period between 2 January, 2020, and 16 April, 2021, that is, covering the three waves of the COVID-19 pandemic crisis.FindingsThis study's results show interesting findings. First, dynamic total return and volatility connectedness changes over time, highlighting a significant increase during the third wave of the pandemic. Second, the MCI index is a leading net transmitter in terms of return and volatility at the introduction of the SARS-CoV-2 coronavirus crisis. Third, this study clearly distinguishes two profiles among industrial metals: copper and tin/zinc as net transmitters and lead and aluminium as net receivers. Finally, the most relevant differences between them are concentrated not only at the beginning of the COVID-19 pandemic (first wave) but also during the second and third waves of the coronavirus outbreak.Originality/valueTo the best of the authors' knowledge, this is the first research that explores the dynamic return and volatility connectedness in the industrial metal market, applying the TVP–VAR methodology during the first waves of the COVID-19 pandemic crisis.

SECTORAL CONNECTEDNESS AND RISK SPILLOVERS IN THAILAND'S STOCK MARKET

Investigating the mechanisms of risk transmission within economic sectors is vital for comprehending the interconnectedness among industries. This study aims to examine the channels of risk propagation by analyzing volatility spillovers within eleven sectors of Thailand's stock market from January 2012 to December 2021. The sectoral volatility is estimated using the ARMA-GARCH technique. The paper utilizes the connectedness measures developed by Diebold and Yilmaz (2009, 2012, 2014) to examine changes in sectoral connectedness and identify significant trends in specific sectors before and during the COVID-19 pandemic. The result is that total volatility connectedness has increased significantly during the COVID-19 pandemic, indicating a significant rise in systematic risk. The Petrochemical and Chemical sector became the largest transmitter during the COVID-19 pandemic. These two findings are consistent with several studies on sectoral connectedness during the COVID-19 situation. In addition, some certain sectors shifted their role from a net transmitter to a net receiver and vice versa. Investors should be aware of the impact of an increase in systematic risk and the switching roles of net transmitters and net receivers when selecting hedging strategies. The Banking sector and the Finance and Security sector did not transmit much volatility to the market. They were net receivers for both the pre-COVID and the COVID periods. The Finance and Security sector was the largest receiver of volatility shocks during the pandemic. This raised concerns about the future stability of Thailand's financial sector. Overall, the results of this study contribute to an understanding of the changes in sectoral connectedness and risk spillovers in Thailand's stock exchange as a result of the COVID-19 situation.

Could volatile cryptocurrency stimulate systemic risks in the energy sector? Evidence from novel connectedness models

By identifying the connectedness of seven indicators from January 1, 2019, to June 13, 2022, we choose an extended joint connectedness approach to a vector autoregression model with time-varying parameter (TVP-VAR) to analyze interlinkages between Crypto Volatility (CV) and Energy Volatility (EV). Our findings show that the COVID-19 outbreak seems to have an impact on the dynamic connectedness of the whole system, which peaks at about 60% toward the end of 2019. According to net total directional connectedness over a quantile, throughout the 2020–2022 timeframe, natural gas and crude oil are net shock transmitters, while the CV, clean energy, solar energy, and green bonds consistently receive all other indicators. Specifically, pairwise connectedness indicates that the CV appears to be a net transmitter of shocks to all energy indicators before the COVID-19 outbreak but acts as a net receiver of shocks from clean energy, wind energy, and green bonds in late 2020. The CV mostly has spillover effects on green bonds. The primary net transmitter of shocks to the Crypto market is crude oil. Our findings are critical in helping investors and authorities design the most effective policies to lessen the vulnerabilities of these indicators and reduce the spread of risk or uncertainty. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Quantile time-frequency connectedness between cryptocurrency volatility and renewable energy volatility during the COVID-19 pandemic and Ukraine-Russia conflicts

Our article employs a quantile vector autoregression (QVAR) to identify the connectedness of seven variables from April 1, 2019, to June 13, 2022, in order to examine the relationships between crypto volatility and energy volatility. Our findings reveal that the dynamic connectedness is approximately 25% in the short term and approximately 9% in the long term. The 50% quantile equates to the overall average connectedness of the entire period, according to dynamic net total directional connectedness over a quantile, which also indicates that connectedness is very intense for both highly positive changes (above the 80% quantile) and crypto and energy volatility (below the 20% quantile). With the exception of the early 2022 period when the Crypto Volatility Index transmits a net of shocks because of the Ukraine-Russia Conflict, dynamic net total directional connectedness implies that in the short term, the Crypto Volatility Index acts as a net shock receiver across time. While this indicator is a net shock receiver for long-term dynamics, wind energy is a net shock transmitter during the short term. Green bonds are a short-term net shock receiver. This role is valid in the long term. Clean energy and solar energy are the long-term net transmitters of shocks;nevertheless, the series is always and only momentarily a net receiver of shocks because of the short-term dynamics. Natural gas and crude oil play roles in both two quantiles. Dynamic net pairwise directional connectedness over a quantile suggests that uncertain events like the COVID-19 epidemic or Ukraine-Russia Conflict influence cryptocurrency volatility and renewable energy volatility. © 2022 Elsevier Ltd

Impacts of COVID-19 on dynamic return and volatility spillovers between rare earth metals and renewable energy stock markets

We examine the time-frequency co-movements and return and volatility spillovers between the rare earths and six major renewable energy stocks. We employ the wavelet analysis and the spillover index methodology from January 1, 2018 to May 15, 2020. We report that the COVID-19-triggered significant increase in co-movements and spillovers in returns and volatility between the rare earths and renewable energy returns and volatility. The rare earths act as net recipient of both return and volatility spillovers, while the clean energy stocks are net transmitters of return and volatility spillovers before and during the COVID-19 crisis. The solar and wind stocks are net transmitters/receivers of spillovers before/during the pandemic. The remaining markets shift from net spillover receivers to transmitters or vice versa;evidencing the effects of the pandemic. Our results show that cross-market hedge strategies may have their efficiency impaired during the periods of crises implying a necessity of portfolio rebalancing. © 2022 The Authors

Industrial instrumentation practices in engineering programs using virtual environments. Case Study: Transmitter-Controller Current Loop

Learning in times of pandemic represented a challenge for teachers and students, due to the difficulties generated by social distancing. During the Covid-19 pandemic, learning processes in educational institutions used multiple computer and electronic media. As for engineering programs, laboratory practices were discarded in many cases. This work develops a computer application with non-immersive virtual reality, applying a physical/actual laboratory guide in a virtual environment, in which a current loop for an Endress+Hausser PMD75 differential pressure transmitter had to be configured. This application was developed by students and the tutor of the AR/VR research incubator in conjunction with the teacher of the Industrial Instrumentation course, who acted as a client. The Unity3D game engine was used to simulate a tank, a cabinet and industrial instrumentation to measure the pressure at the bottom of the tank. Student were allowed to carry out the wiring of the different instruments inside the cabinet, and the configuration of the transmitter via a hand-terminal;In addition, the application includes a record of student events and interactions for future analysis. The perception of the application was evaluated through a survey applied to 43 students. The results showed that this tool, although it is a valuable support during virtual courses, and provides a first approach to real practice, the student requires interaction with real instruments. Therefore, the tool becomes a valuable complement prior to practices in a real laboratory. © 2022 IEEE.

Global Remittances and COVID-19: Locked Down but Not Locked Out

What happens to remittances, an important feature of the global financial system, when a pandemic strikes? Despite early predictions of significant drops in volumes, flows have been affected less than expected. This commentary explains that this outcome is attributable in part to a renewed focus on the infrastructure of global finance and an accelerated development and use of digital solutions, but that it is mostly a result of the individual efforts and resilience of migrants.

On Mutual Information Analysis of Infectious Disease Transmission via Particle Propagation

Besides mimicking bio-chemical and multi-scale communication mechanisms, molecular communication forms a theoretical framework for virus infection processes. Towards this goal, aerosol and droplet transmission has recently been modeled as a multiuser scenario. In this letter, the "infection performance" is evaluated by means of a mutual information analysis, and by an even simpler probabilistic performance measure which is closely related to absorbed viruses. The so-called infection rate depends on the distribution of the channel input events as well as on the transition probabilities between channel input and output events. The infection rate is investigated analytically for five basic discrete memoryless channel models. Numerical results for the transition probabilities are obtained by Monte Carlo simulations for pathogen-laden particle transmission in four typical indoor environments: two-person office, corridor, classroom, and bus. Particle transfer contributed significantly to infectious diseases like SARS-CoV-2 and influenza.

CLIMATE FINANCE IN THE WAKE OF COVID-19: CONNECTEDNESS OF CLEAN ENERGY WITH CONVENTIONAL ENERGY AND REGIONAL STOCK MARKETS

Focusing on raising climate concerns and sustaining a clean ecosystem, the current study strives to examine the connectedness of clean energy markets with conventional energy markets and four regional stock markets of Asia, Pacific, Europe, and America for the period spanning January 1, 2004 to August 31, 2021. We employed the volatility connectedness methodology using dynamic conditional correlation (DCC-GARCH) estimates for analysis purposes. There is pronounced within class connectedness of all markets except conventional energy markets, which showed strong disconnection from the network. However, strong inter-class spillovers are reported between clean energy and regional stock markets. Time-varying analysis revealed that intense spillovers are shaped during the Global Financial Crisis, Shale Oil Crisis, and COVID-19 pandemic. Meanwhile, time-varying net connectedness estimates illuminate that world renewable energy and American stock markets are net transmitters, whereas leftover markets are net recipients of spillovers. Further analysis of sub-sample periods during GFC, SOR, and COVID-19 validate that intense spillovers are formed when markets experience unexpected financial, economic, and global health turmoil. We proposed significant implications for regional stock markets of Asia, Pacific, Europe and America to concentrate on the climate-friendly energy markets than conventional energy markets as they service the clean ecosystem motives more specifically.

Evaluation Index of Basketball Teaching Environment Based on the Wireless Communication Network and Genetic Algorithm

With the advent of the new era, all fields in China are full of vitality. In particular with the vigorous development of network science and technology, many fields are going through a huge change or in the near future. As an important part of the development goal of China’s “sports power,” physical education is also undergoing changes. With the successful conclusion of the Winter Olympics in China, this grand event has added an important stroke to the development of sports in China. In the process of physical education and teaching, the environment of physical education is extremely important. Compared with nonphysical education subjects, it has the characteristics of direct contact between teachers and students and the time of the course teaching process. This paper studies the evaluation index of basketball teaching environment. As a part of physical education environment, it has the general characteristics of physical education environment, but it has its own characteristics. People in the environment are constantly experiencing the influence of the environment on their own individual. Therefore, the research on the evaluation indicators of the basketball teaching environment will play an important role for the students involved. For the research of the mentioned basketball teaching environment evaluation index, this paper proposes the application of genetic algorithm and wireless network technology;the purpose is to make a more scientific and comprehensive target evaluation system for the basketball environment evaluation index. In the simulation experiment of the teaching environment evaluation index, this paper selected a total of 164 people of different grades. The final result showed that 85.16% of the students gave positive comments to this evaluation system. This result confirms the research of this paper.

Impacts of COVID-19 on the Return and Volatility Nexus among Cryptocurrency Market

The impacts of COVID-19 have spread rapidly to global financial markets. In this context, combining the spillover index method introduced by Diebold and Yilmaz (2012) and the complex network analysis framework, we examined the volatility connectedness and the topological structure among the top ten cryptocurrencies before and during the COVID-19 crisis. The results revealed that the total volatility connectedness of the cryptocurrency market markedly increased following the outbreak of COVID-19;statically, Bitcoin, Ethereum, Cardano, and Bitcoin Cash were the net transmitters before COVID-19, while Bitcoin, Ethereum, Ripple, Litecoin, Cardano, and Stellar became the major net transmitters in the market after COVID-19. Dynamically, the dynamic performance of different cryptocurrencies during the COVID-19 pandemic was heterogeneous, and the possible driving factors are diverse. Moreover, from network analysis, we further found that the COVID-19 crisis has significantly changed the topological structure of the cryptocurrency market. Our findings may help understand the typical dynamics in the cryptocurrency market and provide significant implications for portfolio managers, investors, and government agencies in times of highly stressful events like the COVID-19 crisis.

Monitoring and Control of COVID Vaccine Storage Temperature Using IoT and Machine Learning

Corona virus (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. Till now, vaccination is the most effective way of fighting this pandemic of COVID-19. This paper proposes a system which will monitor and control the temperature of the vaccine storage rooms. Here an Internet of things and Machine Learning system has been developed which will measure the real time temperature of the room and will control the temperature automatically. It will try to keep the temperature in the given region, it will predict the temperature of next twenty minutes with the help of Machine learning algorithm-linear regression, it will watch for an anomaly using Z-score analysis, it will also watch if the temperature crosses upper or lower threshold. If any of the above abnormality is detected, we will get notified online through a message, the system will maintain the temperature and the workers will also get alarmed by a led and a buzzer which will work different for each significant case. © 2022 IEEE. All rights reserved

Covid-19 Prevention Kit Based on an Infrared Touchless Thermometer and Distance Detector

Temperature is estimated by detecting the infrared radiation emitted by all materials above absolute zero (0°Kelvin) in an infrared temperature test. IR energy is converted to an electrical signal that may be displayed as a temperature reading after being made up for the surrounding temperature range by using a focal point to focus the IR energy on a finder. With this set-up, you can estimate something's temperature from a distance, without having to go close to the thing you're trying to measure. Because thermocouples or other test type sensors cannot be used or do not provide precise information for a variety of reasons, the infrared temperature sensor is useful for estimating temperature. One of the most essential things to do to avoid COVID is to practise social distancing. This device may be used to maintain a gap of at least 6 feet between devices by measuring distance using ultra-wideband (UWB) technology. There are two nodes in an ultrasonic sensor: a transmitter and a receiver. When the transmitter fires, an ultrasonic wave is thrown out, and this wave hits everything in its path before returning to the transmitter. Using the time it takes for the wave to return to the sensor after being bounced, the sensor determines the obstacle's distance from that sensor. In most cases, ultrasonic sensors are used to detect obstacles in the way and to determine how far away they are from the sensor. © 2021 IEEE.