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The energy sector is one of the most important in the world, so that time series fluctuations in leading energy sources have been analysed widely. As the leading energy commodities are traded on international stock exchanges, the analysis of the fluctuations in stock and financial derivatives prices and returns have also been investigated extensively in recent years. Much of the empirical analysis has concentrated on using daily, weekly or monthly data, with little research based on intra-day data. The paper analyses the relationships among the S&P 500 Index and futures prices, returns and volatility of three leading energy commodities, namely crude oil, natural gas and ethanol, using intra-day data. The detailed analysis of intra-day temporal aggregation in examining returns relationships and volatility spillovers across the equity and energy futures markets, and the effects of overnight returns, volume, realized volatility, asymmetry, and spillovers across the four financial markets, leads to interesting and useful results for decision making and hedging strategies. The empirical results relating to alternative models of mean and variance feedback and asymmetry for intra-daily returns, asymmetry and volatility spillovers, and dynamic conditional correlations and covariances, show that the relationships between the stock market and alternative energy financial derivatives, specifically futures prices and returns, can and do vary according to the trading range, whether daily or overnight effects are considered, and the temporal aggregation and time frequencies that are used.

This paper attempts to find the factors that affect the number of cases and deaths of coronavirus disease 2019 (COVID-19) patients a year after the first outbreak in Wuhan, China. There were 141 countries affected with COVID-19 involved in the study. Countries were grouped based on population. Using ordinary least squares regression, it was found that the total number of cases and deaths were significantly related with the levels of population of the different countries. On the overall, median age of the country, and average temperature are positively related with the number of deaths from the virus. On the other hand, population density is positively related with the deaths due to COVID for low populated countries. The result of this preliminary study can be used as a benchmark for authorities in the formulation of policies with regards to treating COVID-19 related issues.

The paper presents a two-period Walrasian financial market model composed of informed and uninformed rational investors, and noise traders. The rational investors maximize second period consumption utility from the payoffs of trading risk-free holdings to risky assets in the first period. The central bank reacts directly to asset price movements by selling or buying assets to stabilize the market price. It is found that the intervention makes the risky asset’s market price per share less sensitive to information shocks, which presses the market price towards its average price thus reducing price variance. The informed investors’ prediction coefficient remains unaffected, but that of the uninformed investors is magnified, which cancels out the negative effect on shock sensitivity thus keeping the expected value of the risky asset’s dividend constant. Finally, the introduction of the policy rule does not affect rational investors’ risk per share. A general conclusion is that the central bank’s policy can be regarded as an effective automatic stabilizer of financial markets.

The paper examines whether the Moving Average (MA) technique can outperform random market timing in the energy sector, compiled of fossil and renewable energy producers. According to the Capital Asset Pricing Model, random timing is a superior trading strategy in the long run. However, the MA technique may be more successful, if there are predictable stochastic trends in the price series. In the paper, eight representative firms are selected for both fossil and renewable portfolios with actually tradable stocks in order to create two Exchange-Traded Funds (ETF). The paper finds that MA timing outperforms random timing for the ETF of renewable energy companies, but not for the ETF of fossil energy companies.

This paper presents new evidence linking community characteristics and generalized trust, based on the most up to date national-level data from the Quality of Life Under the Sufficiency Economy Survey 2018 conducted by the National Statistical Office of Thailand. We measure generalized trust using the expectation approach based on the difference hypothesis situation questions, including whether a lost wallet or other possessions are likely to be returned, and whether items will be stolen if people leave their house's door unlocked. Our results suggest that the level of trust depends on how close people in communities feel towards each other and whether a member of family takes part in civic engagement. Also, we find that participation in knowledge sharing ideas activity such as community meetings or any type of sharing ideas activity can positively impact trust.

The SARS-CoV-2 virus that causes the COVID-19 disease is now fully entrenched in the international community, and has devastated society in what might seem to be a parallel universe. The long-term medical, physical, psychological, economic and financial consequences for continents, countries, regions, states, provinces, prefectures, cities, and individuals is not yet known, but the short-term effects do not seem promising or encouraging. One of the most heavily affected industries by COVID-19 is the international travel, tourism demand and hospitality industry, which was one of the world’s largest sources of full-time and casual employment in the pre-COVID-19 era. The future of tourism in the COVID-19 era is presently unknown, but substantial research is required to evaluate how the industry might recover and survive in a new-normal COVID-19 world. The paper presents a discussion of the future of tourism, travel, and hospitality in the time of COVID-19 as a contribution to the industry. The paper presents a discussion of the future of tourism, travel, and hospitality industry. Public and private policy considerations include significant contingent planning to accommodate travel plans and restrictions, personal protection equipment, medical and healthcare requirements, major events, short, medium and long haul domestic and international travel by air and sea, public versus private transportation, hotel accommodation, alternative forms of payment and pre-payment, changes in the tourism and transport industries, changes in tourist behaviour, and potential structural changes.

This Editorial evaluates 14 invaluable and interesting articles in the Special Issue “Applied Econometrics” for the Journal of Risk and Financial Management (JRFM). The topics covered include recovering historical inflation data from postage stamps prices, FHA loans in foreclosure proceedings through distinguishing sources of interdependence in competing risks, information in earnings forecasts, nonlinear time series modeling, a systemic approach to management control through determining factors, economic freedom and FDI versus economic growth, efficient cash use of the Taiwan dollar, financial health prediction in companies from post-Communist countries, influence of misery index on U.S. Presidential political elections, multivariate student versus Gaussian regression models in finance, financial derivatives markets and economic development, income inequality and economic growth in middle-income countries, abnormal returns, mis-measured risk, network effects, and risk spillovers in stock returns.

It is generally accepted in the scientific community that carbon dioxide (CO2) emissions, which lead to global warming, arise from using fossil fuels, namely coal, oil and gas, as energy sources. Consequently, alleviating the effects of global warming and climate change necessitates substantial reductions in the use of fossil fuel energy. This paper uses a financial market-based approach to investigate whether positive stock returns cause changes in CO2 emissions, or vice-versa, based on the Granger causality test to determine cause and effect, or leader and follower. If Granger causality can be determined in any direction, this will enable a clear directional statement regarding temporal predictability between stock returns and CO2 emissions. The empirical data include annual CO2 emissions from fuel combustion of the three main fossil energy sources, namely coal, oil and gas, based on 18 countries with sophisticated financial markets that are in the Morgan Stanley Capital International (MSCI) World Index from 1971 to 2017. The empirical results show clearly that all the statistically significant causality findings are unidirectional from the stock market returns to CO2 emissions from coal, oil and gas, but not the reverse. More importantly, the regression results suggest that when stock returns rise by 1%, CO2 emissions from coal combustion decrease by 9% among the countries that are included in MSCI World Index. Furthermore, when stock returns rise 1%, CO2 emissions from oil combustion increase by 2%, but stock returns have no significant effect on CO2 emissions from gas combustion.

This Special Issue publishes high quality papers on contemporary issues in business and economics in Vietnam and other Asian emerging markets. These papers were accepted and presented at the 2019 Vietnam’s Business and Economics Research Conference (VBER2019) organized by Ho Chi Minh City Open University, Vietnam in July 2019. Emerging issues in business and economics from Vietnam and other emerging markets in the Asian region have been addressed from various angles, from economics, finance, and statistics to management science. Five out of the 14 studies in this book were conducted to investigate various issues in relation to the Asian region such as the exchange rate regime in Asia, financial inclusion, and financial development and income inequality in Asian emerging markets. Seven studies were conducted in response to emerging business and economic issues in Vietnam such as fiscal decentralization, urbanization, foreign direct investment, and corporate financial distress. Other papers even considered various relevant aspects from the United States and Europe to the Asian region including double taxation treaties and agricultural shocks to the oil price. The findings from these papers are useful for practitioners, policymakers, and academics.

The SARS-CoV-2 virus that causes the COVID-19 disease is highly infectious and contagious. The long-term consequences for individuals are as yet unknown, while the long-term effects on the international community will be dramatic. COVID-19 has changed the world forever in every imaginable respect and has impacted heavily on the international travel, tourism demand, and hospitality industry, which is one of the world’s largest employers and is highly sensitive to significant shocks like the COVID-19 pandemic. It is essential to investigate how the industry will recover after COVID-19 and how the industry can be made sustainable in a dramatically changed world. This paper presents a charter for tourism, travel, and hospitality after COVID-19 as a contribution to the industry.

Given the volume of research and discussion on the health, medical, economic, financial, political, and travel advisory aspects of the SARS-CoV-2 virus that causes the COVID-19 disease, it is essential to enquire if an outbreak of the epidemic might have been anticipated, given the well-documented history of SARS and MERS, among other infectious diseases. If various issues directly related to health security risks could have been predicted accurately, public health and medical contingency plans might have been prepared and activated in advance of an epidemic such as COVID-19. This paper evaluates an important source of health security, the Global Health Security Index (2019), which provided data before the discovery of COVID-19 in December 2019. Therefore, it is possible to evaluate how countries might have been prepared for a global epidemic, or pandemic, and acted accordingly in an effective and timely manner. The GHS index numerical scores are calculated as the arithmetic (AM), geometric (GM), and harmonic (HM) means of six categories, where AM uses equal weights for each category. The GHS Index scores are regressed on the numerical score rankings of the six categories to check if the use of equal weights of 0.167 in the calculation of the GHS Index using AM is justified, with GM and HM providing a check of the robustness of the arithmetic mean. The highest weights are determined to be around 0.244&ndash, 0.246, while the lowest weights are around 0.186&ndash, 0.187 for AM. The ordinal GHS Index is regressed on the ordinal rankings of the six categories to check for the optimal weights in the calculation of the ordinal Global Health Security (GHS) Index, where the highest weight is 0.368, while the lowest is 0.142, so the estimated results are wider apart than for the numerical score rankings. Overall, Rapid Response and Detection and Reporting have the largest impacts on the GHS Index score, whereas Risk Environment and Prevention have the smallest effects. The quantitative and qualitative results are different when GM and HM are used.

This book is a collection of high-impact papers accepted and presented at the 2019 Vietnam's Business and Economics Research Conference (VBER2019) organised by Ho Chi Minh City Open University held on 18th-20th July 2019. The Special Issue is associated with a broad coverage of the contemporary issues in Business and Economics in Vietnam and other emerging markets reflecting a key theme of VBER2019: Vietnam's Place in the Asia Pacific Region. A total of 14 papers were published from more than the 120 submissions to the VBER2019 Conference. Published papers had been undergone a rigorous reviewing process conducted by the Journal of Risk and Financial Management. The papers incorporated in this book address contemporary issues in business and economics from Vietnam and other emerging markets in the Asian region from various angles such as economics, finance, and statistics to management science.

The SARS-CoV-2 coronavirus that causes the COVID-19 disease led to the most significant change in the world order over the past century, destabilizing the global economy and financial stock markets, the world’s economy, social development, business, risk, financial management and financial markets, among others. COVID-19 has generated great uncertainty, and dramatically affected tourism, travel, hospitality, supply chains, consumption, production, operations, valuations, security, financial stress and the prices of all products, including fossil fuel and renewable energy sources. This Editorial introduces a Special Issue of the Journal of Risk and Financial Management (JRFM) on the “Risk and Financial Management of COVID-19 in Business, Economics and Finance”. This Special Issue will attract practical, state-of-the-art applications of mathematics, probability and statistical techniques on the topic, including empirical applications. This paper investigates important issues that have been discussed in tourism, global health security and risk management in business as well as the social and medical sciences.

This Special Issue publishes high quality papers on contemporary issues in business and economics in Vietnam and other Asian emerging markets. These papers were accepted and presented at the 2019 Vietnam’s Business and Economics Research Conference (VBER2019) organized by Ho Chi Minh City Open University, Vietnam in July 2019. Emerging issues in business and economics from Vietnam and other emerging markets in the Asian region have been addressed from various angles, from economics, finance, and statistics to management science. Five out of the 14 studies in this book were conducted to investigate various issues in relation to the Asian region such as the exchange rate regime in Asia, financial inclusion, and financial development and income inequality in Asian emerging markets. Seven studies were conducted in response to emerging business and economic issues in Vietnam such as fiscal decentralization, urbanization, foreign direct investment, and corporate financial distress. Other papers even considered various relevant aspects from the United States and Europe to the Asian region including double taxation treaties and agricultural shocks to the oil price. The findings from these papers are useful for practitioners, policymakers, and academics.

The paper explores the trade competitiveness of seven major shrimp-exporting countries, namely Vietnam, China, Thailand, Ecuador, India, Indonesia and Mexico, to the United States. Specifically, we investigate whether the US antidumping petitions have an impact on the bilateral revealed comparative advantage (RCA) indexes for each of the seven shrimp-exporting countries with the United States. Monthly data from January 2003 to December 2014 and a panel data model are used to examine the determinants of the RCA for the shrimp-exporting countries. The empirical results show the shrimp-exporting countries have superior competitiveness against the shrimp market in the United States. Moreover, the RCA indexes are significantly negatively influenced by shrimp prices, and are positively affected by US income per capita. However, the EMS (Early Mortality Syndrome) shrimp disease, domestic US shrimp quantity, exchange rates and US antidumping laws are found to have no significant impacts on the RCA indexes. In terms of policy implications, the United States should try to reduce production costs of shrimp in the US market instead of imposing antidumping petitions. Moreover, the shrimp-exporting countries should try to maintain their comparative advantage and diversify into new markets.

There is substantial empirical evidence that energy and financial markets are closely connected. As one of the most widely-used energy resources worldwide, natural gas has a large daily trading volume. In order to hedge the risk of natural gas spot markets, a large number of hedging strategies can be used, especially with the rapid development of natural gas derivatives markets. These hedging instruments include natural gas futures and options, as well as Exchange Traded Fund (ETF) prices that are related to natural gas stock prices. The volatility spillover effect is the delayed effect of a returns shock in one physical, biological or financial asset on the subsequent volatility or co-volatility of another physical, biological or financial asset. Investigating volatility spillovers within and across energy and financial markets is a crucial aspect of constructing optimal dynamic hedging strategies. The paper tests and calculates spillover effects among natural gas spot, futures and ETF markets using the multivariate conditional volatility diagonal BEKK model. The data used include natural gas spot and futures returns data from two major international natural gas derivatives markets, namely NYMEX (USA) and ICE (UK), as well as ETF data of natural gas companies from the stock markets in the USA and UK. The empirical results show that there are significant spillover effects in natural gas spot, futures and ETF markets for both USA and UK. Such a result suggests that both natural gas futures and ETF products within and beyond the country might be considered when constructing optimal dynamic hedging strategies for natural gas spot prices.

The recent and rapidly growing interest in biofuel as a green energy source has raised concerns about its impact on the prices, returns and volatility of related agricultural commodities. Analyzing the spillover effects on agricultural commodities and biofuel helps commodity suppliers hedge their portfolios, and manage the risk and co-risk of their biofuel and agricultural commodities. There have been many papers concerned with analyzing crude oil and agricultural commodities separately. The purpose of this paper is to examine the volatility spillovers for spot and futures returns on bio-ethanol and related agricultural commodities, specifically corn and sugarcane. The diagonal BEKK model is used as it is the only multivariate conditional volatility model with well-established regularity conditions and known asymptotic properties. The daily data used are from 31 October 2005 to 14 January 2015. The empirical results show that, in 2 of 6 cases for the spot market, there were significant negative co-volatility spillover effects: specifically, corn on subsequent sugarcane co-volatility with corn, and sugarcane on subsequent corn co-volatility with sugarcane. In the other 4 cases, there are no significant co-volatility spillover effects. There are significant positive co-volatility spillover effects in all 6 cases, namely between corn and sugarcane, corn and ethanol, and sugarcane and ethanol, and vice-versa, for each of the three pairs of commodities. It is clear that the futures prices of bio-ethanol and the two agricultural commodities, corn and sugarcane, have stronger co-volatility spillovers than their spot price counterparts. These empirical results suggest that the bio-ethanol and agricultural commodities should be considered as viable futures products in financial portfolios for risk management.

Mesophase pitch fabricated through polymerization of polycyclic aromatic hydrocarbons (PAHs) is highly aromatic and of high quality, and it can be used as a raw material to produce other carbon-based materials. Hydrofluoride/boron trifluoride (HF/BF3) is currently an efficient reagent to catalyze the PAH polymerization to produce mesophase pitch. In this study, density functional theory (DFT) calculations are performed to propose a mechanism for naphthalene catalytic polymerization using HF/BF3. The overall reaction mechanism can be conceptualized as having two stages: activation, followed by polymerization. During activation, HF/BF3 acts a proton donor to activate naphthalene, whose then-protonated form can promote the formation of a C–C bond with another naphthalene molecule via electrophilic addition. We also propose a catalyst recovery pathway, which can stabilize the intermediate products. In the polymerization stage, two types of pathways are proposed, those of chain elongation and intramolecular cyclization. According to the proposed catalytic mechanism in this study, the predicted mesophase product shows highly aliphatic hydrogens, which is consistent with the experimental results. We propose the full catalytic mechanism using DFT calculations. Our results provide a better understanding of how to develop novel and green catalysts, which can replace the HF/BF3 reagent in future applications.

Professor Michael John McAleer passed away on 8 July 2021, at the age of 68 [...]

The number of homebound and bedridden elderly has been increasing in Thailand, as the aging population rapidly grows and rates of chronic diseases increase. However, decreasing family size may reflect a decline in the ability of families to provide care. Society, as a result, enhances the need for long-term care (LTC) policy to provide home care and social support for the homebound and bedridden elderly. This paper examines how care-receipt satisfaction in LTC impacts the homebound and bedridden elderly's overall happiness, using a two-year panel of 279 individuals from the Thai Health Promotion Foundation dataset. We use the pooled two-stage least square (Pooled-2SLS) model and random effect two-stage least square (RE-2SLS) model to control the endogeneity problem. The empirical results show that care-receipt satisfaction on LTC service can generate a positive impact on the overall happiness of the homebound and bedridden elderly.

Objective Although major advances have greatly improved the outcomes of assisted reproductive technology in the last two cascades, there remains significant difficulty in achieving pregnancy for many patients even after repeated attempts of IVF. Interestingly, recent studies have shown that transcutaneous electrical acupoint stimulation (TEAS) can improve the reproductive outcomes of select IVF patients. To determine the utility of TEAS in improving IVF outcomes in patients with a history of implantation failure, we conducted a retrospective study of clinical outcomes of women, who had a prior history of unsuccessful pregnancy outcome after IVF-embryo transfer (IVF-ET), following TEAS treatment. Materials and methods A total of 25 patients, who had failed to conceive after multiple IVF cycles in which good embryos were transferred, received noninvasive low frequency TEAS treatment prior to and during an IVF-ET cycle. The clinical outcomes, including biochemical pregnancy rate, clinical pregnancy rate and implantation rate, were compared to those of prior cycles which received only standard IVF treatment. Results Analysis of reproductive outcomes showed that implantation rate and clinical pregnancy rate increased significantly in IVF cycles that included the TEAS treatment when compared to prior cycles that received only the standard IVF treatment in this cohort of patients. Conclusions This surprising finding indicated that TEAS treatment is a promising technique to improve reproductive outcomes in difficult cases of IVF-ET. Because TEAS treatment is noninvasive and has high reproducibility, and can be applied with limited training, further refinement of this procedure would not only substantiate the beneficial effects of TEAS, but also allow the technique to be more effective and reproducible.

The paper develops a novel realized stochastic volatility model of asset returns and realized volatility that incorporates general asymmetry and long memory (hereafter the RSV-GALM model). The contribution of the paper ties in with Robert Basmann’s seminal work in terms of the estimation of highly non-linear model specifications (Basmann, 1988), especially for specifying causal effects from returns to future volatility. This paper discusses asymptotic results of a Whittle likelihood estimator for the RSV-GALM model and a test for general asymmetry, and analyzes the finite sample properties. The paper also develops an approach to obtain volatility estimates and out-of-sample forecasts. Using high frequency data for three US financial assets, the new model is estimated and evaluated. The paper compares the forecasting performance of the new model with a realized conditional volatility model.

Objective Accurate and efficient pre-implantation genetic diagnosis (PGD) based on the analysis of single or oligo-cells is needed for timely identification of embryos that are affected by deleterious genetic traits in in vitro fertilization (IVF) clinics. Polymerase chain reaction (PCR) is the backbone of modern genetic diagnoses, and a spectrum of PCR-based techniques have been used to detect various thalassemia mutations in prenatal diagnosis (PND) and PGD. Among thalassemias, SEA-type α-thalassemia is the most common variety found in Asia, and can lead to Bart's hydrops fetalis and serious maternal complications. Materials and methods To formulate an efficient digital PCR for clinical diagnosis of SEA-type α-thalassemia in cultured embryos, we conducted a pilot study to detect the α-globin and SEA-type deletion alleles in blastomere biopsies with a highly sensitive microfluidics-based digital PCR method. Genomic DNA from embryo biopsy samples were extracted, and crude DNA extracts were first amplified by a conventional PCR procedure followed by a nested PCR reaction with primers and probes that are designed for digital PCR amplification. Results Analysis of microfluidics-based PCR reactions showed that robust signals for normal α-globin and SEA-type deletion alleles, together with an internal control gene, can be routinely generated using crude embryo biopsies after a 10 6 -fold dilution of primary PCR products. Conclusion The SEA-type deletion in cultured embryos can be sensitively diagnosed with the digital PCR procedure in clinics. The adoption of this robust PGD method could prevent the implantation of IVF embryos that are destined to develop Bart's hydrops fetalis in a timely manner. The results also help inform future development of a standard digital PCR procedure for cost-effective PGD of α-thalassemia in a standard IVF clinic.

The paper examines the demand for narcotic drugs, based on Becker (1968), as purported rational behavior of human beings. The results from sampling surveys in eight provinces in Thailand in 2014, representing nationwide drug users/addicts, show that the demand for narcotics (amphetamines, ice drug, and marijuana) are price inelastic (between -0.533 and -0.701), as well as normal goods. The key econometric coefficients in models A and B are 0.192 and 0.0467, respectively, and an increase in income will lead to an increase in the demand for narcotics. In addition, factors affecting the demand for narcotics are the age and age squared of the user, friendship, family member relationship, social relationship, reasons for drug use, risk behavior, and expected punishment. Public policy implications are also proposed and analysed.

textabstractThe paper presents an overview of recent topical research on global, energy, health & medical, and tourism economics, and global software. We have interpreted "global" in the title of the Journal of Reviews on Global Economics to cover contributions that have a global impact on economics, thereby making it "global economics". In this sense, the paper is concerned with papers on global, energy, health & medical, and tourism economics, as well as global software algorithms that have global economic impacts. The topics covered include re-opening the Silk Road to transform Chinese trade, education and skill mismatches, code of practice and indicators for quality management of official statistics, projections of energy use and carbon emissions, multi-fuel allocation for power generation using genetic algorithms, optimal active energy loss with feeder routing and renewable energy for smart grid distribution, demand for narcotics with policy implications, computer technology to improve medical information, heritage tourism, ecotourism impacts on the economy, society and environment, taxi drivers' cross-cultural communication problems and challenges, hybrid knowledge discovery system based on items and tags, game development platform to improve advanced programming skills, quadratic approximation of the newsvendor problem with imperfect quality, classification of workflow management systems for emails, academic search engine for personalized rankings, creative and learning processes using game-based activities, personal software process with automatic requirements traceability to support start-ups, and comparing statistical and data mining techniques for enrichment ontology with instances.

Alzheimer’s disease (AD) is one of the most prevalent severe neurological disorders afflicting our aged population. The study was to determine neuroprotective effects of the Terminalia chebula extracts and ellagic acid by using beta-amyloid25-35 (Ab25-35)-induced cell cytotoxicity in undifferentiated rat pheochromocytoma (PC12) cellular model. The methanolic and water extracts of T. chebula and ellagic acid exhibited the strongest neuroprotective activity against Ab25-35-induced undifferentiated PC12 cell deaths at 0.5–5.0 ug/ml. The ellagic acid also exhibited the partial neuroprotective activity against H2O2-induced undifferentiated PC12 cell deaths at 0.5–5.0 ug/ml. The methanolic and water extracts of T. chebula and ellagic acid protected undifferentiated PC12 cells from the damaging effects of Ab25-35 in several ways: (1) by securing cell viability; (2) by suppressing reactive oxygen species production; and (3) by eliminating calcium ion influx. The T. chebula extracts maybe represent a promising plant-source for medicine in the application of the treatment of AD. Further investigation of the ellagic acid is necessary to verify the neuroprotective efficacy and mechanisms in vivo.

Climate change and global warming are significantly affected by carbon emissions that arise from the burning of fossil fuels, specifically coal, oil, and gas. Accurate prices are essential for the purposes of measuring, capturing, storing, and trading in carbon emissions at regional, national, and international levels, especially as carbon emissions can be taxed appropriately when the price is known and widely accepted. This paper uses a novel Capital (K), Labor (L), Energy (E) and Materials (M) (or KLEM) production function approach to calculate the latent carbon emission prices, where carbon emission is the output and capital (K), labor (L), energy (E) (or electricity), and materials (M) are the inputs for the production process. The variables K, L, and M are essentially fixed on a daily or monthly basis, whereas E can be changed more frequently, such as daily or monthly, so that changes in carbon emissions depend on changes in E. If prices are assumed to depend on the average cost pricing, the prices of carbon emissions and energy may be approximated by an energy production model with a constant factor of proportionality, so that carbon emission prices are a function of energy prices. Using this novel modeling approach, this paper estimates the carbon emission prices for Japan using seasonally adjusted and unadjusted monthly data on the volumes of carbon emissions and energy, as well as energy prices, from December 2008 to April 2018. The econometric models show that, as sources of electricity, the logarithms of coal and oil, though not Liquefied Natural Gas (LNG,) are statistically significant in explaining the logarithm of carbon emissions, with oil being more significant than coal. The models generally displayed a high power in predicting the latent prices of carbon emissions. The usefulness of the empirical findings suggest that the methodology can also be applied for other countries where carbon emission prices are latent.

Background Thrombomodulin (TM), an integral membrane protein, has long been known for its anticoagulant activity. Recent studies showed that TM displays multifaceted activities, including the involvement in cell adhesion and collective cell migration in vitro. However, whether TM contributes similarly to these biological processes in vivo remains elusive. Methods We adapted zebrafish, a prominent animal model for studying molecular/cellular activity, embryonic development, diseases mechanism and drug discovery, to examine how TM functions in modulating cell migration during germ layer formation, a normal and crucial physiological process involving massive cell movement in the very early stages of life. In addition, an in vivo assay was developed to examine the anti-hemostatic activity of TM in zebrafish larva. Results We found that zebrafish TM-b, a zebrafish TM-like protein, was expressed mainly in vasculatures and displayed anti-hemostatic activity. Knocking-down TM-b led to malformation of multiple organs, including vessels, heart, blood cells and neural tissues. Delayed epiboly and incoherent movement of yolk syncytial layer were also observed in early TM-b morphants. Whole mount immunostaining revealed the co-localization of TM-b with both actin and microtubules in epibolic blastomeres. Single-cell tracking revealed impeded migration of blastomeres during epiboly in TM-b-deficient embryos. Conclusion Our results showed that TM-b is crucial to the collective migration of blastomeres during germ layer formation. The structural and functional compatibility and conservation between zebrafish TM-b and mammalian TM support the properness of using zebrafish as an in vivo platform for studying the biological significance and medical use of TM. Electronic supplementary material The online version of this article (10.1186/s12929-019-0549-2) contains supplementary material, which is available to authorized users.

The agricultural and energy industries are closely related, both biologically and financially. The paper discusses the relationship and the interactions on price and volatility, and on the covolatility spillover effects for these two industries. The interaction and covolatility spillovers, or the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset, between the energy and agricultural industries is the primary emphasis of the paper. Although there has already been significant research on biofuel and biofuel-related crops, only a few published papers have been concerned with volatility spillovers. It must be emphasized that there have been numerous technical errors in the theoretical and empirical research, which need to be addressed. The paper considers futures prices as a widely-used hedging instrument, and also considers an interesting new hedging instrument, ETF, which is regarded as index futures when investors manage their portfolios. In the empirical analysis, multivariate conditional volatility diagonal BEKK models are estimated for comparing patterns of covolatility spillovers. The paper provides a new way of analyzing and describing the patterns of covolatility spillovers, which should be useful for the future empirical analysis of estimating and testing covolatility spillover effects.

The main purpose of the paper is to analyze the conditional correlations, conditional covariances, and co-volatility spillovers between international crude oil and associated financial markets. The prices of oil and its interactions with financial markets make it possible to determine the associated prices of financial derivatives, such as carbon emission prices. The approach taken in the paper is different from others in the literature; the purpose is to examine the usefulness of modeling and testing volatility spillovers in the oil and financial markets. The paper investigates co-volatility spillovers (namely, the delayed effect of a returns shock in one physical or financial asset on the subsequent volatility or co-volatility in another physical or financial asset) between the oil and financial markets. The oil industry has four major regions, namely North Sea, the USA, Middle East, and South-East Asia. Associated with these regions are two major financial centers, namely the UK and the USA. For these reasons, the data to be used are the returns on alternative crude oil markets, returns on crude oil derivatives, specifically futures, and stock index returns in the UK and the USA. Given the importance of the Chinese financial and economic systems, the paper also analyzes Chinese financial markets, where the data are more recent. The USA and China are the world's two largest economies and the UK is the world's sixth largest economy (and second in the existing EU) behind the USA, China, Japan, Germany, and India. Moreover, the USA and the UK are associated with WTI and Brent oil, respectively. One of the purposes of the paper is to examine how China might be different from the USA and the UK, which seems to be borne out in the empirical analysis. Based on the conditional covariances to test the co-volatility spillovers, dynamic hedging strategies will be suggested to analyze market fluctuations in crude oil prices and associated financial markets.

Background Three-dimensional joint kinematics during canine locomotion are commonly measured using skin marker-based stereophotogrammetry technologies. However, marker-related errors caused by the displacement of the skin surface relative to the underlying bones (i.e., soft tissue artifacts, STA) may affect the accuracy of the measurements and obscure clinically relevant information. Few studies have assessed STA in canine limbs during kinematic analysis. The magnitudes and patterns of the STA and their influence on kinematic analysis remain unclear. Therefore, the current study aims to quantify the in vivo STA of skin markers on the canine thigh and crus during passive joint motion. The stifle joints of ten dogs were passively extended while the skin markers were measured using a motion capture system, and skeletal kinematics were determined using a CT-to-fluoroscopic image registration method. Results The skin markers exhibited considerable STA relative to the underlying bones, with a peak amplitude of 27.4 mm for thigh markers and 28.7 mm for crus markers; however, the amplitudes and displacement directions at different attachment sites were inconsistent. The markers on the cranial thigh and lateral crus closer to the stifle joint had greater STA amplitudes in comparison to those of other markers. Most markers had STA with linear and quadratic patterns against the stifle flexion angles. These STA resulted in underestimated flexion angles but overestimated adduction and internal rotation when the stifle was flexed to greater than 90°. Conclusions Marker displacements relative to the underlying bones were prominent in the cranial aspect of the thigh and the proximal-lateral aspect of the crus. The calculated stifle kinematic variables were also affected by the STA. These findings can provide a reference for marker selection in canine motion analysis for similar motion tasks and clarify the relationship between STA patterns and stifle kinematics; the results may therefore contribute to the development of STA models and compensation techniques for canine motion analysis. Electronic supplementary material The online version of this article (10.1186/s12917-018-1714-7) contains supplementary material, which is available to authorized users.

This paper derives the statistical properties of a two-step approach to estimating multivariate rotated GARCH-BEKK (RBEKK) models. From the definition of RBEKK, the unconditional covariance matrix is estimated in the first step to rotate the observed variables in order to have the identity matrix for its sample covariance matrix. In the second step, the remaining parameters are estimated by maximizing the quasi-log-likelihood function. For this two-step quasi-maximum likelihood (2sQML) estimator, this paper shows consistency and asymptotic normality under weak conditions. While second-order moments are needed for the consistency of the estimated unconditional covariance matrix, the existence of the finite sixth-order moments is required for the convergence of the second-order derivatives of the quasi-log-likelihood function. This paper also shows the relationship between the asymptotic distributions of the 2sQML estimator for the RBEKK model and variance targeting quasi-maximum likelihood estimator for the VT-BEKK model. Monte Carlo experiments show that the bias of the 2sQML estimator is negligible and that the appropriateness of the diagonal specification depends on the closeness to either the diagonal BEKK or the diagonal RBEKK models. An empirical analysis of the returns of stocks listed on the Dow Jones Industrial Average indicates that the choice of the diagonal BEKK or diagonal RBEKK models changes over time, but most of the differences between the two forecasts are negligible.

Environmental change created worldwide interest in investing in renewable energy. Less reliance on fossil fuels would have a substantial influence on investors for alternative energy, especially renewable energy. The literature has concentrated on empirical studies of herding behaviour in finance, but not in renewable energy. This paper fills the gap by investigating herding in renewable energy, using daily closing prices in renewable and fossil fuel energy stock returns in the USA, Europe, and Asia, for March 24, 2000–May 29, 2020, which covers the Global Financial Crisis (GFC) (2007–2009), the coronavirus crises of SARS (2003). And the ongoing COVID-19 (2019–2020) pandemic. The paper shows that: (1) for low extreme oil returns, investors are more likely to display herding in the stock market; (2) for SARS and COVID-19, herding is more likely during extremely high oil returns after the GFC; and (3) herding is more likely during periods of extremely low oil returns during the coronavirus crises. These results suggest that after the GFC, investors are more sensitive to asset losses, so they will be more likely to display herding in the stock market. However, during SARS and COVID-19, investors panic so they may unwisely sell their assets. There are strong cross-sector herding spillover effects from US fossil fuel energy to renewable energy, especially before the GFC, while the US fossil fuel energy market has a significant influence on the Europe and Asia renewable energy returns during COVID-19. During SARS, which was not a pandemic, US fossil fuels only had an impact on US renewable energy returns., Highlights • Environmental change has led to investing in renewable energy as an alternative to fossil fuels. • The literature has concentrated on herding behaviour in finance, but not in renewable energy, so this paper investigates herding in renewable energy for the USA, Europe, and Asia, for the period March 24, 2000–May 29, 2020 that covers the GFC, SARS, and COVID-19. • For (1) low extreme oil returns, herding is more likely in the stock market; (2) SARS and COVID-19, herding is more likely during extremely high oil returns after the GFC; and (3) extremely low oil returns during SARS and COVID-19, herding is more likely. • After the GFC, investors are more likely to display herding in the stock market but, during SARS and COVID-19, investors may unwisely sell their assets. • There are strong cross-sector herding spillover effects from US fossil fuel energy to renewable energy, especially before the GFC.

Purpose – Both journal self-citations and exchanged citations have the effect of increasing a journal’s impact factor, which may be deceptive. The purpose of this paper is to analyse academic journal quality and research impact using quality-weighted citations vs total citations, based on the widely used Thomson Reuters ISI Web of Science citations database (ISI). A new Index of Citations Quality (ICQ) is presented, based on quality-weighted citations. Design/methodology/approach – The new index is used to analyse the leading 500 journals in both the sciences and social sciences, as well as finance and accounting, using quantifiable Research Assessment Measures (RAMs) that are based on alternative transformations of citations. Findings – It is shown that ICQ is a useful additional measure to 2-year impact factor (2YIF) and other well-known RAMs for the purpose of evaluating the impact and quality, as well as ranking, of journals as it contains information that has very low correlations with the information contained in the well-known RAMs for both the sciences and social sciences, and finance and accounting. Practical implications – Journals can, and do, inflate the number of citations through self-citation practices, which may be coercive. Another method for distorting journal impact is through a set of journals agreeing to cite each other, that is, by exchanging citations. This may be less coercive than self-citations, but is nonetheless unprofessional and distortionary. Social implications – The premise underlying the use of citations data is that higher quality journals generally have a higher number of citations. The impact of citations can be distorted in a number of ways, both consciously and unconsciously. Originality/value – Regardless of whether self-citations arise through collusive practices, the increase in citations will affect both 2YIF and 5-year impact factor (5YIF), though not Eigenfactor and Article Influence. This leads to an ICQ, where a higher ICQ would generally be preferred to lower. Unlike 5YIF, which is increased by journal self-citations and exchanged citations, and Eigenfactor and Article Influence, both of which are affected by quality-weighted exchanged citations, ICQ will be less affected by exchanged citations. In the absence of any empirical evidence to the contrary, 5YIF and AI are assumed to be affected similarly by exchanged citations.

Neuromedin U (NMU) was originally named based on its strong uterine contractile activity, but little is known regarding its signaling/functions in utero. We identified that NMU and one of its receptors, NMUR2, are not only present in normal uterine endometrium but also co-expressed in endometrial cancer tissues, where the NMU level is correlated with the malignant grades and survival of patients. Cell-based assays further confirmed that NMU signaling can promote cell motility and proliferation of endometrial cancer cells derived from grade II tumors. Activation of NMU pathway in these endometrial cancer cells is required in order to sustain expression of various adhesion molecules, such as CD44 and integrin alpha1, as well as production of their corresponding extracellular matrix ligands, hyaluronan and collagen IV; it also increased the activity of SRC and its downstream proteins RHOA and RAC1. Thus, it is concluded that NMU pathway positively controls the adhesion signaling-SRC-Rho GTPase axis in the tested endometrial cancer cells and that changes in cell motility and proliferation can occur when there is manipulation of NMU signaling in these cells either in vitro or in vivo. Intriguingly, this novel mechanism also explains how NMU signaling promotes the EGFR-driven and TGFβ receptor-driven mesenchymal transitions. Through the above axis, NMU signaling not only can promote malignancy of the tested endometrial cancer cells directly, but also helps these cells to become more sensitive to niche growth factors in their microenvironment.

The paper focuses on the robustness of rankings of academic journal quality and research impact in general, and in Economics, in particular, based on the widely-used Thomson Reuters ISI Web of Science citations database (ISI). The paper analyses 299 leading international journals in Economics using quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in various RAMs, which are based on alternative transformations of citations and influence. All existing RAMs to date have been static, so two new dynamic RAMs are developed to capture changes in impact factor over time and escalating journal self citations. Alternative RAMs may be calculated annually or updated daily to determine When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c)). The RAMs are grouped in four distinct classes that include impact factor, mean citations and non-citations, journal policy, number of high quality papers, and journal influence and article influence. These classes include the most widely used RAMs, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Eigenfactor (or Journal Influence), Article Influence, h-index, and PI-BETA (Papers Ignored - By Even The Authors). As all existing RAMs to date have been static, two new dynamic RAMs are developed to capture changes in impact factor over time (5YD2 = 5YIF/2YIF) and Escalating Self Citations. We highlight robust rankings based on the harmonic mean of the ranks of RAMs across the 4 classes. It is shown that emphasizing the 2-year impact factor of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal quality, impact and influence relative to the harmonic mean of the ranks.

Osteoarthritis (OA) is a common and disabling joint disease mainly characterized by cartilage degradation, with the knees most commonly affected. No effective treatment for the cartilage degradation of OA exists. Preliminary studies have revealed the protective and osteogenic effects of osthole, a natural coumarin first isolated from Cnidium monnieri (Fructus Cnidii); however, no evidence of osthole in an OA-related model has been published to date. This study further explored the effects of osthole in a monoiodoacetate (MIA)-induced OA-related animal model and focused on the molecular mechanism(s) behind the anti-inflammatory and cartilage protective effects of osthole. This study revealed that the cartilage protective effect of osthole in a MIA-induced osteoarthritis (OA) murine model can be explained by downregulation of COX-2 and RUNX2 by inhibition of NF-κB and HIF-2α up-regulated by OA induction, resulting in downregulation of MMP-13, Syndecan IV and ADAMTS-5. In addition, osthole might have anti-inflammatory and analgesic effects due to COX-2 inhibition. Osthole can be considered as a potential component of the treatment of OA, for it possesses a cartilage protective effect, as well as anti-inflammation, analgesic, and movement improving effects. Further preclinical and human clinical studies are needed to examine the efficacy and safety profile of long-term therapy.

The number of Chinese tourists visiting Taiwan has been closely related to the political relationship across the Taiwan Strait. The occurrence of political events and disasters or accidents have had, and will continue to have, a huge impact on the Taiwan tourism market. To date, there has been relatively little empirical research conducted on this issue. Tourists are characterized as being involved in one of three types of tourism: group tourism (group-type), individual tourism (individual-type), and medical cosmetology (medical-type). We use the fundamental equation in tourism finance to examine the correlation that exists between the rate of change in the number of tourists and the rate of return on tourism. Second, we use the event study method to observe whether the numbers of tourists have changed abnormally before and after the occurrence of major events on both sides of the Strait. Three different types of conditional variance models, namely, the Generalized Autoregressive Conditional Heteroscedasticity, GARCH (1,1), Glosten, Jagannathan and Runkle, GJR (1,1) and Exponential GARCH, EGARCH (1,1), are used to estimate the abnormal rate of change in the number of tourists. The empirical results concerning the major events affecting the changes in the numbers of tourists from China to Taiwan are economically significant, and confirm the types of tourists that are most likely to be affected by such major events.

Mesophase pitch fabricated through polymerization of polycyclic aromatic hydrocarbons (PAHs) is highly aromatic and of high quality, and it can be used as a raw material to produce other carbon-based materials. Hydrofluoride/boron trifluoride (HF/BF3) is currently an efficient reagent to catalyze the PAH polymerization to produce mesophase pitch. In this study, density functional theory (DFT) calculations are performed to propose a mechanism for naphthalene catalytic polymerization using HF/BF3. The overall reaction mechanism can be conceptualized as having two stages: activation, followed by polymerization. During activation, HF/BF3 acts a proton donor to activate naphthalene, whose then-protonated form can promote the formation of a C-C bond with another naphthalene molecule via electrophilic addition. We also propose a catalyst recovery pathway, which can stabilize the intermediate products. In the polymerization stage, two types of pathways are proposed, those of chain elongation and intramolecular cyclization. According to the proposed catalytic mechanism in this study, the predicted mesophase product shows highly aliphatic hydrogens, which is consistent with the experimental results. We propose the full catalytic mechanism using DFT calculations. Our results provide a better understanding of how to develop novel and green catalysts, which can replace the HF/BF3 reagent in future applications.

This paper is the first to investigate the effect of industrial penetration (geographic concentration of industries) and internet intensity (the proportion of enterprises that uses the internet) for Taiwan manufacturing firms, and analyses whether the relationships are substitutes or complements. The sample observations are based on a unique set of data, namely 153,081 manufacturing plants, and covers 26 two-digit industry categories and 358 geographical townships in Taiwan. The Heckman sample selection model is used to accommodate sample selectivity for unobservable data for firms that use the internet. The empirical results from Heckman’s two-stage estimation show that: (1) a higher degree of industrial penetration will not affect the probability that firms will use the internet, but it will affect the total expenditure on internet intensity; (2) for two-digit SIC (Standard Industrial Classification) industries, industrial penetration generally decreases the total expenditure on internet intensity; and, (3) industrial penetration and internet intensity are substitutes.

The paper provides a brief review of the connecting literature in management information, decision sciences, and financial economics, and discusses some research that is related to the three cognate disciplines. Academics could develop theoretical models and subsequent econometric models to estimate the parameters in the associated models, and analyze some interesting issues in the three related disciplines.

This paper provides a review of some connecting literature in Decision Sciences, Economics, Finance, Business, Computing, and Big Data. We then discuss some research that is related to the six cognate disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models. Moreover, they could then conduct simulations to examine whether the estimators or statistics in the new theories on estimation and hypothesis have small size and high power. Thereafter, academics and practitioners could then apply their theories to analyze interesting problems and issues in the six disciplines and other cognate areas.