Different Moments Create Different Spillovers: A Study of Commodity Markets

Although the spillover effects of return and volatility risk across commodity markets have been demonstrated, evidence of extreme risk spillovers is limited. Using an autoregressive conditional density model, this study estimates the conditional skewness of nine S&P Goldman Sachs Commodity indices and then applies the Diebold-Yilmaz TVP-VAR-based approach to investigate the higher moment spillovers across commodity markets. Our findings provide evidence of extreme risk transfers from one commodity index to another. Among three energy indices including crude oil, natural gas and gasoil, crude oil transmits the most return, volatility risk and extreme risk to the agricultural indices and precious metal indices. Furthermore, our results confirm that spillovers in all three moments were significantly strengthened by extreme events such as the September 11 attacks, the global financial crisis, the food price crisis, the violent shock of international oil prices and the coronavirus disease of 2019. However, different events may have different impacts on spillovers. Finally, the results indicate that return spillover and skewness are affected by extreme events with almost the same intensity and direction for most periods.

COVID-19 and bone health.

A few patients who have recovered from COVID-19 develop persistent or new symptoms that last for weeks or months; this is called "long COVID" or "post-COVID-19 syndrome." Over time, awareness of the short- and long-term consequences of COVID-19 has increased. The pulmonary consequences are now fairly well established, but little is known about the extrapulmonary system of COVID-19, particularly its effects on bones. Current evidence and reports indicate a direct relationship between SARS-CoV-2 infection and bone health, with SARS-CoV-2 having a significant negative effect on bone health. In this review, we analyzed the impact of SARS-CoV-2 infection on bone health and assessed the impact of COVID-19 on the diagnosis and treatment of osteoporosis.

Learning linear non-Gaussian directed acyclic graph with diverging number of nodes

An acyclic model, often depicted as a directed acyclic graph (DAG), has been widely employed to represent directional causal relations among collected nodes. In this article, we propose an efficient method to learn linear non-Gaussian DAG in high dimensional cases, where the noises can be of any continuous non-Gaussian distribution. The proposed method leverages the concept of topological layer to facilitate the DAG learning, and its theoretical justification in terms of exact DAG recovery is also established under mild conditions. Particularly, we show that the topological layers can be exactly reconstructed in a bottom-up fashion, and the parent-child relations among nodes can also be consistently established. The established asymptotic DAG recovery is in sharp contrast to that of many existing learning methods assuming parental faithfulness or ordered noise variances. The advantage of the proposed method is also supported by the numerical comparison against some popular competitors in various simulated examples as well as a real application on the global spread of COVID-19. ©2022 Ruixuan Zhao, Xin He, and Junhui Wang.

Why Zero Trust Framework Adoption has Emerged During and After Covid-19 Pandemic

The rise of COVID-19 brought an unprecedented change in the way people lived. It left several people in a work-from-home situation. This Paper aims to investigate the recent works which applied Zero Trust and the reason that this framework adoption has emerged during and after the Pandemic. In this regard, a questionnaire was prepared, and its results are reported. According to its results, with Zero Trust Architecture (ZTA) gaining skyrocket popularity and trust, for around 60% corporates, ZT Access is planned for future, while for around 30% corporates, the project is in pipeline. None of the organizations surveyed have the ZTA in place. 14% of organizations are uninterested in adopting ZTA. Plus, in past 2 years, the percentage of north American organizations having a ZTA on the plans to establish one in the next 12–18 months has shot up. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The growth, adventitious bud formation, bioactive flavonoid production, antioxidant response, and cryptochrome-mediated light signal transduction in Isatis tinctoria L. hairy root cultures exposed to LED lights

The root of Isatis tinctoria L. is highly appreciated as a Traditional Chinese herbal medicine for the prevention and adjuvant treatment of respiratory diseases caused by coronaviruses viruses such as SARS and COVID-19. I. tinctoria hairy root cultures (ITHRCs) provide a better alternative to field cultivation for the production of antiviral flavonoids. For the first time, ITHRCs were exposed to different colors of LED lights i.e., red, green, blue, red/green/blue (1/1/1, RGB), and white, in an attempt to promote the root growth and enhance the production of bioactive flavonoids. Results revealed that the biomass productivity (7.15 ± 0.63 g/L) in ITHRCs with an initial inoculum size of 0.2% cultured for 50 days under blue light increased by 1.86-fold relative to that under dark (control), and yields of rutin (320.49 ± 27.56 μg/g DW), quercetin (388.75 ± 9.17 μg/g DW), kaempferol (787.90 ± 83.43 μg/g DW), and isorhamnetin (269.11 ± 20.08 μg/g DW) increased by 4.15-fold, 9.31-fold, 9.09-fold, and 2.88-fold as compared with control, respectively. Interestingly, the emergence of adventitious buds was noticed in ITHRCs under all light treatments. Additionally, the enhanced densities of chloroplasts and root hairs were found in blue-light grown ITHRCs as against control, which might account for the elevated biomass productivity. Moreover, blue light induced oxidative stress in ITHRCs in terms of the overproduction of oxidation products and the enhancement of antioxidant enzyme activity. Furthermore, blue light significantly activated photoreceptor (CRY1) and key regulator of light signaling (HY5), thus leading to the up-regulated expression of MYB4 and structural genes (such as CHS and FLS) responsible for flavonoid biosynthesis. And, the transcriptional activation of CUC1 was likely related to the formation of adventitious buds in ITHRCs. Overall, the simple supplementation of blue LED light makes ITHRCs more attractive as plant factories for obtaining higher productivity of biomass and medicinally important flavonoids. © 2023 Elsevier B.V.

Temporal evolution and spatial pattern of the COVID-19 epidemic in the United States

It is the cornerstone of precise and scientific prevention and control to understand the temporal evolution and spatial pattern of the COVID-19 epidemic. Based on the county-level COVID-19 case of the United States from January 22, 2020 to October 8, 2021, we explored and analyzed the epidemic by using time series analysis, spatial autocorrelation analysis and gravity center trajectory analysis. The results show that: (1) the epidemic in the United States experienced four stages of low incidence, growth, peak and rebound with June 15, September 30 and October 1, 2020 as the cut-off points. (2) The global Moran index experienced a process of 'increase-decrease-increase-stability', with the maximum value exceeding 0.6, indicating that the epidemic has obvious spatial aggregation;the epidemic is dominated by high-high clusters (over 150 counties) and low-low clusters (over 500 counties), presenting a pattern of 'three cores and multiple islands' and 'north-south belt'. (3) In 60% of states, the trajectory of the epidemic center of gravity is near-linear type. The epidemic hotspots in these states were relatively stable over time. In more than half of the states, the curve of the moving distance of the epidemic center of gravity is exponential. These states experienced a very rapid epidemic. This study is expected to provide a reference for evaluating the effectiveness of epidemic prevention measures and determining targeted epidemic prevention measures, as well as accumulate experience for future research on the spread of different infectious diseases in different regions. © 2022 IEEE.

Masks, ventilation and exposure time: A web-based calculator of indoor COVID-19 infection risk

Two and half years into the COVID-19 pandemic, there is quite a lot of confusion over public health guidance necessary in order to reduce disease infection risks, from room air ventilation, the use of air cleaners, and type of mask and whether or not to wear a mask. This paper describes the development of a novel web-based calculator for use by the public to assess COVID-19 infection risks between a source and receiver in a typical room. The aim is to inform the disease infection risk in response to varying exposure times, mask-wearing, and viral variant in circulation. The calculator is based on the state-of-the-art research evidence, i.e., a room air ventilation model, mask infiltration efficiencies, room cleaner efficiencies, the quanta emission rates of various viral variants of COVID-19, and the modified Wells Riley equations. The results show that exposure times are critical in determining transmission risk. Masks are important and can reduce infection risk especially over shorter exposure times and for lower source emission quantum. N95 respirators are by far the most effective, especially for Omicron, and the results indicate that N95 respirators are necessary for the more infectious variants. Increasing fresh air ventilation rates from 2ac/h to 6ac/h can have a considerable impact in reducing transmission risk in a well-mixed space. Going from 6 ac/h to 12ac/h is less effective especially at lower exposure times. Venues can be classified in terms of risk, and appropriate high ventilation rates might be recommended for high-risk, speaking loudly and singing, such as classrooms and theatres. However, for low risk, quiet and speaking softly venues, such as offices and libraries, higher ventilation rates may not be required;instead, mechanical ventilation systems in combination with air cleaners can effectively remove small fraction size aerosol particles. The web-based calculator provides an easy-to-use and valuable tool for use in estimating infection risk.