Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice

Energy and agricultural commodities and markets have been examined extensively, albeit separately, for a number of years. In the energy literature, the returns, volatility and volatility spillovers (namely, the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset), among alternative energy commodities, such as oil, gasoline and ethanol across different markets, have been analysed using a variety of univariate and multivariate models, estimation techniques, data sets, and time frequencies. A similar comment applies to the separate theoretical and empirical analysis of a wide range of agricultural commodities and markets. Given the recent interest and emphasis in bio-fuels and green energy, especially bio-ethanol, which is derived from a range of agricultural products, it is not surprising that there is a topical and developing literature on the spillovers between energy and agricultural markets. Modelling and testing spillovers between the energy and agricultural markets has typically been based on estimating multivariate conditional volatility models, specifically the Baba, Engle, Kraft, and Kroner (BEKK) and dynamic conditional correlation (DCC) models. A serious technical deficiency is that the Quasi-Maximum Likelihood Estimates (QMLE) of a Full BEKK matrix, which is typically estimated in examining volatility spillover effects, has no asymptotic properties, except by assumption, so that no valid statistical test of volatility spillovers is possible. Some papers in the literature have used the DCC model to test for volatility spillovers. However, it is well known in the financial econometrics literature that the DCC model has no regularity conditions, and that the QMLE of the parameters of DCC has no asymptotic properties, so that there is no valid statistical testing of volatility spillovers. The purpose of the paper is to evaluate the theory and practice in testing for volatility spillovers between energy and agricultural markets using the multivariate Full BEKK and DCC models, and to make recommendations as to how such spillovers might be tested using valid statistical techniques. Three new definitions of volatility and covolatility spillovers are given, and the different models used in empirical applications are evaluated in terms of the new definitions and statistical criteria

Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice

Energy and agricultural commodities and markets have been examined extensively, albeit separately, for a number of years. In the energy literature, the returns, volatility and volatility spillovers (namely, the delayed effect of a returns shock in one asset on the subsequent volatility or covolatility in another asset), among alternative energy commodities, such as oil, gasoline and ethanol across different markets, have been analysed using a variety of univariate and multivariate models, estimation techniques, data sets, and time frequencies. A similar comment applies to the separate theoretical and empirical analysis of a wide range of agricultural commodities and markets. Given the recent interest and emphasis in bio-fuels and green energy, especially bio-ethanol, which is derived from a range of agricultural products, it is not surprising that there is a topical and developing literature on the spillovers between energy and agricultural markets. Modelling and testing spillovers between the energy and agricultural markets has typically been based on estimating multivariate conditional volatility models, specifically the Baba, Engle, Kraft, and Kroner (BEKK) and dynamic conditional correlation (DCC) models. A serious technical deficiency is that the Quasi-Maximum Likelihood Estimates (QMLE) of a Full BEKK matrix, which is typically estimated in examining volatility spillover effects, has no asymptotic properties, except by assumption, so that no valid statistical test of volatility spillovers is possible. Some papers in the literature have used the DCC model to test for volatility spillovers. However, it is well known in the financial econometrics literature that the DCC model has no regularity conditions, and that the QMLE of the parameters of DCC has no asymptotic properties, so that there is no valid statistical testing of volatility spillovers. The purpose of the paper is to evaluate the theory and practice in testing for volatility spillovers between energy and agricultural markets using the multivariate Full BEKK and DCC models, and to make recommendations as to how such spillovers might be tested using valid statistical techniques. Three new definitions of volatility and covolatility spillovers are given, and the different models used in empirical applications are evaluated in terms of the new definitions and statistical criteria

Anesthetic Propofol Attenuates the Isoflurane-Induced Caspase-3 Activation and Aβ Oligomerization

Accumulation and deposition of β-amyloid protein (Aβ) are the hallmark features of Alzheimer's disease. The inhalation anesthetic isoflurane has been shown to induce caspase activation and increase Aβ accumulation. In addition, recent studies suggest that isoflurane may directly promote the formation of cytotoxic soluble Aβ oligomers, which are thought to be the key pathological species in AD. In contrast, propofol, the most commonly used intravenous anesthetic, has been reported to have neuroprotective effects. We therefore set out to compare the effects of isoflurane and propofol alone and in combination on caspase-3 activation and Aβ oligomerization in vitro and in vivo. Naïve and stably-transfected H4 human neuroglioma cells that express human amyloid precursor protein, the precursor for Aβ; neonatal mice; and conditioned cell culture media containing secreted human Aβ40 or Aβ42 were treated with isoflurane and/or propofol. Here we show for the first time that propofol can attenuate isoflurane-induced caspase-3 activation in cultured cells and in the brain tissues of neonatal mice. Furthermore, propofol-mediated caspase inhibition occurred when there were elevated levels of Aβ. Finally, isoflurane alone induces Aβ42, but not Aβ40, oligomerization, and propofol can inhibit the isoflurane-mediated oligomerization of Aβ42. These data suggest that propofol may mitigate the caspase-3 activation by attenuating the isoflurane-induced Aβ42 oligomerization. Our findings provide novel insights into the possible mechanisms of isoflurane-induced neurotoxicity that may aid in the development of strategies to minimize potential adverse effects associated with the administration of anesthetics to patients

Zebrafish as a Model System to Study the Physiological Function of Telomeric Protein TPP1

Telomeres are specialized chromatin structures at the end of chromosomes. Telomere dysfunction can lead to chromosomal abnormalities, DNA damage responses, and even cancer. In mammalian cells, a six-protein complex (telosome/shelterin) is assembled on the telomeres through the interactions between various domain structures of the six telomere proteins (POT1, TPP1, TIN2, TRF1, TRF2 and RAP1), and functions in telomere maintenance and protection. Within the telosome, TPP1 interacts directly with POT1 and TIN2 and help to mediate telosome assembly. Mechanisms of telomere regulation have been extensively studied in a variety of model organisms. For example, the physiological roles of telomere-targeted proteins have been assessed in mice through homozygous inactivation. In these cases, early embryonic lethality has prevented further studies of these proteins in embryogenesis and development. As a model system, zebrafish offers unique advantages such as genetic similarities with human, rapid developmental cycles, and ease of manipulation of its embryos. In this report, we detailed the identification of zebrafish homologues of TPP1, POT1, and TIN2, and showed that the domain structures and interactions of these telosome components appeared intact in zebrafish. Importantly, knocking down TPP1 led to multiple abnormalities in zebrafish embryogenesis, including neural death, heart malformation, and caudal defect. And these embryos displayed extensive apoptosis. These results underline the importance of TPP1 in zebrafish embryogenesis, and highlight the feasibility and advantages of investigating the signaling pathways and physiological function of telomere proteins in zebrafish

Integrated motor drives: state of the art and future trends

With increased need for high power density, high efficiency and high temperature capabilities in Aerospace and Automotive applications, Integrated Motor Drives (IMD) offers a potential solution. However, close physical integration of the converter and the machine may also lead to an increase in components temperature. This requires careful mechanical, structural and thermal analysis; and design of the IMD system. This paper reviews existing IMD technologies and their thermal effects on the IMD system. The effects of the power electronics (PE) position on the IMD system and its respective thermal management concepts are also investigated. The challenges faced in designing and manufacturing of an IMD along with the mechanical and structural impacts of close physical integration is also discussed and potential solutions are provided. Potential converter topologies for an IMD like the Matrix converter, 2-level Bridge, 3-level NPC and Multiphase full bridge converters are also reviewed. Wide band gap devices like SiC and GaN and their packaging in power modules for IMDs are also discussed. Power modules components and packaging technologies are also presented