Percolative conductivity in alkaline earth silicate melts and glasses

Ion conducting $(CaO)_x(SiO_2)_{1-x}$ glasses and melts show a threshold behaviour in dc conductivity near $x=x_t=0.50$, with conductivities increasing linearly at $x>x_t$. We show that the behaviour can be traced to a rigid ($x0.50$) elastic phase transition near $x=x_t$. In the floppy phase, conductivity enhancement is traced to increased mobility or diffusion of $Ca^{2+}$ carriers as the modified network elastically softens.Comment: 15 pages, 5 figures. Europhysics Letters (2003), in pres

Correlation between floppy to rigid transitions and non-Arrhenius conductivity in glasses

Non-Arrhenius behaviour and fast increase of the ionic conductivity is observed for a number of potassium silicate glasses $(1-x)SiO_2-xK_2O$ with potassium oxide concentration larger than a certain value $x=x_c=0.14$. Recovering of Arrhenius behaviour is provided by the annealing that enhances densification. Conductivity furthermore obeys a percolation law with the same critical concentration $x_c$. These various results are the manifestation of the floppy or rigid nature of the network and can be analyzed with constraint theory. They underscore the key role played by network rigidity for the understanding of conduction and saturation effects in glassy electrolytes.Comment: 4 pages, 4 EPS figure

A Structural Break Approach to Analysing the Impact of the QE Portfolio Balance Channel on the US Stock Market

Following the 1929 Wall Street collapse, the initial response to the institutional failures and collapsing financial system was to allow the markets to self-correct, which led to a significant period of economic depression. In contrast the US (and UK) governments responded to the 2008 financial crisis with extra liquidity for the banking sector and a stimulus package, but why was there such a different response? Following a light touch approach to Bear Stearns and Lehmann’s, it became clear that without greater intervention, the effect would become contagious throughout the financial system. One of the most important forms of intervention was Quantitative Easing (QE) and historically low interest rates. This study finds that QE substantially reduced the Equity Risk Premium on S&P equities through a 9.6% rise in prices, thus reducing returns. Consequentially, this drives portfolios to seek risker asset classes to make up for the shortfall in returns. This suggests that the combination of low interest rates and QE, when compared to expansion alone, has had a marked change on equity prices and ERP. Furthermore, there is evidence that regime shifts support these findings. Such unforeseen consequences in the equity markets is of great interest to policy makers when deciding on a response to such exceptional circumstances, and researchers investigating monetary policy responses to the next inevitable extreme financial crisis

Spill over effects of Geopolitical risk on the banking sector of CIS countries

This study examines the spill over effects of geopolitical risks (GPR) and extreme shocks on Commonwealth of Independent States (CIS) economies, as result of the Russia – Ukraine war, with particular focus on financial institutions. Further, we investigate whether the performance of CIS banks has been impacted by economic sanctions imposed on Russia since the start of the conflict. Understanding GPR transmission mechanisms and consequences on Russia’s neighbouring countries allows policymakers and financial institutions to formulate and implement risk management strategies. For a global measure of geo-political risk, we employ the global GPR index from Caldara and Iacoviello (2022) and we use the Diebold-Yilmaz (2012) connectedness model to estimate the spill over effect. First, we investigate the spill over effect of the recent conflict on the returns of banks for a sample of CIS countries. Further, we examine the spill over effect on macro-economic indicators of our sample of countries. Our preliminary results do not show significant GPR transmissions in terms of returns and risk within the banking sectors of the CIS countries examined

Carbonatite Melts and Electrical Conductivity in the Asthenosphere

Electrically conductive regions in the Earth mantle have been interpreted to reflect the presence of either silicate melt or water dissolved in olivine. On the basis of laboratory measurements we show that molten carbonates have electrical conductivities that are 3 orders of magnitude higher than those of molten silicate and 5 orders of magnitude higher than those of hydrated olivine. High conductivities in the asthenosphere probably indicate the presence of small amounts of carbonate melt in peridotite and can therefore be interpreted in terms of carbon concentration in the upper mantle. We show that the conductivity of the Oceanic asthenosphere can be explained by 0.1 volume % of carbonatite melts on average, which agrees with the CO2 content of Mid Ocean Ridge Basalts

Epigenetic differences in monozygotic twins discordant for major depressive disorder

Although monozygotic (MZ) twins share the majority of their genetic makeup, they can be phenotypically discordant on several traits and diseases. DNA methylation is an epigenetic mechanism that can be influenced by genetic, environmental and stochastic events and may have an important impact on individual variability. In this study we explored epigenetic differences in peripheral blood samples in three MZ twin studies on major depressive disorder (MDD). Epigenetic data for twin pairs were collected as part of a previous study using 8.1-K-CpG microarrays tagging DNA modification in white blood cells from MZ twins discordant for MDD. Data originated from three geographical regions: UK, Australia and the Netherlands. Ninety-seven MZ pairs (194 individuals) discordant for MDD were included. Different methods to address non independently-and-identically distributed (non-i.i.d.) data were evaluated. Machine-learning methods with feature selection centered on support vector machine and random forest were used to build a classifier to predict cases and controls based on epivariations. The most informative variants were mapped to genes and carried forward for network analysis. A mixture approach using principal component analysis (PCA) and Bayes methods allowed to combine the three studies and to leverage the increased predictive power provided by the larger sample. A machine-learning algorithm with feature reduction classified affected from non-affected twins above chance levels in an independent training-testing design. Network analysis revealed gene networks centered on the PPAR-γ (NR1C3) and C-MYC gene hubs interacting through the AP-1 (c-Jun) transcription factor. PPAR-γ (NR1C3) is a drug target for pioglitazone, which has been shown to reduce depression symptoms in patients with MDD. Using a data-driven approach we were able to overcome challenges of non-i.i.d. data when combining epigenetic studies from MZ twins discordant for MDD. Individually, the studies yielded negative results but when combined classification of the disease state from blood epigenome alone was possible. Network analysis revealed genes and gene networks that support the inflammation hypothesis of MDD

Taxonomic diversity of benthic macroinvertebrates along the Oum Er Rbia River (Morocco): implications for water quality bio-monitoring using indicator species

The macroinvertebrates of the Oum Er Rbia River were studied from samples collected seasonally from September 2015 to September 2016 at 10 sampling sites. The macroinvertebrates found during the sampling period were distributed into twelve orders. The most abundant order was diptera, having 9618 individuals, followed by the order Ephemeroptera with 2985 individuals. Coleoptera, odonates and crustaceans represent only a small fraction of the total fauna. Hydropsyche, Chironomidae sp. and Simuliidae are numerically more inventoried. The composition and distribution of the species were directly or indirectly affected by the physicochemical variables and the quality of the habitat. Correspondence analysis results showed that habitat quality and quality of water represented species distribution patterns and species can be used as indicators to assess the quality of the Oum Er Rbia River system. Habitat management along the Oum Er Rbia river should be aimed at preserving native species, especially during the summer, when the biotope requirements are optimal. The results obtained in this study showed an alarming situation of the water quality of the Oum Er Rbia River and particularly in downstream segment. To solve this problem, we recommend the development of the wastewater discharge of Khenifra and Kasba Tadla and the purification of wastewater before it is discharged into the river

Epigenetic differences in monozygotic twins discordant for major depressive disorder

Although monozygotic (MZ) twins share the majority of their genetic makeup, they can be phenotypically discordant on several traits and diseases. DNA methylation is an epigenetic mechanism that can be influenced by genetic, environmental and stochastic events and may have an important impact on individual variability. In this study we explored epigenetic differences in peripheral blood samples in three MZ twin studies on major depressive disorder (MDD). Epigenetic data for twin pairs were collected as part of a previous study using 8.1-K-CpG microarrays tagging DNA modification in white blood cells from MZ twins discordant for MDD. Data originated from three geographical regions: UK, Australia and the Netherlands. Ninety-seven MZ pairs (194 individuals) discordant for MDD were included. Different methods to address non independently-and-identically distributed (non-i.i.d.) data were evaluated. Machine-learning methods with feature selection centered on support vector machine and random forest were used to build a classifier to predict cases and controls based on epivariations. The most informative variants were mapped to genes and carried forward for network analysis. A mixture approach using principal component analysis (PCA) and Bayes methods allowed to combine the three studies and to leverage the increased predictive power provided by the larger sample. A machine-learning algorithm with feature reduction classified affected from non-affected twins above chance levels in an independent training-testing design. Network analysis revealed gene networks centered on the PPAR-γ (NR1C3) and C-MYC gene hubs interacting through the AP-1 (c-Jun) transcription factor. PPAR-γ (NR1C3) is a drug target for pioglitazone, which has been shown to reduce depression symptoms in patients with MDD. Using a data-driven approach we were able to overcome challenges of non-i.i.d. data when combining epigenetic studies from MZ twins discordant for MDD. Individually, the studies yielded negative results but when combined classification of the disease state from blood epigenome alone was possible. Network analysis revealed genes and gene networks that support the inflammation hypothesis of MDD