106 research outputs found

    Synthesis and decomposition of a novel carboxylate precursor to indium oxide

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    Reaction of metallic indium with benzoyl peroxide in 4-1 methylpyridine (4-Mepy) at 25 C produces an eight-coordinate mononuclear indium(III) benzoate, In(eta(sup 2)-O2CC6H5)3(4-Mepy)2 4H2O (I), in yields of up to 60 percent. The indium(III) benzoate was fully characterized by elemental analysis, spectroscopy, and X-ray crystallography; (I) exists in the crystalline state as discrete eight-coordinate molecules; the coordination sphere around the central indium atom is best described as pseudo-square pyramidal. Thermogravimetric analysis of (I) and X-ray diffraction powder studies on the resulting pyrolysate demonstrate that this new benzoate is an inorganic precursor to indium oxide. Decomposition of (I) occurs first by loss of 4-methylpyridine ligands (100 deg-200 deg C), then loss of benzoates with formation of In2O3 at 450 C. We discuss both use of carboxylates as precursors and our approach to their preparation

    A new attraction-detachment model for explaining flow sliding in clay-rich tephras

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    Altered pyroclastic (tephra) deposits are highly susceptible to landsliding, leading to fatalities and property damage every year. Halloysite, a low-activity clay mineral, is commonly associated with landslide-prone layers within altered tephra successions, especially in deposits with high sensitivity, which describes the post-failure strength loss. However, the precise role of halloysite in the development of sensitivity, and thus in sudden and unpredictable landsliding, is unknown. Here we show that an abundance of mushroom cap–shaped (MCS) spheroidal halloysite governs the development of sensitivity, and hence proneness to landsliding, in altered rhyolitic tephras, North Island, New Zealand. We found that a highly sensitive layer, which was involved in a flow slide, has a remarkably high content of aggregated MCS spheroids with substantial openings on one side. We suggest that short-range electrostatic and van der Waals interactions enabled the MCS spheroids to form interconnected aggregates by attraction between the edges of numerous paired silanol and aluminol sheets that are exposed in the openings and the convex silanol faces on the exterior surfaces of adjacent MCS spheroids. If these weak attractions are overcome during slope failure, multiple, weakly attracted MCS spheroids can be separated from one another, and the prevailing repulsion between exterior MCS surfaces results in a low remolded shear strength, a high sensitivity, and a high propensity for flow sliding. The evidence indicates that the attraction-detachment model explains the high sensitivity and contributes to an improved understanding of the mechanisms of flow sliding in sensitive, altered tephras rich in spheroidal halloysite

    Banking Union as a Shock Absorber

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    This study investigates the shock-absorbing properties of a banking union by providing a detailed comparison between the way regional financial shocks have been absorbed at the federal level in the US, but have led to severe regional (national) financial dislocation and tensions in the euro area. The extent to which the institutions of the banking union, which is now emerging in the euro area, should increase its capacity to deal with future regional boom and bust cycles is also discussed. Cross-border capital flows in the form of equity appear to be much more stable than those taking the form of credit, especially inter-bank credit. Moreover, credit booms and bust leave a debt overhang and losses can materialise only via insolvencies, whereas equity flows absorb automatically losses in case of a bust and provide the cross border owner with incentives to continue to provide financing. It follows that cross-border banks can absorb regional shocks. But large banks pose the 'too big to fail' problem and they would also propagate regional shocks, especially if they originate in large countries, to the entire area

    Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells

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    Significant inroads have been made to understand cerebellar cortical processing but neural coding at the output stage of the cerebellum in the deep cerebellar nuclei (DCN) remains poorly understood. The DCN are unlikely to just present a relay nucleus because Purkinje cell inhibition has to be turned into an excitatory output signal, and DCN neurons exhibit complex intrinsic properties. In particular, DCN neurons exhibit a range of rebound spiking properties following hyperpolarizing current injection, raising the question how this could contribute to signal processing in behaving animals. Computer modeling presents an ideal tool to investigate how intrinsic voltage-gated conductances in DCN neurons could generate the heterogeneous firing behavior observed, and what input conditions could result in rebound responses. To enable such an investigation we built a compartmental DCN neuron model with a full dendritic morphology and appropriate active conductances. We generated a good match of our simulations with DCN current clamp data we recorded in acute slices, including the heterogeneity in the rebound responses. We then examined how inhibitory and excitatory synaptic input interacted with these intrinsic conductances to control DCN firing. We found that the output spiking of the model reflected the ongoing balance of excitatory and inhibitory input rates and that changing the level of inhibition performed an additive operation. Rebound firing following strong Purkinje cell input bursts was also possible, but only if the chloride reversal potential was more negative than −70 mV to allow de-inactivation of rebound currents. Fast rebound bursts due to T-type calcium current and slow rebounds due to persistent sodium current could be differentially regulated by synaptic input, and the pattern of these rebounds was further influenced by HCN current. Our findings suggest that active properties of DCN neurons could play a crucial role for signal processing in the cerebellum
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