Sex chromosome abnornalities in a population of 1,662 mental defectives

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Cognition based bTBI mechanistic criteria; a tool for preventive and therapeutic innovations

Blast-induced traumatic brain injury has been associated with neurodegenerative and neuropsychiatric disorders. To date, although damage due to oxidative stress appears to be important, the specific mechanistic causes of such disorders remain elusive. Here, to determine the mechanical variables governing the tissue damage eventually cascading into cognitive deficits, we performed a study on the mechanics of rat brain under blast conditions. To this end, experiments were carried out to analyse and correlate post-injury oxidative stress distribution with cognitive deficits on a live rat exposed to blast. A computational model of the rat head was developed from imaging data and validated against in vivo brain displacement measurements. The blast event was reconstructed in silico to provide mechanistic thresholds that best correlate with cognitive damage at the regional neuronal tissue level, irrespectively of the shape or size of the brain tissue types. This approach was leveraged on a human head model where the prediction of cognitive deficits was shown to correlate with literature findings. The mechanistic insights from this work were finally used to propose a novel helmet design roadmap and potential avenues for therapeutic innovations against blast traumatic brain injury

Assessment of Fluid Cavitation Threshold Using a Polymeric Split Hopkinson Bar-Confinement Chamber Apparatus

The authors would like to acknowledge the Natural Sciences and Engineering Research Council of Canada for financial support, and Compute Canada and Sharcnet for providing the necessary computing resources.Mild Traumatic Brain Injury (mTBI) has been associated with blast exposure resulting from the use of improvised explosive devices (IEDs) in recent and past military conflicts. Experimental and numerical models of head blast exposure have demonstrated the potential for high negative pressures occurring within the head at the contre-coup location relative to the blast exposure, and it has been hypothesized that this negative pressure could result in cavitation of Cerebrospinal Fluid (CSF) surrounding the brain, leading to brain tissue damage. The cavitation threshold of CSF, the effect of temperature, and the effect of impurities or dissolved gases are presently unknown. In this study, a novel Polymeric Split Hopkinson Pressure Bar and confinement chamber apparatus were used to generate loading in distilled water similar to the conditions in the vicinity of the CSF during blast exposure. Cavitation was identified using high-speed imaging of the event, and a validated numerical model of the apparatus was applied to determine the pressure in the fluid during the exposure. Increasing the water temperature resulted in a decrease in the 50% probability of cavitation from 21 °C (−3320 kPa ± 3%) to 37 °C (−3195 kPa ± 5%) in agreement with the theoretical values, but was not statistically significant. Importantly, the effect of water treatment had a significant effect on the cavitation pressure for water with wetting agent (−3320 kPa ± 3%), degassed water (−1369 kPa ± 16%) and untreated distilled water (−528 kPa ± 25%). Thus, reducing dissolved gases through degassing or the use of a wetting agent significantly increases the cavitation pressure and reduces the variability of the cavitation pressure threshold

RIMBAY — a multi-approximation 3D ice-dynamics model for comprehensive applications: model description and examples

Glaciers and ice caps exhibit currently the largest cryospheric contributions to sea level rise. Modelling the dynamics and mass balance of the major ice sheets is therefore an important issue to investigate the current state and the future response of the cryosphere in response to changing environmental conditions, namely global warming. This requires a powerful, easy-to-use, versatile multi-approximation ice dynamics model. Based on the well-known and established ice sheet model of Pattyn (2003) we develop the modular multi-approximation thermomechanic ice model RIMBAY, in which we improve the original version in several aspects like a shallow ice–shallow shelf coupler and a full 3D-grounding-line migration scheme based on Schoof's (2007) heuristic analytical approach. We summarise the full Stokes equations and several approximations implemented within this model and we describe the different numerical discretisations. The results are cross-validated against previous publications dealing with ice modelling, and some additional artificial set-ups demonstrate the robustness of the different solvers and their internal coupling. RIMBAY is designed for an easy adaption to new scientific issues. Hence, we demonstrate in very different set-ups the applicability and functionality of RIMBAY in Earth system science in general and ice modelling in particular

Data- and model-driven determination of flow pathways in the Piako catchment, New Zealand

Quantifying flow pathways within a larger catchment can help improve diffuse pollution management strategies across subcatchments. But, spatial quantification of flow pathway contributions to catchment stream flow is very limited, since it is challenging to physically separate water from different paths and very expensive to measure, especially for larger areas. To overcome this problem, a novel, combined data and modelling approach was employed to partition stream flow in the Piako catchment, New Zealand, which is a predominantly agricultural catchment with medium to high groundwater recharge potential. The approach comprised a digital filtering technique to separate baseflow from total stream flow, machine learning to predict a baseflow index (BFI) for all streams with Strahler 1st order and higher, and hydrological modelling to partition the flow into five flow components: surface runoff, interflow, tile drainage, shallow groundwater, and deep groundwater. The baseflow index scores corroborated the spatial distributions of the flow pathways modelled in 1st order catchments. Average depth to groundwater data matched well with BFI and Hydrological Predictions for the Environment (HYPE) modeled flow pathway partitioning results, with deeper water tables in areas of the catchment predicted to have greater baseflow or shallow and deep groundwater contributions to stream flow. Since direct quantification of flow pathways at catchment-scale is scarce, it is recommended to use soft data and expert knowledge to inform model parameterization and to constrain the model results. The approach developed here is applicable as a screening method in ungauged catchments

Untersuchungen zu biomimetischen Cyclisierungen terpenoider Polyalkene ueber Radikalkationen. Synthese von (#+-#)-3-Hydroxy-spongian-16-on und acyclischer Taxan-Vorstufen

SIGLEAvailable from TIB Hannover: RN 9087(148) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman