Direct Electrolysis of Molten Lunar Regolith for the Production of Oxygen and Metals on the Moon

When considering the construction of a lunar base, the high cost ($100,000 a kilogram) of transporting materials to the surface of the moon is a significant barrier. Therefore in-situ resource utilization will be a key component of any lunar mission. Oxygen gas is a key resource, abundant on earth and absent on the moon. If oxygen could be produced on the moon, this provides a dual benefit. Not only does it no longer need to be transported to the surface for breathing purposes; it can also be used as a fuel oxidizer to support transportation of crew and other materials more cheaply between the surface of the moon, and lower earth orbit (approximately$20,000/kg). To this end a stable, robust (lightly manned) system is required to produce oxygen from lunar resources. Herein, we investigate the feasibility of producing oxygen, which makes up almost half of the weight of the moon by direct electrolysis of the molten lunar regolith thus achieving the generation of usable oxygen gas while producing primarily iron and silicon at the cathode from the tightly bound oxides. The silicate mixture (with compositions and mechanical properties corresponding to that of lunar regolith) is melted at temperatures near 1600 C. With an inert anode and suitable cathode, direct electrolysis (no supporting electrolyte) of the molten silicate is carried out, resulting in production of molten metallic products at the cathode and oxygen gas at the anode. The effect of anode material, sweep rate, and electrolyte composition on the electrochemical behavior was investigated and implications for scale-up are considered. The activity and stability of the candidate anode materials as well as the effect of the electrolyte composition were determined. Additionally, ex-situ capture and analysis of the anode gas to calculate the current efficiency under different voltages, currents and melt chemistries was carried out

Radiation hardness of CMS pixel barrel modules

Pixel detectors are used in the innermost part of the multi purpose experiments at LHC and are therefore exposed to the highest fluences of ionising radiation, which in this part of the detectors consists mainly of charged pions. The radiation hardness of all detector components has thoroughly been tested up to the fluences expected at the LHC. In case of an LHC upgrade, the fluence will be much higher and it is not yet clear how long the present pixel modules will stay operative in such a harsh environment. The aim of this study was to establish such a limit as a benchmark for other possible detector concepts considered for the upgrade. As the sensors and the readout chip are the parts most sensitive to radiation damage, samples consisting of a small pixel sensor bump-bonded to a CMS-readout chip (PSI46V2.1) have been irradiated with positive 200 MeV pions at PSI up to 6E14 Neq and with 21 GeV protons at CERN up to 5E15 Neq. After irradiation the response of the system to beta particles from a Sr-90 source was measured to characterise the charge collection efficiency of the sensor. Radiation induced changes in the readout chip were also measured. The results show that the present pixel modules can be expected to be still operational after a fluence of 2.8E15 Neq. Samples irradiated up to 5E15 Neq still see the beta particles. However, further tests are needed to confirm whether a stable operation with high particle detection efficiency is possible after such a high fluence.Comment: Contribution to the 11th European Symposium on Semiconductor Detectors June 7-11, 2009 Wildbad Kreuth, German

Detecting disease-associated genes with confounding variable adjustment and the impact on genomic meta-analysis: With application to major depressive disorder

<p>Abstract</p> <p>Background</p> <p>Detecting candidate markers in transcriptomic studies often encounters difficulties in complex diseases, particularly when overall signals are weak and sample size is small. Covariates including demographic, clinical and technical variables are often confounded with the underlying disease effects, which further hampers accurate biomarker detection. Our motivating example came from an analysis of five microarray studies in major depressive disorder (MDD), a heterogeneous psychiatric illness with mostly uncharacterized genetic mechanisms.</p> <p>Results</p> <p>We applied a random intercept model to account for confounding variables and case-control paired design. A variable selection scheme was developed to determine the effective confounders in each gene. Meta-analysis methods were used to integrate information from five studies and post hoc analyses enhanced biological interpretations. Simulations and application results showed that the adjustment for confounding variables and meta-analysis improved detection of biomarkers and associated pathways.</p> <p>Conclusions</p> <p>The proposed framework simultaneously considers correction for confounding variables, selection of effective confounders, random effects from paired design and integration by meta-analysis. The approach improved disease-related biomarker and pathway detection, which greatly enhanced understanding of MDD neurobiology. The statistical framework can be applied to similar experimental design encountered in other complex and heterogeneous diseases.</p

Macroscopic Quantum Tunnelling in Rotating Bose-Einstein Condensates

In this paper we investigate the macroscopic quantum tunnelling and the phase coherence property of the rotating Bose-Einstein condensates in both static and dynamic cases by using the mean field theory.Comment: 10 pages, 1 figure, submitted to Phys.Rev.

Age-Related Gene Expression in the Frontal Cortex Suggests Synaptic Function Changes in Specific Inhibitory Neuron Subtypes

Genome-wide expression profiling of the human brain has revealed genes that are differentially expressed across the lifespan. Characterizing these genes adds to our understanding of both normal functions and pathological conditions. Additionally, the specific cell-types that contribute to the motor, sensory and cognitive declines during aging are unclear. Here we test if age-related genes show higher expression in specific neural cell types. Our study leverages data from two sources of murine single-cell expression data and two sources of age-associations from large gene expression studies of postmortem human brain. We used nonparametric gene set analysis to test for age-related enrichment of genes associated with specific cell-types; we also restricted our analyses to specific gene ontology groups. Our analyses focused on a primary pair of single-cell expression data from the mouse visual cortex and age-related human post-mortem gene expression information from the orbitofrontal cortex. Additional pairings that used data from the hippocampus, prefrontal cortex, somatosensory cortex and blood were used to validate and test specificity of our findings. We found robust age-related up-regulation of genes that are highly expressed in oligodendrocytes and astrocytes, while genes highly expressed in layer 2/3 glutamatergic neurons were down-regulated across age. Genes not specific to any neural cell type were also down-regulated, possibly due to the bulk tissue source of the age-related genes. A gene ontology-driven dissection of the cell-type enriched genes highlighted the strong down-regulation of genes involved in synaptic transmission and cell-cell signaling in the Somatostatin (Sst) neuron subtype that expresses the cyclin dependent kinase 6 (Cdk6) and in the vasoactive intestinal peptide (Vip) neuron subtype expressing myosin binding protein C, slow type (Mybpc1). These findings provide new insights into cell specific susceptibility to normal aging, and suggest age-related synaptic changes in specific inhibitory neuron subtypes