Laer-induced Breakdown Spectroscopy Instrument for Element Analysis of Planetary Surfaces

One of the most fundamental pieces of information about any planetary body is the elemental and mineralogical composition of its surface materials. We are developing an instrument to obtain such data at ranges of up to several hundreds of meters using the technique of Laser-Induced Breakdown Spectroscopy (LIBS). We envision our instrument being used from a spacecraft in close rendezvous with small bodies such as comets and asteroids, or deployed on surface-rover vehicles on large bodies such as Mars and the Moon. The elemental analysis is based on atomic emission spectroscopy of a laser-induced plasma or spark. A pulsed, diode pumped Nd:YAG laser of several hundred millijoules optical energy is used to vaporize and electronically excite the constituent elements of a rock surface remotely located from the laser. Light emitted from the excited plasma is collected and introduced to the entrance slit of a small grating spectrometer. The spectrally dispersed spark light is detected with either a linear photo diode array or area CCD array. When the latter detector is used, the optical and spectrometer components of the LIBS instrument can also be used in a passive imaging mode to collect and integrate reflected sunlight from the same rock surface. Absorption spectral analysis of this reflected light gives mineralogical information that provides a remote geochemical characterization of the rock surface. We performed laboratory calibrations in air and in vacuum on standard rock powders to quantify the LIBS analysis. We performed preliminary field tests using commercially available components to demonstrate remote LIBS analysis of terrestrial rock surfaces at ranges of over 25 m, and we have demonstrated compatibility with a six-wheeled Russian robotic rover vehicle. Based on these results, we believe that all major and most minor elements expected on planetary surfaces can be measured with absolute accuracy of 10-15 percent and much higher relative accuracy. We have performed preliminary systems analysis of a LIBS instrument to evaluate probable mass and power requirements; results of this analysis are summarized

Iterative graph cuts for image segmentation with a nonlinear statistical shape prior

Shape-based regularization has proven to be a useful method for delineating objects within noisy images where one has prior knowledge of the shape of the targeted object. When a collection of possible shapes is available, the specification of a shape prior using kernel density estimation is a natural technique. Unfortunately, energy functionals arising from kernel density estimation are of a form that makes them impossible to directly minimize using efficient optimization algorithms such as graph cuts. Our main contribution is to show how one may recast the energy functional into a form that is minimizable iteratively and efficiently using graph cuts.Comment: Revision submitted to JMIV (02/24/13

A deep level set method for image segmentation

This paper proposes a novel image segmentation approachthat integrates fully convolutional networks (FCNs) with a level setmodel. Compared with a FCN, the integrated method can incorporatesmoothing and prior information to achieve an accurate segmentation.Furthermore, different than using the level set model as a post-processingtool, we integrate it into the training phase to fine-tune the FCN. Thisallows the use of unlabeled data during training in a semi-supervisedsetting. Using two types of medical imaging data (liver CT and left ven-tricle MRI data), we show that the integrated method achieves goodperformance even when little training data is available, outperformingthe FCN or the level set model alone

Missense mutations at homologous positions in the fourth and fifth laminin A G-like domains of eyes shut homolog cause autosomal recessive retinitis pigmentosa

Purpose: To describe two novel mutations in the eyes shut homolog (EYS) gene in two families with autosomal recessive retinitis pigmentosa (arRP) from Pakistan and Indonesia. Methods: Genome-wide linkage and homozygosity mapping were performed using single nucleotide polymorphism microarray analysis in affected members of the two arRP families. Sequence analysis was performed to identify genetic changes in protein coding exons of EYS. Results: In the Indonesian and Pakistani families, homozygous regions encompassing the EYS gene at 6q12 were identified, with maximum LOD scores of 1.8 and 3.6, respectively. Novel missense variants in the EYS gene (p.D2767Y and p.D3028Y) were found in the Pakistani and Indonesian families, respectively, that co-segregate with the disease phenotype. Interestingly, the missense variants are located at the same homologous position within the fourth and fifth laminin A G-like domains of EYS. Conclusions: To date, mostly protein-truncating mutations have been described in EYS, while only few patients have been described with pathogenic compound heterozygous missense mutations. The mutations p.D2767Y and p.D3028Y described in this study affect highly conserved residues at homologous positions in laminin A G-like domains and support the notion that missense mutations in EYS can cause arRP

A theoretical and numerical study of a phase field higher-order active contour model of directed networks.

We address the problem of quasi-automatic extraction of directed networks, which have characteristic geometric features, from images. To include the necessary prior knowledge about these geometric features, we use a phase field higher-order active contour model of directed networks. The model has a large number of unphysical parameters (weights of energy terms), and can favour different geometric structures for different parameter values. To overcome this problem, we perform a stability analysis of a long, straight bar in order to find parameter ranges that favour networks. The resulting constraints necessary to produce stable networks eliminate some parameters, replace others by physical parameters such as network branch width, and place lower and upper bounds on the values of the rest. We validate the theoretical analysis via numerical experiments, and then apply the model to the problem of hydrographic network extraction from multi-spectral VHR satellite images

Potential harmful health effects of inhaling nicotine-free shisha-pen vapor: a chemical risk assessment of the main components propylene glycol and glycerol

Background A shisha-pen is an electronic cigarette variant that is advertised to mimic the taste of a water pipe, or shisha. The aim of this study was to assess the potential harmful health effects caused by inhaling the vapor of a nicotine-free shisha-pen. Methods Gas chromatography analysis was performed to determine the major components in shisha-pen vapor. Risk assessment was performed using puff volumes of e-cigarettes and “normal” cigarettes and a 1-puff scenario (one-time exposure). The concentrations that reached the airways and lungs after using a shisha-pen were calculated and compared to data from published toxicity studies. Results The main components in shisha-pen vapor are propylene glycol and glycerol (54%/46%). One puff (50 to 70 mL) results in exposure of propylene glycol and glycerol of 430 to 603 mg/m3 and 348 to 495 mg/m3, respectively. These exposure concentrations were higher than the points of departure for airway irritation based on a human study (propylene glycol, mean concentration of 309 mg/m3) and a rat study (glycerol, no-observed adverse effect level of 165 mg/m3). Conclusions Already after one puff of the shisha-pen, the concentrations of propylene glycol and glycerol are sufficiently high to potentially cause irritation of the airways. New products such as the shisha-pen should be detected and risks should be assessed to inform regulatory actions aimed at limiting potential harm that may be caused to consumers and protecting young people to take up smoking

New <i>Methyloceanibacter</i> diversity from North Sea sediments includes methanotroph containing solely the soluble methane monooxygenase

Marine methylotrophs play a key role in the global carbon cycle by metabolizing reduced one-carbon compounds that are found in high concentrations in marine environments. Genome, physiology and diversity studies have been greatly facilitated by the numerous model organisms brought into culture. However, the availability of marine representatives remains poor. Here, we report the isolation of four novel species from North Sea sediment enrichments closely related to the Alphaproteobacterium Methyloceanibacter caenitepidi. Each of the newly isolated Methyloceanibacter species exhibited a clear genome sequence divergence which was reflected in physiological differences. Notably one strain R-67174 was capable of oxidizing methane as sole source of carbon and energy using solely a soluble methane monooxygenase and represents the first marine Alphaproteobacterial methanotroph brought into culture. Differences in maximum cell density of >1.5 orders of magnitude were observed. Furthermore, three strains were capable of producing nitrous oxide from nitrate. Together, these findings highlight the metabolic and physiologic variability within closely related Methyloceanibacter species and provide a new understanding of the physiological basis of marine methylotrophy

The application of big data and AI in the upstream supply chain

The use of Big Data has grown in popularity in organisations to exploit the purpose of their primary data to enhance their competitiveness. In conjunction with the increased use of Big Data, there has also been a growth in the use of Artificial Intelligence (AI) to analyse the vast amounts of data generated and provide a mechanism for locating and constructing useable patterns that organisations can incorporate in their supply chain strategy programme. As these organisations embrace the use of technology and embed this in their supply chain strategy, there are questions as to how this may affect their upstream supply chains especially with regards to how SME’s may be able to cope with the potential changes. There exists the opportunity to conduct further research into this area, mainly focusing on three key industry sectors of aerospace, rail and automotive supply chains.N/

Spin orbit effects in a GaAs quantum dot in a parallel magnetic field

We analyze the effects of spin-orbit coupling on fluctuations of the conductance of a quantum dot fabricated in a GaAs heterostructure. We argue that spin-orbit effects may become important in the presence of a large parallel magnetic field B_{||}, even if they are negligble for B_{||}=0. This should be manifest in the level repulsion of a closed dot, and in reduced conductance fluctuations in dots with a small number of open channels in each lead, for large B_{||}. Our picture is consistent with the experimental observations of Folk et al.Comment: 5 page