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

Tiebreaker: Certification and Multiple Credit Ratings

This paper explores the economic role credit rating agencies play in the corporate bond market. We consider three existing theories about multiple ratings: information production, rating shopping and regulatory certification. Using differences in rating composition, default prediction and credit spread changes, our evidence only supports regulatory certification. Marginal, additional credit ratings are more likely to occur because of, and seem to matter primarily for regulatory purposes, but do not seem to provide significant additional information related to credit quality.

HDSDF: Hybrid Directional and Signed Distance Functions for Fast Inverse Rendering

Implicit neural representations of 3D shapes form strong priors that areuseful for various applications, such as single and multiple view 3Dreconstruction. A downside of existing neural representations is that theyrequire multiple network evaluations for rendering, which leads to highcomputational costs. This limitation forms a bottleneck particularly in thecontext of inverse problems, such as image-based 3D reconstruction. To addressthis issue, in this paper (i) we propose a novel hybrid 3D objectrepresentation based on a signed distance function (SDF) that we augment with adirectional distance function (DDF), so that we can predict distances to theobject surface from any point on a sphere enclosing the object. Moreover, (ii)using the proposed hybrid representation we address the multi-view consistencyproblem common in existing DDF representations. We evaluate our novel hybridrepresentation on the task of single-view depth reconstruction and show thatour method is several times faster compared to competing methods, while at thesame time achieving better reconstruction accuracy.<br

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