Volumetric plasma source development and characterization.

The development of plasma sources with densities and temperatures in the 10{sup 15}-10{sup 17} cm{sup -3} and 1-10eV ranges which are slowly varying over several hundreds of nanoseconds within several cubic centimeter volumes is of interest for applications such as intense electron beam focusing as part of the x-ray radiography program. In particular, theoretical work [1,2] suggests that replacing neutral gas in electron beam focusing cells with highly conductive, pre-ionized plasma increases the time-averaged e-beam intensity on target, resulting in brighter x-ray sources. This LDRD project was an attempt to generate such a plasma source from fine metal wires. A high voltage (20-60kV), high current (12-45kA) capacitive discharge was sent through a 100 {micro}m diameter aluminum wire forming a plasma. The plasma's expansion was measured in time and space using spectroscopic techniques. Lineshapes and intensities from various plasma species were used to determine electron and ion densities and temperatures. Electron densities from the mid-10{sup 15} to mid-10{sup 16} cm{sup -3} were generated with corresponding electron temperatures of between 1 and 10eV. These parameters were measured at distances of up to 1.85 cm from the wire surface at times in excess of 1 {micro}s from the initial wire breakdown event. In addition, a hydrocarbon plasma from surface contaminants on the wire was also measured. Control of these contaminants by judicious choice of wire material, size, and/or surface coating allows for the ability to generate plasmas with similar density and temperature to those given above, but with lower atomic masses

Machine Learning Approach for Prescriptive Plant Breeding

We explored the capability of fusing high dimensional phenotypic trait (phenomic) data with a machine learning (ML) approach to provide plant breeders the tools to do both in-season seed yield (SY) prediction and prescriptive cultivar development for targeted agro-management practices (e.g., row spacing and seeding density). We phenotyped 32 SoyNAM parent genotypes in two independent studies each with contrasting agro-management treatments (two row spacing, three seeding densities). Phenotypic trait data (canopy temperature, chlorophyll content, hyperspectral reflectance, leaf area index, and light interception) were generated using an array of sensors at three growth stages during the growing season and seed yield (SY) determined by machine harvest. Random forest (RF) was used to train models for SY prediction using phenotypic traits (predictor variables) to identify the optimal temporal combination of variables to maximize accuracy and resource allocation. RF models were trained using data from both experiments and individually for each agro-management treatment. We report the most important traits agnostic of agro-management practices. Several predictor variables showed conditional importance dependent on the agro-management system. We assembled predictive models to enable in-season SY prediction, enabling the development of a framework to integrate phenomics information with powerful ML for prediction enabled prescriptive plant breeding

Comprehensive molecular characterization of the hippo signaling pathway in cancer

Hippo signaling has been recognized as a key tumor suppressor pathway. Here, we perform a comprehensive molecular characterization of 19 Hippo core genes in 9,125 tumor samples across 33 cancer types using multidimensional “omic” data from The Cancer Genome Atlas. We identify somatic drivers among Hippo genes and the related microRNA (miRNA) regulators, and using functional genomic approaches, we experimentally characterize YAP and TAZ mutation effects and miR-590 and miR-200a regulation for TAZ. Hippo pathway activity is best characterized by a YAP/TAZ transcriptional target signature of 22 genes, which shows robust prognostic power across cancer types. Our elastic-net integrated modeling further reveals cancer-type-specific pathway regulators and associated cancer drivers. Our results highlight the importance of Hippo signaling in squamous cell cancers, characterized by frequent amplification of YAP/TAZ, high expression heterogeneity, and significant prognostic patterns. This study represents a systems-biology approach to characterizing key cancer signaling pathways in the post-genomic era

Absolute calibration method for fast-streaked, fiber optic light collection, spectroscopy systems.

This report outlines a convenient method to calibrate fast (<1ns resolution) streaked, fiber optic light collection, spectroscopy systems. Such a system is used to collect spectral data on plasmas generated in the A-K gap of electron beam diodes fielded on the RITS-6 accelerator (8-12MV, 140-200kA). On RITS, light is collected through a small diameter (200 micron) optical fiber and recorded on a fast streak camera at the output of 1 meter Czerny-Turner monochromator (F/7 optics). To calibrate such a system, it is necessary to efficiently couple light from a spectral lamp into a 200 micron diameter fiber, split it into its spectral components, with 10 Angstroms or less resolution, and record it on a streak camera with 1ns or less temporal resolution