Post-Flight Evaluation of Stardust PICA Forebody Heatshield Material

This presentation was part of the session : Sample Return ChallengesSixth International Planetary Probe WorkshopPhenolic Impregnated Carbon Ablator (PICA) was developed at NASA Ames Research Center under the lightweight ceramic ablator development program in the '80s. PICA has the advantages of low density (~ 0.27g/cc) coupled with efficient ablative capability at high heat fluxes making PICA an enabling technology for the Stardust mission. Three cores at key locations were extracted from the forebody heatshield of the Stardust Sample Return Capsule (SRC) post flight and evaluated. Core locations include a near stagnation core, a flank core and a segment taken from the shoulder of the heatshield. Evaluation included density profiles, recession determination, thermal analysis profile, PICA bondline examination, strength of remaining virgin PICA, emissivity profile, chemical analysis profile and microstructural analysis. Comparisons between experimental density profiles and profiles derived from FIAT, a tool used to predict ablative performance, are in good agreement. Recession comparisons from measured values and FIAT predictions are currently being obtained. In addition a laser scanning tool developed at ARC is being used to evaluate recession measurements and compare to experimental and predicted values. In general, the PICA material examined in the cores is in good condition and intact. Impact damage is not evident and the main degradation observed was that caused by heating on entry. A substantial amount of "virgin" PICA was present in all cores examined. It is noted that the post-flight analysis of the Stardust heat shield is especially important since PICA is baselined for both the Orion (CEV) and Mars Science Laboratory vehicles.NASA; NESC; Orion Thermal Protection System Advanced Development Projec

A Composite Analysis of Flowering Time Regulation in Lettuce

Plants undergo profound physiological changes when transitioning from vegetative to reproductive growth. These changes affect crop production, as in the case of leafy vegetables. Lettuce is one of the most valuable leafy vegetable crops in the world. Past genetic studies have identified multiple quantitative trait loci (QTLs) that affect the timing of the floral transition in lettuce. Extensive functional molecular studies in the model organism Arabidopsis provide the opportunity to transfer knowledge to lettuce to explore the mechanisms through which genetic variations translate into changes in flowering time. In this review, we integrated results from past genetic and molecular studies for flowering time in lettuce with orthology and functional inference from Arabidopsis. This summarizes the basis for all known genetic variation underlying the phenotypic diversity of flowering time in lettuce and how the genetics of flowering time in lettuce projects onto the established pathways controlling flowering time in plants. This comprehensive overview reveals patterns across experiments as well as areas in need of further study. Our review also represents a resource for developing cultivars with delayed flowering time

PhytoOracle: Scalable, modular phenomics data processing pipelines

As phenomics data volume and dimensionality increase due to advancements in sensor technology, there is an urgent need to develop and implement scalable data processing pipelines. Current phenomics data processing pipelines lack modularity, extensibility, and processing distribution across sensor modalities and phenotyping platforms. To address these challenges, we developed PhytoOracle (PO), a suite of modular, scalable pipelines for processing large volumes of field phenomics RGB, thermal, PSII chlorophyll fluorescence 2D images, and 3D point clouds. PhytoOracle aims to (i) improve data processing efficiency; (ii) provide an extensible, reproducible computing framework; and (iii) enable data fusion of multi-modal phenomics data. PhytoOracle integrates open-source distributed computing frameworks for parallel processing on high-performance computing, cloud, and local computing environments. Each pipeline component is available as a standalone container, providing transferability, extensibility, and reproducibility. The PO pipeline extracts and associates individual plant traits across sensor modalities and collection time points, representing a unique multi-system approach to addressing the genotype-phenotype gap. To date, PO supports lettuce and sorghum phenotypic trait extraction, with a goal of widening the range of supported species in the future. At the maximum number of cores tested in this study (1,024 cores), PO processing times were: 235 minutes for 9,270 RGB images (140.7 GB), 235 minutes for 9,270 thermal images (5.4 GB), and 13 minutes for 39,678 PSII images (86.2 GB). These processing times represent end-to-end processing, from raw data to fully processed numerical phenotypic trait data. Repeatability values of 0.39-0.95 (bounding area), 0.81-0.95 (axis-aligned bounding volume), 0.79-0.94 (oriented bounding volume), 0.83-0.95 (plant height), and 0.81-0.95 (number of points) were observed in Field Scanalyzer data. We also show the ability of PO to process drone data with a repeatability of 0.55-0.95 (bounding area)

Genome assembly with in vitro proximity ligation data and whole-genome triplication in lettuce.

Lettuce (Lactuca sativa) is a major crop and a member of the large, highly successful Compositae family of flowering plants. Here we present a reference assembly for the species and family. This was generated using whole-genome shotgun Illumina reads plus in vitro proximity ligation data to create large superscaffolds; it was validated genetically and superscaffolds were oriented in genetic bins ordered along nine chromosomal pseudomolecules. We identify several genomic features that may have contributed to the success of the family, including genes encoding Cycloidea-like transcription factors, kinases, enzymes involved in rubber biosynthesis and disease resistance proteins that are expanded in the genome. We characterize 21 novel microRNAs, one of which may trigger phasiRNAs from numerous kinase transcripts. We provide evidence for a whole-genome triplication event specific but basal to the Compositae. We detect 26% of the genome in triplicated regions containing 30% of all genes that are enriched for regulatory sequences and depleted for genes involved in defence

Learning cooking skills at different ages: a cross-sectional study

Background Cooking skills are increasingly included in strategies to prevent and reduce chronic diet-related diseases and obesity. While cooking interventions target all age groups (Child, Teen and Adult), the optimal age for learning these skills on: 1) skills retention, 2) cooking practices, 3) cooking attitudes, 4) diet quality and 5) health is unknown. Similarly, although the source of learning cooking skills has been previously studied, the differences in learning from these different sources has not been considered. This research investigated the associations of the age and source of learning with the aforementioned five factors. Methods A nationally representative (Northern/Republic of Ireland) cross-sectional survey was undertaken with 1049 adults aged between 20–60 years. The survey included both measures developed and tested by the researchers as well as validated measures of cooking (e.g. chopping) and food skills (e.g. budgeting), cooking practices (e.g. food safety), cooking attitudes, diet quality and health. Respondents also stated when they learnt the majority of their skills and their sources of learning. The data was analysed using ANOVAs with post-hoc analysis and Chi2 crosstabs with a significance level of 0.05. Results Results showed that child (<12 years) and/or teen (13–18 years) learners had significantly greater numbers of, and confidence in, their cooking and food skills, cooking practices, cooking attitudes, diet quality (with the exception of fibre intake where adult learners were higher) and health. Mother was the primary source of learning and those who learnt only from this source had significantly better outcomes on 12 of the 23 measures. Conclusions This research highlights the importance of learning cooking skills at an early age for skill retention, confidence, cooking practices, cooking attitude and diet quality. Mother remained the primary source of learning, however, as there is a reported deskilling of domestic cooks, mothers may no longer have the ability to teach cooking skills to the next generation. A focus on alternative sources including practical cooking skills education starting at an early age is required. This study also highlights the need for further longitudinal research on the impact of age and source of learning on cooking skills