355 research outputs found
Decision Aid Tool for Selecting Farm Equipment and Estimating Costs of Machinery Complements�
Agricultural Economic
Experimental L-band SST satellite communications/surveillance terminal study. Volume 3 - Communications/surveillance analysis
Analysis of surveillance and communications functions of L band air traffic control satellite syste
Preliminary evaluation of spectral, normal and meteorological crop stage estimation approaches
Several of the projects in the AgRISTARS program require crop phenology information, including classification, acreage and yield estimation, and detection of episodal events. This study evaluates several crop calendar estimation techniques for their potential use in the program. The techniques, although generic in approach, were developed and tested on spring wheat data collected in 1978. There are three basic approaches to crop stage estimation: historical averages for an area (normal crop calendars), agrometeorological modeling of known crop-weather relationships agrometeorological (agromet) crop calendars, and interpretation of spectral signatures (spectral crop calendars). In all, 10 combinations of planting and biostage estimation models were evaluated. Dates of stage occurrence are estimated with biases between -4 and +4 days while root mean square errors range from 10 to 15 days. Results are inconclusive as to the superiority of any of the models and further evaluation of the models with the 1979 data set is recommended
Large Area Crop Inventory Experiment (LACIE). Composition and assembly of a spectral-met data base for spring and winter wheat, volume 2
There are no author-identified significant results in this report
Markers for the identification of late breast cancer recurrence
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited
Decontamination of Genesis Array Materials by UV Ozone Cleaning
Shortly after the NASA Genesis Mission sample return capsule returned to earth on September 8, 2004, the science team discovered that all nine ultra-pure semiconductor materials were contaminated with a thin molecular organic film approximately 0 to 100 angstroms thick. The organic contaminate layer, possibly a silicone, situated on the surface of the materials is speculated to have formed by condensation of organic matter from spacecraft off-gassing at the Lagrange 1 halo orbit during times of solar exposure. While the valuable solar wind atoms are safely secured directly below this organic contamination and/or native oxide layer in approximately the first 1000 angstroms of the ultra-pure material substrate, some analytical techniques that precisely measure solar wind elemental abundances require the removal of this organic contaminate. In 2005, Genesis science team laboratories began to develop various methods for removing the organic thin film without removing the precious material substrate that contained the solar wind atoms. Stephen Sestak and colleagues at Open University first experimented with ultraviolet radiation ozone (UV/O3) cleaning of several non-flight and flown Genesis silicon wafer fragments under a pure flowing oxygen environment. The UV/O3 technique was able to successfully remove organic contamination without etching into the bulk material substrate. At NASA Johnson Space Center Genesis Curation Laboratory, we have installed an UV/O3 cleaning devise in an ambient air environment to further experimentally test the removal of the organic contamination on Genesis wafer materials. Preliminary results from XPS analysis show that the UV/O3 cleaning instrument is a good non-destructive method for removing carbon contamination from flown Genesis array samples. However, spectroscopic ellipsometry results show little change in the thickness of the surface film. All experiments to date have shown UV/O3 cleaning method to be the best non-destructive method for removing organic contamination from the surface of the Genesis materials. The UV/O3 cleaning process can also clean carbon contamination to levels below non-flight standards. This can be seen by comparing sample 60260's carbon 10667 cps with non-flight Si carbon 21675 cps. Therefore, surface carbon contamination should not hinder the analysis of solar wind
Interpretation of LANDSAT digital data using a cubic color model based on relative energies
There are no author-identified significant results in this report
Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®.
Multi-gene prognostic signatures including the Oncotype® DX Recurrence Score (RS), EndoPredict® (EP) and Prosigna® (Risk Of Recurrence, ROR) are widely used to predict the likelihood of distant recurrence in patients with oestrogen-receptor-positive (ER+), HER2-negative breast cancer. Here, we describe the development and validation of methods to recapitulate RS, EP and ROR scores from NanoString expression data. RNA was available from 107 tumours from postmenopausal women with early-stage, ER+, HER2- breast cancer from the translational Arimidex, Tamoxifen, Alone or in Combination study (TransATAC) where previously these signatures had been assessed with commercial methodology. Gene expression was measured using NanoString nCounter. For RS and EP, conversion factors to adjust for cross-platform variation were estimated using linear regression. For ROR, the steps to perform subgroup-specific normalisation of the gene expression data and calibration factors to calculate the 46-gene ROR score were assessed and verified. Training with bootstrapping (n = 59) was followed by validation (n = 48) using adjusted, research use only (RUO) NanoString-based algorithms. In the validation set, there was excellent concordance between the RUO scores and their commercial counterparts (rc(RS) = 0.96, 95% CI 0.93-0.97 with level of agreement (LoA) of -7.69 to 8.12; rc(EP) = 0.97, 95% CI 0.96-0.98 with LoA of -0.64 to 1.26 and rc(ROR) = 0.97 (95% CI 0.94-0.98) with LoA of -8.65 to 10.54). There was also a strong agreement in risk stratification: (RS: κ = 0.86, p < 0.0001; EP: κ = 0.87, p < 0.0001; ROR: κ = 0.92, p < 0.001). In conclusion, the calibrated algorithms recapitulate the commercial RS and EP scores on individual biopsies and ROR scores on samples based on subgroup-centreing method using NanoString expression data
Anastrozole for prevention of breast cancer in high-risk postmenopausal women (IBIS-II) : an international, double-blind, randomised placebo-controlled trial
This study was funded by Cancer Research UK (C569/A5032), the National Health and Medical Research Council Australia (GNT300755, GNT569213), Sanofi-Aventis, and AstraZeneca. Sanofi-Aventis and AstraZeneca provided anastrozole and matching placebo. The study sponsor was Queen Mary University of London.Peer reviewedPublisher PD
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