Compatibility of potential reinforcing ceramics with Ni and Fe aluminides

There is a great deal of interest in the possible utilization of intermetallic compounds in advanced high temperature gas turbine engines. These compounds exhibit a variety of promising properties, including reasonable strength, high melting points, relatively low densities, and good corrosion resistance. However, in general, they also show limited ductilities and toughness, and less than optimum creep strengths at elevated temperatures. In addition, in applications involving advanced gas turbine engines, it is often necessary for candidate materials to have large elastic moduli. The present study is part of a program whose objective is to identify a high temperature fiber reinforced composite. The approach adopted was to fabricate laboratory samples of the combinations of materials considered by Misra, in order to determine the extent to which the thermodynamic calculations can predict phase stability. As many of the ceramic phases considered are not currently available in fiber form, they were added as particulates to the alloy matrices. The ways in which the materials were produced and evaluated are described

RNA extraction, probe preparation, and competitive hybridization for transcriptional profiling using Neurospora crassa long-oligomer DNA microarrays

We developed protocols optimized for the performance of experiments assaying genomic gene expression using Neurospora crassa long-oligomer microarrays. We present methods for sample growth and harvesting, total RNA extraction, poly(A)+ mRNA selection, preparation of NH3-Allyl Cy3/Cy5 labeled probes, and microarray hybridization. The quality of the data obtained with these protocols is demonstrated by the comparative transcriptional profiling of basal and apical zones of vegetative growth of N. crassa

Using Bioenergetics and Radar-Derived Bird Abundance to Assess the Impact of a Blackbird Roost on Seasonal Sunflower Damage

Methods aimed at reducing avian damage to agricultural crops are routinely implemented in situations where efficacy can be assessed by quantifying blackbird (Icteridae) abundance relative to environmental variables and extrapolating to ensuing crop damage. Concomitantly, Weather Surveillance Radar (WSR) data may have potential to enhance crop damage mitigation through improved monitoring of nuisance wildlife populations. We used WSR to derive daily abundance estimates of blackbirds at a fall roost in North Dakota, USA from 2012 to 2019. We integrated these estimates with previously developed bioenergetics-economic models to estimate local sunflower (Helianthus annuus) damage. The greatest losses usually occurred during a brief period in October, when peak blackbird abundance coincided with large percentages (\u3e50%) of mature but unharvested sunflower fields. Most sunflower fields were harvested later than peak blackbird abundance (360,000–1,120,000 birds) and maximum daily damages ($900–$2,000 USD per day). This seasonal trend suggests advancing harvest time as a strategy to avoid the greatest losses in yield (up to $1,800 in savings at this 1 roost), which may be attainable by earlier planting of early-maturing crop varieties or crop desiccation

Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse

Counterfactuals operationalised through algorithmic recourse have become a powerful tool to make artificial intelligence systems explainable. Conceptually, given an individual classified as y -- the factual -- we seek actions such that their prediction becomes the desired class y' -- the counterfactual. This process offers algorithmic recourse that is (1) easy to customise and interpret, and (2) directly aligned with the goals of each individual. However, the properties of a "good" counterfactual are still largely debated; it remains an open challenge to effectively locate a counterfactual along with its corresponding recourse. Some strategies use gradient-driven methods, but these offer no guarantees on the feasibility of the recourse and are open to adversarial attacks on carefully created manifolds. This can lead to unfairness and lack of robustness. Other methods are data-driven, which mostly addresses the feasibility problem at the expense of privacy, security and secrecy as they require access to the entire training data set. Here, we introduce LocalFACE, a model-agnostic technique that composes feasible and actionable counterfactual explanations using locally-acquired information at each step of the algorithmic recourse. Our explainer preserves the privacy of users by only leveraging data that it specifically requires to construct actionable algorithmic recourse, and protects the model by offering transparency solely in the regions deemed necessary for the intervention.Comment: 7 pages, 5 figures, 3 appendix page

Jet Noise Modeling for Suppressed and Unsuppressed Aircraft in Simulated Flight

This document describes the development of further extensions and improvements to the jet noise model developed by Modern Technologies Corporation (MTC) for the National Aeronautics and Space Administration (NASA). The noise component extraction and correlation approach, first used successfully by MTC in developing a noise prediction model for two-dimensional mixer ejector (2DME) nozzles under the High Speed Research (HSR) Program, has been applied to dual-stream nozzles, then extended and improved in earlier tasks under this contract. Under Task 6, the coannular jet noise model was formulated and calibrated with limited scale model data, mainly at high bypass ratio, including a limited-range prediction of the effects of mixing-enhancement nozzle-exit chevrons on jet noise. Under Task 9 this model was extended to a wider range of conditions, particularly those appropriate for a Supersonic Business Jet, with an improvement in simulated flight effects modeling and generalization of the suppressor model. In the present task further comparisons are made over a still wider range of conditions from more test facilities. The model is also further generalized to cover single-stream nozzles of otherwise similar configuration. So the evolution of this prediction/analysis/correlation approach has been in a sense backward, from the complex to the simple; but from this approach a very robust capability is emerging. Also from these studies, some observations emerge relative to theoretical considerations. The purpose of this task is to develop an analytical, semi-empirical jet noise prediction method applicable to takeoff, sideline and approach noise of subsonic and supersonic cruise aircraft over a wide size range. The product of this task is an even more consistent and robust model for the Footprint/Radius (FOOTPR) code than even the Task 9 model. The model is validated for a wider range of cases and statistically quantified for the various reference facilities. The possible role of facility effects will thus be documented. Although the comparisons that can be accomplished within the limited resources of this task are not comprehensive, they provide a broad enough sampling to enable NASA to make an informed decision on how much further effort should be expended on such comparisons. The improved finalized model is incorporated into the FOOTPR code. MTC has also supported the adaptation of this code for incorporation in NASA s Aircraft Noise Prediction Program (ANOPP)

Multi-targeted priming for genome-wide gene expression assays

<p>Abstract</p> <p>Background</p> <p>Complementary approaches to assaying global gene expression are needed to assess gene expression in regions that are poorly assayed by current methodologies. A key component of nearly all gene expression assays is the reverse transcription of transcribed sequences that has traditionally been performed by priming the poly-A tails on many of the transcribed genes in eukaryotes with oligo-dT, or by priming RNA indiscriminately with random hexamers. We designed an algorithm to find common sequence motifs that were present within most protein-coding genes of <it>Saccharomyces cerevisiae </it>and of <it>Neurospora crassa</it>, but that were not present within their ribosomal RNA or transfer RNA genes. We then experimentally tested whether degenerately priming these motifs with multi-targeted primers improved the accuracy and completeness of transcriptomic assays.</p> <p>Results</p> <p>We discovered two multi-targeted primers that would prime a preponderance of genes in the genomes of <it>Saccharomyces cerevisiae </it>and <it>Neurospora crassa </it>while avoiding priming ribosomal RNA or transfer RNA. Examining the response of <it>Saccharomyces cerevisiae </it>to nitrogen deficiency and profiling <it>Neurospora crassa </it>early sexual development, we demonstrated that using multi-targeted primers in reverse transcription led to superior performance of microarray profiling and next-generation RNA tag sequencing. Priming with multi-targeted primers in addition to oligo-dT resulted in higher sensitivity, a larger number of well-measured genes and greater power to detect differences in gene expression.</p> <p>Conclusions</p> <p>Our results provide the most complete and detailed expression profiles of the yeast nitrogen starvation response and <it>N. crassa </it>early sexual development to date. Furthermore, our multi-targeting priming methodology for genome-wide gene expression assays provides selective targeting of multiple sequences and counter-selection against undesirable sequences, facilitating a more complete and precise assay of the transcribed sequences within the genome.</p

The Impact of Prior Authorization on Buprenorphine Dose, Relapse and Cost of Opioid Addiction Treatment

This presentation discusses the impact of prior authorization on Buprenorphine dose, relapse, and cost for opioid addiction treatment for Massachusetts Medicaid members. Presented at the AcademyHealth Annual Research Meeting 2013

Monitoring Sustainable Global Development Along Shared Socioeconomic Pathways

Sustainable global development is one of the most prevalent challenges facing the world today, hinging on the equilibrium between socioeconomic growth and environmental sustainability. We propose approaches to monitor and quantify sustainable development along the Shared Socioeconomic Pathways (SSPs), including mathematically derived scoring algorithms, and machine learning methods. These integrate socioeconomic and environmental datasets, to produce an interpretable metric for SSP alignment. An initial study demonstrates promising results, laying the groundwork for the application of different methods to the monitoring of sustainable global development.Comment: 5 pages, 1 figure. Presented at NeurIPS 2023 Workshop: Tackling Climate Change with Machine Learnin

Requirement for PCNA in DNA Mismatch Repair at a Step Preceding DNA Resynthesis

Abstractid system was used to screen yeast and human expression libraries for proteins that interact with mismatch repair proteins. PCNA was recovered from both libraries and shown in the case of yeast to interact with both MLH1 and MSH2. A yeast strain containing a mutation in the PCNA gene had a strongly elevated mutation rate in a dinucleotide repeat, and the rate was not further elevated in a strain also containing a mutation in MLH1. Mismatch repair activity was examined in human cell extracts using an assay that does not require DNA repair synthesis. Activity was inhibited by p21 WAF1 or a p21 peptide, both of which bind to PCNA, and activity was restored to inhibited reactions by addition of PCNA. The data suggest a PCNA requirement in mismatch repair at a step preceding DNA resynthesis. The ability of PCNA to bind to MLH1 and MSH2 may reflect linkage between mismatch repair and replication and may be relevant to the roles of mismatch repair proteins in other DNA transactions