OAO-3 end of mission tests report

Twelve engineering type tests were performed on several subsystems and experiment(s) of the OAO 3 spacecraft near its end of mission. The systems tested include: Princeton experiment package (PEP), fine error system guidance, inertial reference unit, star trackers, heat pipes, thermal control coatings, command and data handling, solar array; batteries, and onboard processor/power boost regulator. Generally, the systems performed well for the 8 1/2 years life of OAO 3, although some degradation was noted in the sensitivity of PEP and in the absorptivity of the skin coatings. Battery life was prolonged during the life of the mission in large part by carefully monitoring the charge-discharge cycle with careful attention not to overcharge

Ariel - Volume 8 Number 2

Executive Editor James W. Lockard , Jr. Issue Editor Doug Hiller Business Manager Neeraj K. Kanwal University News Richard J. Perry World News Doug Hiller Opinions Elizabeth A. McGuire Features Patrick P. Sokas Sports Desk Shahab S. Minassian Managing Editor Edward H. Jasper Managing Associate Brenda Peterson Photography Editor Robert D. Lehman, Jr. Graphics Christine M. Kuhnl

Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms

Importance: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective: To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants: In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements: Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. Results: Overall, 144 231 screening mammograms from 85 580 US women (952 cancer positive ≤12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166 578 examinations from 68 008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance: While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation

Physiologic Responses to Dietary Sulfur Amino Acid Restriction in Mice Are Influenced by Atf4 Status and Biological Sex

Background: Dietary sulfur amino acid restriction (SAAR) improves body composition and metabolic health across several model organisms in part through induction of the integrated stress response (ISR). Objective: We investigate the hypothesis that activating transcription factor 4 (ATF4) acts as a converging point in the ISR during SAAR. Methods: Using liver-specific or global gene ablation strategies, in both female and male mice, we address the role of ATF4 during dietary SAAR. Results: We show that ATF4 is dispensable in the chronic induction of the hepatokine fibroblast growth factor 21 while being essential for the sustained production of endogenous hydrogen sulfide. We also affirm that biological sex, independent of ATF4 status, is a determinant of the response to dietary SAAR. Conclusions: Our results suggest that auxiliary components of the ISR, which are independent of ATF4, are critical for SAAR-mediated improvements in metabolic health in mice

Heritability and Artificial Selection on Ambulatory Dispersal Distance in Tetranychus urticae: Effects of Density and Maternal Effects

Dispersal distance is understudied although the evolution of dispersal distance affects the distribution of genetic diversity through space. Using the two-spotted spider mite, Tetranychus urticae, we tested the conditions under which dispersal distance could evolve. To this aim, we performed artificial selection based on dispersal distance by choosing 40 individuals (out of 150) that settled furthest from the home patch (high dispersal, HDIS) and 40 individuals that remained close to the home patch (low dispersal, LDIS) with three replicates per treatment. We did not observe a response to selection nor a difference between treatments in life-history traits (fecundity, survival, longevity, and sex-ratio) after ten generations of selection. However, we show that heritability for dispersal distance depends on density. Heritability for dispersal distance was low and non-significant when using the same density as the artificial selection experiments while heritability becomes significant at a lower density. Furthermore, we show that maternal effects may have influenced the dispersal behaviour of the mites. Our results suggest primarily that selection did not work because high density and maternal effects induced phenotypic plasticity for dispersal distance. Density and maternal effects may affect the evolution of dispersal distance and should be incorporated into future theoretical and empirical studies

Changing MFTF vacuum environment

The Mirror Fusion Test Facility (MFTF) vacuum vessel will be about 60m long and 10m in diameter at the widest point. The allowable operating densities range from 2 x 10/sup 9/ to 5 x 10/sup 10/ particles per cc. The maximum leak rate of 10/sup -6/ tl/sec is dominated during operation by the deliberately injected cold gas of 250 tl/sec. This gas is pumped by over 1000 square meters of cryopanels, external sorption pumps and getters. The design and requirements have changed radically over the past several years, and they are still not in final form. The vacuum system design has also changed, but more slowly and less radically. This paper discusses the engineering effort necessary to meet these stringent and changing requirements. Much of the analysis of the internal systems has been carried out using a 3-D Monte Carlo computer code, which can estimate time dependent operational pressures. This code and its use will also be described