Matched wideband low-noise amplifiers for radio astronomy

Two packaged low noise amplifiers for the 0.3–4 GHz frequency range are described. The amplifiers can be operated at temperatures of 300–4 K and achieve noise temperatures in the 5 K range (<0.1 dB noise figure) at 15 K physical temperature. One amplifier utilizes commercially available, plastic-packaged SiGe transistors for first and second stages; the second amplifier is identical except it utilizes an experimental chip transistor as the first stage. Both amplifiers use resistive feedback to provide input reflection coefficient S11<−10 dB over a decade bandwidth with gain over 30 dB. The amplifiers can be used as rf amplifiers in very low noise radio astronomy systems or as i.f. amplifiers following superconducting mixers operating in the millimeter and submillimeter frequency range

Cryogenic MMIC low noise amplifiers

Monolithic (MMIC) and discrete transistor (MIC) low noise amplifiers are compared on the basis of performance, cost, and reliability. The need for cryogenic LNA’s for future large microwave arrays for radio astronomy is briefly discussed and data is presented on a prototype LNA for the 1 to 10 GHz range along with a very wideband LNA for the 1 to 60 GHz range. A table of MMIC LNA and mixer designs under development for the frequencies up to 210 GHz is reported and data on cryogenic amplifiers in the 85 to 115 GHz is reviewed. The current status of the topics of transconductance fluctuations and cryogenic noise modeling will be briefly summarized

Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.

Purpose:To apply computational techniques to wide-angle swept-source optical coherence tomography (SS-OCT) images to identify novel, glaucoma-related structural features and improve detection of glaucoma and prediction of future glaucomatous progression. Methods:Wide-angle SS-OCT, OCT circumpapillary retinal nerve fiber layer (cpRNFL) circle scans spectral-domain (SD)-OCT, standard automated perimetry (SAP), and frequency doubling technology (FDT) visual field tests were completed every 3 months for 2 years from a cohort of 28 healthy participants (56 eyes) and 93 glaucoma participants (179 eyes). RNFL thickness maps were extracted from segmented SS-OCT images and an unsupervised machine learning approach based on principal component analysis (PCA) was used to identify novel structural features. Area under the receiver operating characteristic curve (AUC) was used to assess diagnostic accuracy of RNFL PCA for detecting glaucoma and progression compared to SAP, FDT, and cpRNFL measures. Results:The RNFL PCA features were significantly associated with mean deviation (MD) in both SAP (R2 = 0.49, P &lt; 0.0001) and FDT visual field testing (R2 = 0.48, P &lt; 0.0001), and with mean circumpapillary RNFL thickness (cpRNFLt) from SD-OCT (R2 = 0.58, P &lt; 0.0001). The identified features outperformed each of these measures in detecting glaucoma with an AUC of 0.95 for RNFL PCA compared to an 0.90 for mean cpRNFLt (P = 0.09), 0.86 for SAP MD (P = 0.034), and 0.83 for FDT MD (P = 0.021). Accuracy in predicting progression was also significantly higher for RNFL PCA compared to SAP MD, FDT MD, and mean cpRNFLt (P = 0.046, P = 0.007, and P = 0.044, respectively). Conclusions:A computational approach can identify structural features that improve glaucoma detection and progression prediction

Exploring the next generation Deep Space Network

As the current 70-meter antennas are quite old (28-35 years) it is necessary to consider replacing these antennas in the near term as well as providing a capability beyond 70-meters in the future. A study was conducted that investigated the remaining service life of the existing antennas and considered alternatives for eventual replacement of the 70 m-subnet capability. This paper examines several of the concepts considered and explores some of the options for the next generation Deep Space Network

Exiting shelter: an epidemiological analysis of barriers and facilitators for families

This study examines the role of individual- and family-level factors in predicting the length of shelter stays for homeless families. Interviews were conducted with all families exiting one of six emergency family shelters in Worcester, Massachusetts, between November 2006, and November 2007. Analyses, using an ordinary least squares regression model, find that families with a positive alcohol or drug screen in the year prior stay 85 days longer than those without a positive screen; families leaving shelter with a housing subsidy stay 66 days longer than those leaving without a subsidy.Demographic factors, education, employment, health, and mental health are not found to predict shelter stay duration. Consistent with prior research, housing resources relate to families\u27 time in shelter; with the exception of a positive substance abuse screen, individual-level problems are not related to their time in shelter. Efforts to expand these resources at the local, state, and national levels are a high priority

Circuit Theory

Contains reports on three research projects.Lincoln Laboratory (Purchase Order DDL-B222)United States Department of the ArmyUnited States Department of the NavyUnited States Department of the Air Force (Contract AF19(604)-5200

Implementation and evaluation of the VA DPP clinical demonstration: protocol for a multi-site non-randomized hybrid effectiveness-implementation type III trial.

BackgroundThe Diabetes Prevention Program (DPP) study showed that lifestyle intervention resulted in a 58% reduction in incidence of type 2 diabetes among individuals with prediabetes. Additional large randomized controlled trials have confirmed these results, and long-term follow-up has shown sustained benefit 10-20 years after the interventions ended. Diabetes is a common and costly disease, especially among Veterans, and despite strong evidence supporting the feasibility of type 2 diabetes prevention, the DPP has not been widely implemented. The first aim of this study will evaluate implementation of the Veterans Affairs (VA) DPP in three VA medical centers. The second aim will assess weight and hemoglobin A1c (A1c) outcomes, and the third aim will determine the cost-effectiveness and budget impact of implementation of the VA DPP from a health system perspective.Methods/designThis partnered multi-site non-randomized systematic assignment study will use a highly pragmatic hybrid effectiveness-implementation type III mixed methods study design. The implementation and administration of the VA DPP will be funded by clinical operations while the evaluation of the VA DPP will be funded by research grants. Seven hundred twenty eligible Veterans will be systematically assigned to the VA DPP clinical demonstration or the usual care VA MOVE!® weight management program. A multi-phase formative evaluation of the VA DPP implementation will be conducted. A theoretical program change model will be used to guide the implementation process and assess applicability and feasibility of the DPP for VA. The Consolidated Framework for Implementation Research (CFIR) will be used to guide qualitative data collection, analysis, and interpretation of barriers and facilitators to implementation. The RE-AIM framework will be used to assess Reach, Effectiveness, Adoption, Implementation, and Maintenance of the VA DPP. Twelve-month weight and A1c change will be evaluated for the VA DPP compared to the VA MOVE!ProgramMediation analyses will be conducted to identify whether program design differences impact outcomes.DiscussionFindings from this pragmatic evaluation will be highly applicable to practitioners who are tasked with implementing the DPP in clinical settings. In addition, findings will determine the effectiveness and cost-effectiveness of the VA DPP in the Veteran population