Highlights of Nanosatellite Propulsion Development Program at NASA-Goddard Space Flight Center

Currently the GN&C’s Propulsion Branch of the NASA’s Goddard Space Flight Center (GSFC) is conducting a broad technology development program for propulsion devices that are ideally suited for nanosatellite missions. The goal of our program is to develop nanosatellite propulsion systems that can be flight qualified in a few years and flown in support of nanosatellite missions. The miniature cold gas thruster technology, the first product from the GSFC’s propulsion component technology development program, will be flown on the upcoming ST-5 mission in 2003. The ST-5 mission is designed to validate various nanosatellite technologies in all major subsystem areas. It is a precursor mission to more ambitious nanosatellite missions such as the Magnetospheric Constellation mission. By teaming with the industry and government partners, the GSFC propulsion component technology development program is aimed at pursuing a multitude of nanosatellite propulsion options simultaneously, ranging from miniaturized thrusters based on traditional chemical engines to MEMS based thruster systems. After a conceptual study phase to determine the feasibility and the applicability to nanosatellite missions, flight like prototypes of selected technology are fabricated for testing. The development program will further narrow down the effort to those technologies that are considered “mission-enabling” for future nanosatellite missions. These technologies will be flight qualified to be flown on upcoming nanosatellite missions. This paper will report on the status of our development program and provide details on the following technologies: Low power miniature cold gas thruster; Nanosatellite solid rocket motor; Solid propellant gas generator system for cold gas thruster; Low temperature hydrazine blends for miniature hydrazine thruster; MEMS mono propellant thruster using hydrogen peroxide

Predicting nutritional status for women of childbearing age from their economic, health, and demographic features: A supervised machine learning approach

Background Malnutrition imposes enormous costs resulting from lost investments in human capital and increased healthcare expenditures. There is a dearth of research focusing on the prediction of women's body mass index (BMI) and malnutrition outcomes (underweight, overweight, and obesity) in developing countries. This paper attempts to fill out this knowledge gap by predicting the BMI and the risks of malnutrition outcomes for Bangladeshi women of childbearing age from their economic, health, and demographic features. Methods Data from the 2017-18 Bangladesh Demographic and Health Survey and a series of supervised machine learning (SML) techniques are used. Additionally, this study circumvents the imbalanced distribution problem in obesity classification by utilizing an oversampling approach. Results Study findings demonstrate that the support vector machine and k-nearest neighbor are the two best-performing methods in BMI prediction based on the coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The combined predictor algorithms consistently yield top specificity, Cohen's kappa, F1-score, and AUC in classifying the malnutrition status, and their performance is robust to alternative standards. The feature importance ranking based on several nonparametric and combined predictors indicates that socioeconomic status, women's age, and breastfeeding status are the most important features in predicting women's nutritional outcomes. Furthermore, the conditional inference trees corroborate that those three features, along with the partner's educational attainment and employment status, significantly predict malnutrition risks. Conclusion To the best of our knowledge, this is the first study that predicts BMI and one of the pioneer studies to classify all three malnutrition outcomes for women of childbearing age in Bangladesh, let alone in any lower-middle income country, using SML techniques. Moreover, in the context of Bangladesh, this paper is the first to identify and rank features that are critical in predicting nutritional outcomes using several feature selection algorithms. The estimators from this study predict the outcomes of interest most accurately and efficiently compared to other existing studies in the relevant literature. Therefore, study findings can aid policymakers in designing policy and programmatic approaches to address the double burden of malnutrition among Bangladeshi women, thereby reducing the country's economic burden

Characterization of the GlnK protein of Escherichia coli

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75120/1/j.1365-2958.1999.01349.x.pd

Transcriptional regulation of the AP-1 and Nrf2 target gene sulfiredoxin

“Two-cysteine” peroxiredoxins are antioxidant enzymes that exert a cytoprotective effect in many models of oxidative stress. However, under highly oxidizing conditions they can be inactivated through hyperoxidation of their peroxidatic active site cysteine residue. Sulfiredoxin can reverse this hyperoxidation, thus, reactivating peroxiredoxins. Here we review recent investigations that have shed further light on sulfiredoxin’s role and regulation. Studies have revealed sulfiredoxin to be a dynamically regulated gene whose transcription is induced by a variety of signals and stimuli. Sulfiredoxin expression is regulated by the transcription factor AP-1, which mediates its up-regulation by synaptic activity in neurons, resulting in protection against oxidative stress. Furthermore, sulfiredoxin has been identified as a new member of the family of genes regulated by Nuclear factor erythroid 2-related factor (Nrf2) via a conserved cis-acting antioxidant response element (ARE). As such, sulfiredoxin is likely to contribute to the net antioxidative effect of small molecule activators of Nrf2. As discussed here. the proximal AP-1 site of the sulfiredoxin promoter is embedded within the ARE, as is common with Nrf2 target genes. Other recent studies have shown that sulfiredoxin induction via Nrf2 may form an important part of the protective response to oxidative stress in the lung, preventing peroxiredoxin hyperoxidation and, in certain cases, subsequent degradation. We illustrate here that sulfiredoxin can be rapidly induced in vivo by administration of CDDO-TFEA, a synthetic triterpenoid inducer of endogenous Nrf2, which may offer a way of reversing peroxiredoxin hyperoxidation in vivo following chronic or acute oxidative stress

National identity predicts public health support during a global pandemic

Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = −0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.publishedVersio