A Multiple Model Based Approach for Deep Space Power System Fault Diagnosis

Improving protection and health management capabilities onboard the electrical power system (EPS) for spacecraft is essential for ensuring safe and reliable conditions for deep space human exploration. Electrical protection and control technologies on the National Aeronautics and Space Administration's (NASA's) current human space platform relies heavily on ground support to monitor and diagnose power systems and failures. As communication bandwidth diminishes for deep space applications, a transformation in system monitoring and control becomes necessary to maintain high reliability of electric power service. This paper presents a novel approach for on-line power system security monitoring for autonomous deep space spacecraft

Advanced eLectrical Bus (ALBus) CubeSat: From Build to Flight

Advanced eLectrical Bus (ALBus) CubeSat is a technology demonstration mission of a 3-U CubeSat with an advanced digitally controlled electrical power system and novel use of Shape Memory Alloy (SMA) technology for reliable deployable solar array mechanisms. The primary objective was to advance the power management and distribution (PMAD) capabilities to enable future missions requiring more flexible and reliable power systems with higher output power capabilities. Goals included demonstration of 100W distribution to a target electrical load, response to continuous and fast transient power requirements, and exhibition of reliable deployment of solar arrays and antennas utilizing re-settable SMA mechanisms. The power distribution function of the ALBus PMAD system is unique in the total power to target load capability, as power is distributed from batteries to provide 100W of power directly to a resistive load. The deployable solar arrays utilize NASA’s Nickel-Titanium-Palladium-Platinum (NiTiPdPt) high-temperature SMAs for the retention and release mechanism, and a superelastic binary NiTi alloy for the hinge component. The project launched as part of the CubeSat Launch Initiative (CLI) Educational Launch of Nanosatellites (ELaNa) XIX mission on Rocket Lab’s Electron in December 2018. This paper summarizes the final launched design and the lessons learned from build to flight

VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center

The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) represents the 2019 merger of VectorBase with the EuPathDB projects. As a Bioinformatics Resource Center funded by the National Institutes of Health, with additional support from the Welllcome Trust, VEuPathDB supports >500 organisms comprising invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Designed to empower researchers with access to Omics data and bioinformatic analyses, VEuPathDB projects integrate >1700 pre-analysed datasets (and associated metadata) with advanced search capabilities, visualizations, and analysis tools in a graphic interface. Diverse data types are analysed with standardized workflows including an in-house OrthoMCL algorithm for predicting orthology. Comparisons are easily made across datasets, data types and organisms in this unique data mining platform. A new site-wide search facilitates access for both experienced and novice users. Upgraded infrastructure and workflows support numerous updates to the web interface, tools, searches and strategies, and Galaxy workspace where users can privately analyse their own data. Forthcoming upgrades include cloud-ready application architecture, expanded support for the Galaxy workspace, tools for interrogating host-pathogen interactions, and improved interactions with affiliated databases (ClinEpiDB, MicrobiomeDB) and other scientific resources, and increased interoperability with the Bacterial & Viral BRC

Modeling Cannabis Use Disorder Treatment Progression: Evidence of Differential Mechanisms Underlying Functional Improvements

The exclusive focus on abstinence, rigid parameters, and lack of population moderation studies limits evidence of mechanisms of behavior change (MOBCs) that explain functional improvements in cannabis use disorder (CUD) treatments. We aimed to surpass these limitations by examining: 1) two untested non-abstinent MOBCs, 2) end-of-treatment (EOT; i.e., proximal) outcomes simultaneously functioning as MOBCs for follow-up (i.e., distal) outcomes, and 3) gender-moderated outcome predictors and MOBCs. Treatment-seeking individuals with CUD (n = 186; 70.1% male; 57.2% White) between ages 18-50 (M = 30.90, SD = 8.95) participated in a 12-week multi-site clinical trial with a four-week follow-up. We collected self-reported data and creatinine-corrected cannabinoid urine concentrations. We modeled treatment progression using moderated multigroup longitudinal path analyses to examine: H1) if mid-treatment, non-abstinent MOBCs (craving and use reductions) mediated the direct effect of CUD severity at the screening visit on proximal outcomes (anxiety, depression, and cannabis-related problems), H2) if proximal outcomes mediated the direct effect of mid-treatment MOBCs on a four-week distal outcome (quality of life challenges), and H3) if gender moderated these effects. We found that craving reduction may be a MOBC for the full and men samples. In women, depression may concurrently function as a proximal outcome and MOBC for quality of life challenges (distal outcome). Further, gender-moderated outcome predictors and MOBCs; for men, it may be craving reduction, and for women, reduced cannabis use. These nontraditional, differential explanations of functional improvements suggest that our understanding of CUD treatments may be more nuanced than currently indicated in the literature

A Control Framework for Autonomous Smart Grids for Space Power Applications

With the National Aeronautics and Space Administration's (NASA) rising interest in lunar surface operations and deep space exploration, there is a growing need to move from traditional ground-based mission operations to more autonomous vehicle level operations. In lunar surface operations, there are periods of time where communications with ground-based mission control could not occur, forcing vehicles and a lunar base to completely operate independent of the ground. For deep space exploration missions, communication latency times increase to greater than 15 minutes making real-time control of critical systems difficult, if not near impossible. These challenges are driving the need for an autonomous power control system that has the capability to manage power and energy. This will ensure that critical loads have the necessary power to support life systems and carry out critical mission objectives. This paper presents a flexible, hierarchical, distributed control methodology that enables autonomous operation of smart grids and can integrate into a higher level autonomous architecture