NASA Operational Simulator for SmallSats (NOS3) – Design Reference Mission

The NASA Operational Simulator for Small Satellites (NOS3) has undergone significant advances including updating the framework to be component based and expanding the open-source code to include a generic design reference mission to enable advanced technologies. This paper details the changes to the framework as well as a number of innovative use-cases the team is currently supporting such as 1) the expansion of NOS3 to support distributed systems missions in collaboration with NASA GSFC, 2) the integration of NASA JPL’s Science Yield improvemeNt via Onboard Prioritization and Summary of Information Systems (SYNOPSIS) for on-orbit science data prioritization, and 3) the inclusion of NASA IV&V JSTAR’s software-only CCSDS encryption library (CryptoLib). NOS3 continues to serve the SmallSat community by providing an open-source digital twin that can significantly reduce costs associated with spacecraft software development, test, and operations. The NOS3 team plans to continue to expand the resources available to the community and partner with others to resolve issues and add new features requested via the NASA GitHub

The Simeck Family of Lightweight Block Ciphers

Two lightweight block cipher families, SIMON and SPECK, have been proposed by researchers from the NSA recently. In this paper, we introduce Simeck, a new family of lightweight block ciphers that combines the good design components from both SIMON and SPECK, in order to devise even more compact and efficient block ciphers. For Simeck32/64, we can achieve 505 GEs (before the Place and Route phase) and 549 GEs (after the Place and Route phase), with the power consumption of 0.417 $\mu W$ in CMOS 130nm ASIC, and 454 GEs (before the Place and Route phase) and 488 GEs (after the Place and Route phase), with the power consumption of 1.292 $\mu W$ in CMOS 65nm ASIC. Furthermore, all of the instances of Simeck are smaller than the ones of hardware-optimized cipher SIMON in terms of area and power consumption in both CMOS 130nm and CMOS 65nm techniques. In addition, we also give the security evaluation of Simeck with respect to many traditional cryptanalysis methods, including differential attacks, linear attacks, impossible differential attacks, meet-in-the-middle attacks, and slide attacks. Overall, all of the instances of Simeck can satisfy the area, power, and throughput requirements in passive RFID tags

Actionable Cytopathogenic Host Responses of Human Alveolar Type 2 Cells to SARS-CoV-2

Human transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causative pathogen of the COVID-19 pandemic, exerts a massive health and socioeconomic crisis. The virus infects alveolar epithelial type 2 cells (AT2s), leading to lung injury and impaired gas exchange, but the mechanisms driving infection and pathology are unclear. We performed a quantitative phosphoproteomic survey of induced pluripotent stem cell-derived AT2s (iAT2s) infected with SARS-CoV-2 at air-liquid interface (ALI). Time course analysis revealed rapid remodeling of diverse host systems, including signaling, RNA processing, translation, metabolism, nuclear integrity, protein trafficking, and cytoskeletal-microtubule organization, leading to cell cycle arrest, genotoxic stress, and innate immunity. Comparison to analogous data from transformed cell lines revealed respiratory-specific processes hijacked by SARS-CoV-2, highlighting potential novel therapeutic avenues that were validated by a high hit rate in a targeted small molecule screen in our iAT2 ALI system. [Display omitted] •SARS-CoV-2 infection in induced lung cells is characterized by phosphoproteomics•Analysis of response reveals host cell signaling and protein expression profile•Comparison to studies in undifferentiated cell lines shows unique pathology in iAT2s•Systems-level predictions find druggable pathways that can impede viral life cycle Hekman et al. describe how a layer of primary stem cells (iAT2s) recapitulating lung biology responds to infection with SARS-CoV-2. They compare their work to previous studies with immortalized cell lines. Their data predict what effect the virus has on a lung cell and which drugs may slow infection