NASA SpaceCube Edge TPU SmallSat Card for Autonomous Operations and Onboard Science-Data Analysis

Using state-of-the-art artificial intelligence (AI)frameworks onboard spacecraft is challenging because common spacecraft processors cannot provide comparable performance to data centers with server-grade CPUs and GPUs available for terrestrial applications and advanced deep-learning networks. This limitation makes small, low-power AI microchip architectures, such as the Google Coral Edge Tensor Processing Unit (TPU), attractive for space missions where the application-specific design enables both high-performance and power-efficient computing for AI applications. To address these challenging considerations for space deployment, this research introduces the design and capabilities of a CubeSat-sized Edge TPU-based co-processor card, known as the SpaceCube Low-power Edge Artificial Intelligence Resilient Node (SC-LEARN). This design conforms to NASA’s CubeSat Card Specification (CS2) for integration into next-generation SmallSat and CubeSat systems. This paper describes the overarching architecture and design of the SC-LEARN, as well as, the supporting test card designed for rapid prototyping and evaluation. The SC-LEARN was developed with three operational modes: (1) a high-performance parallel-processing mode,(2)a fault-tolerant mode for onboard resilience, and (3) a power-saving mode with cold spares. Importantly, this research also elaborates on both training and quantization of TensorFlow models for the SC-LEARN for use onboard with representative, open-source datasets. Lastly, we describe future research plans, including radiation-beam testing and flight demonstration

NASA SpaceCube Intelligent Multi-Purpose System for Enabling Remote Sensing, Communication, and Navigation in Mission Architectures

New, innovative CubeSat mission concepts demand modern capabilities such as artificial intelligence and autonomy, constellation coordination, fault mitigation, and robotic servicing – all of which require vastly more processing resources than legacy systems are capable of providing. Enabling these domains within a scalable, configurable processing architecture is advantageous because it also allows for the flexibility to address varying mission roles, such as a command and data-handling system, a high-performance application processor extension, a guidance and navigation solution, or an instrument/sensor interface. This paper describes the NASA SpaceCube Intelligent Multi-Purpose System (IMPS), which allows mission developers to mix-and-match 1U (10 cm × 10 cm) CubeSat payloads configured for mission-specific needs. The central enabling component of the system architecture to address these concerns is the SpaceCube v3.0 Mini Processor. This single-board computer features the 20nm Xilinx Kintex UltraScale FPGA combined with a radiation-hardened FPGA monitor, and extensive IO to integrate and interconnect varying cards within the system. To unify the re-usable designs within this architecture, the CubeSat Card Standard was developed to guide design of 1U cards. This standard defines pinout configurations, mechanical, and electrical specifications for 1U CubeSat cards, allowing the backplane and mechanical enclosure to be easily extended. NASA has developed several cards adhering to the standard (System-on-Chip, power card, etc.), which allows the flexibility to configure a payload from a common catalog of cards

SpaceCube v3.0 NASA Next-Generation High-Performance Processor for Science Applications

Electronics for space systems must address several considerable challenges including achieving operational resiliency within the hazardous space environment and also meeting application performance needs while simultaneously managing size, weight, and power requirements. To drive the future revolution in space processing, onboard systems need to be more flexible, affordable, and robust. In order to provide a robust solution to a variety of missions and instruments, the Science Data Processing Branch at NASA Goddard Space Flight Center (GSFC)has pioneered a hybrid-processing approach that combines radiation-hardened and commercial components while emphasizing a novel architecture harmonizing the best capabilities of CPUs, DSPs, and FPGAs. This hybrid approach is realized through the SpaceCube family of processor cards that have extensive flight heritage on a variety of mission classes. The latest addition to the SpaceCube family, SpaceCube v3.0, will function as the next evolutionary step for upcoming missions, allow for prototyping of designs and software, and provide a flexible, mature architecture that is also ready to adopt the radiation-hardened High-Performance Spaceflight Computing (HPSC) chiplet when it is released. The research showcased in this paper describes the design methodology, analysis, and capabilities of the SpaceCube v3.0 SpaceVPX Lite (VITA 78.1) 3U-220mm form-factor processor card

Soybean Seedling Damage: Is There an Interaction Between the ILeVO Seed Treatment and Pre-Emergence Herbicides?

Farmers who were lucky enough to plant soybeans and spray pre-emergence herbicides in between rain events may now be seeing discolored or injured seedlings. Reports of fields with these issues are widespread across Indiana, Iowa, and surrounding areas, and many farmers and crop advisors are questioning if damage is more severe when pre-emergence herbicides are applied to fields that have been planted with seed treated with the new fluopyram fungicide seed treatment ILeVO

\u3ci\u3eClinostomum poteae\u3c/i\u3e n. sp. (Digenea: Clinostomidae), in the trachea of a double-crested cormorant \u3ci\u3ePhalacrocorax auritus\u3c/i\u3e Lesson, 1831 and molecular data linking the life-cycle stages of \u3ci\u3eClinostomum album\u3c/i\u3e Rosser, Alberson, Woodyard, Cunningham, Pote & Griffin, 2017 in Mississippi, USA

Clinostomum spp. (Digenea: Clinostomidae) are a group of trematodes commonly found in the buccal cavity and oesophagus of a variety of piscivorous birds. The metacercariae, colloquially known as ‘‘yellow grubs,’’ have been reported from a diverse group of freshwater fishes worldwide. In the catfish farming region of the southeastern USA, piscivorous birds present a continuous challenge for aquaculturists in the form of fish depredation and the introduction of trematodes into these static, earthen pond systems. Clinostomum spp. are commonly encountered in farmraised catfish. While generally considered pests of minimal importance, heavy infections can result in unmarketable fillets. Of the piscivorous birds that frequent catfish aquaculture operations in the southeastern US, the double-crested cormorant (Phalacrocorax auritus Lesson) is one of the most damaging, although reports of Clinostomum spp. from P. auritus are limited. In this study, adult trematodes morphologically consistent with Clinostomum sp. were found in the trachea of a double-crested cormorant captured in Lowndes Co., Mississippi, USA. These specimens differed from other recognised Clinostomum spp. in several key morphological characters. Moreover, sequence data of mitochondrial cytochrome c oxidase subunit 1 gene (cox1), nicotinamide adenine dinucleotide dehydrogenase subunit 1 gene (nad1) and ribosomal internal transcribed spacer (ITS) regions did not match any known Clinostomum sp. for which sequence data are available. While genetically similar to C. marginatum and C. album Rosser, Alberson, Woodyard, Cunningham, Pote & Griffin, 2017 reported from the great egret Ardea alba L. in Mississippi, these adult clinostomids were larger in size and limited to the trachea, whereas both C. marginatum Rudolphi, 1819 and C. album are found in the oral cavity and esophagus. Given these distinct morphological and molecular characters we propose a new member of the genus, known hereafter as Clinostomum poteae n. sp. Additionally, larval stages in the life-cycle of C. album are morphologically and molecularly identified for the first time from ramshorn snails Planorbella trivolvis Say and fathead minnows Pimephales promelas Rafinesque

Meta-analysis of yield response of foliar fungicide-treated hybrid corn in the United States and Ontario, Canada

Foliar fungicide applications to corn (Zea mays L.) occur at one or more application timings ranging from early vegetative growth stages to mid-reproductive stages. Previous studies indicated that fungicide applications are profitable under high disease pressure when applied during the tasseling to silking growth stages. Few comprehensive studies in corn have examined the impact of fungicide applications at an early vegetative growth stage (V6) compared to late application timings (VT) for yield response and return on fungicide investment (ROI) across multiple locations

Meta-analysis of yield response of foliar fungicide-treated hybrid corn in the United States and Ontario, Canada

Background Foliar fungicide applications to corn (Zea mays L.) occur at one or more application timings ranging from early vegetative growth stages to mid-reproductive stages. Previous studies indicated that fungicide applications are profitable under high disease pressure when applied during the tasseling to silking growth stages. Few comprehensive studies in corn have examined the impact of fungicide applications at an early vegetative growth stage (V6) compared to late application timings (VT) for yield response and return on fungicide investment (ROI) across multiple locations. Objective Compare yield response of fungicide application timing across multiple fungicide classes and calculate the probability of positive ROI. Methods Data were collected specifically for this analysis using a uniform protocol conducted in 13 states in the United States and one province in Canada from 2014–2015. Data were subjected to a primary mixed-model analysis of variance. Subsequent univariate meta-analyses, with and without moderator variables, were performed using standard meta-analytic procedures. Follow-up power and prediction analyses were performed to aid interpretation and development of management recommendations. Results Fungicide application resulted in a range of yield responses from -2,683.0 to 3,230.9 kg/ha relative to the non-treated control, with 68.2% of these responses being positive. Evidence suggests that all three moderator variables tested (application timing, fungicide class, and disease base level), had some effect (α = 0.05) on the absolute difference in yield between fungicide treated and non-treated plots (). Application timing influenced , with V6 + VT and the VT application timings resulting in greater yield responses than the V6 application timing alone. Fungicide formulations that combined demethylation inhibitor and quinone outside inhibitor fungicides significantly increased yield response. Conclusion Foliar fungicide applications can increase corn grain yield. To ensure the likelihood of a positive ROI, farmers should focus on applications at VT and use fungicides that include a mix of demethylation inhibitor and quinone outside inhibitor active ingredients

(Re)Storying Obama: An Examination of Recently Published Informational Texts

American publishers have published numerous children’s books about Barack Obama over the past several years; most take the form of informational biographies. This article reports on a research project aimed at how these books incorporate sociohistorical narratives, particularly those related to the civil rights movement. Though the features of the books might cause the reader to presume political neutrality, the books link readers to distinct Discourses (Gee, 1996), suggesting particular ideologies. In this article, we identified the following differences: (1) specific happenings from Obama’s life were included in some texts while omitted in others; (2) when the events were included, how they were framed differed; and (3) the narrative constructions of the events varied. We use the differences amongst these texts to argue for the importance of critical literacy in elementary classrooms

NASA SpaceCube Next-Generation Artificial-Intelligence Computing for STP-H9-SCENIC on ISS

Recently, Artificial Intelligence (AI) and Machine Learning (ML) capabilities have seen an exponential increase in interest from academia and industry that can be a disruptive, transformative development for future missions. Specifically, AI/ML concepts for edge computing can be integrated into future missions for autonomous operation, constellation missions, and onboard data analysis. However, using commercial AI software frameworks onboard spacecraft is challenging because traditional radiation-hardened processors and common spacecraft processors cannot provide the necessary onboard processing capability to effectively deploy complex AI models. Advantageously, embedded AI microchips being developed for the mobile market demonstrate remarkable capability and follow similar size, weight, and power constraints that could be imposed on a space-based system. Unfortunately, many of these devices have not been qualified for use in space. Therefore, Space Test Program - Houston 9 - SpaceCube Edge-Node Intelligent Collaboration (STP-H9-SCENIC) will demonstrate inflight, cutting-edge AI applications on multiple space-based devices for next-generation onboard intelligence. SCENIC will characterize several embedded AI devices in a relevant space environment and will provide NASA and DoD with flight heritage data and lessons learned for developers seeking to enable AI/ML on future missions. Finally, SCENIC also includes new CubeSat form-factor GPS and SDR cards for guidance and navigation