A Blind Search for Magnetospheric Emissions from Planetary Companions to Nearby Solar-type Stars

This paper reports a blind search for magnetospheric emissions from planets around nearby stars. Young stars are likely to have much stronger stellar winds than the Sun, and because planetary magnetospheric emissions are powered by stellar winds, stronger stellar winds may enhance the radio luminosity of any orbiting planets. Using various stellar catalogs, we selected nearby stars (<~ 30 pc) with relatively young age estimates (< 3 Gyr). We constructed different samples from the stellar catalogs, finding between 100 and several hundred stars. We stacked images from the 74-MHz (4-m wavelength) VLA Low-frequency Sky Survey (VLSS), obtaining 3\sigma limits on planetary emission in the stacked images of between 10 and 33 mJy. These flux density limits correspond to average planetary luminosities less than 5--10 x 10^{23} erg/s. Using recent models for the scaling of stellar wind velocity, density, and magnetic field with stellar age, we estimate scaling factors for the strength of stellar winds, relative to the Sun, in our samples. The typical kinetic energy carried by the stellar winds in our samples is 15--50 times larger than that of the Sun, and the typical magnetic energy is 5--10 times larger. If we assume that every star is orbited by a Jupiter-like planet with a luminosity larger than that of the Jovian decametric radiation by the above factors, our limits on planetary luminosities from the stacking analysis are likely to be a factor of 10--100 above what would be required to detect the planets in a statistical sense. Similar statistical analyses with observations by future instruments, such as the Low Frequency Array (LOFAR) and the Long Wavelength Array (LWA), offer the promise of improvements by factors of 10--100.Comment: 11 pages; AASTeX; accepted for publication in A

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

The Emergence of Emotions

Emotion is conscious experience. It is the affective aspect of consciousness. Emotion arises from sensory stimulation and is typically accompanied by physiological and behavioral changes in the body. Hence an emotion is a complex reaction pattern consisting of three components: a physiological component, a behavioral component, and an experiential (conscious) component. The reactions making up an emotion determine what the emotion will be recognized as. Three processes are involved in generating an emotion: (1) identification of the emotional significance of a sensory stimulus, (2) production of an affective state (emotion), and (3) regulation of the affective state. Two opposing systems in the brain (the reward and punishment systems) establish an affective value or valence (stimulus-reinforcement association) for sensory stimulation. This is process (1), the first step in the generation of an emotion. Development of stimulus-reinforcement associations (affective valence) serves as the basis for emotion expression (process 2), conditioned emotion learning acquisition and expression, memory consolidation, reinforcement-expectations, decision-making, coping responses, and social behavior. The amygdala is critical for the representation of stimulus-reinforcement associations (both reward and punishment-based) for these functions. Three distinct and separate architectural and functional areas of the prefrontal cortex (dorsolateral prefrontal cortex, orbitofrontal cortex, anterior cingulate cortex) are involved in the regulation of emotion (process 3). The regulation of emotion by the prefrontal cortex consists of a positive feedback interaction between the prefrontal cortex and the inferior parietal cortex resulting in the nonlinear emergence of emotion. This positive feedback and nonlinear emergence represents a type of working memory (focal attention) by which perception is reorganized and rerepresented, becoming explicit, functional, and conscious. The explicit emotion states arising may be involved in the production of voluntary new or novel intentional (adaptive) behavior, especially social behavior

X-ray absorption spectroscopy insights on the structure anisotropy and charge transfer in Chevrel Phase chalcogenides

The electronic structure and local coordination of binary (Mo6T8) and ternary Chevrel Phases (MxMo6T8) are investigated for a range of metal intercalant and chalcogen compositions. We evaluate differences in the Mo L3-edge and K-edge X-ray absorption near edge structure across the suite of chalcogenides MxMo6T8 (M = Cu, Ni, x = 1-2, T = S, Se, Te), quantifying the effect of compositional and structural modification on electronic structure. Furthermore, we highlight the expansion, contraction, and anisotropy of Mo6 clusters within these Chevrel Phase frameworks through extended X-ray absorption fine structure analysis. Our results show that metal-to-cluster charge transfer upon intercalation is dominated by the chalcogen acceptors, evidenced by significant changes in their respective X-ray absorption spectra in comparison to relatively unaffected Mo cations. These results explain the effects of metal intercalation on the electronic and local structure of Chevrel Phases across various chalcogen compositions, and aid in rationalizing electron distribution within the structure

Hydrogen production with seawater-resilient bipolar membrane electrolyzers

Generation of H2 and O2 from untreated water sources represents a promising alternative to ultrapure water required in contemporary proton exchange membrane-based electrolysis. Bipolar membrane-based devices, often used in electrodialysis and CO2 electrolysis, facilitate impure water electrolysis via simultaneous mediation of ion transport and enforcement of advantageous microenvironments. Herein we report their application in direct seawater electrolysis; we show that upon introduction of ionic species such as Na+ and Cl-, bipolar membrane electrolyzers inhibit the oxidation of Cl- to corrosive OCl- at the anode from real seawater down to a Faradaic efficiency of 0.005% while proton exchange membrane electrolyzers under comparable operating conditions exhibit a 10% Faradaic efficiency to Cl- oxidation. The effective mitigation of Cl- oxidation by bipolar membrane electrolyzers underpins their ability to enable longer term seawater electrolysis than proton exchange membrane assemblies by a factor of 140, suggesting a path to durable seawater electrolysis