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Rainfinity, a company resulting from the commercialization of Reliable Array of Independent Nodes (RAIN), produces the product, Rainwall. Rainwall runs a cluster of computer workstations, creating a distributed Internet gateway. When Rainwall detects a failure in software or hardware, traffic is shifted to a healthy gateway without interruptions to Internet service. It more evenly distributes workload across servers, providing less down time.
Previous studies indicated that damping rates of upstream whistlers strongly depend on the details of the electron distribution function. Moreover, detailed analysis of Doppler-shift and whistler dispersion relation indicated that upstream whistlers propagate obliquely in a broad band. In this paper we present results of a kinetic calculation of damping lengths of wide-band whistlers using the sum of 7-drifting bi-Maxwellian electron distributions as a best fit to the International Sun Earth Explorer (ISEE) 1 electron data. For 2 cases, when upstream whistlers are observed, convective damping lengths derived from ISEE magnetic field and ephemeris data are compared with theoretical results. We find that the calculated convective damping lengths are consistent with the data and that upstream whistlers remain marginally stable. We also show that the slope of plasma frame spectra of upstream whistlers, obtained by direct fitting of the observed spectra is between 5 and 7 with a sharp lower frequency cutoff corresponding to a wavelength of about one ion inertial length. When the solar wind velocity is directed largely along the wave normal of the upstream whistlers the polariztion of the right hand waves becomes reversed and low frequencies are switched to high resulting in a peaked spectrum with a strong high frequency cutoff. The overall spectral, wave and particle characteristics, proximity to the shock as well as propagation and damping properties indicate that these waves cannot be generated locally. Instead the observed upstream whistlers arise in the shock ramp most likely by a variety of cross-field drift and/or anisotropy driven instabilities.
An optical resonator has been developed with reconfigurable filter function that has resonant lines that can be shifted precisely and independently from each other, creating any desirable combination of resonant lines. This is achieved by changing the axial distribution of the effective refractive index of the resonator, which shifts the resonant frequency of particular optical modes, leaving all the rest unchanged. A reconfigurable optical filter is part of the remote chemical detector proposed for the Mars mission (Planetary Instrument Definition and Development Program PIDDP), but it is also useful for photonic communications devices.
Complex interactions between mobile ions and charge carriers in perovskite solar cells (PSCs) make it challenging to fully understand their dynamic interplay. Exposure to light further complicates these interactions, altering the system’s dynamics and inducing nonlinear effects that lead to changes in the J−V curve. Understanding these effects is crucial for improving the operational stability of PSCs. Impedance spectroscopy (IS) is a powerful technique for evaluating relaxation processes in the frequency domain; however, it is limited in capturing nonlinear contributions. Here, in this work, nonlinear impedance spectroscopy (NLIS) is employed to analyze the higher harmonic response to AC perturbation, both in the dark and after short-term light exposure. A shift in the low-frequency (LF) higher harmonic peak is observed after open-circuit light exposure, attributed to an altered electric field suggesting ion re-distribution, whereas closed-circuit exposure shows no LF shift, indicating minimal ion movement. Additionally, light exposure reduces higher-order admittance, more notably in open-circuit conditions, suggesting decreased recombination. Temperature-dependent analysis was conducted to characterize the activation energy of migrating species, identifying iodide as the dominant migrating ion.
INTRODUCTION: Mechanisms responsible for the ocular structural and functional changes that characterize the visual impairment and intracranial pressure (ICP) syndrome (VIIP) are unclear, but hypothesized to be secondary to the cephalad fluid shift experienced in spaceflight. This study will relate the fluid distribution and compartmentalization associated with long-duration spaceflight with VIIP symptoms. We also seek to determine whether the magnitude of fluid shifts during spaceflight, as well as the VIIP-related effects of those shifts, can be predicted preflight with acute hemodynamic manipulations, and also if lower body negative pressure (LBNP) can reverse the VIIP effects. METHODS: Physiologic variables will be examined pre-, in- and post-flight in 10 International Space Station crewmembers including: fluid compartmentalization (D2O and NaBr dilution); interstitial tissue thickness (ultrasound); vascular dimensions and dynamics (ultrasound and MRI (including cerebrospinal fluid pulsatility)); ocular measures (optical coherence tomography, intraocular pressure, ultrasound); and ICP measures (tympanic membrane displacement, otoacoustic emissions). Pre- and post-flight measures will be assessed while upright, supine and during 15 deg head-down tilt (HDT). In-flight measures will occur early and late during 6 or 12 month missions. LBNP will be evaluated as a countermeasure during HDT and during spaceflight. RESULTS: The first two crewmembers are in the preflight testing phase. Preliminary results characterize the acute fluid shifts experienced from upright, to supine and HDT postures (increased stroke volume, jugular dimensions and measures of ICP) which are reversed with 25 millimeters Hg LBNP. DISCUSSION: Initial results indicate that acute cephalad fluid shifts may be related to VIIP symptoms, but also may be reversible by LBNP. The effect of a chronic fluid shift has yet to be evaluated. Learning Objectives: Current spaceflight VIIP research is described, including novel hardware and countermeasures.
A systematic investigation was undertaken to characterize population shifts that occur in cultured human embryonic kidney cells as a function of passage number in vitro after original explantation. This approach to cell population shift analysis follows the suggestion of Mehreshi, Klein and Revesz that perturbed cell populations can be characterized by electrophoretic mobility distributions if they contain subpopulations with different electrophoretic mobilities. It was shown that this is the case with early passage cultured human embryo cells.
Machine learning techniques are increasingly used in high-energy nuclear physics because they can exploit multivariate correlations more efficiently than conventional cut-based analyses. A central challenge is the construction of training samples that faithfully reproduce the detector response observed in data. Signal samples are usually derived from detector simulations; therefore, mismatches between simulation and data can degrade classifier performance and introduce systematic biases. This work presents two practical correction procedures, namely cumulative distribution function (CDF) mapping and a shift-and-scale transformation, to align simulated signal features with those measured in data. Their performance is demonstrated with $J$/$\psi$ yield measurements in $\sqrt{s_{nn}}$ = 200 GeV Ru+Ru and Zr+Zr collisions recorded by STAR. A set of self-consistency tests shows that these procedures substantially suppress the systematic bias associated with data-simulation discrepancies in machine-learning-based signal extraction.
Abstract There is a paradigm shift towards data-centric AI, where model efficacy relies on quality, unified data. The common research analytics and data lifecycle environment (CRADLE™) is an infrastructure and framework that supports a data-centric paradigm and materials data science at scale through heterogeneous data management, elastic scaling, and accessible interfaces. We demonstrate CRADLE’s capabilities through five materials science studies: phase identification in X-ray diffraction, defect segmentation in X-ray computed tomography, polymer crystallization analysis in atomic force microscopy, feature extraction from additive manufacturing, and geospatial data fusion. CRADLE catalyzes scalable, reproducible insights to transform how data is captured, stored, and analyzed. Graphical abstract
The realistic case of a continuous distribution of combustion sources in the axial direction is considered in the investigation. The results obtained are compared with those of an earlier study conducted by Baer et al. (1974) concerning the stability of partially lined combustors with distributed combustion. There is a substantial upward shift of the curves in all cases relative to the curves obtained in the first analysis. The increase in chamber stability indicated is traced to some important damping effects associated with source terms which had been neglected in the previous study.
The environmental aspect of elevated temperature and its relationship to the science of strain gage calibrations of aircraft structures are addressed. A section of a wing designed for a high-speed aircraft structure was used to study this problem. This structure was instrumented with strain gages calibrated at both elevated and room temperatures. Load equations derived from a high-temperature load calibration were compared with equations derived from an identical load calibration at room temperature. The implications of the high temperature load calibration were studied from the viewpoint of applicability and necessity. Load equations derived from the room temperature load calibration resulted in generally lower equation standard errors than equations derived from the elevated temperature load calibration. A distributed load was applied to the structure at elevated temperature and strain gage outputs were measured. This applied load was then calculated using equations derived from both the room temperature and elevated temperature calibration data. It was found that no significant differences between the two equation systems existed in terms of computing this applied distributed load, as long as the thermal shifts resulting from thermal stresses could be identified. This identification requires a heating of the structure. Therefore, it is concluded that for this structure, a high temperature load calibration is not required. However, a heating of the structure is required to determine thermal shifts.
Radiation patterns switched within microseconds. According to concept, digital beam-steering information destined for number of phased antenna elements transmitted in serial multiplex along optical fiber to optoelectronic integrated circuit (OEIC), demultiplexing information into parallel electronic channels to phase shifters associated with various elements. Because of small distances between elements of such arrays, compactness of optical fibers makes them attractive for distribution of beam-steering (phase-shifting) control signals. Also offers advantages of light weight, low attenuation, mechanical flexibility, large bandwidth, and immunity to both crosstalk and electromagnetic interference.
Driven by a need to explore and develop propulsion systems that exceeded current computing capabilities, NASA Glenn embarked on a novel strategy leading to the development of an architecture that enables propulsion simulations never thought possible before. Full engine 3 Dimensional Computational Fluid Dynamic propulsion system simulations were deemed impossible due to the impracticality of the hardware and software computing systems required. However, with a software paradigm shift and an embracing of parallel and distributed processing, an architecture was designed to meet the needs of future propulsion system modeling. The author suggests that the architecture designed at the NASA Glenn Research Center for propulsion system modeling has potential for impacting the direction of development of affordable weapons systems currently under consideration by the Applied Vehicle Technology Panel (AVT). This paper discusses the salient features of the NPSS Architecture including its interface layer, object layer, implementation for accessing legacy codes, numerical zooming infrastructure and its computing layer. The computing layer focuses on the use and deployment of these propulsion simulations on parallel and distributed computing platforms which has been the focus of NASA Ames. Additional features of the object oriented architecture that support MultiDisciplinary (MD) Coupling, computer aided design (CAD) access and MD coupling objects will be discussed. Included will be a discussion of the successes, challenges and benefits of implementing this architecture.
Driven by a need to explore and develop propulsion systems that exceeded current computing capabilities, NASA Glenn embarked on a novel strategy leading to the development of an architecture that enables propulsion simulations never thought possible before. Full engine 3 Dimensional Computational Fluid Dynamic propulsion system simulations were deemed impossible due to the impracticality of the hardware and software computing systems required. However, with a software paradigm shift and an embracing of parallel and distributed processing, an architecture was designed to meet the needs of future propulsion system modeling. The author suggests that the architecture designed at the NASA Glenn Research Center for propulsion system modeling has potential for impacting the direction of development of affordable weapons systems currently under consideration by the Applied Vehicle Technology Panel (AVT).
An error budget is presented to meet 1 Kelvin radiometric accuracy in a geostationary atmospheric sounder with 50 km spatial resolution on the earth. The gain and phase errors are weighted by the magnitude of visibility versus antenna separation, and requirements range between approx.0.5% and 0.3 degrees of amplitude and phase, respectively, for the closest spacings at the center of the array, and about 5% and 3 degrees for the majority of the array. The latter requirement is met by our design without any special testing or stabilizations by reference signals. The former is met using an internal noise diode reference and by measuring the detailed antenna patterns on the antenna range. Biases and other additive errors in the raw visibility samples must be below about 2 mK on average, and this requirement is met by a phase shifting scheme applied to the local oscillator distribution. An outline of the data processing is presented, along with the first images from this system.
The purpose of this study was to extend a baseline empirical model to the case of jets entering the mainstream flow from opposed rows of 45 degrees slanted slots. The results in this report were obtained using a spreadsheet modified from the one posted with NASA/TM--2010-216100. The primary conclusion in this report is that the best mixing configuration for opposed rows of 45 degrees slanted slots at any down stream distance is a parallel staggered configuration where the slots are angled in the same direction on top and bottom walls and one side is shifted by half the orifice spacing. Although distributions from perpendicular slanted slots are similar to those from parallel staggered configurations at some downstream locations, results for perpendicular slots are highly dependent on downstream distance and are no better than parallel staggered slots at locations where they are similar and are worse than parallel ones at other distances.
"Climate dice", describing the chance of unusually warm or cool seasons, have become more and more "loaded" in the past 30 years, coincident with rapid global warming. The distribution of seasonal mean temperature anomalies has shifted toward higher temperatures and the range of anomalies has increased. An important change is the emergence of a category of summertime extremely hot outliers, more than three standard deviations (3 sigma) warmer than the climatology of the 1951-1980 base period. This hot extreme, which covered much less than 1% of Earth's surface during the base period, now typically covers about 10% of the land area. It follows that we can state, with a high degree of confidence, that extreme anomalies such as those in Texas and Oklahoma in 2011 and Moscow in 2010 were a consequence of global warming, because their likelihood in the absence of global warming was exceedingly small. We discuss practical implications of this substantial, growing, climate change.
The purpose of this study was to extend a baseline empirical model to the case of jets entering the mainstream flow from opposed rows of 45 degrees slanted slots. The results in this report were obtained using a spreadsheet modified from the one posted with NASA/TM--2010-216100. The primary conclusion in this report is that the best mixing configuration for opposed rows of 45 degrees slanted slots at any down stream distance is a parallel staggered configuration where the slots are angled in the same direction on top and bottom walls and one side is shifted by half the orifice spacing. Although distributions from perpendicular slanted slots are similar to those from parallel staggered configurations at some downstream locations, results for perpendicular slots are highly dependent on downstream distance and are no better than parallel staggered slots at locations where they are similar and are worse than parallel ones at other distances.
Deep learning models have shown promise in reservoir inflow prediction, yet their performance often deteriorates when applied to different reservoirs due to distributional differences, referred to as the domain shift problem. Domain generalization (DG) solutions aim to address this issue by extracting domain-invariant representations that mitigate errors in unseen domains. However, in hydrological settings, each reservoir exhibits unique inflow patterns, while some metadata beyond observations like spatial information exerts indirect but significant influence. This mismatch limits the applicability of conventional DG techniques to many-domain hydrological systems. To overcome these challenges, we propose HydroDCM, a scalable DG framework for cross-reservoir inflow forecasting. Spatial metadata of reservoirs is used to construct pseudo-domain labels that guide adversarial learning of invariant temporal features. During inference, HydroDCM adapts these features through light-weight conditioning layers informed by the target reservoir’s metadata, reconciling DG’s invariance with location-specific adaptation. Experiment results on 30 real-world reservoirs in the Upper Colorado River Basin demonstrate that our method substantially outperforms state-of-the-art DG baselines under many-domain conditions and remains computationally efficient.