Subspace Identification With Guaranteed Stability Using Constrained Optimization

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57870/1/LacyStableIDTAC2003.pd

Methods for Data-centric Small Satellite Anomaly Detection and Fault Prediction

Autonomy can increase reaction speed, flexibility, and accuracy of satellite operations, especially in uncertain environments caused by delayed communication and/or adversarial conditions. An increased focus on small satellites makes the development of satellite autonomy even more salient, given fewer operators per satellite. Anomaly detection automates satellite health monitoring, ensuring it functions as designed. This is typically achieved using various forms of recurrent neural networks (RNN). While many of these model-based works show promise, a majority use simulated data or assume lossless communication. In contrast, raw satellite telemetry often has dropped packets, sampling frequency mismatches, noise from electrical systems and radiation, and a lack of clear labels for training. This work demonstrates how data-centric artificial intelligence (AI) can be utilized in satellite autonomy, using telemetry from the Very Low Frequency Propagation Mapper (VPM) small satellite flown by the Air Force Research Lab Space Vehicle Directorate in 2020. We introduce simple, but effective, tools for extracting fault labels from system parameters, resampling outliers to a common, uniform timeline, and evaluating outlier fault predictability. Results find that detected outliers were able to predict faults 1-10 minutes before they occurred with high accuracy

Broadband adaptive disturbance rejection for a deployable optical telescope testbed

Abstract-Broadband adaptive disturbance rejection is demonstrated on the artificial white-light source of the Deployable Optical Telescope (DOT) developed by the Air Force Research Laboratory (AFRL). Large deployable optical systems are envisioned as the future of space telescopes. These systems will require active control for disturbance rejection. In this paper, we consider a multi-input, multi-output discretetime adaptive disturbance rejection algorithm. The algorithm requires knowledge of some Markov parameters of the system from the control signal inputs to the performance variables. No information about the disturbance spectrum is required. We demonstrate broadband disturbance rejection numerically on an identified model of DOT's white-light source and experimentally on the system itself

The nuclear star cluster of the Milky Way: proper motions and mass

Nuclear star clusters (NSCs) are located at the photometric and dynamical centers of the majority of galaxies. They are among the densest star clusters in the Universe. The NSC in the Milky Way is the only object of this class that can be resolved into individual stars. We measured the proper motions of more than 6000 stars within ~1.0 pc of the supermassive black hole Sgr A*. The full data set is provided in this work. We largely exclude the known early-type stars with their peculiar dynamical properties from the dynamical analysis. The cluster is found to rotate parallel to Galactic rotation, while the velocity dispersion appears isotropic (or anisotropy may be masked by the cluster rotation). The Keplerian fall-off of the velocity dispersion due to the point mass of Sgr A* is clearly detectable only at R <~ 0.3 pc. Nonparametric isotropic and anisotropic Jeans models are applied to the data. They imply a best-fit black hole mass of 3.6 (+0.2/-0.4) x 10^6 solar masses. Although this value is slightly lower than the current canonical value of 4.0x10^6 solar masses, this is the first time that a proper motion analysis provides a mass for Sagittarius A* that is consistent with the mass inferred from orbits of individual stars. The point mass of Sagittarius A* is not sufficient to explain the velocity data. In addition to the black hole, the models require the presence of an extended mass of 0.5-1.5x10^6 solar masses in the central parsec. This is the first time that the extended mass of the nuclear star cluster is unambiguously detected. The influence of the extended mass on the gravitational potential becomes notable at distances >~0.4 pc from Sgr A*. Constraints on the distribution of this extended mass are weak. The extended mass can be explained well by the mass of the stars that make up the cluster.Comment: accepted for publication in Astronomy & Astrophysics; please contact first author for higher quality figure

Multi-wavelength study of the turbulent central engine of the low-mass agn hosted by Ngc404

The nearby dwarf galaxy NGC 404 harbors a low-luminosity active galactic nucleus powered by the lowest-mass (<150,000 M ⊙) central massive black hole (MBH), with a dynamical mass constraint, currently known, thus providing a rare low-redshift analog to the MBH "seeds" that formed in the early universe. Here, we present new imaging of the nucleus of NGC 404 at 12–18 GHz with the Karl G. Jansky Very Large Array (VLA) and observations of the CO(2–1) line with the Atacama Large Millimeter/Submillimeter Array (ALMA). For the first time, we have successfully resolved the nuclear radio emission, revealing a centrally peaked, extended source spanning 17 pc. Combined with previous VLA observations, our new data place a tight constraint on the radio spectral index and indicate an optically thin synchrotron origin for the emission. The peak of the resolved radio source coincides with the dynamical center of NGC 404, the center of a rotating disk of molecular gas, and the position of a compact, hard X-ray source. We also present evidence for shocks in the NGC 404 nucleus from archival narrowband HST imaging, Chandra X-ray data, and Spitzer mid-infrared spectroscopy, and discuss possible origins for the shock excitation. Given the morphology, location, and steep spectral index of the resolved radio source, as well as constraints on nuclear star formation from the ALMA CO(2–1) data, we find the most likely scenario for the origin of the radio source in the center of NGC 404 to be a radio outflow associated with a confined jet driven by the active nucleus

The Wyoming Survey for H-alpha. III. A Multi-wavelength Look at Attenuation by Dust in Galaxies out to z~0.4

We report results from the Wyoming Survey for H-alpha (WySH), a comprehensive four-square degree survey to probe the evolution of star-forming galaxies over the latter half of the age of the Universe. We have supplemented the H-alpha data from WySH with infrared data from the Spitzer Wide-area Infrared Extragalactic (SWIRE) Survey and ultraviolet data from the Galaxy Evolution Explorer (GALEX) Deep Imaging Survey. This dataset provides a multi-wavelength look at the evolution of the attenuation by dust, and here we compare a traditional measure of dust attenuation (L(TIR)/L(FUV)) to a diagnostic based on a recently-developed robust star formation rate (SFR) indicator, [H-alpha_obs+24-micron]/H-alpha_obs. With such data over multiple epochs, the evolution in the attenuation by dust with redshift can be assessed. We present results from the ELAIS-N1 and Lockman Hole regions at z~0.16, 0.24, 0.32 and 0.40. While the ensemble averages of both diagnostics are relatively constant from epoch to epoch, each epoch individually exhibits a larger attenuation by dust for higher star formation rates. Hence, an epoch to epoch comparison at a fixed star formation rate suggests a mild decrease in dust attenuation with redshift.Comment: 30 pages, 9 figure

Galaxy bulges and their massive black holes: a review

With references to both key and oft-forgotten pioneering works, this article starts by presenting a review into how we came to believe in the existence of massive black holes at the centres of galaxies. It then presents the historical development of the near-linear (black hole)-(host spheroid) mass relation, before explaining why this has recently been dramatically revised. Past disagreement over the slope of the (black hole)-(velocity dispersion) relation is also explained, and the discovery of sub-structure within the (black hole)-(velocity dispersion) diagram is discussed. As the search for the fundamental connection between massive black holes and their host galaxies continues, the competing array of additional black hole mass scaling relations for samples of predominantly inactive galaxies are presented.Comment: Invited (15 Feb. 2014) review article (submitted 16 Nov. 2014). 590 references, 9 figures, 25 pages in emulateApJ format. To appear in "Galactic Bulges", E. Laurikainen, R.F. Peletier, and D.A. Gadotti (eds.), Springer Publishin

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

System identification.

In this dissertation, we present research on identifying Wiener systems with known, noninvertible nonlinearities; on identifying multi-input multi-output nonlinear systems that are linear in unmeasured states; on identifying finite impulse response Wiener systems with polynomial nonlinearities; and on guaranteeing stable solutions in the context of subspace identification methods. Wiener systems consist of a linear dynamic system followed by a static non-linearity. They are often used to model a linear system with a nonlinear sensor. We develop a method for identifying systems with known, not necessarily invertible, nonlinearities based on the minimization of a nonlinear cost function. Next, we identify multi-input multi-output nonlinear systems that are linear in unmeasured states. My approach allows for the identification of nonlinear systems in which the arguments of the system nonlinearities are measured. We write the nonlinearities as a sum of basis functions, and then we simultaneously estimate the coefficients of the basis functions and the linear system. Then we return to the Wiener identification problem and develop a two-stage direct computation approach for the identification of Wiener systems with finite impulse response and polynomial nonlinearities. My approach is based on multi-index notation. Finally, we present a method for guaranteeing stability in the context of subspace identification methods for linear systems. We write the problem as a minimization of a least squares cost function subject to a convex constraint. The constraint is sufficient to ensure stability, but is not necessary. Existing optimization algorithms can be used to solve the resulting convex optimization problem.Ph.D.Aerospace engineeringApplied SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/129833/2/3042104.pd