Generalization of Heterogeneous Multi-Robot Policies via Awareness and Communication of Capabilities

Recent advances in multi-agent reinforcement learning (MARL) are enabling impressive coordination in heterogeneous multi-robot teams. However, existing approaches often overlook the challenge of generalizing learned policies to teams of new compositions, sizes, and robots. While such generalization might not be important in teams of virtual agents that can retrain policies on-demand, it is pivotal in multi-robot systems that are deployed in the real-world and must readily adapt to inevitable changes. As such, multi-robot policies must remain robust to team changes -- an ability we call adaptive teaming. In this work, we investigate if awareness and communication of robot capabilities can provide such generalization by conducting detailed experiments involving an established multi-robot test bed. We demonstrate that shared decentralized policies, that enable robots to be both aware of and communicate their capabilities, can achieve adaptive teaming by implicitly capturing the fundamental relationship between collective capabilities and effective coordination. Videos of trained policies can be viewed at: https://sites.google.com/view/cap-commComment: Presented at the 7th Conference on Robot Learning (CoRL 2023), Atlanta, US

Accessing Opportunities for Household Provisioning Post-COVID-19

In this project, we used a mixed-methods study to collect critical information to evaluate the extent to which people modified their shopping behavior, either by choice or necessity, to meet their provisioning needs during the COVID-19 crisis and the following recovery. First, four waves of a cross-sectional survey were administered online to a representative sample of households in Arizona, Florida, Michigan, Oregon, and Washington. This longitudinal, comparative study responded directly to a critical research gap and advanced behavioral science by providing a rich survey dataset to support and test theories of behavioral change and technology adoption. Second, focus groups were conducted with older adults in Oregon to discuss their arc of technology adoption for grocery shopping. Focus groups were also conducted with two sets of mentors who provide assistance to family members and friends with online food purchases to understand what kinds of interventions might be necessary to broaden access to e-commerce and delivery platforms for vulnerable populations. This report presents high-level descriptive statistics from these surveys comparing results by wave and/or by state. The findings from the focus groups with older adults and mentors are also described. The findings of this research are critical for emergency planning but also for understanding the ever-changing mechanism used to access retail and service opportunities (whether in-person vs. online), and the opportunities for future interventions to remedy barriers to accessing food that are relevant after the pandemic recovery

Accurate telemonitoring of Parkinson's disease symptom severity using nonlinear speech signal processing and statistical machine learning

This study focuses on the development of an objective, automated method to extract clinically useful information from sustained vowel phonations in the context of Parkinson’s disease (PD). The aim is twofold: (a) differentiate PD subjects from healthy controls, and (b) replicate the Unified Parkinson’s Disease Rating Scale (UPDRS) metric which provides a clinical impression of PD symptom severity. This metric spans the range 0 to 176, where 0 denotes a healthy person and 176 total disability. Currently, UPDRS assessment requires the physical presence of the subject in the clinic, is subjective relying on the clinical rater’s expertise, and logistically costly for national health systems. Hence, the practical frequency of symptom tracking is typically confined to once every several months, hindering recruitment for large-scale clinical trials and under-representing the true time scale of PD fluctuations. We develop a comprehensive framework to analyze speech signals by: (1) extracting novel, distinctive signal features, (2) using robust feature selection techniques to obtain a parsimonious subset of those features, and (3a) differentiating PD subjects from healthy controls, or (3b) determining UPDRS using powerful statistical machine learning tools. Towards this aim, we also investigate 10 existing fundamental frequency (F_0) estimation algorithms to determine the most useful algorithm for this application, and propose a novel ensemble F_0 estimation algorithm which leads to a 10% improvement in accuracy over the best individual approach. Moreover, we propose novel feature selection schemes which are shown to be very competitive against widely-used schemes which are more complex. We demonstrate that we can successfully differentiate PD subjects from healthy controls with 98.5% overall accuracy, and also provide rapid, objective, and remote replication of UPDRS assessment with clinically useful accuracy (approximately 2 UPDRS points from the clinicians’ estimates), using only simple, self-administered, and non-invasive speech tests. The findings of this study strongly support the use of speech signal analysis as an objective basis for practical clinical decision support tools in the context of PD assessment.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Metallicity Gradients at Large Galactocentric Radii Using the Near-infrared Calcium Triplet

We describe a new spectroscopic technique for measuring radial metallicity gradients out to large galactocentric radii. We use the DEIMOS multi-object spectrograph on the Keck telescope and the galaxy spectrum extraction technique of Proctor et al. (2009). We also make use of the metallicity sensitive near-infrared (NIR) Calcium triplet (CaT) features together with single stellar population models to obtain metallicities. Our technique is applied as a pilot study to a sample of three relatively nearby (<30 Mpc) intermediate-mass to massive early-type galaxies. Results are compared with previous literature inner region values and generally show good agreement. We also include a comparison with profiles from dissipational disk-disk major merger simulations. Based on our new extended metallicity gradients combined with other observational evidence and theoretical predictions, we discuss possible formation scenarios for the galaxies in our sample. The limitations of our new technique are also discussed.Comment: 13 Pages, 9 Figures, 7 Tables, Accepted for publication in MNRA

The Human–Nature Relationship and Its Impact on Health: A Critical Review

Within the past four decades, research has been increasingly drawn toward understanding whether there is a link between the changing human–nature relationship and its impact on people’s health. However, to examine whether there is a link requires research of its breadth and underlying mechanisms from an interdisciplinary approach. This article begins by reviewing the debates concerning the human–nature relationship, which are then critiqued and redefined from an interdisciplinary perspective. The concept and chronological history of “health” is then explored, based on the World Health Organization’s definition. Combining these concepts, the human–nature relationship and its impact on human’s health are then explored through a developing conceptual model. It is argued that using an interdisciplinary perspective can facilitate a deeper understanding of the complexities involved for attaining optimal health at the human–environmental interface

Standardized ultrasound evaluation of carotid stenosis for clinical trials: University of Washington Ultrasound Reading Center

<p>Abstract</p> <p>Introduction</p> <p>Serial monitoring of patients participating in clinical trials of carotid artery therapy requires noninvasive precision methods that are inexpensive, safe and widely available. Noninvasive ultrasonic duplex Doppler velocimetry provides a precision method that can be used for recruitment qualification, pre-treatment classification and post treatment surveillance for remodeling and restenosis. The University of Washington Ultrasound Reading Center (UWURC) provides a uniform examination protocol and interpretation of duplex Doppler velocity measurements.</p> <p>Methods</p> <p>Doppler waveforms from 6 locations along the common carotid and internal carotid artery path to the brain plus the external carotid and vertebral arteries on each side using a Doppler examination angle of 60 degrees are evaluated. The UWURC verifies all measurements against the images and waveforms for the database, which includes pre-procedure, post-procedure and annual follow-up examinations. Doppler angle alignment errors greater than 3 degrees and Doppler velocity measurement errors greater than 0.05 m/s are corrected.</p> <p>Results</p> <p>Angle adjusted Doppler velocity measurements produce higher values when higher Doppler examination angles are used. The definition of peak systolic velocity varies between examiners when spectral broadening due to turbulence is present. Examples of measurements are shown.</p> <p>Discussion</p> <p>Although ultrasonic duplex Doppler methods are widely used in carotid artery diagnosis, there is disagreement about how the examinations should be performed and how the results should be validated. In clinical trails, a centralized reading center can unify the methods. Because the goals of research examinations are different from those of clinical examinations, screening and diagnostic clinical examinations may require fewer velocity measurements.</p

Probing the 2-D kinematic structure of early-type galaxies out to 3 effective radii

We detail an innovative new technique for measuring the 2-D velocity moments (rotation velocity, velocity dispersion and Gauss-Hermite coefficients h$_3$ and h$_4$) of the stellar populations of galaxy halos using spectra from Keck DEIMOS multi-object spectroscopic observations. The data are used to reconstruct 2-D rotation velocity maps. Here we present data for five nearby early-type galaxies to ~3 effective radii. We provide significant insights into the global kinematic structure of these galaxies, and challenge the accepted morphological classification in several cases. We show that between 1-3 effective radii the velocity dispersion declines very slowly, if at all, in all five galaxies. For the two galaxies with velocity dispersion profiles available from planetary nebulae data we find very good agreement with our stellar profiles. We find a variety of rotation profiles beyond 1 effective radius, i.e rotation speed remaining constant, decreasing \emph{and} increasing with radius. These results are of particular importance to studies which attempt to classify galaxies by their kinematic structure within one effective radius, such as the recent definition of fast- and slow- rotator classes by the SAURON project. Our data suggests that the rotator class may change when larger galacto-centric radii are probed. This has important implications for dynamical modeling of early-type galaxies. The data from this study are available on-line.Comment: 20 pages, 22 figures, Accepted for publication in MNRA

PEDIA: prioritization of exome data by image analysis.

PURPOSE: Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. METHODS: Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. RESULTS: The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20-89% and the top 10 accuracy rate by more than 5-99% for the disease-causing gene. CONCLUSION: Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis

Some behavioral aspects of energy descent: How a biophysical psychology might help people transition through the lean times ahead

This article is part of the Research Topic: Nature and environment: The psychology of its benefits and its protection.We may soon face biophysical limits to perpetual growth. Energy supplies may tighten and then begin a long slow descent while defensive expenditures rise to address problems caused by past resource consumption. The outcome may be significant changes in daily routines at the individual and community level. It is difficult to know when this scenario might begin to unfold but it clearly would constitute a new behavioral context, one that the behavioral sciences least attends to. Even if one posits a less dramatic scenario, people may still need to make many urgent and perhaps unsettling transitions. And while a robust response would be needed, it is not at all clear what should be the details of that response. Since it is likely that no single response will fix things everywhere, for all people or for all time, it would be useful to conduct many social experiments. Indeed, a culture of small experiments should be fostered which, at the individual and small group level, can be described as behavioral entrepreneurship. This may have begun, hidden in plain sight, but more social experiments are needed. To be of help, it may be useful to both package behavioral insights in a way that is practitioner-oriented and grounded in biophysical trends and to propose a few key questions that need attention. This paper begins the process of developing a biophysical psychology, incomplete as it is at this early stage.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109261/1/De Young, R. (2014) Some behavioral aspects of energy descent, How a biophysical psychology might help people transition through the lean times ahead, Frontiers in Psychology, 5, 1255.pdfDescription of De Young, R. (2014) Some behavioral aspects of energy descent, How a biophysical psychology might help people transition through the lean times ahead, Frontiers in Psychology, 5, 1255.pdf : Main articl