A System to Monitor Cognitive Workload in Naturalistic High-Motion Environments

Across many careers, individuals face alternating periods of high and low attention and cognitive workload can impair cognitive function and undermine job performance. We have designed and are developing an unobtrusive system to Monitor, Extract, and Decode Indicators of Cognitive Workload (MEDIC) in naturalistic, high-motion environments. MEDIC is designed to warn individuals, teammates, or supervisors when steps should be taken to augment cognitive readiness. We first designed and manufactured a forehead sensor device that includes a custom fNIRS sensor and a three-axis accelerometer designed to be mounted on the inside of a baseball cap or headband, or standard issue gear such as a helmet or surgeon’s cap. Because the conditions under which MEDIC is designed to operate are more strenuous than typical research efforts assessing cognitive workload, motion artifacts in our data were a persistent issue. Results show wavelet-based filtering improved data quality to salvage data from even the highest-motion conditions. MARA spline motion correction did not further improve data quality. Our testing shows that each of the methods is extremely effective in reducing the effects of motion transients present in the data. In combination, they are able to almost completely remove the transients in the signal while preserving cardiac and low frequency information in the signal which was previously unrecoverable. This has substantially improved the stability of the physiological measures produced by the sensors in high noise conditions

Parallax and Luminosity Measurements of an L Subdwarf

We present the first parallax and luminosity measurements for an L subdwarf, the sdL7 2MASS J05325346+8246465. Observations conducted over three years by the USNO infrared astrometry program yield an astrometric distance of 26.7+/-1.2 pc and a proper motion of 2.6241+/-0.0018"/yr. Combined with broadband spectral and photometric measurements, we determine a luminosity of log(Lbol/Lsun) = -4.24+/-0.06 and Teff = 1730+/-90 K (the latter assuming an age of 5-10 Gyr), comparable to mid-type L field dwarfs. Comparison of the luminosity of 2MASS J05325346+8246465 to theoretical evolutionary models indicates that its mass is just below the sustained hydrogen burning limit, and is therefore a brown dwarf. Its kinematics indicate a ~110 Myr, retrograde Galactic orbit which is both eccentric (3 <~ R <~ 8.5 kpc) and extends well away from the plane (Delta_Z = +/-2 kpc), consistent with membership in the inner halo population. The relatively bright J-band magnitude of 2MASS J05325346+8246465 implies significantly reduced opacity in the 1.2 micron region, consistent with inhibited condensate formation as previously proposed. Its as yet unknown subsolar metallicity remains the primary limitation in constraining its mass; determination of both parameters would provide a powerful test of interior and evolutionary models for low-mass stars and brown dwarfs.Comment: Accepted to ApJ 10 September 2007; 13 pages, 5 figures, 3 tables, formatted in emulateapj styl

Trigonometric Parallaxes of Central Stars of Planetary Nebulae

Trigonometric parallaxes of 16 nearby planetary nebulae are presented, including reduced errors for seven objects with previous initial results and results for six new objects. The median error in the parallax is 0.42 mas, and twelve nebulae have parallax errors less than 20 percent. The parallax for PHL932 is found here to be smaller than was measured by Hipparcos, and this peculiar object is discussed. Comparisons are made with other distance estimates. The distances determined from these parallaxes tend to be intermediate between some short distance estimates and other long estimates; they are somewhat smaller than estimated from spectra of the central stars. Proper motions and tangential velocities are presented. No astrometric perturbations from unresolved close companions are detected.Comment: 24 pages, includes 4 figures. Accepted for A

The USNO-B Catalog

USNO-B is an all-sky catalog that presents positions, proper motions, magnitudes in various optical passbands, and star/galaxy estimators for 1,042,618,261 objects derived from 3,643,201,733 separate observations. The data were obtained from scans of 7,435 Schmidt plates taken for the various sky surveys during the last 50 years. USNO-B1.0 is believed to provide all-sky coverage, completeness down to V = 21, 0.2 arcsecond astrometric accuracy at J2000, 0.3 magnitude photometric accuracy in up to five colors, and 85% accuracy for distinguishing stars from non-stellar objects. A brief discussion of various issues is given here, but the actual data are available from http://www.nofs.navy.mil and other sites.Comment: Accepted by Astronomical Journa

Astrometry and Photometry for Cool Dwarfs and Brown Dwarfs

Trigonometric parallax determinations are presented for 28 late type dwarfs and brown dwarfs, including eight M dwarfs with spectral types between M7 and M9.5, 17 L dwarfs with spectral types between L0 and L8, and three T dwarfs. Broadband photometry at CCD wavelengths (VRIz) and/or near-IR wavelengths (JHK) are presented for these objects and for 24 additional late-type dwarfs. Supplemented with astrometry and photometry from the literature, including ten L and two T dwarfs with parallaxes established by association with bright, usually HIPPARCOS primaries, this material forms the basis for studying various color-color and color-absolute magnitude relations. The I-J color is a good predictor of absolute magnitude for late-M and L dwarfs. M_J becomes monotonically fainter with I-J color and with spectral type through late-L dwarfs, then brightens for early-T dwarfs. The combination of zJK colors alone can be used to classify late-M, early-L, and T dwarfs accurately, and to predict their absolute magnitudes, but is less effective at untangling the scatter among mid- and late-L dwarfs. The mean tangential velocity of these objects is found to be slightly less than that for dM stars in the solar neighborhood, consistent with a sample with a mean age of several Gyr. Using colors to estimate bolometric corrections, and models to estimate stellar radii, effective temperatures are derived. The latest L dwarfs are found to have T_eff ~ 1360 K.Comment: 48 pages, including 7 figures and 6 tables. Accepted for A

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

Snowball ICA : A Model Order Free Independent Component Analysis Strategy for Functional Magnetic Resonance Imaging Data

In independent component analysis (ICA), the selection of model order (i.e., number of components to be extracted) has crucial effects on functional magnetic resonance imaging (fMRI) brain network analysis. Model order selection (MOS) algorithms have been used to determine the number of estimated components. However, simulations show that even when the model order equals the number of simulated signal sources, traditional ICA algorithms may misestimate the spatial maps of the signal sources. In principle, increasing model order will consider more potential information in the estimation, and should therefore produce more accurate results. However, this strategy may not work for fMRI because large-scale networks are widely spatially distributed and thus have increased mutual information with noise. As such, conventional ICA algorithms with high model orders may not extract these components at all. This conflict makes the selection of model order a problem. We present a new strategy for model order free ICA, called Snowball ICA, that obviates these issues. The algorithm collects all information for each network from fMRI data without the limitations of network scale. Using simulations and in vivo resting-state fMRI data, our results show that component estimation using Snowball ICA is more accurate than traditional ICA. The Snowball ICA software is available at https://github.com/GHu-DUT/Snowball-ICA.peerReviewe