Detection of a Variable Infrared Excess Around SDSS 121209.31+013627.7

We present near-infrared $JHK_s$ photometry and light curves of the candidate magnetic white dwarf+brown dwarf binary SDSS J121209.31+013627.7 and report on the detection of near-infrared excess and variability in the $K_s-$band. The observed near-infrared excess can be explained by the presence of an L7 brown dwarf and an extra emission source. The $J$ and $H$ light curves appear flat, which rules out eclipses deeper than 0.2 mag and the presence of an accretion hot spot on the white dwarf. From the variable $K_s$ lightcurve, we get a refined period for the system of 88$\pm$1 minutes. We show that the observed variability in $K_s-$band can be explained by cyclotron emission, which can be modeled by a small spot on the surface of the white dwarf. SDSS 1212 exhibits similarities to the ultra-short period polar EF Eridani, however the lack of evidence for Roche-lobe overflow accretion suggests it may be a pre-polar.Comment: 13 pages, 2 figures, accepted to ApJ

Higher compressive strengths and the Bauschinger effect in conformally passivated copper nanopillars

Our current understanding of size-dependent strength in nano- and microscale crystals is centered around the idea that the overall strength is determined by the stress required to propagate dislocation sources. The nature and type of these dislocation sources is the subject of extensive debate, however, one commonality amongst these theories is that the ability of the free surface to absorb dislocations is a necessary condition for transition to a source controlled regime. In this work we demonstrate that atomic layer deposition (ALD) of conformal 5–25 nm thick TiO_2/Al_(2)O_3 coatings onto electroplated single crystalline copper pillars with diameters ranging from 75 nm to 1 μm generally inhibits the ability of a dislocation to vanish at the free surface. Uniaxial compression tests reveal increased strength and hardening relative to uncoated pillars at equivalent diameters, as well as a notable recovery of plastic strain during unloading, i.e. the Bauschinger effect. Unlike previous reports, these coated pillars retained the stochastic signature in their stress–strain curves. We explain these observations within the framework of a size-dependent strength theory based on a single arm source model, dislocation theory, and microstructural analysis by transmission electron microscopy

Temporal Model Adaptation for Person Re-Identification

Person re-identification is an open and challenging problem in computer vision. Majority of the efforts have been spent either to design the best feature representation or to learn the optimal matching metric. Most approaches have neglected the problem of adapting the selected features or the learned model over time. To address such a problem, we propose a temporal model adaptation scheme with human in the loop. We first introduce a similarity-dissimilarity learning method which can be trained in an incremental fashion by means of a stochastic alternating directions methods of multipliers optimization procedure. Then, to achieve temporal adaptation with limited human effort, we exploit a graph-based approach to present the user only the most informative probe-gallery matches that should be used to update the model. Results on three datasets have shown that our approach performs on par or even better than state-of-the-art approaches while reducing the manual pairwise labeling effort by about 80%

Outbreak of West Nile virus causing severe neurological involvement in children, Nuba Mountains, Sudan, 2002.

An atypical outbreak of West Nile virus (WNV) occurred in Ngorban County, South Kordophan, Sudan, from May to August 2002. We investigated the epidemic and conducted a case-control study in the village of Limon. Blood samples were obtained for cases and controls. Patients with obvious sequelae underwent cerebrospinal fluid (CSF) sampling as well. We used enzyme-linked immunosorbent assay (ELISA) and neutralization tests for laboratory diagnosis and identified 31 cases with encephalitis, four of whom died. Median age was 36 months. Bivariate analysis did not reveal any significant association with the risk factors investigated. Laboratory analysis confirmed presence of IgM antibodies caused by WNV in eight of 13 cases, indicative of recent viral infection. The unique aspects of the WNW outbreak in Sudan, i.e. disease occurrence solely among children and the clinical domination of encephalitis, involving severe neurological sequelae, demonstrate the continuing evolution of WNV virulence. The spread of such a virus to other countries or continents cannot be excluded

High Resolution Mid-Infrared Imaging of Ultraluminous Infrared Galaxies

Observations of ultraluminous infrared galaxies (ULIRGs) with an achieved resolution approaching the diffraction limit in the mid-infrared from 8 - 25 $\mu$m using the Keck Telescopes are reported. We find extremely compact structures, with spatial scales of $< 0.3''$ (diameter) in six of the seven ULIRGs observed. These compact sources emit between 30% and 100% of the mid-infrared energy from these galaxies. We have utilized the compact mid-infrared structures as a diagnostic of whether an AGN or a compact (100 -- 300 pc) starburst is the primary power source in these ULIRGs. In Markarian 231, the upper limit on the diameter of the 12.5 $\mu$m source, 0.13$''$, shows that the size of the infrared source must increase with increasing wavelength, consistent with AGN models. In IRAS 05189-2524 and IRAS 08572+3915 there is strong evidence that the source size increases with increasing wavelength. This suggests heating by a central source rather than an extended luminosity source, consistent with the optical classification as an AGN. The compact mid-infrared sources seen in the other galaxies cannot be used to distinguish the ultimate luminosity source. If these ULIRGs are powered by compact starbursts, the star formation rates seen in the central few hundred parsecs far exceed the global rates seen in nearby starburst galaxies, and approach the surface brightness of individual clusters in nearby starburst galaxies.Comment: 33pages, 6 tables, 5 figures, Accepted for publication in A

Unsupervised Adaptation from Repeated Traversals for Autonomous Driving

For a self-driving car to operate reliably, its perceptual system must generalize to the end-user's environment -- ideally without additional annotation efforts. One potential solution is to leverage unlabeled data (e.g., unlabeled LiDAR point clouds) collected from the end-users' environments (i.e. target domain) to adapt the system to the difference between training and testing environments. While extensive research has been done on such an unsupervised domain adaptation problem, one fundamental problem lingers: there is no reliable signal in the target domain to supervise the adaptation process. To overcome this issue we observe that it is easy to collect unsupervised data from multiple traversals of repeated routes. While different from conventional unsupervised domain adaptation, this assumption is extremely realistic since many drivers share the same roads. We show that this simple additional assumption is sufficient to obtain a potent signal that allows us to perform iterative self-training of 3D object detectors on the target domain. Concretely, we generate pseudo-labels with the out-of-domain detector but reduce false positives by removing detections of supposedly mobile objects that are persistent across traversals. Further, we reduce false negatives by encouraging predictions in regions that are not persistent. We experiment with our approach on two large-scale driving datasets and show remarkable improvement in 3D object detection of cars, pedestrians, and cyclists, bringing us a step closer to generalizable autonomous driving.Comment: Accepted by NeurIPS 2022. Code is available at https://github.com/YurongYou/Rote-D

Point-charge electrostatics in disordered alloys

A simple analytic model of point-ion electrostatics has been previously proposed in which the magnitude of the net charge q_i on each atom in an ordered or random alloy depends linearly on the number N_i^(1) of unlike neighbors in its first coordination shell. Point charges extracted from recent large supercell (256-432 atom) local density approximation (LDA) calculations of Cu-Zn random alloys now enable an assessment of the physical validity and accuracy of the simple model. We find that this model accurately describes (i) the trends in q_i vs. N_i^(1), particularly for fcc alloys, (ii) the magnitudes of total electrostatic energies in random alloys, (iii) the relationships between constant-occupation-averaged charges and Coulomb shifts (i.e., the average over all sites occupied by either $A$ or $B$ atoms) in the random alloy, and (iv) the linear relation between the site charge q_i and the constant- charge-averaged Coulomb shift (i.e., the average over all sites with the same charge) for fcc alloys. However, for bcc alloys the fluctuations predicted by the model in the q_i vs. V_i relation exceed those found in the LDA supercell calculations. We find that (a) the fluctuations present in the model have a vanishing contribution to the electrostatic energy. (b) Generalizing the model to include a dependence of the charge on the atoms in the first three (two) shells in bcc (fcc) - rather than the first shell only - removes the fluctuations, in complete agreement with the LDA data. We also demonstrate an efficient way to extract charge transfer parameters of the generalized model from LDA calculations on small unit cells.Comment: 15 pages, ReVTeX galley format, 7 eps figures embedded using psfig, to be published in Phys. Rev.

Data-adaptive harmonic spectra and multilayer Stuart-Landau models

Harmonic decompositions of multivariate time series are considered for which we adopt an integral operator approach with periodic semigroup kernels. Spectral decomposition theorems are derived that cover the important cases of two-time statistics drawn from a mixing invariant measure. The corresponding eigenvalues can be grouped per Fourier frequency, and are actually given, at each frequency, as the singular values of a cross-spectral matrix depending on the data. These eigenvalues obey furthermore a variational principle that allows us to define naturally a multidimensional power spectrum. The eigenmodes, as far as they are concerned, exhibit a data-adaptive character manifested in their phase which allows us in turn to define a multidimensional phase spectrum. The resulting data-adaptive harmonic (DAH) modes allow for reducing the data-driven modeling effort to elemental models stacked per frequency, only coupled at different frequencies by the same noise realization. In particular, the DAH decomposition extracts time-dependent coefficients stacked by Fourier frequency which can be efficiently modeled---provided the decay of temporal correlations is sufficiently well-resolved---within a class of multilayer stochastic models (MSMs) tailored here on stochastic Stuart-Landau oscillators. Applications to the Lorenz 96 model and to a stochastic heat equation driven by a space-time white noise, are considered. In both cases, the DAH decomposition allows for an extraction of spatio-temporal modes revealing key features of the dynamics in the embedded phase space. The multilayer Stuart-Landau models (MSLMs) are shown to successfully model the typical patterns of the corresponding time-evolving fields, as well as their statistics of occurrence.Comment: 26 pages, double columns; 15 figure

Pre-Training LiDAR-Based 3D Object Detectors Through Colorization

Accurate 3D object detection and understanding for self-driving cars heavily relies on LiDAR point clouds, necessitating large amounts of labeled data to train. In this work, we introduce an innovative pre-training approach, Grounded Point Colorization (GPC), to bridge the gap between data and labels by teaching the model to colorize LiDAR point clouds, equipping it with valuable semantic cues. To tackle challenges arising from color variations and selection bias, we incorporate color as "context" by providing ground-truth colors as hints during colorization. Experimental results on the KITTI and Waymo datasets demonstrate GPC's remarkable effectiveness. Even with limited labeled data, GPC significantly improves fine-tuning performance; notably, on just 20% of the KITTI dataset, GPC outperforms training from scratch with the entire dataset. In sum, we introduce a fresh perspective on pre-training for 3D object detection, aligning the objective with the model's intended role and ultimately advancing the accuracy and efficiency of 3D object detection for autonomous vehicles

High Resolution Mid-Infrared Imaging of Infrared Luminous Starburst Galaxies

Observations for seven infrared luminous starburst galaxies are reported in the mid-infrared from 8 - 18 microns using the Keck Telescopes with spatial resolution approaching the diffraction limit. All of the galaxies observed show evidence of strong interactions based on optical morphologies. For these galaxies, a substantial fraction, usually more than 50%, of the infrared luminosity is generated in regions ranging in sizes from 100pc -- 1 Kpc. Nuclear starbursts often dominate the infrared luminosity, but this is not always true. In some galaxies, most notably NGC 6090, substantial infrared luminosity greatly in excess of the nuclear luminosity is generated in regions associated with the physical interaction between two galaxies. The radio emission is a good tracer of the location of high luminosity young stars. The visual/ultraviolet radiation output of the nearby star forming galaxies is dominated by emission from regions that are generally not producing the copious infrared luminosity of the systems. The regions of high infrared luminosity in local starburst galaxies are significantly smaller than the galaxies as a whole. The integrated spectral energy distributions (SEDs) of these galaxies are very different from the SEDs of the regions of star formation. If the SEDs of star-forming regions in these galaxies reflect the SEDs found in forming galaxies at high redshift, the distant galaxies should be dominated by the mid and far-infrared luminosity output far more than the integrated luminous output of nearby starburst galaxies would suggest