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At least 37 records · Page 2

4DoF Drift Free Navigation Using Inertial Cues and Optical Flow

In this paper, we describe a novel approach in fusing optical flow with inertial cues (3D acceleration and 3D angular velocities) in order to navigate a Micro Aerial Vehicle (MAV) drift free in 4DoF and metric velocity. Our approach only requires two consecutive images with a minimum of three feature matches. It does not require any (point) map nor any type of feature history. Thus it is an inherently failsafe approach that is immune to map and feature-track failures. With these minimal requirements we show in real experiments that the system is able to navigate drift free in all angles including yaw, in one metric position axis, and in 3D metric velocity. Furthermore, it is a power-on-and-go system able to online self-calibrate the inertial biases, the visual scale and the full 6DoF extrinsic transformation parameters between camera and IMU.

reconnissance↗

Supernova 1972 e in NGC 5253

New absolute energy distributions of the Type 1 supernova 1972e in NGC 5253 extending to about 700 days after maximum light were obtained. A physical model of the expanding envelope, based on the identification of the feature at 6550 A with H-alpha, is proposed. It is described as a differentially expanding atmosphere, with electron density ranging from 10 to the 10th power near maximum light to about 10 to the 7th power, 340 days later, illuminated by a photosphere with temperature in the range 10,000 K to 7,000 K. More than 200 days after maximum, the spectrum was dominated by four features between 4200 A and 5500 A. Three of these four features matched the blended emissions from over 100 lines of Fe II. Possible identifications of the fourth feature with Mg I lambda 4571 or permitted lines of Fe II are also discussed.

Kirshner, R. P.↗

Silicates and aromatic hydrocarbons in the 10 micron spectrum of the Taurus dark cloud source Elias 1

We have obtained 10.4-12 micrometer spectra at spectral resolution R approximately equal to 190 of the Herbig Ae star Elias 1 in the Taurus dark cloud with the United Kingdom Infrared Telescope (UKIRT) CGS3 spectrometer, along with an 8-13 micrometer spectrum at R approximately equal to 55. The 11.2 micrometer emission feature matches the wavelength, shape, and full width at half maximum (FWHM) of the 11.22 micrometer aromatic hydrocarbon band, consistent with the presence of other aromatic features. A strong 11.06 micrometer feature is present, and there are two possible new emission features at 11.6 and 11.76 micrometer. The strong silicate emission feature is broader and peaks at a longer wavelength than can be reproduced with the Trapezium emissivity. Larger grains, with mean radius a approximately 1.5 micrometers appear to be required, a possible indication of grain growth around a young star.

Hanner, Martha S.↗

Robust Semantic Mapping and Localization on a Free-Flying Robot in Microgravity

We propose a system that uses semantic object detections to localize a microgravity free-flyer. Many applications require absolute localization in a known reference frame, such as the execution of waypoint trajectories defined by human operators. Classical geometric methods build a map of point features, which may not be able to be associated after lighting or environmental changes. By contrast, semantics remain invariant to changes up to the robustness of the detection algorithm and motion of the semantic objects. In this work, we describe our approaches for both offline semantic map generation as well as online localization against a semantic map, intended to run in real-time on the robot. We additionally demonstrate how our semantic localizer outperforms image-feature matching in some cases, and show the robustness of the algorithm to environmental changes. Crucially, we show in our experiments that when semantics are used to supplement point features, localization is always improved. To our knowledge, these experiments demonstrate the first use of learned semantics for localization on a free-flying robot in microgravity.

Localization↗

Chandra Imaging of the X-Ray Nebula Powered by Pulsar B1509-58

We present observations with the Chandra X-Ray Observatory of the pulsar wind nebula (PWN) powered by the energetic young pulsar B1509-58. These data confirm the complicated morphology of the system indicated by previous observations, and in addition reveal several new components to the nebula. The overall PWN shows a clear symmetry axis oriented at a position angle 150" +- 5" (north through east), which we argue corresponds to the pulsar spin axis. We show that a previously identified radio feature matches well with the overall extent of the X-ray PWN, and propose the former as the long-sought radio nebula powered by the pulsar. We further identify a bright collimated feature, at least 4' long, lying along the nebula's main symmetry axis; we interpret this feature as a physical outflow from the pulsar, and infer a velocity for this jet of greater than 0.2c. The lack of any observed counterjet implies that the pulsar spin axis is inclined at -30" to the line of sight, contrary to previous estimates made from lower resolution data. We also identify a variety of compact features close to the pulsar. A pair of semicircular X-ray arcs lie 17" and 30" to the north of the pulsar; the latter arc shows a highly polarized radio counterpart. We show that these features can be interpreted as ion compression wisps in a particle-dominated equatorial flow, and use their properties to infer a ratio of electromagnetic to particle energy in pairs at the wind shock 0.005, similar to that seen in the Crab Nebula. We further identify several compact knots seen very close to the pulsar; we use these to infer cr < 0.003 at a separation from the pulsar of 0.1 pc.

Gaensler, B. M.↗

Supernova 1972e in NGC 5253

Absolute energy distributions of the Type I supernova 1972e in NGC 5253 extending to about 700 days after maximum light have been obtained. A physical model of the expanding envelope, based on the identification of the feature at 6550 A with H-alpha is proposed. It consists of a differentially expanding atmosphere, with electron density ranging from 10 billion near maximum light to about 10 million 340 days later, illuminated by a photosphere with temperature in the range from 10,000 K to 7000 K. Under these conditions, the identifications of Ca II 8600-A, H, and K lines, the Na D lines, and the Mg I b lines forming P Cygni lines are quite plausible. More than 200 days after maximum, the spectrum is dominated by four features between 4200 and 5500 A. Three of these four features match the blended emissions from over 100 Fe II forbidden lines. If this identification is correct, the envelope requires about 0.01 solar mass of iron, which corresponds to an Fe/H ratio about 20 times higher than the cosmic abundance. Possible identifications of the fourth feature with the Mg I 4571-A line or permitted lines of Fe II are also discussed.

Kirshner, R. P.↗

Transforming AdaPT to Ada9x

How the concepts of AdaPT can be transformed into programs using the object oriented features proposed in the preliminary mapping for Ada9x are described. Emphasizing, as they do, the importance of data types as units of program, these features match well with the development of partitions as translations into Abstract Data Types which was exploited in the Ada83 translation covered in report R3. By providing a form of polymorphic type, the Ada83 version also gives support for the conformant partition idea which could be achieved in Ada83 only by using UNCHECKED CONVERSIONS. It is assumed that the reader understands AdaPT itself, but the translation into Ada83 is briefly reviewed, by applying it to a small example. This is then used to show how the same translation would be achieved in the 9x version. It is important to appreciate that the distribution features which are proposed in current mapping are not used or discussed in any detail, as those are not well matched to the AdaPT approach. Critical evaluation and comparison of these approaches is given in a separate report.

Goldsack, Stephen J.↗

Large-scale stationary and turbulent flow over topography

The contributions made to the formation of stationary features of flow over topography by linear and nonlinear dynamics were examined with an integrated quasi-geostrophic model with idealized topographic forcing. The simulation was run out to several months and generated time-averaged values which were compared with those obtained with linear theory. Linear predictions were converted to turbulent features through the addition of stationary, nonlinear thermodynamic and transient vorticity fluxes. The turbulence features matched atmospheric data on energy spectra, the direction and magnitude of energy transfers, and the spatial magnitudes involved. Transient flow transferred the majority of energy absorbed by the upscale flow and, by absorbing energy, reduced the energy of stationary flow while retaining resonance signatures. Instability was a pervasive feature of the topographically forced flow except at high wavenumbers. The results confirm that transient eddies are interactive with both asymmetric and zonal flow and cannot be adequately described by linear theory.

Vallis, G. K.↗

A bi-channel aided stitching of atomic force microscopy images

Microscopy is an essential tool in scientific research, enabling the visualization of structures at micro- and nanoscale resolutions. However, the field of microscopy often encounters limitations in field-of-view (FOV), restricting the amount of sample that can be imaged in a single capture. To overcome this limitation, image stitching techniques have been developed to seamlessly merge multiple overlapping images into a single, high-resolution composite. The images collected from microscope need to be optimally stitched before accurate physical information can be extracted from post analysis. However, the existing stitching tools either struggle to stitch images together when the microscopy images are feature sparse or cannot address all the transformations of images when performing image stitching. To address these issues, we propose a bi-channel aided feature-based image stitching method and demonstrate its use on Atomic Force Microscopy (AFM) generated Pantoea sp. YR343 biofilm and PTO thin film sample images as experimental data. The topographical channel image of AFM data captures the morphological details of the sample, and a stitched topographical image is desired for researchers. We utilize the amplitude and phase channels of AFM data to maximize the matching features and to estimate the position of the original topographical images and show that the proposed bi-channel aided stitching method outperforms the traditional direct stitching approach in AFM topographical image stitching task. Here, we demonstrated the application on AFM, but similar approaches could be employed of optical microscopy with brightfield and fluorescence channels. We believe this proposed workflow can serve as a valuable augmentation strategy for microscopy image stitching tasks and will benefit the experimentalist to avoid erroneous analysis and discovery due to incorrect stitching.

Atomic force microscopy↗

(Almost) Featureless Stereo: Calibration and Dense 3D Reconstruction Using Whole Image Operations

The conventional approach to shape from stereo is via feature extraction and correspondences. This results in estimates of the camera parameters and a typically spare estimate of the surface. Given a set of calibrated images, a dense surface reconstruction is possible by minimizing the error between the observed image and the image rendered from the estimated surface with respect to the surface model parameters. Given an uncalibrated image and an estimated surface, the camera parameters can be estimated by minimizing the error between the observed and rendered images a function of the camera parameters. We use a very small dense set of matched features to provide camera parameter estimates for the initial dense surface estimate. We then re-estimate the camera parameters as described above, and then re-estimate the surface. This process is iterated. Whilst it can not be proven to converge, we have found that around three iterations results in excellent surface and camera parameters estimates.

Smelyanskiy, V. N.↗

Tightly-coupled camera/LiDAR integration for point cloud generation from GNSS/INS-assisted UAV mapping systems

Unmanned aerial vehicles (UAVs) equipped with integrated global navigation satellite systems/inertial navigation systems (GNSS/INS) together with cameras and/or LiDAR sensors are being widely used for topographic mapping in a variety of applications such as precision agriculture, coastal monitoring, and archaeological documentation. Integration of image-based and LiDAR point clouds can provide a comprehensive 3D model of the area of interest. For such integration, ensuring a good alignment between data from the different sources is critical. Although many works have been conducted on this topic, there is still a need for a rigorous integration approach that minimizes the discrepancy between camera and LiDAR data caused by inaccurate system calibration parameters and/or trajectory artifacts. This study proposes an automated tightly-coupled camera/LiDAR integration workflow for GNSS/INS-assisted UAV systems. The proposed strategy is conducted in three main steps. First, an image-based point cloud is generated using a LiDAR/GNSS/INS-assisted structure from motion (SfM) strategy. Then, feature correspondences between image-based and LiDAR point clouds are automatically identified. Finally, an integrated-bundle adjustment procedure including image points, LiDAR raw measurements, and GNSS/INS information is conducted to minimize the discrepancy between point clouds from different sensors while estimating system calibration parameters and refining the trajectory information. The proposed SfM strategy and integration framework are evaluated using five datasets. The SfM results show that using LiDAR data can facilitate feature matching and further increase the number of reconstructed 3D points. The experimental results also illustrate that the developed automated camera/LiDAR integration strategy is capable of accurately estimating system calibration parameters to achieve good alignment among camera/LiDAR data from single/multiple systems. Finally, an absolute accuracy in the range of 3–5 cm is achieved for the image/LiDAR point clouds after the integration process.

42 ENGINEERING↗

Label-Free Profiling of up to 200 Single-Cell Proteomes per Day Using a Dual-Column Nanoflow Liquid Chromatography Platform

Single-cell proteomics (SCP) has great potential to advance biomedical research and personalized medicine. The sensitivity of such measurements increases with low-flow separations (<100 nL/min) due to improved ionization efficiency, but the time required for sample loading, column washing, and regeneration in these systems can lead to low measurement throughput and inefficient utilization of the mass spectrometer. Herein, we developed a two-column liquid chromatography (LC) system that dramatically increases the throughput of label-free SCP using two parallel subsystems to multiplex sample loading, online desalting, analysis, and column regeneration. The integration of MS1-based feature matching increased proteome coverage when short LC gradients were used. The high-throughput LC system was reproducible between the columns, with a 4% difference in median peptide abundance and a median CV of 18% across 100 replicate analyses of a single-cell-sized peptide standard. An average of 621, 774, 952, and 1622 protein groups were identified with total analysis times of 7, 10, 15, and 30 min, corresponding to a measurement throughput of 206, 144, 96, and 48 samples per day, respectively. When applied to single HeLa cells, we identified nearly 1000 protein groups per cell using 30 min cycles and 660 protein groups per cell for 15 min cycles. Finally, we explored the possibility of measuring cancer therapeutic targets with a pilot study comparing the K562 and Jurkat leukemia cell lines. This work demonstrates the feasibility of high-throughput label-free single-cell proteomics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ultrasensitive single-cell proteomics workflow identifies >1000 protein groups per mammalian cell

Here, we report on the combination of nanodroplet sample preparation, ultra-low-flow nanoLC, high-field asymmetric ion mobility spectrometry (FAIMS), and the latest-generation Orbitrap Eclipse Tribrid mass spectrometer for greatly improved single-cell proteome profiling. FAIMS effectively filtered out singly charged ions for more effective MS analysis of multiply charged peptides, resulting in an average of 1056 protein groups identified from single HeLa cells without MS1-level feature matching. This is 2.3 times more identifications than without FAIMS and a far greater level of proteome coverage for single mammalian cells than has been previously reported for a label-free study. Differential analysis of single microdissected motor neurons and interneurons from human spinal tissue indicated a similar level of proteome coverage, and the two subpopulations of cells were readily differentiated based on single-cell label-free quantification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Backlighting extended gas halos around luminous red galaxies: Kinematic Sunyaev-Zel’dovich effect from DESI Y1 and ACT data

The gas density profile around galaxies, shaped by feedback and affecting the galaxy lensing signal, is imprinted on the cosmic microwave background (CMB) by the kinematic Sunyaev-Zel’dovich effect (kSZ). We precisely measure this effect (𝑆/𝑁 ≈ 10) via velocity stacking with 825,283 spectroscopically confirmed luminous red galaxies (LRG) from the Dark Energy Spectroscopic Instrument Year 1 (DESI Y1) survey, which overlap with the Atacama Cosmology Telescope (ACT) Data Release 6 temperature maps over ≥ 4,000 deg 2 . We explore the kSZ dependence with various galaxy parameters and find no significant trend with redshift but clear trends with stellar mass and absolute magnitude in 𝑔, 𝑟, and 𝑧 bands. Our analysis suggests that the gas extends beyond the dark matter halo (99.5% confidence level, i.e., probability to exceed (PTE)⁢ = 0.005). We find a tentative preference for hydrodynamical simulation models with stronger feedback that drives gas further out (Illustris 𝑧 = 0.5, PTE⁢ = 0.37) over weaker-feedback cases (IllustrisTNG 𝑧 = 0.8, PTE⁢ = 0.045), though with limited statistical significance. In all cases, a free multiplicative amplitude was fit to the simulated profiles, and further modeling work is required to firm up these conclusions. We find consistency between kSZ profiles around spectroscopic and photometric LRG, with comparable statistical power, thus increasing our confidence in the photometric analysis. Additionally, we present the first kSZ measurement around the DESI Y1 bright galaxy sample (BGS) and the emission-line galaxies (ELG) whose features match qualitative expectations. Finally, we forecast 𝑆/𝑁 ∼ 50 for future stacked kSZ measurements using data from the ACT, the DESI Y3, and the Rubin Observatory. Furthermore, these measurements will serve as an input for galaxy formation models and baryonic uncertainties in galaxy lensing.

79 ASTRONOMY AND ASTROPHYSICS↗

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗

All-optical, Microwave-free NV-Diamond Magnetometer for Weak Magnetic Field Environments

Sensitive nitrogen-vacancy (NV) magnetometry typically requires a bias field to lift the spin level degeneracy and has commonly utilized microwave sources to selectively manipulate the sensor's spin state. However, this external bias field and microwave sources may perturb the sample of interest or be incompatible with operational conditions. Here, we demonstrate an all-optical, microwave-free NV-diamond magnetometer in the presence of weak or no bias magnetic field (<20 G). We experimentally measure photoluminescence spectra using diamonds with varying NV concentrations; and numerically simulate matching features due to cross-relaxation between NVs. Our results pave the way towards a sensitive probe to study magnetic systems that can be disrupted by microwave signals and can only tolerate weak bias magnetic field.

Ung, Kristine↗

Fe(III) (oxyhydr)oxide reduction by the thermophilic iron-reducing bacterium Desulfovulcanus ferrireducens

Some thermophilic bacteria from deep-sea hydrothermal vents grow by dissimilatory iron reduction, but our understanding of their biogenic mineral transformations is nascent. Mineral transformations catalyzed by the thermophilic iron-reducing bacterium Desulfovulcanus ferrireducens during growth at 55°C were examined using synthetic nanophase ferrihydrite, akaganeite, and lepidocrocite separately as terminal electron acceptors. Spectral analyses using visible-near infrared (VNIR), Fourier-transform infrared attenuated total reflectance (FTIR-ATR), and Mössbauer spectroscopies were complemented with x-ray diffraction (XRD) and transmission electron microscopy (TEM) using selected area electron diffraction (SAED) and energy dispersive X-ray (EDX) analyses. The most extensive biogenic mineral transformation occurred with ferrihydrite, which produced a magnetic, visibly dark mineral with spectral features matching cation-deficient magnetite. Desulfovulcanus ferrireducens also grew on akaganeite and lepidocrocite and produced non-magnetic, visibly dark minerals that were poorly soluble in the oxalate solution. Bioreduced mineral products from akaganeite and lepidocrocite reduction were almost entirely absorbed in the VNIR spectroscopy in contrast to both parent minerals and the abiotic controls. However, FTIR-ATR and Mössbauer spectra and XRD analyses of both biogenic minerals were almost identical to the parent and control minerals. The TEM of these biogenic minerals showed the presence of poorly crystalline iron nanospheres (50–200 nm in diameter) of unknown mineralogy that were likely coating the larger parent minerals and were absent from the controls. The study demonstrated that thermophilic bacteria transform different types of Fe(III) (oxyhydr)oxide minerals for growth with varying mineral products. These mineral products are likely formed through dissolution-reprecipitation reactions but are not easily predictable through chemical equilibrium reactions alone.

12 reflectance spectroscopy↗

Computer-Vision-Based Vibration Tracking Using a Digital Camera: A Sparse-Optical-Flow-Based Target Tracking Method

Computer-vision-based target tracking is a technology applied to a wide range of research areas, including structural vibration monitoring. However, current target tracking methods suffer from noise in digital image processing. In this paper, a new target tracking method based on the sparse optical flow technique is introduced for improving the accuracy in tracking the target, especially when the target has a large displacement. The proposed method utilizes the Oriented FAST and Rotated BRIEF (ORB) technique which is based on FAST (Features from Accelerated Segment Test), a feature detector, and BRIEF (Binary Robust Independent Elementary Features), a binary descriptor. ORB maintains a variety of keypoints and combines the multi-level strategy with an optical flow algorithm to search the keypoints with a large motion vector for tracking. Then, an outlier removal method based on Hamming distance and interquartile range (IQR) score is introduced to minimize the error. The proposed target tracking method is verified through a lab experiment—a three-story shear building structure subjected to various harmonic excitations. It is compared with existing sparse-optical-flow-based target tracking methods and target tracking methods based on three other types of techniques, i.e., feature matching, dense optical flow, and template matching. The results show that the performance of target tracking is greatly improved through the use of a multi-level strategy and the proposed outlier removal method. The proposed sparse-optical-flow-based target tracking method achieves the best accuracy compared to other existing target tracking methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗