Local Hall effect in hybrid ferromagnetic/semiconductor devices

We have investigated the magnetoresistance of ferromagnet-semiconductor devices in an InAs two-dimensional electron gas system in which the magnetic field has a sinusoidal profile. The magnetoresistance of our device is large. The longitudinal resistance has an additional contribution which is odd in applied magnetic field. It becomes even negative at low temperature where the transport is ballistic. Based on the numerical analysis, we confirmed that our data can be explained in terms of the local Hall effect due to the profile of negative and positive field regions. This device may be useful for future spintronic applications.Comment: 4 pages with 4 fugures. Accepted for publication in Applied Physics Letter

An Efficient ISAR Imaging Method for Multiple Targets

This paper proposes an efficient method to obtain TSAR images of multiple targets flying in formation. The proposed method improves the coarse alignment and segmentation of the existing method. The improved coarse alignment method models the flight trajectory using a combination of a polynomial and Gaussian basis functions, and the optimum parameter of the trajectory is found using particle swarm optimization. In the improved segmentation, the binary image of the bulk TSAR image that contains all targets is constructed using a two-dimensional constant false alarm detector, then the image closing method is applied to the binary image. Finally, the connected set of binary pixels is used to segment each target from the bulk image. Simulations using three targets composed of point scattering centers and the measured data of the Boeing747 aircraft prove the effectiveness of the proposed method to segment three targets flying in formation.X113Ysciescopu

Locally Adaptive Products for Genuine Spherical Harmonic Lighting

Precomputed radiance transfer techniques have been broadly used for supporting complex illumination effects on diffuse and glossy objects. Although working with the wavelet domain is efficient in handling all-frequency illumination, the spherical harmonics domain is more convenient for interactively changing lights and views on the fly due to the rotational invariant nature of the spherical harmonic domain. For interactive lighting, however, the number of coefficients must be limited and the high orders of coefficients have to be eliminated. Therefore spherical harmonic lighting has been preferred and practiced only for interactive soft-diffuse lighting. In this paper, we propose a simple but practical filtering solution using locally adaptive products of high-order harmonic coefficients within the genuine spherical harmonic lighting framework. Our approach works out on the fly in two folds. We first conduct multi-level filtering on vertices in order to determine regions of interests, where the high orders of harmonics are necessary for high frequency lighting. The initially determined regions of interests are then refined through filling in the incomplete regions by traveling the neighboring vertices. Even not relying on graphics hardware, the proposed method allows to compute high order products of spherical harmonic lighting for both diffuse and specular lighting

Micro-Doppler Extraction and ANalysis of the Ballistic Missile Using RDA Based on the Flight Scenario

11Yscopu

Editorial: Role of Microbes in Climate Smart Agriculture

[No abstract available

Comparison of the Plasma Metabolome Profiles Between the Internal Thoracic Artery and Ascending Aorta in Patients Undergoing Coronary Artery Bypass Graft Surgery Using Gas Chromatography Time-of-Flight Mass Spectrometry.

BackgroundThe left internal thoracic artery (LITA) has been used as the first conduit of choice in coronary artery bypass grafting (CABG) because of excellent long-term patency and outcomes. However, no studies have examined substances other than nitric oxide that could be beneficial for the bypass conduit, native coronary artery or ischemic myocardium. This study was conducted to evaluate differences in metabolic profiles between the LITA and ascending aorta using gas chromatography-time of flight-mass spectrometry (GC-TOF-MS).MethodsTwenty patients who underwent CABG using the LITA were prospectively enrolled. Plasma samples were collected simultaneously from the LITA and ascending aorta. GC-TOF-MS based untargeted metabolomic analyses were performed and a 2-step volcano plot analysis was used to identify distinguishable markers from two plasma metabolome profiles. Semi-quantitative and quantitative analyses were performed using GC-TOF-MS and enzyme-linked immunosorbent assay, respectively, after selecting target metabolites based on the metabolite set enrichment analysis.ResultsInitial volcano plot analysis demonstrated 5 possible markers among 851 peaks detected. The final analysis demonstrated that the L-cysteine peak was significantly higher in the LITA than in the ascending aorta (fold change = 1.86). The concentrations of intermediate metabolites such as L-cysteine, L-methionine and L-cystine in the 'cysteine and methionine metabolism pathway' were significantly higher in the LITA than in the ascending aorta (2.0-, 1.4- and 1.2-fold, respectively). Quantitative analysis showed that the concentration of hydrogen sulfide (H₂S) was significantly higher in the LITA.ConclusionThe plasma metabolome profiles of the LITA and ascending aorta were different, particularly higher plasma concentrations of L-cysteine and H₂S in the LITA

Shepherding Slots to Objects: Towards Stable and Robust Object-Centric Learning

Object-centric learning (OCL) aspires general and compositional understanding of scenes by representing a scene as a collection of object-centric representations. OCL has also been extended to multi-view image and video datasets to apply various data-driven inductive biases by utilizing geometric or temporal information in the multi-image data. Single-view images carry less information about how to disentangle a given scene than videos or multi-view images do. Hence, owing to the difficulty of applying inductive biases, OCL for single-view images remains challenging, resulting in inconsistent learning of object-centric representation. To this end, we introduce a novel OCL framework for single-view images, SLot Attention via SHepherding (SLASH), which consists of two simple-yet-effective modules on top of Slot Attention. The new modules, Attention Refining Kernel (ARK) and Intermediate Point Predictor and Encoder (IPPE), respectively, prevent slots from being distracted by the background noise and indicate locations for slots to focus on to facilitate learning of object-centric representation. We also propose a weak semi-supervision approach for OCL, whilst our proposed framework can be used without any assistant annotation during the inference. Experiments show that our proposed method enables consistent learning of object-centric representation and achieves strong performance across four datasets. Code is available at \url{https://github.com/object-understanding/SLASH}