Optimal Feature Transport for Cross-View Image Geo-Localization

This paper addresses the problem of cross-view image geo-localization, where the geographic location of a ground-level street-view query image is estimated by matching it against a large scale aerial map (e.g., a high-resolution satellite image). State-of-the-art deep-learning based methods tackle this problem as deep metric learning which aims to learn global feature representations of the scene seen by the two different views. Despite promising results are obtained by such deep metric learning methods, they, however, fail to exploit a crucial cue relevant for localization, namely, the spatial layout of local features. Moreover, little attention is paid to the obvious domain gap (between aerial view and ground view) in the context of cross-view localization. This paper proposes a novel Cross-View Feature Transport (CVFT) technique to explicitly establish cross-view domain transfer that facilitates feature alignment between ground and aerial images. Specifically, we implement the CVFT as network layers, which transports features from one domain to the other, leading to more meaningful feature similarity comparison. Our model is differentiable and can be learned end-to-end. Experiments on large-scale datasets have demonstrated that our method has remarkably boosted the state-of-the-art cross-view localization performance, e.g., on the CVUSA dataset, with significant improvements for top-1 recall from 40.79% to 61.43%, and for top-10 from 76.36% to 90.49%. We expect the key insight of the paper (i.e., explicitly handling domain difference via domain transport) will prove to be useful for other similar problems in computer vision as well

Preparing and characterizing Fe3O4@cellulose nanocomposites for effective isolation of cellulose-decomposing microorganisms

This study developed Fe3O4@cellulose nanocomposites by co-precipitation synthesis for bacteria capture and isolation. By surface modification with cellulose, the Fe3O4@cellulose nanocomposites have 20 nm average particle size and 3.3–24.9 emu/g saturation magnetization. Living bacteria could be captured by the Fe3O4@cellulose nanocomposites and harvested by magnetic field, with high efficiency (95.1%) and stability (>99.99%). By metabolizing cellulose and destroying the Fe3O4@cellulose@bacteria complex, cellulose-decomposing microorganisms lost the magnetism. They were therefore able to be isolated from the inert microbial community and the separation efficiency achieved over 99.2%. This research opened a door to cultivate the uncultivable cellulose-decomposing microorganisms in situ and further characterize their ecological functions in natural environment

Influence of Laserâ Microtextured Surface Collar on Marginal Bone Loss and Periâ Implant Soft Tissue Response: A Systematic Review and Metaâ Analysis

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142176/1/jper0651-sup-0003.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142176/2/jper0651.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142176/3/jper0651-sup-0004.pd

Ventilation Structure Improvement of Air-cooled Induction Motor Using Multiphysics Simulations

 Optimal design of large induction motor is a process that involves electrical and mechanical skills as well as thermal and fluid dynamic skills. For recent machine layouts, one cannot rely on standard analysis methods. In multiphysics simulations which are done by weak coupling finite-element method, rotation boundary values on interface between air gap and rotor cannot be applied directly for fluid-dynamical analysis. A novel multi-component fluid method is proposed to deal with the influence of rotor rotation upon the air convection. This paper investigates a 3-D multi-physics simulation used in simulation of temperature distribution in air-cooled induction motor. The temperature rise in motor is due to Joule’s losses in stator windings and the induced eddy current in squirrel cages, and heat dissipation by air convection and solid conduction. The Joule’s losses calculated by 3-D eddy-current field analysis are used as the input for the thermal field analysis, which deeply depends on accurate air fluid field analysis. Through the coupled-field calculation, we proposed a new ventilation structure of a 15-phase motor to improve the cooling performance

Mechanism of collective interstitial ordering in Fe–C alloys

Collective interstitial ordering is at the core of martensite formation in Fe–C-based alloys, laying the foundation for high-strength steels. Even though this ordering has been studied extensively for more than a century, some fundamental mechanisms remain elusive. Here, we show the unexpected effects of two correlated phenomena on the ordering mechanism: anharmonicity and segregation. The local anharmonicity in the strain fields induced by interstitials substantially reduces the critical concentration for interstitial ordering, up to a factor of three. Further, the competition between interstitial ordering and segregation results in an effective decrease of interstitial segregation into extended defects for high interstitial concentrations. The mechanism and corresponding impact on interstitial ordering identified here enrich the theory of phase transitions in materials and constitute a crucial step in the design of ultra-high-performance alloys

Study of the correlation between ApoB/ApoA1 and vitreous hemorrhage secondary to diabetic retinopathy

Objective To investigate the correlation between ApoB/ApoA1 and vitreous hemorrhage （VH） secondary to diabetic retinopathy （DR）. Methods 187 patients with DR from August 2021 to December 2022 were recruited and divided into VH （n=96） and non-VH groups （n=91）. Baseline data were compared between two groups. The risk factors of VH secondary to DR were analyzed by Logistic regression analysis. Results There were no significant differences in age， gender， course of disease， body mass index （BMI）， history of hypertension， smoking and drinking between two groups （all P > 0.05）. In the VH group， fasting plasma glucose （FPG）， glycosylated hemoglobin A1c （HbA1c）， total cholesterol （TC）， high-density lipoprotein cholesterol （HDL-C）， low-density lipoprotein cholesterol （LDL-C）， ApoB/ApoA1 and FIBrinogen （FIB） were significantly higher compared with those in the non-VH group， and the differences were statistically significant （all P < 0.05）， while there were no significant differences in TG， APTT， PT and TT between two groups （all P > 0.05）. HbA1c （OR=1.438 （1.179-1.864））， ApoB/ApoA1 （OR=25.274（5.699~112.092）） and FIB （OR=1.471（1.022~2.118）） were the risk factors for VH （all P < 0.05）. Conclusions HbA1c， ApoB/ApoA1 and FIB are closely related to VH. Monitoring blood glucose， lipid and coagulation and timely intervention can delay the progression of DR and reduce the incidence of VH