Deep Shape Matching

We cast shape matching as metric learning with convolutional networks. We break the end-to-end process of image representation into two parts. Firstly, well established efficient methods are chosen to turn the images into edge maps. Secondly, the network is trained with edge maps of landmark images, which are automatically obtained by a structure-from-motion pipeline. The learned representation is evaluated on a range of different tasks, providing improvements on challenging cases of domain generalization, generic sketch-based image retrieval or its fine-grained counterpart. In contrast to other methods that learn a different model per task, object category, or domain, we use the same network throughout all our experiments, achieving state-of-the-art results in multiple benchmarks.Comment: ECCV 201

SD-208, a novel protein kinase D inhibitor, blocks prostate cancer cell proliferation and tumor Growth in Vivo by inducing G2/M cell cycle arrest

Protein kinase D (PKD) has been implicated in many aspects of tumorigenesis and progression, and is an emerging molecular target for the development of anticancer therapy. Despite recent advancement in the development of potent and selective PKD small molecule inhibitors, the availability of in vivo active PKD inhibitors remains sparse. In this study, we describe the discovery of a novel PKD small molecule inhibitor, SD-208, from a targeted kinase inhibitor library screen, and the synthesis of a series of analogs to probe the structure-activity relationship (SAR) vs. PKD1. SD-208 displayed a narrow SAR profile, was an ATP-competitive pan-PKD inhibitor with low nanomolar potency and was cell active. Targeted inhibition of PKD by SD-208 resulted in potent inhibition of cell proliferation, an effect that could be reversed by overexpressed PKD1 or PKD3. SD-208 also blocked prostate cancer cell survival and invasion, and arrested cells in the G2/M phase of the cell cycle. Mechanistically, SD-208-induced G2/M arrest was accompanied by an increase in levels of p21 in DU145 and PC3 cells as well as elevated phosphorylation of Cdc2 and Cdc25C in DU145 cells. Most importantly, SD-208 given orally for 24 days significantly abrogated the growth of PC3 subcutaneous tumor xenografts in nude mice, which was accompanied by reduced proliferation and increased apoptosis and decreased expression of PKD biomarkers including survivin and Bcl-xL. Our study has identified SD-208 as a novel efficacious PKD small molecule inhibitor, demonstrating the therapeutic potential of targeted inhibition of PKD for prostate cancer treatment

Effect of helium ion irradiation on pure W, W-5Ta and W-5Re: a micro-tensile and nanoindentation investigation of mechanical properties

Micro-tensile testing has been used to study the response of pure tungsten and two tungsten alloys to helium ion irradiation. Commercially supplied plates of W, W-5Ta and W-5Re were irradiated using 6 MeV helium ions at room temperature. The ion energy was attenuated with an energy spreading device such that a uniform level of damage at 0.6 dpa (and 11,000 appm He) was deposited at the 3–9 µm depth. Focused ion beam milling was used to fabricate dog-bone shaped, micro-tensile samples 5 × 5 µm in cross-sectional area and 17 µm in length from the unirradiated and irradiated samples. All micro-tensile samples were tested at a quasi-static strain rate and the stress–strain curves were analysed to determine the mechanical properties. A close correlation was found between micro-tensile results and the bulk mechanical properties reported in the literature. Comparison between the unirradiated micro-tensile properties of W-5Re and W-5Ta with W showed that, as expected, W-5Re was softer than W whilst W-5Ta had only minor differences in micro-tensile properties compared with W. The micro-tensile results of the irradiated W, W-5Ta and W-5Re showed an increase in strength and an almost complete loss of ductility compared to the unirradiated samples. In comparing micro-tensile results to nanoindentation measurements, it was found that micro-tensile offers comparable level of precision in measurement of irradiation hardening amongst W, W-5Ta and W-5Re. The implications of the results with respect to the future performance of tungsten-based materials in the divertors in fusion reactors are discussed in detail. Graphical abstract: [Figure not available: see fulltext.

Generic 3D Representation via Pose Estimation and Matching

Though a large body of computer vision research has investigated developing generic semantic representations, efforts towards developing a similar representation for 3D has been limited. In this paper, we learn a generic 3D representation through solving a set of foundational proxy 3D tasks: object-centric camera pose estimation and wide baseline feature matching. Our method is based upon the premise that by providing supervision over a set of carefully selected foundational tasks, generalization to novel tasks and abstraction capabilities can be achieved. We empirically show that the internal representation of a multi-task ConvNet trained to solve the above core problems generalizes to novel 3D tasks (e.g., scene layout estimation, object pose estimation, surface normal estimation) without the need for fine-tuning and shows traits of abstraction abilities (e.g., cross-modality pose estimation). In the context of the core supervised tasks, we demonstrate our representation achieves state-of-the-art wide baseline feature matching results without requiring apriori rectification (unlike SIFT and the majority of learned features). We also show 6DOF camera pose estimation given a pair local image patches. The accuracy of both supervised tasks come comparable to humans. Finally, we contribute a large-scale dataset composed of object-centric street view scenes along with point correspondences and camera pose information, and conclude with a discussion on the learned representation and open research questions.Comment: Published in ECCV16. See the project website http://3drepresentation.stanford.edu/ and dataset website https://github.com/amir32002/3D_Street_Vie

Structural analysis and corrosion studies on an ISO 5832-9 biomedical alloy with TiO2 sol–gel layers

The aim of this study was to demonstrate the relationship between the structural and corrosion properties of an ISO 5832-9 biomedical alloy modified with titanium dioxide (TiO2) layers. These layers were obtained via the sol–gel method by acid-catalyzed hydrolysis of titanium isopropoxide in isopropanol solution. To obtain TiO2 layers with different structural properties, the coated samples were annealed at temperatures of 200, 300, 400, 450, 500, 600 and 800 C for 2 h. For all the prepared samples, accelerated corrosion measurements were performed in Tyrode’s physiological solution using electrochemical methods. The most important corrosion parameters were determined: corrosion potential, polarization resistance, corrosion rate, breakdown and repassivation potentials. Corrosion damage was analyzed using scanning electron microscopy. Structural analysis was carried out for selected TiO2 coatings annealed at 200, 400, 600 and 800 C. In addition, the morphology, chemical composition, crystallinity, thickness and density of the deposited TiO2 layers were determined using suitable electron and X-ray measurement methods. It was shown that the structure and character of interactions between substrate and deposited TiO2 layers depended on annealing temperature. All the obtained TiO2 coatings exhibit anticorrosion properties, but these properties are related to the crystalline structure and character of substrate–layer interaction. From the point of view of corrosion, the best TiO2 sol–gel coatings for stainless steel intended for biomedical applications seem to be those obtained at 400 C.This study was supported by Grant No. N N507 501339 of the National Science Centre. The authors wish to express their thanks to J. Borowski (MEDGAL, Poland) for the Rex 734 alloy

Structure and function of a spectrin-like regulator of bacterial cytokinesis

© 2014 Macmillan Publishers Limited. All rights reserved. Bacterial cell division is facilitated by a molecular machine - the divisome - that assembles at mid-cell in dividing cells. The formation of the cytokinetic Z-ring by the tubulin homologue FtsZ is regulated by several factors, including the divisome component EzrA. Here we describe the structure of the 60-kDa cytoplasmic domain of EzrA, which comprises five linear repeats of an unusual triple helical bundle. The EzrA structure is bent into a semicircle, providing the protein with the potential to interact at both N- and C-termini with adjacent membrane-bound divisome components. We also identify at least two binding sites for FtsZ on EzrA and map regions of EzrA that are responsible for regulating FtsZ assembly. The individual repeats, and their linear organization, are homologous to the spectrin proteins that connect actin filaments to the membrane in eukaryotes, and we thus propose that EzrA is the founding member of the bacterial spectrin family

On the Effectiveness of Image Rotation for Open Set Domain Adaptation

Open Set Domain Adaptation (OSDA) bridges the domain gap between a labeled source domain and an unlabeled target domain, while also rejecting target classes that are not present in the source. To avoid negative transfer, OSDA can be tackled by first separating the known/unknown target samples and then aligning known target samples with the source data. We propose a novel method to addresses both these problems using the self-supervised task of rotation recognition. Moreover, we assess the performance with a new open set metric that properly balances the contribution of recognizing the known classes and rejecting the unknown samples. Comparative experiments with existing OSDA methods on the standard Office-31 and Office-Home benchmarks show that: (i) our method outperforms its competitors, (ii) reproducibility for this field is a crucial issue to tackle, (iii) our metric provides a reliable tool to allow fair open set evaluation.Comment: accepted at ECCV 202

Tracking Target Signal Strengths on a Grid using Sparsity

Multi-target tracking is mainly challenged by the nonlinearity present in the measurement equation, and the difficulty in fast and accurate data association. To overcome these challenges, the present paper introduces a grid-based model in which the state captures target signal strengths on a known spatial grid (TSSG). This model leads to \emph{linear} state and measurement equations, which bypass data association and can afford state estimation via sparsity-aware Kalman filtering (KF). Leveraging the grid-induced sparsity of the novel model, two types of sparsity-cognizant TSSG-KF trackers are developed: one effects sparsity through $\ell_1$-norm regularization, and the other invokes sparsity as an extra measurement. Iterative extended KF and Gauss-Newton algorithms are developed for reduced-complexity tracking, along with accurate error covariance updates for assessing performance of the resultant sparsity-aware state estimators. Based on TSSG state estimates, more informative target position and track estimates can be obtained in a follow-up step, ensuring that track association and position estimation errors do not propagate back into TSSG state estimates. The novel TSSG trackers do not require knowing the number of targets or their signal strengths, and exhibit considerably lower complexity than the benchmark hidden Markov model filter, especially for a large number of targets. Numerical simulations demonstrate that sparsity-cognizant trackers enjoy improved root mean-square error performance at reduced complexity when compared to their sparsity-agnostic counterparts.Comment: Submitted to IEEE Trans. on Signal Processin

Benefits and risks of the hormetic effects of dietary isothiocyanates on cancer prevention

The isothiocyanate (ITC) sulforaphane (SFN) was shown at low levels (1-5 µM) to promote cell proliferation to 120-143% of the controls in a number of human cell lines, whilst at high levels (10-40 µM) it inhibited such cell proliferation. Similar dose responses were observed for cell migration, i.e. SFN at 2.5 µM increased cell migration in bladder cancer T24 cells to 128% whilst high levels inhibited cell migration. This hormetic action was also found in an angiogenesis assay where SFN at 2.5 µM promoted endothelial tube formation (118% of the control), whereas at 10-20 µM it caused significant inhibition. The precise mechanism by which SFN influences promotion of cell growth and migration is not known, but probably involves activation of autophagy since an autophagy inhibitor, 3-methyladenine, abolished the effect of SFN on cell migration. Moreover, low doses of SFN offered a protective effect against free-radical mediated cell death, an effect that was enhanced by co-treatment with selenium. These results suggest that SFN may either prevent or promote tumour cell growth depending on the dose and the nature of the target cells. In normal cells, the promotion of cell growth may be of benefit, but in transformed or cancer cells it may be an undesirable risk factor. In summary, ITCs have a biphasic effect on cell growth and migration. The benefits and risks of ITCs are not only determined by the doses, but are affected by interactions with Se and the measured endpoint