Drone Shadow Tracking

Aerial videos taken by a drone not too far above the surface may contain the drone's shadow projected on the scene. This deteriorates the aesthetic quality of videos. With the presence of other shadows, shadow removal cannot be directly applied, and the shadow of the drone must be tracked. Tracking a drone's shadow in a video is, however, challenging. The varying size, shape, change of orientation and drone altitude pose difficulties. The shadow can also easily disappear over dark areas. However, a shadow has specific properties that can be leveraged, besides its geometric shape. In this paper, we incorporate knowledge of the shadow's physical properties, in the form of shadow detection masks, into a correlation-based tracking algorithm. We capture a test set of aerial videos taken with different settings and compare our results to those of a state-of-the-art tracking algorithm.Comment: 5 pages, 4 figure

Three-Fold Diffraction Symmetry in Epitaxial Graphene and the SiC Substrate

The crystallographic symmetries and spatial distribution of stacking domains in graphene films on SiC have been studied by low energy electron diffraction (LEED) and dark field imaging in a low energy electron microscope (LEEM). We find that the graphene diffraction spots from 2 and 3 atomic layers of graphene have 3-fold symmetry consistent with AB (Bernal) stacking of the layers. On the contrary, graphene diffraction spots from the buffer layer and monolayer graphene have apparent 6-fold symmetry, although the 3-fold nature of the satellite spots indicates a more complex periodicity in the graphene sheets.Comment: An addendum has been added for the arXiv version only, including one figure with five panels. Published paper can be found at http://link.aps.org/doi/10.1103/PhysRevB.80.24140

Spectroscopic and quartz crystal microbalance (QCM) characterisation of protein-based MIPs

We have studied acrylamide-based polymers of varying hydrophobicity (acrylamide, AA; N-hydroxymethylacrylamide, NHMA; N-isopropylacrylamide, NiPAm) for their capability of imprinting protein. Rebinding capacities (Q) from spectroscopic studies were highest for bovine haemoglobin (BHb) MIPs based on AA, Q = 4.8 ± 0.21 76 ± 0.5%). When applied to the QCM sensor as thin-film MIPs, NHMA MIPs were found to exhibit best discrimination between MIP and non-imprinted control polymer (NIP) in the order of NiPAm < AA < NHMA. The extent of template removal and rebinding, using both crystal impedance and frequency measurements, demonstrated that 10% (w/v):10% (v/v) sodium dodecyl sulphate:acetic acid (pH 2.8) was efficient at eluting template BHb (with 80 ± 10% removal). Selectivity studies of NHMA BHb-MIPs revealed higher adsorption and selective recognition properties to BHb (64.5 kDa) when compared to non-cognate BSA (66 kDa), myoglobin (Mb, 17.5 kDa), lysozyme (Lyz, 14.7 kDa) thaumatin (Thau, 22 kDa) and trypsin (Tryp, 22.3 kDa). The QCM gave frequency shifts of ∼1500 ± 50 Hz for template BHb rebinding in both AA and NHMA MIPs, whereas AA-based MIPs exhibited an interference signal of ∼2200 ± 50 Hz for non-cognate BSA in comparison to a ∼500 ± 50 Hz shift with NHMA MIPs. Our results show that NHMA-based hydrogel MIP are superior to AA and NIPAM

MM Algorithms for Geometric and Signomial Programming

This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the geometric-arithmetic mean inequality and a supporting hyperplane inequality to create a surrogate function with parameters separated. Thus, unconstrained signomial programming reduces to a sequence of one-dimensional minimization problems. Simple examples demonstrate that the MM algorithm derived can converge to a boundary point or to one point of a continuum of minimum points. Conditions under which the minimum point is unique or occurs in the interior of parameter space are proved for geometric programming. Convergence to an interior point occurs at a linear rate. Finally, the MM framework easily accommodates equality and inequality constraints of signomial type. For the most important special case, constrained quadratic programming, the MM algorithm involves very simple updates.Comment: 16 pages, 1 figur

Knowledge based cloud FE simulation of sheet metal forming processes

The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques. This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions

Learning to Estimate 3D Human Pose from Point Cloud

3D pose estimation is a challenging problem in computer vision. Most of the existing neural-network-based approaches address color or depth images through convolution networks (CNNs). In this paper, we study the task of 3D human pose estimation from depth images. Different from the existing CNN-based human pose estimation method, we propose a deep human pose network for 3D pose estimation by taking the point cloud data as input data to model the surface of complex human structures. We first cast the 3D human pose estimation from 2D depth images to 3D point clouds and directly predict the 3D joint position. Our experiments on two public datasets show that our approach achieves higher accuracy than previous state-of-art methods. The reported results on both ITOP and EVAL datasets demonstrate the effectiveness of our method on the targeted tasks

TDP2 promotes repair of topoisomerase I-mediated DNA damage in the absence of TDP1

The abortive activity of topoisomerases can result in clastogenic and/or lethal DNA damage in which the topoisomerase is covalently linked to the 3'- or 5'-terminus of a DNA strand break. This type of DNA damage is implicated in chromosome translocations and neurological disease and underlies the clinical efficacy of an important class of anticancer topoisomerase 'poisons'. Tyrosyl DNA phosphodiesterase-1 protects cells from abortive topoisomerase I (Top1) activity by hydrolyzing the 3'-phosphotyrosyl bond that links Top1 to a DNA strand break and is currently the only known human enzyme that displays this activity in cells. Recently, we identified a second tyrosyl DNA phosphodiesterase (TDP2; aka TTRAP/EAPII) that possesses weak 3'-tyrosyl DNA phosphodiesterase (3'-TDP) activity, in vitro. Herein, we have examined whether TDP2 contributes to the repair of Top1-mediated DNA breaks by deleting Tdp1 and Tdp2 separately and together in murine and avian cells. We show that while deletion of Tdp1 in wild-type DT40 cells and mouse embryonic fibroblasts decreases DNA strand break repair rates and cellular survival in response to Top1-induced DNA damage, deletion of Tdp2 does not. However, deletion of both Tdp1 and Tdp2 reduces rates of DNA strand break repair and cell survival below that observed in Tdp1(-)(/)(-) cells, suggesting that Tdp2 contributes to cellular 3'-TDP activity in the absence of Tdp1. Consistent with this idea, over-expression of human TDP2 in Tdp1(-)(/)(-)/Tdp2(-)(/)(-)(/)(-) DT40 cells increases DNA strand break repair rates and cell survival above that observed in Tdp1(-)(/)(-) DT40 cells, suggesting that Tdp2 over-expression can partially complement the defect imposed by loss of Tdp1. Finally, mice lacking both Tdp1 and Tdp2 exhibit greater sensitivity to Top1 poisons than do mice lacking Tdp1 alone, further suggesting that Tdp2 contributes to the repair of Top1-mediated DNA damage in the absence of Tdp1. In contrast, we failed to detect a contribution for Tdp1 to repair Top2-mediated damage. Together, our data suggest that Tdp1 and Tdp2 fulfil overlapping roles following Top1-induced DNA damage, but not following Top2-induced DNA damage, in vivo

Editorial:Metformin: Beyond Diabetes

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