String Reconstruction from Substring Compositions

Motivated by mass-spectrometry protein sequencing, we consider a simply-stated problem of reconstructing a string from the multiset of its substring compositions. We show that all strings of length 7, one less than a prime, or one less than twice a prime, can be reconstructed uniquely up to reversal. For all other lengths we show that reconstruction is not always possible and provide sometimes-tight bounds on the largest number of strings with given substring compositions. The lower bounds are derived by combinatorial arguments and the upper bounds by algebraic considerations that precisely characterize the set of strings with the same substring compositions in terms of the factorization of bivariate polynomials. The problem can be viewed as a combinatorial simplification of the turnpike problem, and its solution may shed light on this long-standing problem as well. Using well known results on transience of multi-dimensional random walks, we also provide a reconstruction algorithm that reconstructs random strings over alphabets of size $\ge4$ in optimal near-quadratic time

Bid Shading in The Brave New World of First-Price Auctions

Online auctions play a central role in online advertising, and are one of the main reasons for the industry's scalability and growth. With great changes in how auctions are being organized, such as changing the second- to first-price auction type, advertisers and demand platforms are compelled to adapt to a new volatile environment. Bid shading is a known technique for preventing overpaying in auction systems that can help maintain the strategy equilibrium in first-price auctions, tackling one of its greatest drawbacks. In this study, we propose a machine learning approach of modeling optimal bid shading for non-censored online first-price ad auctions. We clearly motivate the approach and extensively evaluate it in both offline and online settings on a major demand side platform. The results demonstrate the superiority and robustness of the new approach as compared to the existing approaches across a range of performance metrics.Comment: In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM'20), October 19-23, 2020, Virtual Event, Irelan

Opposite angiogenic outcome of curcumin against ischemia and Lewis lung cancer models: in silico, in vitro and in vivo studies

AbstractThe aim of this study was to investigate the angiogenic effects of curcumin on an ischemia and lung cancer model. To induce ischemia combined with lung cancer models, unilateral femoral arteries of C57BL/6 mice were disconnected on one side of the mouse and Lewis lung carcinoma (LLC) cells were xenografted on the opposite side. Angiogenic effects and underlying mechanisms associated with curcumin were investigated. Molecular target(s), signaling cascades and binding affinities were detected by Western blot, two-dimensional gel electrophoresis (2-DE), computer simulations and surface plasmon resonance (SPR) techniques. Curcumin promoted post-ischemic blood recirculation and suppressed lung cancer progression in inbred C57BL/6 mice via regulation of the HIF1α/mTOR/VEGF/VEGFR cascade oppositely. Inflammatory stimulation induced by neutrophil elastase (NE) promoted angiogenesis in lung cancer tissues, but these changes were reversed by curcumin through directly reducing NE secretion and stimulating α1-antitrypsin (α1-AT) and insulin receptor substrate-1 (IRS-1) production. Meanwhile, curcumin dose-dependently influenced endothelial cells (EC) tube formation and chicken embryo chorioallantoic membrane (CAM) neovascularization. Curcumin had opposite effects on blood vessel regeneration under physiological and pathological angiogenesis, which was effected through negative or positive regulation of the HIF1α/mTOR/VEGF/VEGFR cascade. Curcumin had the promise as a new treatment modality for both ischemic conditions and lung cancer simultaneously in the clinic

A necessary and sufficient criterion for multipartite separable states

We present a necessary and sufficient condition for the separability of multipartite quantum states, this criterion also tells us how to write a multipartite separable state as a convex sum of separable pure states. To work out this criterion, we need to solve a set of equations, actually it is easy to solve these quations analytically if the density matrix of the given quantum state has few nonzero eigenvalues.Comment: 4 pages, Revte

Adaptive non-local means for multiview image denoising: Searching for the right patches via a statistical approach

ABSTRACT We present an adaptive non-local means (NLM) denoising method for a sequence of images captured by a multiview imaging system, where direct extensions of existing single image NLM methods are incapable of producing good results. Our proposed method consists of three major components: (1) a robust joint-view distance metric to measure the similarity of patches; (2) an adaptive procedure derived from statistical properties of the estimates to determine the optimal number of patches to be used; (3) a new NLM algorithm to denoise using only a set of similar patches. Experimental results show that the proposed method is robust to disparity estimation error, out-performs existing algorithms in multiview settings, and performs competitively in video settings. Index Terms-Non-local means, adaptive filtering, multiview denoising, patch-based denoisin

Multipartite pure-state entanglement and the generalized GHZ states

We show that not all 4-party pure states are GHZ reducible (i.e., can be generated reversibly from a combination of 2-, 3- and 4-party maximally entangled states by local quantum operations and classical communication asymptotically) through an example, we also present some properties of the relative entropy of entanglement for those 3-party pure states that are GHZ reducible, and then we relate these properties to the additivity of the relative entropy of entanglement.Comment: 7 pages, Revtex, type error correcte