Group Actions and Elementary Number Theory

Abstract | In this article the shuffling of cards is studied by using the concept of a group action. We use some fundamental results in Elementary Number Theory to obtain formulas for the orders of some special shufflings, namely the Faro and Monge shufflings and give necessary and sufficient conditions for the Monge shuffling to be a cycle. In the final section we extend the considerations to the shuffling of multisets.

Protumorigenic actions of S100A2 involve regulation of PI3/Akt signaling and functional interaction with Smad3

S100 family of calcium-binding proteins is commonly upregulated in a variety of tumor types and is often associated with tumor progression. Among several S100 members, altered expression of S100A2 is a potential diagnostic and prognostic marker in cancer. Several reports suggest a role for S100A2 in metastasis. Earlier, our studies established regulation of S100A2 by transforming growth factor- (TGF-) and its involvement in TGF--mediated cancer cell invasion and migration. However, the molecular mechanisms of S100A2 protumorigenic actions remain unexplored. In the present study, we demonstrate that overexpression of S100A2 in A549 lung cancer cells induced epithelialmesenchymal transition (EMT) followed by increased invasion, loose colony morphology in soft agar and enhanced Akt phosphorylation (Ser-473). Furthermore, overexpression of S100A2 led to increased tumor growth in immunocompromised mice. In agreement, immunohistochemical examination of resected xenograft tumors established inverse correlation between S100A2 and E-cadherin expression together with activated Akt signaling. Interestingly, our study demonstrates a strong dependence of S100A2 and Smad3 in TGF--induced Hep3B cell EMT and invasion. Most importantly, we demonstrate that these effects of S100A2 are manifested through functional interaction with Smad3, which is enhanced in the presence of high calcium and TGF-. S100A2 stabilizes Smad3 and binds to its C-terminal MH2 domain. Additionally, loss of S100A2 attenuates the transcription of TGF-/Smad3 target genes involved in tumor promotion, such as PA1-1 and vimentin. Collectively, our findings present the first mechanistic details of S100A2 protumorigenic actions and its involvement in TGF--mediated cancer cell invasion and EMT.

A Cause and Effect Analysis of Motion Trajectories for Modeling Actions

An action is typically composed of different parts of the object moving in particular sequences. The presence of different motions (represented as a 1D histogram) has been used in the traditional bag-of-words (BoW) approach for recognizing actions. However the interactions among the motions also form a crucial part of an action. Different object-parts have varying degrees of interactions with the other parts during an action cycle. It is these interactions we want to quantify in order to bring in additional information about the actions. In this paper we propose a causality based approach for quantifying the interactions to aid action classification. Granger causality is used to compute the cause and effect relationships for pairs of motion trajectories of a video. A 2D histogram descriptor for the video is constructed using these pairwise measures. Our proposed method of obtaining pairwise measures for videos is also applicable for large datasets. We have conducted experiments on challenging action recognition databases such as HMDB51 and UCF50 and shown that our causality descriptor helps in encoding additional information regarding the actions and performs on par with the state-of-the art approaches. Due to the complementary nature, a further increase in performance can be observed by combining our approach with state-of-the-art approaches.

On-line Dynamic Security Assessment: Determination of Critical Transmission Lines

The main objective of on-line dynamic security assessment is to take preventive action if required or decide remedial action if a contingency actually occurs. Stability limits are obtained for different contingencies. The mode of instability is one of the outputs of dynamic security analysis. When a power system becomes unstable, it splits initially into two groups of generators, and there is a unique cutset in the transmission network known as critical cutset across which the angles become unbounded. The knowledge of critical cutset is additional information obtained from dynamic security assessment, which can be used for initiating preventive control actions, deciding emergency control actions, and adaptive out-of-step relaying. In this article, an analytical technique for the fast prediction of the critical cutset by system simulation for a short duration is presented. Case studies on the New England ten-generator system are presented. The article also suggests the applications of the identification of critical cutsets.