Highly Interconnected Subsystems of the Stock Market

The stock market is a complex system that affects economic and financial activities around the world. Analysis of stock price data can improve our understanding of the past price movements of stocks. In this work, we develop a method to determine the highly interconnected subsystems of the stock market. Our method relies on a k-core decomposition scheme to analyze large networks. Our approach illustrates that the stock market is a nearly decomposable system which comprises hierarchic subsystems. This work also presents results from the analysis of a network derived from a large data set of stock prices. This network analysis technique is a new promising approach to analyze and classify stocks based on price interactions and to decompose the complex system embodied in the stock market

Hand-written Malayalam character recognition an approach based on pen movement

In this paper we introduce a novel approach for character recognition based on the pen movement i.e., recognition based on sequence of pen strokes.A Backpropagation Neural Network is used for identifying individual strokes.The recognizer has a two-pass architecture i.e., the inputs are propagated twice through the network.The first pass does the initial classification and the second for exact recognition. The two-pass structure of the recognizer helped in achieving accuracy of about 95 percent in recognizing Malayalam letters.The training set contains samples of all independent strokes that are commonly used while writing Malayalam.Input values to the network are the directions of pen movement.A “minimum error” technique is used for finding the firing neuron in the output layer. Based on the output of FirstPass the network is dynamically loaded with a fresh set of weights for exact stroke recognition.Analyzing the stroke sequences identifies individual characters.This work also demonstrates how a statistical pre-analysis of training set reduces training time

A Flight Dynamics Perspective of the Orion Pad Abort One Flight Test

The Orion Crew Exploration Vehicle is America s next generation of human rated spacecraft. The Orion Launch Abort System will take the astronauts away from the exploration vehicle in the event of an aborted launch. The pad abort mode of the Launch Abort System will be flight-tested in 2009 from the White Sands Missile Range in New Mexico. This paper examines some of the efforts currently underway at the NASA Dryden Flight Research Center by the Controls & Dynamics group in preparation for the flight test. The concept of operation for the pad abort flight is presented along with an overview of the guidance, control and navigation systems. Preparations for the flight test, such as hardware testing and development of the real-time displays, are examined. The results from the validation and verification efforts for the aerodynamic and atmospheric models are shown along with Monte Carlo analysis results

Surfactant protein D inhibits HIV-1 infection of target cells via interference with gp120-CD4 interaction and modulates pro-inflammatory cytokine production

© 2014 Pandit et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Surfactant Protein SP-D, a member of the collectin family, is a pattern recognition protein, secreted by mucosal epithelial cells and has an important role in innate immunity against various pathogens. In this study, we confirm that native human SP-D and a recombinant fragment of human SP-D (rhSP-D) bind to gp120 of HIV-1 and significantly inhibit viral replication in vitro in a calcium and dose-dependent manner. We show, for the first time, that SP-D and rhSP-D act as potent inhibitors of HIV-1 entry in to target cells and block the interaction between CD4 and gp120 in a dose-dependent manner. The rhSP-D-mediated inhibition of viral replication was examined using three clinical isolates of HIV-1 and three target cells: Jurkat T cells, U937 monocytic cells and PBMCs. HIV-1 induced cytokine storm in the three target cells was significantly suppressed by rhSP-D. Phosphorylation of key kinases p38, Erk1/2 and AKT, which contribute to HIV-1 induced immune activation, was significantly reduced in vitro in the presence of rhSP-D. Notably, anti-HIV-1 activity of rhSP-D was retained in the presence of biological fluids such as cervico-vaginal lavage and seminal plasma. Our study illustrates the multi-faceted role of human SPD against HIV-1 and potential of rhSP-D for immunotherapy to inhibit viral entry and immune activation in acute HIV infection. © 2014 Pandit et al.The work (Project no. 2011-16850) was supported by Medical Innovation Fund of Indian Council of Medical Research, New Delhi, India (www.icmr.nic.in/)

Managing a complex project using a Risk-Risk Multiple Domain Matrix

International audienceThis communication aims at presenting a clustering methodology applied to a complex project consisting of the delivery of three interdependent sub-systems. This enables small and complementary task forces to be constituted, enhancing the communication and coordination on transverse issues related to the complexity of the whole system. The problem is to gather and exploit data for such systems, with numerous and heterogeneous risks of different domains (product, process, organization). The method consists in regrouping actors through the clustering of the risks they own. The result is a highlight on important and transverse risk interdependencies, within and between projects. These should not be neglected in order to avoid potential severe issues, whether during the project or during the exploitation of its deliverable. An application on a real program of plant implementation in the CEA-DAM is presented, with a sensitivity analysis of the clustering results to the inputs and chosen configurations of the problem

Synthesis Of Poly(L-Lactic Acid) Scaffolds From Dioxane/Ethanol Using Control Rate Freezing And Study Of Its Microstructural Properties

Bio-degradable poly (l-lactic acid) (PLLA) scaffolds were prepared by using thermally induced phase separation (TIPS) method. A solution of PLLA-Dioxane was formed by dissolving PLLA in dehydrated 1,4-Dioxane at three wt/vol percentages, specifically 3, 7 and 10%. This PLLA-Dioxane solution was then frozen in borosilicate glass vials (5mL) at three cooling rates (1, 10 and 40 ˚C/min) in a commercially available controlled rate freezer (CRF). The frozen solution was freeze-dried to sublimate the Dioxane. The microstructural properties of the resulting PLLA scaffolds were determined utilizing Scanning Electron Microscopy (SEM) images and uni- axial compressive testing. The relationship between the wt/vol ratio of PLLA and Dioxane and the imposed cooling rates on the structural properties of PLLA scaffolds was determined. This same procedure was then repeated using a mixture of Dioxane and Ethanol. The volume of the mixture constituted 15% of Ethanol and 85% Dioxane

An Online Character Recognition System to Convert Grantha Script to Malayalam

This paper presents a novel approach to recognize Grantha, an ancient script in South India and converting it to Malayalam, a prevalent language in South India using online character recognition mechanism. The motivation behind this work owes its credit to (i) developing a mechanism to recognize Grantha script in this modern world and (ii) affirming the strong connection among Grantha and Malayalam. A framework for the recognition of Grantha script using online character recognition is designed and implemented. The features extracted from the Grantha script comprises mainly of time-domain features based on writing direction and curvature. The recognized characters are mapped to corresponding Malayalam characters. The framework was tested on a bed of medium length manuscripts containing 9-12 sample lines and printed pages of a book titled Soundarya Lahari writtenin Grantha by Sri Adi Shankara to recognize the words and sentences. The manuscript recognition rates with the system are for Grantha as 92.11%, Old Malayalam 90.82% and for new Malayalam script 89.56%. The recognition rates of pages of the printed book are for Grantha as 96.16%, Old Malayalam script 95.22% and new Malayalam script as 92.32% respectively. These results show the efficiency of the developed system.Comment: 6 pages, 6 figure

Prediction of peptide and protein propensity for amyloid formation

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔGº values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation

Polypropylene woven fabric: A good mulch material for young rubber plants

In young rubber   plantations, dry leaf, coco tree mat, polypropylene woven fabric and coir   pith were evaluated as agricultural mulch materials for their influence on   soil moisture conservation, weed control, soil temperature and microflora,   plant growth and durability in two field experiments. The experiments were   conducted in a drought susceptible clone (RRII 105) and a comparatively   drought tolerant clone (RRII 430) at Chimoni Estate, Thrissur district, a   drought-prone area in Kerala. The effects of different treatments were   similar in both the experiments irrespective of clones. Though dry leaf and   coir pith were effective in soil moisture conservation, they remained in the   field for one season only and failed to control weeds during rainy season.   Coco tree mat conserved moisture and also smothered weeds in plant basins. However,   it remained in the field for almost one year only before it was completely   decomposed. Polypropylene woven fabric improved soil moisture retention, as   well as suppressed weed growth and was found durable. Though mulching reduced   the adverse effects of summer, significant impact on soil microflora and   plant growth was not manifested. Polypropylene woven fabric appears to be a   good alternative mulch material for Hevea