Inducing Features of Random Fields

We present a technique for constructing random fields from a set of training samples. The learning paradigm builds increasingly complex fields by allowing potential functions, or features, that are supported by increasingly large subgraphs. Each feature has a weight that is trained by minimizing the Kullback-Leibler divergence between the model and the empirical distribution of the training data. A greedy algorithm determines how features are incrementally added to the field and an iterative scaling algorithm is used to estimate the optimal values of the weights. The statistical modeling techniques introduced in this paper differ from those common to much of the natural language processing literature since there is no probabilistic finite state or push-down automaton on which the model is built. Our approach also differs from the techniques common to the computer vision literature in that the underlying random fields are non-Markovian and have a large number of parameters that must be estimated. Relations to other learning approaches including decision trees and Boltzmann machines are given. As a demonstration of the method, we describe its application to the problem of automatic word classification in natural language processing. Key words: random field, Kullback-Leibler divergence, iterative scaling, divergence geometry, maximum entropy, EM algorithm, statistical learning, clustering, word morphology, natural language processingComment: 34 pages, compressed postscrip

The ATLAS RPC ROD for Super LHC

The number of interactions per bunch crossing for the upgrade of the Large Hadron Collider is expected to be ten times greater than the actual one. As a consequence, the ATLAS detector for SLHC foresees the use of a larger number of readout channels and also a new trigger level is under development. In order to face with such issue, we developed a new architecture for the Read Out Driver (ROD) for the ATLAS RPC Muon Spectrometer in the barrel region. Presently, each ROD board receives ATLAS RPC Muon readout data and arranges all the data fragments of a sector of the spectrometer in a unique event, sending it to the next acquisition systems. Our new design is based on the new generation Xilinx Virtex5 FPGA and it works with a clock frequency six times greater than the actual bunch crossing rate of the LHC. We also implemented the output channel of the ROD, presently based on S-Link protocol, by using the GTP transceivers inside the FPGA. We present an overview of our design, focusing on the newly added hardware features

Anticancer activity of cationic porphyrins in melanoma tumour-bearing mice and mechanistic in vitro studies

Background Porphyrin TMPyP4 (P4) and its C14H28-alkyl derivative (C14) are G-quadruplex binders and singlet oxygen (1O2) generators. In contrast, TMPyP2 (P2) produces 1O2 but it is not a G-quadruplex binder. As their photosensitizing activity is currently undefined, we report in this study their efficacy against a melanoma skin tumour and describe an in vitro mechanistic study which gives insights into their anticancer activity. Methods Uptake and antiproliferative activity of photoactivated P2, P4 and C14 have been investigated in murine melanoma B78-H1 cells by FACS, clonogenic and migration assays. Apoptosis was investigated by PARP-1 cleavage and annexin-propidium iodide assays. Biodistribution and in vivo anticancer activity were tested in melanoma tumour-bearing mice. Porphyrin binding and photocleavage of G-rich mRNA regions were investigated by electrophoresis and RT-PCR. Porphyrin effect on ERK pathway was explored by Western blots. Results Thanks to its higher lipophylicity C14 was taken up by murine melanoma B78-H1 cells up to 30-fold more efficiently than P4. When photoactivated (7.2 J/cm2) in B78-H1 melanoma cells, P4 and C14, but not control P2, caused a strong inhibition of metabolic activity, clonogenic growth and cell migration. Biodistribution studies on melanoma tumour-bearing mice showed that P4 and C14 localize in the tumour. Upon irradiation (660 nm, 193 J/cm2), P4 and C14 retarded tumour growth and increased the median survival time of the treated mice by ~50% (P <0.01 by ANOVA), whereas porphyrin P2 did not. The light-dependent mechanism mediated by P4 and C14 is likely due to the binding to and photocleavage of G-rich quadruplex-forming sequences within the 5\u2032-untranslated regions of the mitogenic ras genes. This causes a decrease of RAS protein and inhibition of downstream ERK pathway, which stimulates proliferation. Annexin V/propidium iodide and PARP-1 cleavage assays showed that the porphyrins arrested tumour growth by apoptosis and necrosis. C14 also showed an intrinsic light-independent anticancer activity, as recently reported for G4-RNA binders. Conclusions Porphyrins P4 and C14 impair the clonogenic growth and migration of B78-H1 melanoma cells and inhibit melanoma tumour growth in vivo. Evidence is provided that C14 acts through light-dependent (mRNA photocleavage) and light-independent (translation inhibition) mechanisms. Keywords: Melanoma B78-H1 cells; Cationic porphyrins; Biodistribution; C57/BL6 mice; Ras genes; G4-RNA; ERK pathwa

Study of Chinese Insurance Company’s Risk Estimation Index System

自从1990年以来，日本多家保险公司因资不抵债相继破产，不仅在国际社会造成了极大的震动，也给我国保险业敲响了警钟：保险公司在经营风险产品的同时，应加强对自身风险的评估。自从我国加入WTO后，保险业受到了巨大的冲击，加强对我国保险公司风险评估指标体系的研究便具有十分重要的意义。首先，对保险公司风险评估指标体系的研究，能为量化保险公司经营风险提供依据。其次，对保险公司风险评估指标体系的研究，有利于保险公司加强风险管理。 本文选择保险公司风险评估指标作为研究的重点，详细介绍了保险公司风险评估指标体系的内容、评价及在我国保险市场上的应用，并选取了四家保险公司近年来的数据，用IRIS指标体系做实证研究...Since 1990, some insurance companies of Japanese have been bankrupted. It made a big ring to the international financial market and Chinese insurance market: Insurance companies should pay more attention to its risk evaluation. After China’s entry into the WTO, some industries fell under big impact, especially the insurance industry. So the study of risk evaluation became more and more important t...学位：经济学硕士院系专业：经济学院财政金融系_金融学(含保险学)学号：20044202

Ageing test of the ATLAS RPCs at X5-GIF

An ageing test of three ATLAS production RPC stations is in course at X5-GIF, the CERN irradiation facility. The chamber efficiencies are monitored using cosmic rays triggered by a scintillator hodoscope. Higher statistics measurements are made when the X5 muon beam is available. We report here the measurements of the efficiency versus operating voltage at different source intensities, up to a maximum counting rate of about 700Hz/cm^2. We describe the performance of the chambers during the test up to an overall ageing of 4 ATLAS equivalent years corresponding to an integrated charge of 0.12C/cm^2, including a safety factor of 5.Comment: 4 pages. Presented at the VII Workshop on Resistive Plate Chambers and Related Detectors; Clermont-Ferrand October 20th-22nd, 200

System Test of the ATLAS Muon Spectrometer in the H8 Beam at the CERN SPS

An extensive system test of the ATLAS muon spectrometer has been performed in the H8 beam line at the CERN SPS during the last four years. This spectrometer will use pressurized Monitored Drift Tube (MDT) chambers and Cathode Strip Chambers (CSC) for precision tracking, Resistive Plate Chambers (RPCs) for triggering in the barrel and Thin Gap Chambers (TGCs) for triggering in the end-cap region. The test set-up emulates one projective tower of the barrel (six MDT chambers and six RPCs) and one end-cap octant (six MDT chambers, A CSC and three TGCs). The barrel and end-cap stands have also been equipped with optical alignment systems, aiming at a relative positioning of the precision chambers in each tower to 30-40 micrometers. In addition to the performance of the detectors and the alignment scheme, many other systems aspects of the ATLAS muon spectrometer have been tested and validated with this setup, such as the mechanical detector integration and installation, the detector control system, the data acquisition, high level trigger software and off-line event reconstruction. Measurements with muon energies ranging from 20 to 300 GeV have allowed measuring the trigger and tracking performance of this set-up, in a configuration very similar to the final spectrometer. A special bunched muon beam with 25 ns bunch spacing, emulating the LHC bunch structure, has been used to study the timing resolution and bunch identification performance of the trigger chambers. The ATLAS first-level trigger chain has been operated with muon trigger signals for the first time

A survey on independence-based Markov networks learning

This work reports the most relevant technical aspects in the problem of learning the \emph{Markov network structure} from data. Such problem has become increasingly important in machine learning, and many other application fields of machine learning. Markov networks, together with Bayesian networks, are probabilistic graphical models, a widely used formalism for handling probability distributions in intelligent systems. Learning graphical models from data have been extensively applied for the case of Bayesian networks, but for Markov networks learning it is not tractable in practice. However, this situation is changing with time, given the exponential growth of computers capacity, the plethora of available digital data, and the researching on new learning technologies. This work stresses on a technology called independence-based learning, which allows the learning of the independence structure of those networks from data in an efficient and sound manner, whenever the dataset is sufficiently large, and data is a representative sampling of the target distribution. In the analysis of such technology, this work surveys the current state-of-the-art algorithms for learning Markov networks structure, discussing its current limitations, and proposing a series of open problems where future works may produce some advances in the area in terms of quality and efficiency. The paper concludes by opening a discussion about how to develop a general formalism for improving the quality of the structures learned, when data is scarce.Comment: 35 pages, 1 figur

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

Standalone vertex finding in the ATLAS muon spectrometer

A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011