Inter-battery topic representation learning

In this paper, we present the Inter-Battery Topic Model (IBTM). Our approach extends traditional topic models by learning a factorized latent variable representation. The structured representation leads to a model that marries benefits traditionally associated with a discriminative approach, such as feature selection, with those of a generative model, such as principled regularization and ability to handle missing data. The factorization is provided by representing data in terms of aligned pairs of observations as different views. This provides means for selecting a representation that separately models topics that exist in both views from the topics that are unique to a single view. This structured consolidation allows for efficient and robust inference and provides a compact and efficient representation. Learning is performed in a Bayesian fashion by maximizing a rigorous bound on the log-likelihood. Firstly, we illustrate the benefits of the model on a synthetic dataset,. The model is then evaluated in both uni- and multi-modality settings on two different classification tasks with off-the-shelf convolutional neural network (CNN) features which generate state-of-the-art results with extremely compact representations

Bayesian alignments of warped multi-output Gaussian processes

We propose a novel Bayesian approach to modelling nonlinear alignments of time series based on latent shared information. We apply the method to the real-world problem of finding common structure in the sensor data of wind turbines introduced by the underlying latent and turbulent wind field. The proposed model allows for both arbitrary alignments of the inputs and non-parametric output warpings to transform the observations. This gives rise to multiple deep Gaussian process models connected via latent generating processes. We present an efficient varia-tional approximation based on nested variational compression and show how the model can be used to extract shared information between dependent time series, recovering an interpretable functional decomposition of the learning problem. We show results for an artificial data set and real-world data of two wind turbines

Learning object, grasping and manipulation activities using hierarchical HMMs

This article presents a probabilistic algorithm for representing and learning complex manipulation activities performed by humans in everyday life. The work builds on the multi-level Hierarchical Hidden Markov Model (HHMM) framework which allows decomposition of longer-term complex manipulation activities into layers of abstraction whereby the building blocks can be represented by simpler action modules called action primitives. This way, human task knowledge can be synthesised in a compact, effective representation suitable, for instance, to be subsequently transferred to a robot for imitation. The main contribution is the use of a robust framework capable of dealing with the uncertainty or incomplete data inherent to these activities, and the ability to represent behaviours at multiple levels of abstraction for enhanced task generalisation. Activity data from 3D video sequencing of human manipulation of different objects handled in everyday life is used for evaluation. A comparison with a mixed generative-discriminative hybrid model HHMM/SVM (support vector machine) is also presented to add rigour in highlighting the benefit of the proposed approach against comparable state of the art techniques. © 2014 Springer Science+Business Media New York

Mass hierarchy, 2-3 mixing and CP-phase with Huge Atmospheric Neutrino Detectors

We explore the physics potential of multi-megaton scale ice or water Cherenkov detectors with low ($\sim 1$ GeV) threshold. Using some proposed characteristics of the PINGU detector setup we compute the distributions of events versus neutrino energy $E_\nu$ and zenith angle $\theta_z$, and study their dependence on yet unknown neutrino parameters. The $(E_\nu - \theta_z)$ regions are identified where the distributions have the highest sensitivity to the neutrino mass hierarchy, to the deviation of the 2-3 mixing from the maximal one and to the CP-phase. We evaluate significance of the measurements of the neutrino parameters and explore dependence of this significance on the accuracy of reconstruction of the neutrino energy and direction. The effect of degeneracy of the parameters on the sensitivities is also discussed. We estimate the characteristics of future detectors (energy and angle resolution, volume, etc.) required for establishing the neutrino mass hierarchy with high confidence level. We find that the hierarchy can be identified at $3\sigma$ -- $10\sigma$ level (depending on the reconstruction accuracies) after 5 years of PINGU operation.Comment: 39 pages, 21 figures. Description of Fig.3 correcte

The Carbon-Rich Gas in the Beta Pictoris Circumstellar Disk

The edge-on disk surrounding the nearby young star Beta Pictoris is the archetype of the "debris disks", which are composed of dust and gas produced by collisions and evaporation of planetesimals, analogues of Solar System comets and asteroids. These disks provide a window on the formation and early evolution of terrestrial planets. Previous observations of Beta Pic concluded that the disk gas has roughly solar abundances of elements [1], but this poses a problem because such gas should be rapidly blown away from the star, contrary to observations of a stable gas disk in Keplerian rotation [1, 2]. Here we report the detection of singly and doubly ionized carbon (CII, CIII) and neutral atomic oxygen (OI) gas in the Beta Pic disk; measurement of these abundant volatile species permits a much more complete gas inventory. Carbon is extremely overabundant relative to every other measured element. This appears to solve the problem of the stable gas disk, since the carbon overabundance should keep the gas disk in Keplerian rotation [3]. New questions arise, however, since the overabundance may indicate the gas is produced from material more carbon-rich than the expected Solar System analogues.Comment: Accepted for publication in Nature. PDF document, 12 pages. Supplementary information may be found at http://www.dtm.ciw.edu/akir/Documents/roberge_supp.pdf *** Version 2 : Removed extraneous publication information, per instructions from the Nature editor. No other changes mad

Binary choice models for external auditors decisions in Asian banks

Summarization: The present study investigates the efficiency of four classification techniques, namely discriminant analysis, logit analysis, UTADIS multicriteria decision aid, and nearest neighbours, in the development of classification models that could assist auditors during the examination of Asian commercial banks. To develop the auditing models and examine their classification ability, the dataset is split into two distinct samples. The training sample consists of 1,701 unqualified financial statements and 146 ones that received a qualified opinion over the period 1996–2001. The models are tested in a holdout sample of 527 unqualified financial statements and 52 ones that received a qualified opinion over the period 2002–2004. The results show that the developed auditing models can discriminate between financial statements that should receive qualified opinions from the ones that should receive unqualified opinions with an out-of-sample accuracy around 60%. The highest classification accuracy is achieved by UTADIS, followed by logit analysis, nearest neighbours and discriminant analysis. Both financial variables and the environment in which banks operate appear to be important factors.Presented on: Operational Research, An International Journa

High Interstitial Fluid Pressure Is Associated with Tumor-Line Specific Vascular Abnormalities in Human Melanoma Xenografts

PURPOSE: Interstitial fluid pressure (IFP) is highly elevated in many solid tumors. High IFP has been associated with low radiocurability and high metastatic frequency in human melanoma xenografts and with poor survival after radiation therapy in cervical cancer patients. Abnormalities in tumor vascular networks have been identified as an important cause of elevated tumor IFP. The aim of this study was to investigate the relationship between tumor IFP and the functional and morphological properties of tumor vascular networks. MATERIALS AND METHODS: A-07-GFP and R-18-GFP human melanomas growing in dorsal window chambers in BALB/c nu/nu mice were used as preclinical tumor models. Functional and morphological parameters of the vascular network were assessed from first-pass imaging movies and vascular maps recorded after intravenous bolus injection of 155-kDa tetramethylrhodamine isothiocyanate-labeled dextran. IFP was measured in the center of the tumors using a Millar catheter. Angiogenic profiles of A-07-GFP and R-18-GFP cells were obtained with a quantitative PCR array. RESULTS: High IFP was associated with low growth rate and low vascular density in A-07-GFP tumors, and with high growth rate and high vascular density in R-18-GFP tumors. A-07-GFP tumors showed chaotic and highly disorganized vascular networks, while R-18-GFP tumors showed more organized vascular networks with supplying arterioles in the tumor center and draining venules in the tumor periphery. Furthermore, A-07-GFP and R-18-GFP cells differed substantially in angiogenic profiles. A-07-GFP tumors with high IFP showed high geometric resistance to blood flow due to high vessel tortuosity. R-18-GFP tumors with high IFP showed high geometric resistance to blood flow due to a large number of narrow tumor capillaries. CONCLUSIONS: High IFP in A-07-GFP and R-18-GFP human melanoma xenografts was primarily a consequence of high blood flow resistance caused by tumor-line specific vascular abnormalities

Cover to Volume 3

The fibroblast mitogen platelet-derived growth factor -BB (PDGF-BB) induces a transient expression of the orphan nuclear receptor NR4A1 (also named Nur77, TR3 or NGFIB). The aim of the present study was to investigate the pathways through which NR4A1 is induced by PDGF-BB and its functional role. We demonstrate that in PDGF-BB stimulated NIH3T3 cells, the MEK1/2 inhibitor CI-1040 strongly represses NR4A1 expression, whereas Erk5 downregulation delays the expression, but does not block it. Moreover, we report that treatment with the NF-κB inhibitor BAY11-7082 suppresses NR4A1 mRNA and protein expression. The majority of NR4A1 in NIH3T3 was found to be localized in the cytoplasm and only a fraction was translocated to the nucleus after continued PDGF-BB treatment. Silencing NR4A1 slightly increased the proliferation rate of NIH3T3 cells; however, it did not affect the chemotactic or survival abilities conferred by PDGF-BB. Moreover, overexpression of NR4A1 promoted anchorage-independent growth of NIH3T3 cells and the glioblastoma cell lines U-105MG and U-251MG. Thus, whereas NR4A1, induced by PDGF-BB, suppresses cell growth on a solid surface, it increases anchorage-independent growth

Gaining and sustaining schistosomiasis control: study protocol and baseline data prior to different treatment strategies in five African countries

The Schistosomiasis Consortium for Operational Research and Evaluation (SCORE) was established in 2008 to answer strategic questions about schistosomiasis control. For programme managers, a high-priority question is: what are the most cost-effective strategies for delivering preventive chemotherapy (PCT) with praziquantel (PZQ)? This paper describes the process SCORE used to transform this question into a harmonized research protocol, the study design for answering this question, the village eligibility assessments and data resulting from the first year of the study.; Beginning in 2009, SCORE held a series of meetings to specify empirical questions and design studies related to different schedules of PCT for schistosomiasis control in communities with high (gaining control studies) and moderate (sustaining control studies) prevalence of Schistosoma infection among school-aged children. Seven studies are currently being implemented in five African countries. During the first year, villages were screened for eligibility, and data were collected on prevalence and intensity of infection prior to randomisation and the implementation of different schemes of PZQ intervention strategies.; These studies of different treatment schedules with PZQ will provide the most comprehensive data thus far on the optimal frequency and continuity of PCT for schistosomiasis infection and morbidity control.; We expect that the study outcomes will provide data for decision-making for country programme managers and a rich resource of information to the schistosomiasis research community.; The trials are registered at International Standard Randomised Controlled Trial registry (identifiers: ISRCTN99401114 , ISRCTN14849830 , ISRCTN16755535 , ISRCTN14117624 , ISRCTN95819193 and ISRCTN32045736 )