Spatial Analysis of Cell Composition Data

A version of Matheron’s discrete Gaussian model is applied to cell composition data.The examples are for map patterns of felsic metavolcanics in two different areas. Q-Qplots of the model for cell values representing proportion of 10 km x 10 km cell areaunderlain by this rock type are approximately linear, and the line of best fit can be usedto estimate the parameters of the model. It is also shown that felsic metavolcanics in theAbitibi area of the Canadian Shield can be modeled as a fractal

Modelling structural zeros in compositional data

This analysis was stimulated by the real data analysis problem of householdexpenditure data. The full dataset contains expenditure data for a sample of 1224 households. The expenditure is broken down at 2 hierarchical levels: 9 major levels (e.g. housing, food, utilities etc.) and 92 minor levels. There are also 5 factors and 5 covariates at the household level. Not surprisingly, there are a small number of zeros at the major level, but many zeros at the minor level. The question is how best to model the zeros. Clearly, models that tryto add a small amount to the zero terms are not appropriate in general as at least some of the zeros are clearly structural, e.g. alcohol/tobacco for households that are teetotal. The key question then is how to build suitable conditional models. For example, is the sub-composition of spendingexcluding alcohol/tobacco similar for teetotal and non-teetotal households?In other words, we are looking for sub-compositional independence. Also, what determines whether a household is teetotal? Can we assume that it is independent of the composition? In general, whether teetotal will clearly depend on the household level variables, so we need to be able to model this dependence. The other tricky question is that with zeros on more than onecomponent, we need to be able to model dependence and independence of zeros on the different components. Lastly, while some zeros are structural, others may not be, for example, for expenditure on durables, it may be chance as to whether a particular household spends money on durableswithin the sample period. This would clearly be distinguishable if we had longitudinal data, but may still be distinguishable by looking at the distribution, on the assumption that random zeros will usually be for situations where any non-zero expenditure is not small.While this analysis is based on around economic data, the ideas carry over tomany other situations, including geological data, where minerals may be missing for structural reasons (similar to alcohol), or missing because they occur only in random regions which may be missed in a sample (similar to the durables)

Recovering Euclidean deformable models from stereo-motion

In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence

Visualització de models fusionats

L’objectiu principal d’aquest projecte era implementar la visualització 3D demodels fusionats i aplicar totes les tècniques possibles per realitzar aquesta fusió. Aquestes tècniques s’integraran en la plataforma de visualització i processament de dades mèdiques STARVIEWER. Per assolir l’ objectiu principal s’ han definit els següents objectius específics:1- estudiar els algoritmes de visualització de models simples i analitzar els diferents paràmetres a tenir en compte. 2- ampliació de la tècnica de visualització bàsica seleccionada per tal de suportar els models fusionats. 3- avaluar i compar tots els mètodes implementats per poder determinar quin ofereix les millors visualitzacions

Self-reported alcohol consumption and its association with adherence and outcome of antiretroviral therapy in the Swiss HIV Cohort Study.

BACKGROUND: Alcohol consumption leading to morbidity and mortality affects HIV-infected individuals. Here, we aimed to study self-reported alcohol consumption and to determine its association with adherence to antiretroviral therapy (ART) and HIV surrogate markers. METHODS: Cross-sectional data on daily alcohol consumption from August 2005 to August 2007 were analysed and categorized according to the World Health Organization definition (light, moderate or severe health risk). Multivariate logistic regression models and Pearson's chi(2) statistics were used to test the influence of alcohol use on endpoints. RESULTS: Of 6,323 individuals, 52.3% consumed alcohol less than once a week in the past 6 months. Alcohol intake was deemed light in 39.9%, moderate in 5.0% and severe in 2.8%. Higher alcohol consumption was significantly associated with older age, less education, injection drug use, being in a drug maintenance programme, psychiatric treatment, hepatitis C virus coinfection and with a longer time since diagnosis of HIV. Lower alcohol consumption was found in males, non-Caucasians, individuals currently on ART and those with more ART experience. In patients on ART (n=4,519), missed doses and alcohol consumption were positively correlated (P<0.001). Severe alcohol consumers, who were pretreated with ART, were more often off treatment despite having CD4+ T-cell count <200 cells/microl; however, severe alcohol consumption per se did not delay starting ART. In treated individuals, alcohol consumption was not associated with worse HIV surrogate markers. CONCLUSIONS: Higher alcohol consumption in HIV-infected individuals was associated with several psychosocial and demographic factors, non-adherence to ART and, in pretreated individuals, being off treatment despite low CD4+ T-cell counts.

The prognostic value of health-related quality-of-life data in predicting survival in glioblastoma cancer patients: results from an international randomised phase III EORTC Brain Tumour and Radiation Oncology Groups, and NCIC Clinical Trials Group study.

This is one of the few studies that have explored the value of baseline symptoms and health-related quality of life (HRQOL) in predicting survival in brain cancer patients. Baseline HRQOL scores (from the EORTC QLQ-C30 and the Brain Cancer Module (BN 20)) were examined in 490 newly diagnosed glioblastoma cancer patients for the relationship with overall survival by using Cox proportional hazards regression models. Refined techniques as the bootstrap re-sampling procedure and the computation of C-indexes and R(2)-coefficients were used to try and validate the model. Classical analysis controlled for major clinical prognostic factors selected cognitive functioning (P=0.0001), global health status (P=0.0055) and social functioning (P<0.0001) as statistically significant prognostic factors of survival. However, several issues question the validity of these findings. C-indexes and R(2)-coefficients, which are measures of the predictive ability of the models, did not exhibit major improvements when adding selected or all HRQOL scores to clinical factors. While classical techniques lead to positive results, more refined analyses suggest that baseline HRQOL scores add relatively little to clinical factors to predict survival. These results may have implications for future use of HRQOL as a prognostic factor in cancer patients.

Gender differences in cardiovascular risk factors in HIV infected patients on antiretroviral therapy: Data from the Spanish Coronator study.

Purpose: HIV-infected patients present an increased cardiovascular risk (CVR) of multifactorial origin, usually lower in women than in men. Information by gender about prevalence of modifiable risk factors is scarce. Methods: Coronator is a cross-sectional survey of a representative sample of HIV-infected patients on ART within 10 hospitals across Spain in 2011. Variables include sociodemographics, CVR factors and 10-year CV disease risk estimation (Regicor: Framingham score adapted to the Spanish population). Results: We included 860 patients (76.3% male) with no history of CVD. Median age 45.6 years; 84.1% were Spaniards; 29.9% women were IDUs. Median time since HIV diagnosis for men and women was 10 and 13 years (p=0.001), 28% had an AIDS diagnosis. Median CD4 cell count was 596 cells/mm3, 88% had undetectable viral load. Median time on ART was 91 and 108 months (p=0.017). There was a family history of early CVD in 113 men (17.9%) and 41 women (20.6%). Classical CVR factors are described in the table. Median (IQR) Regicor Score was 3% (2-5) for men and 2% (1-3) for women (p=0.000), and the proportion of subjects with mid-high risk (>5%) was 26.1% for men and 9.4% for women (p=0.000). Conclusions: In this population of HIV-infected patients, women have lower cardiovascular risk than men, partly due to higher levels of HDL cholesterol. Of note is the high frequency of smoking, abdominal obesity and sedentary lifestyle in our population. (Table Presented).

What spatial data do we need to develop global mammal conservation strategies?

Spatial data on species distributions are available in two main forms, point locations and distribution maps (polygon ranges and grids). The first are often temporally and spatially biased, and too discontinuous, to be useful (untransformed) in spatial analyses. A variety of modelling approaches are used to transform point locations into maps. We discuss the attributes that point location data and distribution maps must satisfy in order to be useful in conservation planning. We recommend that before point location data are used to produce and/or evaluate distribution models, the dataset should be assessed under a set of criteria, including sample size, age of data, environmental/geographical coverage, independence, accuracy, time relevance and (often forgotten) representation of areas of permanent and natural presence of the species. Distribution maps must satisfy additional attributes if used for conservation analyses and strategies, including minimizing commission and omission errors, credibility of the source/assessors and availability for public screening. We review currently available databases for mammals globally and show that they are highly variable in complying with these attributes. The heterogeneity and weakness of spatial data seriously constrain their utility to global and also sub-global scale conservation analyses.

Study and implementation of some quantitative trading models

Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.

Health literacy [Document électronique] : an economic perspective and data for Switzerland. Part 2, A review of health literacy measures and a cost assessment of limited health literacy

Summary : 1. Measuring health literacy in Switzerland: a review of six surveys: 1.1 Comparison of questionnaires - 1.2 Measures of health literacy in Switzerland - 1.3 Discussion of Swiss data on HL - 1.4 Description of the six surveys: 1.4.1 Current health trends and health literacy in the Swiss population (gfs-UNIVOX), 1.4.2 Nutrition, physical exercise and body weight : opinions and perceptions of the Swiss population (USI), 1.4.3 Health Literacy in Switzerland (ISPMZ), 1.4.4 Swiss Health Survey (SHS), 1.4.5 Survey of Health, Ageing and Retirement in Europe (SHARE), 1.4.6 Adult literacy and life skills survey (ALL). - 2 . Economic costs of low health literacy in Switzerland: a rough calculation. Appendix: Screenshots cost model

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Comparative analysis of human and mouse expression data illuminates tissue-specific evolutionary patterns of miRNAs.

MicroRNAs (miRNAs) constitute an important class of gene regulators. While models have been proposed to explain their appearance and expansion, the validation of these models has been difficult due to the lack of comparative studies. Here, we analyze miRNA evolutionary patterns in two mammals, human and mouse, in relation to the age of miRNA families. In this comparative framework, we confirm some predictions of previously advanced models of miRNA evolution, e.g. that miRNAs arise more frequently de novo than by duplication, or that the number of protein-coding gene targeted by miRNAs decreases with evolutionary time. We also corroborate that miRNAs display an increase in expression level with evolutionary time, however we show that this relation is largely tissue-dependent, and especially low in embryonic or nervous tissues. We identify a bias of tag-sequencing techniques regarding the assessment of breadth of expression, leading us, contrary to predictions, to find more tissue-specific expression of older miRNAs. Together, our results refine the models used so far to depict the evolution of miRNA genes. They underline the role of tissue-specific selective forces on the evolution of miRNAs, as well as the potential co-evolution patterns between miRNAs and the protein-coding genes they target.

Neuronal in vitro models for the estimation of acute systemic toxicity.

The objective of the EU funded integrated project "ACuteTox" is to develop a strategy in which general cytotoxicity, together with organ-specific endpoints and biokinetic features, are taken into consideration in the in vitro prediction of oral acute systemic toxicity. With regard to the nervous system, the effects of 23 reference chemicals were tested with approximately 50 endpoints, using a neuronal cell line, primary neuronal cell cultures, brain slices and aggregated brain cell cultures. Comparison of the in vitro neurotoxicity data with general cytotoxicity data generated in a non-neuronal cell line and with in vivo data such as acute human lethal blood concentration, revealed that GABA(A) receptor function, acetylcholine esterase activity, cell membrane potential, glucose uptake, total RNA expression and altered gene expression of NF-H, GFAP, MBP, HSP32 and caspase-3 were the best endpoints to use for further testing with 36 additional chemicals. The results of the second analysis showed that no single neuronal endpoint could give a perfect improvement in the in vitro-in vivo correlation, indicating that several specific endpoints need to be analysed and combined with biokinetic data to obtain the best correlation with in vivo acute toxicity.

Adipose tissue concentrations of persistent organic pollutants and total cancer risk in an adult cohort from Southern Spain: preliminary data from year 9 of the follow-up.

There is an increasing trend in the incidence of cancer worldwide, and it has been accepted that environmental factors account for an important proportion of the global burden. The present paper reports preliminary findings on the influence of the historical exposure to a group of persistent organic pollutants on total cancer risk, at year 9 in the follow-up of a cohort from Southern Spain. A cohort of 368 participants (median age 51 years) was recruited in 2003. Their historical exposure was estimated by analyzing residues of persistent organic pollutants in adipose tissue. Estimation of cancer incidence was based on data from a population-based cancer registry. Statistical analyses were performed using multivariable Cox-regression models. In males, PCB 153 concentrations were positively associated with total cancer risk, with an adjusted hazard ratio (95% confidence interval) of 1.20 (1.01-1.41) for an increment of 100 ng/g lipid. Our preliminary findings suggest a potential relationship between the historical exposure to persistent organic pollutants and the risk of cancer in men. However, these results should be interpreted with caution and require verification during the future follow-up of this cohort.

Two-sided learning in new keynesian models: dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that they observe (which may be distinct for different sets of agents) to form beliefs about unknown aspects of the true model of the economy, use their beliefs to decide on actions, and revise these beliefs through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of our model and derive its policy recommendations, particularly with respect to central bank communications. We demonstrate that two-sided learning can generate substantial increases in volatility and persistence, and alter the behavior of the variables in the model in a signifficant way. Our simulations do not converge to a symmetric rational expectations equilibrium and we highlight one source that invalidates the convergence results of Marcet and Sargent (1989). Finally, we identify a novel aspect of central bank communication in models of learning: communication can be harmful if the central bank's model is substantially mis-specified