From ensemble forecasts to predictive distribution functions

The translation of an ensemble of model runs into a probability distribution is a common task in model-based prediction. Common methods for such ensemble interpretations proceed as if verification and ensemble were draws from the same underlying distribution, an assumption not viable for most, if any, real world ensembles. An alternative is to consider an ensemble as merely a source of information rather than the possible scenarios of reality. This approach, which looks for maps between ensembles and probabilistic distributions, is investigated and extended. Common methods are revisited, and an improvement to standard kernel dressing, called ‘affine kernel dressing’ (AKD), is introduced. AKD assumes an affine mapping between ensemble and verification, typically not acting on individual ensemble members but on the entire ensemble as a whole, the parameters of this mapping are determined in parallel with the other dressing parameters, including a weight assigned to the unconditioned (climatological) distribution. These amendments to standard kernel dressing, albeit simple, can improve performance significantly and are shown to be appropriate for both overdispersive and underdispersive ensembles, unlike standard kernel dressing which exacerbates over dispersion. Studies are presented using operational numerical weather predictions for two locations and data from the Lorenz63 system, demonstrating both effectiveness given operational constraints and statistical significance given a large sample.

Comparison of TAMSAT and CPC rainfall estimates with raingauges, for southern Africa

Two different TAMSAT (Tropical Applications of Meteorological Satellites) methods of rainfall estimation were developed for northern and southern Africa, based on Meteosat images. These two methods were used to make rainfall estimates for the southern rainy season from October 1995 to April 1996. Estimates produced by both TAMSAT methods and estimates produced by the CPC (Climate Prediction Center) method were then compared with kriged data from over 800 raingauges in southern Africa. This shows that operational TAMSAT estimates are better over plateau regions, with 59% of estimates within one standard error (s.e.) of the kriged rainfall. Over mountainous regions the CPC approach is generally better, although all methods underestimate and give only 40% of estimates within 1 s.e. The two TAMSAT methods show little difference across a whole season, but when looked at in detail the northern method gives unsatisfactory calibrations. The CPC method does have significant overall improvements by building in real-time raingauge data, but only where sufficient raingauges are available.

Effective measures to decrease air contaminants through risk and control visualization : a study of the effective use of QR codes to facilitate safety training

Woodworking industries still consists of wood dust problems. Young workers are especially vulnerable to safety risks. To reduce risks, it is important to change attitudes and increase knowledge about safety. Safety training have shown to establish positive attitudes towards safety among employees. The aim of current study is to analyze the effect of QR codes that link to Picture Mix EXposure (PIMEX) videos by analyzing attitudes to this safety training method and safety in student responses. Safety training videos were used in upper secondary school handicraft programs to demonstrate wood dust risks and methods to decrease exposure to wood dust. A preliminary study was conducted to investigate improvement of safety training in two schools in preparation for the main study that investigated a safety training method in three schools. In the preliminary study the PIMEX method was first used in which students were filmed while wood dust exposure was measured and subsequently displayed on a computer screen in real time. Before and after the filming, teachers, students, and researchers together analyzed wood dust risks and effective measures to reduce exposure to them. For the main study, QR codes linked to PIMEX videos were attached at wood processing machines. Subsequent interviews showed that this safety training method enables students in an early stage of their life to learn about risks and safety measures to control wood dust exposure. The new combination of methods can create awareness, change attitudes and motivation among students to work more frequently to reduce wood dust. 

Search for contact interactions using the inclusive jet pT spectrum in pp collisions at √s=7 TeV

Results are reported of a search for a deviation in the jet production cross section from the prediction of perturbative quantum chromodynamics at next-to-leading order. The search is conducted using a 7 TeV proton-proton data sample corresponding to an integrated luminosity of 5.0 fb-1, collected with the Compact Muon Solenoid detector at the Large Hadron Collider. A deviation could arise from interactions characterized by a mass scale Λ too high to be probed directly at the LHC. Such phenomena can be modeled as contact interactions. No evidence of a deviation is found. Using the CL s criterion, lower limits are set on Λ of 9.9 TeV and 14.3 TeV at 95% confidence level for models with destructive and constructive interference, respectively. Limits obtained with a Bayesian method are also reported. © 2013 CERN.

Projeto otimizado de redes neurais artificiais para predição da rugosidade em processos de usinagem com a utilização da metodologia de projeto de experimentos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Spatio-temporal patterns of tuberculosis incidence in Ribeirão Preto, State of São Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis

INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.

Differential expression analysis for sequence count data via mixtures of negative binomials

The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.

The Prevention of Delirium and Complications Associated with Surgical Treatments (PODCAST) study: protocol for an international multicentre randomised controlled trial

INTRODUCTION Postoperative delirium is one of the most common complications of major surgery, affecting 10-70% of surgical patients 60 years and older. Delirium is an acute change in cognition that manifests as poor attention and illogical thinking and is associated with longer intensive care unit (ICU) and hospital stay, long-lasting cognitive deterioration and increased mortality. Ketamine has been used as an anaesthetic drug for over 50 years and has an established safety record. Recent research suggests that, in addition to preventing acute postoperative pain, a subanaesthetic dose of intraoperative ketamine could decrease the incidence of postoperative delirium as well as other neurological and psychiatric outcomes. However, these proposed benefits of ketamine have not been tested in a large clinical trial. METHODS The Prevention of Delirium and Complications Associated with Surgical Treatments (PODCAST) study is an international, multicentre, randomised controlled trial. 600 cardiac and major non-cardiac surgery patients will be randomised to receive ketamine (0.5 or 1 mg/kg) or placebo following anaesthetic induction and prior to surgical incision. For the primary outcome, blinded observers will assess delirium on the day of surgery (postoperative day 0) and twice daily from postoperative days 1-3 using the Confusion Assessment Method or the Confusion Assessment Method for the ICU. For the secondary outcomes, blinded observers will estimate pain using the Behavioral Pain Scale or the Behavioral Pain Scale for Non-Intubated Patients and patient self-report. ETHICS AND DISSEMINATION The PODCAST trial has been approved by the ethics boards of five participating institutions; approval is ongoing at other sites. Recruitment began in February 2014 and will continue until the end of 2016. Dissemination plans include presentations at scientific conferences, scientific publications, stakeholder engagement and popular media. REGISTRATION DETAILS The study is registered at clinicaltrials.gov, NCT01690988 (last updated March 2014). The PODCAST trial is being conducted under the auspices of the Neurological Outcomes Network for Surgery (NEURONS). TRIAL REGISTRATION NUMBER NCT01690988 (last updated December 2013).

Continental-Scale Footprint of Balancing and Positive Selection in a Small Rodent (Microtus arvalis)

Genetic adaptation to different environmental conditions is expected to lead to large differences between populations at selected loci, thus providing a signature of positive selection. Whereas balancing selection can maintain polymorphisms over long evolutionary periods and even geographic scale, thus leads to low levels of divergence between populations at selected loci. However, little is known about the relative importance of these two selective forces in shaping genomic diversity, partly due to difficulties in recognizing balancing selection in species showing low levels of differentiation. Here we address this problem by studying genomic diversity in the European common vole (Microtus arvalis) presenting high levels of differentiation between populations (average FST = 0.31). We studied 3,839 Amplified Fragment Length Polymorphism (AFLP) markers genotyped in 444 individuals from 21 populations distributed across the European continent and hence over different environmental conditions. Our statistical approach to detect markers under selection is based on a Bayesian method specifically developed for AFLP markers, which treats AFLPs as a nearly codominant marker system, and therefore has increased power to detect selection. The high number of screened populations allowed us to detect the signature of balancing selection across a large geographic area. We detected 33 markers potentially under balancing selection, hence strong evidence of stabilizing selection in 21 populations across Europe. However, our analyses identified four-times more markers (138) being under positive selection, and geographical patterns suggest that some of these markers are probably associated with alpine regions, which seem to have environmental conditions that favour adaptation. We conclude that despite favourable conditions in this study for the detection of balancing selection, this evolutionary force seems to play a relatively minor role in shaping the genomic diversity of the common vole, which is more influenced by positive selection and neutral processes like drift and demographic history.

Simulation study of joint transition and Weibull survival model with shared parameters

This study investigates a theoretical model where a longitudinal process, that is a stationary Markov-Chain, and a Weibull survival process share a bivariate random effect. Furthermore, a Quality-of-Life adjusted survival is calculated as the weighted sum of survival time. Theoretical values of population mean adjusted survival of the described model are computed numerically. The parameters of the bivariate random effect do significantly affect theoretical values of population mean. Maximum-Likelihood and Bayesian methods are applied on simulated data to estimate the model parameters. Based on the parameter estimates, predicated population mean adjusted survival can then be calculated numerically and compared with the theoretical values. Bayesian method and Maximum-Likelihood method provide parameter estimations and population mean prediction with comparable accuracy; however Bayesian method suffers from poor convergence due to autocorrelation and inter-variable correlation. ^

Bayesian inference and its application to meta-analysis of epidemiologic data

In Part One, the foundations of Bayesian inference are reviewed, and the technicalities of the Bayesian method are illustrated. Part Two applies the Bayesian meta-analysis program, the Confidence Profile Method (CPM), to clinical trial data and evaluates the merits of using Bayesian meta-analysis for overviews of clinical trials.^ The Bayesian method of meta-analysis produced similar results to the classical results because of the large sample size, along with the input of a non-preferential prior probability distribution. These results were anticipated through explanations in Part One of the mechanics of the Bayesian approach. ^

Validación del método de predicción de direcciones principales de drenaje subterráneo en macizos anisótropos, en los terrenos volcánicos del macizo de Anaga, Tenerife

Actualmente y desde hace ya más de 25 años, el Método de “Predicción de las Direcciones Principales de Drenaje Subterráneo en Macizos Anisótropos”, ha sido utilizado con éxito en diferentes terrenos Kársticos como: calizas, yesos, cuarcitas, pizarras, granitos y criokarst (karst en el hielo glaciar). Sin embargo hasta ahora, nunca se había validado en terrenos volcánicos donde está focalizada esta tesis que lleva por título, Validación de dicho Método en los Terrenos Volcánicos del Macizo de Anaga en Tenerife. Este Método matemático consiste esencialmente en “Predecir y Cuantificar” las direcciones principales de drenaje turbulento subterráneo en macizos anisótropos. Para ello se basa en el estudio realizado en campo de los tectoglifos o deformaciones permanentes del macizo, impresas éstas en la roca, como consecuencia de los esfuerzos tectónicos a los que ha estado sometido dicho macizo. Se consigue de esta manera cubrir el vacío para macizos anisótropos que existe con el modelo matemático de flujo subterráneo laminar (macizos isótropos) definido por Darcy (1856). Para validar el Método se ha elegido el macizo de Anaga, pues es la zona de mayor anisotropía existente en la isla de Tenerife, conformada por una gran y extensa red de diques de diversas formas y tamaños que pertenecen a la familia de diques del eje estructural NE de la isla. En dicho macizo se realizó un exhaustivo trabajo de campo con la toma 331 datos (diques basálticos) y se aplicó el Método, consiguiendo definir las direcciones preferentes de drenaje subterráneo en el macizo de Anaga. Esta predicción obtenida se contrastó con la realidad del drenaje en la zona, conocida gracias a la existencia de cinco galerías ubicadas en la zona trabajo, de las cuales se tiene información sobre sus alumbramientos. En todos los casos se demuestra la bondad de la predicción obtenida con el Método. Queda demostrado que a mayor caos geológico o geotectónico, se ha conseguido mejor predicción del Método, obteniéndose resultados muy satisfactorios para aquellas galerías de agua en las que su rumbo de avance fue coincidente con la dirección perpendicular a la obtenida con la predicción dada por el Método, como dirección preferente de drenaje en la zona en la que se encuentra ubicada cada galería. No cabe duda que la validación de Método en los terrenos volcánicos de Tenerife, supondrá un cambio considerable en el mundo de la hidrogeología en este tipo de terrenos. Es la única herramienta matemática que se dispone para predecir un rumbo acertado en el avance de la perforación de las galerías de aguas, lo que conlleva al mismo tiempo un ahorro importantísimo en la ejecución de las obras. Por otro lado, el Método deja un importante legado a la sociedad canaria, pues con él se abren numerosas vías de trabajo e investigación que generarán un importante desarrollo en el mundo de la hidrogeología volcánica. ABSTRACT Currently and for over 25 years now, the Method of "Prediction of Subsurface Drainage Main Directions in Anisotropic Massifs" has been successfully used in various karstic terrains such as: limestone, gypsum, quartzite, slate, granite and criokarst (karst in the glacier ice). However, until now, it had never been validated in volcanic terrains where is focused this thesis entitled Validation of such Method in the Anaga Massif Volcanic Terrains, in Tenerife. This mathematical method is essentially "predict and quantify" the main directions of groundwater turbulent drainage in anisotropic massifs. This is based on field study of tectoglifes or permanent deformation of the massif, printed on the rocks as a result of previous tectonic stresses. Therefore it is possible to use in anisotropic rock mathematical model instead of the isotropic laminar flow mathematical models defined by Darcy (1856). The Anaga Massif have been chosen to validate the method, because it presents the greatest anisotropy in Tenerife Island, shaped by a large and extensive network of dikes of various shapes and sizes that belong to the family of NE structural axis dikes of the island. An exhaustive field work was carried out in such massif, with 331 collected data (basaltic dikes) and the method was applied, in order to define the preferred direction of the underground drainage in the Anaga massif. This obtained prediction was contrasted to the reality of the drainage in the area, known thanks to the existence of five galleries located in the work area, from which information about their springs was available. In all cases it was possible to demonstrate the fitness of the prediction obtained by the method. It had been demonstrated that a greater geological or geotectonic chaos enhances a better prediction of the method, that predicted very satisfactory results for those water galleries which directions were perpendicular to that predicted by the Method as a drainage preferential direction, for the zone where was located each gallery. No doubt that the validation of the use of the Method in the volcanic terrain of Tenerife, means a considerable change in the world of hydrogeology in this type of terrain. It is the only mathematical tool available to predict a successful drilling direction in advancing water galleries, what also leads to major savings in execution of the drilling works. Furthermore, the method leaves an important legacy to the Canary Islands society, because it opens many lines of work and research to generate a significant development in the world of volcanic hydrogeology.

Genetic analysis of complex demographic scenarios: Spatially expanding populations of the cane toad, Bufo marinus

Inferring the spatial expansion dynamics of invading species from molecular data is notoriously difficult due to the complexity of the processes involved. For these demographic scenarios, genetic data obtained from highly variable markers may be profitably combined with specific sampling schemes and information from other sources using a Bayesian approach. The geographic range of the introduced toad Bufo marinus is still expanding in eastern and northern Australia, in each case from isolates established around 1960. A large amount of demographic and historical information is available on both expansion areas. In each area, samples were collected along a transect representing populations of different ages and genotyped at 10 microsatellite loci. Five demographic models of expansion, differing in the dispersal pattern for migrants and founders and in the number of founders, were considered. Because the demographic history is complex, we used an approximate Bayesian method, based on a rejection-regression algorithm. to formally test the relative likelihoods of the five models of expansion and to infer demographic parameters. A stepwise migration-foundation model with founder events was statistically better supported than other four models in both expansion areas. Posterior distributions supported different dynamics of expansion in the studied areas. Populations in the eastern expansion area have a lower stable effective population size and have been founded by a smaller number of individuals than those in the northern expansion area. Once demographically stabilized, populations exchange a substantial number of effective migrants per generation in both expansion areas, and such exchanges are larger in northern than in eastern Australia. The effective number of migrants appears to be considerably lower than that of founders in both expansion areas. We found our inferences to be relatively robust to various assumptions on marker. demographic, and historical features. The method presented here is the only robust, model-based method available so far, which allows inferring complex population dynamics over a short time scale. It also provides the basis for investigating the interplay between population dynamics, drift, and selection in invasive species.

Extreme learning machine for predicting HLA-peptide binding

Machine learning techniques have been recognized as powerful tools for learning from data. One of the most popular learning techniques, the Back-Propagation (BP) Artificial Neural Networks, can be used as a computer model to predict peptides binding to the Human Leukocyte Antigens (HLA). The major advantage of computational screening is that it reduces the number of wet-lab experiments that need to be performed, significantly reducing the cost and time. A recently developed method, Extreme Learning Machine (ELM), which has superior properties over BP has been investigated to accomplish such tasks. In our work, we found that the ELM is as good as, if not better than, the BP in term of time complexity, accuracy deviations across experiments, and most importantly - prevention from over-fitting for prediction of peptide binding to HLA.

Experimental transmission of dispersion managed solitons

This thesis investigates the feasibility of soliton transmission at 1150nm over standard fibre. This is done using a dispersion compensating fibre module in each amplifier span to compensate for the high dispersion. The basic principles of soliton propagation in optical fibre are discussed within this thesis, followed by an introduction to advantages of dispersion management. In the experimental chapter single channel transmission results are presented in 10Gbit/s and 40Gbit/s. At 10Gbit/s the effects of dispersion management on the power dispersion relationship for solitons are investigated. The detrimental effects of soliton-soliton interactions, which are increased due to the greater overlap breathing solitons are discussed. A technique for reducing the soliton-soliton interactions through amplifier positioning is presented as a solution to this problem. The experiments demonstrate the feasibility of using standard fibre for transmission over trans-oceanic distances at 10Gbit/s. The 40Gbit/s experiment demonstrates transmission over sufficient distance for an terrestrial system. Also contained within this thesis are experimental results showing transmission of solitons over dispersion shifted fibre using a novel technique that makes use of the non-linear polarisation rotation of the soliton in the fibre. This is used to generate the effect of saturable absorption, allowing transmission distances of 200,000km to be achieved.