Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

Lifelong dynamics of human CD4+CD25+ regulatory T cells: insights from in vivo data and mathematical modeling.

Despite their limited proliferation capacity, regulatory T cells (T(regs)) constitute a population maintained over the entire lifetime of a human organism. The means by which T(regs) sustain a stable pool in vivo are controversial. Using a mathematical model, we address this issue by evaluating several biological scenarios of the origins and the proliferation capacity of two subsets of T(regs): precursor CD4(+)CD25(+)CD45RO(-) and mature CD4(+)CD25(+)CD45RO(+) cells. The lifelong dynamics of T(regs) are described by a set of ordinary differential equations, driven by a stochastic process representing the major immune reactions involving these cells. The model dynamics are validated using data from human donors of different ages. Analysis of the data led to the identification of two properties of the dynamics: (1) the equilibrium in the CD4(+)CD25(+)FoxP3(+)T(regs) population is maintained over both precursor and mature T(regs) pools together, and (2) the ratio between precursor and mature T(regs) is inverted in the early years of adulthood. Then, using the model, we identified three biologically relevant scenarios that have the above properties: (1) the unique source of mature T(regs) is the antigen-driven differentiation of precursors that acquire the mature profile in the periphery and the proliferation of T(regs) is essential for the development and the maintenance of the pool; there exist other sources of mature T(regs), such as (2) a homeostatic density-dependent regulation or (3) thymus- or effector-derived T(regs), and in both cases, antigen-induced proliferation is not necessary for the development of a stable pool of T(regs). This is the first time that a mathematical model built to describe the in vivo dynamics of regulatory T cells is validated using human data. The application of this model provides an invaluable tool in estimating the amount of regulatory T cells as a function of time in the blood of patients that received a solid organ transplant or are suffering from an autoimmune disease.

Workshop on new strategies and tools for the eHealth library

The Andalusian eHealth Library (Biblioteca Virtual del Sistema Sanitario Publico de Andalucia, BV-SSPA), was created in June 2006. The 42 librarians who already worked for the Health System were integrated within this new system. The annual library meeting has been held every year since then, and in 2013 the EAHIL workshop held in Stockholm was the model to follow.

Getting ready for malaria elimination: a check list of critical issues to consider

In recent years, a renewed interest in malaria elimination and eradication has emerged and seems to be rooting in the minds of the scientific community, public health specialists, funding bodies, policy makers and politicians. Malaria eradication will certainly benefit from improved and innovative tools; notwithstanding novel knowledge in fields ranging from basic science to mathematical modelling and health systems research. However, the elimination of malaria also encompasses a broad range of essential aspects that countries and other actors need to consider when thinking of embarking on such an adventure, including the implementation of innovative strategies, the ability to incorporate the most up-to-date evidence into policy, the integration of malaria into the broader health agenda, the strengthening of surveillance and health systems, capacity building, funding, advocacy and, very importantly, research. While in some cases this enthusiasm is clearly justified, some countries are still a long way from realistically advancing towards elimination. This paper attempts to provide guidance on all the necessary issues that should be considered when initiating a malaria elimination program.

Mathematical modeling and analysis of the interaction of populations of bacteria and bacteriophages within chicken intestine

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Tissue microarray and immunohistochemistry as tools for evaluation of antibodies against Chlamydia-like bacteria.

Tissue microarray technology was used to establish immunohistochemistry protocols and to determine the specificity of new antisera against various Chlamydia-like bacteria for future use on formalin-fixed and paraffin-embedded tissues. The antisera exhibited strong reactivity against autologous antigen and closely related heterologous antigen, but no cross-reactivity with distantly related species.

Allergie aux venins d'hyménopteres: nouveautés diagnostiques et prise en charge [Hymenoptera venom allergy: new diagnostic tools and management].

Anaphylactic reactions to hymenoptera venoms are common and, in our latitudes, mainly concern wasps and bees. Recently, molecular biology techniques have contributed to identifying and to sequencing the major allergens of insect venoms and led to the production of recombinant allergens. Assays for specific IgE directed against these recombinant allergens have recently been made available in clinical practice. They provide considerable assistance in identifying the insect responsible for an anaphylactic reaction, in particular when standard tests are positive for both wasp and bee. This article focuses on these new laboratory tests and also reviews the management of patients experiencing an anaphylactic reaction after hymenoptera sting.

First insights into the transcriptome and development of new genomic tools of a widespread circum-Mediterranean tree species, Pinus halepensis Mill.

Aleppo pine (Pinus halepensis Mill.) is a relevant conifer species for studying adaptive responses to drought and fire regimes in the Mediterranean region. In this study, we performed Illumina next-generation sequencing of two phenotypically divergent Aleppo pine accessions with the aims of (i) characterizing the transcriptome through Illumina RNA-Seq on trees phenotypically divergent for adaptive traits linked to fire adaptation and drought, (ii) performing a functional annotation of the assembled transcriptome, (iii) identifying genes with accelerated evolutionary rates, (iv) studying the expression levels of the annotated genes and (v) developing gene-based markers for population genomic and association genetic studies. The assembled transcriptome consisted of 48,629 contigs and covered about 54.6 Mbp. The comparison of Aleppo pine transcripts to Picea sitchensis protein-coding sequences resulted in the detection of 34,014 SNPs across species, with a Ka /Ks average value of 0.216, suggesting that the majority of the assembled genes are under negative selection. Several genes were differentially expressed across the two pine accessions with contrasted phenotypes, including a glutathione-s-transferase, a cellulose synthase and a cobra-like protein. A large number of new markers (3334 amplifiable SSRs and 28,236 SNPs) have been identified which should facilitate future population genomics and association genetics in this species. A 384-SNP Oligo Pool Assay for genotyping with the Illumina VeraCode technology has been designed which showed an high overall SNP conversion rate (76.6%). Our results showed that Illumina next-generation sequencing is a valuable technology to obtain an extensive overview on whole transcriptomes of nonmodel species with large genomes.

Segmentation and grid generation for numerical simulations of vad connections with patient-specific data

Objectives: We are interested in the numerical simulation of the anastomotic region comprised between outflow canula of LVAD and the aorta. Segmenta¬tion, geometry reconstruction and grid generation from patient-specific data remain an issue because of the variable quality of DICOM images, in particular CT-scan (e.g. metallic noise of the device, non-aortic contrast phase). We pro¬pose a general framework to overcome this problem and create suitable grids for numerical simulations.Methods: Preliminary treatment of images is performed by reducing the level window and enhancing the contrast of the greyscale image using contrast-limited adaptive histogram equalization. A gradient anisotropic diffusion filter is applied to reduce the noise. Then, watershed segmentation algorithms and mathematical morphology filters allow reconstructing the patient geometry. This is done using the InsightToolKit library (www.itk.org). Finally the Vascular Model¬ing ToolKit (www.vmtk.org) and gmsh (www.geuz.org/gmsh) are used to create the meshes for the fluid (blood) and structure (arterial wall, outflow canula) and to a priori identify the boundary layers. The method is tested on five different patients with left ventricular assistance and who underwent a CT-scan exam.Results: This method produced good results in four patients. The anastomosis area is recovered and the generated grids are suitable for numerical simulations. In one patient the method failed to produce a good segmentation because of the small dimension of the aortic arch with respect to the image resolution.Conclusions: The described framework allows the use of data that could not be otherwise segmented by standard automatic segmentation tools. In particular the computational grids that have been generated are suitable for simulations that take into account fluid-structure interactions. Finally the presented method features a good reproducibility and fast application.

MAR elements as tools to increase protein production by CHO cells

One of the major hurdles of isolating stable, inducible or constitutive high-level producer cell lines is the time-consuming selection, analysis and characterization of the numerous clones required to identify one with the desired characteristics. Various boundary elements, matrix attachment regions, and locus control regions were screened for for their ability to augment the expression of heterologous genes in CHO and other cells. The 5'-matrix-attachment region (MAR) of the chicken lysozyme gene was found to significantly increase stable gene expression, in culture dishes and in bioreactors. These MAR elements can be easily combined with various existing expression systems, as they can be added in trans (i.e. on a separate plasmid) in co-transfections with previously constructed expression vectors. Using cell population analysis, we found that the use of the MAR increases the proportion of high-producing CHO cell clones, thus reducing the number of cell lines that need to be screened while increasing maximal productivity. Random cDNA cloning and sequencing indicated that over 12% of the ESTs correspond to the transgene. Thus, productivity is no longer limited by transcriptional events in such MAR-containing cell lines. The identification of small and more convenient active MAR portions will also be summarized. Finally, we will show examples of how MAR elements can be combined with short term expression to increase the simultaneous synthesis of many proteins in parallel by CHO cells. Overall, we conclude that the MAR sequence is a versatile tool to increase protein expression in short and long term production processes.

IDED Tools and Trends, February, 2001

Newsletter for Economic Development

Tools and Trends, July 2001, Issue 16

Newsletter for Ecnonmic Development

IDED Tools and Trends, January 2002, Issue 17

Newsletter for Economic Development

IDED Tools and Trends, Summer 2002, Issue 20

Newsletter for Ecnonmic Development

IDED Tools and Trends, Fall 2002

Newsletter for Economic Development