Optimal exponent heat balance and refined integral methods applied to Stefan problems

When using a polynomial approximating function the most contentious aspect of the Heat Balance Integral Method is the choice of power of the highest order term. In this paper we employ a method recently developed for thermal problems, where the exponent is determined during the solution process, to analyse Stefan problems. This is achieved by minimising an error function. The solution requires no knowledge of an exact solution and generally produces significantly better results than all previous HBI models. The method is illustrated by first applying it to standard thermal problems. A Stefan problem with an analytical solution is then discussed and results compared to the approximate solution. An ablation problem is also analysed and results compared against a numerical solution. In both examples the agreement is excellent. A Stefan problem where the boundary temperature increases exponentially is analysed. This highlights the difficulties that can be encountered with a time dependent boundary condition. Finally, melting with a time-dependent flux is briefly analysed without applying analytical or numerical results to assess the accuracy.

Estimation of dynamic latent variable models using simulated nonparametric moments

Abstract. Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Because conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. It is shown that as the number of simulations diverges, the estimator is consistent and a higher-order expansion reveals the stochastic difference between the infeasible GMM estimator based on the same moment conditions and the simulated version. In particular, we show how to adjust standard errors to account for the simulations. Monte Carlo results show how the estimator may be applied to a range of dynamic latent variable (DLV) models, and that it performs well in comparison to several other estimators that have been proposed for DLV models.

Variable phenotypic expressivity in a Swiss family with autosomal dominant retinitis pigmentosa due to mutation T494m in the Prpf3 gene

Purpose:to describe the clinical features in a five generations family segregating autosomal dominant retinitis pigmentosa and to identify the causative gene Patient and Methods:Twenty five individuals of a large five-generation family originating from Western Switzerland were ascertained for phenotypic and genotypic characterization. Ophthalmologic evaluations included color vision testing, Goldman perimetry and digital fundus photography. Some patients had autofluorescence (AF) imaging, ocular coherence tomography (OCT) and ISCEV-standard full-field electroretinography (ERG). Blood samples were collected from 10 affected (4 to 70 years of age) and 15 unaffected members after informed consent. DNA was isolated and exons and intron-exons junctions of known adRP genes were sequenced using a Big Dye sequencing kit 1.1. Results:Age of onset of nightblindness and severity of progression of the disease was variable between members of the family. Some patients had early onset of nightblindess aged 3, others at mid-twenties. Most patients had visual acuity above 0.6 for the first 4 decades. Two older patients still had good vision (0.4) in their seventies. Myopia (range: -2 to -5) was noticed in most affected subjects. Fundus findings showed areas of atrophy along the arcades. The AF imaging showed a large high density ring bilaterally. A T494M change was found in exon 11 of PRPF3 gene. The change segregates with the disease in the family. Conclusion: A mutation in the PRPF3 gene is rare compared with other genes causing ADRP. Although a T494M change has been reported, our family is the first one with a variable expressivity. Mutations in PRPF3 gene can cause a variable phenotype of ADRP unlike the previously described Danish and English families. Our report gives a better understanding as to the phenotype/genotype description of ADRP due to PRPF3 mutation.

Comparative Histopathology of Biomphalaria glabrata, B. tenagophila and B. straminea with Variable Degrees of Resistance to Schistosoma mansoni Miracidia

A comparative histopathological study of three snails species - Biomphalaria glabrata, B. tenagophila and B. straminea - which had been infected with Schistosoma mansoni miracidia revealed similar qualitative features, consisting of areas of sporocyst proliferation and differentiation associated with reactive host reaction, at the time they were actively eliminating great number of cercariae. However, in specimens that were exposed to miracidia but failed to eliminate cercariae later on, different histopathological pictures were observed in different snail species. While B. glabrata exhibited frequent focal (granulomatous) proliferation of amebocytes in several organs, B. tenagophila and B. straminea only rarely showed such reactive changes, suggesting that the mechanism of resistance to miracidial infection probably follows different pathways in the snail species studied

Two monoclonal rat antibodies with specificity for the beta-chain variable region V beta 6 of the murine T-cell receptor.

Two rat monoclonal antibodies (mAbs), 44-22-1 and 46-6B5, which recognize an alloreactive cytotoxic clone, 3F9, have been further tested on a panel of T hybridomas and cytotoxic T-cell clones for binding and functional activities. The mAbs recognized only those cells sharing the expression of the T-cell receptor beta-chain variable region gene V beta 6 with 3F9. All V beta 6+ cells were activated by these mAbs under cross-linking conditions and their antigen-specific activation was blocked by soluble mAb. Furthermore, depletion of 46-6B5+ normal lymph node T cells eliminated all cells expressing the epitope recognized by 44-22-1 and V beta 6 mRNA.

Interpolation methods for stochastic processes spaces

In this paper the scales of classes of stochastic processes are introduced. New interpolation theorems and boundedness of some transforms of stochastic processes are proved. Interpolation method for generously-monotonous rocesses is entered. Conditions and statements of interpolation theorems concern he xed stochastic process, which diers from the classical results.

Spaces with Noetherian cohomology

Is the cohomology of the classifying space of a p-compact group, with Noetherian twisted coefficients, a Noetherian module? This note provides, over the ring of p-adic integers, such a generalization to p-compact groups of the Evens-Venkov Theorem. We consider the cohomology of a space with coefficients in a module, and we compare Noetherianity over the field with p elements, with Noetherianity over the p-adic integers, in the case when the fundamental group is a finite p-group.

Hankel operators on holomorphic Hardy-Orlicz spaces

"Vegeu el resum a l'inici del document del fitxer adjunt."

Interpolation and sampling in small Bergman spaces

"Vegeu el resum a l'inici del document del fitxer adjunt."

Genomics of wine yeast: functional analysis of new and variable genes

Projecte de recerca elaborat a partir d’una estada a l’Institut National de la Recherche Agronomique, França, entre 2007 i 2009. Saccharomyces cerevisiae ha estat el llevat utilitzat durant mil.lenis en l'elaboració de vins. Tot i així, es té poc coneixement sobre les pressions de selecció que han actuat en la modelització del genoma dels llevats vínics. S’ha seqüenciat el genoma d'una soca vínica comercial, EC1118, obtenint 31 supercontigs que cobreixen el 97% del genoma de la soca de referència, S288c. S’ha trobat que el genoma de la soca vínica es diferencia bàsicament en la possessió de 3 regions úniques que contenen 34 gens implicats en funcions claus per al procés fermentatiu. A banda, s’han dut a terme estudis de filogènia i synteny (ordre dels gens) que mostren que una d'aquestes tres regions és pròxima a una espècie relacionada amb el gènere Saccharomyces, mentre que les altres dos regions tenen un origen no-Saccharomyces. S’ha identificat mitjançant PCR i seqüenciació a Zygosaccharomyces bailii, una espècie contaminant de les fermentacions víniques, com a espècie donadora d'una de les dues regions. Les hibridacions naturals entre soques de diferents espècies dins del grup Saccharomyces sensu stricto ja han estat descrites. El treball és el primer que presenta hibridacions entre espècies Saccharomyces i no-Saccharomyces (Z. bailii, en aquest cas). També s’assenyala que les noves regions es troben freqüent i diferencialment presents entre els clades de S. cerevisiae, trobant-se de manera gairebé exclusiva en el grup de les soques víniques, suggerint que es tracta d'una adquisició recent de transferència gènica. En general, les dades demostren que el genoma de les soques víniques pateix una constant remodelació mitjançant l'adquisició de gens exògens. Els resultats suggereixen que aquests processos estan afavorits per la proximitat ecològica i estan implicats en l'adaptació molecular de les soques víniques a les condicions d'elevada concentració en sucres, poc nitrogen i elevades concentracions en etanol.

Immunodéficience commune variable: ce qu'il faut savoir [Common variable immune deficiency: what you need to know].

Common variable immune deficiency is the most frequent primary immune deficiency, characterized mainly by a disorder of B lymphocytes differentiation and a deficit in immunoglobulins. The clinical manifestations include recurrent infections, non-infectious lung and digestive involvements, autoimmune diseases, and an increased susceptibility to cancers. Recent breakthroughs have been made in the understanding of some genetic mechanisms of the disease. Replacement therapy with intravenous immunoglobulins remains the treatment of choice, which allows significant improvement in the survival and quality of life. However progress should be made in the understanding of the pathophysiology and in the early detection of this disease, since a delay in the diagnosis may have harmful consequences in terms of morbidity and mortality.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Improving Access to Green Spaces

Evidence Review 8 - Improving access to green spaces Briefing 8 - Improving access to green spaces This pair of documents, commissioned by Public Health England, and written by the UCL Institute of Health Equity, address the role of green space in improving health locally. The first part of the evidence review defines ‘accessible’ green space and provides an overview of the evidence linking access to green spaces with health benefits, setting out the potential for reducing health inequalities. The second part provides an overview of interventions implemented at the local level to increase equitable access and use of good quality green spaces. Local authorities and local organisations have taken action on these issues through the implementation of interventions to: 1. Create new areas of green space and improve the quality of existing green spaces 2. Increase accessibility, engagement and use of green spaces The full evidence review and a shorter summary briefing are available to download above. This document is part of a series. An overview document which provides an introduction to this and other documents in the series, and links to the other topic areas, is available on the ‘Local Action on health inequalities’ project page. A video of Michael Marmot introducing the work is also available on our videos page.

Assessing the Relationship between the Baseline Value of a Continuous Variable and Subsequent Change over Time

Analyzing the relationship between the baseline value and subsequent change of a continuous variable is a frequent matter of inquiry in cohort studies. These analyses are surprisingly complex, particularly if only two waves of data are available. It is unclear for non-biostatisticians where the complexity of this analysis lies and which statistical method is adequate.With the help of simulated longitudinal data of body mass index in children,we review statistical methods for the analysis of the association between the baseline value and subsequent change, assuming linear growth with time. Key issues in such analyses are mathematical coupling, measurement error, variability of change between individuals, and regression to the mean. Ideally, it is better to rely on multiple repeated measurements at different times and a linear random effects model is a standard approach if more than two waves of data are available. If only two waves of data are available, our simulations show that Blomqvist's method - which consists in adjusting for measurement error variance the estimated regression coefficient of observed change on baseline value - provides accurate estimates. The adequacy of the methods to assess the relationship between the baseline value and subsequent change depends on the number of data waves, the availability of information on measurement error, and the variability of change between individuals.

On the presence of hepatic stellate cells in portal spaces

Previous studies in mice with hypervitaminosis A have demonstrated that fat-storing cells (hepatic stellate cells-HSCs) participate in schistosomal granuloma fibrogenesis. The origin of such cells in portal areas, away from the Disse spaces, was herein investigated. HSCs were identified in frozen sections of the liver by means of Sudan III staining. They appeared as red-stained cells disposed along the sinusoids of normal mice, but were never found within portal spaces. However, in the chronically inflamed portal spaces of Capillaria hepatica-infected mice, Sudan III-positive cells were frequently present among leukocytes and fibroblast-like cells. Thus, there are no resident HSCs in portal spaces, but their presence there in chronic inflammatory processes indicates that they are able to migrate from peri-sinusoidal areas in order to reach the portal areas.