Fusion of data sets in multivariate linear regression with errors-in-variables

We consider the application of normal theory methods to the estimation and testing of a general type of multivariate regressionmodels with errors--in--variables, in the case where various data setsare merged into a single analysis and the observable variables deviatepossibly from normality. The various samples to be merged can differ on the set of observable variables available. We show that there is a convenient way to parameterize the model so that, despite the possiblenon--normality of the data, normal--theory methods yield correct inferencesfor the parameters of interest and for the goodness--of--fit test. Thetheory described encompasses both the functional and structural modelcases, and can be implemented using standard software for structuralequations models, such as LISREL, EQS, LISCOMP, among others. An illustration with Monte Carlo data is presented.

Analysis of antiviral immunity in primary and chronic infections

Several evidences in humans underscored the contribution of CD4 and CD8 T-cell responses in controlling viral and bacterial infections. However, CD4 and CD8 Τ cells have distinct and specific effector functions leading to a hierarchical importance in responding to different types of pathogens. In this context, the present work aimed to investigate distinct CD8 T-cell features potentially influencing T-cell efficacy against viral infection. To achieve this-objective, CD8 Τ cells derived from HIV-infected patients and healthy donors harbouring virus-specific immune responses or immunized with an HTV vaccine candidate were studied. In particular, we performed a comprehensive cross-sectional and longitudinal analysis to characterize the function, the phenotype and the functional avidity of HIV-specific CD8 Τ cells during acute (PHI) and chronic infection and, in particular, we investigated immunological parameters potentially associated with the functional avidity of HIV-specific CD8 Τ cells. In addition, we studied the expression pattern of co-inhibitory molecules and the influence of CD 160 on the functions of CD8 Τ cells in absence of chronic infections. From these analyses we observed that the functional avidity of HIV-specific CD8 T- cell responses was significantly lower in acute than in chronic infection, but was not different between chronic progressive and non-progressive patients. Functional avidity remained low after several years of antiretroviral therapy in PHI patients, but increased in patients experiencing a virus rebound following treatment interruption in association with a massive renewal of the global CD8 complementarity-determining region 3 of the TCR. The functional avidity was also directly associated to T-cell exhaustion. In individuals with no sign of HIV or Hepatitis A, Β or C virus infection, CD8 Τ cells expressed higher levels of co-inhibitory molecules than CD4 Τ cells and this was dependent on the stage of T-cell differentiation and activation. The expression of CD 160 impaired the proliferation capacity and IL-2 production of CD8 Τ cells and was reduced upon CD8 T-cell activation, entitling CD 160 as unique marker of CD8 T-cell exhaustion. The CD 160 blockade restored the proliferation capacity of virus-specific CD8 Τ cells providing a potential new target for immunotherapy. All together, these results expand our knowledge regarding the interplay between the immune system and the viruses. - De nombreuses études chez l'Homme ont mis en évidence la contribution des réponses cellulaires Τ CD4 et CD8 dans le contrôle des infections virales et bactériennes. En particulier, les lymphocytes Τ ont différentes fonctions effectrices spécifiques qui leur confèrent un rôle clé lors d'infections par différents pathogènes. Ce travail vise à étudier différentes caractéristiques des cellules Τ CD8 affectant l'efficacité des réponses cellulaires contre les virus. Pour atteindre cet objectif nous avons étudié les cellules Τ CD8 provenant de patients infectés par le VIH et de donneurs sains avec des réponses immunitaires naturelles ou vaccinales contre des virus. Nous avons effectué plusieurs analyses transversales et longitudinales des fonctions, du phénotype et de l'avidité fonctionnelle des lymphocytes Τ CD8 spécifiques au VIH au cours d'infections aiguës et chroniques; en particulier, nous avons étudié les paramètres immunologiques qui pourraient être associés à l'avidité fonctionnelle. De plus, nous avons investigué le profil d'expression des principales molécules co-inhibitrices et en particulier le rôle du CD 160 dans les fonctions des lymphocytes Τ CD8. Sur la base de ces analyses, nous avons constaté que l'avidité fonctionnelle des cellules Τ CD8 spécifiques au VIH était significativement plus faible lors infections aiguës que lors d'infections chroniques, mais n'était, par contre, pas différente entre les patients avec des infections chroniques progressives et non progressives. L'avidité fonctionnelle reste faible après plusieurs années de traitement antirétroviral, mais augmente chez les patients subissant un rebond viral, et donc exposés à des hautes virémies, suite à l'interruption du traitement. Cette augmentation d'avidité des lymphocytes Τ CD8, liée à un épuisement fonctionnel accru, était quantitativement directement associée à un renouvellement massif du TCR. Indépendamment de l'infection par le VIH, les cellules Τ CD8 expriment des niveaux plus élevés de molécules co-inhibitrices (PD-1, 2B4 et CD 160) par rapport aux cellules Τ CD4 et ceci dépend de leur stade de différenciation et d'activation. En particulier, CD 160 semble être un marqueur clé d'épuisement cellulaire des cellules Τ CD8, et donc une nouvelle cible potentielle pour l'immunothérapie, car a) son expression réduit la capacité proliférative et la production d'IL-2 b) CD 160 diminue suite à 1'activation et c) le blocage de CD 160 redonne la capacité proliférative aux cellules Τ CD8 spécifiques aux virus. - Le système immunitaire est un ensemble de cellules, tissus et organes indispensables pour limiter l'entrée des pathogènes à travers la peau et les muqueuses. Parmi les différentes cellules composant le système immunitaire, les cellules Τ CD4 et CD8 sont fondamentales pour le contrôle des infections virales et bactériennes. Les moyens pour combattre les différents pathogènes peuvent être cependant très variables. Les cellules Τ CD8, qui sont indispensables pour la lutte contre les virus, peuvent avoir différents niveaux de sensibilité; les cellules qui répondent à de faibles quantités d'antigène ont une forte sensibilité. Suite à une première infection virale, les cellules Τ CD8 ont une sensibilité plus faible que lors d'expositions répétées au même virus. En effet, la réexposition au pathogène induit une augmentation de sensibilité, grâce au recrutement et/ou à l'expansion de cellules Τ dotées d'une sensibilité plus élevée. Les cellules Τ CD8 avec une plus haute sensibilité semblent être caractérisées par une perte de fonctionnalité (épuisement fonctionnel associé à une haute expression de molécules dites inhibitrices). En absence d'infection, la fonction des molécules inhibitrices n'est pas encore clairement définie. Les cellules Τ CD8 montrent un niveau d'expression plus élevé de ces molécules par rapport aux cellules Τ CD4. Ceci dépend de l'état des cellules. Parmi ces molécules, le CD160 est associé à l'incapacité des cellules à proliférer et à produire de l'IL-2, une protéine importante pour la prolifération et la survie cellulaire. L'incapacité des cellules exprimant le CD 160 à proliférer en réponse à des virus peut être restaurée par le blocage fonctionnel du récepteur CD 160. Cette étude étoffe notre connaissance du rôle des cellules Τ CD8 ainsi que des conséquences induites par leur épuisement fonctionnel. Ces informations sont fondamentales pour le développement de nouvelles stratégies thérapeutiques et vaccinales.

Improving the prediction of plant species distribution and community composition by adding edaphic to topo-climatic variables

Questions Soil properties have been widely shown to influence plant growth and distribution. However, the degree to which edaphic variables can improve models based on topo-climatic variables is still unclear. In this study, we tested the roles of seven edaphic variables, namely (1) pH; (2) the content of nitrogen and of (3) phosphorus; (4) silt; (5) sand; (6) clay and (7) carbon-to-nitrogen ratio, as predictors of species distribution models in an edaphically heterogeneous landscape. We also tested how the respective influence of these variables in the models is linked to different ecological and functional species characteristics. Location The Western Alps, Switzerland. Methods With four different modelling techniques, we built models for 115 plant species using topo-climatic variables alone and then topo-climatic variables plus each of the seven edaphic variables, one at a time. We evaluated the contribution of each edaphic variable by assessing the change in predictive power of the model. In a second step, we evaluated the importance of the two edaphic variables that yielded the largest increase in predictive power in one final set of models for each species. Third, we explored the change in predictive power and the importance of variables across plant functional groups. Finally, we assessed the influence of the edaphic predictors on the prediction of community composition by stacking the models for all species and comparing the predicted communities with the observed community. Results Among the set of edaphic variables studied, pH and nitrogen content showed the highest contributions to improvement of the predictive power of the models, as well as the predictions of community composition. When considering all topo-climatic and edaphic variables together, pH was the second most important variable after degree-days. The changes in model results caused by edaphic predictors were dependent on species characteristics. The predictions for the species that have a low specific leaf area, and acidophilic preferences, tolerating low soil pH and high humus content, showed the largest improvement by the addition of pH and nitrogen in the model. Conclusions pH was an important predictor variable for explaining species distribution and community composition of the mountain plants considered in our study. pH allowed more precise predictions for acidophilic species. This variable should not be neglected in the construction of species distribution models in areas with contrasting edaphic conditions.

Submillimeter three-dimensional coronary MR angiography with real-time navigator correction: comparison of navigator locations.

Three-dimensional free-breathing coronary magnetic resonance angiography was performed in eight healthy volunteers with use of real-time navigator technology. Images acquired with the navigator localized at the right hemidiaphragm and at the left ventricle were objectively compared. The diaphragmatic navigator was found to be superior for vessel delineation of middle to distal portions of the coronary arteries.

Multitask learning of environmental spatial data

The present research deals with an application of artificial neural networks for multitask learning from spatial environmental data. The real case study (sediments contamination of Geneva Lake) consists of 8 pollutants. There are different relationships between these variables, from linear correlations to strong nonlinear dependencies. The main idea is to construct a subsets of pollutants which can be efficiently modeled together within the multitask framework. The proposed two-step approach is based on: 1) the criterion of nonlinear predictability of each variable ?k? by analyzing all possible models composed from the rest of the variables by using a General Regression Neural Network (GRNN) as a model; 2) a multitask learning of the best model using multilayer perceptron and spatial predictions. The results of the study are analyzed using both machine learning and geostatistical tools.

Class of correlated random networks with hidden variables

We study a class of models of correlated random networks in which vertices are characterized by hidden variables controlling the establishment of edges between pairs of vertices. We find analytical expressions for the main topological properties of these models as a function of the distribution of hidden variables and the probability of connecting vertices. The expressions obtained are checked by means of numerical simulations in a particular example. The general model is extended to describe a practical algorithm to generate random networks with an a priori specified correlation structure. We also present an extension of the class, to map nonequilibrium growing networks to networks with hidden variables that represent the time at which each vertex was introduced in the system.

Annual Report Of the State Geologist, March 2012

What we do: Since 1892, the Iowa Geological and Water Survey (IGWS) has provided earth, water, and mapping science to all Iowans. We collect and interpret information on subsurface geologic conditions, groundwater and surface water quantity and quality, and the natural and built features of our landscape. This information is critical for: Predicting the future availability of economic water supplies and mineral resources. Assuring proper function of waste disposal facilities. Delineation of geologic hazards that may jeopardize property and public safety. Assessing trends and providing protection of water quality and soil resources. Applied technical assistance for economic development and environmental stewardship. Our goal: Providing the tools for good decision making to assure the long-term vitality of Iowa’s communities, businesses, and quality of life. Information and technical assistance are provided through web-based databases, comprehensive Geographic Information System (GIS) tools, predictive groundwater models, and watershed assessments and improvement grants. The key service we provide is direct assistance from our technical staff, working with Iowans to overcome real-world challenges. This report describes the basic functions of IGWS program areas and highlights major activities and accomplishments during calendar year 2011. More information on IGWS is available at http://www.igsb.uiowa.edu/.

15-OR: Multi-phase postmortem CT angiography of pulmonary embolism: technique-related artefacts or real findings?

Multi-phase postmortem CT angiography (MPMCTA) is recognized as a valuable tool to explore the vascular system, with higher sensitivity than conventional autopsy. However, a limitation is the impossibility to diagnose pulmonary embolism (PE) due to post-mortem blood clots situated in pulmonary arteries. The purpose of this study was to explore an eventual possibility to distinguish between real PE and artefacts mimicking PE. Our study included 416 medico-legal cases. All of them underwent MPMCTA, conventional autopsy and histological examination. We selected cases presenting arterial luminal filling defects in the pulmonary arteries. Their radiological interpretation was confronted to the one of autopsy and histological examination. We also investigated an eventual correlation between artefacts in pulmonary arteries and those in other parts of the vascular system. In 123 cases, filling defects of pulmonary arteries were described during MPMCTA. In 57 cases, this was interpreted as artefact and in 4 cases as suspected PE. In 62 cases only a differential diagnosis was made. Autopsy and histology could clearly identify the artefacts as such. Only one case of real PE was radiologically misinterpreted as artefact. In 6 of the 62 cases with no interpretation a PE was diagnosed. In 3 out of 4 suspected cases, PE was confirmed. We found out that filling defects in pulmonary arteries are nearly always associated to other vascular artefacts. Therefore, we suggest following some rules for radiological interpretation in order to allow a reliable diagnosis of pulmonary embolism after MPMCTA.

The effect of tax enforcement on tax elasticities: Evidence from charitable contributions in France

Optimal tax formulas expressed in "sufficient statistics" are usually calibrated under the assumptionthat the relevant tax elasticities are unaffected by other available policy instruments.In practice though, tax authorities have many more instruments than the mere tax rates andtax elasticities are functions of all these policy instruments. In this paper we provide evidencethat tax elasticities are extremely sensitive to a particular policy instrument: the level of taxenforcement. We exploit a natural experiment that took place in France in 1983, when the taxadministration tightened the requirements to claim charitable deductions. The reform led to asubstantial drop in the amount of contributions reported to the administration, which can becredibly attributed to overreporting of charitable contributions before the reform, rather thanto a real change in giving behaviours. We show that the reform was also associated with asubstantial decline in the absolute value of the elasticity of reported contributions. This findingallows us to partially identify the elasticity of overreporting contributions, which is shown tobe large and inferior to -2 in the lax enforcement regime. We further show using bunching oftaxpayers at kink-points of the tax schedule that the elasticity of taxable income also experienceda significant decline after the reform. Our results suggest that optimizing the tax rate fora given tax elasticity when other policy instruments are not optimized can lead to misleadingconclusions when tax authorities have another instrument that could set the tax elasticity itselfat its optimal level as in Kopczuk and Slemrod [2002].

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

Insight in the factors associated with the presence of protective antiviral T-cell response.

T cells play a primordial role in antiviral immunity. Virus-specific T-cell responses can be characterized by a number of independent variables. These include the magnitude of the response; the functional quality of the response, i.e. the types of cytokines secreted after stimulation and the proliferative or lytic potential; the tissue distribution of the T cells; the breadth of the response; and the avidity of the response. All of these together constitute the T-cell response to antigen (Ag) and comprise potential variables that may correlate with antiviral protective immunity. Substantial advances have recently been obtained in the characterization of virus-specific T-cell responses. These studies have shown that the quality (in term of functional profile) rather than the quantity of Ag-specific T cells was associated with protection. Recently, the term polyfunctional has been used to define T-cell responses that, in addition to typical effector functions such as secretion of IFN-g, TNF-a and MIP-1b and cytotoxic activity, comprise distinct T-cell populations, also able to secrete IL-2 and retaining Ag-specific proliferation capacity. The term \only effector" defines T-cell responses/ populations able to secrete cytokines such as IFN-g, TNF-a and MIP-1b and endowed with cytotoxic activity but lacking IL-2 and proliferation capacity. Several models of virus infections (HIV-1, cytomegalovirus [CMV], Epstein Barr virus [EBV], influenza [Flu] and Herpes Simplex virus) exclusively differentiated on the basis of Ag exposure and persistence, were investigated: 1) antigen clearance, 2) protracted Ag exposure and persistence and low Ag levels, 3) Ag persistence and high Ag levels, and 4) acute Ag exposure/re-exposure. These analyses have demonstrated that polyfunctional and not \only effector" T-cell responses were associated with protective antiviral immunity. However, the factors and mechanisms governing the generation of functionally distinct T-cell populations remain to be elucidated. Recently, several studies have shown a major influence of HLA genotype in the evolution of HIV and the progression of HIV-associated disease. In particular, certain HLA-B alleles were most closely associated with non-progressive disease and low viral load or disease and had a dominant involvement on the clinical course of HIV-associated diseases. In this study, we have investigated the relationship between HLA restriction and the functional profile of Tcell responses in order to determine whether HLA-B influenced the generation of polyfunctional CD8 T-cell responses. To be able to address this issue, we studied CD8 T-cell responses against HIV-1, CMV, EBV and Flu in 128 subjects. These analyses enabled us to demonstrate that HLA-Arestricted epitopes were mostly associated with \only effector" T-cell responses while, in contrast, polyfunctional CD8 T-cell responses were predominantly driven by virus epitopes restricted by HLA-B alleles. We then characterized eventual differences in the responsiveness of CD8 T-cell populations restricted by different HLA-A and HLA-B alleles. For this purpose, we investigated the T-cell receptor (TCR) avidity for the cognate epitope of polyfunctional and \only effector" CD8 T-cell populations. Our results indicated that overall virus-specific CD8 T-cell populations recognizing virus epitopes restricted by HLA-B alleles were equipped with lower avidity TCR for the cognate epitopes when compared to those recognizing epitopes restricted by HLA-A alleles. In conclusion, these results provide the rationale for the observed protective role of HLA-B genotypes in HIV-1- infection and new insights into the relationship between TCR avidity and functional profile of virus-specific CD8 Tcells.

Introduction of snow and geomorphic disturbance variables into predictive models of alpine plant distribution in the Western Swiss Alps

Indirect topographic variables have been used successfully as surrogates for disturbance processes in plant species distribution models (SDM) in mountain environments. However, no SDM studies have directly tested the performance of disturbance variables. In this study, we developed two disturbance variables: a geomorphic index (GEO) and an index of snow redistribution by wind (SNOW). These were developed in order to assess how they improved both the fit and predictive power of presenceabsence SDM based on commonly used topoclimatic (TC) variables for 91 plants in the Western Swiss Alps. The individual contribution of the disturbance variables was compared to TC variables. Maps of models were prepared to spatially test the effect of disturbance variables. On average, disturbance variables significantly improved the fit but not the predictive power of the TC models and their individual contribution was weak (5.6% for GEO and 3.3% for SNOW). However their maximum individual contribution was important (24.7% and 20.7%). Finally, maps including disturbance variables (i) were significantly divergent from TC models in terms of predicted suitable surfaces and connectivity between potential habitats, and (ii) were interpreted as more ecologically relevant. Disturbance variables did not improve the transferability of models at the local scale in a complex mountain system, and the performance and contribution of these variables were highly species-specific. However, improved spatial projections and change in connectivity are important issues when preparing projections under climate change because the future range size of the species will determine the sensitivity to changing conditions.

Impacts of climate change on Swiss biodiversity: An indicator taxa approach

We present a new indicator taxa approach to the prediction of climate change effects on biodiversity at the national level in Switzerland. As indicators, we select a set of the most widely distributed species that account for 95% of geographical variation in sampled species richness of birds, butterflies, and vascular plants. Species data come from a national program designed to monitor spatial and temporal trends in species richness. We examine some opportunities and limitations in using these data. We develop ecological niche models for the species as functions of both climate and land cover variables. We project these models to the future using climate predictions that correspond to two IPCC 3rd assessment scenarios for the development of 'greenhouse' gas emissions. We find that models that are calibrated with Swiss national monitoring data perform well in 10-fold cross-validation, but can fail to capture the hot-dry end of environmental gradients that constrain some species distributions. Models for indicator species in all three higher taxa predict that climate change will result in turnover in species composition even where there is little net change in predicted species richness. Indicator species from high elevations lose most areas of suitable climate even under the relatively mild B2 scenario. We project some areas to increase in the number of species for which climate conditions are suitable early in the current century, but these areas become less suitable for a majority of species by the end of the century. Selection of indicator species based on rank prevalence results in a set of models that predict observed species richness better than a similar set of species selected based on high rank of model AUC values. An indicator species approach based on selected species that are relatively common may facilitate the use of national monitoring data for predicting climate change effects on the distribution of biodiversity.

Deciphering the global organization of clustering in real complex networks

We uncover the global organization of clustering in real complex networks. To this end, we ask whether triangles in real networks organize as in maximally random graphs with given degree and clustering distributions, or as in maximally ordered graph models where triangles are forced into modules. The answer comes by way of exploring m-core landscapes, where the m-core is defined, akin to the k-core, as the maximal subgraph with edges participating in at least m triangles. This property defines a set of nested subgraphs that, contrarily to k-cores, is able to distinguish between hierarchical and modular architectures. We find that the clustering organization in real networks is neither completely random nor ordered although, surprisingly, it is more random than modular. This supports the idea that the structure of real networks may in fact be the outcome of self-organized processes based on local optimization rules, in contrast to global optimization principles.

Who is afraid of the big bad ban? An evaluation of the effects of the Spanish clean air law on expenditure at hospitality venues

Background:In January 2011 Spain modified clean air legislation in force since 2006, removing all existing exceptions applicable to hospitality venues. Although this legal reform was backed by all political parties with parliamentary representation, the government's initiative was contested by the tobacco industry and its allies in the hospitality industry. One of the most voiced arguments against the reform was its potentially disruptive effect on the revenue of hospitality venues. This paper evaluates the impact of this reform on household expenditure at restaurants and bars and cafeterias. Methods and empirical strategy:We use micro-data from the Encuesta de Presupuestos Familiares (EPF) for years 2006 to 2012 to estimate "two part" models where the probability of observing a positive expenditure and, for those who spend, the expected level of expenditure are functions of an array of explanatory variables. We apply a before-after analysis with a wide range of controls for confounding factors and a flexible modeling of time effects.Results:In line with the majority of studies that analyze the effects of smoking bans using objective data, our results suggest that the reform did not cause reductions in households' expenditures on restaurant services or on bars and cafeteria services.