Imputation in data fusion of heterogeneous data sets a model-based numerical experiment

Given the very large amount of data obtained everyday through population surveys, much of the new research again could use this information instead of collecting new samples. Unfortunately, relevant data are often disseminated into different files obtained through different sampling designs. Data fusion is a set of methods used to combine information from different sources into a single dataset. In this article, we are interested in a specific problem: the fusion of two data files, one of which being quite small. We propose a model-based procedure combining a logistic regression with an Expectation-Maximization algorithm. Results show that despite the lack of data, this procedure can perform better than standard matching procedures.

An iterative Multiscale Finite-Volume algorithm converging to the exact solution

The multiscale finite volume (MsFV) method has been developed to efficiently solve large heterogeneous problems (elliptic or parabolic); it is usually employed for pressure equations and delivers conservative flux fields to be used in transport problems. The method essentially relies on the hypothesis that the (fine-scale) problem can be reasonably described by a set of local solutions coupled by a conservative global (coarse-scale) problem. In most cases, the boundary conditions assigned for the local problems are satisfactory and the approximate conservative fluxes provided by the method are accurate. In numerically challenging cases, however, a more accurate localization is required to obtain a good approximation of the fine-scale solution. In this paper we develop a procedure to iteratively improve the boundary conditions of the local problems. The algorithm relies on the data structure of the MsFV method and employs a Krylov-subspace projection method to obtain an unconditionally stable scheme and accelerate convergence. Two variants are considered: in the first, only the MsFV operator is used; in the second, the MsFV operator is combined in a two-step method with an operator derived from the problem solved to construct the conservative flux field. The resulting iterative MsFV algorithms allow arbitrary reduction of the solution error without compromising the construction of a conservative flux field, which is guaranteed at any iteration. Since it converges to the exact solution, the method can be regarded as a linear solver. In this context, the schemes proposed here can be viewed as preconditioned versions of the Generalized Minimal Residual method (GMRES), with a very peculiar characteristic that the residual on the coarse grid is zero at any iteration (thus conservative fluxes can be obtained).

Modeling complex wells with the multi-scale finite-volume method

In this paper, an extension of the multi-scale finite-volume (MSFV) method is devised, which allows to Simulate flow and transport in reservoirs with complex well configurations. The new framework fits nicely into the data Structure of the original MSFV method,and has the important property that large patches covering the whole well are not required. For each well. an additional degree of freedom is introduced. While the treatment of pressure-constraint wells is trivial (the well-bore reference pressure is explicitly specified), additional equations have to be solved to obtain the unknown well-bore pressure of rate-constraint wells. Numerical Simulations of test cases with multiple complex wells demonstrate the ability of the new algorithm to capture the interference between the various wells and the reservoir accurately. (c) 2008 Elsevier Inc. All rights reserved.

Improved statistical evaluation of group differences in connectomes by screening-filtering strategy with application to study maturation of brain connections between childhood and adolescence.

Detecting local differences between groups of connectomes is a great challenge in neuroimaging, because the large number of tests that have to be performed and the impact on multiplicity correction. Any available information should be exploited to increase the power of detecting true between-group effects. We present an adaptive strategy that exploits the data structure and the prior information concerning positive dependence between nodes and connections, without relying on strong assumptions. As a first step, we decompose the brain network, i.e., the connectome, into subnetworks and we apply a screening at the subnetwork level. The subnetworks are defined either according to prior knowledge or by applying a data driven algorithm. Given the results of the screening step, a filtering is performed to seek real differences at the node/connection level. The proposed strategy could be used to strongly control either the family-wise error rate or the false discovery rate. We show by means of different simulations the benefit of the proposed strategy, and we present a real application of comparing connectomes of preschool children and adolescents.

Innate sensors for Gram-positive bacteria.

More than half of invasive bacterial infections are Gram-positive in origin. This class of bacteria has neither endotoxins nor an outer membrane, yet it generates some of the most powerful inflammatory responses known in medicine. Some recent seminal studies go a long way toward settling the controversies that surround the process by which Gram-positive bacterial surfaces trigger the human immune system. Although the components of the cell wall are now chemically defined in exquisite detail and the interaction with the toll-like receptor 2 pathway has been discovered, it is only very recently that definitive studies combining these advanced biochemical and cell biological tools have been carried out. It is these breakthrough studies that have finally confirmed the paradigm of innate sensors for Gram-positive bacteria.

Estimation of the correlation structure of crustal velocity heterogeneity from seismic reflection data

Numerous sources of evidence point to the fact that heterogeneity within the Earth's deep crystalline crust is complex and hence may be best described through stochastic rather than deterministic approaches. As seismic reflection imaging arguably offers the best means of sampling deep crustal rocks in situ, much interest has been expressed in using such data to characterize the stochastic nature of crustal heterogeneity. Previous work on this problem has shown that the spatial statistics of seismic reflection data are indeed related to those of the underlying heterogeneous seismic velocity distribution. As of yet, however, the nature of this relationship has remained elusive due to the fact that most of the work was either strictly empirical or based on incorrect methodological approaches. Here, we introduce a conceptual model, based on the assumption of weak scattering, that allows us to quantitatively link the second-order statistics of a 2-D seismic velocity distribution with those of the corresponding processed and depth-migrated seismic reflection image. We then perform a sensitivity study in order to investigate what information regarding the stochastic model parameters describing crustal velocity heterogeneity might potentially be recovered from the statistics of a seismic reflection image using this model. Finally, we present a Monte Carlo inversion strategy to estimate these parameters and we show examples of its application at two different source frequencies and using two different sets of prior information. Our results indicate that the inverse problem is inherently non-unique and that many different combinations of the vertical and lateral correlation lengths describing the velocity heterogeneity can yield seismic images with the same 2-D autocorrelation structure. The ratio of all of these possible combinations of vertical and lateral correlation lengths, however, remains roughly constant which indicates that, without additional prior information, the aspect ratio is the only parameter describing the stochastic seismic velocity structure that can be reliably recovered.

3-D density structure and geological evolution of Stromboli volcano (Aeolian Islands, Italy) inferred from land-based and sea-surface gravity data

We present the first density model of Stromboli volcano (Aeolian Islands, Italy) obtained by simultaneously inverting land-based (543) and sea-surface (327) relative gravity data. Modern positioning technology, a 1 x 1 m digital elevation model, and a 15 x 15 m bathymetric model made it possible to obtain a detailed 3-D density model through an iteratively reweighted smoothness-constrained least-squares inversion that explained the land-based gravity data to 0.09 mGal and the sea-surface data to 5 mGal. Our inverse formulation avoids introducing any assumptions about density magnitudes. At 125 m depth from the land surface, the inferred mean density of the island is 2380 kg m(-3), with corresponding 2.5 and 97.5 percentiles of 2200 and 2530 kg m-3. This density range covers the rock densities of new and previously published samples of Paleostromboli I, Vancori, Neostromboli and San Bartolo lava flows. High-density anomalies in the central and southern part of the island can be related to two main degassing faults crossing the island (N41 and NM) that are interpreted as preferential regions of dyke intrusions. In addition, two low-density anomalies are found in the northeastern part and in the summit area of the island. These anomalies seem to be geographically related with past paroxysmal explosive phreato-magmatic events that have played important roles in the evolution of Stromboli Island by forming the Scari caldera and the Neostromboli crater, respectively. (C) 2014 Elsevier B.V. All rights reserved.

Structure du temps de travail des infirmières de santé publique: effets de l'âge des patients, de la nature des prestations fournies et du lieu du contact. [Structure of work times of public health nurses: effect of the age of patients, nature of care given and location of contact].

In the framework of health services research sponsored by the Swiss National Science Foundation, a research was undertaken of the activity of the large majority of the public health nurses working in the Swiss cantons of Vaud and Fribourg (total population 700,000). During one week, 130 nurses gathered, with a specially devised instrument, data on 4165 patient visits. Studying the duration of the contacts, one has distinguished contact duration per se (DC), duration of the travel time preceding the contact (DD), and total duration in relation with the contact (DTC-addition of the first two). It was noted that the three durations increased significantly with patient age (as regard travel time, this is explained by the higher proportion of home visits in higher age groups, as compared with visits at a health center). Examined according to location of the visit, contact duration per se (without travel) is higher for visits at home and in nursing homes than for those taking place at a health center. Looked at in respect to the care given (technical care, or basic nursing care, or both simultaneously), our data show that the provision of basic nursing care (alone or with technical care) doubles contact duration (from 20 to 42-45'). The analyses according to patient age shows that, at an advanced age (beyond 80 years particularly), there is an important increase of the visits where both types of care are given. However, contact duration per se shows a significant raise with age only for the group "technical care only"; it can be demonstrated that this is due to the fact that older patients require more complex technical acts (e.g., bladder care, as compared with simpler acts such as injection). A model of the relationships between patient age and contact duration is proposed: it is because of the increase in the proportions of home visits, of visits including basic nursing care, and of more complex technical acts that older persons require more of the working time of public health nurses.

Bacterial community structure of a pesticide-contaminated site and assessment of changes induced in community structure during bioremediation.

The introduction of culture-independent molecular screening techniques, especially based on 16S rRNA gene sequences, has allowed microbiologists to examine a facet of microbial diversity not necessarily reflected by the results of culturing studies. The bacterial community structure was studied for a pesticide-contaminated site that was subsequently remediated using an efficient degradative strain Arthrobacter protophormiae RKJ100. The efficiency of the bioremediation process was assessed by monitoring the depletion of the pollutant, and the effect of addition of an exogenous strain on the existing soil community structure was determined using molecular techniques. The 16S rRNA gene pool amplified from the soil metagenome was cloned and restriction fragment length polymorphism studies revealed 46 different phylotypes on the basis of similar banding patterns. Sequencing of representative clones of each phylotype showed that the community structure of the pesticide-contaminated soil was mainly constituted by Proteobacteria and Actinomycetes. Terminal restriction fragment length polymorphism analysis showed only nonsignificant changes in community structure during the process of bioremediation. Immobilized cells of strain RKJ100 enhanced pollutant degradation but seemed to have no detectable effects on the existing bacterial community structure.

Delinquency in male adolescents: the role of alexithymia and family structure

The purpose of this study was to examine the linkages between alexithymia and delinquency in male adolescents (age ranging from 14 to 18 years), and to investigate whether alexithymia was a good discriminatory factor for juvenile delinquency. Thirty-six offender adolescents and 46 non-offender control adolescents participated in the study and completed the 20-item Toronto Alexithymia Scale (TAS-20) (alexithymia), the Revised Children's Manifest Anxiety Scale (R-CMAS) (anxiety), the Liste d'Adjectifs Bipolaires et en Echelles de Likert (LABEL) (personality-Big Five) and demographic data. Findings revealed that the adolescents of the offender group scored high on alexithymia and that proportion of disrupted family structure in the offender group is higher than in the control group. Logistic regressions confirmed that alexithymia and family structure are the strongest discriminatory factors for juvenile delinquency. Limitations and clinical implications are discussed, and recommendations for future research are provided

A collaborative approach for incorporating forensic case data into crime investigation using criminal intelligence analysis and visualisation

There is an increasing awareness that the articulation of forensic science and criminal investigation is critical to the resolution of crimes. However, models and methods to support an effective collaboration between these partners are still poorly expressed or even lacking. Three propositions are borrowed from crime intelligence methods in order to bridge this gap: (a) the general intelligence process, (b) the analyses of investigative problems along principal perspectives: entities and their relationships, time and space, quantitative aspects and (c) visualisation methods as a mode of expression of a problem in these dimensions. Indeed, in a collaborative framework, different kinds of visualisations integrating forensic case data can play a central role for supporting decisions. Among them, link-charts are scrutinised for their abilities to structure and ease the analysis of a case by describing how relevant entities are connected. However, designing an informative chart that does not bias the reasoning process is not straightforward. Using visualisation as a catalyser for a collaborative approach integrating forensic data thus calls for better specifications.

Cysteine 230 is essential for the structure and activity of the cytotoxic ligand TRAIL.

Unlike other tumor necrosis factor family members, the cytotoxic ligand tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)/Apo-2L contains an unpaired cysteine residue (Cys(230)) in its receptor-binding domain. Here we show that the biological activity of both soluble recombinant TRAIL and cell-associated, full-length TRAIL is critically dependent on the presence of Cys(230). Mutation of Cys(230) to alanine or serine strongly affected its ability to kill target cells. Binding to its receptors was decreased by at least 200-fold, and the stability of its trimeric structure was reduced. In recombinant TRAIL, Cys(230) was found engaged either in interchain disulfide bridge formation, resulting in poorly active TRAIL, or in the chelation of one zinc atom per TRAIL trimer in the active, pro-apoptotic form of TRAIL.

Modelling the distribution of bats in relation to landscape structure in a temperate mountain environment

1. Landscape modification is often considered the principal cause of population decline in many bat species. Thus, schemes for bat conservation rely heavily on knowledge about species-landscape relationships. So far, however, few studies have quantified the possible influence of landscape structure on large-scale spatial patterns in bat communities. 2. This study presents quantitative models that use landscape structure to predict (i) spatial patterns in overall community composition and (ii) individual species' distributions through canonical correspondence analysis and generalized linear models, respectively. A geographical information system (GIS) was then used to draw up maps of (i) overall community patterns and (ii) distribution of potential species' habitats. These models relied on field data from the Swiss Jura mountains. 3. Fight descriptors of landscape structure accounted for 30% of the variation in bat community composition. For some species, more than 60% of the variance in distribution could be explained by landscape structure. Elevation, forest or woodland cover, lakes and suburbs, were the most frequent predictors. 4. This study shows that community composition in bats is related to landscape structure through species-specific relationships to resources. Due to their nocturnal activities and the difficulties of remote identification, a comprehensive bat census is rarely possible, and we suggest that predictive modelling of the type described here provides an indispensable conservation tool.

Catabolic ornithine carbamoyltransferase of Pseudomonas aeruginosa. Importance of the N-terminal region for dodecameric structure and homotropic carbamoylphosphate cooperativity.

Pseudomonas aeruginosa has an anabolic (ArgF) and a catabolic (ArcB) ornithine carbamoyltransferase (OTCase). Despite extensive sequence similarities, these enzymes function unidirectionally in vivo. In the dodecameric catabolic OTCase, homotropic cooperativity for carbamoylphosphate strongly depresses the anabolic reaction; the residue Glu1O5 and the C-terminus are known to be essential for this cooperativity. When Glu1O5 and nine C-terminal amino acids of the catabolic OTCase were introduced, by in vitro genetic manipulation, into the closely related, trimeric, anabolic (ArgF) OTCase of Escherichia coli, the enzyme displayed Michaelis-Menten kinetics and no cooperativity was observed. This indicates that additional amino acid residues are required to produce homotropic cooperativity and a dodecameric assembly. To localize these residues, we constructed several hybrid enzymes by fusing, in vivo or in vitro, the E. coli argF gene to the P. aeruginosa arcB gene. A hybrid enzyme consisting of 101 N-terminal ArgF amino acids fused to 233 C-terminal ArcB residues and the reciprocal ArcB-ArgF hybrid were both trimers with little or no cooperativity. Replacing the seven N-terminal residues of the ArcB enzyme by the corresponding six residues of E. coli ArgF enzyme produced a dodecameric enzyme which showed a reduced affinity for carbamoylphosphate and an increase in homotropic cooperativity. Thus, the N-terminal amino acids of catabolic OTCase are important for interaction with carbamoylphosphate, but do not alone determine dodecameric assembly. Hybrid enzymes consisting of either 26 or 42 N-terminal ArgF amino acids and the corresponding C-terminal ArcB residues were both trimeric, yet they retained some homotropic cooperativity. Within the N-terminal ArcB region, a replacement of motif 28-33 by the corresponding ArgF segment destabilized the dodecameric structure and the enzyme existed in trimeric and dodecameric states, indicating that this region is important for dodecameric assembly. These findings were interpreted in the light of the three-dimensional structure of catabolic OTCase, which allows predictions about trimer-trimer interactions. Dodecameric assembly appears to require at least three regions: the N- and C-termini (which are close to each other in a monomer), residues 28-33 and residues 147-154. Dodecameric structure correlates with high carbamoylphosphate cooperativity and thermal stability, but some trimeric hybrid enzymes retain cooperativity, and the dodecameric Glu1O5-->Ala mutant gives hyperbolic carbamoylphosphate saturation, indicating that dodecameric structure is neither necessary nor sufficient to ensure cooperativity.