Geomodelling of a fluvial system with semi-supervised support vector regression

Fluvial deposits are a challenge for modelling flow in sub-surface reservoirs. Connectivity and continuity of permeable bodies have a major impact on fluid flow in porous media. Contemporary object-based and multipoint statistics methods face a problem of robust representation of connected structures. An alternative approach to model petrophysical properties is based on machine learning algorithm ? Support Vector Regression (SVR). Semi-supervised SVR is able to establish spatial connectivity taking into account the prior knowledge on natural similarities. SVR as a learning algorithm is robust to noise and captures dependencies from all available data. Semi-supervised SVR applied to a synthetic fluvial reservoir demonstrated robust results, which are well matched to the flow performance

Inaugural adress: The concept of biostratigraphy: the view point of a stratigrapher

Colleagues, Ladies and Gentlemen. My presence here is due to accidental circumstances and I must confess that I feel a little embarassed by the fact Both your scientific quality and the worlwide acceptance of the results achieved by you in your research fields make me prudent and, to a certain extent, cautious.

Instructions pour aides-opérateurs des laboratoires de surveillance bactériologique des eaux au point de vue des cultures et recherches quantitatives de bactéries et bacilles coli. [Lettres de MM. Charles Todd et Danysz.]

Comprend : Lettre

A joint back calculation model for the imputation of the date of HIV infection in a prevalent cohort.

In studies of the natural history of HIV-1 infection, the time scale of primary interest is the time since infection. Unfortunately, this time is very often unknown for HIV infection and using the follow-up time instead of the time since infection is likely to provide biased results because of onset confounding. Laboratory markers such as the CD4 T-cell count carry important information concerning disease progression and can be used to predict the unknown date of infection. Previous work on this topic has made use of only one CD4 measurement or based the imputation on incident patients only. However, because of considerable intrinsic variability in CD4 levels and because incident cases are different from prevalent cases, back calculation based on only one CD4 determination per person or on characteristics of the incident sub-cohort may provide unreliable results. Therefore, we propose a methodology based on the repeated individual CD4 T-cells marker measurements that use both incident and prevalent cases to impute the unknown date of infection. Our approach uses joint modelling of the time since infection, the CD4 time path and the drop-out process. This methodology has been applied to estimate the CD4 slope and impute the unknown date of infection in HIV patients from the Swiss HIV Cohort Study. A procedure based on the comparison of different slope estimates is proposed to assess the goodness of fit of the imputation. Results of simulation studies indicated that the imputation procedure worked well, despite the intrinsic high volatility of the CD4 marker.

Genetic association tests: a method for the joint analysis of family and case-control data.

With the trend in molecular epidemiology towards both genome-wide association studies and complex modelling, the need for large sample sizes to detect small effects and to allow for the estimation of many parameters within a model continues to increase. Unfortunately, most methods of association analysis have been restricted to either a family-based or a case-control design, resulting in the lack of synthesis of data from multiple studies. Transmission disequilibrium-type methods for detecting linkage disequilibrium from family data were developed as an effective way of preventing the detection of association due to population stratification. Because these methods condition on parental genotype, however, they have precluded the joint analysis of family and case-control data, although methods for case-control data may not protect against population stratification and do not allow for familial correlations. We present here an extension of a family-based association analysis method for continuous traits that will simultaneously test for, and if necessary control for, population stratification. We further extend this method to analyse binary traits (and therefore family and case-control data together) and accurately to estimate genetic effects in the population, even when using an ascertained family sample. Finally, we present the power of this binary extension for both family-only and joint family and case-control data, and demonstrate the accuracy of the association parameter and variance components in an ascertained family sample.

Selecting statistical models to study the relationship between soybean yield and soil physical properties

Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

Characteristics and outcome of 27 elbow periprosthetic joint infections: results from a 14-year cohort study of 358 elbow prostheses.

Elbow arthroplasty is increasingly performed in patients with rheumatic and post-traumatic arthritis. Data on elbow periprosthetic joint infection (PJI) are limited. We investigated the characteristics and outcome of elbow PJI in a 14-year cohort of total elbow arthroplasties in a single centre. Elbow prosthesis, which were implanted between 1994 and 2007 at Schulthess Clinic in Zurich, were retrospectively screened for infection. PJI was defined as periprosthetic purulence, the presence of sinus tract or microbial growth. A Kaplan-Meier survival method and Cox proportional hazard analysis were performed. Of 358 elbow prostheses, PJI was identified in 27 (7.5%). The median patient age (range) was 61 (39-82) years; 63% were females. Seventeen patients (63%) had a rheumatic disorder and ten (37%) had osteoarthritis. Debridement and implant retention was performed in 78%, followed by exchange or removal of the prosthesis (15%) or no surgery (7%).The relapse-free survival (95% CI) was 79% (63-95%) after 1 year and 65% (45-85%) after 2 years. The outcome after 2 years was significantly better when patients were treated according to the algorithm compared to patients who were not (100% vs. 33%, p <0.05). In 21 patients treated with debridement and retention, the cure rate was also higher when the algorithm was followed (100% vs. 11%, p <0.05). The findings of the present study suggest that the treatment algorithm developed for hip and knee PJI can be applied to elbow PJI. With proper patient selection and antimicrobial therapy, debridement and retention of the elbow prosthesis is associated with good treatment outcome.

Comment on "Reappraisal of experimental values of third-order elastic constants of some cubic semiconductors and metals"

In a recent paper A. S. Johal and D. J. Dunstan [Phys. Rev. B 73, 024106 (2006)] have applied multivariate linear regression analysis to the published data of the change in ultrasonic velocity with applied stress. The aim is to obtain the best estimates for the third-order elastic constants in cubic materials. From such an analysis they conclude that uniaxial stress data on metals turns out to be nearly useless by itself. The purpose of this comment is to point out that by a proper analysis of uniaxial stress data it is possible to obtain reliable values of third-order elastic constants in cubic metals and alloys. Cu-based shape memory alloys are used as an illustrative example.

Modelling non-industrial private forest landowners' strategic decision making by using logistic regression and neural networks: case of predicting the choice of forest taxation basis

Summary

Interim Guide for Optimum Joint Performance of Concrete Pavements, September 2011

The purpose of this guide is to help practitioners understand how to optimize concrete pavement joint performance through the identification, mitigation, and prevention of joint deterioration. It summarizes current knowledge from research and practice to help practitioners access the latest knowledge and implement proven techniques. Emphasizing that water is the common factor in most premature joint deterioration, this guide describes various types of joint deterioration that can occur. Some distresses are caused by improper joint detailing or construction, and others can be attributed to inadequate materials or proportioning. D cracking is a form of joint distress that results from the use of poor-quality aggregates. A particular focus in this guide is joint distress due to freeze-thaw action. Numerous factors are at play in the occurrence of this distress, including the increased use of a variety of deicing chemicals and application strategies. Finally, this guide provides recommendations for minimizing the potential for joint deterioration, along with recommendations for mitigation practices to slow or stop the progress of joint deterioration.

Hysteresis and return-point memory in deterministic cellular automata

We have investigated hysteresis and the return-point memory (RPM) property in deterministic cellular automata with avalanche dynamics. The RPM property reflects a partial ordering of metastable states, preserved by the dynamics. Recently, Sethna et al. [Phys. Rev. Lett. 70, 3347 (1993)] proved this behavior for a homogeneously driven system with static disorder. This Letter shows that the partial ordering and the RPM can be displayed as well by systems driven heterogeneously, as a result of its own evolution dynamics. In particular, we prove the RPM property for a deterministic 2D sandpile automaton driven at a central site.