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.

Genetic variation in the Cytbgene of human cerebral Taenia soliumcysticerci recovered from clinically and radiologically heterogeneous patients with neurocysticercosis

Neurocysticercosis (NC) is a clinically and radiologically heterogeneous parasitic disease caused by the establishment of larval Taenia solium in the human central nervous system. Host and/or parasite variations may be related to this observed heterogeneity. Genetic differences between pig and human-derived T. solium cysticerci have been reported previously. In this study, 28 cysticerci were surgically removed from 12 human NC patients, the mitochondrial gene that encodes cytochrome b was amplified from the cysticerci and genetic variations that may be related to NC heterogeneity were characterised. Nine different haplotypes (Ht), which were clustered in four haplogroups (Hg), were identified. Hg 3 and 4 exhibited a tendency to associate with age and gender, respectively. However, no significant associations were found between NC heterogeneity and the different T. solium cysticerci Ht or Hg. Parasite variants obtained from patients with similar NC clinical or radiological features were genetically closer than those found in groups of patients with a different NC profile when using the Mantel test. Overall, this study establishes the presence of genetic differences in the Cytb gene of T. solium isolated from human cysticerci and suggests that parasite variation could contribute to NC heterogeneity.

LMM: an OWL-DL metamodel to represent heterogeneous lexical knowledge

In this paper we present a Linguistic Meta-Model (LMM) allowing a semiotic-cognitive representation of knowledge. LMM is freely available and integrates the schemata of linguistic knowledge resources, such as WordNet and FrameNet, as well as foundational ontologies, such as DOLCE and its extensions. In addition, LMM is able to deal with multilinguality and to represent individuals and facts in an open domain perspective.

Parenteral is more efficient than mucosal immunization to induce regression of human papillomavirus-associated genital tumors.

Cervical cancer is a public health concern as it represents the second cause of cancer death in women worldwide. High-risk human papillomaviruses (HPV) are the etiologic agents, and HPV E6 and/or E7 oncogene-specific therapeutic vaccines are under development to treat HPV-related lesions in women. Whether the use of mucosal routes of immunization may be preferable for inducing cell-mediated immune responses able to eradicate genital tumors is still debated because of the uniqueness of the female genital mucosa (GM) and the limited experimentation. Here, we compared the protective activity resulting from immunization of mice via intranasal (i.n.), intravaginal (IVAG) or subcutaneous (s.c.) routes with an adjuvanted HPV type 16 E7 polypeptide vaccine. Our data show that s.c. and i.n. immunizations elicited similar frequencies and avidity of TetE71CD81 and E7-specific Interferon-gamma-secreting cells in the GM, whereas slightly lower immune responses were induced by IVAG immunization. In a novel orthotopic murine model, both s.c. and i.n. immunizations allowed for complete long-term protection against genital E7-expressing tumor challenge. However, only s.c. immunization induced complete regression of already established genital tumors. This suggests that the higher E7-specific systemic response observed after s.c. immunization may contribute to the regression of growing genital tumors, whereas local immune responses may be sufficient to impede genital challenges. Thus, our data show that for an efficiently adjuvanted protein-based vaccine, parenteral vaccination route is superior to mucosal vaccination route for inducing regression of established genital tumors in a murine model of HPV-associated genital cancer.

Clinical and Virological Efficacy of Etravirine Plus Two Active Nucleos(t)ide Analogs in an Heterogeneous HIV-Infected Population.

Etravirine (ETV) is recommended in combination with a boosted protease inhibitor plus an optimized background regimen for salvage therapy, but there is limited experience with its use in combination with two nucleos(t)ide reverse-transcriptase inhibitors (NRTIs). This multicenter study aimed to assess the efficacy of this combination in two scenarios: group A) subjects without virologic failure on or no experience with non-nucleoside reverse-transcriptase inhibitors (NNRTIs) switched due to adverse events and group B) subjects switched after a virologic failure on an efavirenz- or nevirapine-based regimen. The primary endpoint was efficacy at 52 weeks analysed by intention-to-treat. Virologic failure was defined as the inability to suppress plasma HIV-RNA to <50 copies/mL after 24 weeks on treatment, or a confirmed viral load >200 copies/mL in patients who had previously achieved a viral suppression or had an undetectable viral load at inclusion. Two hundred eighty seven patients were included. Treatment efficacy rates in group A and B were 88.0% (CI95, 83.9-92.1%) and 77.4% (CI95, 65.0-89.7%), respectively; the rates reached 97.2% (CI95, 95.1-99.3%) and 90.5% (CI95, 81.7-99.3), by on-treatment analysis. The once-a-day ETV treatment was as effective as the twice daily dosing regimen. Grade 1-2 adverse events were observed motivating a treatment switch in 4.2% of the subjects. In conclusion, ETV (once- or twice daily) plus two analogs is a suitable, well-tolerated combination both as a switching strategy and after failure with first generation NNRTIs, ensuring full drug activity. TRIAL REGISTRATION ClinicalTrials.gov NCT01437241.

Heterogeneous metabolic adaptation of C57BL/6J mice to high-fat diet.

C57BL/6J mice were fed a high-fat, carbohydrate-free diet (HFD) for 9 mo. Approximately 50% of the mice became obese and diabetic (ObD), approximately 10% lean and diabetic (LD), approximately 10% lean and nondiabetic (LnD), and approximately 30% displayed intermediate phenotype. All of the HFD mice were insulin resistant. In the fasted state, whole body glucose clearance was reduced in ObD mice, unchanged in the LD mice, and increased in the LnD mice compared with the normal-chow mice. Because fasted ObD mice were hyperinsulinemic and the lean mice slightly insulinopenic, there was no correlation between insulin levels and increased glucose utilization. In vivo, tissue glucose uptake assessed by 2-[(14)C]deoxyglucose accumulation was reduced in most muscles in the ObD mice but increased in the LnD mice compared with the values of the control mice. In the LD mice, the glucose uptake rates were reduced in extensor digitorum longus (EDL) and total hindlimb but increased in soleus, diaphragm, and heart. When assessed in vitro, glucose utilization rates in the absence and presence of insulin were similar in diaphragm, soleus, and EDL muscles isolated from all groups of mice. Thus, in genetically homogenous mice, HFD feeding lead to different metabolic adaptations. Whereas all of the mice became insulin resistant, this was associated, in obese mice, with decreased glucose clearance and hyperinsulinemia and, in lean mice, with increased glucose clearance in the presence of mild insulinopenia. Therefore, increased glucose clearance in lean mice could not be explained by increased insulin level, indicating that other in vivo mechanisms are triggered to control muscle glucose utilization. These adaptive mechanisms could participate in the protection against development of obesity.

Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

An alternative method for dating unknown tephras based on a segmented regression model

In CoDaWork’05, we presented an application of discriminant function analysis (DFA) to 4 differentcompositional datasets and modelled the first canonical variable using a segmented regression modelsolely based on an observation about the scatter plots. In this paper, multiple linear regressions areapplied to different datasets to confirm the validity of our proposed model. In addition to dating theunknown tephras by calibration as discussed previously, another method of mapping the unknown tephrasinto samples of the reference set or missing samples in between consecutive reference samples isproposed. The application of these methodologies is demonstrated with both simulated and real datasets.This new proposed methodology provides an alternative, more acceptable approach for geologists as theirfocus is on mapping the unknown tephra with relevant eruptive events rather than estimating the age ofunknown tephra.Kew words: Tephrochronology; Segmented regression

Regression of cardiac growth in kidney transplant recipients using anti-m-TOR drugs plus RAS blockers: a controlled longitudinal study.

BACKGROUND Left ventricular hypertrophy (LVH) is common in kidney transplant (KT) recipients. LVH is associated with a worse outcome, though m-TOR therapy may help to revert this complication. We therefore conducted a longitudinal study to assess morphological and functional echocardiographic changes after conversion from CNI to m-TOR inhibitor drugs in nondiabetic KT patients who had previously received RAS blockers during the follow-up. METHODS We undertook a 1-year nonrandomized controlled study in 30 non-diabetic KT patients who were converted from calcineurin inhibitor (CNI) to m-TOR therapy. A control group received immunosuppressive therapy based on CNIs. Two echocardiograms were done during the follow-up. RESULTS Nineteen patients were switched to SRL and 11 to EVL. The m-TOR group showed a significant reduction in LVMi after 1 year (from 62 ± 22 to 55 ± 20 g/m2.7; P=0.003, paired t-test). A higher proportion of patients showing LVMi reduction was observed in the m-TOR group (53.3 versus 29.3%, P=0.048) at the study end. In addition, only 56% of the m-TOR patients had LVH at the study end compared to 77% of the control group (P=0.047). A significant change from baseline in deceleration time in early diastole was observed in the m-TOR group compared with the control group (P=0.019). CONCLUSIONS Switching from CNI to m-TOR therapy in non-diabetic KT patients may regress LVH, independently of blood pressure changes and follow-up time. This suggests a direct non-hemodynamic effect of m-TOR drugs on cardiac mass.

Analysis and Monte Carlo simulations of a model for the spread of infectious diseases in heterogeneous metapopulations

We present a study of the continuous-time equations governing the dynamics of a susceptible infected-susceptible model on heterogeneous metapopulations. These equations have been recently proposed as an alternative formulation for the spread of infectious diseases in metapopulations in a continuous-time framework. Individual-based Monte Carlo simulations of epidemic spread in uncorrelated networks are also performed revealing a good agreement with analytical predictions under the assumption of simultaneous transmission or recovery and migration processes

Continuous-time formulation of reaction-diffusion processes on heterogeneous metapopulations

We present the derivation of the continuous-time equations governing the limit dynamics of discrete-time reaction-diffusion processes defined on heterogeneous metapopulations. We show that, when a rigorous time limit is performed, the lack of an epidemic threshold in the spread of infections is not limited to metapopulations with a scale-free architecture, as it has been predicted from dynamical equations in which reaction and diffusion occur sequentially in time

Speed of reaction-diffusion fronts in spatially heterogeneous media

The front speed problem for nonuniform reaction rate and diffusion coefficient is studied by using singular perturbation analysis, the geometric approach of Hamilton-Jacobi dynamics, and the local speed approach. Exact and perturbed expressions for the front speed are obtained in the limit of large times. For linear and fractal heterogeneities, the analytic results have been compared with numerical results exhibiting a good agreement. Finally we reach a general expression for the speed of the front in the case of smooth and weak heterogeneities

The building blocks of international ecological footprint inequality: a regression-based decomposition

This paper performs an empirical Decomposition of International Inequality in Ecological Footprint in order to quantify to what extent explanatory variables such as a country’s affluence, economic structure, demographic characteristics, climate and technology contributed to international differences in terms of natural resource consumption during the period 1993-2007. We use a Regression-Based Inequality Decomposition approach. As a result, the methodology extends qualitatively the results obtained in standard environmental impact regressions as it comprehends further social dimensions of the Sustainable Development concept, i.e. equity within generations. The results obtained point to prioritizing policies that take into account both future and present generations.