State-of-the-Art and Comparative Review of Adaptive Sampling Methods for Kriging

Metamodels aim to approximate characteristics of functions or systems from the knowledge extracted on only a finite number of samples. In recent years kriging has emerged as a widely applied metamodeling technique for resource-intensive computational experiments. However its prediction quality is highly dependent on the size and distribution of the given training points. Hence, in order to build proficient kriging models with as few samples as possible adaptive sampling strategies have gained considerable attention. These techniques aim to find pertinent points in an iterative manner based on information extracted from the current metamodel. A review of adaptive schemes for kriging proposed in the literature is presented in this article. The objective is to provide the reader with an overview of the main principles of adaptive techniques, and insightful details to pertinently employ available tools depending on the application at hand. In this context commonly applied strategies are compared with regards to their characteristics and approximation capabilities. In light of these experiments, it is found that the success of a scheme depends on the features of a specific problem and the goal of the analysis. In order to facilitate the entry into adaptive sampling a guide is provided. All experiments described herein are replicable using a provided open source toolbox. © 2020, The Author(s)

PI/PID controller stabilizing sets of uncertain nonlinear systems: an efficient surrogate model-based approach

Closed forms of stabilizing sets are generally only available for linearized systems. An innovative numerical strategy to estimate stabilizing sets of PI or PID controllers tackling (uncertain) nonlinear systems is proposed. The stability of the closed-loop system is characterized by the sign of the largest Lyapunov exponent (LLE). In this framework, the bottleneck is the computational cost associated with the solution of the system, particularly including uncertainties. To overcome this issue, an adaptive surrogate algorithm, the Monte Carlo intersite Voronoi (MiVor) scheme, is adopted to pertinently explore the domain of the controller parameters and classify it into stable/unstable regions from a low number of nonlinear estimations. The result of the random analysis is a stochastic set providing probability information regarding the capabilities of PI or PID controllers to stabilize the nonlinear system and the risk of instabilities. The minimum of the LLE is proposed as tuning rule of the controller parameters. It is expected that using a tuning rule like this results in PID controllers producing the highest closed-loop convergence rate, thus being robust against model parametric uncertainties and capable of avoiding large fluctuating behavior. The capabilities of the innovative approach are demonstrated by estimating robust stabilizing sets for the blood glucose regulation problem in type 1 diabetes patients

PI/PID controller stabilizing sets of uncertain nonlinear systems: an efficient surrogate model-based approach

AbstractClosed forms of stabilizing sets are generally only available for linearized systems. An innovative numerical strategy to estimate stabilizing sets of PI or PID controllers tackling (uncertain) nonlinear systems is proposed. The stability of the closed-loop system is characterized by the sign of the largest Lyapunov exponent (LLE). In this framework, the bottleneck is the computational cost associated with the solution of the system, particularly including uncertainties. To overcome this issue, an adaptive surrogate algorithm, the Monte Carlo intersite Voronoi (MiVor) scheme, is adopted to pertinently explore the domain of the controller parameters and classify it into stable/unstable regions from a low number of nonlinear estimations. The result of the random analysis is a stochastic set providing probability information regarding the capabilities of PI or PID controllers to stabilize the nonlinear system and the risk of instabilities. The minimum of the LLE is proposed as tuning rule of the controller parameters. It is expected that using a tuning rule like this results in PID controllers producing the highest closed-loop convergence rate, thus being robust against model parametric uncertainties and capable of avoiding large fluctuating behavior. The capabilities of the innovative approach are demonstrated by estimating robust stabilizing sets for the blood glucose regulation problem in type 1 diabetes patients

A collocation scheme for deep uncertainty treatment

Considering an uncertain correlation length of the input random fields described by a Karhunen-Loève expansion leads to a probability-box approach for the stochastic finite element computation. But, these computations are highly costly. Then, a stochastic collocation method using sparse grids within a Smolyak algorithm is proposed to reduce the computational cost, particularly in the context of non-linear computations. The interest and the development of the Smolyak algorithm for stochastic model with non-linear finite element methods regarding mixed, aleatory and epistemic, uncertain inputs are here introduced. The limitations of Smolyak algorithm are critically discussed and suggestions for improvement are made

Interleukin-2 therapy in patients with HIV infection

BACKGROUND Used in combination with antiretroviral therapy, subcutaneous recombinant interleukin-2 raises CD4+ cell counts more than does antiretroviral therapy alone. The clinical implication of these increases is not known. METHODS We conducted two trials: the Subcutaneous Recombinant, Human Interleukin-2 in HIV-Infected Patients with Low CD4+ Counts under Active Antiretroviral Therapy (SILCAAT) study and the Evaluation of Subcutaneous Proleukin in a Randomized International Trial (ESPRIT). In each, patients infected with the human immunodeficiency virus (HIV) who had CD4+ cell counts of either 50 to 299 per cubic millimeter (SILCAAT) or 300 or more per cubic millimeter (ESPRIT) were randomly assigned to receive interleukin-2 plus antiretroviral therapy or antiretroviral therapy alone. The interleukin-2 regimen consisted of cycles of 5 consecutive days each, administered at 8-week intervals. The SILCAAT study involved six cycles and a dose of 4.5 million IU of interleukin-2 twice daily; ESPRIT involved three cycles and a dose of 7.5 million IU twice daily. Additional cycles were recommended to maintain the CD4+ cell count above predefined target levels. The primary end point of both studies was opportunistic disease or death from any cause. RESULTS In the SILCAAT study, 1695 patients (849 receiving interleukin-2 plus antiretroviral therapy and 846 receiving antiretroviral therapy alone) who had a median CD4+ cell count of 202 cells per cubic millimeter were enrolled; in ESPRIT, 4111 patients (2071 receiving interleukin-2 plus antiretroviral therapy and 2040 receiving antiretroviral therapy alone) who had a median CD4+ cell count of 457 cells per cubic millimeter were enrolled. Over a median follow-up period of 7 to 8 years, the CD4+ cell count was higher in the interleukin-2 group than in the group receiving antiretroviral therapy alone--by 53 and 159 cells per cubic millimeter, on average, in the SILCAAT study and ESPRIT, respectively. Hazard ratios for opportunistic disease or death from any cause with interleukin-2 plus antiretroviral therapy (vs. antiretroviral therapy alone) were 0.91 (95% confidence interval [CI], 0.70 to 1.18; P=0.47) in the SILCAAT study and 0.94 (95% CI, 0.75 to 1.16; P=0.55) in ESPRIT. The hazard ratios for death from any cause and for grade 4 clinical events were 1.06 (P=0.73) and 1.10 (P=0.35), respectively, in the SILCAAT study and 0.90 (P=0.42) and 1.23 (P=0.003), respectively, in ESPRIT. CONCLUSIONS Despite a substantial and sustained increase in the CD4+ cell count, as compared with antiretroviral therapy alone, interleukin-2 plus antiretroviral therapy yielded no clinical benefit in either study. (ClinicalTrials.gov numbers, NCT00004978 [ESPRIT] and NCT00013611 [SILCAAT study].

Meta-analysis of the diagnostic performance of stress perfusion cardiovascular magnetic resonance for detection of coronary artery disease

<p>Abstract</p> <p>Aim</p> <p>Evaluation of the diagnostic accuracy of stress perfusion cardiovascular magnetic resonance for the diagnosis of significant obstructive coronary artery disease (CAD) through meta-analysis of the available data.</p> <p>Methodology</p> <p>Original articles in any language published before July 2009 were selected from available databases (MEDLINE, Cochrane Library and BioMedCentral) using the combined search terms of magnetic resonance, perfusion, and coronary angiography; with the exploded term coronary artery disease. Statistical analysis was only performed on studies that: (1) used a [greater than or equal to] 1.5 Tesla MR scanner; (2) employed invasive coronary angiography as the reference standard for diagnosing significant obstructive CAD, defined as a [greater than or equal to] 50% diameter stenosis; and (3) provided sufficient data to permit analysis.</p> <p>Results</p> <p>From the 263 citations identified, 55 relevant original articles were selected. Only 35 fulfilled all of the inclusion criteria, and of these 26 presented data on patient-based analysis. The overall patient-based analysis demonstrated a sensitivity of 89% (95% CI: 88-91%), and a specificity of 80% (95% CI: 78-83%). Adenosine stress perfusion CMR had better sensitivity than with dipyridamole (90% (88-92%) versus 86% (80-90%), P = 0.022), and a tendency to a better specificity (81% (78-84%) versus 77% (71-82%), P = 0.065).</p> <p>Conclusion</p> <p>Stress perfusion CMR is highly sensitive for detection of CAD but its specificity remains moderate.</p

Predicting general and cancer-related distress in women with newly diagnosed breast cancer

Background: Psychological distress can impact medical outcomes such as recovery from surgery and experience of side effects during treatment. Identifying the factors that explain variability in distress would guide future interventions aimed at decreasing distress. Two factors that have been implicated in distress are illness perceptions and coping, and are part of the Self-Regulatory Model of Illness Behaviour (SRM). The model suggests that coping mediates the relationship between illness perceptions and distress. Despite this; very little research has assessed this relationship with cancer-related distress, and none have examined women with screen-detected breast cancer. This study is the first to examine the relative contribution of illness perceptions and coping on general and cancer-related distress in women with screen-detected breast cancer. Methods: Women recently diagnosed with breast cancer (N = 94) who had yet to receive treatment completed measures of illness perceptions (Revised Illness Perception Questionnaire), cancer-specific coping (Mental Adjustment to Cancer Scale), general anxiety and depression (Hospital Anxiety and Depression scale), and cancer-related distress. Results: Hierarchical regression analyses revealed that medical variables, illness perceptions and coping predicted 50% of the variance in depression, 42% in general anxiety, and 40% in cancer-related distress. Believing in more emotional causes to breast cancer (beta = .22, p = .021), more illness identity (beta = .25, p = .004), greater anxious preoccupation (beta = .23, p = .030), and less fighting spirit (beta = -.31, p = .001) predicted greater depression. Greater illness coherence predicted less cancer-related distress (beta = -.20, p = .043). Greater anxious preoccupation also led to greater general anxiety (beta = .44, p &amp;lt; .001) and cancer-related distress (beta = .37, p = .001). Mediation analyses revealed that holding greater beliefs in a chronic timeline, more severe consequences, greater illness identity and less illness coherence increases cancer-specific distress (ps &amp;lt; .001) only if women were also more anxiously preoccupied with their diagnosis. Conclusions: Screening women for anxious preoccupation may help identify women with screen-detected breast cancer at risk of experiencing high levels of cancer-related distress; whilst illness perceptions and coping could be targeted for use in future interventions to reduce distress

Fuel pyrolysis through porous media: Coke formation and coupled effect on permeability

International audienceThe development of hypersonic vehicles (up to Mach 10) leads to an important heating of the whole structure. The fuel is thus used as a coolant. It presents an endothermic decomposition with possible coke formation. Its additional permeation through the porous structure involves internal convection. This implies very complex phenomena (heat and mass transfers with chemistry). In this paper, the n-dodecane pyrolysis is studied through stainless steel porous medium up to 820 K and 35 bar (supercritical state). The longitudinal profiles of chemical compositions inside the porous medium are given thanks to a specific sampling technique with off-line Gas Chromatograph and Mass Spectrometer analysis. By comparison with previous experiments under plug flow reactor, the conversion of dodecane is higher for the present experimental configuration. The pyrolysis produces preferentially light gaseous species, which results in a higher gasification rate for a similar pyrolysis rate. The effects of the residence time and of the contact surface area are demonstrated. The transient changes of Darcy's permeability are related to the coke formation thanks to previous experimental relationship with methane production. A time shift is observed between coke chemistry and permeability change. This work is quite unique to the author's knowledge because of the complex chemistry of heavy hydrocarbon fuels pyrolysis, particularly in porous medium

Severity of cardiovascular disease outcomes among patients with HIV is related to markers of inflammation and coagulation

Background-In the general population, raised levels of inflammatory markers are stronger predictors of fatal than nonfatal cardiovascular disease (CVD) events. People with HIV have elevated levels of interleukin-6 (IL-6), high-sensitivity C-reactive protein (hsCRP), and D-dimer; HIV-induced activation of inflammatory and coagulation pathways may be responsible for their greater risk of CVD. Whether the enhanced inflammation and coagulation associated with HIV is associated with more fatal CVD events has not been investigated. Methods and Results-Biomarkers were measured at baseline for 9764 patients with HIV and no history of CVD. Of these patients, we focus on the 288 that experienced either a fatal (n=74) or nonfatal (n=214) CVD event over a median of 5 years. Odds ratios (ORs) (fatal versus nonfatal CVD) (95% confidence intervals [CIs]) associated with a doubling of IL-6, D-dimer, hsCRP, and a 1-unit increase in an IL-6 and D-dimer score, measured a median of 2.6 years before the event, were 1.39 (1.07 to 1.79), 1.40 (1.10 to 1.78), 1.09 (0.93 to 1.28), and 1.51 (1.15 to 1.97), respectively. Of the 214 patients with nonfatal CVD, 23 died during follow-up. Hazard ratios (95% CI) for all-cause mortality were 1.72 (1.28 to 2.31), 1.73 (1.27 to 2.36), 1.44 (1.15 to 1.80), and 1.88 (1.39 to 2.55), respectively, for IL-6, D-dimer, hsCRP, and the IL-6 and D-dimer score. Conclusions-Higher IL-6 and D-dimer levels reflecting enhanced inflammation and coagulation associated with HIV are associated with a greater risk of fatal CVD and a greater risk of death after a nonfatal CVD even