A benchmark of kriging-based infill criteria for noisy optimization

Responses of many real-world problems can only be evaluated perturbed by noise. In order to make an efficient optimization of these problems possible, intelligent optimization strategies successfully coping with noisy evaluations are required. In this article, a comprehensive review of existing kriging-based methods for the optimization of noisy functions is provided. In summary, ten methods for choosing the sequential samples are described using a unified formalism. They are compared on analytical benchmark problems, whereby the usual assumption of homoscedastic Gaussian noise made in the underlying models is meet. Different problem configurations (noise level, maximum number of observations, initial number of observations) and setups (covariance functions, budget, initial sample size) are considered. It is found that the choices of the initial sample size and the covariance function are not critical. The choice of the method, however, can result in significant differences in the performance. In particular, the three most intuitive criteria are found as poor alternatives. Although no criterion is found consistently more efficient than the others, two specialized methods appear more robust on average.

Relationship between glomerular filtration rate and the adipokines adiponectin, resistin and leptin in coronary patients with predominantly normal or mildly impaired renal function

BACKGROUND: Due to their molecular weight, it is possible that the adipokines adiponectin, resistin and leptin accumulate when glomerular filtration rate (GFR) is decreased. In reduced renal clearance, altered serum concentrations of these proteins might affect cardiovascular risk. The objective of the study was to investigate the relationship between adipokine concentrations and GFR. METHODS: The association between GFR, as determined by the abbreviated MDRD equation, and the concentrations of the adipokines adiponectin, resistin and leptin was assessed in a cohort of coronary patients (n=538; 363 male, 165 female). After calculation of correlations between GFR and adipokine concentrations, the association was further assessed by analysis of covariance following adjustment for age, gender, BMI, presence of type 2 diabetes, presence of hypertension, history of smoking as well as for serum lipid concentrations. RESULTS: Mean GFR in our study population was 68.74+/-15.27 ml/min/1.73 m(2). 74.3% of the patients had a GFR >60 ml/min/1.73 m(2), 24% of the patients had a GFR between 30 and 60 ml/min/1.73 m(2), and 1.7% of the patients had a GFR <30 ml/min/1.73 m(2). There were significant inverse correlations between adiponectin (r=-0.372; p<0.001), resistin (r=-0.227; p<0.001) and leptin (r=-0.151; p=0.009) concentrations and GFR. After multivariate adjustment, the associations remained significant for adiponectin and resistin. Subgroup analysis in patients with GFR >60 ml/min/1.73 m(2) showed a significant correlation between GFR and adiponectin as well as leptin concentrations. However, after adjustment, these associations no longer were significant. CONCLUSIONS: There is an independent association between GFR and the serum concentrations of adiponectin and resistin. However, this association is not present at GFR >60 ml/min/1.73 m(2). This finding suggests that adipokine concentrations in mildly impaired and normal renal function are influenced by factors other than GFR.

A covariance analysis to optimize the optical follow-up strategies

The Astronomical Institute of the University of Bern (AIUB) is conducting several search campaigns for space debris using optical sensors. The debris objects are discovered during systematic survey observations. In general, the result of a discovery consists in only a short observation arc, or tracklet, which is used to perform a first orbit determination in order to be able to observe t he object again in subsequent follow-up observations. The additional observations are used in the orbit improvement process to obtain accurate orbits to be included in a catalogue. In order to obtain the most accurate orbit within the time available it is necessary to optimize the follow-up observations strategy. In this paper an in‐depth study, using simulations and covariance analysis, is performed to identify the optimal sequence of follow-up observations to obtain the most accurate orbit propagation to be used for the space debris catalogue maintenance. The main factors that determine the accuracy of the results of an orbit determination/improvement process are: tracklet length, number of observations, type of orbit, astrometric error of the measurements, time interval between tracklets, and the relative position of the object along its orbit with respect to the observing station. The main aim of the covariance analysis is to optimize the follow-up strategy as a function of the object-observer geometry, the interval between follow-up observations and the shape of the orbit. This an alysis can be applied to every orbital regime but particular attention was dedicated to geostationary, Molniya, and geostationary transfer orbits. Finally the case with more than two follow-up observations and the influence of a second observing station are also analyzed.

A Thalamic-Fronto-Parietal Structural Covariance Network Emerging in the Course of Recovery from Hand Paresis after Ischemic Stroke.

AIM To describe structural covariance networks of gray matter volume (GMV) change in 28 patients with first-ever stroke to the primary sensorimotor cortices, and to investigate their relationship to hand function recovery and local GMV change. METHODS Tensor-based morphometry maps derived from high-resolution structural images were subject to principal component analyses to identify the networks. We calculated correlations between network expression and local GMV change, sensorimotor hand function and lesion volume. To verify which of the structural covariance networks of GMV change have a significant relationship to hand function, we performed an additional multivariate regression approach. RESULTS Expression of the second network, explaining 9.1% of variance, correlated with GMV increase in the medio-dorsal (md) thalamus and hand motor skill. Patients with positive expression coefficients were distinguished by significantly higher GMV increase of this structure during stroke recovery. Significant nodes of this network were located in md thalamus, dorsolateral prefrontal cortex, and higher order sensorimotor cortices. Parameter of hand function had a unique relationship to the network and depended on an interaction between network expression and lesion volume. Inversely, network expression is limited in patients with large lesion volumes. CONCLUSION Chronic phase of sensorimotor cortical stroke has been characterized by a large scale co-varying structural network in the ipsilesional hemisphere associated specifically with sensorimotor hand skill. Its expression is related to GMV increase of md thalamus, one constituent of the network, and correlated with the cortico-striato-thalamic loop involved in control of motor execution and higher order sensorimotor cortices. A close relation between expression of this network with degree of recovery might indicate reduced compensatory resources in the impaired subgroup.