Improving predictive quality of Kriging metamodel by variogram adaptation

Application of interpolation/approximation techniques (metamodels, for brevity) is commonly adopted in numerical optimization, typically to reduce the overall execution time of the optimization process. A limited number of trial solution are computed, cov- ering the design variable space: those trial points are then used for the determination of an estimate of the objective function in any desired location of the design space.

Tropospheric Ozone Monitoring with IASI/MetOP Using a Self - Adapting Regularizati on Method

Tropospheric ozone is a key species for tropospheric chemistry and air quality. Its monitoring is essential to quantify sources, transport, chemical transformation and sinks of atmospheric pollution. Accurate data are required for understanding and predicting chemical weather. Space-borne observations are very promising for these concerns, especially those from IASI/MetOp.

A patient with PMP22-related hereditary neuropathy and DBH-gene-related dysautonomia

Recurrent focal neuropathy with liability to pressure palsies is a relatively frequent autosomal-dominant demyelinating neuropathy linked to peripheral myelin protein 22 (PMP22) gene deletions. The combination of PMP22 gene mutations with other genetic variants is known to cause a more severe phenotype than expected. We present the case of a patient with severe orthostatic hypotension since 12 years of age, who inherited a PMP22 gene deletion from his father. Genetic double trouble was suspected because of selective sympathetic autonomic disturbances.

An inner-point modification of PSO for constrained optimization

In the last two decades, PSO (Particle Swarm Optimization) gained a lot of attention among the different derivative-free algorithms for global optimization. The simplicity of the implementation, compact memory usage and parallel structure represent some key features, largely appreciated. On the other hand, the absence of local information about the objective function slow down the algorithm when one or more constraints are violated, even if a penalty approach is applied.

A destination-preserving model for simulating Wardrop equilibria in traffic flow on networks

In this paper we propose a LWR-like model for traffic flow on networks which allows to track several groups of drivers, each of them being characterized only by their destination in the network. The path actually followed to reach the destination is not assigned a priori, and can be chosen by the drivers during the journey, taking decisions at junctions. The model is then used to describe three possible behaviors of drivers, as- sociated to three different ways to solve the route choice problem: 1. Drivers ignore the presence of the other vehicles; 2.

Information content of long-range NMR data for the characterization of conformational heterogeneity

Long-range NMR data, namely residual dipolar couplings (RDCs) from external alignment and paramagnetic data, are becoming increasingly popular for the characterization of conformational heterogeneity of multidomain biomacromolecules and protein complexes. The question addressed here is how much information is contained in these averaged data.