Dietary interferences with lithium therapy.

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Multi-Objective Optimisation of an Aerostatic Pad: Design of Position, Number and Diameter of the Supply Holes

ABSTRACTIn this paper, a rectangular aerostatic bearing with multiple supply holes is optimised with a multiobjective optimisation approach. The design variables taken into account are the supply holes position, their number and diameter, the supply pressure, while the objective functions are the load capacity, the air consumption and the stiffness and damping coefficients. A genetic algorithm is applied in order to find the Pareto set of solutions. The novelty with respect to other optimisations which can be found in literature is that number and location of the supply holes is completely free and not associated to a pre-defined scheme. A vector x associated with the supply holes location is introduced in the design parameters and given in input to the optimizer

A valence bond description of the bromine halogen bond

A theoretical investigation on the nature of the halogen bond through a valence-bond approach has been carried out with two main goals: (a) finding further confirmations of already existing explanations on the physical origins of the halogen bond and (b) possibly enriching the current models with new details. To achieve these goals we have exploited the spin-coupled method and we have performed computations on RBr efNH3 dimers characterized by a different electron withdrawing power of substituent \uf8ffR to the bromine atom. The analysis of typical spin-coupled descriptors (eg, shapes and overlaps of the spin-coupled orbitals, weights of the spin-coupled structures) in the different cases and in function of the distance between the monomers allowed us to draw qualitative conclusions about the formation and the strength of the halogen bonds. In particular, the investigation not only confirmed the validity of already existing models (ie, \u3c3-hole and lump-hole models) but also highlighted interesting new features, such as the fact that the depletion of electron density around the bromine atom does not extend only toward the acceptor of the halogen bond, but also in the opposite direction (toward the substituent of the halogen), thus forming a sort of \u3c3-tunnel, rather than a simple \u3c3-hole

Halogen bonding in the framework of classical force fields: The case of chlorine

Halogen bonding is nowadays a consolidated tool in chemistry. Only recently, the importance of halogen bonding has been demonstrated also in biological systems, owing to the presence of halogens in drugs. This interaction is due to the anisotropy of the electron density around the halogen that leads to the formation of the \u2018\u3c3-hole\u2019, which is responsible for the interaction with a nucleophile site. Unfortunately, classical force fields used in the study of ligand-receptor systems are not able to describe the \u2018\u3c3-hole\u2019. Here, we propose a pseudo-atom based methodology able to correctly describe halogen bonding involving chlorine using classical force field

Coupling traffic models on networks and urban dispersion models for simulating sustainable mobility strategies

The aim of the present paper is to investigate the viability of macroscopic traffic models for modeling and testing different traffic scenarios, in order to define the impact on air quality of different strategies for the reduction of traffic emissions. To this aim, we complement a well assessed traffic model on networks (Garavello, Piccoli, 2006) with a strategy for estimating data needed from the model and we couple it with the urban dispersion model Sirane (Soulhac, 2000)

Machine learning for flux regression in discrete fracture networks

AbstractIn several applications concerning underground flow simulations in fractured media, the fractured rock matrix is modeled by means of the Discrete Fracture Network (DFN) model. The fractures are typically described through stochastic parameters sampled from known distributions. In this framework, it is worth considering the application of suitable complexity reduction techniques, also in view of possible uncertainty quantification analyses or other applications requiring a fast approximation of the flow through the network. Herein, we propose the application of Neural Networks to flux regression problems in a DFN characterized by stochastic trasmissivities as an approach to predict fluxes

A hybrid mortar virtual element method for discrete fracture network simulations

The most challenging issue in performing underground flow simulations in Discrete Fracture Networks (DFN), is to effectively tackle the geometrical difficulties of the problem. In this work we put forward a new application of the Virtual Element Method combined with the Mortar method for domain decomposition: we exploit the flexibility of the VEM in handling polygonal meshes in order to easily construct meshes conforming to the traces on each fracture, and we resort to the mortar approach in order to ``weakly'' impose continuity of the solution on intersecting fractures. The resulting method replaces the need for matching grids between fractures, so that the meshing process can be performed independently for each fracture. Numerical results show optimal convergence and robustness in handling very complex geometries

Hybrid Newton-type method for a class of semismooth equations

In this paper, we present a hybrid method for the solution of a class of composite semismooth equations encountered frequently in applications. The method is obtained by combining a generalized finite-difference Newton method to an inexpensive direct search method. We prove that, under standard assumptions, the method is globally convergent with a local rate of convergence which is superlinear or quadratic. We report also several numerical results obtained applying the method to suitable reformulations of well-known nonlinear complementarity problem