ICGE: an R package for detecting relevant clusters and atypical units in gene expression

Background: Gene expression technologies have opened up new ways to diagnose and treat cancer and other diseases. Clustering algorithms are a useful approach with which to analyze genome expression data. They attempt to partition the genes into groups exhibiting similar patterns of variation in expression level. An important problem associated with gene classification is to discern whether the clustering process can find a relevant partition as well as the identification of new genes classes. There are two key aspects to classification: the estimation of the number of clusters, and the decision as to whether a new unit (gene, tumor sample ... ) belongs to one of these previously identified clusters or to a new group. Results: ICGE is a user-friendly R package which provides many functions related to this problem: identify the number of clusters using mixed variables, usually found by applied biomedical researchers; detect whether the data have a cluster structure; identify whether a new unit belongs to one of the pre-identified clusters or to a novel group, and classify new units into the corresponding cluster. The functions in the ICGE package are accompanied by help files and easy examples to facilitate its use. Conclusions: We demonstrate the utility of ICGE by analyzing simulated and real data sets. The results show that ICGE could be very useful to a broad research community.

Kalman Filtering in R

Support in R for state space estimation via Kalman filtering was limited to one package, until fairly recently. In the last five years, the situation has changed with no less than four additional packages offering general implementations of the Kalman filter, including in some cases smoothing, simulation smoothing and other functionality. This paper reviews some of the offerings in R to help the prospective user to make an informed choice.

Multi-agent modelling for the simulation of a simple smart microgrid

The smart grid is a highly complex system that is being formed from the traditional power grid, adding new and sophisticated communication and control devices. This will enable integrating new elements for distributed power generation and also achieving an increasingly automated operation so for actions of the utilities as for customers. In order to model such systems a bottom-up method is followed, using only a few basic elements which are structured into two layers: a physical layer for the electrical power transmission, and one logical layer for element communication. A simple case study is presented to analyse the possibilities of simulation. It shows a microgrid model with dynamic load management and an integrated approach that can process both electrical and communication flows.

A complex systems modelling approach for decentralized simulation of electrical microgrids

ICECCS 2010

Object oriented simulation of hybrid renewable energy systems focused on supervisor control

EFTA 2009

TUNPOP, a computer simulation model of the yellowfin tuna population and the surface tuna fishery of the Eastern Pacific Ocean

ENGLISH: Mathematical documentation of TUNP0P, an age-structured computer simulation model of the yellowfin tuna population and surface tuna fishery of the eastern Pacific Ocean, is described. Example runs of the model are presented and discussed, and the sensitivity of the model output to changes in various parameters is examined. SPANISH: Se describe la documentación matemática de TUNP0P, un modelo computador de simulación basado en la edad de la población del atún aleta amarilla y de la pesca atunera epipelágíca del Océano Pacífico oriental. Se presentan y se discuten ejemplos de las pasadas del modelo, y se examina la sensibilidad de los resultados de salida con relación a los cambios de varios parámetros. (PDF contains 47 pages.)

Complete agent based simulation of mini-grids

EuroPES 2009

Atomistic Simulation On Size-Dependent Yield Strength And Defects Evolution Of Metal Nanowires

A simple derivation based on continuum mechanics is given, which shows the surface stress is critical for yield strength at ultra-small scales. Molecular dynamics (MD) simulations with modified embedded atom method (MEAM) are employed to investigate the mechanical behaviors of single-crystalline metal nanowires under tensile loading. The calculated yield strengths increasing with the decrease of the cross-sectional area of the nanowires are in accordance with the theoretical prediction. Reorientation induced by stacking faults is observed at the nanowire edge. In addition. the mechanism of yielding is discussed in details based on the snapshots of defects evolution. The nanowires in different crystallographic orientations behave differently in stretching deformation. This study on the plastic properties of metal nanowires will be helpful to further understanding of the mechanical properties of nanomaterials. (C) 2009 Elsevier B.V. All rights reserved.

Hybrid Qm/Mm Simulation Of The Hydration Phenomena Of Dipalmitoylphosphatidylcholine Headgroup

The polar headgroup of dipalmitoylphosphatidylcholine (DPPC) molecule both in gas phase and aqueous Solution is investigated by the hybrid quantum mechanical/molecular mechanical (QM/MM) method, in which the polar head of DPPC molecule and the bound water molecules are treated with density functional theory (DFT), while the apolar hydrocarbon chain of DPPC molecule is treated with MM method. It is demonstrated that the hybrid QM/MM method is both accurate and efficient to describe the conformations of DPPC headgroup. Folded structures of headgroup are found in gas phase calculations. In this work, both monohydration and polyhydration phenomena are investigated. In monohydration, different water association sites are studied. Both the hydration energy and the quantum properties of DPPC and water molecules are calculated at the DFT level of theory after geometry optimization. The binding force of monohydration is estimated by using the scan method. In polyhydration, more extended conformations are found and hydration energies in different polyhydration styles are estimated. (C) 2008 Elsevier Inc. All rights reserved.

An Atomistic-Continuum Hybrid Simulation Of Fluid Flows Over Superhydrophobic Surfaces

Recent experiments have found that slip length could be as large as on the order of 1 mu m for fluid flows over superhydrophobic surfaces. Superhydrophobic surfaces can be achieved by patterning roughness on hydrophobic surfaces. In the present paper, an atomistic-continuum hybrid approach is developed to simulate the Couette flows over superhydrophobic surfaces, in which a molecular dynamics simulation is used in a small region near the superhydrophobic surface where the continuum assumption is not valid and the Navier-Stokes equations are used in a large region for bulk flows where the continuum assumption does hold. These two descriptions are coupled using the dynamic coupling model in the overlap region to ensure momentum continuity. The hybrid simulation predicts a superhydrophobic state with large slip lengths, which cannot be obtained by molecular dynamics simulation alone.

Shape effects on the yield stress and deformation of silicon nanowires: A molecular dynamics simulation

The tension and compression of single-crystalline silicon nanowires (SiNWs) with different cross-sectional shapes are studied systematically using molecular dynamics simulation. The shape effects on the yield stresses are characterized. For the same surface to volume ratio, the circular cross-sectional SiNWs are stronger than the square cross-sectional ones under tensile loading, but reverse happens in compressive loading. With the atoms colored by least-squares atomic local shear strain, the deformation processes reveal that the failure modes of incipient yielding are dependent on the loading directions. The SiNWs under tensile loading slip in {111} surfaces, while the compressive loading leads the SiNWs to slip in the {110} surfaces. The present results are expected to contribute to the design of the silicon devices in nanosystems.

Agent based modeling of energy networks

Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed.