Online exercise for the design and simulation of PCR and PCR-RFLP experiments

[EN] Background: Polymerase Chain Reaction (PCR) and Restriction Fragment Length Polymorphism of PCR products (PCR-RFLP) are extensively used molecular biology techniques. An exercise for the design and simulation of PCR and PCR-RFLP experiments will be a useful educational tool. Findings: An online PCR and PCR-RFLP exercise has been create that requires users to find the target genes,compare them, design primers, search for restriction endonucleases, and finally to simulate the experiment. Each user of the service is randomly assigned a gene from Escherichia coli; to complete the exercise, users must design an experiment capable of distinguishing among E. coli strains. By applying the experimental procedure to all completely sequenced E. coli, a basic understanding of strain comparison and clustering can also be acquired. Comparison of results obtained in different experiments is also very instructive. Conclusions: The exercise is freely available at http://insilico.ehu.es/edu.

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

Complete agent based simulation of mini-grids

EuroPES 2009

Atomistic simulation studies of the cement paste components

230 p.

Digital-Analog Quantum Simulation of Spin Systems in Trapped Ions

65 p.

Methods and tools for the assessment of daylight transmittance through expanded metal meshes

306 p.

Insights into mechanism kinematics for protein motion simulation

Background: The high demanding computational requirements necessary to carry out protein motion simulations make it difficult to obtain information related to protein motion. On the one hand, molecular dynamics simulation requires huge computational resources to achieve satisfactory motion simulations. On the other hand, less accurate procedures such as interpolation methods, do not generate realistic morphs from the kinematic point of view. Analyzing a protein's movement is very similar to serial robots; thus, it is possible to treat the protein chain as a serial mechanism composed of rotational degrees of freedom. Recently, based on this hypothesis, new methodologies have arisen, based on mechanism and robot kinematics, to simulate protein motion. Probabilistic roadmap method, which discretizes the protein configurational space against a scoring function, or the kinetostatic compliance method that minimizes the torques that appear in bonds, aim to simulate protein motion with a reduced computational cost. Results: In this paper a new viewpoint for protein motion simulation, based on mechanism kinematics is presented. The paper describes a set of methodologies, combining different techniques such as structure normalization normalization processes, simulation algorithms and secondary structure detection procedures. The combination of all these procedures allows to obtain kinematic morphs of proteins achieving a very good computational cost-error rate, while maintaining the biological meaning of the obtained structures and the kinematic viability of the obtained motion. Conclusions: The procedure presented in this paper, implements different modules to perform the simulation of the conformational change suffered by a protein when exerting its function. The combination of a main simulation procedure assisted by a secondary structure process, and a side chain orientation strategy, allows to obtain a fast and reliable simulations of protein motion.

Modelling and Simulation of ERTMS for Current and Future Mobile Technologies

Nowadays, train control in-lab simulation tools play a crucial role in reducing extensive and expensive on-site railway testing activities. In this paper, we present our contribution in this arena by detailing the internals of our European Railway Train Management System in-lab demonstrator. This demonstrator is built over a general-purpose simulation framework, Riverbed Modeler, previously Opnet Modeler. Our framework models both ERTMS subsystems, the Automatic Train Protection application layer based on movement authority message exchange and the telecommunication subsystem based on GSM-R communication technology. We provide detailed information on our modelling strategy. We also validate our simulation framework with real trace data. To conclude, under current industry migration scenario from GSM-R legacy obsolescence to IP-based heterogeneous technologies, our simulation framework represents a singular tool to railway operators. As an example, we present the assessment of related performance indicators for a specific railway network using a candidate replacement technology, LTE, versus current legacy technology. To the best of our knowledge, there is no similar initiative able to measure the impact of the telecommunication subsystem in the railway network availability.

Quantum Simulation of Dissipative Processes without Reservoir Engineering

We present a quantum algorithm to simulate general finite dimensional Lindblad master equations without the requirement of engineering the system-environment interactions. The proposed method is able to simulate both Markovian and non-Markovian quantum dynamics. It consists in the quantum computation of the dissipative corrections to the unitary evolution of the system of interest, via the reconstruction of the response functions associated with the Lindblad operators. Our approach is equally applicable to dynamics generated by effectively non-Hermitian Hamiltonians. We confirm the quality of our method providing specific error bounds that quantify its accuracy.

Theory and simulation of the optical response of novel nanomaterials from visible to terahertz

133 p.

Digital Quantum Simulation of Spin Models with Circuit Quantum Electrodynamics

Systems of interacting quantum spins show a rich spectrum of quantum phases and display interesting many-body dynamics. Computing characteristics of even small systems on conventional computers poses significant challenges. A quantum simulator has the potential to outperform standard computers in calculating the evolution of complex quantum systems. Here, we perform a digital quantum simulation of the paradigmatic Heisenberg and Ising interacting spin models using a two transmon-qubit circuit quantum electrodynamics setup. We make use of the exchange interaction naturally present in the simulator to construct a digital decomposition of the model-specific evolution and extract its full dynamics. This approach is universal and efficient, employing only resources that are polynomial in the number of spins, and indicates a path towards the controlled simulation of general spin dynamics in superconducting qubit platforms.

hp-Adaptive simulation and inversion of magnetotelluric measurements

xlix, 121 p.