8,298 research outputs found
Time-programmable drug dosing allows the manipulation, suppression and reversal of antibiotic drug resistance in vitro
Multi-drug strategies have been attempted to prolong the efficacy of existing antibiotics, but with limited success. Here we show that the evolution of multi-drug-resistant Escherichia coli can be manipulated in vitro by administering pairs of antibiotics and switching between them in ON/OFF manner. Using a multiplexed cell culture system, we find that switching between certain combinations of antibiotics completely suppresses the development of resistance to one of the antibiotics. Using this data, we develop a simple deterministic model, which allows us to predict the fate of multi-drug evolution in this system. Furthermore, we are able to reverse established drug resistance based on the model prediction by modulating antibiotic selection stresses. Our results support the idea that the development of antibiotic resistance may be potentially controlled via continuous switching of drugs
Integrated chaos generators
This paper surveys the different design issues, from mathematical model to silicon, involved on the design of integrated circuits for the generation of chaotic behavior.Comisión Interministerial de Ciencia y Tecnología 1FD97-1611(TIC)European Commission ESPRIT 3110
Optimizing Traffic Lights in a Cellular Automaton Model for City Traffic
We study the impact of global traffic light control strategies in a recently
proposed cellular automaton model for vehicular traffic in city networks. The
model combines basic ideas of the Biham-Middleton-Levine model for city traffic
and the Nagel-Schreckenberg model for highway traffic. The city network has a
simple square lattice geometry. All streets and intersections are treated
equally, i.e., there are no dominant streets. Starting from a simple
synchronized strategy we show that the capacity of the network strongly depends
on the cycle times of the traffic lights. Moreover we point out that the
optimal time periods are determined by the geometric characteristics of the
network, i.e., the distance between the intersections. In the case of
synchronized traffic lights the derivation of the optimal cycle times in the
network can be reduced to a simpler problem, the flow optimization of a single
street with one traffic light operating as a bottleneck. In order to obtain an
enhanced throughput in the model improved global strategies are tested, e.g.,
green wave and random switching strategies, which lead to surprising results.Comment: 13 pages, 10 figure
Analysis, Design and Control of a Modular Full-Si Converter Concept for Electric Vehicle Ultra-Fast Charging
L'abstract è presente nell'allegato / the abstract is in the attachmen
Importance sampling for thermally induced switching and non-switching probabilities in spin-torque magnetic nanodevices
Spin-transfer torque magnetoresistive random access memory is a potentially
transformative technology in the non-volatile memory market. Its viability
depends, in part, on one's ability to predictably induce or prevent switching;
however, thermal fluctuations cause small but important errors in both the
writing and reading processes. Computing these very small probabilities for
magnetic nanodevices using naive Monte Carlo simulations is essentially
impossible due to their slow statistical convergence, but variance reduction
techniques can offer an effective way to improve their efficiency. Here, we
provide an illustration of how importance sampling can be efficiently used to
estimate low read and write soft error rates of macrospin and coupled-spin
systems.Comment: 11 pages, 14 figure
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