Antiferromagnetic spintronics

Antiferromagnetic materials are magnetic inside, however, the direction of their ordered microscopic moments alternates between individual atomic sites. The resulting zero net magnetic moment makes magnetism in antiferromagnets invisible on the outside. It also implies that if information was stored in antiferromagnetic moments it would be insensitive to disturbing external magnetic fields, and the antiferromagnetic element would not affect magnetically its neighbors no matter how densely the elements were arranged in a device. The intrinsic high frequencies of antiferromagnetic dynamics represent another property that makes antiferromagnets distinct from ferromagnets. The outstanding question is how to efficiently manipulate and detect the magnetic state of an antiferromagnet. In this article we give an overview of recent works addressing this question. We also review studies looking at merits of antiferromagnetic spintronics from a more general perspective of spin-ransport, magnetization dynamics, and materials research, and give a brief outlook of future research and applications of antiferromagnetic spintronics.Comment: 13 pages, 7 figure

Biochemical systems identification by a random drift particle swarm optimization approach

BACKGROUND: Finding an efficient method to solve the parameter estimation problem (inverse problem) for nonlinear biochemical dynamical systems could help promote the functional understanding at the system level for signalling pathways. The problem is stated as a data-driven nonlinear regression problem, which is converted into a nonlinear programming problem with many nonlinear differential and algebraic constraints. Due to the typical ill conditioning and multimodality nature of the problem, it is in general difficult for gradient-based local optimization methods to obtain satisfactory solutions. To surmount this limitation, many stochastic optimization methods have been employed to find the global solution of the problem. RESULTS: This paper presents an effective search strategy for a particle swarm optimization (PSO) algorithm that enhances the ability of the algorithm for estimating the parameters of complex dynamic biochemical pathways. The proposed algorithm is a new variant of random drift particle swarm optimization (RDPSO), which is used to solve the above mentioned inverse problem and compared with other well known stochastic optimization methods. Two case studies on estimating the parameters of two nonlinear biochemical dynamic models have been taken as benchmarks, under both the noise-free and noisy simulation data scenarios. CONCLUSIONS: The experimental results show that the novel variant of RDPSO algorithm is able to successfully solve the problem and obtain solutions of better quality than other global optimization methods used for finding the solution to the inverse problems in this study

Parameter optimization in S-system models

© 2008 Vilela et al; licensee BioMed Central Ltd. ; This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.DOI: 10.1186/1752-0509-2-35Background: The inverse problem of identifying the topology of biological networks from their time series responses is a cornerstone challenge in systems biology. We tackle this challenge here through the parameterization of S-system models. It was previously shown that parameter identification can be performed as an optimization based on the decoupling of the differential Ssystem equations, which results in a set of algebraic equations. Results: A novel parameterization solution is proposed for the identification of S-system models from time series when no information about the network topology is known. The method is based on eigenvector optimization of a matrix formed from multiple regression equations of the linearized decoupled S-system. Furthermore, the algorithm is extended to the optimization of network topologies with constraints on metabolites and fluxes. These constraints rejoin the system in cases where it had been fragmented by decoupling. We demonstrate with synthetic time series why the algorithm can be expected to converge in most cases. Conclusion: A procedure was developed that facilitates automated reverse engineering tasks for biological networks using S-systems. The proposed method of eigenvector optimization constitutes an advancement over S-system parameter identification from time series using a recent method called Alternating Regression. The proposed method overcomes convergence issues encountered in alternate regression by identifying nonlinear constraints that restrict the search space to computationally feasible solutions. Because the parameter identification is still performed for each metabolite separately, the modularity and linear time characteristics of the alternating regression method are preserved. Simulation studies illustrate how the proposed algorithm identifies the correct network topology out of a collection of models which all fit the dynamical time series essentially equally well

Hamartoma angiomatoso écrino: um tumor doloroso Eccrine angiomatous hamartoma: a painful tumor

O hamartoma angiomatoso écrino (HAE) é lesão benigna, em geral, congênita. Apresenta-se na maioria dos casos como nódulo ou placa cor da pele ou eritematosa associada ou não à hiperidrose focal e dor. Localiza-se preferencialmente nos membros inferiores, próximo aos joelhos ou nos artelhos, mas lesões na face, região cervical, sacra e tronco foram descritas. O principal diagnóstico diferencial deve ser feito com o tumor glômico. Em geral, o HAE tem evolução benigna, havendo relatos de remissão espontânea da dor, sem necessidade de remoção. Contudo, foram descritos casos em que a dor levou à exérese da lesão e mesmo à amputação do membro afetado. Os autores relatam um caso de hamartoma angiomatoso écrino de aparecimento tardio, com sintomatologia exuberante e de difícil tratamento.<br>Eccrine angiomatous hamartoma (EAH) is a benign lesion usually present at birth. In most cases it presents as a flesh-colored or erythematous nodule or patch. It may or may not be associated with focal hyperhydrosis and pain. It is most commonly located in the lower extremities, near the knee or on the toes, but lesions on the face, sacral and cervical region and trunk have been described. The main differential diagnosis should be made with a glomus tumor. In general, EAH shows benign behavior, and spontaneous remission of pain has been described. Cases have been reported in which the pain led to excision and even to amputation of the affected member. The authors present a case of late onset EAH, with exuberant symptoms, which was difficult to treat