Total generalized variation regularization for multi-modal electron tomography.

In multi-modal electron tomography, tilt series of several signals such as X-ray spectra, electron energy-loss spectra, annular dark-field, or bright-field data are acquired at the same time in a transmission electron microscope and subsequently reconstructed in three dimensions. However, the acquired data are often incomplete and suffer from noise, and generally each signal is reconstructed independently of all other signals, not taking advantage of correlation between different datasets. This severely limits both the resolution and validity of the reconstructed images. In this paper, we show how image quality in multi-modal electron tomography can be greatly improved by employing variational modeling and multi-channel regularization techniques. To achieve this aim, we employ a coupled Total Generalized Variation (TGV) regularization that exploits correlation between different channels. In contrast to other regularization methods, coupled TGV regularization allows to reconstruct both hard transitions and gradual changes inside each sample, and links different channels at the level of first and higher order derivatives. This favors similar interface positions for all reconstructions, thereby improving the image quality for all data, in particular, for 3D elemental maps. We demonstrate the joint multi-channel TGV reconstruction on tomographic energy-dispersive X-ray spectroscopy (EDXS) and high-angle annular dark field (HAADF) data, but the reconstruction method is generally applicable to all types of signals used in electron tomography, as well as all other types of projection-based tomographies.

Coupled regularization with multiple data discrepancies.

We consider a class of regularization methods for inverse problems where a coupled regularization is employed for the simultaneous reconstruction of data from multiple sources. Applications for such a setting can be found in multi-spectral or multimodality inverse problems, but also in inverse problems with dynamic data. We consider this setting in a rather general framework and derive stability and convergence results, including convergence rates. In particular, we show how parameter choice strategies adapted to the interplay of different data channels allow to improve upon convergence rates that would be obtained by treating all channels equally. Motivated by concrete applications, our results are obtained under rather general assumptions that allow to include the Kullback-Leibler divergence as data discrepancy term. To simplify their application to concrete settings, we further elaborate several practically relevant special cases in detail. To complement the analytical results, we also provide an algorithmic framework and source code that allows to solve a class of jointly regularized inverse problems with any number of data discrepancies. As concrete applications, we show numerical results for multi-contrast MR and joint MR-PET reconstruction.

Molecular sequelae of topographically guided peripheral nerve repair.

Peripheral nerve injuries cause severe disability with decreased nerve function often followed by neuropathic pain that impacts the quality of life. Even though use of autografts is the current gold standard, nerve conduits fabricated from electrospun nanofibers have shown promise to successfully bridge critical length nerve gaps. However, in depth analysis of the role of topographical cues in the context of spatio-temporal progression of the regenerative sequence has not been elucidated. Here, we explored the influence of topographical cues (aligned, random, and smooth films) on the regenerative sequence and potential to successfully support nerve regeneration in critical size gaps. A number of key findings emerged at the cellular, cytokine and molecular levels from the study. Higher quantities of IL-1α and TNF-α were detected in aligned fiber based scaffolds. Differential gene expression of BDNF, NGFR, ErbB2, and ErbB3 were observed suggesting a role for these genes in influencing Schwann cell migration, myelination, etc. that impact the regeneration in various topographies. Fibrin matrix stabilization and arrest of nerve-innervated muscle atrophy was also evident. Taken together, our data shed light on the cascade of events that favor regeneration in aligned topography and should stimulate research to further refine the strategy of nerve regeneration using topographical cues.

Uso de instrumentos econômicos na gestäo ambiental da América Latina e Caribe: liçöes e recomendaçöes / Use of economics instruments in environmental management of Latin America and Caribbe: lessons and recommendations

Investiga o uso dos instrumentos econômicos (IEs) no contexto da América Latina e do Caribe (ALC). Abrange um painel de dez países - Barbados, Brasil, Chile, Colômbia, Equador, Jamaica, México, Peru, Trinidad e Tobago e Venezuela. Faz um corte transversal de questöes - abastecimento/captaçäo de água, qualidade da água, qualidade do ar, energia, gestäo dos resíduos sólidos e líquidos, poluiçäo sonora e agricultura - dentro de um ambiente urbano. Uma das principais conclusöes é que o uso de IEs está bastante difundido na regiäo, mas que, devido à fragilidade institucional dos órgäos ambientais locais, sua implementaçäo näo fornecerá uma rápida panacéia para os problemas freqüentemente associados aos procedimentos tipos de comando e controle. Procura apontar as condiçöes necessárias para que haja um escopo definido para a cuidadosa e oportuna implementaçäo de certos IEs e que estes venham a garantir uma melhoria ambiental com menor custo social.