Automated analysis of fluorescence lifetime imaging microscopy (FLIM) data based on the Laguerre deconvolution method

In fluorescence lifetime imaging microscopy (FLIM), fluorescence time decay at each pixel of the imaged sample are measured. Every recorded fluorescence decay corresponds to the time convolution of the instrument response with the intrinsic fluorescence impulse response function (IRF), from which the sample fluorescence lifetime is determined. To estimate the IRF, the instrument response thus needs to be deconvolved from the recorded fluorescence decay. We have recently introduced a novel FLIM time-deconvolution method based on the linear expansion of the fluorescence decays on an orthonormal Laguerre basis. Since this method allows simultaneous estimation of the IRFs at all pixels, it performs at least two orders of magnitude faster than standard algorithms. In its original implementation, however, the Laguerre basis, determined by the Laguerre parameter α, is selected using a heuristic approach. Here, we present an automated implementation, whereby the Laguerre parameter α is treated as a free parameter within a nonlinear least squares optimization scheme. The new implementation combines the unmatched inherent computational speed of the Laguerre deconvolution method with a systematic model selection approach. This method will thus facilitate applications of FLIM requiring automatic estimation of the spatial distribution of fluorescence lifetimes, such as in in vivo tissue FLIM imaging.     

BETaaS: A Platform for Development and Execution of Machine-to-Machine Applications in the Internet of Things

Wireless Personal Communications - The integration of everyday objects into the Internet represents the foundation of the forthcoming Internet of Things (IoT). Smart objects will be the building...     

Fabrication of CdSe‐Nanofibers with Potential for Biomedical Applications

The design and synthesis of nanostructured functional hybrid biomaterials are essential for the next generation of advanced diagnostics and the treatment of disease. A simple route to fabricate semiconductor nanofibers by self‐assembled, elastin‐like polymer (ELP)‐templated semiconductor nanoparticles is reported. Core–shell nanostructures of CdSe nanoparticles with a shell of ELPs are used as building blocks to fabricate functional one‐dimensional (1D) nanostructures. The CdSe particles are generated in situ within the ELP matrix at room temperature. The ELP controls the size and the size‐distribution of the CdSe nanoparticles in an aqueous medium and simultaneously directs the self‐assembly of core–shell building blocks into fibril architectures. It was found that the self‐assembly of core–shell building blocks into nanofibers is strongly dependent on the pH value of the medium. Results of cytotoxicity and antiproliferation of the CdSe‐ELP nanofibers demonstrate that the CdSe‐ELP does not exhibit any toxicity towards B14 cells. Moreover, these are found to be markedly capable of crossing the cell membrane of B14. In contrast, unmodified CdSe nanoparticles with ELPs cause a strong toxic response and reduction in the cell proliferation. This concept is valid for the fabrication of a variety of metallic and semiconductor 1D‐architectures. Therefore, it is believed that these could be used not only for biomedical purposes but for application in a wide range of advanced miniaturized devices.     

Modified Shuffled Based Architecture for High-Throughput Decoding of LDPC Codes

Low Density Parity-Check (LDPC) codes achieve the best performance when they are decoded with the sum-product (SP) algorithm. This is a two-phase iterative algorithm where two types of messages are interchanged and updated in each iteration. The group-shuffled or layered decoding schemes applied to the SP algorithm speed up its convergence by modifying its schedule, so they yield a reduction in the number of iterations required to achieve a given performance. However, the two-phase processing is still maintained. In this paper a modification of the group-shuffled scheme suitable for high-rate LDPC codes is proposed. The modification allows the overlapping of the two-phase computation, achieving a convergence speed up close to that of the group-shuffled scheme with higher throughput. Besides, high throughput architectures are presented for the modified algorithm. As an example, the proposed architecture has been implemented for the 2048-bit LDPC code of the IEEE 802.3an standard and it was synthesized in a 90 nm CMOS process achieving a throughput of 22.40 Gbps at 14 iterations with a clock frequency of 306 MHz and a total area of 10.5 mm². Furthermore, the decoder performs within 0.5 dB of the floating-point 100 iterations sum-product algorithm at a PER of 10⁻⁵.     

Unprecedented Improvement of Single Li‐Ion Conductive Solid Polymer Electrolyte Through Salt Additive

Solid‐state lithium metal (Li°) batteries (SSLMBs) are believed to be the most promising technologies to tackle the safety concerns and the insufficient energy density encountered in conventional Li‐ion batteries. Solid polymer electrolytes (SPEs) inherently own good processability and flexibility, enabling large‐scale preparation of SSLMBs. To minimize the growth of Li° dendrites and cell polarization in SPE‐based SSLMBs, an additive‐containing single Li‐ion conductive SPE is reported. The characterization results show that a small dose of electrolyte additive (2 wt%) substantially increases the ionic conductivity of single Li‐ion conductive SPEs as well as the interfacial compatibility between electrode and SPE, allowing the cycling of SPE‐based cells with good electrochemical performance. This work may provide a paradigm shift on the design of highly cationic conductive electrolytes, which are essential for developing safe and high‐performance rechargeable batteries.     

On the Influence of the Propagation Channel in the Performance of Energy-Efficient Geographic Routing Algorithms for Wireless Sensor Networks (WSN)

In this paper, the influence of the features of the propagation channel in the performance of energy-efficient routing algorithms for wireless sensor networks is studied. Although there are a lot of works regarding energy-efficient routing protocols, almost no reference to realistic propagation channel models and influence is made in the literature. Considering that the propagation channel may affect the efficiency of the different energy-efficient routing algorithms, different propagation scenarios are proposed in this work, from the most simplistic free-space propagation model to more complex ones. The latter includes the effects of multipath propagation, shadowing, fading, etc. In addition, spatial diversity transmission/reception models are considered to mitigate the effects of hard propagation fading. Some results are provided comparing the performance of several energy-efficient routing algorithms in different scenarios.     

STC power for 15 MW of PV comparing nameplate,initial power and power after 4 years

To date, the majority of quality controls performed at PV plants are based on the measurement of a small sample of individual modules. Consequently, there is very little representative data on the real Standard Test Conditions (STC) power output values for PV generators. This paper presents the power output values for more than 1300 PV generators having a total installed power capacity of almost 15.3 MW. The values were obtained by the INGEPER‐UPNA group, in collaboration with the IES‐UPM, through a study to monitor the power output of a number of PV plants from 2006 to 2009. This work has made it possible to determine, amongst other things, the power dispersion that can be expected amongst generators made by different manufacturers, amongst generators made by the same manufacturer but comprising modules of different nameplate ratings and also amongst generators formed by modules with the same characteristics. The work also analyses the STC power output evolution over time in the course of this 4‐year study. The values presented here could be considered to be representative of generators with fault‐free modules. Copyright © 2012 John Wiley & Sons, Ltd.     

Super Resolution of Multispectral Images using ℓ1 Image Models and Interband Correlations

In this paper we propose a novel super-resolution based algorithm for the pansharpening of multispectral images. Within the Bayesian formulation, the proposed methodology incorporates prior knowledge on the expected characteristics of multispectral images; that is, it imposes smoothness within each band by means of the energy associated with the ℓ1 norm of vertical and horizontal first order differences of image pixel values and also takes into account the correlation among the bands of the multispectral image. The observation process is modeled using the sensor characteristics of both panchromatic and multispectral images. The method is tested on real and synthetic images, compared with other pansharpening methods, and the quality of the results assessed both qualitatively and quantitatively.