Intermolecular energy transfer and photostability of luminescence-tuneable multicolour PMMA films doped with lanthanide-beta-diketonate complexes

It is reported in this work the preparation, characterisation and photoluminescence study of poly(methylmethacrylate) (PMMA) thin films co-doped with [Eu(tta)(3)(H(2)O)(2)] and [Tb(acac)(3)(H(2)O)(3)] complexes. Both the composition and excitation wavelength may be tailored to fine-tune the emission properties of these Ln(3+)-beta-diketonate doped polymer films, exhibiting green and red primary colours, as well as intermediate colours. In addition to the ligand-Ln(3+) intramolecular energy transfer, it is observed an unprecedented intermolecular energy transfer process from the (5)D(4) emitting level of the Tb(3+) ion to the excited triplet state T(1) of the tta ligand coordinated to the Eu(3+) ion. The PMMA polymer matrix acts as a co-sensitizer and enhances the overall luminescence intensity of the polymer films. Furthermore, it provides considerable UV protection for the luminescent species and improves the photostability of the doped system.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Making solar fuels by artificial photosynthesis

In order for solar energy to serve as a primary energy source, it must be paired with energy storage on a massive scale. At this scale, solar fuels and energy storage in chemical bonds is the only practical approach. Solar fuels are produced in massive amounts by photosynthesis with the reduction of CO(2) by water to give carbohydrates but efficiencies are low. In photosystem II (PSII), the oxygen-producing site for photosynthesis, light absorption and sensitization trigger a cascade of coupled electron-proton transfer events with time scales ranging from picoseconds to microseconds. Oxidative equivalents are built up at the oxygen evolving complex (OEC) for water oxidation by the Kok cycle. A systematic approach to artificial photo synthesis is available based on a ""modular approach"" in which the separate functions of a final device are studied separately, maximized for rates and stability, and used as modules in constructing integrated devices based on molecular assemblies, nanoscale arrays, self-assembled monolayers, etc. Considerable simplification is available by adopting a ""dyesensitized photoelectrosynthesis cell"" (DSPEC) approach inspired by dye-sensitized solar cells (DSSCs). Water oxidation catalysis is a key feature, and significant progress has been made in developing a single-site solution and surface catalysts based on polypyridyl complexes of Ru. In this series, ligand variations can be used to tune redox potentials and reactivity over a wide range. Water oxidation electrocatalysis has been extended to chromophore-catalyst assemblies for both water oxidation and DSPEC applications.

Automatic tuning method for the design of supplementary damping controllers for flexible alternating current transmission system devices

The design of supplementary damping controllers to mitigate the effects of electromechanical oscillations in power systems is a highly complex and time-consuming process, which requires a significant amount of knowledge from the part of the designer. In this study, the authors propose an automatic technique that takes the burden of tuning the controller parameters away from the power engineer and places it on the computer. Unlike other approaches that do the same based on robust control theories or evolutionary computing techniques, our proposed procedure uses an optimisation algorithm that works over a formulation of the classical tuning problem in terms of bilinear matrix inequalities. Using this formulation, it is possible to apply linear matrix inequality solvers to find a solution to the tuning problem via an iterative process, with the advantage that these solvers are widely available and have well-known convergence properties. The proposed algorithm is applied to tune the parameters of supplementary controllers for thyristor controlled series capacitors placed in the New England/New York benchmark test system, aiming at the improvement of the damping factor of inter-area modes, under several different operating conditions. The results of the linear analysis are validated by non-linear simulation and demonstrate the effectiveness of the proposed procedure.

Exploring the random genesis of co-occurrence networks

Using the network random generation models from Gustedt (2009)[23], we simulate and analyze several characteristics (such as the number of components, the degree distribution and the clustering coefficient) of the generated networks. This is done for a variety of distributions (fixed value, Bernoulli, Poisson, binomial) that are used to control the parameters of the generation process. These parameters are in particular the size of newly appearing sets of objects, the number of contexts in which new elements appear initially, the number of objects that are shared with `parent` contexts, and, the time period inside which a context may serve as a parent context (aging). The results show that these models allow to fine-tune the generation process such that the graphs adopt properties as can be found in real world graphs. (C) 2011 Elsevier B.V. All rights reserved.

Real-time detection of pneumothorax using electrical impedance tomogyaphy

Objectives: Pneumothorax is a frequent complication during mechanical ventilation. Electrical impedance tomography (EIT) is a noninvasive tool that allows real-time imaging of regional ventilation. The purpose of this study was to 1) identify characteristic changes in the EIT signals associated with pneumothoraces; 2) develop and fine-tune an algorithm for their automatic detection; and 3) prospectively evaluate this algorithm for its sensitivity and specificity in detecting pneumothoraces in real time. Design: Prospective controlled laboratory animal investigation. Setting: Experimental Pulmonology Laboratory of the University of Sao Paulo. Subjects: Thirty-nine anesthetized mechanically ventilated supine pigs (31.0 +/- 3.2 kg, mean +/- SD). Interventions. In a first group of 18 animals monitored by EIT, we either injected progressive amounts of air (from 20 to 500 mL) through chest tubes or applied large positive end-expiratory pressure (PEEP) increments to simulate extreme lung overdistension. This first data set was used to calibrate an EIT-based pneumothorax detection algorithm. Subsequently, we evaluated the real-time performance of the detection algorithm in 21 additional animals (with normal or preinjured lungs), submitted to multiple ventilatory interventions or traumatic punctures of the lung. Measurements and Main Results: Primary EIT relative images were acquired online (50 images/sec) and processed according to a few imaging-analysis routines running automatically and in parallel. Pneumothoraces as small as 20 mL could be detected with a sensitivity of 100% and specificity 95% and could be easily distinguished from parenchymal overdistension induced by PEEP or recruiting maneuvers, Their location was correctly identified in all cases, with a total delay of only three respiratory cycles. Conclusions. We created an EIT-based algorithm capable of detecting early signs of pneumothoraces in high-risk situations, which also identifies its location. It requires that the pneumothorax occurs or enlarges at least minimally during the monitoring period. Such detection was operator-free and in quasi real-time, opening opportunities for improving patient safety during mechanical ventilation.

Deuterium Equilibrium Time in Saliva of Newborn Infants

There is an increasing interest about the use of stable isotopes for body composition analysis in pediatrics. To ensure the success of total body water analysis by the deuterium dilution method, it is fundamental to determine the equilibrium tune (plateau) of deuterium in the body fluid studied. Objectives: We report here the equilibration time of deuterium oxide in the saliva of newborns after oral intake of the isotope. Methods: Twenty healthy term newborn infants, 10 males and 10 females, were analyzed. Saliva was collected from each newborn before the oral administration of a 100 mg/kg dose of deuterium oxide (baseline sample) and then at 1-hour intervals for 5 hours after administration. Deuterium enrichment of saliva was determined by isotope ratio mass spectrometry according to the recommendations of the International Atomic Energy Agency. Results: The plateau time of deuterium in saliva occurred 3 hours after oral administration of the stable isotope. Conclusion: These data are essential for further studies on the body composition of newborn infants. To the best of our knowledge, this is the first study regarding the equilibration time of deuterium in the saliva of term newborns. JPGN 48:471-474, 2009.

The Cochaperone BAG2 Sweeps Paired Helical Filament-Insoluble Tau from the Microtubule

Tau inclusions are a prominent feature of many neurodegenerative diseases including Alzheimer`s disease. Their accumulation in neurons as ubiquitinated filaments suggests a failure in the degradation limb of the Tau pathway. The components of a Tau protein triage system consisting of CHIP/Hsp70 and other chaperones have begun to emerge. However, the site of triage and the master regulatory elements are unknown. Here, we report an elegant mechanism of Tau degradation involving the cochaperone BAG2. The BAG2/Hsp70 complex is tethered to the microtubule and this complex can capture and deliver Tau to the proteasome for ubiquitin-independent degradation. This complex preferentially degrades Sarkosyl insoluble Tau and phosphorylated Tau. BAG2 levels in cells are under the physiological control of the microRNA miR-128a, which can tune paired helical filament Tau levels in neurons. Thus, we propose that ubiquitinated Tau inclusions arise due to shunting of Tau degradation toward a less efficient ubiquitin-dependent pathway.

CspC and CspD are essential for Caulobacter crescentus stationary phase survival

The cold shock response in bacteria involves the expression of low-molecular weight cold shock proteins (CSPs) containing a nucleic acid-binding cold shock domain (CSD), which are known to destabilize secondary structures on mRNAs, facilitating translation at low temperatures. Caulobacter crescentus cspA and cspB are induced upon cold shock, while cspC and cspD are induced during stationary phase. In this work, we determined a new coding sequence for the cspC gene, revealing that it encodes a protein containing two CSDs. The phenotypes of C. crescentus csp mutants were analyzed, and we found that cspC is important for cells to maintain viability during extended periods in stationary phase. Also, cspC and cspCD strains presented altered morphology, with frequent non-viable filamentous cells, and cspCD also showed a pronounced cell death at late stationary phase. In contrast, the cspAB mutant presented increased viability in this phase, which is accompanied by an altered expression of both cspC and cspD, but the triple cspABD mutant loses this characteristic. Taken together, our results suggest that there is a hierarchy of importance among the csp genes regarding stationary phase viability, which is probably achieved by a fine tune balance of the levels of these proteins.

An incremental space to visualize dynamic data sets

In Information Visualization, adding and removing data elements can strongly impact the underlying visual space. We have developed an inherently incremental technique (incBoard) that maintains a coherent disposition of elements from a dynamic multidimensional data set on a 2D grid as the set changes. Here, we introduce a novel layout that uses pairwise similarity from grid neighbors, as defined in incBoard, to reposition elements on the visual space, free from constraints imposed by the grid. The board continues to be updated and can be displayed alongside the new space. As similar items are placed together, while dissimilar neighbors are moved apart, it supports users in the identification of clusters and subsets of related elements. Densely populated areas identified in the incSpace can be efficiently explored with the corresponding incBoard visualization, which is not susceptible to occlusion. The solution remains inherently incremental and maintains a coherent disposition of elements, even for fully renewed sets. The algorithm considers relative positions for the initial placement of elements, and raw dissimilarity to fine tune the visualization. It has low computational cost, with complexity depending only on the size of the currently viewed subset, V. Thus, a data set of size N can be sequentially displayed in O(N) time, reaching O(N (2)) only if the complete set is simultaneously displayed.

Evolutionary tuning of SVM parameter values in multiclass problems

Support vector machines (SVMs) were originally formulated for the solution of binary classification problems. In multiclass problems, a decomposition approach is often employed, in which the multiclass problem is divided into multiple binary subproblems, whose results are combined. Generally, the performance of SVM classifiers is affected by the selection of values for their parameters. This paper investigates the use of genetic algorithms (GAs) to tune the parameters of the binary SVMs in common multiclass decompositions. The developed GA may search for a set of parameter values common to all binary classifiers or for differentiated values for each binary classifier. (C) 2008 Elsevier B.V. All rights reserved.

Substitutional Impurities in PPV Crystals: An Intrinsic Donor-Acceptor System for High V(oc) Photovoltaic Devices

Defects are usually present in organic polymer films and are commonly invoked to explain the low efficiency obtained in organic-based optoelectronic devices. We propose that controlled insertion of substitutional impurities may, on the contrary, tune the optoelectronic properties of the underivatized organic material and, in the case studied here, maximize the efficiency of a solar cell. We investigate a specific oxygen-impurity substitution, the keto-defect -(CH(2)-C=O)- in underivatized crystalline poly(p-phenylenevinylene) (PPV), and its impact on the electronic structure of the bulk film, through a combined classical (force-field) and quantum mechanical (DFT) approach. We find defect states which suggest a spontaneous electron hole separation typical of a donor acceptor interface, optimal for photovoltaic devices. Furthermore, the inclusion of oxygen impurities does not introduce defect states in the gap and thus, contrary to standard donor-acceptor systems, should preserve the intrinsic high open circuit voltage (V(oc)) that may be extracted from PPV-based devices.