Upconversion in Nd(3+)-doped glasses: Microscopic theory and spectroscopic measurements

In this work, we report a systematic investigation of upconversion losses and their effects on fluorescence quantum efficiency and fractional thermal loading in Nd(3+)-doped fluoride glasses. The energy transfer upconversion (gamma(up)) parameter, which describes upconversion losses, was experimentally determined using different methods: thermal lens (TL) technique and steady state luminescence (SSL) measurements. Additionally, the upconversion parameter was also obtained from energy transfer models and excited state absorption measurements. The results reveal that the microscopic treatment provided by the energy transfer models is similar to the macroscopic ones achieved from the TL and SSL measurements because similar gamma(up) parameters were obtained. Besides, the achieved results also point out the migration-assisted energy transfer according to diffusion-limited regime rather than hopping regime as responsible for the upconversion losses in Nd-doped glasses. (c) 2008 American Institute of Physics.

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.

Feature selection environment for genomic applications

Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e., for dimensionality reduction). There are many genomic and proteomic applications that rely on feature selection to answer questions such as selecting signature genes which are informative about some biological state, e. g., normal tissues and several types of cancer; or inferring a prediction network among elements such as genes, proteins and external stimuli. In these applications, a recurrent problem is the lack of samples to perform an adequate estimate of the joint probabilities between element states. A myriad of feature selection algorithms and criterion functions have been proposed, although it is difficult to point the best solution for each application. Results: The intent of this work is to provide an open-source multiplataform graphical environment for bioinformatics problems, which supports many feature selection algorithms, criterion functions and graphic visualization tools such as scatterplots, parallel coordinates and graphs. A feature selection approach for growing genetic networks from seed genes ( targets or predictors) is also implemented in the system. Conclusion: The proposed feature selection environment allows data analysis using several algorithms, criterion functions and graphic visualization tools. Our experiments have shown the software effectiveness in two distinct types of biological problems. Besides, the environment can be used in different pattern recognition applications, although the main concern regards bioinformatics tasks.

Context tree selection: A unifying view

Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

Knoop Microhardness and FT-Raman Spectroscopic Evaluation of a Resin-Based Dental Material Light-Cured by an Argon Ion Laser and Halogen Lamp: An in Vitro Study

Objective: The purpose of this study was to evaluate in vitro the Knoop microhardness (Knoop hardness number [KHN]) and the degree of conversion using FT-Raman spectroscopy of a light-cured microhybrid resin composite (Z350-3M-ESPE) Vita shade A3 photopolymerized with a halogen lamp or an argon ion laser. Background Data: Optimal polymerization of resin-based dental materials is important for longevity of restorations in dentistry. Materials and Methods: Thirty specimens were prepared and inserted into a disc-shaped polytetrafluoroethylene mold that was 2.0 mm thick and 3 mm in diameter. The specimens were divided into three groups (n = 10 each). Group 1 (G1) was light-cured for 20 sec with an Optilux 501 halogen light with an intensity of 1000 mW/cm(2). Group 2 (G2) was photopolymerized with an argon laser with a power of 150 mW for 10 sec, and group 3 (G3) was photopolymerized with an argon laser at 200 mW of power for 10 sec. All specimens were stored in distilled water for 24 h at 37 degrees C and kept in lightproof containers. For the KHN test five indentations were made and a depth of 100 mu m was maintained in each specimen. One hundred and fifty readings were obtained using a 25-g load for 45 sec. The degree of conversion values were measured by Raman spectroscopy. KHN and degree of conversion values were obtained on opposite sides of the irradiated surface. KHN and degree of conversion data were analyzed by one-way ANOVA and Tukey tests with statistical significance set at p < 0.05. Results: The results of KHN testing were G1 = 37.428 +/- 4.765; G2 = 23.588 +/- 6.269; and G3 = 21.652 +/- 4.393. The calculated degrees of conversion (DC%) were G1 = 48.57 +/- 2.11; G2 = 43.71 +/- 3.93; and G3 = 44.19 +/- 2.71. Conclusions: Polymerization with the halogen lamp ( G1) attained higher microhardness values than polymerization with the argon laser at power levels of 150 and 200 mW; there was no difference in hardness between the two argon laser groups. The results showed no statistically significant different degrees of conversion for the polymerization of composite samples with the two light sources tested.

Spectroscopic, structural, and functional characterization of the alternative low-spin state of horse heart cytochrome c

The alternative low-spin states of Fe3+ and Fe2+ cytochrome c induced by SDS or AOT/hexane reverse micelles exhibited the heme group in a less rhombic symmetry and were characterized by electron paramagnetic resonance, UV-visible, CD, magnetic CD, fluorescence, and Raman resonance. Consistent with the replacement of Met 80 by another strong field ligand at the sixth heme iron coordination position, Fe3+ ALSScytc exhibited 1-nm Soret band blue shift and e enhancement accompanied by disappearance of the 695-nm charge transfer band. The Raman resonance, CD, and magnetic CD spectra of Fe3+ and Fe2+ ALSScytc exhibited significant changes suggestive of alterations in the heme iron microenvironment and conformation and should not be assigned to unfold because the Trp(59) fluorescence remained quenched by the neighboring heme group. ALSScytc was obtained with His(33) and His(26) carboxyethoxylated horse cytochrome c and with tuna cytochrome c (His(33) replaced by Asn) pointing out Lys(79) as the probable heme iron ligand. Fe3+ ALSScytc retained the capacity to cleave tert-butylhydroperoxide and to be reduced by dithiothreitol and diphenylacetaldehyde but not by ascorbate. Compatible with a more open heme crevice, ALSScytc exhibited a redox potential similar to 200 mV lower than the wild-type protein (1220 mV) and was more susceptible to the attack of free radicals.

Ethanol electrooxidation onto stepped surfaces modified by Ru deposition: electrochemical and spectroscopic studies

Oxidation of ethanol on ruthenium-modified Pt(775) and Pt(332) stepped electrodes has been studied using electrochemical and FTIR techniques. It has been found that the oxidation of ethanol on these electrodes takes place preferentially on the step sites yielding CO(2) as the major final product. The cleavage of the C-C bond, which is the required step to yield CO(2), occurs only on this type of site. The presence of low ruthenium coverages on the step sites promotes the complete oxidation of ethanol since it facilitates the oxidation of CO formed on the step from the cleavage of the C-C bond. However, high ruthenium coverages have an important inhibiting effect since the adatoms block the step sites, which are required for the cleavage of the C-C bond. Under these conditions, the oxidation current diminishes and the major product in the oxidation process is acetic acid, which is the product formed preferentially on the (111) terrace sites.

Electrochemical and spectroscopic studies of ethanol oxidation on Pt stepped surfaces modified by tin adatoms

Ethanol oxidation on platinum stepped surfaces vicinal to the (111) pole modified by tin has been studied to determine the role of this adatom in the oxidation mechanism. Tin has been slowly deposited so that the initial stages of the deposition take place on the step, and deposition on the terrace only occurs when the step has been completely decorated. Voltammetric and chronoamperometric experiments demonstrate that tin on the step catalyzes the oxidation. The maximum enhancement is found when the step is completely decorated by tin. FTIR experiments using normal and isotopically labeled ethanol have been used to elucidate the effect of the tin adatoms in the mechanism. The obtained results indicate that the role of tin is double: (i) when the surface has sites capable of breaking the C-C bond of the molecule, that is, when the step sites are not completely covered by tin, it promotes the oxidation of CO formed from the molecular fragments to CO(2) through a bifunctional mechanism and (ii) it catalyzes the oxidation of ethanol to acetic acid.

MAMMALIAN TARGET OF RAPAMYCIN COMPLEX 1 IS INVOLVED IN DIFFERENTIATION OF REGENERATING MYOFIBERS IN VIVO

This work was undertaken to provide further insight into the role of mammalian target of rapamycin complex 1 (mTORC1) in skeletal muscle regeneration, focusing on myofiber size recovery. Rats were treated or not with rapamycin, an mTORC1 inhibitor. Soleus muscles were then subjected to cryolesion and analyzed 1, 10, and 21 days later. A decrease in soleus myofiber cross-section area on post-cryolesion days 10 and 21 was accentuated by rapamycin, which was also effective in reducing protein synthesis in these freeze-injured muscles. The incidence of proliferating satellite cells during regeneration was unaltered by rapamycin, although immunolabeling for neonatal myosin heavy chain (MHC) was weaker in cryolesion+rapamycin muscles than in cryolesion-only muscles. In addition, the decline in tetanic contraction of freeze-injured muscles was accentuated by rapamycin. This study indicates that mTORC1 plays a key role in the recovery of muscle mass and the differentiation of regenerating myofibers, independently of necrosis and satellite cell proliferation mechanisms. Muscle Nerve 42: 778-787,2010

Control of interceptive actions is based on expectancy of time to target arrival

In this study the hypothesis that interceptive movements are controlled on the basis of expectancy of time to target arrival was tested. The study was conducted through assessment of temporal errors and kinematics of interceptive movements to a moving virtual target. Initial target velocity was kept unchanged in part of the trials, and in the others it was decreased 300 ms before the due time of target arrival at the interception position, increasing in 100 ms time to target arrival. Different probabilities of velocity decrease ranging from 25 to 100% were compared. The results revealed that while there were increasing errors between probabilities of 25 and 75% for unchanged target velocity, the opposite relationship was observed for target velocity decrease. Kinematic analysis indicated that movement timing adjustments to target velocity decrease were made online. These results support the conception that visuomotor integration in the interception of moving targets is mediated by an internal forward model whose weights can be flexibly adjusted according to expectancy of time to target arrival.

Intercepting moving targets: does memory from practice in a specific condition of target displacement affect movement timing?

This investigation aimed at assessing the extent to which memory from practice in a specific condition of target displacement modulates temporal errors and movement timing of interceptive movements. We compared two groups practicing with certainty of future target velocity either in unchanged target velocity or in target velocity decrease. Following practice, both experimental groups were probed in the situations of unchanged target velocity and target velocity decrease either under the context of certainty or uncertainty about target velocity. Results from practice showed similar improvement of temporal accuracy between groups, revealing that target velocity decrease did not disturb temporal movement organization when fully predictable. Analysis of temporal errors in the probing trials indicated that both groups had higher timing accuracy in velocity decrease in comparison with unchanged velocity. Effect of practice was detected by increased temporal accuracy of the velocity decrease group in situations of decreased velocity; a trend consistent with the expected effect of practice was observed for temporal errors in the unchanged velocity group and in movement initiation at a descriptive level. An additional point of theoretical interest was the fast adaptation in both groups to a target velocity pattern different from that practiced. These points are discussed under the perspective of integration of vision and motor control by means of an internal forward model of external motion.

Raspberry (Rubus idaeus L.) wine: Yeast selection, sensory evaluation and instrumental analysis of volatile and other compounds

To evaluate the potential for fermentation of raspberry pulp, sixteen yeast strains (S. cerevisiae and S. bayanus) were studied. Volatile compounds were determined by GC-MS, GC-FID, and GC-PFPD. Ethanol. glycerol and organic acids were determined by HPLC. HPLC-DAD was used to analyse phenolic acids. Sensory analysis was performed by trained panellists. After a screening step, CAT-1, UFLA FW 15 and S. bayanus CBS 1505 were previously selected based on their fermentative characteristics and profile of the metabolites identified. The beverage produced with CAT-1 showed the highest volatile fatty acid concentration (1542.6 mu g/L), whereas the beverage produced with UFLA FIN 15 showed the highest concentration of acetates (2211.1 mu g/L) and total volatile compounds (5835 mu g/L). For volatile sulphur compounds. 566.5 mu g/L were found in the beverage produced with S. bayanus CBS 1505. The lowest concentration of volatile sulphur compounds (151.9 mu g/L) was found for the beverage produced with UFLA FW 15. In the sensory analysis, the beverage produced with UFLA FW 15 was characterised by the descriptors raspberry, cherry, sweet, strawberry, floral and violet. In conclusion, strain UFLA FW 15 was the yeast that produced a raspberry wine with a good chemical and sensory quality. (C) 2010 Elsevier Ltd. All rights reserved.

Selection of new glass-forming compositions in Al-La system using a combination of topological instability and thermodynamic criteria

A combination of an extension of the topological instability ""lambda criterion"" and a thermodynamic criterion were applied to the Al-La system, indicating the best range of compositions for glass formation. Alloy compositions in this range were prepared by melt-spinning and casting in an arc-melting furnace with a wedge-section copper mold. The GFA of these samples was evaluated by X-ray diffraction, differential scanning calorimetry and scanning electron microscopy. The results indicated that the gamma* parameter of compositions with high GFA is higher, corresponding to a range in which the lambda parameter is greater than 0.1, which are compositions far from Al solid solution. A new alloy was identified with the best GFA reported so far for this system, showing a maximum thickness of 286 mu m in a wedge-section copper mold. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

Accelerating autonomous learning by using heuristic selection of actions

This paper investigates how to make improved action selection for online policy learning in robotic scenarios using reinforcement learning (RL) algorithms. Since finding control policies using any RL algorithm can be very time consuming, we propose to combine RL algorithms with heuristic functions for selecting promising actions during the learning process. With this aim, we investigate the use of heuristics for increasing the rate of convergence of RL algorithms and contribute with a new learning algorithm, Heuristically Accelerated Q-learning (HAQL), which incorporates heuristics for action selection to the Q-Learning algorithm. Experimental results on robot navigation show that the use of even very simple heuristic functions results in significant performance enhancement of the learning rate.

Risk-based decision making method for maintenance policy selection of thermal power plant equipment

This study presents a decision-making method for maintenance policy selection of power plants equipment. The method is based on risk analysis concepts. The method first step consists in identifying critical equipment both for power plant operational performance and availability based on risk concepts. The second step involves the proposal of a potential maintenance policy that could be applied to critical equipment in order to increase its availability. The costs associated with each potential maintenance policy must be estimated, including the maintenance costs and the cost of failure that measures the critical equipment failure consequences for the power plant operation. Once the failure probabilities and the costs of failures are estimated, a decision-making procedure is applied to select the best maintenance policy. The decision criterion is to minimize the equipment cost of failure, considering the costs and likelihood of occurrence of failure scenarios. The method is applied to the analysis of a lubrication oil system used in gas turbines journal bearings. The turbine has more than 150 MW nominal output, installed in an open cycle thermoelectric power plant. A design modification with the installation of a redundant oil pump is proposed for lubricating oil system availability improvement. (C) 2009 Elsevier Ltd. All rights reserved.