Africanized honey bees are efficient at detecting, uncapping and removing dead brood

The hygienic behavior of honey bees is based on a two-step process, including uncapping and removing diseased, dead, damaged, or parasitized brood inside the cell. We evaluated during periods of 1 h the time that hygienic and non-hygienic colonies of Africanized honey bees spend to detect, uncap and remove pin-killed brood using comb inserts with transparent walls placed in observation hives. We observed that hygienic colonies are significantly faster in detecting, uncapping and removing dead brood in the cells (P < 0.001).

Determination of the Most Efficient Temperature for Radiofrequency Ablation of Renal Cells: A Prospective Study in Dogs

Background and Purpose: Radiofrequency (RF) ablation of renal tumors is a major technique for tumor cell destruction while preserving healthy renal parenchyma. There is no consensus in the literature regarding the optimal temperature, impedance, and time for RF application for effective cell destruction. This study investigated two variables while keeping time unchanged: Temperature for RF cell destruction and tissue impedance in dog kidneys. Materials and Methods: Sixteen dogs had renal punctures through videolaparoscopy for RF interstitial tissue ablation. A RF generator was applied for 10 minutes to the dog's kidney at different target temperatures: 80 degrees C, 90 degrees C, and 100 degrees C. On postoperative day14, the animals were sacrificed and nephrectomized. All lesions were macroscopically and microscopically examined. The bioelectrical impedance was evaluated at three different temperatures. Results: Renal injuries were wider and deeper at 90 degrees C (P < 0.001), and they were similar at 80 degrees C and 100 degrees C. The bioelectrical impedance was lower at 90 degrees C than at the temperatures of 80 degrees C and 100 degrees C (P < 0.001). Viable cells in the RF ablation tissue area were not found in the microscopic examination. Conclusion: The most effective cell destruction in terms of width and depth was achieved at 90 degrees C, which was also the optimal temperature for tissue impedance. RF ablation of renal cells eliminated all viable cells.

Continental passive microwave-based rainfall estimation algorithm: Application to the Amazon Basin

This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.

Bayesian online algorithms for learning in discrete Hidden Markov Models

We propose and analyze two different Bayesian online algorithms for learning in discrete Hidden Markov Models and compare their performance with the already known Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalization we draw learning curves in simplified situations for these algorithms and compare their performances.

Organic molecule assembled between carbon nanotubes: A highly efficient switch device

We report a highly efficient switch built from an organic molecule assembled between single-wall carbon nanotube electrodes. We theoretically show that changes in the distance between the electrodes alter the molecular conformation within the gap, affecting in a dramatic way the electronic and charge transport properties, with an on/off ratio larger than 300. This opens up the perspective of combining molecular electronics with carbon nanotubes, bringing great possibilities for the design of nanodevices.

Lossless filter for multiple repeats with bounded edit distance

Background: Identifying local similarity between two or more sequences, or identifying repeats occurring at least twice in a sequence, is an essential part in the analysis of biological sequences and of their phylogenetic relationship. Finding such fragments while allowing for a certain number of insertions, deletions, and substitutions, is however known to be a computationally expensive task, and consequently exact methods can usually not be applied in practice. Results: The filter TUIUIU that we introduce in this paper provides a possible solution to this problem. It can be used as a preprocessing step to any multiple alignment or repeats inference method, eliminating a possibly large fraction of the input that is guaranteed not to contain any approximate repeat. It consists in the verification of several strong necessary conditions that can be checked in a fast way. We implemented three versions of the filter. The first is simply a straightforward extension to the case of multiple sequences of an application of conditions already existing in the literature. The second uses a stronger condition which, as our results show, enable to filter sensibly more with negligible (if any) additional time. The third version uses an additional condition and pushes the sensibility of the filter even further with a non negligible additional time in many circumstances; our experiments show that it is particularly useful with large error rates. The latter version was applied as a preprocessing of a multiple alignment tool, obtaining an overall time (filter plus alignment) on average 63 and at best 530 times smaller than before (direct alignment), with in most cases a better quality alignment. Conclusion: To the best of our knowledge, TUIUIU is the first filter designed for multiple repeats and for dealing with error rates greater than 10% of the repeats length.

omega-Transaminases as efficient biocatalysts to obtain novel chiral selenium-amine ligands for Pd-catalysis

omega-Transaminases have been evaluated as biocatalysts in the reductive amination of organoselenium acetophenones to the corresponding amines, and in the kinetic resolution of racemic organoselenium amines. Kinetic resolution proved to be more efficient than the asymmetric reductive amination. By using these methodologies we were able to obtain both amine enantiomers in high enantiomeric excess (up to 99%). Derivatives of the obtained optically pure o-selenium 1-phenylethyl amine were evaluated as ligands in the palladium-catalyzed asymmetric alkylation, giving the alkylated product in up to 99% ee.

Gold is not a Faradaic-Efficient Borohydride Oxidation Electrocatalyst: An Online Electrochemical Mass Spectrometry Study

Direct borohydride fuel cells are promising high energy density portable generators. However, their development remains limited by the complexity of the anodic reaction: The borohydride oxidation reaction (BOR) kinetics is slow and occurs at high overvoltages, while it may compete with the heterogeneous hydrolysis of BH(4)(-). Nevertheless, one usually admits that gold is rather inactive toward the heterogeneous hydrolysis of BH(4)(-) and presents some activity regarding the BOR, therefore yielding to the complete eight-electron BOR. In the present paper, by coupling online mass spectrometry to electrochemistry, we in situ monitored the H(2) yield during BOR experiments on sputtered gold electrodes. Our results show non-negligible H(2) generation on Au on the whole BOR potential range (0-0.8 V vs reversible hydrogen electrode), thus revealing that gold cannot be considered as a faradaic-efficient BOR electrocatalyst. We further propose a relevant reaction pathway for the BOR on gold that accounts for these findings.

Mechanistic studies of the 'blue' Cu enzyme, bilirubin oxidase, as a highly efficient electrocatalyst for the oxygen reduction reaction

The 'blue copper' enzyme bilirubin oxidase from Myrothecium verrucaria shows significantly enhanced adsorption on a pyrolytic graphite 'edge' (PGE) electrode that has been covalently modified with naphthyl-2-carboxylate functionalities by diazonium coupling. Modified electrodes coated with bilirubin oxidase show electrocatalytic voltammograms for the direct, four-electron reduction of O(2) by bilirubin oxidase with up to four times the current density of an unmodified PGE electrode. Electrocatalytic voltammograms measured with a rapidly rotating electrode (to remove effects of O(2) diffusion limitation) have a complex shape (an almost linear dependence of current on potential below pH 6) that is similar regardless of how PGE is chemically modified. Importantly, the same waveform is observed if bilirubin oxidase is adsorbed on Au(111) or Pt(111) single-crystal electrodes (at which activity is short-lived). The electrocatalytic behavior of bilirubin oxidase, including its enhanced response on chemically-modified PGE, therefore reflects inherent properties that do not depend on the electrode material. The variation of voltammetric waveshapes and potential-dependent (O(2)) Michaelis constants with pH and analysis in terms of the dispersion model are consistent with a change in rate-determining step over the pH range 5-8: at pH 5, the high activity is limited by the rate of interfacial redox cycling of the Type 1 copper whereas at pH 8 activity is much lower and a sigmoidal shape is approached, showing that interfacial electron transfer is no longer a limiting factor. The electrocatalytic activity of bilirubin oxidase on Pt(111) appears as a prominent pre-wave to electrocatalysis by Pt surface atoms, thus substantiating in a single, direct experiment that the minimum overpotential required for O(2) reduction by the enzyme is substantially smaller than required at Pt. At pH 8, the onset of O(2) reduction lies within 0.14 V of the four-electron O(2)/2H(2)O potential.

Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

Efficient method for obtaining Lep(ob)/Lep(ob)-derived animal models using adipose tissue transplantations

Background: Leptin-deficient mice (Lep(ob)/Lep(ob), also known as ob/ob) are of great importance for studies of obesity, diabetes and other correlated pathologies. Thus, generation of animals carrying the Lep(ob) gene mutation as well as additional genomic modifications has been used to associate genes with metabolic diseases. However, the infertility of Lep(ob)/Lep(ob) mice impairs this kind of breeding experiment. Objective: To propose a new method for production of Lep(ob)/Lep(ob) animals and Lep(ob)/Lep(ob)-derived animal models by restoring the fertility of Lep(ob)/Lep(ob) mice in a stable way through white adipose tissue transplantations. Methods: For this purpose, 1 g of peri-gonadal adipose tissue from lean donors was used in subcutaneous transplantations of Lep(ob)/Lep(ob) animals and a crossing strategy was established to generate Lep(ob)/Lep(ob)-derived mice. Results: The presented method reduced by four times the number of animals used to generate double transgenic models (from about 20 to 5 animals per double mutant produced) and minimized the number of genotyping steps (from 3 to 1 genotyping step, reducing the number of Lep gene genotyping assays from 83 to 6). Conclusion: The application of the adipose transplantation technique drastically improves both the production of Lep(ob)/Lep(ob) animals and the generation of Lep(ob)/Lep(ob)-derived animal models. International Journal of Obesity (2009) 33, 938-944; doi: 10.1038/ijo.2009.95; published online 16 June 2009

GOOAL: A routine based on Genetic Algorithms to track harmonics in electric power systems

Voltage and current waveforms of a distribution or transmission power system are not pure sinusoids. There are distortions in these waveforms that can be represented as a combination of the fundamental frequency, harmonics and high frequency transients. This paper presents a novel approach to identifying harmonics in power system distorted waveforms. The proposed method is based on Genetic Algorithms, which is an optimization technique inspired by genetics and natural evolution. GOOAL, a specially designed intelligent algorithm for optimization problems, was successfully implemented and tested. Two kinds of representations concerning chromosomes are utilized: binary and real. The results show that the proposed method is more precise than the traditional Fourier Transform, especially considering the real representation of the chromosomes.

Hybrid Algorithms for Routing and Assignment Wavelengths in Optical Networks

This paper presents a strategy for the solution of the WDM optical networks planning. Specifically, the problem of Routing and Wavelength Allocation (RWA) in order to minimize the amount of wavelengths used. In this case, the problem is known as the Min-RWA. Two meta-heuristics (Tabu Search and Simulated Annealing) are applied to take solutions of good quality and high performance. The key point is the degradation of the maximum load on the virtual links in favor of minimization of number of wavelengths used; the objective is to find a good compromise between the metrics of virtual topology (load in Gb/s) and of the physical topology (quantity of wavelengths). The simulations suggest good results when compared to some existing in the literature.

Information Filtering and Array Algorithms for Discrete-Time Markovian Jump Linear Systems

This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided.

A Taxonomy for Locality Algorithms on Peer-to-Peer Networks

The continuous growth of peer-to-peer networks has made them responsible for a considerable portion of the current Internet traffic. For this reason, improvements in P2P network resources usage are of central importance. One effective approach for addressing this issue is the deployment of locality algorithms, which allow the system to optimize the peers` selection policy for different network situations and, thus, maximize performance. To date, several locality algorithms have been proposed for use in P2P networks. However, they usually adopt heterogeneous criteria for measuring the proximity between peers, which hinders a coherent comparison between the different solutions. In this paper, we develop a thoroughly review of popular locality algorithms, based on three main characteristics: the adopted network architecture, distance metric, and resulting peer selection algorithm. As result of this study, we propose a novel and generic taxonomy for locality algorithms in peer-to-peer networks, aiming to enable a better and more coherent evaluation of any individual locality algorithm.