Adenylate kinase phosphotransfer communicates cellular energetic signals to ATP-sensitive potassium channels

Transduction of energetic signals into membrane electrical events governs vital cellular functions, ranging from hormone secretion and cytoprotection to appetite control and hair growth. Central to the regulation of such diverse cellular processes are the metabolism sensing ATP-sensitive K+ (KATP) channels. However, the mechanism that communicates metabolic signals and integrates cellular energetics with KATP channel-dependent membrane excitability remains elusive. Here, we identify that the response of KATP channels to metabolic challenge is regulated by adenylate kinase phosphotransfer. Adenylate kinase associates with the KATP channel complex, anchoring cellular phosphotransfer networks and facilitating delivery of mitochondrial signals to the membrane environment. Deletion of the adenylate kinase gene compromised nucleotide exchange at the channel site and impeded communication between mitochondria and KATP channels, rendering cellular metabolic sensing defective. Assigning a signal processing role to adenylate kinase identifies a phosphorelay mechanism essential for efficient coupling of cellular energetics with KATP channels and associated functions.

Scientific bases of human-machine communication by voice.

The scientific bases for human-machine communication by voice are in the fields of psychology, linguistics, acoustics, signal processing, computer science, and integrated circuit technology. The purpose of this paper is to highlight the basic scientific and technological issues in human-machine communication by voice and to point out areas of future research opportunity. The discussion is organized around the following major issues in implementing human-machine voice communication systems: (i) hardware/software implementation of the system, (ii) speech synthesis for voice output, (iii) speech recognition and understanding for voice input, and (iv) usability factors related to how humans interact with machines.

An��lise de acetona em ar exalado: desenvolvimento de m��todo eletroanal��tico e algoritmo para processamento de sinais

Prop��e-se m��todo novo e completo para an��lise de acetona em ar exalado envolvendo coleta com pr��-concentra����o em ��gua, derivatiza����o qu��mica e determina����o eletroqu��mica assistida por novo algoritmo de processamento de sinais. Na literatura recente a acetona expirada vem sendo avaliada como biomarcador para monitoramento n��o invasivo de quadros cl��nicos como diabetes e insufici��ncia card��aca, da�� a import��ncia da proposta. Entre as aminas que reagem com acetona para formar iminas eletroativas, estudadas por polarografia em meados do s��culo passado, a glicina apresentou melhor conjunto de caracter��sticas para a defini����o do m��todo de determina����o por voltametria de onda quadrada sem a necessidade de remo����o de oxig��nio (25 Hz, amplitude de 20 mV, incremento de 5 mV, eletrodo de gota de merc��rio). O meio reacional, composto de glicina (2 mol��L-1) em meio NaOH (1 mol��L-1), serviu tamb��m de eletr��lito e o pico de redu����o da imina em -1,57 V vs. Ag|AgCl constituiu o sinal anal��tico. Para tratamento dos sinais, foi desenvolvido e avaliado um algoritmo inovador baseado em interpola����o de linha base por ajuste de curvas de B��zier e ajuste de gaussiana ao pico. Essa combina����o permitiu reconhecimento e quantifica����o de picos relativamente baixos e largos sobre linha com curvatura acentuada e ru��do, situa����o em que m��todos convencionais falham e curvas do tipo spline se mostraram menos apropriadas. A implementa����o do algoritmo (dispon��vel em http://github.com/batistagl/chemapps) foi realizada utilizando programa open source de ��lgebra matricial integrado diretamente com software de controle do potenciostato. Para demonstrar a generalidade da extens��o dos recursos nativos do equipamento mediante integra����o com programa����o externa em linguagem Octave (open source), implementou-se a t��cnica da cronocoulometria tridimensional, com visualiza����o de resultados j�� tratados em proje����es de malha de perspectiva 3D sob qualquer ��ngulo. A determina����o eletroqu��mica de acetona em fase aquosa, assistida pelo algoritmo baseado em curvas de B��zier, �� r��pida e autom��tica, tem limite de detec����o de 3,5��10-6 mol��L-1 (0,2 mg��L-1) e faixa linear que atende aos requisitos da an��lise em ar exalado. O acetalde��do, comumente presente em ar exalado, em especial, ap��s consumo de bebidas alco��licas, d�� origem a pico voltam��trico em -1,40 V, contornando interfer��ncia que prejudica v��rios outros m��todos publicados na literatura e abrindo possibilidade de determina����o simult��nea. Resultados obtidos com amostras reais s��o concordantes com os obtidos por m��todo espectrofotom��trico, em uso rotineiro desde o seu aperfei��oamento na disserta����o de mestrado do autor desta tese. Em rela����o �� disserta����o, tamb��m se otimizou a geometria do dispositivo de coleta, de modo a concentrar a acetona num volume menor de ��gua gelada e prover maior conforto ao paciente. O m��todo completo apresentado, englobando o dispositivo de amostragem aperfei��oado e o novo e efetivo algoritmo para tratamento autom��tico de sinais voltam��tricos, est�� pronto para ser aplicado. Evolu����o para um analisador port��til depende de melhorias no limite de detec����o e facilidade de obten����o eletrodos s��lidos (impressos) com filme de merc��rio, vez que eletrodos de bismuto ou diamante dopado com boro, entre outros, n��o apresentaram resposta.

Impact of artifact correction methods on R-R interbeat signals to quantifying heart rate variability (HRV) according to linear and nonlinear methods.

In the analysis of heart rate variability (HRV) are used temporal series that contains the distances between successive heartbeats in order to assess autonomic regulation of the cardiovascular system. These series are obtained from the electrocardiogram (ECG) signal analysis, which can be affected by different types of artifacts leading to incorrect interpretations in the analysis of the HRV signals. Classic approach to deal with these artifacts implies the use of correction methods, some of them based on interpolation, substitution or statistical techniques. However, there are few studies that shows the accuracy and performance of these correction methods on real HRV signals. This study aims to determine the performance of some linear and non-linear correction methods on HRV signals with induced artefacts by quantification of its linear and nonlinear HRV parameters. As part of the methodology, ECG signals of rats measured using the technique of telemetry were used to generate real heart rate variability signals without any error. In these series were simulated missing points (beats) in different quantities in order to emulate a real experimental situation as accurately as possible. In order to compare recovering efficiency, deletion (DEL), linear interpolation (LI), cubic spline interpolation (CI), moving average window (MAW) and nonlinear predictive interpolation (NPI) were used as correction methods for the series with induced artifacts. The accuracy of each correction method was known through the results obtained after the measurement of the mean value of the series (AVNN), standard deviation (SDNN), root mean square error of the differences between successive heartbeats (RMSSD), Lomb\'s periodogram (LSP), Detrended Fluctuation Analysis (DFA), multiscale entropy (MSE) and symbolic dynamics (SD) on each HRV signal with and without artifacts. The results show that, at low levels of missing points the performance of all correction techniques are very similar with very close values for each HRV parameter. However, at higher levels of losses only the NPI method allows to obtain HRV parameters with low error values and low quantity of significant differences in comparison to the values calculated for the same signals without the presence of missing points.

M��todo de estimativa de torque da articula����o do joelho baseada em EMG

Este trabalho apresenta um m��todo de estimativa de torque do joelho baseado em sinais eletromiogr��ficos (EMG) durante terapia de reabilita����o rob��tica. Os EMGs, adquiridos de cinco m��sculos envolvidos no movimento de flex��o e extens��o do joelho, s��o processados para encontrar as ativa����es musculares. Em seguida, mediante um modelo simples de contra����o muscular, s��o calculadas as for��as e, usando a geometria da articula����o, o torque do joelho. As fun����es de ativa����o e contra����o musculares possuem par��metros limitados que devem ser calibrados para cada usu��rio, sendo o ajuste feito mediante a minimiza����o do erro entre o torque estimado e o torque medido na articula����o usando a din��mica inversa. S��o comparados dois m��todos iterativos para fun����es n��o-lineares como t��cnicas de otimiza����o restrita para a calibra����o dos par��metros: Gradiente Descendente e Quasi-Newton. O processamento de sinais, calibra����o de par��metros e c��lculo de torque estimado foram desenvolvidos no software MATLAB��; o c��lculo de torque medido foi feito no software OpenSim com sua ferramenta de din��mica inversa.

Sistema para monitoramento e an��lise de paisagens ac��sticas submarinas.

O Monitoramento Ac��stico Passivo (PAM) submarino refere-se ao uso de sistemas de escuta e grava����o subaqu��tica, com o intuito de detectar, monitorar e identificar fontes sonoras atrav��s das ondas de press��o que elas produzem. Se diz que �� passivo j�� que tais sistemas unicamente ouvem, sem perturbam o meio ambiente ac��stico existente, diferentemente de ativos, como os sonares. O PAM submarino tem diversas ��reas de aplica����o, como em sistemas de vigil��ncia militar, seguridade portu��ria, monitoramento ambiental, desenvolvimento de ��ndices de densidade populacional de esp��cies, identifica����o de esp��cies, etc. Tecnologia nacional nesta ��rea �� praticamente inexistente apesar da sua import��ncia. Neste contexto, o presente trabalho visa contribuir com o desenvolvimento de tecnologia nacional no tema atrav��s da concep����o, constru����o e opera����o de equipamento aut��nomo de PAM e de m��todos de processamento de sinais para detec����o automatizada de eventos ac��sticos submarinos. Foi desenvolvido um equipamento, nomeado OceanPod, que possui caracter��sticas como baixo custo de fabrica��c~ao, flexibilidade e facilidade de configura����o e uso, voltado para a pesquisa cient��fica, industrial e para controle ambiental. V��rios prot��tipos desse equipamento foram constru��dos e utilizados em miss��es no mar. Essas jornadas de monitoramento permitiram iniciar a cria����o de um banco de dados ac��stico, o qual permitiu fornecer a mat��ria prima para o teste de detectores de eventos ac��sticos automatizados e em tempo real. Adicionalmente tamb��m �� proposto um novo m��todo de detec����o-identifica����o de eventos ac��sticos, baseado em an��lise estat��stica da representa����o tempo-frequ��ncia dos sinais ac��sticos. Este novo m��todo foi testado na detec����o de cet��ceos, presentes no banco de dados gerado pelas miss��es de monitoramento.

Modelagem de sinais neuronais utilizando filtros lineares de tempo discreto.

A aquisi����o experimental de sinais neuronais �� um dos principais avan��os da neuroci��ncia. Por meio de observa����es da corrente e do potencial el��tricos em uma regi��o cerebral, �� poss��vel entender os processos fisiol��gicos envolvidos na gera����o do potencial de a����o, e produzir modelos matem��ticos capazes de simular o comportamento de uma c��lula neuronal. Uma pr��tica comum nesse tipo de experimento �� obter leituras a partir de um arranjo de eletrodos posicionado em um meio compartilhado por diversos neur��nios, o que resulta em uma mistura de sinais neuronais em uma mesma s��rie temporal. Este trabalho prop��e um modelo linear de tempo discreto para o sinal produzido durante o disparo do neur��nio. Os coeficientes desse modelo s��o calculados utilizando-se amostras reais dos sinais neuronais obtidas in vivo. O processo de modelagem concebido emprega t��cnicas de identifica����o de sistemas e processamento de sinais, e �� dissociado de considera����es sobre o funcionamento biof��sico da c��lula, fornecendo uma alternativa de baixa complexidade para a modelagem do disparo neuronal. Al��m disso, a representa����o por meio de sistemas lineares permite idealizar um sistema inverso, cuja fun����o �� recuperar o sinal original de cada neur��nio ativo em uma mistura extracelular. Nesse contexto, s��o discutidas algumas solu����es baseadas em filtros adaptativos para a simula����o do sistema inverso, introduzindo uma nova abordagem para o problema de separa����o de spikes neuronais.

Electroencephalogram based Causality Graph Analysis in Behavior Tasks of Parkinson���s Disease Patients

Electroencephalographic (EEG) signals of the human brains represent electrical activities for a number of channels recorded over a the scalp. The main purpose of this thesis is to investigate the interactions and causality of different parts of a brain using EEG signals recorded during a performance subjects of verbal fluency tasks. Subjects who have Parkinson's Disease (PD) have difficulties with mental tasks, such as switching between one behavior task and another. The behavior tasks include phonemic fluency, semantic fluency, category semantic fluency and reading fluency. This method uses verbal generation skills, activating different Broca's areas of the Brodmann's areas (BA44 and BA45). Advanced signal processing techniques are used in order to determine the activated frequency bands in the granger causality for verbal fluency tasks. The graph learning technique for channel strength is used to characterize the complex graph of Granger causality. Also, the support vector machine (SVM) method is used for training a classifier between two subjects with PD and two healthy controls. Neural data from the study was recorded at the Colorado Neurological Institute (CNI). The study reveals significant difference between PD subjects and healthy controls in terms of brain connectivities in the Broca's Area BA44 and BA45 corresponding to EEG electrodes. The results in this thesis also demonstrate the possibility to classify based on the flow of information and causality in the brain of verbal fluency tasks. These methods have the potential to be applied in the future to identify pathological information flow and causality of neurological diseases.

Efficient sampling of band-limited signals from sine wave crossings

This correspondence presents an efficient method for reconstructing a band-limited signal in the discrete domain from its crossings with a sine wave. The method makes it possible to design A/D converters that only deliver the crossing timings, which are then used to interpolate the input signal at arbitrary instants. Potentially, it may allow for reductions in power consumption and complexity in these converters. The reconstruction in the discrete domain is based on a recently-proposed modification of the Lagrange interpolator, which is readily implementable with linear complexity and efficiently, given that it re-uses known schemes for variable fractional-delay (VFD) filters. As a spin-off, the method allows one to perform spectral analysis from sine wave crossings with the complexity of the FFT. Finally, the results in the correspondence are validated in several numerical examples.

Estimation Models for Nonuniformly Sampled Signals���Application to Multiple Delay Estimation

This letter presents a method to model propagation channels for estimation, in which the sampling scheme can be arbitrary. Additionally, the method yields accurate models, with a size that converges to the channel duration, measured in Nyquist periods. It can be viewed as an improvement on the usual discretization based on regular sampling at the Nyquist rate. The method is introduced in the context of multiple delay estimation using the MUSIC estimator, and is assessed through a numerical example.

Adjustable compression method for still JPEG images

There are a large number of image processing applications that work with different performance requirements and available resources. Recent advances in image compression focus on reducing image size and processing time, but offer no real-time solutions for providing time/quality flexibility of the resulting image, such as using them to transmit the image contents of web pages. In this paper we propose a method for encoding still images based on the JPEG standard that allows the compression/decompression time cost and image quality to be adjusted to the needs of each application and to the bandwidth conditions of the network. The real-time control is based on a collection of adjustable parameters relating both to aspects of implementation and to the hardware with which the algorithm is processed. The proposed encoding system is evaluated in terms of compression ratio, processing delay and quality of the compressed image when compared with the standard method.

Parametrized Architecture for Hough Transform Recursive Evaluation

Paper submitted to International Workshop on Spectral Methods and Multirate Signal Processing (SMMSP), Barcelona, Espa��a, 2003.

FFT Interpolation From Nonuniform Samples Lying in a Regular Grid

This paper presents a method to interpolate a periodic band-limited signal from its samples lying at nonuniform positions in a regular grid, which is based on the FFT and has the same complexity order as this last algorithm. This kind of interpolation is usually termed ���the missing samples problem��� in the literature, and there exists a wide variety of iterative and direct methods for its solution. The one presented in this paper is a direct method that exploits the properties of the so-called erasure polynomial and provides a significant improvement on the most efficient method in the literature, which seems to be the burst error recovery (BER) technique of Marvasti���s The paper includes numerical assessments of the method���s stability and complexity.

Estimation of Time-Limited Channel Spectra From Nonuniform Samples

This paper deals with the estimation of a time-invariant channel spectrum from its own nonuniform samples, assuming there is a bound on the channel���s delay spread. Except for this last assumption, this is the basic estimation problem in systems providing channel spectral samples. However, as shown in the paper, the delay spread bound leads us to view the spectrum as a band-limited signal, rather than the Fourier transform of a tapped delay line (TDL). Using this alternative model, a linear estimator is presented that approximately minimizes the expected root-mean-square (RMS) error for a deterministic channel. Its main advantage over the TDL is that it takes into account the spectrum���s smoothness (time width), thus providing a performance improvement. The proposed estimator is compared numerically with the maximum likelihood (ML) estimator based on a TDL model in pilot-assisted channel estimation (PACE) for OFDM.

Proceedings of the Institution of Electrical Engineers.

Vols.1-87,1872-1940 also called no.1-258.