968 resultados para Signal detection
Resumo:
Glutamine has multiple roles in brain metabolism and its concentration can be altered in various pathological conditions. An accurate knowledge of its concentration is therefore highly desirable to monitor and study several brain disorders in vivo. However, in recent years, several MRS studies have reported conflicting glutamine concentrations in the human brain. A recent hypothesis for explaining these discrepancies is that a short T2 component of the glutamine signal may impact on its quantification at long echo times. The present study therefore aimed to investigate the impact of acquisition parameters on the quantified glutamine concentration using two different acquisition techniques, SPECIAL at ultra-short echo time and MEGA-SPECIAL at moderate echo time. For this purpose, MEGA-SPECIAL was optimized for the first time for glutamine detection. Based on the very good agreement of the glutamine concentration obtained between the two measurements, it was concluded that no impact of a short T2 component of the glutamine signal was detected.
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In this paper, we describe several techniques for detecting tonic pitch value in Indian classical music. In Indian music, the raga is the basic melodic framework and it is built on the tonic. Tonic detection is therefore fundamental for any melodic analysis in Indian classical music. This workexplores detection of tonic by processing the pitch histograms of Indian classic music. Processing of pitch histograms using group delay functions and its ability to amplify certain traits of Indian music in the pitch histogram, is discussed. Three different strategies to detect tonic, namely, the concert method, the template matching and segmented histogram method are proposed. The concert method exploits the fact that the tonic is constant over a piece/concert.templatematchingmethod and segmented histogrammethodsuse the properties: (i) the tonic is always present in the background, (ii) some notes are less inflected and dominant, to detect the tonic of individual pieces. All the three methods yield good results for Carnatic music (90−100% accuracy), while for Hindustanimusic, the templatemethod works best, provided the v¯adi samv¯adi notes for a given piece are known (85%).
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Detection of variations in blood glucose concentrations by pancreatic beta-cells and a subsequent appropriate secretion of insulin are key events in the control of glucose homeostasis. Because a decreased capability to sense glycemic changes is a hallmark of type 2 diabetes, the glucose signalling pathway leading to insulin secretion in pancreatic beta-cells has been extensively studied. This signalling mechanism depends on glucose metabolism and requires the presence of specific molecules such as GLUT2, glucokinase and the K(ATP) channel subunits Kir6.2 and SUR1. Other cells are also able to sense variations in glycemia or in local glucose concentrations and to modulate different physiological functions participating in the general control of glucose and energy homeostasis. These include cells forming the hepatoportal vein glucose sensor, which controls glucose storage in the liver, counterregulation, food intake and glucose utilization by peripheral tissues and neurons in the hypothalamus and brainstem whose firing rates are modulated by local variations in glucose concentrations or, when not protected by a blood-brain barrier, directly by changes in blood glucose levels. These glucose-sensing neurons are involved in the control of insulin and glucagon secretion, food intake and energy expenditure. Here, recent physiological studies performed with GLUT2-/- mice will be described, which indicate that this transporter is essential for glucose sensing by pancreatic beta-cells, by the hepatoportal sensor and by sensors, probably located centrally, which control activity of the autonomic nervous system and stimulate glucagon secretion. These studies may pave the way to a fine dissection of the molecular and cellular components of extra-pancreatic glucose sensors involved in the control of glucose and energy homeostasis.
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In this paper we propose an endpoint detection system based on the use of several features extracted from each speech frame, followed by a robust classifier (i.e Adaboost and Bagging of decision trees, and a multilayer perceptron) and a finite state automata (FSA). We present results for four different classifiers. The FSA module consisted of a 4-state decision logic that filtered false alarms and false positives. We compare the use of four different classifiers in this task. The look ahead of the method that we propose was of 7 frames, which are the number of frames that maximized the accuracy of the system. The system was tested with real signals recorded inside a car, with signal to noise ratio that ranged from 6 dB to 30dB. Finally we present experimental results demonstrating that the system yields robust endpoint detection.
Resumo:
In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.
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Changes in technology have an impact on standard practice, materials, and equipment. The traffic signal industry is constantly producing more energy-efficient and durable equipment, better communications, and more sophisticated detection and monitoring capabilities. Accordingly, this project provides an update to the traffic signal content within the Statewide Urban Design and Specifications (SUDAS) Design Manual and Standard Specifications. This work was completed through a technical advisory committee with a variety of participants representing contractors, the Iowa Department of Transportation, cities, consultants, vendors, and university research and support staff.
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A major problem with holographic optical tweezers (HOTs) is their incompatibility with laser-based position detection methods, such as back-focal-plane interferometry (BFPI). The alternatives generally used with HOTs, like high-speed video tracking, do not offer the same spatial and temporal bandwidths. This has limited the use of this technique in precise quantitative experiments. In this paper, we present an optical trap design that combines digital holography and back-focal-plane displacement detection. We show that, with a particularly simple setup, it is possible to generate a set of multiple holographic traps and an additional static non-holographic trap with orthogonal polarizations and that they can be, therefore, easily separated for measuring positions and forces with the high positional and temporal resolutions of laser-based detection. We prove that measurements from both polarizations contain less than 1% crosstalk and that traps in our setup are harmonic within the typical range. We further tested the instrument in a DNA stretching experiment and we discuss an interesting property of this configuration: the small drift of the differential signal between traps.
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Combining bacterial bioreporters with microfluidics systems holds great promise for in-field detection of chemical or toxicity targets. Recently we showed how Escherichia coli cells engineered to produce a variant of green fluorescent protein after contact to arsenite and arsenate can be encapsulated in agarose beads and incorporated into a microfluidic chip to create a device for in-field detection of arsenic, a contaminant of well known toxicity and carcinogenicity in potable water both in industrialized and developing countries. Cell-beads stored in the microfluidics chip at -20°C retained inducibility up to one month and we were able to reproducibly discriminate concentrations of 10 and 50 μg arsenite per L (the drinking water standards for European countries and the United States, and for the developing countries, respectively) from the blank in less than 200 minutes. We discuss here the reasons for decreasing bioreporter signal development upon increased storage of cell beads but also show how this decrease can be reduced, leading to a faster detection and a longer lifetime of the device.
Resumo:
In order to improve the efficacy and safety of treatments, drug dosage needs to be adjusted to the actual needs of each patient in a truly personalized medicine approach. Key for widespread dosage adjustment is the availability of point-of-care devices able to measure plasma drug concentration in a simple, automated, and cost-effective fashion. In the present work, we introduce and test a portable, palm-sized transmission-localized surface plasmon resonance (T-LSPR) setup, comprised of off-the-shelf components and coupled with DNA-based aptamers specific to the antibiotic tobramycin (467 Da). The core of the T-LSPR setup are aptamer-functionalized gold nanoislands (NIs) deposited on a glass slide covered with fluorine-doped tin oxide (FTO), which acts as a biosensor. The gold NIs exhibit localized plasmon resonance in the visible range matching the sensitivity of the complementary metal oxide semiconductor (CMOS) image sensor employed as a light detector. The combination of gold NIs on the FTO substrate, causing NIs size and pattern irregularity, might reduce the overall sensitivity but confers extremely high stability in high-ionic solutions, allowing it to withstand numerous regeneration cycles without sensing losses. With this rather simple T-LSPR setup, we show real-time label-free detection of tobramycin in buffer, measuring concentrations down to 0.5 μM. We determined an affinity constant of the aptamer-tobramycin pair consistent with the value obtained using a commercial propagating-wave based SPR. Moreover, our label-free system can detect tobramycin in filtered undiluted blood serum, measuring concentrations down to 10 μM with a theoretical detection limit of 3.4 μM. While the association signal of tobramycin onto the aptamer is masked by the serum injection, the quantification of the captured tobramycin is possible during the dissociation phase and leads to a linear calibration curve for the concentrations over the tested range (10-80 μM). The plasmon shift following surface binding is calculated in terms of both plasmon peak location and hue, with the latter allowing faster data elaboration and real-time display of the results. The presented T-LSPR system shows for the first time label-free direct detection and quantification of a small molecule in the complex matrix of filtered undiluted blood serum. Its uncomplicated construction and compact size, together with the remarkable performances, represent a leap forward toward effective point-of-care devices for therapeutic drug concentration monitoring.
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To develop systems in order to detect Alzheimer’s disease we want to use EEG signals. Available database is raw, so the first step must be to clean signals properly. We propose a new way of ICA cleaning on a database recorded from patients with Alzheimer's disease (mildAD, early stage). Two researchers visually inspected all the signals (EEG channels), and each recording's least corrupted (artefact-clean) continuous 20 sec interval were chosen for the analysis. Each trial was then decomposed using ICA. Sources were ordered using a kurtosis measure, and the researchers cleared up to seven sources per trial corresponding to artefacts (eye movements, EMG corruption, EKG, etc), using three criteria: (i) Isolated source on the scalp (only a few electrodes contribute to the source), (ii) Abnormal wave shape (drifts, eye blinks, sharp waves, etc.), (iii) Source of abnormally high amplitude ( �100 �V). We then evaluated the outcome of this cleaning by means of the classification of patients using multilayer perceptron neural networks. Results are very satisfactory and performance is increased from 50.9% to 73.1% correctly classified data using ICA cleaning procedure.
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The enhanced functional sensitivity offered by ultra-high field imaging may significantly benefit simultaneous EEG-fMRI studies, but the concurrent increases in artifact contamination can strongly compromise EEG data quality. In the present study, we focus on EEG artifacts created by head motion in the static B0 field. A novel approach for motion artifact detection is proposed, based on a simple modification of a commercial EEG cap, in which four electrodes are non-permanently adapted to record only magnetic induction effects. Simultaneous EEG-fMRI data were acquired with this setup, at 7T, from healthy volunteers undergoing a reversing-checkerboard visual stimulation paradigm. Data analysis assisted by the motion sensors revealed that, after gradient artifact correction, EEG signal variance was largely dominated by pulse artifacts (81-93%), but contributions from spontaneous motion (4-13%) were still comparable to or even larger than those of actual neuronal activity (3-9%). Multiple approaches were tested to determine the most effective procedure for denoising EEG data incorporating motion sensor information. Optimal results were obtained by applying an initial pulse artifact correction step (AAS-based), followed by motion artifact correction (based on the motion sensors) and ICA denoising. On average, motion artifact correction (after AAS) yielded a 61% reduction in signal power and a 62% increase in VEP trial-by-trial consistency. Combined with ICA, these improvements rose to a 74% power reduction and an 86% increase in trial consistency. Overall, the improvements achieved were well appreciable at single-subject and single-trial levels, and set an encouraging quality mark for simultaneous EEG-fMRI at ultra-high field.
Resumo:
Post-testicular sperm maturation occurs in the epididymis. The ion concentration and proteins secreted into the epididymal lumen, together with testicular factors, are believed to be responsible for the maturation of spermatozoa. Disruption of the maturation of spermatozoa in the epididymis provides a promising strategy for generating a male contraceptive. However, little is known about the proteins involved. For drug development, it is also essential to have tools to study the function of these proteins in vitro. One approach for screening novel targets is to study the secretory products of the epididymis or the G protein-coupled receptors (GPCRs) that are involved in the maturation process of the spermatozoa. The modified Ca2+ imaging technique to monitor release from PC12 pheochromocytoma cells can also be applied to monitor secretory products involved in the maturational processes of spermatozoa. PC12 pheochromocytoma cells were chosen for evaluation of this technique as they release catecholamines from their cell body, thus behaving like endocrine secretory cells. The results of the study demonstrate that depolarisation of nerve growth factor -differentiated PC12 cells releases factors which activate nearby randomly distributed HEL erythroleukemia cells. Thus, during the release process, the ligands reach concentrations high enough to activate receptors even in cells some distance from the release site. This suggests that communication between randomly dispersed cells is possible even if the actual quantities of transmitter released are extremely small. The development of a novel method to analyse GPCR-dependent Ca2+ signalling in living slices of mouse caput epididymis is an additional tool for screening for drug targets. By this technique it was possible to analyse functional GPCRs in the epithelial cells of the ductus epididymis. The results revealed that, both P2X- and P2Y-type purinergic receptors are responsible for the rapid and transient Ca2+ signal detected in the epithelial cells of caput epididymides. Immunohistochemical and reverse transcriptase-polymerase chain reaction (RTPCR) analyses showed the expression of at least P2X1, P2X2, P2X4 and P2X7, and P2Y1 and P2Y2 receptors in the epididymis. Searching for epididymis-specific promoters for transgene delivery into the epididymis is of key importance for the development of specific models for drug development. We used EGFP as the reporter gene to identify proper promoters to deliver transgenes into the epithelial cells of the mouse epididymis in vivo. Our results revealed that the 5.0 kb murine Glutathione peroxidase 5 (GPX5) promoter can be used to target transgene expression into the epididymis while the 3.8 kb Cysteine-rich secretory protein-1 (CRISP-1) promoter can be used to target transgene expression into the testis. Although the visualisation of EGFP in living cells in culture usually poses few problems, the detection of EGFP in tissue sections can be more difficult because soluble EGFP molecules can be lost if the cell membrane is damaged by freezing, sectioning, or permeabilisation. Furthermore, the fluorescence of EGFP is dependent on its conformation. Therefore, fixation protocols that immobilise EGFP may also destroy its usefulness as a fluorescent reporter. We therefore developed a novel tissue preparation and preservation techniques for EGFP. In addition, fluorescence spectrophotometry with epididymal epithelial cells in suspension revealed the expression of functional purinergic, adrenergic, cholinergic and bradykinin receptors in these cell lines (mE-Cap27 and mE-Cap28). In conclusion, we developed new tools for studying the role of the epididymis in sperm maturation. We developed a new technique to analyse GPCR dependent Ca2+ signalling in living slices of mouse caput epididymis. In addition, we improved the method of detecting reporter gene expression. Furthermore, we characterised two epididymis-specific gene promoters, analysed the expression of GPCRs in epididymal epithelial cells and developed a novel technique for measurement of secretion from cells.
Resumo:
A method to detect Apple stem grooving virus (ASGV) based on reverse transcription polymerase chain reaction (RT-PCR) was developed using primers ASGV4F-ASGV4R targeting the viral replicase gene, followed by a sandwich hybridisation, in microtiter plates, for colorimetric detection of the PCR products. The RT-PCR was performed with the Titan™ RT-PCR system, using AMV and diluted crude extracts of apple (Malus domestica) leaf or bark for the first strand synthesis and a mixture of Taq and PWO DNA polymerase for the PCR step. The RT-PCR products is hybridised with both a biotin-labelled capture probe linked to a streptavidin-coated microtiter plate and a digoxigenin (DIG)-labelled detection probe. The complex was detected with an anti-DIG conjugate labelled with alkaline phosphatase. When purified ASGV was added to extracts of plant tissue, as little as 400 fg of the virus was detected with this method. The assay with ASGV4F-ASGV4R primers specifically detected the virus in ASGV-infected apple trees from different origins, whereas no signal was observed with amplification products obtained with primers targeting the coat protein region of the ASGV genome or with primers specific for Apple chlorotic leaf spot virus (ACLSV) and Apple stem pitting virus (ASPV). The technique combines the power of PCR to increase the number of copies of the targeted gene, the specificity of DNA hybridization, and the ease of colorimetric detection and sample handling in microplates.
Resumo:
One of the main problems related to the transport and manipulation of multiphase fluids concerns the existence of characteristic flow patterns and its strong influence on important operation parameters. A good example of this occurs in gas-liquid chemical reactors in which maximum efficiencies can be achieved by maintaining a finely dispersed bubbly flow to maximize the total interfacial area. Thus, the ability to automatically detect flow patterns is of crucial importance, especially for the adequate operation of multiphase systems. This work describes the application of a neural model to process the signals delivered by a direct imaging probe to produce a diagnostic of the corresponding flow pattern. The neural model is constituted of six independent neural modules, each of which trained to detect one of the main horizontal flow patterns, and a last winner-take-all layer responsible for resolving when two or more patterns are simultaneously detected. Experimental signals representing different bubbly, intermittent, annular and stratified flow patterns were used to validate the neural model.