908 resultados para Feature detector


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We present the concept of a sensitive and broadband resonant mass gravitational wave detector. A massive sphere is suspended inside a second hollow one. Short, high-finesse Fabry-Perot optical cavities read out the differential displacements of the two spheres as their quadrupole modes are excited. At cryogenic temperatures, one approaches the standard quantum limit for broadband operation with reasonable choices for the cavity finesses and the intracavity light power. A molybdenum detector, of overall size of 2 m, would reach spectral strain sensitivities of 2x10-23Hz-1/2 between 1000 and 3000 Hz.

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In this paper we propose an innovative methodology for automated profiling of illicit tablets bytheir surface granularity; a feature previously unexamined for this purpose. We make use of the tinyinconsistencies at the tablet surface, referred to as speckles, to generate a quantitative granularity profileof tablets. Euclidian distance is used as a measurement of (dis)similarity between granularity profiles.The frequency of observed distances is then modelled by kernel density estimation in order to generalizethe observations and to calculate likelihood ratios (LRs). The resulting LRs are used to evaluate thepotential of granularity profiles to differentiate between same-batch and different-batches tablets.Furthermore, we use the LRs as a similarity metric to refine database queries. We are able to derivereliable LRs within a scope that represent the true evidential value of the granularity feature. Thesemetrics are used to refine candidate hit-lists form a database containing physical features of illicittablets. We observe improved or identical ranking of candidate tablets in 87.5% of cases when granularityis considered.

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The purpose of this article was to review the strategies to control patient dose in adult and pediatric computed tomography (CT), taking into account the change of technology from single-detector row CT to multi-detector row CT. First the relationships between computed tomography dose index, dose length product, and effective dose in adult and pediatric CT are revised, along with the diagnostic reference level concept. Then the effect of image noise as a function of volume computed tomography dose index, reconstructed slice thickness, and the size of the patient are described. Finally, the potential of tube current modulation CT is discussed.

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Drosophila avoid food contaminated by pathogenic bacteria and fungi using an olfactory pathway that is exquisitely tuned to a single microbial odour.

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The aim of this study was to provide an insight into normative values of the ascending aorta in regards to novel endovascular procedures using ECG-gated multi-detector CT angiography. Seventy-seven adult patients without ascending aortic abnormalities were evaluated. Measurements at relevant levels of the aortic root and ascending aorta were obtained. Diameter variations of the ascending aorta during cardiac cycle were also considered. Mean diameters (mm) were as follows: LV outflow tract 20.3 +/- 3.4, coronary sinus 34.2 +/- 4.1, sino-tubular junction 29.7 +/- 3.4 and mid ascending aorta 32.7 +/- 3.8 with coefficients of variation (CV) ranging from 12 to 17%. Mean distances (mm) were: from the plane passing through the proximal insertions of the aortic valve cusps to the right brachio-cephalic artery (BCA) 92.6 +/- 11.8, from the plane passing through the proximal insertions of the aortic valve cusps to the proximal coronary ostium 12.1 +/- 3.7, and between both coronary ostia 7.2 +/- 3.1, minimal arc of the ascending aorta from left coronary ostium to right BCA 52.9 +/- 9.5, and the fibrous continuity between the aortic valve and the anterior leaflet of the mitral valve 14.6 +/- 3.3, CV 13-43%. Mean aortic valve area was 582.0 +/- 131.9 mm(2). The variation of the antero-posterior and transverse diameters of the ascending aorta during the cardiac cycle were 8.4% and 7.3%, respectively. Results showed large inter-individual variations in diameters and distances but with limited intra-individual variations during the cardiac cycle. A personalized approach for planning endovascular devices must be considered.

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Individuals harboring germ-line DICER1 mutations are predisposed to a rare cancer syndrome, the DICER1 Syndrome or pleuropulmonary blastoma-familial tumor and dysplasia syndrome [online Mendelian inheritance in man (OMIM) #601200]. In addition, specific somatic mutations in the DICER1 RNase III catalytic domain have been identified in several DICER1-associated tumor types. Pituitary blastoma (PitB) was identified as a distinct entity in 2008, and is a very rare, potentially lethal early childhood tumor of the pituitary gland. Since the discovery by our team of an inherited mutation in DICER1 in a child with PitB in 2011, we have identified 12 additional PitB cases. We aimed to determine the contribution of germ-line and somatic DICER1 mutations to PitB. We hypothesized that PitB is a pathognomonic feature of a germ-line DICER1 mutation and that each PitB will harbor a second somatic mutation in DICER1. Lymphocyte or saliva DNA samples ascertained from ten infants with PitB were screened and nine were found to harbor a heterozygous germ-line DICER1 mutation. We identified additional DICER1 mutations in nine of ten tested PitB tumor samples, eight of which were confirmed to be somatic in origin. Seven of these mutations occurred within the RNase IIIb catalytic domain, a domain essential to the generation of 5p miRNAs from the 5' arm of miRNA-precursors. Germ-line DICER1 mutations are a major contributor to PitB. Second somatic DICER1 "hits" occurring within the RNase IIIb domain also appear to be critical in PitB pathogenesis.

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This study investigated the development of all 3 components of episodic memory (EM), as defined by Tulving, namely, core factual content, spatial context, and temporal context. To this end, a novel, ecologically valid test was administered to 109 participants aged 4-16 years. Results showed that each EM component develops at a different rate. Ability to memorize factual content emerges early, whereas context retrieval abilities continue to improve until adolescence, due to persistent encoding difficulties (isolated by comparing results on free recall and recognition tasks). Exploration of links with other cognitive functions revealed that short-term feature-binding abilities contribute to all EM components, and executive functions to temporal and spatial context, although ability to memorize temporal context is predicted mainly by age.

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The Hi·Art II Helical TomoTherapy (HT) unit is equipped with a built-in onboard MVCT detector used for patient imaging and beam monitoring. Our aim was to study the detector stability for treatment beam measurements. We studied the MVCT detector response with the 6 MV photon beam over time, throughout short-term (during an irradiation) and long-term (two times 50 days) periods. Our results show a coefficient of variation ≤ 1% for detector chambers inside the beam (excluding beam gradients) for short- and long-term response of the MVCT detector. Larger variations were observed in beam gradients and an influence of the X-ray target where degradation was found. The results assume that an 'air scan' procedure is performed daily to recalibrate the detector with the imaging beam. On short term, the detector response stability is comparable to other devices. Long-term measure- ments during two 50-day periods show a good reproducibility. 

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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.

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In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.

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BACKGROUND: As the long-term survival of pancreatic head malignancies remains dismal, efforts have been made for a better patient selection and a tailored treatment. Tumour size could also be used for patient stratification. METHODS: One hundred and fourteen patients underwent a pancreaticoduodenectomy for pancreatic adenocarcinoma, peri-ampullary and biliary cancer stratified according to: ≤20 mm, 21-34 mm, 35-45 mm and >45 mm tumour size. RESULTS: Patients with tumour sizes of ≤20 mm had a N1 rate of 41% and a R1/2 rate of 7%. The median survival was 3.4 years. N1 and R1/2 rates increased to 84% and 31% for tumour sizes of 21-34 mm (P = 0.0002 for N, P = 0.02 for R). The median survival decreased to 1.6 years (P = 0.0003). A further increase in tumour size of 35-45 mm revealed a further increase of N1 and R1/2 rates of 93% (P < 0.0001) and 33%, respectively. The median survival was 1.2 years (P = 0.004). Tumour sizes >45 mm were related to a further decreased median survival of 1.1 years (P = 0.2), whereas N1 and R1/2 rates were 87% and 20%, respectively. DISCUSSION: Tumour size is an important feature of pancreatic head malignancies. A tumour diameter of 20 mm seems to be the cut-off above which an increased rate of incomplete resections and metastatic lymph nodes must be encountered and the median survival is reduced.

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This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.