942 resultados para Detecting


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Real-time battery impedance spectrum is acquired using a one-time record. Fast Summation Transformation (FST) is a parallel method of acquiring a real-time battery impedance spectrum using a one-time record that enables battery diagnostics. An excitation current to a battery is a sum of equal amplitude sine waves of frequencies that are octave harmonics spread over a range of interest. A sample frequency is also octave and harmonically related to all frequencies in the sum. The time profile of this signal has a duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known and octave and harmonically related, a simple algorithm, FST, processes the time record by rectifying relative to the sine and cosine of each frequency. Another algorithm yields real and imaginary components for each frequency.

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Methods of rapidly measuring an impedance spectrum of an energy storage device in-situ over a limited number of logarithmically distributed frequencies are described. An energy storage device is excited with a known input signal, and aresponse is measured to ascertain the impedance spectrum. An excitation signal is a limited time duration sum-of-sines consisting of a select number offrequencies. In one embodiment, magnitude and phase of each frequency ofinterest within the sum-of-sines is identified when the selected frequencies and sample rate are logarithmic integer steps greater than two. This technique requires a measurement with a duration of one period of the lowest frequency. In another embodiment, where selected frequencies are distributed in octave steps, the impedance spectrum can be determined using a captured time record that is reduced to a half-period of the lowest frequency.

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Real time battery impedance spectrum is acquired using one time record, Compensated Synchronous Detection (CSD). This parallel method enables battery diagnostics. The excitation current to a test battery is a sum of equal amplitude sin waves of a few frequencies spread over range of interest. The time profile of this signal has duration that is a few periods of the lowest frequency. The voltage response of the battery, average deleted, is the impedance of the battery in the time domain. Since the excitation frequencies are known, synchronous detection processes the time record and each component, both magnitude and phase, is obtained. For compensation, the components, except the one of interest, are reassembled in the time domain. The resulting signal is subtracted from the original signal and the component of interest is synchronously detected. This process is repeated for each component.

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The accuracy of Global Positioning System (GPS) time series is degraded by the presence of offsets. To assess the effectiveness of methods that detect and remove these offsets, we designed and managed the Detection of Offsets in GPS Experiment. We simulated time series that mimicked realistic GPS data consisting of a velocity component, offsets, white and flicker noises (1/f spectrum noises) composed in an additive model. The data set was made available to the GPS analysis community without revealing the offsets, and several groups conducted blind tests with a range of detection approaches. The results show that, at present, manual methods (where offsets are hand picked) almost always give better results than automated or semi‒automated methods (two automated methods give quite similar velocity bias as the best manual solutions). For instance, the fifth percentile range (5% to 95%) in velocity bias for automated approaches is equal to 4.2 mm/year (most commonly ±0.4 mm/yr from the truth), whereas it is equal to 1.8 mm/yr for the manual solutions (most commonly 0.2 mm/yr from the truth). The magnitude of offsets detectable by manual solutions is smaller than for automated solutions, with the smallest detectable offset for the best manual and automatic solutions equal to 5 mm and 8 mm, respectively. Assuming the simulated time series noise levels are representative of real GPS time series, robust geophysical interpretation of individual site velocities lower than 0.2–0.4 mm/yr is therefore certainly not robust, although a limit of nearer 1 mm/yr would be a more conservative choice. Further work to improve offset detection in GPS coordinates time series is required before we can routinely interpret sub‒mm/yr velocities for single GPS stations.

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Background Accidental poisoning is one of the leading causes of injury in the United States, second only to motor vehicle accidents. According to the Centers for Disease Control and Prevention, the rates of accidental poisoning mortality have been increasing in the past fourteen years nationally. In Texas, mortality rates from accidental poisoning have mirrored national trends, increasing linearly from 1981 to 2001. The purpose of this study was to determine if there are spatiotemporal clusters of accidental poisoning mortality among Texas counties, and if so, whether there are variations in clustering and risk according to gender and race/ethnicity. The Spatial Scan Statistic in combination with GIS software was used to identify potential clusters between 1980 and 2001 among Texas counties, and Poisson regression was used to evaluate risk differences. Results Several significant (p < 0.05) accidental poisoning mortality clusters were identified in different regions of Texas. The geographic and temporal persistence of clusters was found to vary by racial group, gender, and race/gender combinations, and most of the clusters persisted into the present decade. Poisson regression revealed significant differences in risk according to race and gender. The Black population was found to be at greatest risk of accidental poisoning mortality relative to other race/ethnic groups (Relative Risk (RR) = 1.25, 95% Confidence Interval (CI) = 1.24 – 1.27), and the male population was found to be at elevated risk (RR = 2.47, 95% CI = 2.45 – 2.50) when the female population was used as a reference. Conclusion The findings of the present study provide evidence for the existence of accidental poisoning mortality clusters in Texas, demonstrate the persistence of these clusters into the present decade, and show the spatiotemporal variations in risk and clustering of accidental poisoning deaths by gender and race/ethnicity. By quantifying disparities in accidental poisoning mortality by place, time and person, this study demonstrates the utility of the spatial scan statistic combined with GIS and regression methods in identifying priority areas for public health planning and resource allocation.

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The purpose of this study was to determine the perception and knowledge of targeted ultrasound in women who screen positive for Down syndrome in the first or second trimester, and to assess the perceived detection rate of Down syndrome by targeted ultrasound in this population. While several studies have reported patient perceptions’ of routine ultrasound, no study has specifically examined knowledge regarding the targeted ultrasound and its role in detecting Down syndrome. A targeted ultrasound is a special ultrasound during the second trimester offered to women who may be at a higher-than-average risk of having a baby with some type of birth defect or complication. The purpose of the ultrasound is to evaluate the overall growth and development of the baby as well as screen for birth defects and genetic conditions. Women under the age of 35 referred for an abnormal first or second trimester maternal serum screen to several Houston area clinics were asked to complete a questionnaire to obtain demographic and ultrasound knowledge information as well as assess perceived detection rate of Down syndrome by ultrasound. Seventy-seven women completed the questionnaire and participated in the study. Our findings revealed that women have limited background knowledge about the targeted ultrasound and its role in detecting Down syndrome. These findings are consistent with other studies that have reported a lack of understanding about the purpose of ultrasound examinations. One factor that seems to increase background knowledge about the targeted ultrasound is individuals having a higher level of education. However, most participants regardless of race, education, income, and exposure to targeted ultrasound information did not know the capabilities of a targeted ultrasound. This study confirmed women lack background knowledge about the targeted ultrasound and do not know enough about the technology to form a perception regarding its ability to detect Down syndrome. Additional studies to identify appropriate education techniques are necessary to determine how to best inform our patient population about targeted ultrasound.

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DNA mediated gene transfection is an important tool for moving and isolating genes from one cell type and putting them into a foreign genetic background. DNA transfection studies have been done routinely in many laboratories to identify and isolate transforming sequences in human tumors and tumor cell lines. A second technique, microcell-mediated chromosome transfer, allows the transfer of small numbers of intact human chromosome from one cell to another. This work was done to compare the efficiency of these two techniques in the transformation of NIH 3T3 mouse fibroblast cells.^ My intent in comparing these two techniques was to see if there was a difference in the transforming capability of DNA which has been purified of all associated protein and RNAs, and that of DNA which is introduced into a cell in its native form, the chromosome. If chromosomal sequences were capable of transforming the 3T3 cells in culture, the method could then be used as a way to isolate the relevant tumorigenic chromosomes from human tumors.^ The study shows, however, that even for those cell lines that contain transforming sequences identified by DNA-mediated gene transfer, those same sequences were unable to transform 3T3 cells when introduced to the cells by somatic fusion of human tumor microcells. I believe that the human transforming sequences in their original genetic conformation are not recognized by the mouse cell as genes which should be expressed; therefore, no noticeable transformation event was selected by this technique. ^

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Quantitative EEG (qEEG) has modified our understanding of epileptic seizures, shifting our view from the traditionally accepted hyper-synchrony paradigm toward more complex models based on re-organization of functional networks. However, qEEG measurements are so far rarely considered during the clinical decision-making process. To better understand the dynamics of intracranial EEG signals, we examine a functional network derived from the quantification of information flow between intracranial EEG signals. Using transfer entropy, we analyzed 198 seizures from 27 patients undergoing pre-surgical evaluation for pharmaco-resistant epilepsy. During each seizure we considered for each network the in-, out- and total "hubs", defined respectively as the time and the EEG channels with the maximal incoming, outgoing or total (bidirectional) information flow. In the majority of cases we found that the hubs occur around the middle of seizures, and interestingly not at the beginning or end, where the most dramatic EEG signal changes are found by visual inspection. For the patients who then underwent surgery, good postoperative clinical outcome was on average associated with a higher percentage of out- or total-hubs located in the resected area (for out-hubs p = 0.01, for total-hubs p = 0.04). The location of in-hubs showed no clear predictive value. We conclude that the study of functional networks based on qEEG measurements may help to identify brain areas that are critical for seizure generation and are thus potential targets for focused therapeutic interventions.

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The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

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Analogies may arise from the conscious detection of similarities between a present and a past situation. In this functional magnetic resonance imaging study, we tested whether young volunteers would detect analogies unconsciously between a current supraliminal (visible) and a past subliminal (invisible) situation. The subliminal encoding of the past situation precludes awareness of analogy detection in the current situation. First, participants encoded subliminal pairs of unrelated words in either one or nine encoding trials. Later, they judged the semantic fit of supraliminally presented new words that either retained a previously encoded semantic relation (“analog”) or not (“broken analog”). Words in analogs versus broken analogs were judged closer semantically, which indicates unconscious analogy detection. Hippocampal activity associated with subliminal encoding correlated with the behavioral measure of unconscious analogy detection. Analogs versus broken analogs were processed with reduced prefrontal but enhanced medial temporal activity. We conclude that analogous episodes can be detected even unconsciously drawing on the episodic memory network.

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Endovascular aortic repair (EVAR) necessitates lifelong surveillance for the patient, in order to detect complications timely. Endoleaks (ELs) are among the most common complications of EVAR. Especially type II ELs can have a very unpredictable clinical course and this can range from spontaneous sealing to aortic rupture. Subgroups of this type of EL need to be identified in order to make a proper risk stratification. Aim of this review is to describe the existing imaging techniques, including their advantages and disadvantages in the context of post-EVAR surveillance with a particular emphasis on low-flow ELs. Low flow ELs cause pressurization of the aortic aneurysm sac with a low velocity filling, leading to difficulty of detection by routine imaging protocols for EVAR surveillance, e.g. bi- or triphasic multislice computed tomographic angiography, magnetic resonance imaging and contrast enhanced ultrasound. In this article, we review the imaging possibilities of ELs and discuss the different imaging strategies available for depicting low flow ELs.