961 resultados para Event Data Recorders


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We present a program (Ragu; Randomization Graphical User interface) for statistical analyses of multichannel event-related EEG and MEG experiments. Based on measures of scalp field differences including all sensors, and using powerful, assumption-free randomization statistics, the program yields robust, physiologically meaningful conclusions based on the entire, untransformed, and unbiased set of measurements. Ragu accommodates up to two within-subject factors and one between-subject factor with multiple levels each. Significance is computed as function of time and can be controlled for type II errors with overall analyses. Results are displayed in an intuitive visual interface that allows further exploration of the findings. A sample analysis of an ERP experiment illustrates the different possibilities offered by Ragu. The aim of Ragu is to maximize statistical power while minimizing the need for a-priori choices of models and parameters (like inverse models or sensors of interest) that interact with and bias statistics.

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We have searched for periodic variations of the electronic recoil event rate in the (2-6) keV energy range recorded between February 2011 and March 2012 with the XENON100 detector, adding up to 224.6 live days in total. Following a detailed study to establish the stability of the detector and its background contributions during this run, we performed an un-binned profile likelihood analysis to identify any periodicity up to 500 days. We find a global significance of less than 1 sigma for all periods suggesting no statistically significant modulation in the data. While the local significance for an annual modulation is 2.8 sigma, the analysis of a multiple-scatter control sample and the phase of the modulation disfavor a dark matter interpretation. The DAMA/LIBRA annual modulation interpreted as a dark matter signature with axial-vector coupling of WIMPs to electrons is excluded at 4.8 sigma.

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Adult male and female Weddell seals (Leptonychotes weddellii) were fitted with Time-depth recorders (TDR) at Drescher Inlet (Riiser Larsen Ice Shelf), eastern Weddell Sea coast, in February 1998. Eight of 15 data sets were selected for analyses to investigate the seals' foraging behaviour (doi:10.1594/PANGAEA.511465, doi:10.1594/PANGAEA.511454, doi:10.1594/PANGAEA.511456, doi:10.1594/PANGAEA.511457, doi:10.1594/PANGAEA.511459, doi:10.1594/PANGAEA.511462, doi:10.1594/PANGAEA.511466, doi:10.1594/PANGAEA.511467). These data sets provided simultaneous dive records of eight seals over eight days. The seals primarily foraged within two depth layers, these being from the sea surface to 160 m where temperature and salinity varied considerably, and from 340 to 450 m near the bottom where temperature was lowest and salinity highest, with little variation. While pelagic and benthic diving occurred during daylight, the seals foraged almost exclusively in the upper water column at night. Trawling during daytime confirmed that Pleuragramma antarcticum were by far the most abundant fish both in the pelagial and close to the bottom. Pelagic night-hauls at 110-170 m depth showed highly variable biomass of P. antarcticum with a peak at around midnight. The temporal changes in the local abundance of P. antarcticum, particularly in the pelagial, may explain the trends in the seals' pelagic and benthic foraging activities. This is the first study which describes the jaw movements of a hunting seal which are presumably indicative of feeding events. Trophic links from the Weddell seal to fish, zooplankton and krill, Euphausia superba, are discussed. Another seven data sets did not overlap substantially with the selected time frame (doi:10.1594/PANGAEA.511458, doi:10.1594/PANGAEA.511460, doi:10.1594/PANGAEA.511464, doi:10.1594/PANGAEA.511468, doi:10.1594/PANGAEA.511469, doi:10.1594/PANGAEA.511453, doi:10.1594/PANGAEA.511463). A total of 25 Weddell seals were immobilised during the study period using a combination of ketamine, xylazine, and diazepam. Seven seals were drugged once, 15 seals two times, and three were drugged three times, coming to a total of 46 immobilisation procedures. Narcoses were terminated with yohimbine (doi:10.1594/PANGAEA.438933).

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To date, big data applications have focused on the store-and-process paradigm. In this paper we describe an initiative to deal with big data applications for continuous streams of events. In many emerging applications, the volume of data being streamed is so large that the traditional ‘store-then-process’ paradigm is either not suitable or too inefficient. Moreover, soft-real time requirements might severely limit the engineering solutions. Many scenarios fit this description. In network security for cloud data centres, for instance, very high volumes of IP packets and events from sensors at firewalls, network switches and routers and servers need to be analyzed and should detect attacks in minimal time, in order to limit the effect of the malicious activity over the IT infrastructure. Similarly, in the fraud department of a credit card company, payment requests should be processed online and need to be processed as quickly as possible in order to provide meaningful results in real-time. An ideal system would detect fraud during the authorization process that lasts hundreds of milliseconds and deny the payment authorization, minimizing the damage to the user and the credit card company.

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Traffic flow time series data are usually high dimensional and very complex. Also they are sometimes imprecise and distorted due to data collection sensor malfunction. Additionally, events like congestion caused by traffic accidents add more uncertainty to real-time traffic conditions, making traffic flow forecasting a complicated task. This article presents a new data preprocessing method targeting multidimensional time series with a very high number of dimensions and shows its application to real traffic flow time series from the California Department of Transportation (PEMS web site). The proposed method consists of three main steps. First, based on a language for defining events in multidimensional time series, mTESL, we identify a number of types of events in time series that corresponding to either incorrect data or data with interference. Second, each event type is restored utilizing an original method that combines real observations, local forecasted values and historical data. Third, an exponential smoothing procedure is applied globally to eliminate noise interference and other random errors so as to provide good quality source data for future work.

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The EPA promulgated the Exceptional Events Rule codifying guidance regarding exclusion of monitoring data from compliance decisions due to uncontrollable natural or exceptional events. This capstone examines documentation systems utilized by agencies requesting data be excluded from compliance decisions due to exceptional events. A screening tool is developed to determine whether an event would meet exceptional event criteria. New data sources are available to enhance analysis but evaluation shows many are unusable in their current form. The EPA and States must collaborate to develop consistent evaluation methodologies documenting exceptional events to improve the efficiency and effectiveness of the new rule. To utilize newer sophisticated data, consistent, user-friendly translation systems must be developed.

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At present a complete mtDNA sequence has been reported for only two hymenopterans, the Old World honey bee, Apis mellifera and the sawfly Perga condei. Among the bee group, the tribe Meliponini (stingless bees) has some distinction due to its Pantropical distribution, great number of species and large importance as main pollinators in several ecosystems, including the Brazilian rain forest. However few molecular studies have been conducted on this group of bees and few sequence data from mitochondrial genomes have been described. In this project, we PCR amplified and sequenced 78% of the mitochondrial genome of the stingless bee Melipona bicolor (Apidae, Meliponini). The sequenced region contains all of the 13 mitochondrial protein-coding genes, 18 of 22 tRNA genes, and both rRNA genes (one of them was partially sequenced). We also report the genome organization (gene content and order), gene translation, genetic code, and other molecular features, such as base frequencies, codon usage, gene initiation and termination. We compare these characteristics of M. bicolor to those of the mitochondrial genome of A. mellifera and other insects. A highly biased A+T content is a typical characteristic of the A. mellifera mitochondrial genome and it was even more extreme in that of M. bicolor. Length and compositional differences between M. bicolor and A. mellifera genes were detected and the gene order was compared. Eleven tRNA gene translocations were observed between these two species. This latter finding was surprising, considering the taxonomic proximity of these two bee tribes. The tRNA Lys gene translocation was investigated within Meliponini and showed high conservation across the Pantropical range of the tribe.

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Fluctuations in the initial geometry of a nucleus-nucleus collision have been recently shown to result in a new type of directed flow (v(1)) that, unlike the usual directed flow, is also present at midrapidity. We compute this new v(1) versus transverse momentum and centrality for Au-Au collisions at RHIC using the hydrodynamic code NeXSPheRIO. We find that the event plane of v(1) is correlated with the angle of the initial dipole of the distribution, as predicted, though with a large dispersion. It is uncorrelated with the reaction plane. Our results are in excellent agreement with results inferred from STAR correlation data.

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The pre-Mesozoic geodynamic evolution of SW Iberia has been investigated on the basis of detailed structural analysis, isotope dating, and petrologic study of high-pressure (HP) rocks, revealing the superposition of several tectonometamorphic events: (1) An HP event older than circa 358 Ma is recorded in basic rocks preserved inside marbles, which suggests subduction of a continental margin. The deformation associated with this stage is recorded by a refractory graphite fabric and noncoaxial mesoscopic structures found within the host metasediments. The sense of shear is top to south, revealing thrusting synthetic with subduction (underthrusting) to the north. (2) Recrystallization before circa 358 Ma is due to a regional-scale thermal episode and magmatism. (3) Noncoaxial deformation with top to north sense of shear in northward dipping large-scale shear zones is associated with pervasive hydration and metamorphic retrogression under mostly greenschist facies. This indicates exhumation by normal faulting in a detachment zone confined to the top to north and north dipping shear zones during postorogenic collapse soon after 358 Ma ago (inversion of earlier top to south thrusts). (4) Static recrystallization at circa 318 Ma is due to regional-scale granitic intrusions. Citation: Rosas, F. M., F. O. Marques, M. Ballevre, and C. Tassinari (2008), Geodynamic evolution of the SW Variscides: Orogenic collapse shown by new tectonometamorphic and isotopic data from western Ossa-Morena Zone, SW Iberia, Tectonics, 27, TC6008, doi:10.1029/2008TC002333.

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Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

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Functional magnetic resonance imaging (FMRI) analysis methods can be quite generally divided into hypothesis-driven and data-driven approaches. The former are utilised in the majority of FMRI studies, where a specific haemodynamic response is modelled utilising knowledge of event timing during the scan, and is tested against the data using a t test or a correlation analysis. These approaches often lack the flexibility to account for variability in haemodynamic response across subjects and brain regions which is of specific interest in high-temporal resolution event-related studies. Current data-driven approaches attempt to identify components of interest in the data, but currently do not utilise any physiological information for the discrimination of these components. Here we present a hypothesis-driven approach that is an extension of Friman's maximum correlation modelling method (Neurolmage 16, 454-464, 2002) specifically focused on discriminating the temporal characteristics of event-related haemodynamic activity. Test analyses, on both simulated and real event-related FMRI data, will be presented.

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The BOLD contrast signal history determined by lagged Unear correlation has a significant contribution to functional connectivity in activation data sets. It has been demonstrated that in resting state fMRI data, the major contribution to synchronous correlation between functionally connected areas arises from low frequency contributions (