971 resultados para Round Robin Database Measurement Archive
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Resonant sensors and crystal oscillators for mass detection need to be excited at very high natural frequencies (MHz). Use of such systems to measure mass of biological materials affects the accuracy of mass measurement due to their viscous and/or viscoelastic properties. The measurement limitation of such sensor system is the difficulty in accounting for the ``missing mass'' of the biological specimen in question. A sensor system has been developed in this work, to be operated in the stiffness controlled region at very low frequencies as compared to its fundamental natural frequency. The resulting reduction in the sensitivity due to non-resonant mode of operation of this sensor is compensated by the high resolution of the sensor. The mass of different aged drosophila melanogaster (fruit fly) is measured. The difference in its mass measurement during resonant mode of operation is also presented. That, viscosity effects do not affect the working of this non-resonant mass sensor is clearly established by direct comparison. (C) 2014 AIP Publishing LLC.
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In the present work, we report a novel, in vivo, noninvasive technique to determine radial arterial compliance using the radial arterial pressure pulse waveform (RAPPW) acquired by fiber Bragg grating pulse recorder (FBGPR). The radial arterial compliance of the subject can be measured during sphygmomanometric examination by the unique signatures of arterial diametrical variations and the beat-to-beat pulse pressure acquired simultaneously from the RAPPW recorded using FBGPR. This proposed technique has been validated against the radial arterial diametrical measurements obtained from the color Doppler ultrasound. Two distinct trials have been illustrated in this work and the results from both techniques have been found to be in good agreement with each other.
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Background: Haemophilus influenzae (H. Influenzae) is the causative agent of pneumonia, bacteraemia and meningitis. The organism is responsible for large number of deaths in both developed and developing countries. Even-though the first bacterial genome to be sequenced was that of H. Influenzae, there is no exclusive database dedicated for H. Influenzae. This prompted us to develop the Haemophilus influenzae Genome Database (HIGDB). Methods: All data of HIGDB are stored and managed in MySQL database. The HIGDB is hosted on Solaris server and developed using PERL modules. Ajax and JavaScript are used for the interface development. Results: The HIGDB contains detailed information on 42,741 proteins, 18,077 genes including 10 whole genome sequences and also 284 three dimensional structures of proteins of H. influenzae. In addition, the database provides ``Motif search'' and ``GBrowse''. The HIGDB is freely accessible through the URL:http://bioserverl.physicslisc.ernetin/HIGDB/. Discussion: The HIGDB will be a single point access for bacteriological, clinical, genomic and proteomic information of H. influenzae. The database can also be used to identify DNA motifs within H. influenzae genomes and to compare gene or protein sequences of a particular strain with other strains of H. influenzae. (C) 2014 Elsevier Ltd. All rights reserved.
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Streptococcus pneumoniae causes pneumonia, septicemia and meningitis. S. pneumoniae is responsible for significant mortality both in children and in the elderly. In recent years, the whole genome sequencing of various S. pneumoniae strains have increased manifold and there is an urgent need to provide organism specific annotations to the scientific community. This prompted us to develop the Streptococcus pneumoniae Genome Database (SPGDB) to integrate and analyze the completely sequenced and available S. pneumoniae genome sequences. Further, links to several tools are provided to compare the pool of gene and protein sequences, and proteins structure across different strains of S. pneumoniae. SPGDB aids in the analysis of phenotypic variations as well as to perform extensive genomics and evolutionary studies with reference to S. pneumoniae. (C) 2014 Elsevier Inc. All rights reserved.
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Most of the signals recorded in experiments are inevitably contaminated by measurement noise. Hence, it is important to understand the effect of such noise on estimating causal relations between such signals. A primary tool for estimating causality is Granger causality. Granger causality can be computed by modeling the signal using a bivariate autoregressive (AR) process. In this paper, we greatly extend the previous analysis of the effect of noise by considering a bivariate AR process of general order p. From this analysis, we analytically obtain the dependence of Granger causality on various noise-dependent system parameters. In particular, we show that measurement noise can lead to spurious Granger causality and can suppress true Granger causality. These results are verified numerically. Finally, we show how true causality can be recovered numerically using the Kalman expectation maximization algorithm.
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SARAS is a correlation spectrometer connected to a frequency independent antenna that is purpose-designed for precision measurements of the radio background at long wavelengths. The design, calibration, and observing strategies admit solutions for the internal additive contributions to the radiometer response, and hence a separation of these contaminants from the antenna temperature. We present here a wideband measurement of the radio sky spectrum by SARAS that provides an accurate measurement of the absolute brightness and spectral index between 110 and 175MHz. Accuracy in the measurement of absolute sky brightness is limited by systematic errors of magnitude 1.2%; errors in calibration and in the joint estimation of sky and system model parameters are relatively smaller. We use this wide-angle measurement of the sky brightness using the precision wide-band dipole antenna to provide an improved absolute calibration for the 150 MHz all-sky map of Landecker and Wielebinski: subtracting an offset of 21.4 K and scaling by a factor of 1.05 will reduce the overall offset error to 8 K (from 50 K) and scale error to 0.8% (from 5%). The SARAS measurement of the temperature spectral index is in the range -2.3 to -2.45 in the 110-175MHz band and indicates that the region toward the Galactic bulge has a relatively flatter index.
Bayesian parameter identification in dynamic state space models using modified measurement equations
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When Markov chain Monte Carlo (MCMC) samplers are used in problems of system parameter identification, one would face computational difficulties in dealing with large amount of measurement data and (or) low levels of measurement noise. Such exigencies are likely to occur in problems of parameter identification in dynamical systems when amount of vibratory measurement data and number of parameters to be identified could be large. In such cases, the posterior probability density function of the system parameters tends to have regions of narrow supports and a finite length MCMC chain is unlikely to cover pertinent regions. The present study proposes strategies based on modification of measurement equations and subsequent corrections, to alleviate this difficulty. This involves artificial enhancement of measurement noise, assimilation of transformed packets of measurements, and a global iteration strategy to improve the choice of prior models. Illustrative examples cover laboratory studies on a time variant dynamical system and a bending-torsion coupled, geometrically non-linear building frame under earthquake support motions. (C) 2015 Elsevier Ltd. All rights reserved.
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We report a novel 1D J-edited pure shift NMR experiment (J-PSHIFT) that was constructed from a pseudo 2D experiment for the direct measurement of proton-proton scalar couplings. The experiment gives homonuclear broad-band H-1-decoupled H-1 NMR spectra, which provide a single peak for chemically distinct protons, and only retain the homonuclear-scalar-coupled doublet pattern at the chemical-shift positions of the protons in the coupled network of a specific proton. This permits the direct and unambiguous measurement of the magnitudes of the couplings. The incorporation of a 1D selective correlation spectroscopy (COSY)/ total correlation spectroscopy (TOCSY) block in lieu of the initial selective pulse, results in the exclusive detection of the correlated spectrum of a specific proton.
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A new 2D NMR technique cited as CH-RES-TOCSY, for complete unraveling the spectra of enantiomers and for the measurement of structurally important C-HRDC sis reported. The spectral overlap and complexity of peaks were reduced by the blend of selective excitation and homo-decoupling. Differential values of C-H RDCs of enantiomers (R and S) are exploited to separate the enantiomeric peaks. The complete unraveling of the spectra of both the enantiomers is achieved by incorporating a TOCSY mixing blockprior to signal acquisition. The additional application of the method is demonstrated for the assignment of symmetric isomers. (C) 2015 Elsevier B.V. All rights reserved.
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Measurement of the self-coupling of the 125 GeV Higgs boson is one of the most crucial tasks for a high luminosity run of the LHC, and it can only be measured in the di-Higgs final state. In the minimal supersymmetric standard model, heavy CP even Higgs (H) can decay into a lighter 125 GeV Higgs boson (h) and, therefore, can influence the rate of di-Higgs production. We investigate the role of single H production in the context of measuring the self-coupling of h. We have found that the H -> hh decay can change the value of Higgs (h) self-coupling substantially, in a low tan beta regime where the mass of the heavy Higgs boson lies between 250 and 600 GeV and, depending on the parameter space, it may be seen as an enhancement of the self-coupling of the 125 GeV Higgs boson.
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The seasonality and mutual dependence of aerosol optical properties and cloud condensation nuclei (CCN) activity under varying meteorological conditions at the high-altitude Nainital site (2km) in the Indo-Gangetic Plains were examined using nearly year-round measurements (June 2011 to March 2012) at the Atmospheric Radiation Measurement mobile facility as part of the Regional Aerosol Warming Experiment-Ganges Valley Aerosol Experiment of the Indian Space Research Organization and the U.S. Department of Energy. The results from collocated measurements provided enhanced aerosol scattering and absorption coefficients, CCN concentrations, and total condensation nuclei concentrations during the dry autumn and winter months. The CCN concentration (at a supersaturation of 0.46) was higher during the periods of high aerosol absorption (single scattering albedo (SSA)<0.80) than during the periods of high aerosol scattering (SSA>0.85), indicating that the aerosol composition seasonally changes and influences the CCN activity. The monthly mean CCN activation ratio (at a supersaturation of 0.46) was highest (>0.7) in late autumn (November); this finding is attributed to the contribution of biomass-burning aerosols to CCN formation at high supersaturation conditions.
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The high species richness of tropical forests has long been recognized, yet there remains substantial uncertainty regarding the actual number of tropical tree species. Using a pantropical tree inventory database from closed canopy forests, consisting of 657,630 trees belonging to 11,371 species, we use a fitted value of Fisher's alpha and an approximate pantropical stem total to estimate the minimum number of tropical forest tree species to fall between similar to 40,000 and similar to 53,000, i.e., at the high end of previous estimates. Contrary to common assumption, the Indo-Pacific region was found to be as species-rich as the Neotropics, with both regions having a minimum of similar to 19,000-25,000 tree species. Continental Africa is relatively depauperate with a minimum of similar to 4,500-6,000 tree species. Very few species are shared among the African, American, and the Indo-Pacific regions. We provide a methodological framework for estimating species richness in trees that may help refine species richness estimates of tree-dependent taxa.
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The present study reports a noninvasive technique for the measurement of the pulse transit time differential (PTTD) from the pulse pressure waveforms obtained at the carotid artery and radial artery using fiber Bragg grating pulse recorders (FBGPR). PTTD is defined as the time difference between the arrivals of a pulse pressure waveform at the carotid and radial arterial sites. The PTTD is investigated as an indicator of variation in the systolic blood pressure. The results are validated against blood pressure variation obtained from a Mindray Patient Monitor. Furthermore, the pulse wave velocity computed from the obtained PTTD is compared with the pulse wave velocity obtained from the color Doppler ultrasound system and is found to be in good agreement. The major advantage of the PTTD measurement via FBGPRs is that the data acquisition system employed can simultaneously acquire pulse pressure waveforms from both FBGPRs placed at carotid and radial arterial sites with a single time scale, which eliminates time synchronization complexity. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)
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Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVNI classifier gives promising results.