343 research outputs found
AM/FM signal estimation with micro-segmentation and polynomial fit
Cataloged from PDF version of article.Amplitude and phase estimation of AM/FM signals with parametric polynomial representation require the polynomial orders for phase and amplitude to be known. But in reality, they are not known and have to be estimated. A well-known method for estimation is the higher-order ambiguity function (HAF) or its variants. But the HAF method has several reported drawbacks such as error propagation and slowly varying or even constant amplitude assumption. Especially for the long duration time-varying signals like AM/FM signals, which require high orders for the phase and amplitude, computational load is very heavy due to nonlinear optimization involving many variables. This paper utilizes a micro-segmentation approach where the length of segment is selected such that the amplitude and instantaneous frequency (IF) is constant over the segment. With this selection first, the amplitude and phase estimates for each micro-segment are obtained optimally in the LS sense, and then, these estimates are concatenated to obtain the overall
amplitude and phase estimates. The initial estimates are not optimal but sufficiently close to the optimal solution for subsequent processing. Therefore, by using the initial estimates, the overall polynomial orders for the amplitude and phase are estimated. Using estimated orders, the initial amplitude
and phase functions are fitted to the polynomials to obtain the final signal. The method does not use any multivariable nonlinear optimization and is efficient in the sense that the MSE performance is close enough to the Cramer–Rao bound. Simulation examples are presented
Tribological interaction between polytetrafluoroethylene and silicon oxide surfaces
Cataloged from PDF version of article.We investigated the tribological interaction between polytetrafluoroethylene (PTFE) and silicon oxide surfaces. A simple rig was designed to bring about a friction between the surfaces via sliding a piece of PTFE on a thermally oxidized silicon wafer specimen. A very mild inclination (similar to 0.5 degrees) along the sliding motion was also employed in order to monitor the tribological interaction in a gradual manner as a function of increasing contact force. Additionally, some patterns were sketched on the silicon oxide surface using the PTFE tip to investigate changes produced in the hydrophobicity of the surface, where the approximate water contact angle was 45 degrees before the transfer. The nature of the transferred materials was characterized by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). XPS results revealed that PTFE was faithfully transferred onto the silicon oxide surface upon even at the slightest contact and SEM images demonstrated that stable morphological changes could be imparted onto the surface. The minimum apparent contact pressure to realize the PTFE transfer is estimated as 5 kPa, much lower than reported previously. Stability of the patterns imparted towards many chemical washing processes lead us to postulate that the interaction is most likely to be chemical. Contact angle measurements, which were carried out to characterize and monitor the hydrophobicity of the silicon oxide surface, showed that upon PTFE transfer the hydrophobicity of the SiO2 surface could be significantly enhanced, which might also depend upon the pattern sketched onto the surface. Contact angle values above 100 degrees were obtained. (C) 2014 AIP Publishing LLC
A new approach to time-frequency localized signal design
A novel approach is presented for the design of signals in Wigner Domain. In this method, the desired signal features in the time-frequency domain are specified in two stages. First the user specifies the spine curve around which the energy of the desired signal is distributed in the time-frequency plane. Then, the user specifies the spread of the desired signal energy around the spine. In addition to this fundamentally new way of defining the time-frequency features of the desired signal, the actual synthesis of the signal is performed in a warped fractional Fourier transform approach [1]. After obtaining the designed signal, it is transformed back to the original time domain providing the final result of the new signal synthesis technique. In contrast to the conventional algorithms, the proposed method provides very good results even if the inner cross-term structure of the desired signal is not specified
Space weather studies of IONOLAB group
IONOLAB is an interdisciplinary research group dedicated for handling the challenges of near earth environment on communication, positioning and remote sensing systems. IONOLAB group contributes to the space weather studies by developing state-of-the-art analysis and imaging techniques. On the website of IONOLAB group, www.ionolab.org, four unique space weather services, namely, IONOLAB-TEC, IRI-PLAS-2015, IRI-PLAS-MAP and IRI-PLAS-STEC, are provided in a user friendly graphical interface unit. Newly developed algorithm for ionospheric tomography, IONOLAB-CIT, provides not only 3-D electron density but also tracking of ionospheric state with high reliability and fidelity. The algorithm for ray tracing through ionosphere, IONOLAB-RAY, provides a simulation environment in all communication bands. The background ionosphere is generated in voxels where IRI-Plas electron density is used to obtain refractive index. One unique feature is the possible update of ionospheric state by insertion of Total Electron Content (TEC) values into IRI-Plas. Both ordinary and extraordinary paths can be traced with high ray and low ray scenarios for any desired date, time and transmitter location. 2-D regional interpolation and mapping algorithm, IONOLAB-MAP, is another tool of IONOLAB group where automatic TEC maps with Kriging algorithm are generated from GPS network with high spatio-temporal resolution. IONOLAB group continues its studies in all aspects of ionospheric and plasmaspheric signal propagation, imaging and mapping. © 2016 IEEE
Accurate automated quantitative imaging of tortoise erythrocytes using the NIS image analysis system
The standard method for assessing blood cell characteristics using an ocular micrometer is time-consuming and limited. We used the Nikon NIS Elements imaging software and May-Grünwald-Giemsa staining to determine whether automated image analysis is suitable for rapid and accurate quantitative morphometry of erythrocytes. Blood was collected during four seasons from 126 geometric tortoises and the blood smears were evaluated for cell (C) and nuclear (N) characteristics of the erythrocytes. We measured area, length (L), width (W), perimeter, elongation and pixelation intensity, and calculated L/W and N/C areas. Erythrocyte size differed among cohorts; females, the larger sex, had smaller erythrocytes than either males or juveniles. Males had more elongated erythrocytes than females and erythrocytes of adults were more elongated than those of juveniles. Erythrocyte size and shape influence the efficiency of gas exchange owing to surface area to volume ratios, which are greater for small, elongated cells than for large, round cells. The high N/C ratio and low pixelation intensities of males and juveniles indicate that they may have had more immature erythrocytes in their circulation than females. The use of pixelation intensity to indicate the presence of immature erythrocytes was validated by seasonal differences that corresponded to the biology of the tortoises. Pixelation intensity was lowest in winter. We found that automated image analysis is a rapid and reliable method for determining cell size and shape, and it offers the potential for distinguishing among developmental stages that differ in staining intensity. The method should be useful for rapid health assessments, particularly of threatened species, and for comparative studies among different vertebrates.Web of Scienc
Status of Pandemic Influenza Vaccination and Factors Affecting It in Pregnant Women in Kahramanmaras, an Eastern Mediterranean City of Turkey
BACKGROUND: Pregnant women are a target group for receipt of influenza vaccine because there appears to be an elevated mortality and morbidity rate associated with influenza virus infection in pregnant women. The goal of this study is to determine the factors affecting the decisions of pregnant women in Turkey to be vaccinated or not for 2009 H1N1 influenza. METHODOLOGY: We enrolled 314 of 522 (60.2%) pregnant women who attended to the antenatal clinics of the Medical Faculty of Kahramanmaras Sutcuimam University's Department of Gynecology and Obstetrics between December 23, 2009, and February 1, 2010. We developed a 48-question survey which was completed in a face-to-face interview at the clinic with each pregnant woman. PRINCIPAL FINDINGS: Of the 314 pregnant women, 27.4% were in the first trimester, 33.8% were in the second trimester, and 38.8% were in the third trimester. Twenty-eight pregnant women (8.9%) got vaccinated. Of all the women interviewed, 68.5% stated that they were comfortable with their decisions about the vaccine, 7.3% stated they were not comfortable, and 24.2% stated that they were hesitant about their decisions. The probability of receiving the 2009 H1N1 vaccine was 3.46 times higher among working women than housewives, 1.85 times higher among women who have a child than those who do not, and 1.29 times higher among women with a high-school education or higher than those with only a secondary-school education and below. Correct knowledge about the minimal risks associated with receipt of influenza vaccine were associated with a significant increase in the probability of receiving the 2009 H1N1 vaccine. CONCLUSIONS/SIGNIFICANCE: The number of pregnant women in the study group who received the 2009 H1N1 vaccine was very low (8.9%) and two-thirds of them stated that they were comfortable with their decisions concerning the vaccine. Our results may have implications for public health measures to increase the currently low vaccination rate among pregnant women. Further studies are required to confirm whether our findings generalize to other influenza seasons and other settings
Estimation and analysis of multi-GNSS differential code biases using a hardware signal simulator
In ionospheric modeling, the differential code biases (DCBs) are a non-negligible error source, which are routinely estimated by the different analysis centers of the International GNSS Service (IGS) as a by-product of their global ionospheric analysis. These are, however, estimated only for the IGS station receivers and for all the satellites of the different GNSS constellations. A technique is proposed for estimating the receiver and satellites DCBs in a global or regional network by first estimating the DCB of one receiver set as reference. This receiver DCB is then used as a ‘known’ parameter to constrain the global ionospheric solution, where the receiver and satellite DCBs are estimated for the entire network. This is in contrast to the constraint used by the IGS, which assumes that the involved satellites DCBs have a zero mean. The ‘known’ receiver DCB is obtained by simulating signals that are free of the ionospheric, tropospheric and other group delays using a hardware signal simulator. When applying the proposed technique for Global Positioning System legacy signals, mean offsets in the order of 3 ns for satellites and receivers were found to exist between the estimated DCBs and the IGS published DCBs. It was shown that these estimated DCBs are fairly stable in time, especially for the legacy signals. When the proposed technique is applied for the DCBs estimation using the newer Galileo signals, an agreement at the level of 1–2 ns was found between the estimated DCBs and the manufacturer’s measured DCBs, as published by the European Space Agency, for the three still operational Galileo in-orbit validation satellites
A Large Hadron Electron Collider at CERN
This document provides a brief overview of the recently published report on
the design of the Large Hadron Electron Collider (LHeC), which comprises its
physics programme, accelerator physics, technology and main detector concepts.
The LHeC exploits and develops challenging, though principally existing,
accelerator and detector technologies. This summary is complemented by brief
illustrations of some of the highlights of the physics programme, which relies
on a vastly extended kinematic range, luminosity and unprecedented precision in
deep inelastic scattering. Illustrations are provided regarding high precision
QCD, new physics (Higgs, SUSY) and electron-ion physics. The LHeC is designed
to run synchronously with the LHC in the twenties and to achieve an integrated
luminosity of O(100) fb. It will become the cleanest high resolution
microscope of mankind and will substantially extend as well as complement the
investigation of the physics of the TeV energy scale, which has been enabled by
the LHC
Data-driven approach for creating synthetic electronic medical records
<p>Abstract</p> <p>Background</p> <p>New algorithms for disease outbreak detection are being developed to take advantage of full electronic medical records (EMRs) that contain a wealth of patient information. However, due to privacy concerns, even anonymized EMRs cannot be shared among researchers, resulting in great difficulty in comparing the effectiveness of these algorithms. To bridge the gap between novel bio-surveillance algorithms operating on full EMRs and the lack of non-identifiable EMR data, a method for generating complete and synthetic EMRs was developed.</p> <p>Methods</p> <p>This paper describes a novel methodology for generating complete synthetic EMRs both for an outbreak illness of interest (tularemia) and for background records. The method developed has three major steps: 1) synthetic patient identity and basic information generation; 2) identification of care patterns that the synthetic patients would receive based on the information present in real EMR data for similar health problems; 3) adaptation of these care patterns to the synthetic patient population.</p> <p>Results</p> <p>We generated EMRs, including visit records, clinical activity, laboratory orders/results and radiology orders/results for 203 synthetic tularemia outbreak patients. Validation of the records by a medical expert revealed problems in 19% of the records; these were subsequently corrected. We also generated background EMRs for over 3000 patients in the 4-11 yr age group. Validation of those records by a medical expert revealed problems in fewer than 3% of these background patient EMRs and the errors were subsequently rectified.</p> <p>Conclusions</p> <p>A data-driven method was developed for generating fully synthetic EMRs. The method is general and can be applied to any data set that has similar data elements (such as laboratory and radiology orders and results, clinical activity, prescription orders). The pilot synthetic outbreak records were for tularemia but our approach may be adapted to other infectious diseases. The pilot synthetic background records were in the 4-11 year old age group. The adaptations that must be made to the algorithms to produce synthetic background EMRs for other age groups are indicated.</p
Regulation of Progranulin Expression in Human Microglia and Proteolysis of Progranulin by Matrix Metalloproteinase-12 (MMP-12)
Background: The essential role of progranulin (PGRN) as a neurotrophic factor has been demonstrated by the discovery that haploinsufficiency due to GRN gene mutations causes frontotemporal lobar dementia. In addition to neurons, microglia in vivo express PGRN, but little is known about the regulation of PGRN expression by microglia. Goal: In the current study, we examined the regulation of expression and function of PGRN, its proteolytic enzyme macrophage elastase (MMP-12), as well as the inhibitor of PGRN proteolysis, secretory leukocyte protease inhibitor (SLPI), in human CNS cells. Methods: Cultures of primary human microglia and astrocytes were stimulated with the TLR ligands (LPS or poly IC), Th1 cytokines (IL-1/IFNc), or Th2 cytokines (IL-4, IL-13). Results were analyzed by Q-PCR, immunoblotting or ELISA. The roles of MMP-12 and SLPI in PGRN cleavage were also examined. Results: Unstimulated microglia produced nanogram levels of PGRN, and PGRN release from microglia was suppressed by the TLR ligands or IL-1/IFNc, but increased by IL-4 or IL-13. Unexpectedly, while astrocytes stimulated with proinflammatory factors released large amounts of SLPI, none were detected in microglial cultures. We also identified MMP-12 as a PGRN proteolytic enzyme, and SLPI as an inhibitor of MMP-12-induced PGRN proteolysis. Experiments employing PGRN siRNA demonstrated that microglial PGRN was involved in the cytokine and chemokine production following TLR3/4 activation
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