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Sample records for modeling radioxenon signals

  1. Categorisation of nuclear explosions from legitimate radioxenon sources with atmospheric transport modelling

    NASA Astrophysics Data System (ADS)

    Schoeppner, M.; Postelt, F.; Kalinowski, M.; Plastino, W.

    2012-04-01

    Radioxenon is produced during nuclear explosions and due to its high fission ratio during the reaction and its noble gas character the isotopes can be detected remote from the location of the explosion. Therefore it is used by the Comprehensive Nuclear-Test-Ban Organization (CTBTO) as an indicator for the nuclear character of an explosion and is monitored with the International Monitoring System (IMS). The concentration of radioxenon in the air is continuously measured by multiple stations worldwide and is in need of an automatic categorization scheme in order to highlight signals of interest and to sort out signals that can be explained by legitimate sources. The dispersion and transport of radioxenon emissions through the atmosphere can be simulated with atmospheric transport modelling. Many legitimate sources of radioxenon exist: Nuclear power plants and isotope production facilities are mainly responsible for the worldwide background. The characterisation of this background is an important prerequisite to discriminate nuclear explosion signals against the background. It has been discovered that the few existing isotope production facilities are the major contributors to the background, each with emission strengths in the order of magnitude or more than all nuclear power plants together. Therefore, especially the characterization of these few, but strong, emitters can improve the quality of the signal prediction. Since the location of such an emitter is usually known the source-receptor sensitivity matrices can be utilized together with measured radioxenon concentrations from IMS stations in order to deduct information about the time dependent emissions from the strong emitter. An automatic method to determine an approximated, time dependent source term of an emitter with known location has been developed and is presented. This is a potentially valid tool for the categorization of radioxenon samples, because it can be used to assess whether the measured

  2. Evaluation of environmental radioxenon isotopical signals from a singular large source emitter

    NASA Astrophysics Data System (ADS)

    Saey, P. R. J.; Bowyer, T. W.; Aldener, M.; Becker, A.; Cooper, M. W.; Elmgren, K.; Faanhof, A.; Hayes, J. C.; Hosticka, B.; Lidey, L. S.

    2009-04-01

    In the framework of the verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) the atmospheric background of environmental radioxenon is been studied near areas that could be affected by man-made sources. It was recently shown that radiopharmaceutical facilities (RPF) make a major contribution to the general background of 133Xe and other xenon isotopes both in the northern and southern hemisphere. The daily IMS noble gas measurements around the globe are influenced from such anthropogenic sources that could mask radioxenon signals from a nuclear explosion. To distinguish a nuclear explosion signal from releases from civil nuclear facilities, not only the activity concentration but also the ratio of different radioxenon isotopes (131mXe, 133mXe, 133Xe and 135Xe) plays a crucial role, since the ratios can be used to discriminate source types. Theoretical release and ratio studies were recently published, but no measurements close to radiopharmaceutical facilities have ever been performed. The world's fourth largest radiopharmaceutical facility, NTP Radioisotopes Ltd, is located in Pelindaba, South Africa. Other than a small nuclear power plant, located 1300 km southwest, near Cape Town and a small research reactor in the DR of Congo, located 2700 km northwest, this is the only facility that is known to emit any radioxenon on the African continent south of the Equator. This source is likely very dominant with respect to xenon emission. This makes it a point source, which is a unique situation, as all other worldwide large radiopharmaceutical facilities are situated in regions surrounded by many other nuclear facilities. Between 10 November and 22 December 2008, radioxenon was measured continuously with a radioactive xenon measurement system, at the North-West University, Mafikeng, South Africa, which is situated 250 km northwest of Pelindaba. Fifty-six 12-hour samples were measured with a beta-gamma coincidence detector, of which 55 contained 133Xe with

  3. Estimates of radioxenon released from Southern Hemisphere medical isotope production facilities using measured air concentrations and atmospheric transport modeling.

    PubMed

    Eslinger, Paul W; Friese, Judah I; Lowrey, Justin D; McIntyre, Justin I; Miley, Harry S; Schrom, Brian T

    2014-09-01

    The International Monitoring System (IMS) of the Comprehensive-Nuclear-Test-Ban-Treaty monitors the atmosphere for radioactive xenon leaking from underground nuclear explosions. Emissions from medical isotope production represent a challenging background signal when determining whether measured radioxenon in the atmosphere is associated with a nuclear explosion prohibited by the treaty. The Australian Nuclear Science and Technology Organisation (ANSTO) operates a reactor and medical isotope production facility in Lucas Heights, Australia. This study uses two years of release data from the ANSTO medical isotope production facility and (133)Xe data from three IMS sampling locations to estimate the annual releases of (133)Xe from medical isotope production facilities in Argentina, South Africa, and Indonesia. Atmospheric dilution factors derived from a global atmospheric transport model were used in an optimization scheme to estimate annual release values by facility. The annual releases of about 6.8 × 10(14) Bq from the ANSTO medical isotope production facility are in good agreement with the sampled concentrations at these three IMS sampling locations. Annual release estimates for the facility in South Africa vary from 2.2 × 10(16) to 2.4 × 10(16) Bq, estimates for the facility in Indonesia vary from 9.2 × 10(13) to 3.7 × 10(14) Bq and estimates for the facility in Argentina range from 4.5 × 10(12) to 9.5 × 10(12) Bq. PMID:24811887

  4. Estimates of Radioxenon Released from Southern Hemisphere Medical isotope Production Facilities Using Measured Air Concentrations and Atmospheric Transport Modeling

    SciTech Connect

    Eslinger, Paul W.; Friese, Judah I.; Lowrey, Justin D.; McIntyre, Justin I.; Miley, Harry S.; Schrom, Brian T.

    2014-09-01

    Abstract The International Monitoring System (IMS) of the Comprehensive-Nuclear-Test-Ban-Treaty monitors the atmosphere for radioactive xenon leaking from underground nuclear explosions. Emissions from medical isotope production represent a challenging background signal when determining whether measured radioxenon in the atmosphere is associated with a nuclear explosion prohibited by the treaty. The Australian Nuclear Science and Technology Organisation (ANSTO) operates a reactor and medical isotope production facility in Lucas Heights, Australia. This study uses two years of release data from the ANSTO medical isotope production facility and Xe-133 data from three IMS sampling locations to estimate the annual releases of Xe-133 from medical isotope production facilities in Argentina, South Africa, and Indonesia. Atmospheric dilution factors derived from a global atmospheric transport model were used in an optimization scheme to estimate annual release values by facility. The annual releases of about 6.8×1014 Bq from the ANSTO medical isotope production facility are in good agreement with the sampled concentrations at these three IMS sampling locations. Annual release estimates for the facility in South Africa vary from 1.2×1016 to 2.5×1016 Bq and estimates for the facility in Indonesia vary from 6.1×1013 to 3.6×1014 Bq. Although some releases from the facility in Argentina may reach these IMS sampling locations, the solution to the objective function is insensitive to the magnitude of those releases.

  5. Categorization of Radioxenon

    SciTech Connect

    Keller, Paul E.

    2012-04-26

    This report summarizes a study into some false positive issues in the use of radioxenon as a method to verify a clandestine nuclear weapons explosion. False positives arise due to similarities between the radioxenon signature generated in medical isotope production and that generated in a nuclear weapon explosion. This report also discusses how to categorize the radioxenon by levels of urgency for manual analysis and interpretation and recommends applying machine learning and time series analysis techniques in the automation of radioxenon characterization. The literature indicates that medical isotope production is a major contributor to atmospheric radioxenon and is the main source of confusion in determining the source of radioxenon. While radioxenon emissions from nuclear power plants can be distinguished from that from nuclear weapon explosions, emissions from medical isotope production generate signatures similar to certain nuclide ratios found in nuclear weapons explosions. Different techniques for analyzing nuclide concentrations and ratios as well as including other sensing modalities via sensor fusion are discussed.

  6. RADIOXENON MEASUREMENTS WITH THE PHOSWATCH DETECTOR SYSTEM

    SciTech Connect

    Hennig, Wolfgang; Warburton, William K.; Fallu-Labruyere, A.; Sabourov, K.; Cooper, Matthew W.; McIntyre, Justin I.; Gleyzer, A.; Bean, Marc; Korpach, E.; Ungar, R. Kurt; Zhang, W.; Mekarski, P.; Ward, Rebecca; Biegalski, S.; Haas, Derek A.

    2009-09-22

    Many of the radioxenon detector systems used in the International Monitoring System and in other applications employ beta/gamma coincidence detection to achieve high sensitivity. In these systems, the coincidence detection is implemented by requiring simultaneous signals from separate beta and gamma detectors. While very sensitive to small amounts of radioxenon, this approach requires careful calibration and gain matching of several detectors and photomultiplier tubes. An alternative approach is the use of a phoswich detector in which beta-gamma coincidences are detected by pulse shape analysis. The phoswich requires only a single photomultiplier tube and thus is easier to set up and calibrate, and can be assembled into a more compact and robust system. In the past, we have developed a COTS detector system, named PhosWatch, which consists of a CsI(Tl)/BC-404 phoswich detector, digital readout electronics, and on-board software to perform the pulse shape analysis. Several units of this system have been manufactured and are now evaluated at several radioxenon research laboratories. In this paper, we will report results from production tests and some of the evaluations, including a side-by-side comparison of a SAUNA detector and a PhosWatch system using atmospheric radioxenon samples. In addition, we will show initial results obtained with a higher speed version of the readout electronics, digitizing at 500 MHz and thus able to better resolve the fast pulses from the BC-404.

  7. Automated radioxenon monitoring for the comprehensive nuclear-test-ban treaty in two distinctive locations: Ottawa and Tahiti.

    PubMed

    Stocki, T J; Blanchard, X; D'Amours, R; Ungar, R K; Fontaine, J P; Sohier, M; Bean, M; Taffary, T; Racine, J; Tracy, B L; Brachet, G; Jean, M; Meyerhof, D

    2005-01-01

    In preparation for verification of the Comprehensive Nuclear-Test-Ban-Treaty, automated radioxenon monitoring is performed in two distinctive environments: Ottawa and Tahiti. These sites are monitored with SPALAX (Systeme de Prelevement d'air Automatique en Ligne avec l'Analyse des radioXenons) technology, which automatically extracts radioxenon from the atmosphere and measures the activity concentrations of (131m,133m,133,135)Xe. The resulting isotopic concentrations can be useful to discern nuclear explosions from nuclear industry xenon emissions. Ambient radon background, which may adversely impact analyser sensitivity, is discussed. Upper concentration limits are reported for the apparently radioxenon free Tahiti environment. Ottawa has a complex radioxenon background due to proximity to nuclear reactors and medical isotope facilities. Meteorological models suggest that, depending on the wind direction, the radioxenon detected in Ottawa can be characteristic of the normal radioxenon background in the Eastern United States, Europe, and Japan or distinctive due to medical isotope production.

  8. SPECTRAL ANALYSIS OF RADIOXENON

    SciTech Connect

    Cooper, Matthew W.; Bowyer, Ted W.; Hayes, James C.; Heimbigner, Tom R.; Hubbard, Charles W.; McIntyre, Justin I.; Schrom, Brian T.

    2008-09-23

    Monitoring changes in atmospheric radioxenon concentrations is a major tool in the detection of an underground nuclear explosion. Ground based systems like the Automated Radioxenon Sampler /Analyzer (ARSA), the Swedish Unattended Noble gas Analyzer (SAUNA) and the Automatic portable radiometer of isotopes Xe (ARIX), can collect and detect several radioxenon isotopes by processing and transferring samples into a high efficiency beta-gamma coincidence detector. The high efficiency beta-gamma coincidence detector makes these systems highly sensitive to the radioxenon isotopes 133Xe, 131mXe, 133mXe and 135Xe. The standard analysis uses regions of interest (ROI) to determine the amount of a particular radioxenon isotope present. The ROI method relies on the peaks of interest falling within energy limits of the ROI. Some potential problems inherent in this method are the reliance on stable detector gains and a fixed resolution for each energy peak. In addition, when a high activity sample is measured there will be more interference among the ROI, in particular within the 133Xe, 133mXe, and 131mXe regions. A solution to some of these problems can be obtained through spectral fitting of the data. Spectral fitting is simply the fitting of the peaks using known functions to determine the number and relative peak positions and widths. By knowing this information it is possible to determine which isotopes are present. Area under each peak can then be used to determine an overall concentration for each isotope. Using the areas of the peaks several key detector characteristics can be determined: efficiency, energy calibration, energy resolution and ratios between interfering isotopes (Radon daughters).

  9. A phoswich well detector for radioxenon monitoring

    NASA Astrophysics Data System (ADS)

    Hennig, Wolfgang; Tan, Hui; Fallu-Labruyere, Anthony; Warburton, William K.; McIntyre, Justin I.; Gleyzer, Anshel

    2007-08-01

    One of several methods used to detect nuclear weapons testing is the monitoring of radioactive xenon in the atmosphere. For high sensitivity, monitoring stations use a complex system of separate beta and gamma detectors to detect beta-gamma coincidences from characteristic radioxenon isotopes in small amounts of xenon extracted from large volumes of air. We report a simpler approach that uses a single phoswich detector, comprising optically coupled plastic and CsI scintillators to absorb beta particles and gamma rays, respectively, and then detect coincidences by pulse shape analysis of the detector signal. Previous studies with a planar prototype detector have shown that the technique can clearly separate beta only, gamma only and coincidence events, does not degrade the energy resolution, and has an error rate for detecting coincidences of less than 0.1%. In this paper, we will present a new phoswich well detector design, consisting of a 1'' diameter plastic cell enclosed in a 3'' CsI crystal. Based on Monte Carlo modeling and experimental results, the design will be characterized in terms of energy resolution and its ability to separate beta and gamma only, and coincidence events.

  10. Environmental characterisation of a major radioxenon source in Europe

    NASA Astrophysics Data System (ADS)

    Saey, P. R. J.; Ringbom, A.; Becker, A.; Camps, J.; Paquet, N.; Sonck, M.; Taffary, T.; van der Meer, K.; Verboomen, B.; Zähringer, M.

    2009-04-01

    In the framework of the verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) the atmospheric background of environmental radioxenon has been studied. It was recently shown that radiopharmaceutical facilities (RPF) have a major contribution to the general background of 133Xe and other xenon isotopes both in the northern and southern hemisphere. The daily International Monitoring System (IMS) noble gas measurements around the globe are influenced from such anthropogenic sources that could hide relevant radioxenon signals. To distinguish a nuclear explosion from releases from civil nuclear facilities, not only the activity concentration but also the ratio of different radioxenon isotopes (131mXe, 133mXe, 133Xe and 135Xe) plays a crucial role, since the ratios can be used to discriminate source types. Theoretical release and ratio studies were recently published, but no high-sensitive measurements in and close to radiopharmaceutical facilities have ever been performed. During the summer of 2008, a three week field campaign was carried out in the region around the Belgian radiopharmaceutical facility IRE in Fleurus, the world third largest one. The scope was to obtain the activity concentration of the releases and the isotopic composition. Two 6-hour noble gas measurements, using mobile SAUNA sampling equipment were collected each day at different distances from the facility (1 - 100 km). The sampling locations were guided by atmospheric dispersion model results. Three samples from the stack itself were also collected. All 38 samples were shipped after collection to and measured with a SAUNA at the laboratory in Stockholm, Sweden. The environmental concentrations of 133Xe were measured and found to be in the range between 0.7 - 4 105 mBq/m3. Nine samples contained all four CTBT relevant radioxenon isotopes. The concentrations of the stack spike samples were in the range 2 109 - 4 1010 mBq/m3. This corresponds to a daily release of around 1 TBq. This is

  11. Machine learning for radioxenon event classification for the Comprehensive Nuclear-Test-Ban Treaty.

    PubMed

    Stocki, Trevor J; Li, Guichong; Japkowicz, Nathalie; Ungar, R Kurt

    2010-01-01

    A method of weapon detection for the Comprehensive nuclear-Test-Ban-Treaty (CTBT) consists of monitoring the amount of radioxenon in the atmosphere by measuring and sampling the activity concentration of (131m)Xe, (133)Xe, (133m)Xe, and (135)Xe by radionuclide monitoring. Several explosion samples were simulated based on real data since the measured data of this type is quite rare. These data sets consisted of different circumstances of a nuclear explosion, and are used as training data sets to establish an effective classification model employing state-of-the-art technologies in machine learning. A study was conducted involving classic induction algorithms in machine learning including Naïve Bayes, Neural Networks, Decision Trees, k-Nearest Neighbors, and Support Vector Machines, that revealed that they can successfully be used in this practical application. In particular, our studies show that many induction algorithms in machine learning outperform a simple linear discriminator when a signal is found in a high radioxenon background environment. PMID:19811861

  12. Radioxenon Atmospheric Measurements in North Las Vegas

    SciTech Connect

    Milbrath, Brian D.; Cooper, Matthew W.; Lidey, Lance S.; Bowyer, Ted W.; Hayes, James C.; McIntyre, Justin I.; Karr, L.; Shafer, David S.; Tappen, J.

    2007-09-25

    Pacific Northwest National Laboratory (PNNL) deployed the Automated Radioxenon Sampler/Analyzer (ARSA) in North Las Vegas for two weeks in February and March 2006 for the purpose of measuring the radioxenon background at a level of sensitivity much higher than previously done in the vicinity of the Nevada Test Site (NTS). The measurements establish what might be expected if future measurements are taken at NTS itself and investigate improved methods of environmental monitoring of NTS for test site readiness. Also, such radioxenon measurements have not previously been performed in a United States location considered to be as remote from nuclear reactors. A second detector, the Portable Environmental Monitoring Station (PEMS), built and operated by the Desert Research Institute (DRI), was deployed in conjunction with the ARSA and contained a pressure ion chamber, aerosol collection filters, and meteorological sensors. Some of the radioxenon measurements detected 133Xe at levels up to 3 mBq/m3. This concentration of radioxenon is consistent with the observation of low levels of radioxenon emanating from distance nuclear reactors. Previous measurements in areas of high nuclear reactor concentration have shown similar results, but the western US, in general, does not have many nuclear reactors. Measurements of the wind direction indicate that the air carrying the radioxenon came from south of the detector and not from the NTS.

  13. Progress in Advanced Spectral Analysis of Radioxenon

    SciTech Connect

    Haas, Derek A.; Schrom, Brian T.; Cooper, Matthew W.; Ely, James H.; Flory, Adam E.; Hayes, James C.; Heimbigner, Tom R.; McIntyre, Justin I.; Saunders, Danielle L.; Suckow, Thomas J.

    2010-09-21

    Improvements to a Java based software package developed at Pacific Northwest National Laboratory (PNNL) for display and analysis of radioxenon spectra acquired by the International Monitoring System (IMS) are described here. The current version of the Radioxenon JavaViewer implements the region of interest (ROI) method for analysis of beta-gamma coincidence data. Upgrades to the Radioxenon JavaViewer will include routines to analyze high-purity germanium detector (HPGe) data, Standard Spectrum Method to analyze beta-gamma coincidence data and calibration routines to characterize beta-gamma coincidence detectors. These upgrades are currently under development; the status and initial results will be presented. Implementation of these routines into the JavaViewer and subsequent release is planned for FY 2011-2012.

  14. Gain Calibration of a Beta/Gamma Coincidence Spectrometer for Automated Radioxenon Analysis

    SciTech Connect

    Reeder, Paul L.; Bowyer, Ted W.; McIntyre, Justin I.; Pitts, W. K.; Ringbom, Anders; Johansson, Cecilia

    2004-04-01

    Abstract Detection and measurement of atmospheric radioxenon is an important component of international monitoring systems for nuclear weapons testing. Monitoring stations separate xenon from air and perform isotopic analysis of the radioxenon. In one such radioxenon measurement scheme, the isotopes of interest are identified by coincident spectroscopy of electrons and photons in a bg coincidence spectrometer (BGCS). The b spectrometer is a plastic scintillator, produced as a cylindrical cell containing the separated xenon sample. This cell is surrounded by the NaI(Tl) g spectrometer. We report here the development of a calibration process for the BGCS suitable for use in remote sampling systems. This procedure is based upon g-ray Compton scattering, resulting in a true coincident signal in both detectors, generation of electrons over a wide energy range that matches the energy distribution of electrons from radioxenon decay, and a relative insensitivity to source location. Besides gain calibration, this procedure determines the resolution of the b detector as a function of energy.

  15. Testing of the KRI-developed Silicon PIN Radioxenon Detector

    SciTech Connect

    Foxe, Michael P.; McIntyre, Justin I.

    2015-01-23

    Radioxenon detectors are used for the verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) in a network of detectors throughout the world called the International Monitoring System (IMS). The Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) Provisional Technical Secretariat (PTS) has tasked Pacific Northwest National Laboratory (PNNL) with testing a V.G. Khlopin Radium Institute (KRI) and Lares Ltd-developed Silicon PIN detector for radioxenon detection. PNNL measured radioxenon with the silicon PIN detector and determined its potential compared to current plastic scintillator beta cells. While the PNNL tested Si detector experienced noise issues, a second detector was tested in Russia at Lares Ltd, which did not exhibit the noise issues. Without the noise issues, the Si detector produces much better energy resolution and isomer peak separation than a conventional plastic scintillator cell used in the SAUNA systems in the IMS. Under the assumption of 1 cm3 of Xe in laboratory-like conditions, 24-hr count time (12-hr count time for the SAUNA), with the respective shielding the minimum detectable concentrations for the Si detector tested by Lares Ltd (and a conventional SAUNA system) were calculated to be: 131mXe – 0.12 mBq/m3 (0.12 mBq/m3); 133Xe – 0.18 mBq/m3 (0.21 mBq/m3); 133mXe – 0.07 mBq/m3 (0.15 mBq/m3); 135Xe – 0.45 mBq/m3 (0.67 mBq/m3). Detection limits, which are one of the important factors in choosing the best detection technique for radioxenon in field conditions, are significantly better than for SAUNA-like detection systems for 131mXe and 133mXe, but similar for 133Xe and 135Xe. Another important factor is the amount of “memory effect” or carry over signal from one radioxenon measurement to the subsequent sample. The memory effect is

  16. Examining Changes in Radioxenon Isotope Activity Ratios during Subsurface Transport

    NASA Astrophysics Data System (ADS)

    Annewandter, R.

    2013-12-01

    The Non-Proliferation Experiment (NPE) has demonstrated and modelled the usefulness of barometric pumping induced soil gas sampling during On-Site inspections. Gas transport has been widely studied with different numerical codes. However, gas transport of all radioxenons in the post-detonation regime and their possible fractionation is still neglected in the open literature. Atmospheric concentrations of the radioxenons Xe-135, Xe-133m, Xe-133 and Xe-131m can be used to discriminate between civilian releases (nuclear power plants or medical isotope facilities), and nuclear explosion sources. It is based on the isotopic activity ratio method. Yet it is not clear whether subsurface migration of the radioxenons, with eventual release into the atmosphere, can affect the activity ratios due to fractionation. Fractionation can be caused by different diffusivities due to mass differences between the radioxenons. A previous study showed surface arrival time of a chemically inert gaseous tracer is affected by its diffusivity. They observed detectable amount for SF6 50 days after detonation and 375 days for He-3. They predict 50 and 80 days for Xe-133 and Ar-37 respectively. Cyclical changes in atmospheric pressure can drive subsurface gas transport. This barometric pumping phenomenon causes an oscillatoric flow in upward trending fractures which, combined with diffusion into the porous matrix, leads to a net transport of gaseous components - a ratcheting effect. We use a general purpose reservoir simulator (Complex System Modelling Platform, CSMP++) which has been applied in a range of fields such as deep geothermal systems, three-phase black oil simulations , fracture propagation in fractured, porous media, Navier-Stokes pore-scale modelling among others. It is specifically designed to account for structurally complex geologic situation of fractured, porous media. Parabolic differential equations are solved by a continuous Galerkin finite-element method, hyperbolic

  17. Global radioxenon emission inventory based on nuclear power reactor reports.

    PubMed

    Kalinowski, Martin B; Tuma, Matthias P

    2009-01-01

    Atmospheric radioactivity is monitored for the verification of the Comprehensive Nuclear-Test-Ban Treaty, with xenon isotopes 131mXe, 133Xe, 133mXe and 135Xe serving as important indicators of nuclear explosions. The treaty-relevant interpretation of atmospheric concentrations of radioxenon is enhanced by quantifying radioxenon emissions released from civilian facilities. This paper presents the first global radioxenon emission inventory for nuclear power plants, based on North American and European emission reports for the years 1995-2005. Estimations were made for all power plant sites for which emission data were unavailable. According to this inventory, a total of 1.3PBq of radioxenon isotopes are released by nuclear power plants as continuous or pulsed emissions in a generic year.

  18. Radioxenon retention in the skeleton on a routine ventilation study

    SciTech Connect

    Kramer, E.L.; Tiu, S.; Sanger, J.J.; Benjamin, D.D.

    1983-07-01

    Marked retention of radioxenon by the skeletal structures during a routine ventilation scan is described. Xenon uptake by bones occurs largely in the intraosseous fat. Augmented uptake in this case may be related to the patient's prolonged steroid therapy.

  19. Atmospheric Radioxenon Measurements in North Las Vegas, NV

    SciTech Connect

    Milbrath, Brian D.; Cooper, Matthew W.; Lidey, Lance S.; Bowyer, Ted W.; Hayes, James C.; McIntyre, Justin I.; Karr, L.; Shafer, D.; Tappen, J.

    2006-07-31

    PNNL deployed the ARSA radioxenon measurement system in North Las Vegas for two weeks in February and March 2006 for the purpose of measuring the radioxenon background at a level of sensitivity much higher than previously done in the vicinity of the NTS. The measurements establish what might be expected if future measurements are taken at NTS itself. The measurements are also relevant to test site readiness. A second detector, the PEMS, built and operated by DRI, was deployed in conjunction with the ARSA and contained a PIC, aerosol collection filters, and meteorological sensors. Originally, measurements were also to be performed at Mercury, NV on the NTS, but these were canceled due to initial equipment problems with the ARSA detector. Some of the radioxenon measurements detected 133Xe at levels up to 3 mBq/m3. This concentration of radioxenon is consistent with the observation of low levels of radioxenon emanating from distance nuclear reactors. Previous measurements in areas of high nuclear reactor concentration have shown similar results, but the western US, in general, does not have many nuclear reactors. Measurements of the wind direction indicate that the air carrying the radioxenon came from south of the detector and not from the NTS.

  20. Measurements of Worldwide Radioxenon Backgrounds - The "EU" Project

    SciTech Connect

    Bowyer, Ted W.; Cooper, Matthew W.; Hayes, James C.; Forrester, Joel B.; Haas, Derek A.; Hansen, Randy R.; Keller, Paul E.; Kirkham, Randy R.; Lidey, Lance S.; McIntyre, Justin I.; Miley, Harry S.; Payne, Rosara F.; Saey, Paul R.; Thompson, Robert C.; Woods, Vincent T.; Williams, Richard M.

    2009-09-24

    Under the Comprehensive Nuclear-Test-Ban Treaty (CTBT), radioactive xenon (radioxenon) measurements are one of the principle techniques used to detect nuclear underground nuclear explosions, and specifically, the presence of one or more radioxenon isotopes allows one to determine whether a suspected event was a nuclear explosion or originated from an innocent source. During the design of the International Monitoring System (IMS), which was designed as the verification mechanism for the Treaty, it was determined that radioxenon measurements should be performed at 40 or more stations worldwide. At the time of the design of the IMS, however, very few details about the background of the xenon isotopes was known and it is now recognized that the backgrounds were probably evolving anyhow. This paper lays out the beginning of a study of the worldwide concentrations of xenon isotopes that can be used to detect nuclear explosions and several sources that also release radioxenons, and will have to be accounted for during analysis of atmospheric levels. Although the global concentrations of the xenon isotopes are the scope of a much larger activity that could span over several years, this study measures radioxenon concentrations in locations where there was either very little information or there was a unique opportunity to learn more about emissions from known sources. The locations where radioxenon levels were measured and reported are included.

  1. Understanding radioxenon isotopical ratios originating from radiopharmaceutical facilities

    NASA Astrophysics Data System (ADS)

    Saey, P. R. J.; Ringbom, A.; Bowyer, T. W.; Becker, A.; de Geer, L.-E.; Nikkinen, M.; Payne, R. F.

    2009-04-01

    It was recently shown that radiopharmaceutical facilities (RPF) are major contributors to the general background of 133Xe and other xenon isotopes both in the northern and southern hemisphere. To distinguish a nuclear explosion signal from releases from civil nuclear facilities, not only the activity concentrations but also the ratios of the four different CTBT relevant radioxenon isotopes (131mXe, 133mXe, 133Xe and 135Xe) have to be well understood. First measurements taken recently in and around two of the world's largest RPF's: NTP at Pelindaba, South Africa and IRE at Fleurus, Belgium have been presented. At both sites, also stack samples were taken in close cooperation with the facility operators. The radioxenon in Belgium could be classified in four classes: the normal European background (133Xe activity between 0 - 5 mBq/m3) on one hand and then the samples where all four isotopes were detected with 133mXe/131mXe > 1. In northern South Africa the Pelindaba RPF is in practice the sole source of radioxenon. It generated a background of 133Xe at the measurement site some 230 km to the west of the RPF of 0 - 5 mBq/m3. In the cases where the air from the Pelindaba facility reached the measurement site directly and in a short time period, the 133Xe was higher, also 135Xe was present and in some samples 133mXe as well. The ratios of the activity concentrations of 135Xe/133Xe vs. 133mXe/131mXe (Multiple Isotope Ratio Plot - MIRC) have been analysed. For both facilities, the possible theoretical ratio's for different scenarios were calculated with the information available and compared with the measurements. It was found that there is an excess of 131mXe present in the European samples compared to theoretical calculations. A similar excess has also been seen in samples measured in northern America. In South Africa, neither the environmental samples nor the stack ones contained 131mXe at measurable levels. This can probably be explained by different processes and

  2. Examining Changes in Radioxenon Isotope Activity Ratios during Subsurface Transport

    NASA Astrophysics Data System (ADS)

    Annewandter, Robert

    2014-05-01

    The Non-Proliferation Experiment (NPE) has demonstrated and modelled the usefulness of barometric pumping induced gas transport and subsequent soil gas sampling during On-Site inspections. Generally, gas transport has been widely studied with different numerical codes. However, gas transport of radioxenons and radioiodines in the post-detonation regime and their possible fractionation is still neglected in the open peer-reviewed literature. Atmospheric concentrations of the radioxenons Xe-135, Xe-133m, Xe-133 and Xe-131m can be used to discriminate between civilian releases (nuclear power plants or medical isotope facilities), and nuclear explosion sources. It is based on the multiple isotopic activity ratio method. Yet it is not clear whether subsurface migration of the radionuclides, with eventual release into the atmosphere, can affect the activity ratios due to fractionation. Fractionation can be caused by different mass diffusivities due to mass differences between the radionuclides. Cyclical changes in atmospheric pressure can drive subsurface gas transport. This barometric pumping phenomenon causes an oscillatoric flow in upward trending fractures or highly conductive faults which, combined with diffusion into the porous matrix, leads to a net transport of gaseous components - a so-called ratcheting effect. We use a general purpose reservoir simulator (Complex System Modelling Platform, CSMP++) which is recognized by the oil industry as leading in Discrete Fracture-Matrix (DFM) simulations. It has been applied in a range of fields such as deep geothermal systems, three-phase black oil simulations, fracture propagation in fractured, porous media, and Navier-Stokes pore-scale modelling among others. It is specifically designed to account for structurally complex geologic situation of fractured, porous media. Parabolic differential equations are solved by a continuous Galerkin finite-element method, hyperbolic differential equations by a complementary finite

  3. Radioxenon Production and Transport from an Underground Nuclear Detonation to Ground Surface

    NASA Astrophysics Data System (ADS)

    Sun, Yunwei; Carrigan, Charles R.; Hao, Yue

    2015-02-01

    Radioxenon isotopes are considered as possible indicators for detecting and discriminating underground nuclear explosions. To monitor and sample the release of radioxenon isotopes, both independent and chain-reaction yields need to be considered together with multiphase transport in geological systems from the detonation point to the ground surface. For the sake of simplicity, modeling of radioxenon isotopic radioactivities has typically been focused either on chain reactions in a batch reactor without considering multiphase transport or on radionuclide transport with simplified reactions. Although numerical methods are available for integrating coupled differential equations of complex decay networks, the stiffness of ordinary differential equations due to greatly differing decay rates may require substantial additional effort to obtain solutions for the fully coupled system. For this reason, closed-form solutions for sequential reactions and numerical solutions for multiparent converging and multidaughter branching reactions were previously developed and used to simulate xenon isotopic radioactivities in the batch reactor mode. In this paper, we develop a fully coupled numerical model, which involves tracking 24 components (i.e., 22 radionuclide components plus air and water) in two phases to enhance model predictability of simultaneously simulating xenon isotopic transport and fully coupled chain reactions. To validate the numerical model and verify the corresponding computer code, we derived closed-form solutions for first-order xenon reactions in a batch reactor mode and for single-gas phase transport coupled with the xenon reactions in a one-dimensional column. Finally, cylindrical 3-D simulations of two-phase flow within a dual permeability fracture-matrix medium, simulating the geohydrologic regime of an underground nuclear explosion, indicate the existence of both a strong temporal and spatial dependence of xenon isotopic ratios sampled at the surface. In

  4. Radioxenons: Their role in monitoring a Comprehensive Test Ban Treaty

    SciTech Connect

    Perkins, R. W.; Casey, L. A.

    1996-06-01

    Monitoring for xenon radionuclides which are produced in a nuclear detonation can provide a strong deterrent to the violation of a Comprehensive nuclear Test Ban Treaty (CTBT). There are 18 known radioactive xenon isotopes produced in nuclear fission with half-lives ranging from less than one second to 11.9 days. However, only four of these remain in significant amounts more than a day after a detonation. In order for radioxenon monitoring to be practical, it was necessary to develop an automated measurement system which could operate unattended for periods of months, measure the entire spectrum of radioxenons, and provide hundreds of times better sensitivities than current laboratory procedures. This capability was developed at the US Department of Energy`s Pacific Northwest National Laboratory based on rapid separation of atmospheric xenon coupled with a unique high sensitivity measurement device for the radioxenons. A fieldable prototype analyzer is scheduled for testing in August 1996 with commercial availability planned by 1998.

  5. Measurements of radioxenon in ground level air in South Korea following the claimed nuclear test in North Korea on October 9, 2006

    SciTech Connect

    Ringbom, Anders; Elmgren, K.; Lindh, Karin; Peterson, Jenny; Bowyer, Ted W.; Hayes, James C.; McIntyre, Justin I.; Panisko, Mark E.; Williams, Richard M.

    2009-12-03

    Abstract Following the claimed nuclear test in the Democratic People’s Republic of Korea (DPRK) on October 9, 2006, and a reported seismic event, a mobile system for sampling of atmospheric xenon was transported to the Republic of South Korea (ROK) in an attempt to detect possible emissions of radioxenon in the region from a presumed test. Five samples were collected in the ROK during October 11–14, 2006 near the ROK–DPRK border, and thereafter transported to the Swedish Defense Research Agency (FOI) in Stockholm, Sweden, for analysis. Following the initial measurements, an automatic radioxenon sampling and analysis system was installed at the same location in the ROK, and measurements on the ambient atmospheric radioxenon background in the region were performed during November 2006 to February 2007. The measured radioxenon concentrations strongly indicate that the explosion in October 9, 2006 was a nuclear test. The conclusion is further strengthened by atmospheric transport models. Radioactive xenon measurement was the only independent confirmation that the supposed test was in fact a nuclear explosion and not a conventional (chemical) explosive.

  6. Neural Network Based State of Health Diagnostics for an Automated Radioxenon Sampler/Analyzer

    SciTech Connect

    Keller, Paul E.; Kangas, Lars J.; Hayes, James C.; Schrom, Brian T.; Suarez, Reynold; Hubbard, Charles W.; Heimbigner, Tom R.; McIntyre, Justin I.

    2009-05-13

    Artificial neural networks (ANNs) are used to determine the state-of-health (SOH) of the Automated Radioxenon Analyzer/Sampler (ARSA). ARSA is a gas collection and analysis system used for non-proliferation monitoring in detecting radioxenon released during nuclear tests. SOH diagnostics are important for automated, unmanned sensing systems so that remote detection and identification of problems can be made without onsite staff. Both recurrent and feed-forward ANNs are presented. The recurrent ANN is trained to predict sensor values based on current valve states, which control air flow, so that with only valve states the normal SOH sensor values can be predicted. Deviation between modeled value and actual is an indication of a potential problem. The feed-forward ANN acts as a nonlinear version of principal components analysis (PCA) and is trained to replicate the normal SOH sensor values. Because of ARSA’s complexity, this nonlinear PCA is better able to capture the relationships among the sensors than standard linear PCA and is applicable to both sensor validation and recognizing off-normal operating conditions. Both models provide valuable information to detect impending malfunctions before they occur to avoid unscheduled shutdown. Finally, the ability of ANN methods to predict the system state is presented.

  7. Source term estimation of radioxenon released from the Fukushima Dai-ichi nuclear reactors using measured air concentrations and atmospheric transport modeling.

    PubMed

    Eslinger, P W; Biegalski, S R; Bowyer, T W; Cooper, M W; Haas, D A; Hayes, J C; Hoffman, I; Korpach, E; Yi, J; Miley, H S; Rishel, J P; Ungar, K; White, B; Woods, V T

    2014-01-01

    Systems designed to monitor airborne radionuclides released from underground nuclear explosions detected radioactive fallout across the northern hemisphere resulting from the Fukushima Dai-ichi Nuclear Power Plant accident in March 2011. Sampling data from multiple International Modeling System locations are combined with atmospheric transport modeling to estimate the magnitude and time sequence of releases of (133)Xe. Modeled dilution factors at five different detection locations were combined with 57 atmospheric concentration measurements of (133)Xe taken from March 18 to March 23 to estimate the source term. This analysis suggests that 92% of the 1.24 × 10(19) Bq of (133)Xe present in the three operating reactors at the time of the earthquake was released to the atmosphere over a 3 d period. An uncertainty analysis bounds the release estimates to 54-129% of available (133)Xe inventory.

  8. Source Term Estimation of Radioxenon Released from the Fukushima Dai-ichi Nuclear Reactors Using Measured Air Concentrations and Atmospheric Transport Modeling

    SciTech Connect

    Eslinger, Paul W.; Biegalski, S.; Bowyer, Ted W.; Cooper, Matthew W.; Haas, Derek A.; Hayes, James C.; Hoffman, Ian; Korpach, E.; Yi, Jing; Miley, Harry S.; Rishel, Jeremy P.; Ungar, R. Kurt; White, Brian; Woods, Vincent T.

    2014-01-01

    Systems designed to monitor airborne radionuclides released from underground nuclear explosions detected radioactive fallout from the Fukushima Daiichi nuclear accident in March 2011. Atmospheric transport modeling (ATM) of plumes of noble gases and particulates were performed soon after the accident to determine plausible detection locations of any radioactive releases to the atmosphere. We combine sampling data from multiple International Modeling System (IMS) locations in a new way to estimate the magnitude and time sequence of the releases. Dilution factors from the modeled plume at five different detection locations were combined with 57 atmospheric concentration measurements of 133-Xe taken from March 18 to March 23 to estimate the source term. This approach estimates that 59% of the 1.24×1019 Bq of 133-Xe present in the reactors at the time of the earthquake was released to the atmosphere over a three day period. Source term estimates from combinations of detection sites have lower spread than estimates based on measurements at single detection sites. Sensitivity cases based on data from four or more detection locations bound the source term between 35% and 255% of available xenon inventory.

  9. Environmental Applications of Stable Xenon and Radioxenon Monitoring

    SciTech Connect

    Dresel, P. Evan; Olsen, Khris B.; Hayes, James C.; McIntyre, Justin I.; Waichler, Scott R.; Kennedy, B. M.

    2008-06-01

    Improved detection capabilities are needed at several Department of Energy sites to make remedial decisions about facilities and landfill cleanup. For facility monitoring air samples can be collected from within a facility and analyzed for short lived radioxenons to estimate inventories of residual plutonium holdup within the facility. For landfill cleanup activities soil gas sampling for xenon isotopes can be used to define the locations of spent fuel and transuranic wastes. Short-lived radioxenon isotopes are continuously produced by spontaneous fission of plutonium-240 in transuranic wastes. Large volume soil-gas samples provide extremely sensitive measurement of radioxenon in the subsurface; a characteristic of transuranic waste. The analysis employs a modified Automated Radioxenon Sampling and Analysis (ARSA) system. Proof of principle measurements at a Hanford Site liquid waste disposal site showed xenon-133 at levels in soil gas are approximately 16,000 times the detection limit and lower levels of xenon-135 from the spontaneous fission of plutonium-240 were also measured. Stable xenon isotopes are also produced by spontaneous fission but are subject to background concentrations in ambient air samples (facilities) but less so in soil gas where free exchange with ambient air is restricted. Rare gas mass spectrometry is used for highly precise stable xenon isotopic measurements. Stable xenon isotopic ratios from fission are distinct from natural xenon background ratios. Neutron capture on xenon-135 produces an excess of xenon-136 above fission ratios and thus provides a means of distinguishing reactor sources (e.g. spent fuel) from separated transuranic materials (plutonium).

  10. A Multi-Layer Phoswich Radioxenon Detection System (7th Qtr Report), Reporting Period 10/01/07 - 12/31/07

    SciTech Connect

    David M. Hamby

    2008-01-29

    Description of activities conducted this report period: (1) Electronics Development--To improve the overall performance of the two-channel digital pulse processor (DPP2), the PCB has been redesigned and the new printed board is now under assembly. The system is enhanced with two new fast ADCs from Analog Devices (AD9230-250), each with a sampling rate of 250 MHz and a resolution of 12 bits. The data bus uses a high performance Low Voltage Differential Signaling (LVDS) standard. The offset and gain of each channel are separately controlled digitally by the GUI software. (2) GUI Software Development--A GUI is being developed using the Python programming language. All functions from the preceding MATLAB code have been re-implemented including basic waveform readout, pulse shape discrimination, and plotting of energy spectra. In addition, the GUI can be used to control sampling runs based on the number of pulses captured, either in real or live time. Calibration coefficients and pulse shape discrimination boundaries can be changed on the fly so that the detector may be characterized experimentally. Plots generated by the GUI can be exported as graphic data. At present, the software has only been tested using one channel, pending availability of the new DPP board (DPP2). However, the functions have been written to allow easy expansion to two channels. (3) Light Collection Modeling--The XEPHWICH design has been modeled to determine its light capture efficiency. Research in the 7th quarter includes additional simulations representing significant increase in data resolution, well over an order of magnitude greater than previous simulations. The final data set represents approximately 11 billion visible photons divided equally among 110 thousand data points. A laboratory experiment is being designed and executed to experimentally determine light capture efficiency as a function of position within the scintillators. (4) Radioxenon Fission Source--We have designed and

  11. Improved β-γ Coincidence Detector For Radioxenon Detection

    SciTech Connect

    Cooper, Matthew W; Carman, April J; Hayes, James C; Heimbigner, Tom R; Hubbard, Charles W; Litke, Kevin E; McIntyre, Justin I; Morris, Scott J; Ripplinger, Michael D; Suarez, Reynold

    2005-08-31

    The Automated Radio-xenon Analyzer/Sampler (ARSA), built by Pacific Northwest National Laboratory (PNNL), can collect and detect several radioxenon isotopes. ARSA is very sensitive to 133Xe, 131mXe, 133mXe and 135Xe due to the compact high efficiency coincidence detector it uses. For this reason it is an excellent treaty monitoring and environmental sampling device. Although the system is shown to be both robust and reliable, based on several field tests, it is also complex due to a detailed photomultiplier tube gain matching regime. This complexity is a problem from a maintenance and quality assurance/quality control (QA/QC) standpoint. To reduce these issues a simplified coincident detector has been developed. A comparison of three different well detectors has been completed. In addition, a new plastic scintillator gas cell was constructed. The new simplified detector system has been demonstrated to equal or better performance compared with the original ARSA design in spectral resolution and efficiency and significantly easier to setup and calibrate.

  12. Field test of the PNNL Automated Radioxenon Sampler/Analyzer (ARSA)

    SciTech Connect

    Lagomarsino, R.J.; Ku, E.; Latner, N.; Sanderson, C.G.

    1998-07-01

    As part of the requirements of the Comprehensive Test Ban Treaty (CTBT), the Automated Radioxenon/Sampler Analyzer (ARSA) was designed and engineered by the Pacific Northwest National Laboratory (PNNL). The instrument is to provide near real-time detection and measurement of the radioxenons released into the atmosphere after a nuclear test. Forty-six field tests, designed to determine the performance of the ARSA prototype under simulated field conditions, were conducted at EML from March to December 1997. This final report contains detailed results of the tests with recommendations for improvements in instrument performance.

  13. Metastable Radioxenon Verification Laboratory (MRVL) Year-End Report

    SciTech Connect

    Cooper, Matthew W.; Hayes, James C.; Lidey, Lance S.

    2014-11-07

    This is the year end report that is due to the client. The MRVL system is designed to measure multiple radioxenon isotopes (135Xe, 133Xe, 133mXe and 133mXe) simultaneously. The system has 12 channels to load samples and make nuclear measurements. Although the MRVL system has demonstrated excellent stability in measurements of Xe-133 and Xe-135 over the year of evaluation prior to delivery, there has been concern about system stability over measurements performed on samples with orders of magnitude different radioactivity, and samples containing multiple isotopes. To address these concerns, a series of evaluation test have been performed at the end-user laboratory. The evaluation was performed in two separate phases. Phase 1 made measurements on isotopically pure Xe-133 from high radioactivity down to the system background levels of activity, addressing the potential count rate dependencies when activities change from extreme high to very low. The second phase performed measurements on samples containing multiple isotopes (Xe-135, Xe-133 and Xe-133m), and addressed concerns about the dependence of isotopic concentrations on the presence of additional isotopes. The MRVL showed a concentration dependence on the Xe-133 due to the amount of Xe-133m that was in the sample. The dependency is due to the decay of Xe-133m into Xe-133. This document focuses on the second phase and will address the analysis used to account for ingrowth of Xe-133 from Xe-133m.

  14. Mathematical model for classification of EEG signals

    NASA Astrophysics Data System (ADS)

    Ortiz, Victor H.; Tapia, Juan J.

    2015-09-01

    A mathematical model to filter and classify brain signals from a brain machine interface is developed. The mathematical model classifies the signals from the different lobes of the brain to differentiate the signals: alpha, beta, gamma and theta, besides the signals from vision, speech, and orientation. The model to develop further eliminates noise signals that occur in the process of signal acquisition. This mathematical model can be used on different platforms interfaces for rehabilitation of physically handicapped persons.

  15. Comparison of Phoswich and ARSA-type detectors for Radioxenon Measurements

    SciTech Connect

    Ward, Rebecca; Biegalski, Steven R.; Haas, Derek A.; Hennig, Wolfgang

    2009-12-01

    The monitoring of atmospheric radioxenon to ensure compliance with the Comprehensive Nuclear Test Ban Treaty has driven the development of improved detectors for measuring xenon, including the development of a phoswich detector. This detector uses only one PMT to detect beta-gamma coincidence, thus greatly reducing the bulk and electronics of the detector in comparison to the ARSA-type detector. In this experiment, 135Xe was produced through neutron activation and a phoswich detector was used to attain spectra from the gas. These results were compared to similar results from an ARSA-type beta-gamma coincidence spectrum. The spectral characteristics and resolution were compared for the coincidence and beta spectra. Using these metrics, the overall performance of the phoswich detector for beta-gamma coincidence of radioxenon was evaluated.

  16. Verifying the Comprehensive Nuclear-Test-Ban Treaty by Radioxenon Monitoring

    SciTech Connect

    Ringbom, Anders

    2005-05-24

    The current status of the ongoing establishment of a verification system for the Comprehensive Nuclear-Test-Ban Treaty using radioxenon detection is discussed. As an example of equipment used in this application the newly developed fully automatic noble gas sampling and detection system SAUNA is described, and data collected with this system are discussed. It is concluded that the most important remaining scientific challenges in the field concern event categorization and meteorological backtracking.

  17. Verifying the Comprehensive Nuclear-Test-Ban Treaty by Radioxenon Monitoring

    NASA Astrophysics Data System (ADS)

    Ringbom, Anders

    2005-05-01

    The current status of the ongoing establishment of a verification system for the Comprehensive Nuclear-Test-Ban Treaty using radioxenon detection is discussed. As an example of equipment used in this application the newly developed fully automatic noble gas sampling and detection system SAUNA is described, and data collected with this system are discussed. It is concluded that the most important remaining scientific challenges in the field concern event categorization and meteorological backtracking.

  18. Diabetes: Models, Signals, and Control

    PubMed Central

    Cobelli, Claudio; Man, Chiara Dalla; Sparacino, Giovanni; Magni, Lalo; De Nicolao, Giuseppe; Kovatchev, Boris P.

    2010-01-01

    The control of diabetes is an interdisciplinary endeavor, which includes a significant biomedical engineering component, with traditions of success beginning in the early 1960s. It began with modeling of the insulin-glucose system, and progressed to large-scale in silico experiments, and automated closed-loop control (artificial pancreas). Here, we follow these engineering efforts through the last, almost 50 years. We begin with the now classic minimal modeling approach and discuss a number of subsequent models, which have recently resulted in the first in silico simulation model accepted as substitute to animal trials in the quest for optimal diabetes control. We then review metabolic monitoring, with a particular emphasis on the new continuous glucose sensors, on the analyses of their time-series signals, and on the opportunities that they present for automation of diabetes control. Finally, we review control strategies that have been successfully employed in vivo or in silico, presenting a promise for the development of a future artificial pancreas and, in particular, discuss a modular architecture for building closed-loop control systems, including insulin delivery and patient safety supervision layers. We conclude with a brief discussion of the unique interactions between human physiology, behavioral events, engineering modeling and control relevant to diabetes. PMID:20936056

  19. Radioxenon detections in the CTBT International Monitoring System likely related to the announced nuclear test in North Korea conducted on February 12, 2013

    SciTech Connect

    Ringbom, Anders; Axelssson, A.; Aldener, M.; Auer, M.; Bowyer, Ted W.; Fritioff, T.; Hoffman, Ian; Khrustalev, Kirill; Nikkinen, Mika; Popov, Vladimir Y.; Popov, Y.; Ungar, R. Kurt; Wotawa, G.

    2014-02-01

    Abstract: Observations of the radioxenon isotopes 133Xe and 131mXe collected at the IMS stations RN38 and RN58 on April 7-8, and April 12-13 2013, respectively, are unique with respect to the measurement history of these stations. Comparison of measured data with calculated isotopic ratios as well as analysis using atmospheric transport modeling indicate that it is likely that the xenon measured was created in the underground nuclear test conducted by North Korea on February 12, 2013, and released 7 weeks later. More than one release is required to explain all observations. The 131mXe source terms for each release were calculated to 7x1011 Bq, corresponding to about 1-10% of the total xenon inventory for a 10-kt explosion, depending on fractionation and release scenario. The observed ratios could not be used to obtain any information regarding the fissile material that was used in the test.

  20. Sonar signal processing using probabilistic signal and ocean environmental models.

    PubMed

    Culver, R Lee; Camin, H John

    2008-12-01

    Acoustic signals propagating through the ocean are refracted, scattered, and attenuated by the ocean volume and boundaries. Many aspects of how the ocean affects acoustic propagation are understood, such that the characteristics of a received signal can often be predicted with some degree of certainty. However, acoustic ocean parameters vary with time and location in a manner that is not, and cannot be, precisely known; some uncertainty will always remain. For this reason, the characteristics of the received signal can never be precisely predicted and must be described in probabilistic terms. A signal processing structure recently developed relies on knowledge of the ocean environment to predict the statistical characteristics of the received signal, and incorporates this description into the processor in order to detect and classify targets. Acoustic measurements at 250 Hz from the 1996 Strait of Gibraltar Acoustic Monitoring Experiment are used to illustrate how the processor utilizes environmental data to classify source depth and to underscore the importance of environmental model fidelity and completeness.

  1. Low-energy degassing mechanisms for a fluid-based radioxenon detection system

    SciTech Connect

    Russ, W.R.; Stuenkel, D.O.; Valentine, J.D.; Gross, K.C.

    1998-09-01

    A method to concentrate heavy noble gases from the atmosphere using certain organic fluids is being developed. To use this technique in a system to monitor the atmosphere for important noble gas fission products (Xe-131, Xe-131m, Xe-133, Xe-133m, and Xe-135) generated by nuclear testing, the radionuclides captured in the fluid must either be detected in the fluid or degassed. This study presents experimental results for a number of possible degassing methods, including heating bubbling with a purge gas, ultrasonic agitation, vacuum, and combinations thereof. Methods were evaluated for energy and time requirements and dilution of the degas product. Initial experiments indicate that in addition to overcoming the standard desorption process dictated by partial pressures per Henry`s Law, a capture mechanism must also be overcome to degas. Some type of agitation, thermal or mechanical, can be used to release weakly trapped gas atoms from the fluid, while diffusional mass transfer can be enhanced through entrainment with a purge gas or use of a vacuum. Ultrasonic agitation of a thin film in a strong vacuum has been shown to be the most effective method of those tested. Implementation of an efficient degas system, along with an absorption system and radioxenon detector could result in an ultrasensitive fluid-based radioxenon measurement system that is more portable, less expensive, and simpler than charcoal-based systems which use cryogenic techniques.

  2. A Mathematical Model for Segmenting ECG Signals

    NASA Astrophysics Data System (ADS)

    Feier, Horea; Roşu, Doina; Falniţǎ, Lucian; Roşu, Şerban; Pater, Liana

    2010-09-01

    This paper deals with the behavior of the modulus of the continuous wavelet transform (CWT) for some known mother wavelets like the Morlet wavelet and the Mexican Hat. By exploiting these properties, the models presented can behave as a segmentation/ recognition signal processing tool by modeling the temporal structure of the observed surface ECG.

  3. A Multi-Layer Phoswich Radioxenon Detection System

    SciTech Connect

    David M. Hamby

    2008-07-14

    Laboratory radioactive sources were used to characterize the phoswich detector. The CaF{sub 2} scintillator has a low light-yield and slow decay time, thus produces very small signals due to low-energy gamma rays or X-rays. Therefore, detection of 30 keV X-rays (from the xenon radioisotopes) using this layer and discriminating its very small signals from electronic noise was a challenging task. Several solutions were considered and experimentally evaluated. We found that the best solution would be extending the fast triangular filter from 10 taps to 30 taps. This will extend the peaking time of this filter from 25 nsec to 75 nsec. The digital filter is implemented in FPGA on our DPP2.0 and is used to trigger the detection system. Functionality of the new filter in capturing and discriminating 30 keV X-rays was confirmed by using a {sup 133}Ba gamma-ray source. Development of the DPP GUI software has continued with the addition of two new panels to display histograms of beta/gamma and beta/x-ray coincidence events. This includes coincidence events from a single channel, as well as two-channel, coincidence event. A pileup rejection algorithm has been implemented in the FPGA code, and controls to adjust its sensitivity have been added to the GUI. Work has begun on a new prototype system to develop a USB host interface between the PC and the FPGA to end reliance on Opal Kelly prototyping boards; the hardware for this system has been completely assembled, and the PC-side software is currently in development.

  4. Patterns of flavor signals in supersymmetric models

    SciTech Connect

    Goto, Toru; Okada, Yasuhiro; Shindou, Tetsuo

    2008-05-01

    Quark and lepton flavor signals are studied in four supersymmetric models, namely, the minimal supergravity model, the minimal supersymmetric standard model with right-handed neutrinos, SU(5) supersymmetric grand unified theory with right-handed neutrinos, and the minimal supersymmetric standard model with U(2) flavor symmetry. We calculate b{yields}s(d) transition observables in B{sub d} and B{sub s} decays, taking the constraint from the B{sub s}-B{sub s} mixing recently observed at the Tevatron into account. We also calculate lepton flavor violating processes {mu}{yields}e{gamma}, {tau}{yields}{mu}{gamma}, and {tau}{yields}e{gamma} for the models with right-handed neutrinos. We investigate possibilities to distinguish the flavor structure of the supersymmetry breaking sector with use of patterns of various flavor signals which are expected to be measured in experiments such as MEG, LHCb, and a future Super B factory.

  5. Logical modelling of Drosophila signalling pathways.

    PubMed

    Mbodj, Abibatou; Junion, Guillaume; Brun, Christine; Furlong, Eileen E M; Thieffry, Denis

    2013-09-01

    A limited number of signalling pathways are involved in the specification of cell fate during the development of all animals. Several of these pathways were originally identified in Drosophila. To clarify their roles, and possible cross-talk, we have built a logical model for the nine key signalling pathways recurrently used in metazoan development. In each case, we considered the associated ligands, receptors, signal transducers, modulators, and transcription factors reported in the literature. Implemented using the logical modelling software GINsim, the resulting models qualitatively recapitulate the main characteristics of each pathway, in wild type as well as in various mutant situations (e.g. loss-of-function or gain-of-function). These models constitute pluggable modules that can be used to assemble comprehensive models of complex developmental processes. Moreover, these models of Drosophila pathways could serve as scaffolds for more complicated models of orthologous mammalian pathways. Comprehensive model annotations and GINsim files are provided for each of the nine considered pathways.

  6. Stochastic models of intracellular calcium signals

    NASA Astrophysics Data System (ADS)

    Rüdiger, Sten

    2014-01-01

    Cellular signaling operates in a noisy environment shaped by low molecular concentrations and cellular heterogeneity. For calcium release through intracellular channels-one of the most important cellular signaling mechanisms-feedback by liberated calcium endows fluctuations with critical functions in signal generation and formation. In this review it is first described, under which general conditions the environment makes stochasticity relevant, and which conditions allow approximating or deterministic equations. This analysis provides a framework, in which one can deduce an efficient hybrid description combining stochastic and deterministic evolution laws. Within the hybrid approach, Markov chains model gating of channels, while the concentrations of calcium and calcium binding molecules (buffers) are described by reaction-diffusion equations. The article further focuses on the spatial representation of subcellular calcium domains related to intracellular calcium channels. It presents analysis for single channels and clusters of channels and reviews the effects of buffers on the calcium release. For clustered channels, we discuss the application and validity of coarse-graining as well as approaches based on continuous gating variables (Fokker-Planck and chemical Langevin equations). Comparison with recent experiments substantiates the stochastic and spatial approach, identifies minimal requirements for a realistic modeling, and facilitates an understanding of collective channel behavior. At the end of the review, implications of stochastic and local modeling for the generation and properties of cell-wide release and the integration of calcium dynamics into cellular signaling models are discussed.

  7. Spatial Modeling of Cell Signaling Networks

    PubMed Central

    Cowan, Ann E.; Moraru, Ion I.; Schaff, James C.; Slepchenko, Boris M.; Loew, Leslie M.

    2012-01-01

    The shape of a cell, the sizes of subcellular compartments and the spatial distribution of molecules within the cytoplasm can all control how molecules interact to produce a cellular behavior. This chapter describes how these spatial features can be included in mechanistic mathematical models of cell signaling. The Virtual Cell computational modeling and simulation software is used to illustrate the considerations required to build a spatial model. An explanation of how to appropriately choose between physical formulations that implicitly or explicitly account for cell geometry and between deterministic vs, stochastic formulations for molecular dynamics is provided, along with a discussion of their respective strengths and weaknesses. As a first step toward constructing a spatial model, the geometry needs to be specified and associated with the molecules, reactions and membrane flux processes of the network. Initial conditions, diffusion coefficients, velocities and boundary conditions complete the specifications required to define the mathematics of the model. The numerical methods used to solve reaction-diffusion problems both deterministically and stochastically are then described and some guidance is provided in how to set up and run simulations. A study of cAMP signaling in neurons ends the chapter, providing an example of the insights that can be gained in interpreting experimental results through the application of spatial modeling. PMID:22482950

  8. Radioxenon detections in the CTBT international monitoring system likely related to the announced nuclear test in North Korea on February 12, 2013.

    PubMed

    Ringbom, A; Axelsson, A; Aldener, M; Auer, M; Bowyer, T W; Fritioff, T; Hoffman, I; Khrustalev, K; Nikkinen, M; Popov, V; Popov, Y; Ungar, K; Wotawa, G

    2014-02-01

    Observations made in April 2013 of the radioxenon isotopes (133)Xe and (131m)Xe at measurement stations in Japan and Russia, belonging to the International Monitoring System for verification of the Comprehensive Nuclear-Test-Ban Treaty, are unique with respect to the measurement history of these stations. Comparison of measured data with calculated isotopic ratios as well as analysis using atmospheric transport modeling indicate that it is likely that the xenon measured was created in the underground nuclear test conducted by North Korea on February 12, 2013, and released 7-8 weeks later. More than one release is required to explain all observations. The (131m)Xe source terms for each release were calculated to 0.7 TBq, corresponding to about 1-10% of the total xenon inventory for a 10 kt explosion, depending on fractionation and release scenario. The observed ratios could not be used to obtain any information regarding the fissile material that was used in the test.

  9. Logic integer programming models for signaling networks.

    PubMed

    Haus, Utz-Uwe; Niermann, Kathrin; Truemper, Klaus; Weismantel, Robert

    2009-05-01

    We propose a static and a dynamic approach to model biological signaling networks, and show how each can be used to answer relevant biological questions. For this, we use the two different mathematical tools of Propositional Logic and Integer Programming. The power of discrete mathematics for handling qualitative as well as quantitative data has so far not been exploited in molecular biology, which is mostly driven by experimental research, relying on first-order or statistical models. The arising logic statements and integer programs are analyzed and can be solved with standard software. For a restricted class of problems the logic models reduce to a polynomial-time solvable satisfiability algorithm. Additionally, a more dynamic model enables enumeration of possible time resolutions in poly-logarithmic time. Computational experiments are included.

  10. Nonthermal dark matter models and signals

    NASA Astrophysics Data System (ADS)

    Okada, Hiroshi; Orikasa, Yuta; Toma, Takashi

    2016-03-01

    Many experiments exploring weakly interacting massive particles (WIMPs) such as direct, indirect and collider searches have been carried out until now. However, a clear signal of a WIMP has not been found yet and it makes us to suspect that WIMPs are questionable as a dark matter candidate. Taking into account this situation, we propose two models in which dark matter relic density is produced by decay of a metastable particle. In the first model, the metastable particle is a feebly interacting massive particle, which is the so-called FIMP, produced by freeze-in mechanism in the early universe. In the second model, the decaying particle is thermally produced the same as the usual WIMP. However decay of the particle into dark matter is led by a higher dimensional operator. As a phenomenologically interesting feature of nonthermal dark matter discussed in this paper, a strong sharp gamma-ray emission as an indirect detection signal occurs due to internal bremsstrahlung, although some parameter space has already been ruled out by this process. Moreover combining other experimental and theoretical constraints such as dark matter relic density, big bang nucleosynthesis, collider, gamma-rays and perturbativity of couplings, we discuss the two nonthermal DM models.

  11. Maximum reasonable radioxenon releases from medical isotope production facilities and their effect on monitoring nuclear explosions.

    PubMed

    Bowyer, Theodore W; Kephart, Rosara; Eslinger, Paul W; Friese, Judah I; Miley, Harry S; Saey, Paul R J

    2013-01-01

    Fission gases such as (133)Xe are used extensively for monitoring the world for signs of nuclear testing in systems such as the International Monitoring System (IMS). These gases are also produced by nuclear reactors and by fission production of (99)Mo for medical use. Recently, medical isotope production facilities have been identified as the major contributor to the background of radioactive xenon isotopes (radioxenon) in the atmosphere (Stocki et al., 2005; Saey, 2009). These releases pose a potential future problem for monitoring nuclear explosions if not addressed. As a starting point, a maximum acceptable daily xenon emission rate was calculated, that is both scientifically defendable as not adversely affecting the IMS, but also consistent with what is possible to achieve in an operational environment. This study concludes that an emission of 5 × 10(9) Bq/day from a medical isotope production facility would be both an acceptable upper limit from the perspective of minimal impact to monitoring stations, but also appears to be an achievable limit for large isotope producers. PMID:22995862

  12. Maximum reasonable radioxenon releases from medical isotope production facilities and their effect on monitoring nuclear explosions.

    PubMed

    Bowyer, Theodore W; Kephart, Rosara; Eslinger, Paul W; Friese, Judah I; Miley, Harry S; Saey, Paul R J

    2013-01-01

    Fission gases such as (133)Xe are used extensively for monitoring the world for signs of nuclear testing in systems such as the International Monitoring System (IMS). These gases are also produced by nuclear reactors and by fission production of (99)Mo for medical use. Recently, medical isotope production facilities have been identified as the major contributor to the background of radioactive xenon isotopes (radioxenon) in the atmosphere (Stocki et al., 2005; Saey, 2009). These releases pose a potential future problem for monitoring nuclear explosions if not addressed. As a starting point, a maximum acceptable daily xenon emission rate was calculated, that is both scientifically defendable as not adversely affecting the IMS, but also consistent with what is possible to achieve in an operational environment. This study concludes that an emission of 5 × 10(9) Bq/day from a medical isotope production facility would be both an acceptable upper limit from the perspective of minimal impact to monitoring stations, but also appears to be an achievable limit for large isotope producers.

  13. International challenge to predict the impact of radioxenon releases from medical isotope production on a comprehensive nuclear test ban treaty sampling station.

    PubMed

    Eslinger, Paul W; Bowyer, Ted W; Achim, Pascal; Chai, Tianfeng; Deconninck, Benoit; Freeman, Katie; Generoso, Sylvia; Hayes, Philip; Heidmann, Verena; Hoffman, Ian; Kijima, Yuichi; Krysta, Monika; Malo, Alain; Maurer, Christian; Ngan, Fantine; Robins, Peter; Ross, J Ole; Saunier, Olivier; Schlosser, Clemens; Schöppner, Michael; Schrom, Brian T; Seibert, Petra; Stein, Ariel F; Ungar, Kurt; Yi, Jing

    2016-06-01

    The International Monitoring System (IMS) is part of the verification regime for the Comprehensive Nuclear-Test-Ban-Treaty Organization (CTBTO). At entry-into-force, half of the 80 radionuclide stations will be able to measure concentrations of several radioactive xenon isotopes produced in nuclear explosions, and then the full network may be populated with xenon monitoring afterward. An understanding of natural and man-made radionuclide backgrounds can be used in accordance with the provisions of the treaty (such as event screening criteria in Annex 2 to the Protocol of the Treaty) for the effective implementation of the verification regime. Fission-based production of (99)Mo for medical purposes also generates nuisance radioxenon isotopes that are usually vented to the atmosphere. One of the ways to account for the effect emissions from medical isotope production has on radionuclide samples from the IMS is to use stack monitoring data, if they are available, and atmospheric transport modeling. Recently, individuals from seven nations participated in a challenge exercise that used atmospheric transport modeling to predict the time-history of (133)Xe concentration measurements at the IMS radionuclide station in Germany using stack monitoring data from a medical isotope production facility in Belgium. Participants received only stack monitoring data and used the atmospheric transport model and meteorological data of their choice. Some of the models predicted the highest measured concentrations quite well. A model comparison rank and ensemble analysis suggests that combining multiple models may provide more accurate predicted concentrations than any single model. None of the submissions based only on the stack monitoring data predicted the small measured concentrations very well. Modeling of sources by other nuclear facilities with smaller releases than medical isotope production facilities may be important in understanding how to discriminate those releases from

  14. International challenge to predict the impact of radioxenon releases from medical isotope production on a comprehensive nuclear test ban treaty sampling station.

    PubMed

    Eslinger, Paul W; Bowyer, Ted W; Achim, Pascal; Chai, Tianfeng; Deconninck, Benoit; Freeman, Katie; Generoso, Sylvia; Hayes, Philip; Heidmann, Verena; Hoffman, Ian; Kijima, Yuichi; Krysta, Monika; Malo, Alain; Maurer, Christian; Ngan, Fantine; Robins, Peter; Ross, J Ole; Saunier, Olivier; Schlosser, Clemens; Schöppner, Michael; Schrom, Brian T; Seibert, Petra; Stein, Ariel F; Ungar, Kurt; Yi, Jing

    2016-06-01

    The International Monitoring System (IMS) is part of the verification regime for the Comprehensive Nuclear-Test-Ban-Treaty Organization (CTBTO). At entry-into-force, half of the 80 radionuclide stations will be able to measure concentrations of several radioactive xenon isotopes produced in nuclear explosions, and then the full network may be populated with xenon monitoring afterward. An understanding of natural and man-made radionuclide backgrounds can be used in accordance with the provisions of the treaty (such as event screening criteria in Annex 2 to the Protocol of the Treaty) for the effective implementation of the verification regime. Fission-based production of (99)Mo for medical purposes also generates nuisance radioxenon isotopes that are usually vented to the atmosphere. One of the ways to account for the effect emissions from medical isotope production has on radionuclide samples from the IMS is to use stack monitoring data, if they are available, and atmospheric transport modeling. Recently, individuals from seven nations participated in a challenge exercise that used atmospheric transport modeling to predict the time-history of (133)Xe concentration measurements at the IMS radionuclide station in Germany using stack monitoring data from a medical isotope production facility in Belgium. Participants received only stack monitoring data and used the atmospheric transport model and meteorological data of their choice. Some of the models predicted the highest measured concentrations quite well. A model comparison rank and ensemble analysis suggests that combining multiple models may provide more accurate predicted concentrations than any single model. None of the submissions based only on the stack monitoring data predicted the small measured concentrations very well. Modeling of sources by other nuclear facilities with smaller releases than medical isotope production facilities may be important in understanding how to discriminate those releases from

  15. Wideband radar signal modeling of ground moving targets in clutter

    NASA Astrophysics Data System (ADS)

    Malas, John A.; Pasala, Krishna M.; Westerkamp, John J.

    2002-08-01

    Research in the area of air-to-ground target detection, track and identification (ID) requires the development of target signal models for known geometric shapes moving in ground clutter. Space-time adaptive filtering techniques in particular make good use of temporal-spatial synthetic radar signal return data. A radar signal model is developed to generate synthetic wideband radar signal data for use in multi-channel adaptive signal processing.

  16. Modelling protein functional domains in signal transduction using Maude

    NASA Technical Reports Server (NTRS)

    Sriram, M. G.

    2003-01-01

    Modelling of protein-protein interactions in signal transduction is receiving increased attention in computational biology. This paper describes recent research in the application of Maude, a symbolic language founded on rewriting logic, to the modelling of functional domains within signalling proteins. Protein functional domains (PFDs) are a critical focus of modern signal transduction research. In general, Maude models can simulate biological signalling networks and produce specific testable hypotheses at various levels of abstraction. Developing symbolic models of signalling proteins containing functional domains is important because of the potential to generate analyses of complex signalling networks based on structure-function relationships.

  17. Improvements of low-level radioxenon detection sensitivity by a state-of-the art coincidence setup.

    PubMed

    Cagniant, A; Le Petit, G; Gross, P; Douysset, G; Richard-Bressand, H; Fontaine, J-P

    2014-05-01

    The ability to quantify isotopic ratios of 135, 133 m, 133 and 131 m radioxenon is essential for the verification of the Comprehensive Nuclear-Test Ban Treaty (CTBT). In order to improve detection limits, CEA has developed a new on-site setup using photon/electron coincidence (Le Petit et al., 2013. J. Radioanal. Nucl. Chem., DOI : 10.1007/s 10697-013-2525-8.). Alternatively, the electron detection cell equipped with large silicon chips (PIPS) can be used with HPGe detector for laboratory analysis purpose. This setup allows the measurement of β/γ coincidences for the detection of (133)Xe and (135)Xe; and K-shell Conversion Electrons (K-CE)/X-ray coincidences for the detection of (131m)Xe, (133m)Xe and (133)Xe as well. Good energy resolution of 11 keV at 130 keV and low energy threshold of 29 keV for the electron detection were obtained. This provides direct discrimination between K-CE from (133)Xe, (133m)Xe and (131m)Xe. Estimation of Minimum Detectable Activity (MDA) for (131m)Xe is in the order of 1mBq over a 4 day measurement. An analysis of an environmental radioxenon sample using this method is shown. PMID:24332879

  18. Inverse Modelling to Obtain Head Movement Controller Signal

    NASA Technical Reports Server (NTRS)

    Kim, W. S.; Lee, S. H.; Hannaford, B.; Stark, L.

    1984-01-01

    Experimentally obtained dynamics of time-optimal, horizontal head rotations have previously been simulated by a sixth order, nonlinear model driven by rectangular control signals. Electromyography (EMG) recordings have spects which differ in detail from the theoretical rectangular pulsed control signal. Control signals for time-optimal as well as sub-optimal horizontal head rotations were obtained by means of an inverse modelling procedures. With experimentally measured dynamical data serving as the input, this procedure inverts the model to produce the neurological control signals driving muscles and plant. The relationships between these controller signals, and EMG records should contribute to the understanding of the neurological control of movements.

  19. Signal Processing Model for Radiation Transport

    SciTech Connect

    Chambers, D H

    2008-07-28

    This note describes the design of a simplified gamma ray transport model for use in designing a sequential Bayesian signal processor for low-count detection and classification. It uses a simple one-dimensional geometry to describe the emitting source, shield effects, and detector (see Fig. 1). At present, only Compton scattering and photoelectric absorption are implemented for the shield and the detector. Other effects may be incorporated in the future by revising the expressions for the probabilities of escape and absorption. Pair production would require a redesign of the simulator to incorporate photon correlation effects. The initial design incorporates the physical effects that were present in the previous event mode sequence simulator created by Alan Meyer. The main difference is that this simulator transports the rate distributions instead of single photons. Event mode sequences and other time-dependent photon flux sequences are assumed to be marked Poisson processes that are entirely described by their rate distributions. Individual realizations can be constructed from the rate distribution using a random Poisson point sequence generator.

  20. New approach in bats' sonar signals parametrization and modelling

    NASA Astrophysics Data System (ADS)

    Herman, Krzysztof; Gudra, Tadeusz

    2010-01-01

    Parameterization of bats' echolocation signal is essentially based on determination of spectral power density by means of the classic Fourier transform FFT. This study presents an alternative solution in this area of research, that is parametric and non-parametric modelling of short-time signals. The above mentioned methods are based on modelling of white noise with the use of digital filters the transmission of which was set in a way that allows the output signal to be as close to the modelled signal as possible. Proper selection of parameterization method - MA (Moving Average), AR (Autoregressive), ARMA (Autoregressive Moving Average), in respect of the character of signal spectrum (line spectrum, noise) maximally reduces the number of filter coefficients and improves the accuracy of bat's signal modelling. The work also presents the possibility of using the suggested parameterization methods in automatic species identification.

  1. Dynalets: a new method for modelling and compressing biological signals. Applications to physiological and molecular signals.

    PubMed

    Demongeot, Jacques; Hansen, Olivier; Hamie, Ali; Franco, Céline; Sutton, Brian; Cohen, Elie-Paul

    2014-11-01

    The biological information coming from electrophysiologic sensors like ECG, pulse sensor or from molecular signal devices like NMR spectrometry has to be visualized and manipulated in a compressed way for an efficient medical use by clinicians, if stored in scientific data bases or in personalized patient records repositories. Here, we define a new transform called Dynalet based on Liénard ordinary differential equations susceptible to model the mechanism at the source of the studied signal, and we propose to apply this new technique first to the modelling and compression of real biological periodic signals like ECG and pulse rhythm. We consider that the cardiovascular activity results from the summation of cellular oscillators located in the cardiac sinus node and we show that, as a result, the van der Pol oscillator (a particular Liénard system) fits well the ECG signal and the pulse signal. The reconstruction of the original signal (pulse or ECG) using Dynalet transform is then compared with that of Fourier, counting the number of parameters to be set for obtaining an expected signal-to-noise ratio. Then, we apply the Dynalet transform to the modelling and compression of molecular spectra obtained by protein NMR spectroscopy. The reconstruction of the original signal (peak) using Dynalet transform is again compared with that of Fourier. After reconstructing visually the peak, we propose to periodize the signal and give it to hear, the whole process being called the protein "stethoscope". PMID:25444705

  2. A Dynamic Stimulus-Driven Model of Signal Detection

    ERIC Educational Resources Information Center

    Turner, Brandon M.; Van Zandt, Trisha; Brown, Scott

    2011-01-01

    Signal detection theory forms the core of many current models of cognition, including memory, choice, and categorization. However, the classic signal detection model presumes the a priori existence of fixed stimulus representations--usually Gaussian distributions--even when the observer has no experience with the task. Furthermore, the classic…

  3. LHC diphoton Higgs signal predicted by little Higgs models

    SciTech Connect

    Wang Lei; Yang Jinmin

    2011-10-01

    Little Higgs theory naturally predicts a light Higgs boson whose most important discovery channel at the LHC is the diphoton signal pp{yields}h{yields}{gamma}{gamma}. In this work, we perform a comparative study for this signal in some typical little Higgs models, namely, the littlest Higgs model, two littlest Higgs models with T-parity (named LHT-I and LHT-II), and the simplest little Higgs models. We find that compared with the standard model prediction, the diphoton signal rate is always suppressed and the suppression extent can be quite different for different models. The suppression is mild (< or approx. 10%) in the littlest Higgs model but can be quite severe ({approx_equal}90%) in other three models. This means that discovering the light Higgs boson predicted by the little Higgs theory through the diphoton channel at the LHC will be more difficult than discovering the standard model Higgs boson.

  4. Analytical model of signal amplification in silicon waveguides

    NASA Astrophysics Data System (ADS)

    Meng, Fan; Yu, Chong-Xiu; Yuan, Jin-Hui

    2012-07-01

    In this paper, an analytical model to investigate the parametric amplification (PA) and the PA + stimulated Raman scattering (SRS) in silicon waveguides is put forward. When two pump signals are employed, the PA bandwidth of the probe signal is so large that the Raman contribution has to be considered. When Raman contribution fraction f is set to be 0, only the PA occurs to amplify the probe signal, and when f is set to be 0.043, the PA and the SRS amplify the probe signal at the same time. The signal amplifications of both single and dual pump schemes are investigated by using this model. With this model, three main affecting factors, i.e., zero dispersion wavelength (ZDWL), third-order dispersion (TOD), and fourth-order dispersion (FOD), are discussed in detail.

  5. Modeling laser velocimeter signals as triply stochastic Poisson processes

    NASA Technical Reports Server (NTRS)

    Mayo, W. T., Jr.

    1976-01-01

    Previous models of laser Doppler velocimeter (LDV) systems have not adequately described dual-scatter signals in a manner useful for analysis and simulation of low-level photon-limited signals. At low photon rates, an LDV signal at the output of a photomultiplier tube is a compound nonhomogeneous filtered Poisson process, whose intensity function is another (slower) Poisson process with the nonstationary rate and frequency parameters controlled by a random flow (slowest) process. In the present paper, generalized Poisson shot noise models are developed for low-level LDV signals. Theoretical results useful in detection error analysis and simulation are presented, along with measurements of burst amplitude statistics. Computer generated simulations illustrate the difference between Gaussian and Poisson models of low-level signals.

  6. A biologically inspired model for signal compression

    NASA Astrophysics Data System (ADS)

    McDonnell, Mark D.; Abbott, Derek

    2007-12-01

    A model of a biological sensory neuron stimulated by a noisy analog information source is considered. It is demonstrated that action-potential generation by the neuron model can be described in terms of lossy compression theory. Lossy compression is generally characterized by (i) how much distortion is introduced, on average, due to a loss of information, and (ii) the 'rate,' or the amount of compression. Conventional compression theory is used to measure the performance of the model in terms of both distortion and rate, and the tradeoff between each. The model's applicability to a number of situations relevant to biomedical engineering, including cochlear implants, and bio-sensors is discussed.

  7. Software for multimodal battlefield signal modeling and optimal sensor placement

    NASA Astrophysics Data System (ADS)

    Yamamoto, Kenneth K.; Vecherin, Sergey N.; Wilson, D. Keith; Borden, Christian T.; Bettencourt, Elizabeth; Pettit, Chris L.

    2012-05-01

    Effective use of passive and active sensors for surveillance, security, and intelligence must consider terrain and atmospheric effects on the sensor performance. Several years ago, U.S. Army ERDC undertook development of software for modeling environmental effects on target signatures, signal propagation, and battlefield sensors for many signal modalities (e.g., optical, acoustic, seismic, magnetic, radio-frequency, chemical, biological, and nuclear). Since its inception, the software, called Environmental Awareness for Sensor and Emitter Employment (EASEE), has matured and evolved significantly for simulating a broad spectrum of signal-transmission and sensing scenarios. The underlying software design involves a flexible, object-oriented approach to the various stages of signal modeling from emission through processing into inferences. A sensor placement algorithm has also been built in for optimizing sensor selections and placements based on specification of sensor supply limitations, coverage priorities, and wireless sensor communication requirements. Some recent and ongoing enhancements are described, including modeling of active sensing scenarios and signal reflections, directivity of signal emissions and sensors, improved handling of signal feature dependencies, extensions to realistically model additional signal modalities such as infrared and RF, and XML-based communication with other calculation and display engines.

  8. Modeling of Nonlinear Beat Signals of TAE's

    NASA Astrophysics Data System (ADS)

    Zhang, Bo; Berk, Herbert; Breizman, Boris; Zheng, Linjin

    2012-03-01

    Experiments on Alcator C-Mod reveal Toroidal Alfven Eigenmodes (TAE) together with signals at various beat frequencies, including those at twice the mode frequency. The beat frequencies are sidebands driven by quadratic nonlinear terms in the MHD equations. These nonlinear sidebands have not yet been quantified by any existing codes. We extend the AEGIS code to capture nonlinear effects by treating the nonlinear terms as a driving source in the linear MHD solver. Our goal is to compute the spatial structure of the sidebands for realistic geometry and q-profile, which can be directly compared with experiment in order to interpret the phase contrast imaging diagnostic measurements and to enable the quantitative determination of the Alfven wave amplitude in the plasma core

  9. Dynamic Signal Tracking in a Simple V1 Spiking Model.

    PubMed

    Lajoie, Guillaume; Young, Lai-Sang

    2016-09-01

    This work is part of an effort to understand the neural basis for our visual system's ability, or failure, to accurately track moving visual signals. We consider here a ring model of spiking neurons, intended as a simplified computational model of a single hypercolumn of the primary visual cortex of primates. Signals that consist of edges with time-varying orientations localized in space are considered. Our model is calibrated to produce spontaneous and driven firing rates roughly consistent with experiments, and our two main findings, for which we offer dynamical explanation on the level of neuronal interactions, are the following. First, we have documented consistent transient overshoots in signal perception following signal switches due to emergent interactions of the E- and I-populations. Second, for continuously moving signals, we have found that accuracy is considerably lower at reversals of orientation than when continuing in the same direction (as when the signal is a rotating bar). To measure performance, we use two metrics, called fidelity and reliability, to compare signals reconstructed by the system to the ones presented and assess trial-to-trial variability. We propose that the same population mechanisms responsible for orientation selectivity also impose constraints on dynamic signal tracking that manifest in perception failures consistent with psychophysical observations. PMID:27391687

  10. Bayesian hierarchical modeling for detecting safety signals in clinical trials.

    PubMed

    Xia, H Amy; Ma, Haijun; Carlin, Bradley P

    2011-09-01

    Detection of safety signals from clinical trial adverse event data is critical in drug development, but carries a challenging statistical multiplicity problem. Bayesian hierarchical mixture modeling is appealing for its ability to borrow strength across subgroups in the data, as well as moderate extreme findings most likely due merely to chance. We implement such a model for subject incidence (Berry and Berry, 2004 ) using a binomial likelihood, and extend it to subject-year adjusted incidence rate estimation under a Poisson likelihood. We use simulation to choose a signal detection threshold, and illustrate some effective graphics for displaying the flagged signals.

  11. Modeling Protein Expression and Protein Signaling Pathways

    PubMed Central

    Telesca, Donatello; Müller, Peter; Kornblau, Steven M.; Suchard, Marc A.; Ji, Yuan

    2015-01-01

    High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case, inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The proposed approach exploits available expert knowledge about the target pathway to define an informative prior on the hidden conditional dependence structure. An important feature of this prior is that it provides an instrument to explicitly anchor the model space to a set of interactions of interest, favoring a local search approach to model determination. We apply our model to reverse-phase protein array data from a study on acute myeloid leukemia. Our inference identifies relevant subpathways in relation to the unfolding of the biological process under study. PMID:26246646

  12. Collective signaling behavior in a networked-oscillator model

    NASA Astrophysics Data System (ADS)

    Liu, Z.-H.; Hui, P. M.

    2007-09-01

    We propose and study the collective behavior of a model of networked signaling objects that incorporates several ingredients of real-life systems. These ingredients include spatial inhomogeneity with grouping of signaling objects, signal attenuation with distance, and delayed and impulsive coupling between non-identical signaling objects. Depending on the coupling strength and/or time-delay effect, the model exhibits completely, partially, and locally collective signaling behavior. In particular, a correlated signaling (CS) behavior is observed in which there exist time durations when nearly a constant fraction of oscillators in the system are in the signaling state. These time durations are much longer than the duration of a spike when a single oscillator signals, and they are separated by regular intervals in which nearly all oscillators are silent. Such CS behavior is similar to that observed in biological systems such as fireflies, cicadas, crickets, and frogs. The robustness of the CS behavior against noise is also studied. It is found that properly adjusting the coupling strength and noise level could enhance the correlated behavior.

  13. Modeling Horizontal GPS Seasonal Signals Caused by Ocean Loading

    NASA Astrophysics Data System (ADS)

    Bartlow, N. M.; Fialko, Y. A.

    2014-12-01

    GPS monuments around the world exhibit seasonal signals in both the horizontal and vertical components with amplitudes on the order of centimeters. For analysis of tectonic signals, researchers typically fit and remove a sine wave with an annual period, and sometimes an additional sine wave with a semiannual period. As interest grows in analyzing smaller, slower signals it becomes more important to correct for these seasonal signals accurately. It is well established that the vertical component of seasonal GPS signals is largely due to continental water storage cycles (e.g. van Dam et al., GRL, 2001). Horizontal seasonal signals however are not well explained by continental water storage. We examine horizontal seasonal signals across western North America and find that the horizontal component is coherent at very large spatial scales and is in general oriented perpendicular to the nearest coastline, indicating an oceanic origin. Additionally, horizontal and vertical annual signals are out of phase by approximately 2 months indicating different physical origins. Studies of GRACE and ocean bottom pressure data indicate an annual variation of non-steric, non-tidal ocean height with an average amplitude of 1 cm globally (e.g. Ponte et al., GRL, 2007). We use Some Programs for Ocean Tide Loading (SPOTL; Agnew, SIO Technical Report, 2012) to model predicted displacements due to these (non-tidal) ocean loads and find general agreement with observed horizontal GPS seasonal signals. In the future, this may lead to a more accurate way to predict and remove the seasonal component of GPS displacement time-series, leading to better discrimination of the true tectonic signal. Modeling this long wavelength signal also provides a potential opportunity to probe the structure of the Earth.

  14. Modeling Neuronal Current MRI Signal with Human Neuron

    PubMed Central

    Luo, Qingfei; Jiang, Xia; Chen, Bin; Zhu, Yi; Gao, Jia-Hong

    2010-01-01

    Up to date, no consensus has been achieved regarding the possibility of detecting neuronal currents by MRI (ncMRI) in human brain. To evaluate the detectability of ncMRI, an effective way is to simulate ncMRI signal with the realistic neuronal geometry and electrophysiological processes. Unfortunately, previous realistic ncMRI models are based on rat and monkey neurons. The species difference in neuronal morphology and physiology would prevent these models from simulating the ncMRI signal accurately in human subjects. The aim of the present study is to bridge this gap by establishing a realistic ncMRI model specifically for human cerebral cortex. In this model, the ncMRI signal was simulated using anatomically reconstructed human pyramidal neurons and their biophysical properties. The modeling results showed that the amplitude of ncMRI signal significantly depends on the density of synchronously firing neurons and imaging conditions such as position of imaging voxel, direction of main magnetic field (B0) relative to the cortical surface and echo time. The results indicated that physiologically-evoked ncMRI signal is too weak to be detected (magnitude/phase change ≤ -1.4×10−6/0.02°), but the phase signal induced by spontaneous activity may reach a detectable level (up to 0.2°) in favorable conditions. PMID:21254209

  15. Small-signal model for the series resonant converter

    NASA Technical Reports Server (NTRS)

    King, R. J.; Stuart, T. A.

    1985-01-01

    The results of a previous discrete-time model of the series resonant dc-dc converter are reviewed and from these a small signal dynamic model is derived. This model is valid for low frequencies and is based on the modulation of the diode conduction angle for control. The basic converter is modeled separately from its output filter to facilitate the use of these results for design purposes. Experimental results are presented.

  16. Wnt signaling and gastrointestinal tumorigenesis in mouse models.

    PubMed

    Taketo, M M

    2006-12-01

    The canonical Wnt signaling plays important roles in embryonic development and tumorigenesis. For the latter, induced mutations in mice have greatly contributed to our understanding of the molecular mechanisms of cancer initiation and progression. Here, I will review recent reports on gastrointestinal cancer model mice, with an emphasis on the roles of the Wnt signal pathway. They include: mouse models for familial adenomatous polyposis; modifying factors that affect mouse intestinal polyposis, including the genes that help cancer progression; Wnt target genes that affect mouse intestinal polyposis; and a mouse model of gastric cancer that mimics Helicobacter pyroli infection. PMID:17143296

  17. Modeling Signal Transduction and Lipid Rafts in Immune Cells

    NASA Astrophysics Data System (ADS)

    Prasad, Ashok

    2011-03-01

    Experimental evidence increasingly suggests that lipid rafts are nanometer sized cholesterol dependent dynamic assemblies enriched in sphingolipids and associated proteins. Lipid rafts are dynamic structures that break-up and reform on a relatively short time-scale, and are believed to facilitate the interactions of raft-associated proteins. The role of these rafts in signaling has been controversial, partly due to controversies regarding the existence and nature of the rafts themselves. Experimental evidence has indicated that in several cell types, especially T cells, rafts do influence signal transduction and T cell activation. Given the emerging consensus on the biophysical character of lipid rafts, the question can be asked as to what roles they possibly play in signal transduction. Here we carry out simulations of minimal models of the signal transduction network that regulates Src-family kinase dynamics in T cells and other cell types. By separately treating raft-based biochemical interactions, we find that rafts can indeed putatively play an important role in signal transduction, and in particular may affect the sensitivity of signal transduction. This illuminates possible functional consequences of membrane heterogeneities on signal transduction and points towards mechanisms for spatial control of signaling by cells.

  18. Detection of visual signals by rats: A computational model

    EPA Science Inventory

    We applied a neural network model of classical conditioning proposed by Schmajuk, Lam, and Gray (1996) to visual signal detection and discrimination tasks designed to assess sustained attention in rats (Bushnell, 1999). The model describes the animals’ expectation of receiving fo...

  19. Stimulus design for model selection and validation in cell signaling.

    PubMed

    Apgar, Joshua F; Toettcher, Jared E; Endy, Drew; White, Forest M; Tidor, Bruce

    2008-02-01

    Mechanism-based chemical kinetic models are increasingly being used to describe biological signaling. Such models serve to encapsulate current understanding of pathways and to enable insight into complex biological processes. One challenge in model development is that, with limited experimental data, multiple models can be consistent with known mechanisms and existing data. Here, we address the problem of model ambiguity by providing a method for designing dynamic stimuli that, in stimulus-response experiments, distinguish among parameterized models with different topologies, i.e., reaction mechanisms, in which only some of the species can be measured. We develop the approach by presenting two formulations of a model-based controller that is used to design the dynamic stimulus. In both formulations, an input signal is designed for each candidate model and parameterization so as to drive the model outputs through a target trajectory. The quality of a model is then assessed by the ability of the corresponding controller, informed by that model, to drive the experimental system. We evaluated our method on models of antibody-ligand binding, mitogen-activated protein kinase (MAPK) phosphorylation and de-phosphorylation, and larger models of the epidermal growth factor receptor (EGFR) pathway. For each of these systems, the controller informed by the correct model is the most successful at designing a stimulus to produce the desired behavior. Using these stimuli we were able to distinguish between models with subtle mechanistic differences or where input and outputs were multiple reactions removed from the model differences. An advantage of this method of model discrimination is that it does not require novel reagents, or altered measurement techniques; the only change to the experiment is the time course of stimulation. Taken together, these results provide a strong basis for using designed input stimuli as a tool for the development of cell signaling models. PMID

  20. Reduced modeling of signal transduction – a modular approach

    PubMed Central

    Koschorreck, Markus; Conzelmann, Holger; Ebert, Sybille; Ederer, Michael; Gilles, Ernst Dieter

    2007-01-01

    Background Combinatorial complexity is a challenging problem in detailed and mechanistic mathematical modeling of signal transduction. This subject has been discussed intensively and a lot of progress has been made within the last few years. A software tool (BioNetGen) was developed which allows an automatic rule-based set-up of mechanistic model equations. In many cases these models can be reduced by an exact domain-oriented lumping technique. However, the resulting models can still consist of a very large number of differential equations. Results We introduce a new reduction technique, which allows building modularized and highly reduced models. Compared to existing approaches further reduction of signal transduction networks is possible. The method also provides a new modularization criterion, which allows to dissect the model into smaller modules that are called layers and can be modeled independently. Hallmarks of the approach are conservation relations within each layer and connection of layers by signal flows instead of mass flows. The reduced model can be formulated directly without previous generation of detailed model equations. It can be understood and interpreted intuitively, as model variables are macroscopic quantities that are converted by rates following simple kinetics. The proposed technique is applicable without using complex mathematical tools and even without detailed knowledge of the mathematical background. However, we provide a detailed mathematical analysis to show performance and limitations of the method. For physiologically relevant parameter domains the transient as well as the stationary errors caused by the reduction are negligible. Conclusion The new layer based reduced modeling method allows building modularized and strongly reduced models of signal transduction networks. Reduced model equations can be directly formulated and are intuitively interpretable. Additionally, the method provides very good approximations especially for

  1. Plant hormone signaling during development: insights from computational models.

    PubMed

    Oliva, Marina; Farcot, Etienne; Vernoux, Teva

    2013-02-01

    Recent years have seen an impressive increase in our knowledge of the topology of plant hormone signaling networks. The complexity of these topologies has motivated the development of models for several hormones to aid understanding of how signaling networks process hormonal inputs. Such work has generated essential insights into the mechanisms of hormone perception and of regulation of cellular responses such as transcription in response to hormones. In addition, modeling approaches have contributed significantly to exploring how spatio-temporal regulation of hormone signaling contributes to plant growth and patterning. New tools have also been developed to obtain quantitative information on hormone distribution during development and to test model predictions, opening the way for quantitative understanding of the developmental roles of hormones.

  2. Experimental measurements of seismoelectric signals in borehole models

    NASA Astrophysics Data System (ADS)

    Wang, Jun; Hu, Hengshan; Guan, Wei

    2015-12-01

    An experimental system is built for the electrokinetic measurements with a small scaled seismoelectric detector and a high resolution digitizer (1 MS s-1, 22 bits). The acoustic and seismoelectric experiments are carried out in different borehole models at the high frequency of 90 kHz in the laboratory. All the localized seismoelectric signals that accompany compressional wave, shear wave and Stoneley wave are first clearly observed with a monopole source in sandstone boreholes that are saturated by tap water. The amplitudes of these signals are measured in the range of 1-120 μV, which is useful for designing the seismoelectric logging instruments. Then the amplitude ratio of electric signal to acoustic pressure (REP) for each of the three waves is calculated and compared with the theoretical simulations. Based on the experimental data, we find that seismoelectric logging signals as well as REP become stronger at the more permeable borehole model. We also find that seismoelectric logging signals are more sensitive to permeability and porosity compared with acoustic logging signals. Therefore, this study verifies the feasibility of seismoelectric well logging, and further indicates that the seismoelectric logging technique might be a preferable method to estimate formation parameters in the field measurements.

  3. Reference analysis of the signal + background model in counting experiments

    NASA Astrophysics Data System (ADS)

    Casadei, D.

    2012-01-01

    The model representing two independent Poisson processes, labelled as ``signal'' and ``background'' and both contributing additively to the total number of counted events, is considered from a Bayesian point of view. This is a widely used model for the searches of rare or exotic events in presence of a background source, as for example in the searches performed by high-energy physics experiments. In the assumption of prior knowledge about the background yield, a reference prior is obtained for the signal alone and its properties are studied. Finally, the properties of the full solution, the marginal reference posterior, are illustrated with few examples.

  4. Skeletal metastasis: treatments, mouse models, and the Wnt signaling

    PubMed Central

    Valkenburg, Kenneth C.; Steensma, Matthew R.; Williams, Bart O.; Zhong, Zhendong

    2013-01-01

    Skeletal metastases result in significant morbidity and mortality. This is particularly true of cancers with a strong predilection for the bone, such as breast, prostate, and lung cancers. There is currently no reliable cure for skeletal metastasis, and palliative therapy options are limited. The Wnt signaling pathway has been found to play an integral role in the process of skeletal metastasis and may be an important clinical target. Several experimental models of skeletal metastasis have been used to find new biomarkers and test new treatments. In this review, we discuss pathologic process of bone metastasis, the roles of the Wnt signaling, and the available experimental models and treatments. PMID:23327798

  5. A systems model of phosphorylation for inflammatory signaling events.

    PubMed

    Sadreev, Ildar I; Chen, Michael Z Q; Welsh, Gavin I; Umezawa, Yoshinori; Kotov, Nikolay V; Valeyev, Najl V

    2014-01-01

    Phosphorylation is a fundamental biochemical reaction that modulates protein activity in cells. While a single phosphorylation event is relatively easy to understand, multisite phosphorylation requires systems approaches for deeper elucidation of the underlying molecular mechanisms. In this paper we develop a mechanistic model for single- and multi-site phosphorylation. The proposed model is compared with previously reported studies. We compare the predictions of our model with experiments published in the literature in the context of inflammatory signaling events in order to provide a mechanistic description of the multisite phosphorylation-mediated regulation of Signal Transducer and Activator of Transcription 3 (STAT3) and Interferon Regulatory Factor 5 (IRF-5) proteins. The presented model makes crucial predictions for transcription factor phosphorylation events in the immune system. The model proposes potential mechanisms for T cell phenotype switching and production of cytokines. This study also provides a generic framework for the better understanding of a large number of multisite phosphorylation-regulated biochemical circuits.

  6. New Modeling Approaches to Investigate Cell Signaling in Radiation Response

    NASA Technical Reports Server (NTRS)

    Plante, Ianik; Cucinotta, Francis A.; Ponomarev, Artem L.

    2011-01-01

    Ionizing radiation damages individual cells and tissues leading to harmful biological effects. Among many radiation-induced lesions, DNA double-strand breaks (DSB) are considered the key precursors of most early and late effects [1] leading to direct mutation or aberrant signal transduction processes. In response to damage, a flow of information is communicated to cells not directly hit by the radiation through signal transduction pathways [2]. Non-targeted effects (NTE), which includes bystander effects and genomic instability in the progeny of irradiated cells and tissues, may be particularly important for space radiation risk assessment [1], because astronauts are exposed to a low fluence of heavy ions and only a small fraction of cells are traversed by an ion. NTE may also have important consequences clinical radiotherapy [3]. In the recent years, new simulation tools and modeling approaches have become available to study the tissue response to radiation. The simulation of signal transduction pathways require many elements such as detailed track structure calculations, a tissue or cell culture model, knowledge of biochemical pathways and Brownian Dynamics (BD) propagators of the signaling molecules in their micro-environment. Recently, the Monte-Carlo simulation code of radiation track structure RITRACKS was used for micro and nano-dosimetry calculations [4]. RITRACKS will be used to calculate the fraction of cells traversed by an ion and delta-rays and the energy deposited in cells in a tissue model. RITRACKS also simulates the formation of chemical species by the radiolysis of water [5], notably the .OH radical. This molecule is implicated in DNA damage and in the activation of the transforming growth factor beta (TGF), a signaling molecule involved in NTE. BD algorithms for a particle near a membrane comprising receptors were also developed and will be used to simulate trajectories of signaling molecules in the micro-environment and characterize autocrine

  7. Learning robust cell signalling models from high throughput proteomic data

    PubMed Central

    Koch, Mitchell; Broom, Bradley M.; Subramanian, Devika

    2015-01-01

    We propose a framework for learning robust Bayesian network models of cell signalling from high-throughput proteomic data. We show that model averaging using Bayesian bootstrap resampling generates more robust structures than procedures that learn structures using all of the data. We also develop an algorithm for ranking the importance of network features using bootstrap resample data. We apply our algorithms to derive the T-cell signalling network from the flow cytometry data of Sachs et al. (2005). Our learning algorithm has identified, with high confidence, several new crosstalk mechanisms in the T-cell signalling network. Many of them have already been confirmed experimentally in the recent literature and six new crosstalk mechanisms await experimental validation. PMID:19525198

  8. State-time spectrum of signal transduction logic models

    NASA Astrophysics Data System (ADS)

    MacNamara, Aidan; Terfve, Camille; Henriques, David; Peñalver Bernabé, Beatriz; Saez-Rodriguez, Julio

    2012-08-01

    Despite the current wealth of high-throughput data, our understanding of signal transduction is still incomplete. Mathematical modeling can be a tool to gain an insight into such processes. Detailed biochemical modeling provides deep understanding, but does not scale well above relatively a few proteins. In contrast, logic modeling can be used where the biochemical knowledge of the system is sparse and, because it is parameter free (or, at most, uses relatively a few parameters), it scales well to large networks that can be derived by manual curation or retrieved from public databases. Here, we present an overview of logic modeling formalisms in the context of training logic models to data, and specifically the different approaches to modeling qualitative to quantitative data (state) and dynamics (time) of signal transduction. We use a toy model of signal transduction to illustrate how different logic formalisms (Boolean, fuzzy logic and differential equations) treat state and time. Different formalisms allow for different features of the data to be captured, at the cost of extra requirements in terms of computational power and data quality and quantity. Through this demonstration, the assumptions behind each formalism are discussed, as well as their advantages and disadvantages and possible future developments.

  9. Analysis and logical modeling of biological signaling transduction networks

    NASA Astrophysics Data System (ADS)

    Sun, Zhongyao

    The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

  10. Signal Transduction Model of Magnetic Sensing in Cryptochrome Mediated Photoreception

    NASA Astrophysics Data System (ADS)

    Todd, Phillise Tiffeny

    While migratory birds have long been known to use the Earth's magnetic field for navigation, the precise biophysical mechanism behind this magnetic sense remains unconfirmed. A leading theory of magnetoreception suggests a chemical compass model with a yet undetermined molecular reaction site and unknown magnetically sensitive reactants. The cryptochrome photoreceptor has emerged as a promising candidate site. This investigation numerically models the first order kinetics of cryptochrome mediated photoreception, in order to evaluate its ability to function as a magnetic sensor and transduce orientation information along a neural pathway. A signal-to-noise ratio is defined to quantify the threshold for the functioning of a cryptochrome-based chemical compass. The model suggests that a flavin-superoxide radical pair in cryptochrome functions as the chemical reactants for magnetoreception. Such a cryptochrome-based signal transduction model reasonably predicts the general light intensity and wavelength effects that have been experimentally observed in migratory birds.

  11. Modeling signalized intersection safety with corridor-level spatial correlations.

    PubMed

    Guo, Feng; Wang, Xuesong; Abdel-Aty, Mohamed A

    2010-01-01

    Intersections in close spatial proximity along a corridor should be considered as correlated due to interacted traffic flows as well as similar road design and environmental characteristics. It is critical to incorporate this spatial correlation for assessing the true safety impacts of risk factors. In this paper, several Bayesian models were developed to model the crash data from 170 signalized intersections in the state of Florida. The safety impacts of risk factors such as geometric design features, traffic control, and traffic flow characteristics were evaluated. The Poisson and Negative Binomial Bayesian models with non-informative priors were fitted but the focus is to incorporate spatial correlations among intersections. Two alternative models were proposed to capture this correlation: (1) a mixed effect model in which the corridor-level correlation is incorporated through a corridor-specific random effect and (2) a conditional autoregressive model in which the magnitude of correlations is determined by spatial distances among intersections. The models were compared using the Deviance Information Criterion. The results indicate that the Poisson spatial model provides the best model fitting. Analysis of the posterior distributions of model parameters indicated that the size of intersection, the traffic conditions by turning movement, and the coordination of signal phase have significant impacts on intersection safety.

  12. Decoding Problem Gamblers' Signals: A Decision Model for Casino Enterprises.

    PubMed

    Ifrim, Sandra

    2015-12-01

    The aim of the present study is to offer a validated decision model for casino enterprises. The model enables those users to perform early detection of problem gamblers and fulfill their ethical duty of social cost minimization. To this end, the interpretation of casino customers' nonverbal communication is understood as a signal-processing problem. Indicators of problem gambling recommended by Delfabbro et al. (Identifying problem gamblers in gambling venues: final report, 2007) are combined with Viterbi algorithm into an interdisciplinary model that helps decoding signals emitted by casino customers. Model output consists of a historical path of mental states and cumulated social costs associated with a particular client. Groups of problem and non-problem gamblers were simulated to investigate the model's diagnostic capability and its cost minimization ability. Each group consisted of 26 subjects and was subsequently enlarged to 100 subjects. In approximately 95% of the cases, mental states were correctly decoded for problem gamblers. Statistical analysis using planned contrasts revealed that the model is relatively robust to the suppression of signals performed by casino clientele facing gambling problems as well as to misjudgments made by staff regarding the clients' mental states. Only if the last mentioned source of error occurs in a very pronounced manner, i.e. judgment is extremely faulty, cumulated social costs might be distorted. PMID:24938732

  13. Decoding Problem Gamblers' Signals: A Decision Model for Casino Enterprises.

    PubMed

    Ifrim, Sandra

    2015-12-01

    The aim of the present study is to offer a validated decision model for casino enterprises. The model enables those users to perform early detection of problem gamblers and fulfill their ethical duty of social cost minimization. To this end, the interpretation of casino customers' nonverbal communication is understood as a signal-processing problem. Indicators of problem gambling recommended by Delfabbro et al. (Identifying problem gamblers in gambling venues: final report, 2007) are combined with Viterbi algorithm into an interdisciplinary model that helps decoding signals emitted by casino customers. Model output consists of a historical path of mental states and cumulated social costs associated with a particular client. Groups of problem and non-problem gamblers were simulated to investigate the model's diagnostic capability and its cost minimization ability. Each group consisted of 26 subjects and was subsequently enlarged to 100 subjects. In approximately 95% of the cases, mental states were correctly decoded for problem gamblers. Statistical analysis using planned contrasts revealed that the model is relatively robust to the suppression of signals performed by casino clientele facing gambling problems as well as to misjudgments made by staff regarding the clients' mental states. Only if the last mentioned source of error occurs in a very pronounced manner, i.e. judgment is extremely faulty, cumulated social costs might be distorted.

  14. The Accuratre Signal Model and Imaging Processing in Geosynchronous SAR

    NASA Astrophysics Data System (ADS)

    Hu, Cheng

    With the development of synthetic aperture radar (SAR) application, the disadvantage of low earth orbit (LEO) SAR becomes more and more apparent. The increase of orbit altitude can shorten the revisit time and enlarge the coverage area in single look, and then satisfy the application requirement. The concept of geosynchronous earth orbit (GEO) SAR system is firstly presented and deeply discussed by K.Tomiyasi and other researchers. A GEO SAR, with its fine temporal resolution, would overcome the limitations of current imaging systems, allowing dense interpretation of transient phenomena as GPS time-series analysis with a spatial density several orders of magnitude finer. Until now, the related literatures about GEO SAR are mainly focused in the system parameter design and application requirement. As for the signal characteristic, resolution calculation and imaging algorithms, it is nearly blank in the related literatures of GEO SAR. In the LEO SAR, the signal model analysis adopts the `Stop-and-Go' assumption in general, and this assumption can satisfy the imaging requirement in present advanced SAR system, such as TerraSAR, Radarsat2 and so on. However because of long propagation distance and non-negligible earth rotation, the `Stop-and-Go' assumption does not exist and will cause large propagation distance error, and then affect the image formation. Furthermore the long propagation distance will result in the long synthetic aperture time such as hundreds of seconds, therefore the linear trajectory model in LEO SAR imaging will fail in GEO imaging, and the new imaging model needs to be proposed for the GEO SAR imaging processing. In this paper, considering the relative motion between satellite and earth during signal propagation time, the accurate analysis method for propagation slant range is firstly presented. Furthermore, the difference between accurate analysis method and `Stop-and-Go' assumption is analytically obtained. Meanwhile based on the derived

  15. Nonstationary harmonic modeling for ECG removal in surface EMG signals.

    PubMed

    Zivanovic, Miroslav; González-Izal, Miriam

    2012-06-01

    We present a compact approach for mitigating the presence of electrocardiograms (ECG) in surface electromyographic (EMG) signals by means of time-variant harmonic modeling of the cardiac artifact. Heart rate and QRS complex variability, which often account for amplitude and frequency time variations of the ECG, are simultaneously captured by a set of third-order constant-coefficient polynomials modulating a stationary harmonic basis in the analysis window. Such a characterization allows us to significantly suppress ECG from the mixture by preserving most of the EMG signal content at low frequencies (less than 20 Hz). Moreover, the resulting model is linear in parameters and the least-squares solution to the corresponding linear system of equations efficiently provides model parameter estimates. The comparative results suggest that the proposed method outperforms two reference methods in terms of the EMG preservation at low frequencies. PMID:22453600

  16. Modeling intracellular signaling underlying striatal function in health and disease.

    PubMed

    Nair, Anu G; Gutierrez-Arenas, Omar; Eriksson, Olivia; Jauhiainen, Alexandra; Blackwell, Kim T; Kotaleski, Jeanette H

    2014-01-01

    Striatum, which is the input nucleus of the basal ganglia, integrates cortical and thalamic glutamatergic inputs with dopaminergic afferents from the substantia nigra pars compacta. The combination of dopamine and glutamate strongly modulates molecular and cellular properties of striatal neurons and the strength of corticostriatal synapses. These actions are performed via intracellular signaling networks, containing several intertwined feedback loops. Understanding the role of dopamine and other neuromodulators requires the development of quantitative dynamical models for describing the intracellular signaling, in order to provide precise unambiguous descriptions and quantitative predictions. Building such models requires integration of data from multiple data sources containing information regarding the molecular interactions, the strength of these interactions, and the subcellular localization of the molecules. Due to the uncertainty, variability, and sparseness of these data, parameter estimation techniques are critical for inferring or constraining the unknown parameters, and sensitivity analysis evaluates which parameters are most critical for a given observed macroscopic behavior. Here, we briefly review the modeling approaches and tools that have been used to investigate biochemical signaling in the striatum, along with some of the models built around striatum. We also suggest a future direction for the development of such models from the, now becoming abundant, high-throughput data.

  17. Modeling intracellular signaling underlying striatal function in health and disease.

    PubMed

    Nair, Anu G; Gutierrez-Arenas, Omar; Eriksson, Olivia; Jauhiainen, Alexandra; Blackwell, Kim T; Kotaleski, Jeanette H

    2014-01-01

    Striatum, which is the input nucleus of the basal ganglia, integrates cortical and thalamic glutamatergic inputs with dopaminergic afferents from the substantia nigra pars compacta. The combination of dopamine and glutamate strongly modulates molecular and cellular properties of striatal neurons and the strength of corticostriatal synapses. These actions are performed via intracellular signaling networks, containing several intertwined feedback loops. Understanding the role of dopamine and other neuromodulators requires the development of quantitative dynamical models for describing the intracellular signaling, in order to provide precise unambiguous descriptions and quantitative predictions. Building such models requires integration of data from multiple data sources containing information regarding the molecular interactions, the strength of these interactions, and the subcellular localization of the molecules. Due to the uncertainty, variability, and sparseness of these data, parameter estimation techniques are critical for inferring or constraining the unknown parameters, and sensitivity analysis evaluates which parameters are most critical for a given observed macroscopic behavior. Here, we briefly review the modeling approaches and tools that have been used to investigate biochemical signaling in the striatum, along with some of the models built around striatum. We also suggest a future direction for the development of such models from the, now becoming abundant, high-throughput data. PMID:24560149

  18. Discrete echo signal modeling of ultrasound imaging systems

    NASA Astrophysics Data System (ADS)

    Chen, Ming; Zhang, Cishen

    2008-03-01

    In this paper, a discrete model representing the pulse-tissue interaction in the medical ultrasound scanning and imaging process is developed. The model is based on discretizing the acoustical wave equation and is in terms of convolution between the input ultrasound pulses and the tissue mass density variation. Such a model can provide a useful means for ultrasound echo signal processing and imaging. Most existing models used for ultrasound imaging are based on frequency domain transform. A disadvantage of the frequency domain transform is that it is only applicable to shift-invariant models. Thus it has ignored the shift-variant nature of the original acoustic wave equation where the tissue compressibility and mass density distributions are spatial-variant factors. The discretized frequency domain model also obscures the compressibility and mass density representations of the tissue, which may mislead the physical understanding and interpretation of the image obtained. Moreover, only the classical frequency domain filtering methods have been applied to the frequency domain model for acquiring some tissue information from the scattered echo signals. These methods are non-parametric and require a prior knowledge of frequency spectra of the transmitted pulses. Our proposed model technique will lead to discrete, multidimensional, shift-variant and parametric difference or convolution equations with the transmitted pulse pressure as the input, the measurement data of the echo signals as the output, and functions of the tissue compressibility and mass density distributions as shift-variant parameters that can be readily identified from input-output measurements. The proposed model represents the entire multiple scattering process, and hence overcomes the key limitation in the current ultrasound imaging methods.

  19. Linear System Models for Ultrasonic Imaging: Application to Signal Statistics

    PubMed Central

    Zemp, Roger J.; Abbey, Craig K.; Insana, Michael F.

    2009-01-01

    Linear equations for modeling echo signals from shift-variant systems forming ultrasonic B-mode, Doppler, and strain images are analyzed and extended. The approach is based on a solution to the homogeneous wave equation for random inhomogeneous media. When the system is shift-variant, the spatial sensitivity function—defined as a spatial weighting function that determines the scattering volume for a fixed point of time—has advantages over the point-spread function traditionally used to analyze ultrasound systems. Spatial sensitivity functions are necessary for determining statistical moments in the context of rigorous image quality assessment, and they are time-reversed copies of point-spread functions for shift variant systems. A criterion is proposed to assess the validity of a local shift-invariance assumption. The analysis reveals realistic situations in which in-phase signals are correlated to the corresponding quadrature signals, which has strong implications for assessing lesion detectability. Also revealed is an opportunity to enhance near- and far-field spatial resolution by matched filtering unfocused beams. The analysis connects several well-known approaches to modeling ultrasonic echo signals. PMID:12839176

  20. Internal wave signal processing: A model-based approach

    SciTech Connect

    Candy, J.V.; Chambers, D.H.

    1995-02-22

    A model-based approach is proposed to solve the oceanic internal wave signal processing problem that is based on state-space representations of the normal-mode vertical velocity and plane wave horizontal velocity propagation models. It is shown that these representations can be utilized to spatially propagate the modal (depth) vertical velocity functions given the basic parameters (wave numbers, Brunt-Vaisala frequency profile etc.) developed from the solution of the associated boundary value problem as well as the horizontal velocity components. These models are then generalized to the stochastic case where an approximate Gauss-Markov theory applies. The resulting Gauss-Markov representation, in principle, allows the inclusion of stochastic phenomena such as noise and modeling errors in a consistent manner. Based on this framework, investigations are made of model-based solutions to the signal enhancement problem for internal waves. In particular, a processor is designed that allows in situ recursive estimation of the required velocity functions. Finally, it is shown that the associated residual or so-called innovation sequence that ensues from the recursive nature of this formulation can be employed to monitor the model`s fit to the data.

  1. Fish and frogs: models for vertebrate cilia signaling

    PubMed Central

    Wessely, Oliver; Obara, Tomoko

    2013-01-01

    The presence of cilia in many vertebrate cell types and its function has been ignored for many years. Only in the past few years has its importance been rediscovered. In part, this was triggered by the realization that many gene products mutated in polycystic kidney diseases are localized to cilia and dysfunctional cilia result in kidney disease. Another breakthrough was the observation that the establishment of the left-right body axis is dependent on cilia function. Since then, many other developmental paradigms have been shown to rely on cilia-dependent signaling. In addition to mouse and Chlamydomonas, lower vertebrate model systems such as zebrafish, medaka and Xenopus have provided important new insights into cilia signaling and its role during embryonic development. This review will summarize those studies. We will also illustrate how these lower vertebrates are promising model systems for future studies defining the physiological function of cilia during organogenesis and disease pathophysiology. PMID:17981674

  2. Nonlinear signal processing using neural networks: Prediction and system modelling

    SciTech Connect

    Lapedes, A.; Farber, R.

    1987-06-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

  3. Stochastic Model of Traffic Jam and Traffic Signal Control

    NASA Astrophysics Data System (ADS)

    Shin, Ji-Sun; Cui, Cheng-You; Lee, Tae-Hong; Lee, Hee-Hyol

    Traffic signal control is an effective method to solve the traffic jam. and forecasting traffic density has been known as an important part of the Intelligent Transportation System (ITS). The several methods of the traffic signal control are known such as random walk method, Neuron Network method, Bayesian Network method, and so on. In this paper, we propose a new method of a traffic signal control using a predicted distribution of traffic jam based on a Dynamic Bayesian Network model. First, a forecasting model to predict a probabilistic distribution of the traffic jam during each period of traffic lights is built. As the forecasting model, the Dynamic Bayesian Network is used to predict the probabilistic distribution of a density of the traffic jam. According to measurement of two crossing points for each cycle, the inflow and outflow of each direction and the number of standing vehicles at former cycle are obtained. The number of standing vehicle at k-th cycle will be calculated synchronously. Next, the probabilistic distribution of the density of standing vehicle in each cycle will be predicted using the Dynamic Bayesian Network constructed for the traffic jam. And then a control rule to adjust the split and the cycle to increase the probability between a lower limit and ceiling of the standing vehicles is deduced. As the results of the simulation using the actual traffic data of Kitakyushu city, the effectiveness of the method is shown.

  4. Volume conductor model of transcutaneous electrical stimulation with kilohertz signals

    PubMed Central

    Medina, Leonel E.; Grill, Warren M.

    2014-01-01

    Objective Incorporating high-frequency components in transcutaneous electrical stimulation (TES) waveforms may make it possible to stimulate deeper nerve fibers since the impedance of tissue declines with increasing frequency. However, the mechanisms of high-frequency TES remain largely unexplored. We investigated the properties of TES with frequencies beyond those typically used in neural stimulation. Approach We implemented a multilayer volume conductor model including dispersion and capacitive effects, coupled to a cable model of a nerve fiber. We simulated voltage- and current-controlled transcutaneous stimulation, and quantified the effects of frequency on the distribution of potentials and fiber excitation. We also quantified the effects of a novel transdermal amplitude modulated signal (TAMS) consisting of a non-zero offset sinusoidal carrier modulated by a square-pulse train. Main results The model revealed that high-frequency signals generated larger potentials at depth than did low frequencies, but this did not translate into lower stimulation thresholds. Both TAMS and conventional rectangular pulses activated more superficial fibers in addition to the deeper, target fibers, and at no frequency did we observe an inversion of the strength-distance relationship. Current regulated stimulation was more strongly influenced by fiber depth, whereas voltage regulated stimulation was more strongly influenced by skin thickness. Finally, our model reproduced the threshold-frequency relationship of experimentally measured motor thresholds. Significance The model may be used for prediction of motor thresholds in TES, and contributes to the understanding of high-frequency TES. PMID:25380254

  5. Modeling signal loss in surficial marine sediments containing occluded gas.

    PubMed

    Gardner, Trevor

    2003-03-01

    The presence of occluded gas in inland lakes, harbor muds, and surficial marine sediments is well documented. Surficial gassy sediments cause underlying beds to be acoustically impenetrable to seismic surveys; therefore, the modeling of signal loss arising from mudline reflection and transmission absorption is of particular interest. The Anderson and Hampton [J. Acoust. Soc. Am. 67, 1890-1903 (1980)] model for attenuation in gassy sediments was evaluated against the physical and acoustical properties of eight laboratory silty clay soils containing different amounts of occluded gas in bubbles of 0.2- to 1.8-mm diameter. The model was shown to give good agreement with measured data over the lower frequencies of bubble resonance and above resonance. It did not agree with measured data at frequencies below resonance, for which the model did not simulate the bulk properties of the gassy soils. The Mackenzie [J. Acoust. Soc. Am. 32, 221-231 (1960)] model for reflection loss was also examined for the gassy soils. The maximum reflection losses of 6 dB, at a grazing angle of 40 degrees, does not wholly support speculation by Levin [Geophysics 27, 35-47 (1962)] of highly reflective pressure-release boundaries arising from substantial reflection and absorption losses in gassy sediments. It was found that mudlines formed from sediments with significant occluded gas may be successfully penetrated, although the substantial absorption loss arising from signal transmission through the sediment prevents penetration of the surficial layers to much beyond a meter in depth.

  6. Modeling Guidelines for Code Generation in the Railway Signaling Context

    NASA Technical Reports Server (NTRS)

    Ferrari, Alessio; Bacherini, Stefano; Fantechi, Alessandro; Zingoni, Niccolo

    2009-01-01

    Modeling guidelines constitute one of the fundamental cornerstones for Model Based Development. Their relevance is essential when dealing with code generation in the safety-critical domain. This article presents the experience of a railway signaling systems manufacturer on this issue. Introduction of Model-Based Development (MBD) and code generation in the industrial safety-critical sector created a crucial paradigm shift in the development process of dependable systems. While traditional software development focuses on the code, with MBD practices the focus shifts to model abstractions. The change has fundamental implications for safety-critical systems, which still need to guarantee a high degree of confidence also at code level. Usage of the Simulink/Stateflow platform for modeling, which is a de facto standard in control software development, does not ensure by itself production of high-quality dependable code. This issue has been addressed by companies through the definition of modeling rules imposing restrictions on the usage of design tools components, in order to enable production of qualified code. The MAAB Control Algorithm Modeling Guidelines (MathWorks Automotive Advisory Board)[3] is a well established set of publicly available rules for modeling with Simulink/Stateflow. This set of recommendations has been developed by a group of OEMs and suppliers of the automotive sector with the objective of enforcing and easing the usage of the MathWorks tools within the automotive industry. The guidelines have been published in 2001 and afterwords revisited in 2007 in order to integrate some additional rules developed by the Japanese division of MAAB [5]. The scope of the current edition of the guidelines ranges from model maintainability and readability to code generation issues. The rules are conceived as a reference baseline and therefore they need to be tailored to comply with the characteristics of each industrial context. Customization of these

  7. Modeling of Acoustic Emission Signal Propagation in Waveguides

    PubMed Central

    Zelenyak, Andreea-Manuela; Hamstad, Marvin A.; Sause, Markus G. R.

    2015-01-01

    Acoustic emission (AE) testing is a widely used nondestructive testing (NDT) method to investigate material failure. When environmental conditions are harmful for the operation of the sensors, waveguides are typically mounted in between the inspected structure and the sensor. Such waveguides can be built from different materials or have different designs in accordance with the experimental needs. All these variations can cause changes in the acoustic emission signals in terms of modal conversion, additional attenuation or shift in frequency content. A finite element method (FEM) was used to model acoustic emission signal propagation in an aluminum plate with an attached waveguide and was validated against experimental data. The geometry of the waveguide is systematically changed by varying the radius and height to investigate the influence on the detected signals. Different waveguide materials were implemented and change of material properties as function of temperature were taken into account. Development of the option of modeling different waveguide options replaces the time consuming and expensive trial and error alternative of experiments. Thus, the aim of this research has important implications for those who use waveguides for AE testing. PMID:26007731

  8. Similarity-Based Modeling Applied to Signal Detection in Pharmacovigilance

    PubMed Central

    Vilar, S; Ryan, P B; Madigan, D; Stang, P E; Schuemie, M J; Friedman, C; Tatonetti, N P; Hripcsak, G

    2014-01-01

    One of the main objectives in pharmacovigilance is the detection of adverse drug events (ADEs) through mining of healthcare databases, such as electronic health records or administrative claims data. Although different approaches have been shown to be of great value, research is still focusing on the enhancement of signal detection to gain efficiency in further assessment and follow-up. We applied similarity-based modeling techniques, using 2D and 3D molecular structure, ADE, target, and ATC (anatomical therapeutic chemical) similarity measures, to the candidate associations selected previously in a medication-wide association study for four ADE outcomes. Our results showed an improvement in the precision when we ranked the subset of ADE candidates using similarity scorings. This method is simple, useful to strengthen or prioritize signals generated from healthcare databases, and facilitates ADE detection through the identification of the most similar drugs for which ADE information is available. PMID:25250527

  9. Signal analysis of accelerometry data using gravity-based modeling

    NASA Astrophysics Data System (ADS)

    Davey, Neil P.; James, Daniel A.; Anderson, Megan E.

    2004-03-01

    Triaxial accelerometers have been used to measure human movement parameters in swimming. Interpretation of data is difficult due to interference sources including interaction of external bodies. In this investigation the authors developed a model to simulate the physical movement of the lower back. Theoretical accelerometery outputs were derived thus giving an ideal, or noiseless dataset. An experimental data collection apparatus was developed by adapting a system to the aquatic environment for investigation of swimming. Model data was compared against recorded data and showed strong correlation. Comparison of recorded and modeled data can be used to identify changes in body movement, this is especially useful when cyclic patterns are present in the activity. Strong correlations between data sets allowed development of signal processing algorithms for swimming stroke analysis using first the pure noiseless data set which were then applied to performance data. Video analysis was also used to validate study results and has shown potential to provide acceptable results.

  10. Thermally driven advection for radioxenon transport from an underground nuclear explosion

    NASA Astrophysics Data System (ADS)

    Sun, Yunwei; Carrigan, Charles R.

    2016-05-01

    Barometric pumping is a ubiquitous process resulting in migration of gases in the subsurface that has been studied as the primary mechanism for noble gas transport from an underground nuclear explosion (UNE). However, at early times following a UNE, advection driven by explosion residual heat is relevant to noble gas transport. A rigorous measure is needed for demonstrating how, when, and where advection is important. In this paper three physical processes of uncertain magnitude (oscillatory advection, matrix diffusion, and thermally driven advection) are parameterized by using boundary conditions, system properties, and source term strength. Sobol' sensitivity analysis is conducted to evaluate the importance of all physical processes influencing the xenon signals. This study indicates that thermally driven advection plays a more important role in producing xenon signals than oscillatory advection and matrix diffusion at early times following a UNE, and xenon isotopic ratios are observed to have both time and spatial dependence.

  11. Stochastic model for detection of signals in noise

    PubMed Central

    Klein, Stanley A.; Levi, Dennis M.

    2010-01-01

    Fifty years ago Birdsall, Tanner, and colleagues made rapid progress in developing signal detection theory into a powerful psychophysical tool. One of their major insights was the utility of adding external noise to the signals of interest. These methods have been enhanced in recent years by the addition of multipass and classification-image methods for opening up the black box. There remain a number of as yet unresolved issues. In particular, Birdsall developed a theorem that large amounts of external input noise can linearize nonlinear systems, and Tanner conjectured, with mathematical backup, that what had been previously thought of as a nonlinear system could actually be a linear system with uncertainty. Recent findings, both experimental and theoretical, have validated Birdsall’s theorem and Tanner’s conjecture. However, there have also been experimental and theoretical findings with the opposite outcome. In this paper we present new data and simulations in an attempt to sort out these issues. Our simulations and experiments plus data from others show that Birdsall’s theorem is quite robust. We argue that uncertainty can serve as an explanation for violations of Birdsall’s linearization by noise and also for reports of stochastic resonance. In addition, we modify present models to better handle detection of signals with both noise and pedestal backgrounds. PMID:19884912

  12. Small-signal, continuous, exact model of PWM voltage regulators

    NASA Astrophysics Data System (ADS)

    Burkhardt, W.; Maranesi, P.; Varoli, V.

    1985-02-01

    The small-signal time-continuous open-loop response of buck, boost, and buck-boost pulse-width-modulation (PWM) voltage regulators using MOSFET switches in their power stages is modeled, applying a time-domain sampling theorem (Woodward, 1953) to obtain the Fourier open-loop transfer function corresponding to the comb function describing the response at the chopping instants only. The results are presented graphically along with simplified circuit diagrams of the PWM devices, and the accuracy and computational efficiency of the analytical approach are indicated.

  13. Acquiring neural signals for developing a perception and cognition model

    NASA Astrophysics Data System (ADS)

    Li, Wei; Li, Yunyi; Chen, Genshe; Shen, Dan; Blasch, Erik; Pham, Khanh; Lynch, Robert

    2012-06-01

    The understanding of how humans process information, determine salience, and combine seemingly unrelated information is essential to automated processing of large amounts of information that is partially relevant, or of unknown relevance. Recent neurological science research in human perception, and in information science regarding contextbased modeling, provides us with a theoretical basis for using a bottom-up approach for automating the management of large amounts of information in ways directly useful for human operators. However, integration of human intelligence into a game theoretic framework for dynamic and adaptive decision support needs a perception and cognition model. For the purpose of cognitive modeling, we present a brain-computer-interface (BCI) based humanoid robot system to acquire brainwaves during human mental activities of imagining a humanoid robot-walking behavior. We use the neural signals to investigate relationships between complex humanoid robot behaviors and human mental activities for developing the perception and cognition model. The BCI system consists of a data acquisition unit with an electroencephalograph (EEG), a humanoid robot, and a charge couple CCD camera. An EEG electrode cup acquires brainwaves from the skin surface on scalp. The humanoid robot has 20 degrees of freedom (DOFs); 12 DOFs located on hips, knees, and ankles for humanoid robot walking, 6 DOFs on shoulders and arms for arms motion, and 2 DOFs for head yaw and pitch motion. The CCD camera takes video clips of the human subject's hand postures to identify mental activities that are correlated to the robot-walking behaviors. We use the neural signals to investigate relationships between complex humanoid robot behaviors and human mental activities for developing the perception and cognition model.

  14. A model integration approach linking signalling and gene-regulatory logic with kinetic metabolic models.

    PubMed

    Ryll, A; Bucher, J; Bonin, A; Bongard, S; Gonçalves, E; Saez-Rodriguez, J; Niklas, J; Klamt, S

    2014-10-01

    Systems biology has to increasingly cope with large- and multi-scale biological systems. Many successful in silico representations and simulations of various cellular modules proved mathematical modelling to be an important tool in gaining a solid understanding of biological phenomena. However, models spanning different functional layers (e.g. metabolism, signalling and gene regulation) are still scarce. Consequently, model integration methods capable of fusing different types of biological networks and various model formalisms become a key methodology to increase the scope of cellular processes covered by mathematical models. Here we propose a new integration approach to couple logical models of signalling or/and gene-regulatory networks with kinetic models of metabolic processes. The procedure ends up with an integrated dynamic model of both layers relying on differential equations. The feasibility of the approach is shown in an illustrative case study integrating a kinetic model of central metabolic pathways in hepatocytes with a Boolean logical network depicting the hormonally induced signal transduction and gene regulation events involved. In silico simulations demonstrate the integrated model to qualitatively describe the physiological switch-like behaviour of hepatocytes in response to nutritionally regulated changes in extracellular glucagon and insulin levels. A simulated failure mode scenario addressing insulin resistance furthermore illustrates the pharmacological potential of a model covering interactions between signalling, gene regulation and metabolism. PMID:25063553

  15. Hierarchic stochastic modelling applied to intracellular Ca(2+) signals.

    PubMed

    Moenke, Gregor; Falcke, Martin; Thurley, Keven

    2012-01-01

    Important biological processes like cell signalling and gene expression have noisy components and are very complex at the same time. Mathematical analysis of such systems has often been limited to the study of isolated subsystems, or approximations are used that are difficult to justify. Here we extend a recently published method (Thurley and Falcke, PNAS 2011) which is formulated in observable system configurations instead of molecular transitions. This reduces the number of system states by several orders of magnitude and avoids fitting of kinetic parameters. The method is applied to Ca(2+) signalling. Ca(2+) is a ubiquitous second messenger transmitting information by stochastic sequences of concentration spikes, which arise by coupling of subcellular Ca(2+) release events (puffs). We derive analytical expressions for a mechanistic Ca(2+) model, based on recent data from live cell imaging, and calculate Ca(2+) spike statistics in dependence on cellular parameters like stimulus strength or number of Ca(2+) channels. The new approach substantiates a generic Ca(2+) model, which is a very convenient way to simulate Ca(2+) spike sequences with correct spiking statistics.

  16. Increased GABAB receptor signaling in a rat model for schizophrenia

    PubMed Central

    Selten, Martijn M.; Meyer, Francisca; Ba, Wei; Vallès, Astrid; Maas, Dorien A.; Negwer, Moritz; Eijsink, Vivian D.; van Vugt, Ruben W. M.; van Hulten, Josephus A.; van Bakel, Nick H. M.; Roosen, Joey; van der Linden, Robert J.; Schubert, Dirk; Verheij, Michel M. M.; Kasri, Nael Nadif; Martens, Gerard J. M.

    2016-01-01

    Schizophrenia is a complex disorder that affects cognitive function and has been linked, both in patients and animal models, to dysfunction of the GABAergic system. However, the pathophysiological consequences of this dysfunction are not well understood. Here, we examined the GABAergic system in an animal model displaying schizophrenia-relevant features, the apomorphine-susceptible (APO-SUS) rat and its phenotypic counterpart, the apomorphine-unsusceptible (APO-UNSUS) rat at postnatal day 20–22. We found changes in the expression of the GABA-synthesizing enzyme GAD67 specifically in the prelimbic- but not the infralimbic region of the medial prefrontal cortex (mPFC), indicative of reduced inhibitory function in this region in APO-SUS rats. While we did not observe changes in basal synaptic transmission onto LII/III pyramidal cells in the mPFC of APO-SUS compared to APO-UNSUS rats, we report reduced paired-pulse ratios at longer inter-stimulus intervals. The GABAB receptor antagonist CGP 55845 abolished this reduction, indicating that the decreased paired-pulse ratio was caused by increased GABAB signaling. Consistently, we find an increased expression of the GABAB1 receptor subunit in APO-SUS rats. Our data provide physiological evidence for increased presynaptic GABAB signaling in the mPFC of APO-SUS rats, further supporting an important role for the GABAergic system in the pathophysiology of schizophrenia. PMID:27687783

  17. Vibration signal models for fault diagnosis of planet bearings

    NASA Astrophysics Data System (ADS)

    Feng, Zhipeng; Ma, Haoqun; Zuo, Ming J.

    2016-05-01

    Rolling element bearings are key components of planetary gearboxes. Among them, the motion of planet bearings is very complex, encompassing spinning and revolution. Therefore, planet bearing vibrations are highly intricate and their fault characteristics are completely different from those of fixed-axis case, making planet bearing fault diagnosis a difficult topic. In order to address this issue, we derive the explicit equations for calculating the characteristic frequency of outer race, rolling element and inner race fault, considering the complex motion of planet bearings. We also develop the planet bearing vibration signal model for each fault case, considering the modulation effects of load zone passing, time-varying angle between the gear pair mesh and fault induced impact force, as well as the time-varying vibration transfer path. Based on the developed signal models, we derive the explicit equations of Fourier spectrum in each fault case, and summarize the vibration spectral characteristics respectively. The theoretical derivations are illustrated by numerical simulation, and further validated experimentally and all the three fault cases (i.e. outer race, rolling element and inner race localized fault) are diagnosed.

  18. Modeling the global positioning system signal propagation through the ionosphere

    NASA Technical Reports Server (NTRS)

    Bassiri, S.; Hajj, G. A.

    1992-01-01

    Based on realistic modeling of the electron density of the ionosphere and using a dipole moment approximation for the Earth's magnetic field, one is able to estimate the effect of the ionosphere on the Global Positioning System (GPS) signal for a ground user. The lowest order effect, which is on the order of 0.1-100 m of group delay, is subtracted out by forming a linear combination of the dual frequencies of the GPS signal. One is left with second- and third-order effects that are estimated typically to be approximately 0-2 cm and approximately 0-2 mm at zenith, respectively, depending on the geographical location, the time of day, the time of year, the solar cycle, and the relative geometry of the magnetic field and the line of sight. Given the total electron content along a line of sight, the authors derive an approximation to the second-order term which is accurate to approximately 90 percent within the magnetic dipole moment model; this approximation can be used to reduce the second-order term to the millimeter level, thus potentially improving precise positioning in space and on the ground. The induced group delay, or phase advance, due to second- and third-order effects is examined for two ground receivers located at equatorial and mid-latitude regions tracking several GPS satellites.

  19. Design and use of multisine signals for Li-ion battery equivalent circuit modelling. Part 1: Signal design

    NASA Astrophysics Data System (ADS)

    Widanage, W. D.; Barai, A.; Chouchelamane, G. H.; Uddin, K.; McGordon, A.; Marco, J.; Jennings, P.

    2016-08-01

    The Pulse Power Current (PPC) profile is often the signal of choice for obtaining the parameters of a Lithium-ion (Li-ion) battery Equivalent Circuit Model (ECM). Subsequently, a drive-cycle current profile is used as a validation signal. Such a profile, in contrast to a PPC, is more dynamic in both the amplitude and frequency bandwidth. Modelling errors can occur when using PPC data for parametrisation since the model is optimised over a narrower bandwidth than the validation profile. A signal more representative of a drive-cycle, while maintaining a degree of generality, is needed to reduce such modelling errors. In Part 1 of this 2-part paper a signal design technique defined as a pulse-multisine is presented. This superimposes a signal known as a multisine to a discharge, rest and charge base signal to achieve a profile more dynamic in amplitude and frequency bandwidth, and thus more similar to a drive-cycle. The signal improves modelling accuracy and reduces the experimentation time, per state-of-charge (SoC) and temperature, to several minutes compared to several hours for an PPC experiment.

  20. Cell-type-specific modelling of intracellular calcium signalling: a urothelial cell model.

    PubMed

    Appleby, Peter A; Shabir, Saqib; Southgate, Jennifer; Walker, Dawn

    2013-09-01

    Calcium signalling plays a central role in regulating a wide variety of cell processes. A number of calcium signalling models exist in the literature that are capable of reproducing a variety of experimentally observed calcium transients. These models have been used to examine in more detail the mechanisms underlying calcium transients, but very rarely has a model been directly linked to a particular cell type and experimentally verified. It is important to show that this can be achieved within the general theoretical framework adopted by these models. Here, we develop a framework designed specifically for modelling cytosolic calcium transients in urothelial cells. Where possible, we draw upon existing calcium signalling models, integrating descriptions of components known to be important in this cell type from a number of studies in the literature. We then add descriptions of several additional pathways that play a specific role in urothelial cell signalling, including an explicit ionic influx term and an active pumping mechanism that drives the cytosolic calcium concentration to a target equilibrium. The resulting one-pool model of endoplasmic reticulum (ER)-dependent calcium signalling relates the cytosolic, extracellular and ER calcium concentrations and can generate a wide range of calcium transients, including spikes, bursts, oscillations and sustained elevations in the cytosolic calcium concentration. Using single-variate robustness and multivariate sensitivity analyses, we quantify how varying each of the parameters of the model leads to changes in key features of the calcium transient, such as initial peak amplitude and the frequency of bursting or spiking, and in the transitions between bursting- and plateau-dominated modes. We also show that, novel to our urothelial cell model, the ionic and purinergic P2Y pathways make distinct contributions to the calcium transient. We then validate the model using human bladder epithelial cells grown in monolayer cell

  1. Chemotaxis signaling systems in model beneficial plant-bacteria associations.

    PubMed

    Scharf, Birgit E; Hynes, Michael F; Alexandre, Gladys M

    2016-04-01

    Beneficial plant-microbe associations play critical roles in plant health. Bacterial chemotaxis provides a competitive advantage to motile flagellated bacteria in colonization of plant root surfaces, which is a prerequisite for the establishment of beneficial associations. Chemotaxis signaling enables motile soil bacteria to sense and respond to gradients of chemical compounds released by plant roots. This process allows bacteria to actively swim towards plant roots and is thus critical for competitive root surface colonization. The complete genome sequences of several plant-associated bacterial species indicate the presence of multiple chemotaxis systems and a large number of chemoreceptors. Further, most soil bacteria are motile and capable of chemotaxis, and chemotaxis-encoding genes are enriched in the bacteria found in the rhizosphere compared to the bulk soil. This review compares the architecture and diversity of chemotaxis signaling systems in model beneficial plant-associated bacteria and discusses their relevance to the rhizosphere lifestyle. While it is unclear how controlling chemotaxis via multiple parallel chemotaxis systems provides a competitive advantage to certain bacterial species, the presence of a larger number of chemoreceptors is likely to contribute to the ability of motile bacteria to survive in the soil and to compete for root surface colonization.

  2. Linear effects models of signaling pathways from combinatorial perturbation data

    PubMed Central

    Szczurek, Ewa; Beerenwinkel, Niko

    2016-01-01

    Motivation: Perturbations constitute the central means to study signaling pathways. Interrupting components of the pathway and analyzing observed effects of those interruptions can give insight into unknown connections within the signaling pathway itself, as well as the link from the pathway to the effects. Different pathway components may have different individual contributions to the measured perturbation effects, such as gene expression changes. Those effects will be observed in combination when the pathway components are perturbed. Extant approaches focus either on the reconstruction of pathway structure or on resolving how the pathway components control the downstream effects. Results: Here, we propose a linear effects model, which can be applied to solve both these problems from combinatorial perturbation data. We use simulated data to demonstrate the accuracy of learning the pathway structure as well as estimation of the individual contributions of pathway components to the perturbation effects. The practical utility of our approach is illustrated by an application to perturbations of the mitogen-activated protein kinase pathway in Saccharomyces cerevisiae. Availability and Implementation: lem is available as a R package at http://www.mimuw.edu.pl/∼szczurek/lem. Contact: szczurek@mimuw.edu.pl; niko.beerenwinkel@bsse.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307630

  3. The development of attenuation compensation models of fluorescence spectroscopy signals

    NASA Astrophysics Data System (ADS)

    Dremin, Victor V.; Zherebtsov, Evgeny A.; Rafailov, Ilya E.; Vinokurov, Andrey Y.; Novikova, Irina N.; Zherebtsova, Angelina I.; Litvinova, Karina S.; Dunaev, Andrey V.

    2016-04-01

    This study examines the effect of blood absorption on the endogenous fluorescence signal intensity of biological tissues. Experimental studies were conducted to identify these effects. To register the fluorescence intensity, the fluorescence spectroscopy method was employed. The intensity of the blood flow was measured by laser Doppler flowmetry. We proposed one possible implementation of the Monte Carlo method for the theoretical analysis of the effect of blood on the fluorescence signals. The simulation is constructed as a four-layer skin optical model based on the known optical parameters of the skin with different levels of blood supply. With the help of the simulation, we demonstrate how the level of blood supply can affect the appearance of the fluorescence spectra. In addition, to describe the properties of biological tissue, which may affect the fluorescence spectra, we turned to the method of diffuse reflectance spectroscopy (DRS). Using the spectral data provided by the DRS, the tissue attenuation effect can be extracted and used to correct the fluorescence spectra.

  4. Underwater Signal Modeling for Subsurface Classification Using Computational Intelligence.

    NASA Astrophysics Data System (ADS)

    Setayeshi, Saeed

    In the thesis a method for underwater layered media (UWLM) modeling is proposed, and a simple nonlinear structure for implementation of this model based on the behaviour of its characteristics and the propagation of the acoustic signal in the media accounting for attenuation effects is designed. The model that responds to the acoustic input is employed to test the artificial intelligence classifiers ability. Neural network models, the basic principles of the back-propagation algorithm, and the Hopfield model of associative memories are reviewed, and they are employed to use min-max amplitude ranges of a reflected signal of UWLM based on attenuation effects, to define the classes of the synthetic data, detect its peak features and estimate parameters of the media. It has been found that there is a correlation between the number of layers in the media and the optimum number of nodes in the hidden layer of the neural networks. The integration of the result of the neural networks that classify and detect underwater layered media acoustic signals based on attenuation effects to prove the correspondence between the peak points and decay values has introduced a powerful tool for UWLM identification. The methods appear to have applications in replacing original system, for parameter estimation and output prediction in system identification by the proposed networks. The results of computerized simulation of the UWLM modeling in conjunction with the proposed neural networks training process are given. Fuzzy sets is an idea that allows representing and manipulating inexact concepts, fuzzy min-max pattern classification method, and the learning and recalling algorithms for fuzzy neural networks implementation is explained in this thesis. A fuzzy neural network that uses peak amplitude ranges to define classes is proposed and evaluated for UWLM pattern recognition. It is demonstrated to be able to classify the layered media data sets, and can distinguish between the peak points

  5. Signal processing of MEMS gyroscope arrays to improve accuracy using a 1st order Markov for rate signal modeling.

    PubMed

    Jiang, Chengyu; Xue, Liang; Chang, Honglong; Yuan, Guangmin; Yuan, Weizheng

    2012-01-01

    This paper presents a signal processing technique to improve angular rate accuracy of the gyroscope by combining the outputs of an array of MEMS gyroscope. A mathematical model for the accuracy improvement was described and a Kalman filter (KF) was designed to obtain optimal rate estimates. Especially, the rate signal was modeled by a first-order Markov process instead of a random walk to improve overall performance. The accuracy of the combined rate signal and affecting factors were analyzed using a steady-state covariance. A system comprising a six-gyroscope array was developed to test the presented KF. Experimental tests proved that the presented model was effective at improving the gyroscope accuracy. The experimental results indicated that six identical gyroscopes with an ARW noise of 6.2 °/√h and a bias drift of 54.14 °/h could be combined into a rate signal with an ARW noise of 1.8 °/√h and a bias drift of 16.3 °/h, while the estimated rate signal by the random walk model has an ARW noise of 2.4 °/√h and a bias drift of 20.6 °/h. It revealed that both models could improve the angular rate accuracy and have a similar performance in static condition. In dynamic condition, the test results showed that the first-order Markov process model could reduce the dynamic errors 20% more than the random walk model.

  6. Modeling and processing of laser Doppler reactive hyperaemia signals

    NASA Astrophysics Data System (ADS)

    Humeau, Anne; Saumet, Jean-Louis; L'Huiller, Jean-Pierre

    2003-07-01

    Laser Doppler flowmetry is a non-invasive method used in the medical domain to monitor the microvascular blood cell perfusion through tissue. Most commercial laser Doppler flowmeters use an algorithm calculating the first moment of the power spectral density to give the perfusion value. Many clinical applications measure the perfusion after a vascular provocation such as a vascular occlusion. The response obtained is then called reactive hyperaemia. Target pathologies include diabetes, hypertension and peripheral arterial occlusive diseases. In order to have a deeper knowledge on reactive hyperaemia acquired by the laser Doppler technique, the present work first proposes two models (one analytical and one numerical) of the observed phenomenon. Then, a study on the multiple scattering between photons and red blood cells occurring during reactive hyperaemia is carried out. Finally, a signal processing that improves the diagnosis of peripheral arterial occlusive diseases is presented.

  7. Simulation of signal transduction in model multiprotein systems

    NASA Astrophysics Data System (ADS)

    Su, Julius

    2009-03-01

    To simulate the dynamics of multiprotein machines, I have developed a method called multiconformer Brownian dynamics (mcBD). In this method, proteins rotate and translate via Brownian motion while their conformations are varied among a prestored set of structures on a simplified energy landscape, taking into account inter-protein interactions. As an example, I build a simple model of a G-protein coupled receptor/G-protein complex, and show that ligand binding causes conformational shifts, which induce GDP to leave, GTP to bind, and the complex to dissociate. The two proteins couple their fast fluctuations together into large-scale coordinated functional motions, resulting in signal transduction. I vary the shapes, electrostatics, and energy landscapes of the proteins independently and examine the impact this has on the system's function. In one result, increasing the binding between proteins improves the fidelity of communication, but at the expense of overall switching frequency.

  8. Principles of model building: an experimentation-aided approach to development of models for signaling networks.

    PubMed

    Ganesan, Ambhighainath; Levchenko, Andre

    2012-01-01

    Living cells continuously probe their environment and respond to a multitude of external cues. The information about the environment is carried by signaling cascades that act as "internal transducing and computing modules," coupled into complex and interconnected networks. A comprehensive understanding of how cells make decisions therefore necessitates a sound theoretical framework, which can be achieved through mathematical modeling of the signaling networks. In this chapter, we conceptually describe the typical workflow involved in building mathematical models that are motivated by and are developed in a tight integration with experimental analysis. In particular, we delineate the steps involved in a generic, iterative experimentation-driven model-building process, both through informal discussion and using a recently published study as an example. Experiments guide the initial development of mathematical models, including choice of appropriate template model and parameter revision. The model can then be used to generate and test hypotheses quickly and inexpensively, aiding in judicious design of future experiments. These experiments, in turn, are used to update the model. The model developed at the end of this exercise not only predicts functional behavior of the system under study but also provides insight into the biophysical underpinnings of signaling networks.

  9. SEMICONDUCTOR DEVICES MEXTRAM model based SiGe HBT large-signal modeling

    NASA Astrophysics Data System (ADS)

    Bo, Han; Shoulin, Li; Jiali, Cheng; Qiuyan, Yin; Jianjun, Gao

    2010-10-01

    An improved large-signal equivalent-circuit model for SiGe HBTs based on the MEXTRAM model (level 504.5) is proposed. The proposed model takes into account the soft knee effect. The model keeps the main features of the MEXTRAM model even though some simplifications have been made in the equivalent circuit topology. This model is validated in DC and AC analyses for SiGe HBTs fabricated with 0.35-μm BiCMOS technology, 1 × 8 μm2 emitter area. Good agreement is achieved between the measured and modeled results for DC and S-parameters (from 50 MHz to 20 GHz), which shows that the proposed model is accurate and reliable. The model has been implemented in Verilog-A using the ADS circuit simulator.

  10. Fetal QRS extraction from abdominal recordings via model-based signal processing and intelligent signal merging.

    PubMed

    Haghpanahi, Masoumeh; Borkholder, David A

    2014-08-01

    Noninvasive fetal ECG (fECG) monitoring has potential applications in diagnosing congenital heart diseases in a timely manner and assisting clinicians to make more appropriate decisions during labor. However, despite advances in signal processing and machine learning techniques, the analysis of fECG signals has still remained in its preliminary stages. In this work, we describe an algorithm to automatically locate QRS complexes in noninvasive fECG signals obtained from a set of four electrodes placed on the mother's abdomen. The algorithm is based on an iterative decomposition of the maternal and fetal subspaces and filtering of the maternal ECG (mECG) components from the fECG recordings. Once the maternal components are removed, a novel merging technique is applied to merge the signals and detect the fetal QRS (fQRS) complexes. The algorithm was trained and tested on the fECG datasets provided by the PhysioNet/CinC challenge 2013. The final results indicate that the algorithm is able to detect fetal peaks for a variety of signals with different morphologies and strength levels encountered in clinical practice.

  11. Modeling the integration of motion signals across space

    NASA Astrophysics Data System (ADS)

    Loffler, Gunter; Orbach, Harry S.

    2003-08-01

    Experiments by Loffler and Orbach on the integration of motion signals across space [J. Opt. Soc. Am. A 20, 1461 (2003)] revealed that both three-dimensional analysis and object interpretation play a much smaller role than previously assumed. These results motivated the quantitative description of a low-level, bottom-up model presented here. Motion is computed in parallel at different spatial sites, and excitatory interactions operate between sites. The strength of these interactions is determined mainly by distance. Simulations correctly predict behavior for a variety of manipulations on multi-aperture stimuli: aligned and skewed lines, different presentation times, different inter-aperture gaps, and different spatial frequencies. However, strictly distance-dependent mechanisms are too simplistic to account for all experimental data. Mismatches for grossly misoriented lines suggest collinear facilitation as a promising extension. Once incorporated, collinear facilitation not only correctly predicts results for misoriented patterns but also accounts for the lack of motion integration between heterogeneous stimuli such as lines and dots.

  12. Estimating Internal Respiratory Motion from Respiratory Surrogate Signals Using Correspondence Models

    NASA Astrophysics Data System (ADS)

    McClelland, Jamie

    It is often difficult or impossible to directly monitor the respiratory motion of the tumour and other internal anatomy during RT treatment. Implanted markers can be used, but this involves an invasive procedure and has a number of other associated risks and problems. An alternative option is to use a correspondence model. This models the relationship between a respiratory surrogate signal(s), such as spirometry or the displacement of the skin surface, and the motion of the internal anatomy. Such a model allows the internal motion to be estimated from the surrogate signal(s), which can be easily monitored during RT treatment. The correspondence model is constructed prior to RT treatment. Imaging data is simultaneously acquired with the surrogate signal(s), and the internal motion is measured from the imaging data, e.g. using deformable image registration. A correspondence model is then fit relating the internal motion to the surrogate signal(s). This can then be used during treatment to estimate the internal motion from the surrogate signal(s). This chapter reviews the most popular correspondence models that have been used in the literature, as well as the different surrogate signals, types of imaging data used to measure the internal motion, and fitting methods used to fit the correspondence model to the data.

  13. Signal Processing of MEMS Gyroscope Arrays to Improve Accuracy Using a 1st Order Markov for Rate Signal Modeling

    PubMed Central

    Jiang, Chengyu; Xue, Liang; Chang, Honglong; Yuan, Guangmin; Yuan, Weizheng

    2012-01-01

    This paper presents a signal processing technique to improve angular rate accuracy of the gyroscope by combining the outputs of an array of MEMS gyroscope. A mathematical model for the accuracy improvement was described and a Kalman filter (KF) was designed to obtain optimal rate estimates. Especially, the rate signal was modeled by a first-order Markov process instead of a random walk to improve overall performance. The accuracy of the combined rate signal and affecting factors were analyzed using a steady-state covariance. A system comprising a six-gyroscope array was developed to test the presented KF. Experimental tests proved that the presented model was effective at improving the gyroscope accuracy. The experimental results indicated that six identical gyroscopes with an ARW noise of 6.2 °/√h and a bias drift of 54.14 °/h could be combined into a rate signal with an ARW noise of 1.8 °/√h and a bias drift of 16.3 °/h, while the estimated rate signal by the random walk model has an ARW noise of 2.4 °/√h and a bias drift of 20.6 °/h. It revealed that both models could improve the angular rate accuracy and have a similar performance in static condition. In dynamic condition, the test results showed that the first-order Markov process model could reduce the dynamic errors 20% more than the random walk model. PMID:22438734

  14. The truthful signalling hypothesis: an explicit general equilibrium model.

    PubMed

    Hausken, Kjell; Hirshleifer, Jack

    2004-06-21

    In mating competition, the truthful signalling hypothesis (TSH), sometimes known as the handicap principle, asserts that higher-quality males signal while lower-quality males do not (or else emit smaller signals). Also, the signals are "believed", that is, females mate preferentially with higher-signalling males. Our analysis employs specific functional forms to generate analytic solutions and numerical simulations that illuminate the conditions needed to validate the TSH. Analytic innovations include: (1) A Mating Success Function indicates how female mating choices respond to higher and lower signalling levels. (2) A congestion function rules out corner solutions in which females would mate exclusively with higher-quality males. (3) A Malthusian condition determines equilibrium population size as related to per-capita resource availability. Equilibria validating the TSH are achieved over a wide range of parameters, though not universally. For TSH equilibria it is not strictly necessary that the high-quality males have an advantage in terms of lower per-unit signalling costs, but a cost difference in favor of the low-quality males cannot be too great if a TSH equilibrium is to persist. And although the literature has paid less attention to these points, TSH equilibria may also fail if: the quality disparity among males is too great, or the proportion of high-quality males in the population is too large, or if the congestion effect is too weak. Signalling being unprofitable in aggregate, it can take off from a no-signalling equilibrium only if the trait used for signalling is not initially a handicap, but instead is functionally useful at low levels. Selection for this trait sets in motion a bandwagon, whereby the initially useful indicator is pushed by male-male competition into the domain where it does indeed become a handicap. PMID:15178198

  15. Radioxenon spiked air

    DOE PAGES

    Watrous, Matthew G.; Delmore, James E.; Hague, Robert K.; Houghton, Tracy P.; Jenson, Douglas D.; Mann, Nick R.

    2015-08-27

    Four of the radioactive xenon isotopes (131mXe, 133mXe, 133Xe and 135Xe) with half-lives ranging from 9 h to 12 days are produced from nuclear fission and can be detected from days to weeks following their production and release. Being inert gases, they are readily transported through the atmosphere. Sources for release of radioactive xenon isotopes include operating nuclear reactors via leaks in fuel rods, medical isotope production facilities, and nuclear weapons' detonations. They are not normally released from fuel reprocessing due to the short half-lives. The Comprehensive Nuclear-Test-Ban Treaty has led to creation of the International Monitoring System. The Internationalmore » Monitoring System, when fully implemented, will consist of one component with 40 stations monitoring radioactive xenon around the globe. Monitoring these radioactive xenon isotopes is important to the Comprehensive Nuclear-Test-Ban Treaty in determining whether a seismically detected event is or is not a nuclear detonation. A variety of radioactive xenon quality control check standards, quantitatively spiked into various gas matrices, could be used to demonstrate that these stations are operating on the same basis in order to bolster defensibility of data across the International Monitoring System. This study focuses on Idaho National Laboratory's capability to produce three of the xenon isotopes in pure form and the use of the four xenon isotopes in various combinations to produce radioactive xenon spiked air samples that could be subsequently distributed to participating facilities.« less

  16. Radioxenon spiked air

    SciTech Connect

    Watrous, Matthew G.; Delmore, James E.; Hague, Robert K.; Houghton, Tracy P.; Jenson, Douglas D.; Mann, Nick R.

    2015-08-27

    Four of the radioactive xenon isotopes (131mXe, 133mXe, 133Xe and 135Xe) with half-lives ranging from 9 h to 12 days are produced from nuclear fission and can be detected from days to weeks following their production and release. Being inert gases, they are readily transported through the atmosphere. Sources for release of radioactive xenon isotopes include operating nuclear reactors via leaks in fuel rods, medical isotope production facilities, and nuclear weapons' detonations. They are not normally released from fuel reprocessing due to the short half-lives. The Comprehensive Nuclear-Test-Ban Treaty has led to creation of the International Monitoring System. The International Monitoring System, when fully implemented, will consist of one component with 40 stations monitoring radioactive xenon around the globe. Monitoring these radioactive xenon isotopes is important to the Comprehensive Nuclear-Test-Ban Treaty in determining whether a seismically detected event is or is not a nuclear detonation. A variety of radioactive xenon quality control check standards, quantitatively spiked into various gas matrices, could be used to demonstrate that these stations are operating on the same basis in order to bolster defensibility of data across the International Monitoring System. This study focuses on Idaho National Laboratory's capability to produce three of the xenon isotopes in pure form and the use of the four xenon isotopes in various combinations to produce radioactive xenon spiked air samples that could be subsequently distributed to participating facilities.

  17. Radioxenon spiked air.

    PubMed

    Watrous, Matthew G; Delmore, James E; Hague, Robert K; Houghton, Tracy P; Jenson, Douglas D; Mann, Nick R

    2015-12-01

    Four of the radioactive xenon isotopes ((131m)Xe, (133m)Xe, (133)Xe and (135)Xe) with half-lives ranging from 9 h to 12 days are produced from nuclear fission and can be detected from days to weeks following their production and release. Being inert gases, they are readily transported through the atmosphere. Sources for release of radioactive xenon isotopes include operating nuclear reactors via leaks in fuel rods, medical isotope production facilities, and nuclear weapons' detonations. They are not normally released from fuel reprocessing due to the short half-lives. The Comprehensive Nuclear-Test-Ban Treaty has led to creation of the International Monitoring System. The International Monitoring System, when fully implemented, will consist of one component with 40 stations monitoring radioactive xenon around the globe. Monitoring these radioactive xenon isotopes is important to the Comprehensive Nuclear-Test-Ban Treaty in determining whether a seismically detected event is or is not a nuclear detonation. A variety of radioactive xenon quality control check standards, quantitatively spiked into various gas matrices, could be used to demonstrate that these stations are operating on the same basis in order to bolster defensibility of data across the International Monitoring System. This paper focuses on Idaho National Laboratory's capability to produce three of the xenon isotopes in pure form and the use of the four xenon isotopes in various combinations to produce radioactive xenon spiked air samples that could be subsequently distributed to participating facilities. PMID:26318775

  18. Radioxenon spiked air.

    PubMed

    Watrous, Matthew G; Delmore, James E; Hague, Robert K; Houghton, Tracy P; Jenson, Douglas D; Mann, Nick R

    2015-12-01

    Four of the radioactive xenon isotopes ((131m)Xe, (133m)Xe, (133)Xe and (135)Xe) with half-lives ranging from 9 h to 12 days are produced from nuclear fission and can be detected from days to weeks following their production and release. Being inert gases, they are readily transported through the atmosphere. Sources for release of radioactive xenon isotopes include operating nuclear reactors via leaks in fuel rods, medical isotope production facilities, and nuclear weapons' detonations. They are not normally released from fuel reprocessing due to the short half-lives. The Comprehensive Nuclear-Test-Ban Treaty has led to creation of the International Monitoring System. The International Monitoring System, when fully implemented, will consist of one component with 40 stations monitoring radioactive xenon around the globe. Monitoring these radioactive xenon isotopes is important to the Comprehensive Nuclear-Test-Ban Treaty in determining whether a seismically detected event is or is not a nuclear detonation. A variety of radioactive xenon quality control check standards, quantitatively spiked into various gas matrices, could be used to demonstrate that these stations are operating on the same basis in order to bolster defensibility of data across the International Monitoring System. This paper focuses on Idaho National Laboratory's capability to produce three of the xenon isotopes in pure form and the use of the four xenon isotopes in various combinations to produce radioactive xenon spiked air samples that could be subsequently distributed to participating facilities.

  19. Vehicular headways on signalized intersections: theory, models, and reality

    NASA Astrophysics Data System (ADS)

    Krbálek, Milan; Šleis, Jiří

    2015-01-01

    We discuss statistical properties of vehicular headways measured on signalized crossroads. On the basis of mathematical approaches, we formulate theoretical and empirically inspired criteria for the acceptability of theoretical headway distributions. Sequentially, the multifarious families of statistical distributions (commonly used to fit real-road headway statistics) are confronted with these criteria, and with original empirical time clearances gauged among neighboring vehicles leaving signal-controlled crossroads after a green signal appears. Using three different numerical schemes, we demonstrate that an arrangement of vehicles on an intersection is a consequence of the general stochastic nature of queueing systems, rather than a consequence of traffic rules, driver estimation processes, or decision-making procedures.

  20. The Linear Model Research on Tibetan Six-Character Poetry's Respiratory Signal

    NASA Astrophysics Data System (ADS)

    Yonghong, Li; Yangrui, Yang; Lei, Guo; Hongzhi, Yu

    In this paper, we studied the Tibetan six-character pomes' respiratory signal during reading from the perspective of the physiological. Main contents include: 1) Selected 40 representative Tibetan six-character and four lines pomes from ldquo; The Love-songs of 6th Dalai Lama Tshang•yangGya•tsho ", and recorded speech sounds, voice and respiratory signals; 2) Designed a set of respiratory signal parameters for the study of poetry; 3) Extracted the relevant parameters of poetry respiratory signal by using the well-established respiratory signal processing platform; 4) Studied the type of breathing pattern, established the linear model of poetry respiratory signal.

  1. Moment-flux models for bacterial chemotaxis in large signal gradients.

    PubMed

    Xue, Chuan; Yang, Xige

    2016-10-01

    Chemotaxis is a fundamental process in the life of many prokaryotic and eukaryotic cells. Chemotaxis of bacterial populations has been modeled by both individual-based stochastic models that take into account the biochemistry of intracellular signaling, and continuum PDE models that track the evolution of the cell density in space and time. Continuum models have been derived from individual-based models that describe intracellular signaling by a system of ODEs. The derivations rely on quasi-steady state approximations of the internal ODE system. While this assumption is valid if cell movement is subject to slowly changing signals, it is often violated if cells are exposed to rapidly changing signals. In the latter case current continuum models break down and do not match the underlying individual-based model quantitatively. In this paper, we derive new PDE models for bacterial chemotaxis in large signal gradients that involve not only the cell density and flux, but also moments of the intracellular signals as a measure of the deviation of cell's internal state from its steady state. The derivation is based on a new moment closure method without calling the quasi-steady state assumption of intracellular signaling. Numerical simulations suggest that the resulting model matches the population dynamics quantitatively for a much larger range of signals. PMID:26922437

  2. Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform

    PubMed Central

    Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong

    2016-01-01

    We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features. PMID:27304979

  3. Imaging TGFβ Signaling in Mouse Models of Cancer Metastasis.

    PubMed

    Kang, Yibin

    2016-01-01

    Metastatic spread of cancer cells from the primary tumors to distant vital organs, such as lung, liver, brain, and bone, is responsible for the majority of cancer-related deaths. Development of metastatic lesions is critically dependent on the interaction of tumor cells with the stromal microenvironment. As a multifunctional paracrine signaling factor that is abundantly produced by both tumor and stromal cells, TGFβ has been well established as an important mediator of tumor-stromal interaction during cancer metastasis. Imaging the in vivo dynamic of TGFβ signaling activity during cancer metastasis is critical for understanding the pathogenesis of the disease, and for the development of effective anti-metastasis treatments. In this chapter, I describe several xenograft methods to introduce human breast cancer cells into nude mice in order to generate spontaneous and experimental metastases, as well as the luciferase-based bioluminescence imaging method for quantitative imaging analysis of TGFβ signaling in tumor cells during metastasis.

  4. Computational models of signalling networks for non-linear control.

    PubMed

    Fuente, Luis A; Lones, Michael A; Turner, Alexander P; Stepney, Susan; Caves, Leo S; Tyrrell, Andy M

    2013-05-01

    Artificial signalling networks (ASNs) are a computational approach inspired by the signalling processes inside cells that decode outside environmental information. Using evolutionary algorithms to induce complex behaviours, we show how chaotic dynamics in a conservative dynamical system can be controlled. Such dynamics are of particular interest as they mimic the inherent complexity of non-linear physical systems in the real world. Considering the main biological interpretations of cellular signalling, in which complex behaviours and robust cellular responses emerge from the interaction of multiple pathways, we introduce two ASN representations: a stand-alone ASN and a coupled ASN. In particular we note how sophisticated cellular communication mechanisms can lead to effective controllers, where complicated problems can be divided into smaller and independent tasks.

  5. Moving beyond Pure Signal-Detection Models: Comment on Wixted (2007)

    ERIC Educational Resources Information Center

    Parks, Colleen M.; Yonelinas, Andrew P.

    2007-01-01

    The dual-process signal-detection (DPSD) model assumes that recognition memory is based on recollection of qualitative information or on a signal-detection-based familiarity process. The model has proven useful for understanding results from a wide range of memory research, including behavioral, neuropsychological, electrophysiological, and…

  6. Modeling the effects of Multi-path propagation and scintillation on GPS signals

    NASA Astrophysics Data System (ADS)

    Habash Krause, L.; Wilson, S. J.

    2014-12-01

    GPS signals traveling through the earth's ionosphere are affected by charged particles that often disrupt the signal and the information it carries due to "scintillation", which resembles an extra noise source on the signal. These signals are also affected by weather changes, tropospheric scattering, and absorption from objects due to multi-path propagation of the signal. These obstacles cause distortion within information and fading of the signal, which ultimately results in phase locking errors and noise in messages. In this work, we attempted to replicate the distortion that occurs in GPS signals using a signal processing simulation model. We wanted to be able to create and identify scintillated signals so we could better understand the environment that caused it to become scintillated. Then, under controlled conditions, we simulated the receiver's ability to suppress scintillation in a signal. We developed a code in MATLAB that was programmed to: 1. Create a carrier wave and then plant noise (four different frequencies) on the carrier wave, 2. Compute a Fourier transform on the four different frequencies to find the frequency content of a signal, 3. Use a filter and apply it to the Fourier transform of the four frequencies and then compute a Signal-to-noise ratio to evaluate the power (in Decibels) of the filtered signal, and 4.Plot each of these components into graphs. To test the code's validity, we used user input and data from an AM transmitter. We determined that the amplitude modulated signal or AM signal would be the best type of signal to test the accuracy of the MATLAB code due to its simplicity. This code is basic to give students the ability to change and use it to determine the environment and effects of noise on different AM signals and their carrier waves. Overall, we were able to manipulate a scenario of a noisy signal and interpret its behavior and change due to its noisy components: amplitude, frequency, and phase shift.

  7. A spatial focusing model for G protein signals. Regulator of G protein signaling (RGS) protien-mediated kinetic scaffolding.

    PubMed

    Zhong, Huailing; Wade, Susan M; Woolf, Peter J; Linderman, Jennifer J; Traynor, John R; Neubig, Richard R

    2003-02-28

    Regulators of G protein signaling (RGS) are GTPase-accelerating proteins (GAPs), which can inhibit heterotrimeric G protein pathways. In this study, we provide experimental and theoretical evidence that high concentrations of receptors (as at a synapse) can lead to saturation of GDP-GTP exchange making GTP hydrolysis rate-limiting. This results in local depletion of inactive heterotrimeric G-GDP, which is reversed by RGS GAP activity. Thus, RGS enhances receptor-mediated G protein activation even as it deactivates the G protein. Evidence supporting this model includes a GTP-dependent enhancement of guanosine 5'-3-O-(thio)triphosphate (GTPgammaS) binding to G(i) by RGS. The RGS domain of RGS4 is sufficient for this, not requiring the NH(2)- or COOH-terminal extensions. Furthermore, a kinetic model including only the GAP activity of RGS replicates the GTP-dependent enhancement of GTPgammaS binding observed experimentally. Finally in a Monte Carlo model, this mechanism results in a dramatic "spatial focusing" of active G protein. Near the receptor, G protein activity is maintained even with RGS due to the ability of RGS to reduce depletion of local Galpha-GDP levels permitting rapid recoupling to receptor and maintained G protein activation near the receptor. In contrast, distant signals are suppressed by the RGS, since Galpha-GDP is not depleted there. Thus, a novel RGS-mediated "kinetic scaffolding" mechanism is proposed which narrows the spatial range of active G protein around a cluster of receptors limiting the spill-over of G protein signals to more distant effector molecules, thus enhancing the specificity of G(i) protein signals. PMID:12446706

  8. A spatial focusing model for G protein signals. Regulator of G protein signaling (RGS) protien-mediated kinetic scaffolding.

    PubMed

    Zhong, Huailing; Wade, Susan M; Woolf, Peter J; Linderman, Jennifer J; Traynor, John R; Neubig, Richard R

    2003-02-28

    Regulators of G protein signaling (RGS) are GTPase-accelerating proteins (GAPs), which can inhibit heterotrimeric G protein pathways. In this study, we provide experimental and theoretical evidence that high concentrations of receptors (as at a synapse) can lead to saturation of GDP-GTP exchange making GTP hydrolysis rate-limiting. This results in local depletion of inactive heterotrimeric G-GDP, which is reversed by RGS GAP activity. Thus, RGS enhances receptor-mediated G protein activation even as it deactivates the G protein. Evidence supporting this model includes a GTP-dependent enhancement of guanosine 5'-3-O-(thio)triphosphate (GTPgammaS) binding to G(i) by RGS. The RGS domain of RGS4 is sufficient for this, not requiring the NH(2)- or COOH-terminal extensions. Furthermore, a kinetic model including only the GAP activity of RGS replicates the GTP-dependent enhancement of GTPgammaS binding observed experimentally. Finally in a Monte Carlo model, this mechanism results in a dramatic "spatial focusing" of active G protein. Near the receptor, G protein activity is maintained even with RGS due to the ability of RGS to reduce depletion of local Galpha-GDP levels permitting rapid recoupling to receptor and maintained G protein activation near the receptor. In contrast, distant signals are suppressed by the RGS, since Galpha-GDP is not depleted there. Thus, a novel RGS-mediated "kinetic scaffolding" mechanism is proposed which narrows the spatial range of active G protein around a cluster of receptors limiting the spill-over of G protein signals to more distant effector molecules, thus enhancing the specificity of G(i) protein signals.

  9. SEMICONDUCTOR DEVICES: RF CMOS modeling: a novel empirical large-signal model for an RF-MOSFET

    NASA Astrophysics Data System (ADS)

    Lingling, Sun; Binyi, Lü; Jun, Liu; Lei, Chen

    2010-04-01

    A novel empirical model for large-signal modeling of an RF-MOSFET is proposed. The proposed model is validated in the DC, AC, small-signal and large-signal characteristics of a 32-finger nMOSFET fabricated in SMIC's 0.18 μm RF CMOS technology. The power dissipation caused by self-heating is described. Excellent agreement is achieved between simulation and measurement for DC, S-parameters (50 MHz-40 GHz), and power characteristics, which shows that our model is accurate and reliable.

  10. The evolution of novel animal signals: silk decorations as a model system.

    PubMed

    Walter, André; Elgar, Mark A

    2012-08-01

    Contemporary animal signals may derive from an elaboration of existing forms or novel non-signalling traits. Unravelling the evolution of the latter is challenging because experiments investigating the maintenance of the signal may provide little insight into its early evolution. The web decorations, or stabilimenta of some orb web spiders represent an intriguing model system to investigate novel animal signals. For over 100 years, biologists have struggled to explain why spiders decorate their webs with additional threads of silk, producing a conspicuous signal on a construction whose function is to entangle unsuspecting prey. The numerous explanations for the maintenance of this behaviour starkly contrast with the absence of a plausible explanation for its evolutionary origin. Our review highlights the difficulties in resolving both the evolution and maintenance of animal signalling, and inferring the causative arrow-even from experimental studies. Drawing on recent research that focuses on physiological processes, we provide a model of the evolutionary progression of web-decorating behaviour.

  11. Modeling automotive FlexRay transceivers for signal integrity and EMC simulations

    NASA Astrophysics Data System (ADS)

    Günther, H.; Hilger, U.; Frei, S.

    2011-07-01

    Automotive bus systems like FlexRay or CAN transmit safety critical data. To ensure correct functionality under all circumstances, extensive investigations about signal integrity and EMC have to be performed. To be able to use simulation in this validation process, suitable models for the components of the bus systems have to be developed. This paper shows how a combined transceiver model for signal integrity and EMC investigations can be created. The model shows good results in comparison to measurement data.

  12. Power-Law Modeling of Cancer Cell Fates Driven by Signaling Data to Reveal Drug Effects

    PubMed Central

    Zhang, Fan; Wu, Min; Kwoh, Chee Keong; Zheng, Jie

    2016-01-01

    Extracellular signals are captured and transmitted by signaling proteins inside a cell. An important type of cellular responses to the signals is the cell fate decision, e.g., apoptosis. However, the underlying mechanisms of cell fate regulation are still unclear, thus comprehensive and detailed kinetic models are not yet available. Alternatively, data-driven models are promising to bridge signaling data with the phenotypic measurements of cell fates. The traditional linear model for data-driven modeling of signaling pathways has its limitations because it assumes that the a cell fate is proportional to the activities of signaling proteins, which is unlikely in the complex biological systems. Therefore, we propose a power-law model to relate the activities of all the measured signaling proteins to the probabilities of cell fates. In our experiments, we compared our nonlinear power-law model with the linear model on three cancer datasets with phosphoproteomics and cell fate measurements, which demonstrated that the nonlinear model has superior performance on cell fates prediction. By in silico simulation of virtual protein knock-down, the proposed model is able to reveal drug effects which can complement traditional approaches such as binding affinity analysis. Moreover, our model is able to capture cell line specific information to distinguish one cell line from another in cell fate prediction. Our results show that the power-law data-driven model is able to perform better in cell fate prediction and provide more insights into the signaling pathways for cancer cell fates than the linear model. PMID:27764199

  13. SEMICONDUCTOR DEVICES Intrinsic stability of an HBT based on a small signal equivalent circuit model

    NASA Astrophysics Data System (ADS)

    Yanhu, Chen; Huajun, Shen; Xinyu, Liu; Huijun, Li; Hui, Xu; Ling, Li

    2010-12-01

    Intrinsic stability of the heterojunction bipolar transistor (HBT) was analyzed and discussed based on a small signal equivalent circuit model. The stability factor of the HBT device was derived based on a compact T-type small signal equivalent circuit model of the HBT. The effect of the mainly small signal model parameters of the HBT on the stability of the HBT was thoroughly examined. The discipline of parameter optimum to improve the intrinsic stability of the HBT was achieved. The theoretic analysis results of the stability were also used to explain the experimental results of the stability of the HBT and they were verified by the experimental results.

  14. SEMICONDUCTOR DEVICES: A symbolically defined InP double heterojunction bipolar transistor large-signal model

    NASA Astrophysics Data System (ADS)

    Yuxiong, Cao; Zhi, Jin; Ji, Ge; Yongbo, Su; Xinyu, Liu

    2009-12-01

    A self-built accurate and flexible large-signal model based on an analysis of the characteristics of InP double heterojunction bipolar transistors (DHBTs) is implemented as a seven-port symbolically defined device (SDD) in Agilent ADS. The model accounts for most physical phenomena including the self-heating effect, Kirk effect, soft knee effect, base collector capacitance and collector transit time. The validity and the accuracy of the large-signal model are assessed by comparing the simulation with the measurement of DC, multi-bias small signal S parameters for InP DHBTs.

  15. An integrated model of epidermal growth factor receptor trafficking and signal transduction.

    PubMed

    Resat, Haluk; Ewald, Jonathan A; Dixon, David A; Wiley, H Steven

    2003-08-01

    Endocytic trafficking of many types of receptors can have profound effects on subsequent signaling events. Quantitative models of these processes, however, have usually considered trafficking and signaling independently. Here, we present an integrated model of both the trafficking and signaling pathway of the epidermal growth factor receptor (EGFR) using a probability weighted-dynamic Monte Carlo simulation. Our model consists of hundreds of distinct endocytic compartments and approximately 13,000 reactions/events that occur over a broad spatio-temporal range. By using a realistic multicompartment model, we can investigate the distribution of the receptors among cellular compartments as well as their potential signal transduction characteristics. Our new model also allows the incorporation of physiochemical aspects of ligand-receptor interactions, such as pH-dependent binding in different endosomal compartments. To determine the utility of this approach, we simulated the differential activation of the EGFR by two of its ligands, epidermal growth factor (EGF) and transforming growth factor-alpha (TGF-alpha). Our simulations predict that when EGFR is activated with TGF-alpha, receptor activation is biased toward the cell surface whereas EGF produces a signaling bias toward the endosomal compartment. Experiments confirm these predictions from our model and simulations. Our model accurately predicts the kinetics and extent of receptor downregulation induced by either EGF or TGF-alpha. Our results suggest that receptor trafficking controls the compartmental bias of signal transduction, rather than simply modulating signal magnitude. Our model provides a new approach to evaluating the complex effect of receptor trafficking on signal transduction. Importantly, the stochastic and compartmental nature of the simulation allows these models to be directly tested by high-throughput approaches, such as quantitative image analysis. PMID:12885624

  16. An Integrated Model of Epidermal Growth Factor Receptor Trafficking and Signal Transduction

    SciTech Connect

    Resat, Haluk; Ewald, Jonathan A.; Dixon, David A.; Wiley, H. S.

    2003-08-01

    Endocytic trafficking of many types of receptors can have profound effects on subsequent signaling events. Quantitative models of these processes, however, have usually considered trafficking and signaling independently. Here, we present an integrated model of both the trafficking and signaling pathway of the epidermal growth factor receptor (EGFR) using a probability weighted-dynamic Monte Carlo simulation. Our model consists of hundreds of distinct endocytic compartments and about 13,000 reactions/events that occur over a broad spatio-temporal range. By using a realistic multi-compartment model, we can investigate the distribution of the receptors among cellular compartments as well as their potential signal transduction characteristics. Our new model also allows the incorporation of physio-chemical aspects of ligand-receptor interactions, such as pH-dependent binding in different endosomal compartments. To determine the utility of this approach, we simulated the differential activation of the EGFR by two of its ligands, epidermal growth factor (EGF) and transforming growth factor- alpha (TGF-a). Our simulations predict that when EGFR is activated with TGF-a, receptor activation is biased toward the cell surface whereas EGF produces a signaling bias towards the endosomal compartment. Experiments confirm these predictions from our model and simulations. Our model accurately predicts the kinetics and extent of receptor down-regulation induced by either EGF or TGF-a. Our results suggest that receptor trafficking controls the compartmental bias of signal transduction, rather than simply modulating signal magnitude. Our model provides a new approach to evaluating the complex effect of receptor trafficking on signal transduction. Importantly, the stochastic and compartmental nature of the simulation allows these models to be directly tested by high-throughput approaches, such as quantitative image analysis.

  17. Models of Response Inhibition in the Stop-Signal and Stop-Change Paradigms

    PubMed Central

    Verbruggen, Frederick; Logan, Gordon D.

    2009-01-01

    The stop-signal paradigm is very useful for the study of response inhibition. Stop-signal performance is typically described as a race between a go process, triggered by a go stimulus, and a stop process, triggered by the stop signal. Response inhibition depends on the relative finishing time of these two processes. Numerous studies have shown that the independent horse-race model of Logan and Cowan (1984) accounts for the data very well. In the present article, we review the independent horse-race model and related models, such as the interactive horse-race model (Boucher, Palmeri, Logan & Schall, 2007). We present evidence that favors the independent horse-race model but also some evidence that challenges the model. We end with a discussion of recent models that elaborate the role of a stop process in inhibiting a response. PMID:18822313

  18. Dynamical system modeling via signal reduction and neural network simulation

    SciTech Connect

    Paez, T.L.; Hunter, N.F.

    1997-11-01

    Many dynamical systems tested in the field and the laboratory display significant nonlinear behavior. Accurate characterization of such systems requires modeling in a nonlinear framework. One construct forming a basis for nonlinear modeling is that of the artificial neural network (ANN). However, when system behavior is complex, the amount of data required to perform training can become unreasonable. The authors reduce the complexity of information present in system response measurements using decomposition via canonical variate analysis. They describe a method for decomposing system responses, then modeling the components with ANNs. A numerical example is presented, along with conclusions and recommendations.

  19. Knowledge-guided fuzzy logic modeling to infer cellular signaling networks from proteomic data

    PubMed Central

    Liu, Hui; Zhang, Fan; Mishra, Shital Kumar; Zhou, Shuigeng; Zheng, Jie

    2016-01-01

    Modeling of signaling pathways is crucial for understanding and predicting cellular responses to drug treatments. However, canonical signaling pathways curated from literature are seldom context-specific and thus can hardly predict cell type-specific response to external perturbations; purely data-driven methods also have drawbacks such as limited biological interpretability. Therefore, hybrid methods that can integrate prior knowledge and real data for network inference are highly desirable. In this paper, we propose a knowledge-guided fuzzy logic network model to infer signaling pathways by exploiting both prior knowledge and time-series data. In particular, the dynamic time warping algorithm is employed to measure the goodness of fit between experimental and predicted data, so that our method can model temporally-ordered experimental observations. We evaluated the proposed method on a synthetic dataset and two real phosphoproteomic datasets. The experimental results demonstrate that our model can uncover drug-induced alterations in signaling pathways in cancer cells. Compared with existing hybrid models, our method can model feedback loops so that the dynamical mechanisms of signaling networks can be uncovered from time-series data. By calibrating generic models of signaling pathways against real data, our method supports precise predictions of context-specific anticancer drug effects, which is an important step towards precision medicine. PMID:27774993

  20. A Verilog-A large signal model for InP DHBT including thermal effects

    NASA Astrophysics Data System (ADS)

    Yuxia, Shi; Zhi, Jin; Zhijian, Pan; Yongbo, Su; Yuxiong, Cao; Yan, Wang

    2013-06-01

    A large signal model for InP/InGaAs double heterojunction bipolar transistors including thermal effects has been reported, which demonstrated good agreements of simulations with measurements. On the basis of the previous model in which the double heterojunction effect, current blocking effect and high current effect in current expression are considered, the effect of bandgap narrowing with temperature has been considered in transport current while a formula for model parameters as a function of temperature has been developed. This model is implemented by Verilog-A and embedded in ADS. The proposed model is verified with DC and large signal measurements.

  1. Construction of cell type-specific logic models of signaling networks using CellNOpt.

    PubMed

    Morris, Melody K; Melas, Ioannis; Saez-Rodriguez, Julio

    2013-01-01

    Mathematical models are useful tools for understanding protein signaling networks because they provide an integrated view of pharmacological and toxicological processes at the molecular level. Here we describe an approach previously introduced based on logic modeling to generate cell-specific, mechanistic and predictive models of signal transduction. Models are derived from a network encoding prior knowledge that is trained to signaling data, and can be either binary (based on Boolean logic) or quantitative (using a recently developed formalism, constrained fuzzy logic). The approach is implemented in the freely available tool CellNetOptimizer (CellNOpt). We explain the process CellNOpt uses to train a prior knowledge network to data and illustrate its application with a toy example as well as a realistic case describing signaling networks in the HepG2 liver cancer cell line.

  2. Model-based detector and extraction of weak signal frequencies from chaotic data.

    PubMed

    Zhou, Cangtao; Cai, Tianxing; Heng Lai, Choy; Wang, Xingang; Lai, Ying-Cheng

    2008-03-01

    Detecting a weak signal from chaotic time series is of general interest in science and engineering. In this work we introduce and investigate a signal detection algorithm for which chaos theory, nonlinear dynamical reconstruction techniques, neural networks, and time-frequency analysis are put together in a synergistic manner. By applying the scheme to numerical simulation and different experimental measurement data sets (Henon map, chaotic circuit, and NH(3) laser data sets), we demonstrate that weak signals hidden beneath the noise floor can be detected by using a model-based detector. Particularly, the signal frequencies can be extracted accurately in the time-frequency space. By comparing the model-based method with the standard denoising wavelet technique as well as supervised principal components analysis detector, we further show that the nonlinear dynamics and neural network-based approach performs better in extracting frequencies of weak signals hidden in chaotic time series.

  3. Reiteration of Hankel singular value decomposition for modeling of complex-valued signal

    NASA Astrophysics Data System (ADS)

    Staniszewski, Michał; Skorupa, Agnieszka; Boguszewicz, Łukasz; Wicher, Magdalena; Konopka, Marek; Sokół, Maria; Polański, Andrzej

    2016-06-01

    Modeling signal which forms complex values is a common scientific problem, which is present in many applications, i.e. in medical signals, computer graphics and vision. One of the possible solution is utilization of Hankel Singular Value Decomposition. In the first step complex-valued signal is arranged in a special form called Hankel matrix, which is in the next step decomposed in operation of Singular Value Decomposition. Obtained matrices can be then reformulated in order to get parameters describing system. Basic method can be applied for fitting whole signal but it fails in modeling each particular component of signal. Modification of basic HSVD method, which relies on reiteration and is used for main components, and application of prior knowledge solves presented problem.

  4. Flavour changing Z ' signals in a 6D inspired model

    NASA Astrophysics Data System (ADS)

    Frère, Jean-Marie; Libanov, Maxim; Mollet, Simon; Troitsky, Sergey

    2016-06-01

    We consider the phenomenology of new neutral gauge bosons with flavour non-diagonal couplings to fermions, inherent in 6D models explaining successfully the hierarchy of masses as well as the mixing for quarks, charged leptons and neutrinos (this model can in particular be credited with the correct prediction of the neutrino mixing angle θ 13). We present a general relation between masses of new gauge bosons and their couplings to fermions. We show that in the current realization of the model, the new heavy bosons are unreachable at LHC but argue why the constraint could be relaxed in the context of a different realization. In view of a more systematic study, we use an effective model inspired by the above to relate directly rare meson decays to possible LHC observations. In terms of effective Lagrangians, this can be seen as the introduction in the model of only one overall scaling parameter to extend our approach without modifying the 4D (gauge) structure.

  5. Model of human breathing reflected signal received by PN-UWB radar.

    PubMed

    Mabrouk, Mohamed; Rajan, Sreeraman; Bolic, Miodrag; Batkin, Izmail; Dajani, Hilmi R; Groza, Voicu Z

    2014-01-01

    Human detection is an integral component of civilian and military rescue operations, military surveillance and combat operations. Human detection can be achieved through monitoring of vital signs. In this article, a mathematical model of human breathing reflected signal received in PN-UWB radar is proposed. Unlike earlier published works, both chest and abdomen movements are considered for modeling the radar return signal along with the contributions of fundamental breathing frequency and its harmonics. Analyses of recorded reflected signals from three subjects in different postures and at different ranges from the radar indicate that ratios of the amplitudes of the harmonics contain information about posture and posture change.

  6. Signal Modulation of Super Read Only Memory with Thermally Activated Aperture Model

    NASA Astrophysics Data System (ADS)

    Kim, June Seo; Kwak, Keumcheol; You, Chun-Yeol

    2008-07-01

    We describe the signal modulation of super read only memory (ROM) with thermally activated aperture model using a three-dimensional finite-difference time-domain method. The thermally activated aperture is modeled using a spatially varied refractive indices of the GeSbTe layer. No meaningful signal modulation is observed without thermally activated aperture below the resolution limit of 120 nm. When we open the thermally activated aperture by considering the temperature dependence of the refractive indices in the GeSbTe layer, the 2.8 and 1.7% signal modulations are observed for 120 and 80 nm pits, respectively. The experimentally observed signal modulation under the resolution limit can be explained using the thermally activated aperture model.

  7. Modeling and a correlation algorithm for spaceborne SAR signals

    NASA Technical Reports Server (NTRS)

    Wu, C.; Liu, K. Y.; Jin, M.

    1982-01-01

    A mathematical model of a spaceborne synthetic aperture radar (SAR) response is presented. Thhe associated SAR system performance, in terms of the resolution capability, is also discussed. The analysis of spaceborne SAR target response indicates that the SAR correlation problem is a two-dimensional one with a linear shift-variant response function. A new digital processing algorithm is proposed here in order to realize an economical digital SAR correlation system. The proposed algorithm treats the two-dimensional correlation by a combination of frequency domain fast correlation in the azimuth dimension and a time-domain convolver type of operation in the range dimension. Finally, digitally correlated SEASAT satellite SAR imagery is used in an exemplary sense to validate the SAR response model and the new digital processing technique developed.

  8. Frequency-Domain Models for Nonlinear Microwave Devices Based on Large-Signal Measurements

    PubMed Central

    Jargon, Jeffrey A.; DeGroot, Donald C.; Gupta, K. C.

    2004-01-01

    In this paper, we introduce nonlinear large-signal scattering ( S) parameters, a new type of frequency-domain mapping that relates incident and reflected signals. We present a general form of nonlinear large-signal S-parameters and show that they reduce to classic S-parameters in the absence of nonlinearities. Nonlinear large-signal impedance ( Z) and admittance ( D) parameters are also introduced, and equations relating the different representations are derived. We illustrate how nonlinear large-signal S-parameters can be used as a tool in the design process of a nonlinear circuit, specifically a single-diode 1 GHz frequency-doubler. For the case where a nonlinear model is not readily available, we developed a method of extracting nonlinear large-signal S-parameters obtained with artificial neural network models trained with multiple measurements made by a nonlinear vector network analyzer equipped with two sources. Finally, nonlinear large-signal S-parameters are compared to another form of nonlinear mapping, known as nonlinear scattering functions. The nonlinear large-signal S-parameters are shown to be more general. PMID:27366621

  9. Model reduction of the intracellular-signaling subsystem of apoptosis.

    PubMed

    Bykov, V; Gol'dshtein, V

    2016-05-01

    In recent few decades numerical treatment has become a standard tool in the system analysis and investigation of complex chemical reactions networks of reacting flows. The information about certain networks of biochemical reactions constantly increases. This leads to detailed descriptions of biochemical processes as a system of differential equations of high complexity and dimension. Nowadays methods, which are able automatically reduce the system dimension and complexity, are highly desirable. Recently several methods were developed for model reduction in combustion and chemical kinetics aiming at automatic numerical treatment and constructing the reduced system. The reduced system represents reliable description reproducing the detailed system behavior accurately enough. In this work the method of qualitative ODEs system analysis and the global quasi-linearization method (GQL) for kinetic mechanism reduction of combustion models are applied to the biochemical reaction network of the apoptosis. It is shown that the original model of the apoptosis can be essentially simplified firstly by using linear system integrals (9 dimensions) of the ODEs system, secondly the results of GQL analysis reveals the possibility of a further reduction (4 dimensions). It means that the final system dimension reaches 15 compare to the original 28 without any noticeable accuracy losses. PMID:26880618

  10. Model reduction of the intracellular-signaling subsystem of apoptosis.

    PubMed

    Bykov, V; Gol'dshtein, V

    2016-05-01

    In recent few decades numerical treatment has become a standard tool in the system analysis and investigation of complex chemical reactions networks of reacting flows. The information about certain networks of biochemical reactions constantly increases. This leads to detailed descriptions of biochemical processes as a system of differential equations of high complexity and dimension. Nowadays methods, which are able automatically reduce the system dimension and complexity, are highly desirable. Recently several methods were developed for model reduction in combustion and chemical kinetics aiming at automatic numerical treatment and constructing the reduced system. The reduced system represents reliable description reproducing the detailed system behavior accurately enough. In this work the method of qualitative ODEs system analysis and the global quasi-linearization method (GQL) for kinetic mechanism reduction of combustion models are applied to the biochemical reaction network of the apoptosis. It is shown that the original model of the apoptosis can be essentially simplified firstly by using linear system integrals (9 dimensions) of the ODEs system, secondly the results of GQL analysis reveals the possibility of a further reduction (4 dimensions). It means that the final system dimension reaches 15 compare to the original 28 without any noticeable accuracy losses.

  11. Modeling approaches for qualitative and semi-quantitative analysis of cellular signaling networks

    PubMed Central

    2013-01-01

    A central goal of systems biology is the construction of predictive models of bio-molecular networks. Cellular networks of moderate size have been modeled successfully in a quantitative way based on differential equations. However, in large-scale networks, knowledge of mechanistic details and kinetic parameters is often too limited to allow for the set-up of predictive quantitative models. Here, we review methodologies for qualitative and semi-quantitative modeling of cellular signal transduction networks. In particular, we focus on three different but related formalisms facilitating modeling of signaling processes with different levels of detail: interaction graphs, logical/Boolean networks, and logic-based ordinary differential equations (ODEs). Albeit the simplest models possible, interaction graphs allow the identification of important network properties such as signaling paths, feedback loops, or global interdependencies. Logical or Boolean models can be derived from interaction graphs by constraining the logical combination of edges. Logical models can be used to study the basic input–output behavior of the system under investigation and to analyze its qualitative dynamic properties by discrete simulations. They also provide a suitable framework to identify proper intervention strategies enforcing or repressing certain behaviors. Finally, as a third formalism, Boolean networks can be transformed into logic-based ODEs enabling studies on essential quantitative and dynamic features of a signaling network, where time and states are continuous. We describe and illustrate key methods and applications of the different modeling formalisms and discuss their relationships. In particular, as one important aspect for model reuse, we will show how these three modeling approaches can be combined to a modeling pipeline (or model hierarchy) allowing one to start with the simplest representation of a signaling network (interaction graph), which can later be refined to

  12. Modeling approaches for qualitative and semi-quantitative analysis of cellular signaling networks.

    PubMed

    Samaga, Regina; Klamt, Steffen

    2013-01-01

    A central goal of systems biology is the construction of predictive models of bio-molecular networks. Cellular networks of moderate size have been modeled successfully in a quantitative way based on differential equations. However, in large-scale networks, knowledge of mechanistic details and kinetic parameters is often too limited to allow for the set-up of predictive quantitative models.Here, we review methodologies for qualitative and semi-quantitative modeling of cellular signal transduction networks. In particular, we focus on three different but related formalisms facilitating modeling of signaling processes with different levels of detail: interaction graphs, logical/Boolean networks, and logic-based ordinary differential equations (ODEs). Albeit the simplest models possible, interaction graphs allow the identification of important network properties such as signaling paths, feedback loops, or global interdependencies. Logical or Boolean models can be derived from interaction graphs by constraining the logical combination of edges. Logical models can be used to study the basic input-output behavior of the system under investigation and to analyze its qualitative dynamic properties by discrete simulations. They also provide a suitable framework to identify proper intervention strategies enforcing or repressing certain behaviors. Finally, as a third formalism, Boolean networks can be transformed into logic-based ODEs enabling studies on essential quantitative and dynamic features of a signaling network, where time and states are continuous.We describe and illustrate key methods and applications of the different modeling formalisms and discuss their relationships. In particular, as one important aspect for model reuse, we will show how these three modeling approaches can be combined to a modeling pipeline (or model hierarchy) allowing one to start with the simplest representation of a signaling network (interaction graph), which can later be refined to logical

  13. Skull Defects in Finite Element Head Models for Source Reconstruction from Magnetoencephalography Signals.

    PubMed

    Lau, Stephan; Güllmar, Daniel; Flemming, Lars; Grayden, David B; Cook, Mark J; Wolters, Carsten H; Haueisen, Jens

    2016-01-01

    Magnetoencephalography (MEG) signals are influenced by skull defects. However, there is a lack of evidence of this influence during source reconstruction. Our objectives are to characterize errors in source reconstruction from MEG signals due to ignoring skull defects and to assess the ability of an exact finite element head model to eliminate such errors. A detailed finite element model of the head of a rabbit used in a physical experiment was constructed from magnetic resonance and co-registered computer tomography imaging that differentiated nine tissue types. Sources of the MEG measurements above intact skull and above skull defects respectively were reconstructed using a finite element model with the intact skull and one incorporating the skull defects. The forward simulation of the MEG signals reproduced the experimentally observed characteristic magnitude and topography changes due to skull defects. Sources reconstructed from measured MEG signals above intact skull matched the known physical locations and orientations. Ignoring skull defects in the head model during reconstruction displaced sources under a skull defect away from that defect. Sources next to a defect were reoriented. When skull defects, with their physical conductivity, were incorporated in the head model, the location and orientation errors were mostly eliminated. The conductivity of the skull defect material non-uniformly modulated the influence on MEG signals. We propose concrete guidelines for taking into account conducting skull defects during MEG coil placement and modeling. Exact finite element head models can improve localization of brain function, specifically after surgery. PMID:27092044

  14. Skull Defects in Finite Element Head Models for Source Reconstruction from Magnetoencephalography Signals

    PubMed Central

    Lau, Stephan; Güllmar, Daniel; Flemming, Lars; Grayden, David B.; Cook, Mark J.; Wolters, Carsten H.; Haueisen, Jens

    2016-01-01

    Magnetoencephalography (MEG) signals are influenced by skull defects. However, there is a lack of evidence of this influence during source reconstruction. Our objectives are to characterize errors in source reconstruction from MEG signals due to ignoring skull defects and to assess the ability of an exact finite element head model to eliminate such errors. A detailed finite element model of the head of a rabbit used in a physical experiment was constructed from magnetic resonance and co-registered computer tomography imaging that differentiated nine tissue types. Sources of the MEG measurements above intact skull and above skull defects respectively were reconstructed using a finite element model with the intact skull and one incorporating the skull defects. The forward simulation of the MEG signals reproduced the experimentally observed characteristic magnitude and topography changes due to skull defects. Sources reconstructed from measured MEG signals above intact skull matched the known physical locations and orientations. Ignoring skull defects in the head model during reconstruction displaced sources under a skull defect away from that defect. Sources next to a defect were reoriented. When skull defects, with their physical conductivity, were incorporated in the head model, the location and orientation errors were mostly eliminated. The conductivity of the skull defect material non-uniformly modulated the influence on MEG signals. We propose concrete guidelines for taking into account conducting skull defects during MEG coil placement and modeling. Exact finite element head models can improve localization of brain function, specifically after surgery. PMID:27092044

  15. Structural modeling and analysis of signaling pathways based on Petri nets.

    PubMed

    Li, Chen; Suzuki, Shunichi; Ge, Qi-Wei; Nakata, Mitsuru; Matsuno, Hiroshi; Miyano, Satoru

    2006-10-01

    The purpose of this paper is to discuss how to model and analyze signaling pathways by using Petri net. Firstly, we propose a modeling method based on Petri net by paying attention to the molecular interactions and mechanisms. Then, we introduce a new notion "activation transduction component" in order to describe an enzymic activation process of reactions in signaling pathways and shows its correspondence to a so-called elementary T-invariant in the Petri net models. Further, we design an algorithm to effectively find basic enzymic activation processes by obtaining a series of elementary T-invariants in the Petri net models. Finally, we demonstrate how our method is practically used in modeling and analyzing signaling pathway mediated by thrombopoietin as an example.

  16. Model-Based Information Extraction From Synthetic Aperture Radar Signals

    NASA Astrophysics Data System (ADS)

    Matzner, Shari A.

    2011-07-01

    Synthetic aperture radar (SAR) is a remote sensing technology for imaging areas of the earth's surface. SAR has been successfully used for monitoring characteristics of the natural environment such as land cover type and tree density. With the advent of higher resolution sensors, it is now theoretically possible to extract information about individual structures such as buildings from SAR imagery. This information could be used for disaster response and security-related intelligence. SAR has an advantage over other remote sensing technologies for these applications because SAR data can be collected during the night and in rainy or cloudy conditions. This research presents a model-based method for extracting information about a building -- its height and roof slope -- from a single SAR image. Other methods require multiple images or ancillary data from specialized sensors, making them less practical. The model-based method uses simulation to match a hypothesized building to an observed SAR image. The degree to which a simulation matches the observed data is measured by mutual information. The success of this method depends on the accuracy of the simulation and on the reliability of the mutual information similarity measure. Electromagnetic theory was applied to relate a building's physical characteristics to the features present in a SAR image. This understanding was used to quantify the precision of building information contained in SAR data, and to identify the inputs needed for accurate simulation. A new SAR simulation technique was developed to meet the accuracy and efficiency requirements of model-based information extraction. Mutual information, a concept from information theory, has become a standard for measuring the similarity between medical images. Its performance in the context of matching a simulation image to a SAR image was evaluated in this research, and it was found to perform well under certain conditions. The factors that affect its performance

  17. Thematic Minireview Series: Complexities of Cellular Signaling Revealed by Simple Model Organisms.

    PubMed

    Dohlman, Henrik G

    2016-04-01

    All cells discriminate environmental signals and generate appropriate intracellular responses. Our understanding of these signal transduction mechanisms has benefitted from studies across the kingdoms of life, from fungi and fish to mice and men. This thematic minireview series examines lessons learned from three of the simplest (and best understood) eukaryotic model organisms. The first article focuses on the mating pheromone pathway in budding yeastSaccharomyces cerevisiae The second describes stress-mediated signaling in the roundwormCaenorhabditis elegans The third outlines some of the signaling pathways that dictate growth and development in the fruit flyDrosophila melanogaster Each system has provided unique insights into hormone and neurotransmitter signaling mechanisms, in particular those mediated by the MAPKs. The advances described in these articles will continue to improve our understanding of human physiology and pharmacology. PMID:26907688

  18. Thematic Minireview Series: Complexities of Cellular Signaling Revealed by Simple Model Organisms.

    PubMed

    Dohlman, Henrik G

    2016-04-01

    All cells discriminate environmental signals and generate appropriate intracellular responses. Our understanding of these signal transduction mechanisms has benefitted from studies across the kingdoms of life, from fungi and fish to mice and men. This thematic minireview series examines lessons learned from three of the simplest (and best understood) eukaryotic model organisms. The first article focuses on the mating pheromone pathway in budding yeastSaccharomyces cerevisiae The second describes stress-mediated signaling in the roundwormCaenorhabditis elegans The third outlines some of the signaling pathways that dictate growth and development in the fruit flyDrosophila melanogaster Each system has provided unique insights into hormone and neurotransmitter signaling mechanisms, in particular those mediated by the MAPKs. The advances described in these articles will continue to improve our understanding of human physiology and pharmacology.

  19. Knowledge representation model for systems-level analysis of signal transduction networks.

    PubMed

    Lee, Dong-Yup; Zimmer, Ralf; Lee, Sang-Yup; Hanisch, Daniel; Park, Sunwon

    2004-01-01

    A Petri-net based model for knowledge representation has been developed to describe as explicitly and formally as possible the molecular mechanisms of cell signaling and their pathological implications. A conceptual framework has been established for reconstructing and analyzing signal transduction networks on the basis of the formal representation. Such a conceptual framework renders it possible to qualitatively understand the cell signaling behavior at systems-level. The mechanisms of the complex signaling network are explored by applying the established framework to the signal transduction induced by potent proinflammatory cytokines, IL-1beta and TNF-alpha The corresponding expert-knowledge network is constructed to evaluate its mechanisms in detail. This strategy should be useful in drug target discovery and its validation.

  20. A three-signal model of T-cell lymphoma pathogenesis.

    PubMed

    Wilcox, Ryan A

    2016-01-01

    T-cell lymphoma pathogenesis and classification have, until recently, remained enigmatic. Recently performed whole-exome sequencing and gene-expression profiling studies have significant implications for their classification and treatment. Recurrent genetic modifications in antigen ("signal 1"), costimulatory ("signal 2"), or cytokine receptors ("signal 3"), and the tyrosine kinases and other signaling proteins they activate, have emerged as important therapeutic targets in these lymphomas. Many of these genetic modifications do not function in a cell-autonomous manner, but require the provision of ligand(s) by constituents of the tumor microenvironment, further supporting the long-appreciated view that these lymphomas are dependent upon and driven by their microenvironment. Therefore, the seemingly disparate fields of genomics and immunology are converging. A unifying "3 signal model" for T-cell lymphoma pathogenesis that integrates these findings will be presented, and its therapeutic implications briefly reviewed. PMID:26408334

  1. Design and use of multisine signals for Li-ion battery equivalent circuit modelling. Part 2: Model estimation

    NASA Astrophysics Data System (ADS)

    Widanage, W. D.; Barai, A.; Chouchelamane, G. H.; Uddin, K.; McGordon, A.; Marco, J.; Jennings, P.

    2016-08-01

    An Equivalent Circuit Model (ECM) of a lithium ion (Li-ion) battery is an empirical, linear dynamic model and the bandwidth of the input current signal and level of non-linearity in the voltage response are important for the model's validity. An ECM is, however, generally parametrised with a pulse current signal, which is low in signal bandwidth (Part 1) and any non-linear dependence of the voltage on the current due to transport limitations is ignored. This paper presents a general modelling methodology which utilises the higher bandwidth and number of signal levels of a pulse-multisine signal to estimate the battery dynamics and non-linear characteristics without the need of a 3D look-up table for the model parameters. In the proposed methodology a non-parametric estimate of the battery dynamics and non-linear characteristics are first obtained which assists in the model order selection, and to assess the level of non-linearity. The new model structure, termed as the Non-linear ECM (NL-ECM), gives a lower Root Mean Square (RMS) and peak error when compared to an ECM estimated using a pulse data set.

  2. Phenomenological models of vibration signals for condition monitoring and fault diagnosis of epicyclic gearboxes

    NASA Astrophysics Data System (ADS)

    Lei, Yaguo; Liu, Zongyao; Lin, Jing; Lu, Fanbo

    2016-05-01

    Condition monitoring and fault diagnosis of epicyclic gearboxes using vibration signals are not as straightforward as that of fixed-axis gearboxes since epicyclic gearboxes behave quite differently from fixed-axis gearboxes in many aspects, like spectral structures. Aiming to present the spectral structures of vibration signals of epicyclic gearboxes, phenomenological models of vibration signals of epicyclic gearboxes are developed by algebraic equations and spectral structures of these models are deduced using Fourier series analysis. In the phenomenological models, all the possible vibration transfer paths from gear meshing points to a fixed transducer and the effects of angular shifts of planet gears on the spectral structures are considered. Accordingly, time-varying vibration transfer paths from sun-planet/ring-planet gear meshing points to the fixed transducer due to carrier rotation are given by window functions with different amplitudes. And an angular shift in one planet gear position is introduced in the process of modeling. After the theoretical derivations, three experiments are conducted on an epicyclic gearbox test rig and the spectral structures of collected vibration signals are analyzed. As a result, the effects of angular shifts of planet gears are verified, and the phenomenological models of vibration signals when a local fault occurs on the sun gear and the planet gear are validated, respectively. The experiment results demonstrate that the established phenomenological models in this paper are helpful to the condition monitoring and fault diagnosis of epicyclic gearboxes.

  3. Variables and potential models for the bleaching of luminescence signals in fluvial environments

    USGS Publications Warehouse

    Gray, Harrison J.; Mahan, Shannon

    2015-01-01

    Luminescence dating of fluvial sediments rests on the assumption that sufficient sunlight is available to remove a previously obtained signal in a process deemed bleaching. However, luminescence signals obtained from sediment in the active channels of rivers often contain residual signals. This paper explores and attempts to build theoretical models for the bleaching of luminescence signals in fluvial settings. We present two models, one for sediment transported in an episodic manner, such as flood-driven washes in arid environments, and one for sediment transported in a continuous manner, such as in large continental scale rivers. The episodic flow model assumes that the majority of sediment is bleached while exposed to sunlight at the near surface between flood events and predicts a power-law decay in luminescence signal with downstream transport distance. The continuous flow model is developed by combining the Beer–Lambert law for the attenuation of light through a water column with a general-order kinetics equation to produce an equation with the form of a double negative exponential. The inflection point of this equation is compared with the sediment concentration from a Rouse profile to derive a non-dimensional number capable of assessing the likely extent of bleaching for a given set of luminescence and fluvial parameters. Although these models are theoretically based and not yet necessarily applicable to real-world fluvial systems, we introduce these ideas to stimulate discussion and encourage the development of comprehensive bleaching models with predictive power.

  4. A Coupled Phase-Temperature Model for Dynamics of Transient Neuronal Signal in Mammals Cold Receptor

    PubMed Central

    Kirana, Firman Ahmad; Husein, Irzaman Sulaiman

    2016-01-01

    We propose a theoretical model consisting of coupled differential equation of membrane potential phase and temperature for describing the neuronal signal in mammals cold receptor. Based on the results from previous work by Roper et al., we modified a nonstochastic phase model for cold receptor neuronal signaling dynamics in mammals. We introduce a new set of temperature adjusted functional parameters which allow saturation characteristic at high and low steady temperatures. The modified model also accommodates the transient neuronal signaling process from high to low temperature by introducing a nonlinear differential equation for the “effective temperature” changes which is coupled to the phase differential equation. This simple model can be considered as a candidate for describing qualitatively the physical mechanism of the corresponding transient process. PMID:27774102

  5. Simulation of CIS speech signal processing strategy based on electrical stimulating model of cochlear implant

    NASA Astrophysics Data System (ADS)

    Qian, Zheng; Yu, Dan

    2006-11-01

    During the operating course of Cochlear implant, the speech signal processing strategy converts original speech signal into dim current signal. And then this signal will be transmitted into the embedded electrode to stimulate the remnant auditory nerve to restore the audition of patient. It could be shown that the speech processing strategy is the key part to realize the performance of cochlear implant, but its evaluation method for validity is always lacking. In this paper, the electrical stimulating model of cochlear implant is established at first, and then the acoustic simulation of Continuous Interleaved Sampling (CIS) strategy could be finished on this model. The synthesizing signal simulates the speech signal which could be heard by the deaf with cochlear implant. Therefore, the identification ability of CIS strategy could be estimated by delivering this synthesizing signal to normal audition people. Further more, some detailed analyses for every step of this acoustic simulation could be considered in order to improve the performance and parameters selection of CIS strategy. This work will be helpful for the deaf to enhance their perception and understanding during the speech identification course.

  6. Extraction and modeling of the Oscillatory Potential: signal conditioning to obtain minimally corrupted Oscillatory Potentials.

    PubMed

    Derr, Peter H; Meyer, Andrew U; Haupt, Edward J; Brigell, Mitchell G

    2002-01-01

    A method of extracting a temporally bounded component of a composite signal has been developed which minimizes data corruption in signal processing. The composite signal is windowed in the time domain, padding signals are attached, and finally, the conditioned signal is filtered to extract the component of interest. The method has been utilized to extract the Oscillatory Potential (OP) from the Electroretinogram (ERG). ERGs can contain impulse like transients, including flash artifacts and a-b wave transition, which may not be related to the Oscillatory Potential. Such transients will stimulate a filter, yielding its natural (filter) response and thus distort the actual OP signal. To avoid this effect, time-domain windowing and signal conditioning is used to extract the OP from the ERG. The extraction and modeling approach is applied to ERGs obtained from patients with recent monocular central retinal vein occlusion (CRVO). Model parameters clearly differentiate affected from fellow eyes and show subtle differences between eyes with benign and complicated outcomes.

  7. Wave pinning and spatial patterning in a mathematical model of Antivin/Lefty-Nodal signalling.

    PubMed

    Middleton, A M; King, J R; Loose, M

    2013-12-01

    Nodal signals are key regulators of mesoderm and endoderm development in vertebrate embryos. It has been observed experimentally that in Xenopus embryos the spatial range of Nodal signals is restricted by the signal Antivin (also known as Lefty). Nodal signals can activate both Nodal and Antivin, whereas Antivin is thought to antagonise Nodal by binding either directly to it or to its receptor. In this paper we develop a mathematical model of this signalling network in a line of cells. We consider the heterodimer and receptor-mediated inhibition mechanisms separately and find that, in both cases, the restriction by Antivin to the range of Nodal signals corresponds to wave pinning in the model. Our analysis indicates that, provided Antivin diffuses faster than Nodal, either mechanism can robustly account for the experimental data. We argue that, in the case of Xenopus development, it is wave pinning, rather than Turing-type patterning, that is underlying Nodal-Antivin dynamics. This leads to several experimentally testable predictions, which are discussed. Furthermore, for heterodimer-mediated inhibition to prevent waves of Nodal expression from propagating, the Nodal-Antivin complex must be turned over, and diffusivity of the complex must be negligible. In the absence of molecular mechanisms regulating these, we suggest that Antivin restricts Nodal signals via receptor-mediated, and not heterodimer-mediated, inhibition. PMID:23070212

  8. Transfer functions for protein signal transduction: application to a model of striatal neural plasticity.

    PubMed

    Scheler, Gabriele

    2013-01-01

    We present a novel formulation for biochemical reaction networks in the context of protein signal transduction. The model consists of input-output transfer functions, which are derived from differential equations, using stable equilibria. We select a set of "source" species, which are interpreted as input signals. Signals are transmitted to all other species in the system (the "target" species) with a specific delay and with a specific transmission strength. The delay is computed as the maximal reaction time until a stable equilibrium for the target species is reached, in the context of all other reactions in the system. The transmission strength is the concentration change of the target species. The computed input-output transfer functions can be stored in a matrix, fitted with parameters, and even recalled to build dynamical models on the basis of state changes. By separating the temporal and the magnitudinal domain we can greatly simplify the computational model, circumventing typical problems of complex dynamical systems. The transfer function transformation of biochemical reaction systems can be applied to mass-action kinetic models of signal transduction. The paper shows that this approach yields significant novel insights while remaining a fully testable and executable dynamical model for signal transduction. In particular we can deconstruct the complex system into local transfer functions between individual species. As an example, we examine modularity and signal integration using a published model of striatal neural plasticity. The modularizations that emerge correspond to a known biological distinction between calcium-dependent and cAMP-dependent pathways. Remarkably, we found that overall interconnectedness depends on the magnitude of inputs, with higher connectivity at low input concentrations and significant modularization at moderate to high input concentrations. This general result, which directly follows from the properties of individual transfer

  9. Dynamical patterns of calcium signaling in a functional model of neuron–astrocyte networks

    PubMed Central

    Koreshkov, R. N.; Brazhe, N. A.; Brazhe, A. R.; Sosnovtseva, O. V.

    2009-01-01

    We propose a functional mathematical model for neuron-astrocyte networks. The model incorporates elements of the tripartite synapse and the spatial branching structure of coupled astrocytes. We consider glutamate-induced calcium signaling as a specific mode of excitability and transmission in astrocytic–neuronal networks. We reproduce local and global dynamical patterns observed experimentally. PMID:19669421

  10. Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible un...

  11. Finite Element Modeling of Magnetic Flux Leakage Signals from Mechanical Damage Containing Corrosion Pits

    NASA Astrophysics Data System (ADS)

    Babbar, Vijay; Clapham, Lynann

    2009-03-01

    Steel pipeline defects such as mechanical damage (dents) and corrosion pits have been studied using the magnetic flux leakage (MFL) technique and finite element modeling (FEM). The nature of MFL signals from these defects is generally known. However, since a dented region is more susceptible to corrosion, a dent-pit defect combination may be formed, which adds complexity to signal interpretation. The present work employs FEM to investigate the change in dent signal in the presence of a pit of varying dimensions. It helps to infer if a pit located inside a dent is detectable.

  12. Modeling Signal Transduction Networks: A comparison of two Stochastic Kinetic Simulation Algorithms

    SciTech Connect

    Pettigrew, Michel F.; Resat, Haluk

    2005-09-15

    Simulations of a scalable four compartment reaction model based on the well known epidermal growth factor receptor (EGFR) signal transduction system are used to compare two stochastic algorithms ? StochSim and the Gibson-Gillespie. It is concluded that the Gibson-Gillespie is the algorithm of choice for most realistic cases with the possible exception of signal transduction networks characterized by a moderate number (< 100) of complex types, each with a very small population, but with a high degree of connectivity amongst the complex types. Keywords: Signal transduction networks, Stochastic simulation, StochSim, Gillespie

  13. Construction and Experimental Validation of a Petri Net Model of Wnt/β-Catenin Signaling.

    PubMed

    Jacobsen, Annika; Heijmans, Nika; Verkaar, Folkert; Smit, Martine J; Heringa, Jaap; van Amerongen, Renée; Feenstra, K Anton

    2016-01-01

    The Wnt/β-catenin signaling pathway is important for multiple developmental processes and tissue maintenance in adults. Consequently, deregulated signaling is involved in a range of human diseases including cancer and developmental defects. A better understanding of the intricate regulatory mechanism and effect of physiological (active) and pathophysiological (hyperactive) WNT signaling is important for predicting treatment response and developing novel therapies. The constitutively expressed CTNNB1 (commonly and hereafter referred to as β-catenin) is degraded by a destruction complex, composed of amongst others AXIN1 and GSK3. The destruction complex is inhibited during active WNT signaling, leading to β-catenin stabilization and induction of β-catenin/TCF target genes. In this study we investigated the mechanism and effect of β-catenin stabilization during active and hyperactive WNT signaling in a combined in silico and in vitro approach. We constructed a Petri net model of Wnt/β-catenin signaling including main players from the plasma membrane (WNT ligands and receptors), cytoplasmic effectors and the downstream negative feedback target gene AXIN2. We validated that our model can be used to simulate both active (WNT stimulation) and hyperactive (GSK3 inhibition) signaling by comparing our simulation and experimental data. We used this experimentally validated model to get further insights into the effect of the negative feedback regulator AXIN2 upon WNT stimulation and observed an attenuated β-catenin stabilization. We furthermore simulated the effect of APC inactivating mutations, yielding a stabilization of β-catenin levels comparable to the Wnt-pathway activities observed in colorectal and breast cancer. Our model can be used for further investigation and viable predictions of the role of Wnt/β-catenin signaling in oncogenesis and development. PMID:27218469

  14. Construction and Experimental Validation of a Petri Net Model of Wnt/β-Catenin Signaling

    PubMed Central

    Heijmans, Nika; Verkaar, Folkert; Smit, Martine J.; Heringa, Jaap

    2016-01-01

    The Wnt/β-catenin signaling pathway is important for multiple developmental processes and tissue maintenance in adults. Consequently, deregulated signaling is involved in a range of human diseases including cancer and developmental defects. A better understanding of the intricate regulatory mechanism and effect of physiological (active) and pathophysiological (hyperactive) WNT signaling is important for predicting treatment response and developing novel therapies. The constitutively expressed CTNNB1 (commonly and hereafter referred to as β-catenin) is degraded by a destruction complex, composed of amongst others AXIN1 and GSK3. The destruction complex is inhibited during active WNT signaling, leading to β-catenin stabilization and induction of β-catenin/TCF target genes. In this study we investigated the mechanism and effect of β-catenin stabilization during active and hyperactive WNT signaling in a combined in silico and in vitro approach. We constructed a Petri net model of Wnt/β-catenin signaling including main players from the plasma membrane (WNT ligands and receptors), cytoplasmic effectors and the downstream negative feedback target gene AXIN2. We validated that our model can be used to simulate both active (WNT stimulation) and hyperactive (GSK3 inhibition) signaling by comparing our simulation and experimental data. We used this experimentally validated model to get further insights into the effect of the negative feedback regulator AXIN2 upon WNT stimulation and observed an attenuated β-catenin stabilization. We furthermore simulated the effect of APC inactivating mutations, yielding a stabilization of β-catenin levels comparable to the Wnt-pathway activities observed in colorectal and breast cancer. Our model can be used for further investigation and viable predictions of the role of Wnt/β-catenin signaling in oncogenesis and development. PMID:27218469

  15. An approach for optimally extending mathematical models of signaling networks using omics data.

    PubMed

    Bianconi, Fortunato; Patiti, Federico; Baldelli, Elisa; Crino, Lucio; Valigi, Paolo

    2015-01-01

    Mathematical modeling is a key process in Systems Biology and the use of computational tools such as Cytoscape for omics data processing, need to be integrated in the modeling activity. In this paper we propose a new methodology for modeling signaling networks by combining ordinary differential equation models and a gene recommender system, GeneMANIA. We started from existing models, that are stored in the BioModels database, and we generated a query to use as input for the GeneMANIA algorithm. The output of the recommender system was then led back to the kinetic reactions that were finally added to the starting model. We applied the proposed methodology to EGFR-IGF1R signal transduction network, which plays an important role in translational oncology and cancer therapy of non small cell lung cancer.

  16. Data-Derived Modeling Characterizes Plasticity of MAPK Signaling in Melanoma

    PubMed Central

    Bernardo-Faura, Marti; Massen, Stefan; Falk, Christine S.; Brady, Nathan R.; Eils, Roland

    2014-01-01

    The majority of melanomas have been shown to harbor somatic mutations in the RAS-RAF-MEK-MAPK and PI3K-AKT pathways, which play a major role in regulation of proliferation and survival. The prevalence of these mutations makes these kinase signal transduction pathways an attractive target for cancer therapy. However, tumors have generally shown adaptive resistance to treatment. This adaptation is achieved in melanoma through its ability to undergo neovascularization, migration and rearrangement of signaling pathways. To understand the dynamic, nonlinear behavior of signaling pathways in cancer, several computational modeling approaches have been suggested. Most of those models require that the pathway topology remains constant over the entire observation period. However, changes in topology might underlie adaptive behavior to drug treatment. To study signaling rearrangements, here we present a new approach based on Fuzzy Logic (FL) that predicts changes in network architecture over time. This adaptive modeling approach was used to investigate pathway dynamics in a newly acquired experimental dataset describing total and phosphorylated protein signaling over four days in A375 melanoma cell line exposed to different kinase inhibitors. First, a generalized strategy was established to implement a parameter-reduced FL model encoding non-linear activity of a signaling network in response to perturbation. Next, a literature-based topology was generated and parameters of the FL model were derived from the full experimental dataset. Subsequently, the temporal evolution of model performance was evaluated by leaving time-defined data points out of training. Emerging discrepancies between model predictions and experimental data at specific time points allowed the characterization of potential network rearrangement. We demonstrate that this adaptive FL modeling approach helps to enhance our mechanistic understanding of the molecular plasticity of melanoma. PMID:25188314

  17. Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise

    PubMed Central

    Brown, Patrick T.; Li, Wenhong; Cordero, Eugene C.; Mauget, Steven A.

    2015-01-01

    The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal. PMID:25898351

  18. Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

    PubMed

    Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G

    2012-01-01

    Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

  19. A dual receptor crosstalk model of G-protein-coupled signal transduction.

    PubMed

    Flaherty, Patrick; Radhakrishnan, Mala L; Dinh, Tuan; Rebres, Robert A; Roach, Tamara I; Jordan, Michael I; Arkin, Adam P

    2008-09-26

    Macrophage cells that are stimulated by two different ligands that bind to G-protein-coupled receptors (GPCRs) usually respond as if the stimulus effects are additive, but for a minority of ligand combinations the response is synergistic. The G-protein-coupled receptor system integrates signaling cues from the environment to actuate cell morphology, gene expression, ion homeostasis, and other physiological states. We analyze the effects of the two signaling molecules complement factors 5a (C5a) and uridine diphosphate (UDP) on the intracellular second messenger calcium to elucidate the principles that govern the processing of multiple signals by GPCRs. We have developed a formal hypothesis, in the form of a kinetic model, for the mechanism of action of this GPCR signal transduction system using data obtained from RAW264.7 macrophage cells. Bayesian statistical methods are employed to represent uncertainty in both data and model parameters and formally tie the model to experimental data. When the model is also used as a tool in the design of experiments, it predicts a synergistic region in the calcium peak height dose response that results when cells are simultaneously stimulated by C5a and UDP. An analysis of the model reveals a potential mechanism for crosstalk between the Galphai-coupled C5a receptor and the Galphaq-coupled UDP receptor signaling systems that results in synergistic calcium release.

  20. Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.

    PubMed

    Brown, Patrick T; Li, Wenhong; Cordero, Eugene C; Mauget, Steven A

    2015-04-21

    The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.

  1. An empirical Bayesian approach for model-based inference of cellular signaling networks

    PubMed Central

    2009-01-01

    Background A common challenge in systems biology is to infer mechanistic descriptions of biological process given limited observations of a biological system. Mathematical models are frequently used to represent a belief about the causal relationships among proteins within a signaling network. Bayesian methods provide an attractive framework for inferring the validity of those beliefs in the context of the available data. However, efficient sampling of high-dimensional parameter space and appropriate convergence criteria provide barriers for implementing an empirical Bayesian approach. The objective of this study was to apply an Adaptive Markov chain Monte Carlo technique to a typical study of cellular signaling pathways. Results As an illustrative example, a kinetic model for the early signaling events associated with the epidermal growth factor (EGF) signaling network was calibrated against dynamic measurements observed in primary rat hepatocytes. A convergence criterion, based upon the Gelman-Rubin potential scale reduction factor, was applied to the model predictions. The posterior distributions of the parameters exhibited complicated structure, including significant covariance between specific parameters and a broad range of variance among the parameters. The model predictions, in contrast, were narrowly distributed and were used to identify areas of agreement among a collection of experimental studies. Conclusion In summary, an empirical Bayesian approach was developed for inferring the confidence that one can place in a particular model that describes signal transduction mechanisms and for inferring inconsistencies in experimental measurements. PMID:19900289

  2. Using signals associated with safety in avoidance learning: computational model of sex differences

    PubMed Central

    Beck, Kevin D.; Pang, Kevin C.H.; Myers, Catherine E.

    2015-01-01

    Avoidance behavior involves learning responses that prevent upcoming aversive events; these responses typically extinguish when the aversive events stop materializing. Stimuli that signal safety from aversive events can paradoxically inhibit extinction of avoidance behavior. In animals, males and females process safety signals differently. These differences help explain why women are more likely to be diagnosed with an anxiety disorder and exhibit differences in symptom presentation and course compared to men. In the current study, we extend an existing model of strain differences in avoidance behavior to simulate sex differences in rats. The model successfully replicates data showing that the omission of a signal associated with a period of safety can facilitate extinction in females, but not males, and makes novel predictions that this effect should depend on the duration of the period, the duration of the signal itself, and its occurrence within that period. Non-reinforced responses during the safe period were also found to be important in the expression of these patterns. The model also allowed us to explore underlying mechanisms for the observed sex effects, such as whether safety signals serve as occasion setters for aversive events, to determine why removing them can facilitate extinction of avoidance. The simulation results argue against this account, and instead suggest the signal may serve as a conditioned reinforcer of avoidance behavior. PMID:26213650

  3. Identifying Ensembles of Signal Transduction Models using Pareto Optimal Ensemble Techniques (POETs)

    PubMed Central

    Song, Sang Ok; Chakrabarti, Anirikh; Varner, Jeffrey D.

    2010-01-01

    Mathematical modeling of complex gene expression programs is an emerging tool for understanding disease mechanisms. However, identification of large models sometimes requires training using qualitative, conflicting or even contradictory data sets. One strategy to address this challenge is to estimate experimentally constrained model ensembles using multiobjective optimization. In this study, we used Pareto Optimal Ensemble Techniques (POETs) to identify a family of proof-of-concept signal transduction models. POETs integrate Simulated Annealing (SA) with Pareto optimality to identify models near the optimal tradeoff surface between competing training objectives. We modeled a prototypical-signaling network using mass action kinetics within an ordinary differential equation (ODE) framework (64-ODEs in total). The true model was used to generate synthetic immunoblots from which the POET algorithm identified the 117 unknown model parameters. POET generated an ensemble of signaling models, which collectively exhibited population-like behavior. For example, scaled gene expression levels were approximately normally distributed over the ensemble following the addition of extracellular ligand. Also, the ensemble recovered robust and fragile features of the true model, despite significant parameter uncertainty. Taken together, these results suggest that experimentally constrained model ensembles could capture qualitatively important network features without exact parameter information. PMID:20665647

  4. Ensembles of signal transduction models using Pareto Optimal Ensemble Techniques (POETs).

    PubMed

    Song, Sang Ok; Chakrabarti, Anirikh; Varner, Jeffrey D

    2010-07-01

    Mathematical modeling of complex gene expression programs is an emerging tool for understanding disease mechanisms. However, identification of large models sometimes requires training using qualitative, conflicting or even contradictory data sets. One strategy to address this challenge is to estimate experimentally constrained model ensembles using multiobjective optimization. In this study, we used Pareto Optimal Ensemble Techniques (POETs) to identify a family of proof-of-concept signal transduction models. POETs integrate Simulated Annealing (SA) with Pareto optimality to identify models near the optimal tradeoff surface between competing training objectives. We modeled a prototypical-signaling network using mass-action kinetics within an ordinary differential equation (ODE) framework (64 ODEs in total). The true model was used to generate synthetic immunoblots from which the POET algorithm identified the 117 unknown model parameters. POET generated an ensemble of signaling models, which collectively exhibited population-like behavior. For example, scaled gene expression levels were approximately normally distributed over the ensemble following the addition of extracellular ligand. Also, the ensemble recovered robust and fragile features of the true model, despite significant parameter uncertainty. Taken together, these results suggest that experimentally constrained model ensembles could capture qualitatively important network features without exact parameter information.

  5. Probability image of tissue characteristics for liver fibrosis using multi-Rayleigh model with removal of nonspeckle signals

    NASA Astrophysics Data System (ADS)

    Mori, Shohei; Hirata, Shinnosuke; Yamaguchi, Tadashi; Hachiya, Hiroyuki

    2015-07-01

    We have been developing a quantitative diagnostic method for liver fibrosis using an ultrasound image. In our previous study, we proposed a multi-Rayleigh model to express a probability density function of the echo amplitude from liver fibrosis and proposed a probability imaging method of tissue characteristics on the basis of the multi-Rayleigh model. In an evaluation using the multi-Rayleigh model, we found that a modeling error of the multi-Rayleigh model was increased by the effect of nonspeckle signals. In this paper, we proposed a method of removing nonspeckle signals using the modeling error of the multi-Rayleigh model and evaluated the probability image of tissue characteristics after removing the nonspeckle signals. By removing nonspeckle signals, the modeling error of the multi-Rayleigh model was decreased. A correct probability image of tissue characteristics was obtained by removing nonspeckle signals. We concluded that the removal of nonspeckle signals is important for evaluating liver fibrosis quantitatively.

  6. Performance comparison of rigid and affine models for motion estimation using ultrasound radio-frequency signals.

    PubMed

    Pan, Xiaochang; Liu, Ke; Shao, Jinghua; Gao, Jing; Huang, Lingyun; Bai, Jing; Luo, Jianwen

    2015-11-01

    Tissue motion estimation is widely used in many ultrasound techniques. Rigid-model-based and nonrigid-modelbased methods are two main groups of space-domain methods of tissue motion estimation. The affine model is one of the commonly used nonrigid models. The performances of the rigid model and affine model have not been compared on ultrasound RF signals, which have been demonstrated to obtain higher accuracy, precision, and resolution in motion estimation compared with B-mode images. In this study, three methods, i.e., the normalized cross-correlation method with rigid model (NCC), the optical flow method with rigid model (OFRM), and the optical flow method with affine model (OFAM), are compared using ultrasound RF signals, rather than the B-mode images used in previous studies. Simulations, phantom, and in vivo experiments are conducted to make the comparison. In the simulations, the root-mean-square errors (RMSEs) of axial and lateral displacements and strains are used to assess the accuracy of motion estimation, and the elastographic signal-tonoise ratio (SNRe) and contrast-to-noise ratio (CNRe) are used to evaluate the quality of axial strain images. In the phantom experiments, the registration error between the pre- and postdeformation RF signals, as well as the SNRe and CNRe of axial strain images, are utilized as the evaluation criteria. In the in vivo experiments, the registration error is used to evaluate the estimation performance. The results show that the affinemodel- based method (i.e., OFAM) obtains the lowest RMSE or registration error and the highest SNRe and CNRe among all the methods. The affine model is demonstrated to be superior to the rigid model in motion estimation based on RF signals.

  7. A fault diagnosis methodology for rolling element bearings based on advanced signal pretreatment and autoregressive modelling

    NASA Astrophysics Data System (ADS)

    Al-Bugharbee, Hussein; Trendafilova, Irina

    2016-05-01

    This study proposes a methodology for rolling element bearings fault diagnosis which gives a complete and highly accurate identification of the faults present. It has two main stages: signals pretreatment, which is based on several signal analysis procedures, and diagnosis, which uses a pattern-recognition process. The first stage is principally based on linear time invariant autoregressive modelling. One of the main contributions of this investigation is the development of a pretreatment signal analysis procedure which subjects the signal to noise cleaning by singular spectrum analysis and then stationarisation by differencing. So the signal is transformed to bring it close to a stationary one, rather than complicating the model to bring it closer to the signal. This type of pretreatment allows the use of a linear time invariant autoregressive model and improves its performance when the original signals are non-stationary. This contribution is at the heart of the proposed method, and the high accuracy of the diagnosis is a result of this procedure. The methodology emphasises the importance of preliminary noise cleaning and stationarisation. And it demonstrates that the information needed for fault identification is contained in the stationary part of the measured signal. The methodology is further validated using three different experimental setups, demonstrating very high accuracy for all of the applications. It is able to correctly classify nearly 100 percent of the faults with regard to their type and size. This high accuracy is the other important contribution of this methodology. Thus, this research suggests a highly accurate methodology for rolling element bearing fault diagnosis which is based on relatively simple procedures. This is also an advantage, as the simplicity of the individual processes ensures easy application and the possibility for automation of the entire process.

  8. Small-signal model parameter extraction for AlGaN/GaN HEMT

    NASA Astrophysics Data System (ADS)

    Le, Yu; Yingkui, Zheng; Sheng, Zhang; Lei, Pang; Ke, Wei; Xiaohua, Ma

    2016-03-01

    A new 22-element small signal equivalent circuit model for the AlGaN/GaN high electron mobility transistor (HEMT) is presented. Compared with the traditional equivalent circuit model, the gate forward and breakdown conductions (G gsf and G gdf) are introduced into the new model to characterize the gate leakage current. Additionally, for the new gate-connected field plate and the source-connected field plate of the device, an improved method for extracting the parasitic capacitances is proposed, which can be applied to the small-signal extraction for an asymmetric device. To verify the model, S-parameters are obtained from the modeling and measurements. The good agreement between the measured and the simulated results indicate that this model is accurate, stable and comparatively clear in physical significance.

  9. An improved temperature-dependent large signal model of microwave GaN HEMTs

    NASA Astrophysics Data System (ADS)

    Changsi, Wang; Yuehang, Xu; Zhang, Wen; Zhikai, Chen; Ruimin, Xu

    2016-07-01

    Accurate modeling of the electrothermal effects of GaN electronic devices is critical for reliability design and assessment. In this paper, an improved temperature-dependent model for large signal equivalent circuit modeling of GaN HEMTs is proposed. To accurately describe the thermal effects, a modified nonlinear thermal sub-circuit which is related not only to power dissipation, but also ambient temperature is used to calculate the variations of channel temperature of the device; the temperature-dependent parasitic and intrinsic elements are also taken into account in this model. The parameters of the thermal sub-circuit are extracted by using the numerical finite element method. The results show that better performance can be achieved by using the proposed large signal model in the range of ‑55 to 125 °C compared with the conventional model with a linear thermal sub-circuit. Project supported by the National Natural Science Foundation of China (No. 61106115).

  10. An improved temperature-dependent large signal model of microwave GaN HEMTs

    NASA Astrophysics Data System (ADS)

    Changsi, Wang; Yuehang, Xu; Zhang, Wen; Zhikai, Chen; Ruimin, Xu

    2016-07-01

    Accurate modeling of the electrothermal effects of GaN electronic devices is critical for reliability design and assessment. In this paper, an improved temperature-dependent model for large signal equivalent circuit modeling of GaN HEMTs is proposed. To accurately describe the thermal effects, a modified nonlinear thermal sub-circuit which is related not only to power dissipation, but also ambient temperature is used to calculate the variations of channel temperature of the device; the temperature-dependent parasitic and intrinsic elements are also taken into account in this model. The parameters of the thermal sub-circuit are extracted by using the numerical finite element method. The results show that better performance can be achieved by using the proposed large signal model in the range of -55 to 125 °C compared with the conventional model with a linear thermal sub-circuit. Project supported by the National Natural Science Foundation of China (No. 61106115).

  11. Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model

    PubMed Central

    Boulton, Chris A.; Allison, Lesley C.; Lenton, Timothy M.

    2014-01-01

    The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached. PMID:25482065

  12. Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model.

    PubMed

    Boulton, Chris A; Allison, Lesley C; Lenton, Timothy M

    2014-01-01

    The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached. PMID:25482065

  13. A decision model applied to alcohol effects on driver signal light behavior

    NASA Technical Reports Server (NTRS)

    Schwartz, S. H.; Allen, R. W.

    1978-01-01

    A decision model including perceptual noise or inconsistency is developed from expected value theory to explain driver stop and go decisions at signaled intersections. The model is applied to behavior in a car simulation and instrumented vehicle. Objective and subjective changes in driver decision making were measured with changes in blood alcohol concentration (BAC). Treatment levels averaged 0.00, 0.10 and 0.14 BAC for a total of 26 male subjects. Data were taken for drivers approaching signal lights at three timing configurations. The correlation between model predictions and behavior was highly significant. In contrast to previous research, analysis indicates that increased BAC results in increased perceptual inconsistency, which is the primary cause of increased risk taking at low probability of success signal lights.

  14. Multiple Model-Informed Open-Loop Control of Uncertain Intracellular Signaling Dynamics

    PubMed Central

    Perley, Jeffrey P.; Mikolajczak, Judith; Harrison, Marietta L.; Buzzard, Gregery T.; Rundell, Ann E.

    2014-01-01

    Computational approaches to tune the activation of intracellular signal transduction pathways both predictably and selectively will enable researchers to explore and interrogate cell biology with unprecedented precision. Techniques to control complex nonlinear systems typically involve the application of control theory to a descriptive mathematical model. For cellular processes, however, measurement assays tend to be too time consuming for real-time feedback control and models offer rough approximations of the biological reality, thus limiting their utility when considered in isolation. We overcome these problems by combining nonlinear model predictive control with a novel adaptive weighting algorithm that blends predictions from multiple models to derive a compromise open-loop control sequence. The proposed strategy uses weight maps to inform the controller of the tendency for models to differ in their ability to accurately reproduce the system dynamics under different experimental perturbations (i.e. control inputs). These maps, which characterize the changing model likelihoods over the admissible control input space, are constructed using preexisting experimental data and used to produce a model-based open-loop control framework. In effect, the proposed method designs a sequence of control inputs that force the signaling dynamics along a predefined temporal response without measurement feedback while mitigating the effects of model uncertainty. We demonstrate this technique on the well-known Erk/MAPK signaling pathway in T cells. In silico assessment demonstrates that this approach successfully reduces target tracking error by 52% or better when compared with single model-based controllers and non-adaptive multiple model-based controllers. In vitro implementation of the proposed approach in Jurkat cells confirms a 63% reduction in tracking error when compared with the best of the single-model controllers. This study provides an experimentally

  15. Multiple model-informed open-loop control of uncertain intracellular signaling dynamics.

    PubMed

    Perley, Jeffrey P; Mikolajczak, Judith; Harrison, Marietta L; Buzzard, Gregery T; Rundell, Ann E

    2014-04-01

    Computational approaches to tune the activation of intracellular signal transduction pathways both predictably and selectively will enable researchers to explore and interrogate cell biology with unprecedented precision. Techniques to control complex nonlinear systems typically involve the application of control theory to a descriptive mathematical model. For cellular processes, however, measurement assays tend to be too time consuming for real-time feedback control and models offer rough approximations of the biological reality, thus limiting their utility when considered in isolation. We overcome these problems by combining nonlinear model predictive control with a novel adaptive weighting algorithm that blends predictions from multiple models to derive a compromise open-loop control sequence. The proposed strategy uses weight maps to inform the controller of the tendency for models to differ in their ability to accurately reproduce the system dynamics under different experimental perturbations (i.e. control inputs). These maps, which characterize the changing model likelihoods over the admissible control input space, are constructed using preexisting experimental data and used to produce a model-based open-loop control framework. In effect, the proposed method designs a sequence of control inputs that force the signaling dynamics along a predefined temporal response without measurement feedback while mitigating the effects of model uncertainty. We demonstrate this technique on the well-known Erk/MAPK signaling pathway in T cells. In silico assessment demonstrates that this approach successfully reduces target tracking error by 52% or better when compared with single model-based controllers and non-adaptive multiple model-based controllers. In vitro implementation of the proposed approach in Jurkat cells confirms a 63% reduction in tracking error when compared with the best of the single-model controllers. This study provides an experimentally

  16. A Model for Carrier-Mediated Biological Signal Transduction Based on Equilibrium Ligand Binding Theory.

    PubMed

    Martini, Johannes W R; Schlather, Martin; Schütz, Stefan

    2016-05-01

    Different variants of a mathematical model for carrier-mediated signal transduction are introduced with focus on the odor dose-electrophysiological response curve of insect olfaction. The latter offers a unique opportunity to observe experimentally the effect of an alteration in the carrier molecule composition on the signal molecule-dependent response curve. Our work highlights the role of involved carrier molecules, which have largely been ignored in mathematical models for response curves in the past. The resulting model explains how the involvement of more than one carrier molecule in signal molecule transport can cause dose-response curves as observed in experiments, without the need of more than one receptor per neuron. In particular, the model has the following features: (1) An extended sensitivity range of neuronal response is implemented by a system consisting of only one receptor but several carrier molecules with different affinities for the signal molecule. (2) Given that the sensitivity range is extended by the involvement of different carrier molecules, the model implies that a strong difference in the expression levels of the carrier molecules is absolutely essential for wide range responses. (3) Complex changes in dose-response curves which can be observed when the expression levels of carrier molecules are altered experimentally can be explained by interactions between different carrier molecules. The principles we demonstrate here for electrophysiological responses can also be applied to any other carrier-mediated biological signal transduction process. The presented concept provides a framework for modeling and statistical analysis of signal transduction processes if sufficient information on the underlying biology is available.

  17. A hardware model of the auditory periphery to transduce acoustic signals into neural activity

    PubMed Central

    Tateno, Takashi; Nishikawa, Jun; Tsuchioka, Nobuyoshi; Shintaku, Hirofumi; Kawano, Satoyuki

    2013-01-01

    To improve the performance of cochlear implants, we have integrated a microdevice into a model of the auditory periphery with the goal of creating a microprocessor. We constructed an artificial peripheral auditory system using a hybrid model in which polyvinylidene difluoride was used as a piezoelectric sensor to convert mechanical stimuli into electric signals. To produce frequency selectivity, the slit on a stainless steel base plate was designed such that the local resonance frequency of the membrane over the slit reflected the transfer function. In the acoustic sensor, electric signals were generated based on the piezoelectric effect from local stress in the membrane. The electrodes on the resonating plate produced relatively large electric output signals. The signals were fed into a computer model that mimicked some functions of inner hair cells, inner hair cell–auditory nerve synapses, and auditory nerve fibers. In general, the responses of the model to pure-tone burst and complex stimuli accurately represented the discharge rates of high-spontaneous-rate auditory nerve fibers across a range of frequencies greater than 1 kHz and middle to high sound pressure levels. Thus, the model provides a tool to understand information processing in the peripheral auditory system and a basic design for connecting artificial acoustic sensors to the peripheral auditory nervous system. Finally, we discuss the need for stimulus control with an appropriate model of the auditory periphery based on auditory brainstem responses that were electrically evoked by different temporal pulse patterns with the same pulse number. PMID:24324432

  18. A hardware model of the auditory periphery to transduce acoustic signals into neural activity.

    PubMed

    Tateno, Takashi; Nishikawa, Jun; Tsuchioka, Nobuyoshi; Shintaku, Hirofumi; Kawano, Satoyuki

    2013-01-01

    To improve the performance of cochlear implants, we have integrated a microdevice into a model of the auditory periphery with the goal of creating a microprocessor. We constructed an artificial peripheral auditory system using a hybrid model in which polyvinylidene difluoride was used as a piezoelectric sensor to convert mechanical stimuli into electric signals. To produce frequency selectivity, the slit on a stainless steel base plate was designed such that the local resonance frequency of the membrane over the slit reflected the transfer function. In the acoustic sensor, electric signals were generated based on the piezoelectric effect from local stress in the membrane. The electrodes on the resonating plate produced relatively large electric output signals. The signals were fed into a computer model that mimicked some functions of inner hair cells, inner hair cell-auditory nerve synapses, and auditory nerve fibers. In general, the responses of the model to pure-tone burst and complex stimuli accurately represented the discharge rates of high-spontaneous-rate auditory nerve fibers across a range of frequencies greater than 1 kHz and middle to high sound pressure levels. Thus, the model provides a tool to understand information processing in the peripheral auditory system and a basic design for connecting artificial acoustic sensors to the peripheral auditory nervous system. Finally, we discuss the need for stimulus control with an appropriate model of the auditory periphery based on auditory brainstem responses that were electrically evoked by different temporal pulse patterns with the same pulse number. PMID:24324432

  19. Modeling the relationship between Higuchi's fractal dimension and Fourier spectra of physiological signals.

    PubMed

    Kalauzi, Aleksandar; Bojić, Tijana; Vuckovic, Aleksandra

    2012-07-01

    The exact mathematical relationship between FFT spectrum and fractal dimension (FD) of an experimentally recorded signal is not known. In this work, we tried to calculate signal FD directly from its Fourier amplitudes. First, dependence of Higuchi's FD of mathematical sinusoids on their individual frequencies was modeled with a two-parameter exponential function. Next, FD of a finite sum of sinusoids was found to be a weighted average of their FDs, weighting factors being their Fourier amplitudes raised to a fractal degree. Exponent dependence on frequency was modeled with exponential, power and logarithmic functions. A set of 280 EEG signals and Weierstrass functions were analyzed. Cross-validation was done within EEG signals and between them and Weierstrass functions. Exponential dependence of fractal exponents on frequency was found to be the most accurate. In this work, signal FD was for the first time expressed as a fractal weighted average of FD values of its Fourier components, also allowing researchers to perform direct estimation of signal fractal dimension from its FFT spectrum.

  20. Improved signal model for confocal sensors accounting for object depending artifacts.

    PubMed

    Mauch, Florian; Lyda, Wolfram; Gronle, Marc; Osten, Wolfgang

    2012-08-27

    The conventional signal model of confocal sensors is well established and has proven to be exceptionally robust especially when measuring rough surfaces. Its physical derivation however is explicitly based on plane surfaces or point like objects, respectively. Here we show experimental results of a confocal point sensor measurement of a surface standard. The results illustrate the rise of severe artifacts when measuring curved surfaces. On this basis, we present a systematic extension of the conventional signal model that is proven to be capable of qualitatively explaining these artifacts.

  1. Time-domain model of quantum-dot semiconductor optical amplifiers for wideband optical signals.

    PubMed

    Puris, D; Schmidt-Langhorst, C; Lüdge, K; Majer, N; Schöll, E; Petermann, K

    2012-11-19

    We present a novel theoretical time-domain model for a quantum dot semiconductor optical amplifier, that allows to simulate subpicosecond pulse propagation including power-based and phase-based effects. Static results including amplified spontaneous emission spectra, continuous wave amplification, and four-wave mixing experiments in addition to dynamic pump-probe simulations are presented for different injection currents. The model uses digital filters to describe the frequency dependent gain and microscopically calculated carrier-carrier scattering rates for the interband carrier dynamics. It can be used to calculate the propagation of multiple signals with different wavelengths or one wideband signal with high bitrate.

  2. Investigating dynamics of inhibitory and feedback loops in ERK signalling using power-law models.

    PubMed

    Vera, Julio; Rath, Oliver; Balsa-Canto, Eva; Banga, Julio R; Kolch, Walter; Wolkenhauer, Olaf

    2010-11-01

    The investigation of the structure and dynamics of signal transduction systems through data-based mathematical models in ordinary differential equations or other paradigms has proven to be a successful approach in recent times. Extending this concept, we here analysed the use of kinetic models based on power-law terms with non-integer kinetic orders in the validation of hypotheses concerning regulatory structures in signalling systems. We integrated pre-existent biological knowledge, hypotheses and experimental quantitative data into a power-law model to validate the existence of certain regulatory loops in the Ras/Raf-1/MEK/ERK pathway, a MAPK pathway involved in the transduction of mitogenic and differentiation signals. Towards this end, samples of a human mammary epithelial cell line (MCF-10A) were used to obtain time-series data, characterising the behaviour of the system after epidermal growth factor stimulation in different scenarios of expression for the critical players of the system regarding the investigated loops (e.g., the inhibitory protein RKIP). The mathematical model was calibrated using a computational procedure that included: analysis of structural identifiability, global ranking of parameters to detect the most sensitivity ones towards the experimental setup, model calibration using global optimization methods to find the parameter values that better fit the data, and practical identifiability analysis to estimate the confidence in the estimated values for the parameters. The obtained model was used to perform computational simulations concerning the role of the investigated regulatory loops in the time response of the signalling pathway. Our findings suggest that the special regularity in the structure of the power-law terms make them suitable for a data-based validation of regulatory loops in signalling pathways. The model-based analysis performed identified RKIP as an actual inhibitor of the activation of the ERK pathway, but also suggested

  3. Synaptic signal transduction aided by noise in a dynamical saturating model

    NASA Astrophysics Data System (ADS)

    Chapeau-Blondeau, François; Duan, Fabing; Abbott, Derek

    2010-02-01

    A generic dynamical model with saturation for neural signal transduction at the synaptic stage is presented. Analysis of this model of a synaptic pathway demonstrates its ability to give rise to stochastic resonance or improvement by noise, at this stage of signal transmission. Beyond the case of the intrinsic threshold nonlinearity of the neuron response, the results extend the feasibility of stochastic resonance to neural saturating dynamics at the synaptic stage. The present results also constitute the exposition of a new type of nonlinear (saturating) dynamics capable of stochastic resonance.

  4. The Clickable Guard Cell, Version II: Interactive Model of Guard Cell Signal Transduction Mechanisms and Pathways.

    PubMed

    Kwak, June M; Mäser, Pascal; Schroeder, Julian I

    2008-01-01

    Guard cells are located in the leaf epidermis and pairs of guard cells surround and form stomatal pores, which regulate CO(2) influx from the atmosphere into leaves for photosynthetic carbon fixation. Stomatal guard cells also regulate water loss of plants via transpiration to the atmosphere. Signal transduction mechanisms in guard cells integrate a multitude of different stimuli to modulate stomatal apertures. Stomata open in response to light. Stomata close in response to drought stress, elevated CO(2), ozone and low humidity. In response to drought, plants synthesize the hormone abscisic acid (ABA) that triggers closing of stomatal pores. Guard cells have become a highly developed model system for dissecting signal transduction mechanisms in plants and for elucidating how individual signaling mechanisms can interact within a network in a single cell. Many new findings have been made in the last few years. This chapter is an update of an electronic interactive chapter in the previous edition of The Arabidopsis Book (Mäser et al. 2003). Here we focus on mechanisms for which genes and mutations have been characterized, including signaling components for which there is substantial signaling, biochemical and genetic evidence. Ion channels have been shown to represent targets of early signal transduction mechanisms and provide functional signaling and quantitative analysis points to determine where and how mutations affect branches within the guard cell signaling network. Although a substantial number of genes and proteins that function in guard cell signaling have been identified in recent years, there are many more left to be identified and the protein-protein interactions within this network will be an important subject of future research. A fully interactive clickable electronic version of this publication can be accessed at the following web site: http://www-biology.ucsd.edu/labs/schroeder/clickablegc2/. The interactive clickable version includes the following

  5. Model cerebellar granule cells can faithfully transmit modulated firing rate signals

    PubMed Central

    Rössert, Christian; Solinas, Sergio; D'Angelo, Egidio; Dean, Paul; Porrill, John

    2014-01-01

    A crucial assumption of many high-level system models of the cerebellum is that information in the granular layer is encoded in a linear manner. However, granule cells are known for their non-linear and resonant synaptic and intrinsic properties that could potentially impede linear signal transmission. In this modeling study we analyse how electrophysiological granule cell properties and spike sampling influence information coded by firing rate modulation, assuming no signal-related, i.e., uncorrelated inhibitory feedback (open-loop mode). A detailed one-compartment granule cell model was excited in simulation by either direct current or mossy-fiber synaptic inputs. Vestibular signals were represented as tonic inputs to the flocculus modulated at frequencies up to 20 Hz (approximate upper frequency limit of vestibular-ocular reflex, VOR). Model outputs were assessed using estimates of both the transfer function, and the fidelity of input-signal reconstruction measured as variance-accounted-for. The detailed granule cell model with realistic mossy-fiber synaptic inputs could transmit information faithfully and linearly in the frequency range of the vestibular-ocular reflex. This was achieved most simply if the model neurons had a firing rate at least twice the highest required frequency of modulation, but lower rates were also adequate provided a population of neurons was utilized, especially in combination with push-pull coding. The exact number of neurons required for faithful transmission depended on the precise values of firing rate and noise. The model neurons were also able to combine excitatory and inhibitory signals linearly, and could be replaced by a simpler (modified) integrate-and-fire neuron in the case of high tonic firing rates. These findings suggest that granule cells can in principle code modulated firing-rate inputs in a linear manner, and are thus consistent with the high-level adaptive-filter model of the cerebellar microcircuit. PMID:25352777

  6. A sparse digital signal model for ultrasonic nondestructive evaluation of layered materials.

    PubMed

    Bochud, N; Gomez, A M; Rus, G; Peinado, A M

    2015-09-01

    Signal modeling has been proven to be an useful tool to characterize damaged materials under ultrasonic nondestructive evaluation (NDE). In this paper, we introduce a novel digital signal model for ultrasonic NDE of multilayered materials. This model borrows concepts from lattice filter theory, and bridges them to the physics involved in the wave-material interactions. In particular, the proposed theoretical framework shows that any multilayered material can be characterized by a transfer function with sparse coefficients. The filter coefficients are linked to the physical properties of the material and are analytically obtained from them, whereas a sparse distribution naturally arises and does not rely on heuristic approaches. The developed model is first validated with experimental measurements obtained from multilayered media consisting of homogeneous solids. Then, the sparse structure of the obtained digital filter is exploited through a model-based inverse problem for damage identification in a carbon fiber-reinforced polymer (CFRP) plate.

  7. Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling.

    PubMed

    D'Alessandro, Lorenza A; Samaga, Regina; Maiwald, Tim; Rho, Seong-Hwan; Bonefas, Sandra; Raue, Andreas; Iwamoto, Nao; Kienast, Alexandra; Waldow, Katharina; Meyer, Rene; Schilling, Marcel; Timmer, Jens; Klamt, Steffen; Klingmüller, Ursula

    2015-04-01

    Signaling pathways are characterized by crosstalk, feedback and feedforward mechanisms giving rise to highly complex and cell-context specific signaling networks. Dissecting the underlying relations is crucial to predict the impact of targeted perturbations. However, a major challenge in identifying cell-context specific signaling networks is the enormous number of potentially possible interactions. Here, we report a novel hybrid mathematical modeling strategy to systematically unravel hepatocyte growth factor (HGF) stimulated phosphoinositide-3-kinase (PI3K) and mitogen activated protein kinase (MAPK) signaling, which critically contribute to liver regeneration. By combining time-resolved quantitative experimental data generated in primary mouse hepatocytes with interaction graph and ordinary differential equation modeling, we identify and experimentally validate a network structure that represents the experimental data best and indicates specific crosstalk mechanisms. Whereas the identified network is robust against single perturbations, combinatorial inhibition strategies are predicted that result in strong reduction of Akt and ERK activation. Thus, by capitalizing on the advantages of the two modeling approaches, we reduce the high combinatorial complexity and identify cell-context specific signaling networks.

  8. Role of FGF/FGFR signaling in skeletal development and homeostasis: learning from mouse models

    PubMed Central

    Su, Nan; Jin, Min; Chen, Lin

    2014-01-01

    Fibroblast growth factor (FGF)/fibroblast growth factor receptor (FGFR) signaling plays essential roles in bone development and diseases. Missense mutations in FGFs and FGFRs in humans can cause various congenital bone diseases, including chondrodysplasia syndromes, craniosynostosis syndromes and syndromes with dysregulated phosphate metabolism. FGF/FGFR signaling is also an important pathway involved in the maintenance of adult bone homeostasis. Multiple kinds of mouse models, mimicking human skeleton diseases caused by missense mutations in FGFs and FGFRs, have been established by knock-in/out and transgenic technologies. These genetically modified mice provide good models for studying the role of FGF/FGFR signaling in skeleton development and homeostasis. In this review, we summarize the mouse models of FGF signaling-related skeleton diseases and recent progresses regarding the molecular mechanisms, underlying the role of FGFs/FGFRs in the regulation of bone development and homeostasis. This review also provides a perspective view on future works to explore the roles of FGF signaling in skeletal development and homeostasis. PMID:26273516

  9. Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling

    PubMed Central

    Rho, Seong-Hwan; Bonefas, Sandra; Raue, Andreas; Iwamoto, Nao; Kienast, Alexandra; Waldow, Katharina; Meyer, Rene; Schilling, Marcel; Timmer, Jens; Klamt, Steffen; Klingmüller, Ursula

    2015-01-01

    Signaling pathways are characterized by crosstalk, feedback and feedforward mechanisms giving rise to highly complex and cell-context specific signaling networks. Dissecting the underlying relations is crucial to predict the impact of targeted perturbations. However, a major challenge in identifying cell-context specific signaling networks is the enormous number of potentially possible interactions. Here, we report a novel hybrid mathematical modeling strategy to systematically unravel hepatocyte growth factor (HGF) stimulated phosphoinositide-3-kinase (PI3K) and mitogen activated protein kinase (MAPK) signaling, which critically contribute to liver regeneration. By combining time-resolved quantitative experimental data generated in primary mouse hepatocytes with interaction graph and ordinary differential equation modeling, we identify and experimentally validate a network structure that represents the experimental data best and indicates specific crosstalk mechanisms. Whereas the identified network is robust against single perturbations, combinatorial inhibition strategies are predicted that result in strong reduction of Akt and ERK activation. Thus, by capitalizing on the advantages of the two modeling approaches, we reduce the high combinatorial complexity and identify cell-context specific signaling networks. PMID:25905717

  10. Disentangling the Complexity of HGF Signaling by Combining Qualitative and Quantitative Modeling.

    PubMed

    D'Alessandro, Lorenza A; Samaga, Regina; Maiwald, Tim; Rho, Seong-Hwan; Bonefas, Sandra; Raue, Andreas; Iwamoto, Nao; Kienast, Alexandra; Waldow, Katharina; Meyer, Rene; Schilling, Marcel; Timmer, Jens; Klamt, Steffen; Klingmüller, Ursula

    2015-04-01

    Signaling pathways are characterized by crosstalk, feedback and feedforward mechanisms giving rise to highly complex and cell-context specific signaling networks. Dissecting the underlying relations is crucial to predict the impact of targeted perturbations. However, a major challenge in identifying cell-context specific signaling networks is the enormous number of potentially possible interactions. Here, we report a novel hybrid mathematical modeling strategy to systematically unravel hepatocyte growth factor (HGF) stimulated phosphoinositide-3-kinase (PI3K) and mitogen activated protein kinase (MAPK) signaling, which critically contribute to liver regeneration. By combining time-resolved quantitative experimental data generated in primary mouse hepatocytes with interaction graph and ordinary differential equation modeling, we identify and experimentally validate a network structure that represents the experimental data best and indicates specific crosstalk mechanisms. Whereas the identified network is robust against single perturbations, combinatorial inhibition strategies are predicted that result in strong reduction of Akt and ERK activation. Thus, by capitalizing on the advantages of the two modeling approaches, we reduce the high combinatorial complexity and identify cell-context specific signaling networks. PMID:25905717

  11. An Agent-Based Model of Signal Transduction in Bacterial Chemotaxis

    PubMed Central

    Miller, Jameson; Parker, Miles; Bourret, Robert B.; Giddings, Morgan C.

    2010-01-01

    We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state. PMID:20485527

  12. Insulin Signaling in Insulin Resistance States and Cancer: A Modeling Analysis

    PubMed Central

    Bertuzzi, Alessandro; Conte, Federica; Mingrone, Geltrude; Papa, Federico; Salinari, Serenella

    2016-01-01

    Insulin resistance is the common denominator of several diseases including type 2 diabetes and cancer, and investigating the mechanisms responsible for insulin signaling impairment is of primary importance. A mathematical model of the insulin signaling network (ISN) is proposed and used to investigate the dose-response curves of components of this network. Experimental data of C2C12 myoblasts with phosphatase and tensin homologue (PTEN) suppressed and data of L6 myotubes with induced insulin resistance have been analyzed by the model. We focused particularly on single and double Akt phosphorylation and pointed out insulin signaling changes related to insulin resistance. Moreover, a new characterization of the upstream signaling of the mammalian target of rapamycin complex 2 (mTORC2) is presented. As it is widely recognized that ISN proteins have a crucial role also in cell proliferation and death, the ISN model was linked to a cell population model and applied to data of a cell line of acute myeloid leukemia treated with a mammalian target of rapamycin inhibitor with antitumor activity. The analysis revealed simple relationships among the concentrations of ISN proteins and the parameters of the cell population model that characterize cell cycle progression and cell death. PMID:27149630

  13. Modeled Microgravity Disrupts Collagen I/Integrin Signaling During Osteoblastic Differentiation of Human Mesenchymal Stem Cells

    NASA Technical Reports Server (NTRS)

    Meyers, Valerie E.; Zayzafoon, Majd; Gonda, Steven R.; Gathings, William E.; McDonald, Jay M.

    2004-01-01

    Spaceflight leads to reduced bone mineral density in weight bearing bones that is primarily attributed to a reduction in bone formation. We have previously demonstrated severely reduced osteoblastogenesis of human mesenchymal stem cells (hMSC) following seven days culture in modeled microgravity. One potential mechanism for reduced osteoblastic differentiation is disruption of type I collagen-integrin interactions and reduced integrin signaling. Integrins are heterodimeric transmembrane receptors that bind extracellular matrix proteins and produce signals essential for proper cellular function, survival, and differentiation. Therefore, we investigated the effects of modeled microgravity on integrin expression and function in hMSC. We demonstrate that seven days of culture in modeled microgravity leads to reduced expression of the extracellular matrix protein, type I collagen (Col I). Conversely, modeled microgravity consistently increases Col I-specific alpha2 and beta1 integrin protein expression. Despite this increase in integrin sub-unit expression, autophosphorylation of adhesion-dependent kinases, focal adhesion kinase (FAK) and proline-rich tyrosine kinase 2 (PYK2), is significantly reduced. Activation of Akt is unaffected by the reduction in FAK activation. However, reduced downstream signaling via the Ras-MAPK pathway is evidenced by a reduction in Ras and ERK activation. Taken together, our findings indicate that modeled microgravity decreases integrin/MAPK signaling, which likely contributes to the observed reduction in osteoblastogenesis.

  14. Postsynaptic Signal Transduction Models for Long-Term Potentiation and Depression

    PubMed Central

    Manninen, Tiina; Hituri, Katri; Kotaleski, Jeanette Hellgren; Blackwell, Kim T.; Linne, Marja-Leena

    2010-01-01

    More than a hundred biochemical species, activated by neurotransmitters binding to transmembrane receptors, are important in long-term potentiation (LTP) and long-term depression (LTD). To investigate which species and interactions are critical for synaptic plasticity, many computational postsynaptic signal transduction models have been developed. The models range from simple models with a single reversible reaction to detailed models with several hundred kinetic reactions. In this study, more than a hundred models are reviewed, and their features are compared and contrasted so that similarities and differences are more readily apparent. The models are classified according to the type of synaptic plasticity that is modeled (LTP or LTD) and whether they include diffusion or electrophysiological phenomena. Other characteristics that discriminate the models include the phase of synaptic plasticity modeled (induction, expression, or maintenance) and the simulation method used (deterministic or stochastic). We find that models are becoming increasingly sophisticated, by including stochastic properties, integrating with electrophysiological properties of entire neurons, or incorporating diffusion of signaling molecules. Simpler models continue to be developed because they are computationally efficient and allow theoretical analysis. The more complex models permit investigation of mechanisms underlying specific properties and experimental verification of model predictions. Nonetheless, it is difficult to fully comprehend the evolution of these models because (1) several models are not described in detail in the publications, (2) only a few models are provided in existing model databases, and (3) comparison to previous models is lacking. We conclude that the value of these models for understanding molecular mechanisms of synaptic plasticity is increasing and will be enhanced further with more complete descriptions and sharing of the published models. PMID:21188161

  15. Discrete Dynamics Model for the Speract-Activated Ca2+ Signaling Network Relevant to Sperm Motility

    PubMed Central

    Espinal, Jesús; Aldana, Maximino; Guerrero, Adán; Wood, Christopher

    2011-01-01

    Understanding how spermatozoa approach the egg is a central biological issue. Recently a considerable amount of experimental evidence has accumulated on the relation between oscillations in intracellular calcium ion concentration ([Ca]) in the sea urchin sperm flagellum, triggered by peptides secreted from the egg, and sperm motility. Determination of the structure and dynamics of the signaling pathway leading to these oscillations is a fundamental problem. However, a biochemically based formulation for the comprehension of the molecular mechanisms operating in the axoneme as a response to external stimulus is still lacking. Based on experiments on the S. purpuratus sea urchin spermatozoa, we propose a signaling network model where nodes are discrete variables corresponding to the pathway elements and the signal transmission takes place at discrete time intervals according to logical rules. The validity of this model is corroborated by reproducing previous empirically determined signaling features. Prompted by the model predictions we performed experiments which identified novel characteristics of the signaling pathway. We uncovered the role of a high voltage-activated channel as a regulator of the delay in the onset of fluctuations after activation of the signaling cascade. This delay time has recently been shown to be an important regulatory factor for sea urchin sperm reorientation. Another finding is the participation of a voltage-dependent calcium-activated channel in the determination of the period of the fluctuations. Furthermore, by analyzing the spread of network perturbations we find that it operates in a dynamically critical regime. Our work demonstrates that a coarse-grained approach to the dynamics of the signaling pathway is capable of revealing regulatory sperm navigation elements and provides insight, in terms of criticality, on the concurrence of the high robustness and adaptability that the reproduction processes are predicted to have developed

  16. Modeling distinct imaging hemodynamics early after TBI: the relationship between signal amplitude and connectivity.

    PubMed

    Medaglia, John D; McAleavey, Andrew A; Rostami, Sohayla; Slocomb, Julia; Hillary, Frank G

    2015-06-01

    Over the past decade, fMRI studies of cognitive change following traumatic brain injury (TBI) have investigated blood oxygen level dependent (BOLD) activity during working memory (WM) performance in individuals in early and chronic phases of recovery. Recently, BOLD fMRI work has largely shifted to focus on WM and resting functional connectivity following TBI. However, fundamental questions in WM remain. Specifically, the effects of injury on the basic relationships between local and interregional functional neuroimaging signals during WM processing early following moderate to severe TBI have not been examined. This study employs a mixed effects model to examine prefrontal cortex and parietal lobe signal change during a WM task, the n-back, and whether there is covariance between regions of high amplitude signal change, (synchrony of elicited activity (SEA) very early following TBI. We also examined whether signal change and SEA differentially predict performance during WM. Overall, percent signal change in the right prefrontal cortex (rPFC) was and important predictor of both reaction time (RT) and SEA in early TBI and matched controls. Right prefrontal cortex (rPFC) percent signal change positively predicted SEA within and between persons regardless of injury status, suggesting that the link between these neurodynamic processes in WM-activated regions remains unaffected even very early after TBI. Additionally, rPFC activity was positively related to RT within and between persons in both groups. Right parietal (rPAR) activity was negatively related to RT within subjects in both groups. Thus, the local signal intensity of the rPFC in TBI appears to be a critical property of network functioning and performance in WM processing and may be a precursor to recruitment observed in chronic samples. The present results suggest that as much research moves toward large scale functional connectivity modeling, it will be essential to develop integrated models of how local and

  17. Discrete dynamics model for the speract-activated Ca2+ signaling network relevant to sperm motility.

    PubMed

    Espinal, Jesús; Aldana, Maximino; Guerrero, Adán; Wood, Christopher; Darszon, Alberto; Martínez-Mekler, Gustavo

    2011-01-01

    Understanding how spermatozoa approach the egg is a central biological issue. Recently a considerable amount of experimental evidence has accumulated on the relation between oscillations in intracellular calcium ion concentration ([Ca2+]i) in the sea urchin sperm flagellum, triggered by peptides secreted from the egg, and sperm motility. Determination of the structure and dynamics of the signaling pathway leading to these oscillations is a fundamental problem. However, a biochemically based formulation for the comprehension of the molecular mechanisms operating in the axoneme as a response to external stimulus is still lacking. Based on experiments on the S. purpuratus sea urchin spermatozoa, we propose a signaling network model where nodes are discrete variables corresponding to the pathway elements and the signal transmission takes place at discrete time intervals according to logical rules. The validity of this model is corroborated by reproducing previous empirically determined signaling features. Prompted by the model predictions we performed experiments which identified novel characteristics of the signaling pathway. We uncovered the role of a high voltage-activated Ca2+ channel as a regulator of the delay in the onset of fluctuations after activation of the signaling cascade. This delay time has recently been shown to be an important regulatory factor for sea urchin sperm reorientation. Another finding is the participation of a voltage-dependent calcium-activated K+ channel in the determination of the period of the [Ca2+]i fluctuations. Furthermore, by analyzing the spread of network perturbations we find that it operates in a dynamically critical regime. Our work demonstrates that a coarse-grained approach to the dynamics of the signaling pathway is capable of revealing regulatory sperm navigation elements and provides insight, in terms of criticality, on the concurrence of the high robustness and adaptability that the reproduction processes are predicted

  18. Mass detection on mammograms: signal variations and performance changes for human and model observers

    NASA Astrophysics Data System (ADS)

    Castella, C.; Kinkel, K.; Eckstein, M. P.; Abbey, C. K.; Verdun, F. R.; Saunders, R. S.; Samei, E.; Bochud, F. O.

    2008-03-01

    We studied the influence of signal variability on human and model observer performances for a detection task with mammographic backgrounds and computer generated clustered lumpy backgrounds (CLB). We used synthetic yet realistic masses and backgrounds that have been validated by radiologists during previous studies, ensuring conditions close to the clinical situation. Four trained non-physician observers participated in two-alternative forced-choice (2-AFC) experiments. They were asked to detect synthetic masses superimposed on real mammographic backgrounds or CLB. Separate experiments were conducted with sets of benign and malignant masses. Results under the signal-known-exactly (SKE) paradigm were compared with signal-known-statistically (SKS) experiments. In the latter case, the signal was chosen randomly for each of the 1,400 2-AFC trials (image pairs) among a set of 50 masses with similar dimensions, and the observers did not know which signal was present. Human observers' results were then compared with model observers (channelized Hotelling with Difference-of-Gaussian and Gabor channels) in the same experimental conditions. Results show that the performance of the human observers does not differ significantly when benign masses are superimposed on real images or on CLB with locally matched gray level mean and standard deviation. For both benign and malignant masses, the performance does not differ significantly between SKE and SKS experiments, when the signals' dimensions do not vary throughout the experiment. However, there is a performance drop when the SKS signals' dimensions vary from 5.5 to 9.5 mm in the same experiment. Noise level in the model observers can be adjusted to reproduce human observers' proportion of correct answers in the 2-AFC task within 5% accuracy for most conditions.

  19. Error-Rate Estimation Based on Multi-Signal Flow Graph Model and Accelerated Radiation Tests

    PubMed Central

    Wang, Yueke; Xing, Kefei; Deng, Wei; Zhang, Zelong

    2016-01-01

    A method of evaluating the single-event effect soft-error vulnerability of space instruments before launched has been an active research topic in recent years. In this paper, a multi-signal flow graph model is introduced to analyze the fault diagnosis and meantime to failure (MTTF) for space instruments. A model for the system functional error rate (SFER) is proposed. In addition, an experimental method and accelerated radiation testing system for a signal processing platform based on the field programmable gate array (FPGA) is presented. Based on experimental results of different ions (O, Si, Cl, Ti) under the HI-13 Tandem Accelerator, the SFER of the signal processing platform is approximately 10−3(error/particle/cm2), while the MTTF is approximately 110.7 h. PMID:27583533

  20. Modeling and Simulation for Realistic Propagation Environments of Communications Signals at SHF Band

    NASA Technical Reports Server (NTRS)

    Ho, Christian

    2005-01-01

    In this article, most of widely accepted radio wave propagation models that have proven to be accurate in practice as well as numerically efficient at SHF band will be reviewed. Weather and terrain data along the signal's paths can be input in order to more accurately simulate the propagation environments under particular weather and terrain conditions. Radio signal degradation and communications impairment severity will be investigated through the realistic radio propagation channel simulator. Three types of simulation approaches in predicting signal's behaviors are classified as: deterministic, stochastic and attenuation map. The performance of the simulation can be evaluated under operating conditions for the test ranges of interest. Demonstration tests of a real-time propagation channel simulator will show the capabilities and limitations of the simulation tool and underlying models.

  1. Error-Rate Estimation Based on Multi-Signal Flow Graph Model and Accelerated Radiation Tests.

    PubMed

    He, Wei; Wang, Yueke; Xing, Kefei; Deng, Wei; Zhang, Zelong

    2016-01-01

    A method of evaluating the single-event effect soft-error vulnerability of space instruments before launched has been an active research topic in recent years. In this paper, a multi-signal flow graph model is introduced to analyze the fault diagnosis and meantime to failure (MTTF) for space instruments. A model for the system functional error rate (SFER) is proposed. In addition, an experimental method and accelerated radiation testing system for a signal processing platform based on the field programmable gate array (FPGA) is presented. Based on experimental results of different ions (O, Si, Cl, Ti) under the HI-13 Tandem Accelerator, the SFER of the signal processing platform is approximately 10-3(error/particle/cm2), while the MTTF is approximately 110.7 h. PMID:27583533

  2. A method for modelling peak signal statistics on a mobile satellite transponder

    NASA Technical Reports Server (NTRS)

    Bilodeau, Andre; Lecours, Michel; Pelletier, Marcel; Delisle, Gilles Y.

    1990-01-01

    A simulation method is proposed. The simulation was developed to model the peak duration and energy content of signal peaks in a mobile communication satellite operating in a Frequency Division Multiple Access (FDMA) mode and presents an estimate of those power peaks for a system where the channels are modeled as band limited Gaussian noise, which is taken as a reasonable representation for Amplitude Commanded Single Sideband (ACSSB), Minimum Shift Keying (MSK), or Phase Shift Keying (PSK) modulated signals. The simulation results show that, under this hypothesis, the level of the signal power peaks for 10 percent, 1 percent, and 0.1 percent of the time are well described by a Rayleigh law and that their duration is extremely short and inversely proportional to the total FDM system bandwidth.

  3. Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model

    NASA Astrophysics Data System (ADS)

    Ismail, Mohd Tahir; Mamat, Siti Salwana; Hamzah, Firdaus Mohamad; Karim, Samsul Ariffin Abdul

    2014-07-01

    The goal of this research is to determine the forecasting performance of denoising signal. Monthly rainfall and monthly number of raindays with duration of 20 years (1990-2009) from Bayan Lepas station are utilized as the case study. The Fast Fourier Transform (FFT) and Wavelet Transform (WT) are used in this research to find the denoise signal. The denoise data obtained by Fast Fourier Transform and Wavelet Transform are being analyze by seasonal ARIMA model. The best fitted model is determined by the minimum value of MSE. The result indicates that Wavelet Transform is an effective method in denoising the monthly rainfall and number of rain days signals compared to Fast Fourier Transform.

  4. Jitter model and signal processing techniques for pulse width modulation optical recording

    NASA Technical Reports Server (NTRS)

    Liu, Max M.-K.

    1991-01-01

    A jitter model and signal processing techniques are discussed for data recovery in Pulse Width Modulation (PWM) optical recording. In PWM, information is stored through modulating sizes of sequential marks alternating in magnetic polarization or in material structure. Jitter, defined as the deviation from the original mark size in the time domain, will result in error detection if it is excessively large. A new approach is taken in data recovery by first using a high speed counter clock to convert time marks to amplitude marks, and signal processing techniques are used to minimize jitter according to the jitter model. The signal processing techniques include motor speed and intersymbol interference equalization, differential and additive detection, and differential and additive modulation.

  5. Application of Mathematical Modelling as a Tool to Analyze the EEG Signals in Rat Model of Focal Cerebral Ischemia

    NASA Astrophysics Data System (ADS)

    Paul, S.; Bhattacharya, P.; Pandey, A. K.; Patnaik, R.

    2014-01-01

    The present paper envisages the application of mathematical modelling with the autoregressive (AR) model method as a tool to analyze electroencephalogram data in rat subjects of transient focal cerebral ischemia. This modelling method was used to determine the frequencies and characteristic changes in brain waveforms which occur as a result of disorders or fluctuating physiological states. This method of analysis was utilized to ensure actual correlation of the different mathematical paradigms. The EEG data was obtained from different regions of the rat brain and was modelled by AR method in a MATLAB platform. AR modelling was utilized to study the long-term functional outcomes of a stroke and also is preferable for EEG signal analysis because the signals consist of discrete frequency intervals. Modern spectral analysis, namely AR spectrum analysis, was used to correlate the conditional and prevalent changes in brain function in response to a stroke.

  6. The Input Signal Step Function (ISSF), a Standard Method to Encode Input Signals in SBML Models with Software Support, Applied to Circadian Clock Models

    PubMed Central

    Adams, R.R.; Tsorman, N.; Stratford, K.; Akman, O.E.; Gilmore, S.; Juty, N.; Le Novère, N.; Millar, A.J.; Millar, A.J.

    2012-01-01

    Time-dependent light input is an important feature of computational models of the circadian clock. However, publicly available models encoded in standard representations such as the Systems Biology Markup Language (SBML) either do not encode this input or use different mechanisms to do so, which hinders reproducibility of published results as well as model reuse. The authors describe here a numerically continuous function suitable for use in SBML for models of circadian rhythms forced by periodic light-dark cycles. The Input Signal Step Function (ISSF) is broadly applicable to encoding experimental manipulations, such as drug treatments, temperature changes, or inducible transgene expression, which may be transient, periodic, or mixed. It is highly configurable and is able to reproduce a wide range of waveforms. The authors have implemented this function in SBML and demonstrated its ability to modify the behavior of publicly available models to accurately reproduce published results. The implementation of ISSF allows standard simulation software to reproduce specialized circadian protocols, such as the phase-response curve. To facilitate the reuse of this function in public models, the authors have developed software to configure its behavior without any specialist knowledge of SBML. A community-standard approach to represent the inputs that entrain circadian clock models could particularly facilitate research in chronobiology. PMID:22855577

  7. Propagation modeling of ocean-scattered low-elevation GPS signals for maritime tropospheric duct inversion

    NASA Astrophysics Data System (ADS)

    Zhang, Jin-Peng; Wu, Zhen-Sen; Zhao, Zhen-Wei; Zhang, Yu-Sheng; Wang, Bo

    2012-10-01

    The maritime tropospheric duct is a low-altitude anomalous refractivity structure over the ocean surface, and it can significantly affect the performance of many shore-based/shipboard radar and communication systems. We propose the idea that maritime tropospheric ducts can be retrieved from ocean forward-scattered low-elevation global positioning system (GPS) signals. Retrieval is accomplished by matching the measured power patterns of the signals to those predicted by the forward propagation model as a function of the modified refractivity profile. On the basis of a parabolic equation method and bistatic radar equation, we develop such a forward model for computing the trapped propagation characteristics of an ocean forward-scattered GPS signal within a tropospheric duct. A new GPS scattering initial field is defined for this model to start the propagation modeling. A preliminary test on the performance of this model is conducted using measured data obtained from a 2009-experiment in the South China Sea. Results demonstrate that this model can predict GPS propagation characteristics within maritime tropospheric ducts and serve as a forward model for duct inversion.

  8. Evolutionary model of flexible exponential function to characterize decay pattern of OCT signal in turbid tissues

    NASA Astrophysics Data System (ADS)

    Chen, Bingling; Guo, Zhouyi

    2008-12-01

    Conventional analyses of OCT signal measurements resolve the signal decay profile in terms of single discrete exponential function with distinct exponential model. In symmetrical medium, mono-exponential decay function can appear to provide a well fit to OCT signal decay data, but the assuption of symmetrical components is essentially arbitrary and is often erroneous. Actually, the real biological samples such as tissue contained more complex components and are more heterogeneous. To avoid the shortages of mono-exponential decay function fitting to OCT signal decay data from heterogeneous biological tissues, a novel model of flexible exponential function has been developed. The main idea of the flexible exponential function modle is based on the assuption that heterogeneous biological tissue can be considered as a multi-layered tissue. Each layer is symmetric and the OCT signal decay profile in each layer obeies to a distinct single exponential function. If we can find out all the distinct single exponential function for each layer, the total flexible exponential function is determined by summing up all the single exponential functions. As pilot studies on the practical application of flexibleexponential decay model for monitoring and quantifying the diffusion of different analytes in turbid biological tissues in vivo by using OCT system, we demonstrate an experiment of monitoring of glucose diffusion in agar gel. In addition, the flexible-exponential decay model can provide a direct measure of the heterogeneity of the sample, and the analysis of turbid tissues OCT map using the flexible-exponential decay model can reveal subtle tissue differences that other models fail to show.

  9. Comparing Infants' Preference for Correlated Audiovisual Speech with Signal-Level Computational Models

    ERIC Educational Resources Information Center

    Hollich, George; Prince, Christopher G.

    2009-01-01

    How much of infant behaviour can be accounted for by signal-level analyses of stimuli? The current paper directly compares the moment-by-moment behaviour of 8-month-old infants in an audiovisual preferential looking task with that of several computational models that use the same video stimuli as presented to the infants. One type of model…

  10. THE COMPARISON OF TWO VITRO PALATAL ORGAN CULTURE MODELS TO STUDY CELL SIGNALING PATHWAYS DURING PALATOGENESIS

    EPA Science Inventory

    This study was performed to determine the best palatal organ culture model to use in evaluating the role of epidermal growth factor (EGF) signaling in the response to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Previous work has shown that TCDD and EGF can induce teratogenic effe...

  11. A Comprehensive Statistical Model for Cell Signaling and Protein Activity Inference

    PubMed Central

    Yörük, Erdem; Ochs, Michael F.; Geman, Donald; Younes, Laurent

    2010-01-01

    Protein signaling networks play a central role in transcriptional regulation and the etiology of many diseases. Statistical methods, particularly Bayesian networks, have been widely used to model cell signaling, mostly for model organisms and with focus on uncovering connectivity rather than inferring aberrations. Extensions to mammalian systems have not yielded compelling results, due likely to greatly increased complexity and limited proteomic measurements in vivo. In this study, we propose a comprehensive statistical model that is anchored to a predefined core topology, has a limited complexity due to parameter sharing and uses micorarray data of mRNA transcripts as the only observable components of signaling. Specifically, we account for cell heterogeneity and a multi-level process, representing signaling as a Bayesian network at the cell level, modeling measurements as ensemble averages at the tissue level and incorporating patient-to-patient differences at the population level. Motivated by the goal of identifying individual protein abnormalities as potential therapeutical targets, we applied our method to the RAS-RAF network using a breast cancer study with 118 patients. We demonstrated rigorous statistical inference, established reproducibility through simulations and the ability to recover receptor status from available microarray data. PMID:20855924

  12. Range discrimination by big brown bats (Eptesicus fuscus) using altered model echoes: implications for signal processing.

    PubMed

    Masters, W M; Raver, K A

    2000-01-01

    The sonar emissions of two big brown bats (Eptesicus fuscus) were modeled to create a "normal" echolocation signal for each bat which was then used as an artificial echo to synthesize a phantom target. The bat's task was to indicate which of two phantom targets (presented singly) was the "near" target and which the "far" target. Threshold range discrimination at a nominal target distance of 80 cm was about 0.6 cm for both bats. The normal signal was then modified to change the relative energy in each harmonic, the signal duration, the curvature of the frequency sweep, the absolute frequency, the phase of the second and third harmonics relative to the first, or the Doppler shift of the signal. To determine which modifications affected ranging performance, the altered models were used in tests of range discrimination that were interleaved on a day-to-day basis with tests using the normal model. Of the 12 modifications tested, only those changing the curvature of the frequency sweep affected performance. This result appears not to be predicted by current models of echo processing in FM bats. Eptesicus may be able to compensate for certain types of distortions of a returning echo, an ability possibly related to Doppler tolerance or to the characteristics of the natural variation in a bat's emissions.

  13. Approaches and tools for modeling signaling pathways and calcium dynamics in neurons

    PubMed Central

    Blackwell, KT

    2013-01-01

    Signaling pathways are cascades of intracellular biochemical reactions that are activated by transmembrane receptors, and ultimately lead to transcription in the nucleus. In neurons, both calcium permeable synaptic and ionic channels as well as G protein coupled receptors initiate activation of signaling pathway molecules that interact with electrical activity at multiple spatial and time scales. At small temporal and spatial scales, calcium modifies the properties of ionic channels, whereas at larger temporal and spatial scales, various kinases and phosphatases modify the properties of ionic channels, producing phenomena such as synaptic plasticity and homeostatic plasticity. The elongated structure of neuronal dendrites and the organization of multi-protein complexes by anchoring proteins implies that the spatial dimension must be explicit. Therefore, modeling signaling pathways in neurons utilizes algorithms for both diffusion and reactions. The small size of spines coupled with small concentrations of some molecules implies that some reactions occur stochastically. The need for stochastic simulation of many reaction and diffusion events coupled with the multiple temporal and spatial scales makes modeling of signaling pathways a difficult problem. Several different software programs have achieved different aspects of these capabilities. This review explains some of the mathematical formulas used for modeling reactions and diffusion. In addition, it briefly presents the simulators used for modeling reaction-diffusion systems in neurons, together with scientific problems addressed. PMID:23743449

  14. Pavement cells: a model system for non-transcriptional auxin signalling and crosstalks.

    PubMed

    Chen, Jisheng; Wang, Fei; Zheng, Shiqin; Xu, Tongda; Yang, Zhenbiao

    2015-08-01

    Auxin (indole acetic acid) is a multifunctional phytohormone controlling various developmental patterns, morphogenetic processes, and growth behaviours in plants. The transcription-based pathway activated by the nuclear TRANSPORT INHIBITOR RESISTANT 1/auxin-related F-box auxin receptors is well established, but the long-sought molecular mechanisms of non-transcriptional auxin signalling remained enigmatic until very recently. Along with the establishment of the Arabidopsis leaf epidermal pavement cell (PC) as an exciting and amenable model system in the past decade, we began to gain insight into non-transcriptional auxin signalling. The puzzle-piece shape of PCs forms from intercalated or interdigitated cell growth, requiring local intra- and inter-cellular coordination of lobe and indent formation. Precise coordination of this interdigitated pattern requires auxin and an extracellular auxin sensing system that activates plasma membrane-associated Rho GTPases from plants and subsequent downstream events regulating cytoskeletal reorganization and PIN polarization. Apart from auxin, mechanical stress and cytokinin have been shown to affect PC interdigitation, possibly by interacting with auxin signals. This review focuses upon signalling mechanisms for cell polarity formation in PCs, with an emphasis on non-transcriptional auxin signalling in polarized cell expansion and pattern formation and how different auxin pathways interplay with each other and with other signals. PMID:26047974

  15. Pavement cells: a model system for non-transcriptional auxin signalling and crosstalks.

    PubMed

    Chen, Jisheng; Wang, Fei; Zheng, Shiqin; Xu, Tongda; Yang, Zhenbiao

    2015-08-01

    Auxin (indole acetic acid) is a multifunctional phytohormone controlling various developmental patterns, morphogenetic processes, and growth behaviours in plants. The transcription-based pathway activated by the nuclear TRANSPORT INHIBITOR RESISTANT 1/auxin-related F-box auxin receptors is well established, but the long-sought molecular mechanisms of non-transcriptional auxin signalling remained enigmatic until very recently. Along with the establishment of the Arabidopsis leaf epidermal pavement cell (PC) as an exciting and amenable model system in the past decade, we began to gain insight into non-transcriptional auxin signalling. The puzzle-piece shape of PCs forms from intercalated or interdigitated cell growth, requiring local intra- and inter-cellular coordination of lobe and indent formation. Precise coordination of this interdigitated pattern requires auxin and an extracellular auxin sensing system that activates plasma membrane-associated Rho GTPases from plants and subsequent downstream events regulating cytoskeletal reorganization and PIN polarization. Apart from auxin, mechanical stress and cytokinin have been shown to affect PC interdigitation, possibly by interacting with auxin signals. This review focuses upon signalling mechanisms for cell polarity formation in PCs, with an emphasis on non-transcriptional auxin signalling in polarized cell expansion and pattern formation and how different auxin pathways interplay with each other and with other signals.

  16. Modelling intracellular competition for calcium: kinetic and thermodynamic control of different molecular modes of signal decoding

    PubMed Central

    Antunes, Gabriela; Roque, Antonio C.; Simoes de Souza, Fabio M.

    2016-01-01

    Frequently, a common chemical entity triggers opposite cellular processes, which implies that the components of signalling networks must detect signals not only through their chemical natures, but also through their dynamic properties. To gain insights on the mechanisms of discrimination of the dynamic properties of cellular signals, we developed a computational stochastic model and investigated how three calcium ion (Ca2+)-dependent enzymes (adenylyl cyclase (AC), phosphodiesterase 1 (PDE1), and calcineurin (CaN)) differentially detect Ca2+ transients in a hippocampal dendritic spine. The balance among AC, PDE1 and CaN might determine the occurrence of opposite Ca2+-induced forms of synaptic plasticity, long-term potentiation (LTP) and long-term depression (LTD). CaN is essential for LTD. AC and PDE1 regulate, indirectly, protein kinase A, which counteracts CaN during LTP. Stimulations of AC, PDE1 and CaN with artificial and physiological Ca2+ signals demonstrated that AC and CaN have Ca2+ requirements modulated dynamically by different properties of the signals used to stimulate them, because their interactions with Ca2+ often occur under kinetic control. Contrarily, PDE1 responds to the immediate amplitude of different Ca2+ transients and usually with the same Ca2+ requirements observed under steady state. Therefore, AC, PDE1 and CaN decode different dynamic properties of Ca2+ signals. PMID:27033299

  17. A prediction model of signal degradation in LMSS for urban areas

    NASA Technical Reports Server (NTRS)

    Matsudo, Takashi; Minamisono, Kenichi; Karasawa, Yoshio; Shiokawa, Takayasu

    1993-01-01

    A prediction model of signal degradation in a Land Mobile Satellite Service (LMSS) for urban areas is proposed. This model treats shadowing effects caused by buildings statistically and can predict a Cumulative Distribution Function (CDF) of signal diffraction losses in urban areas as a function of system parameters such as frequency and elevation angle and environmental parameters such as number of building stories and so on. In order to examine the validity of the model, we compared the percentage of locations where diffraction losses were smaller than 6 dB obtained by the CDF with satellite visibility measured by a radiometer. As a result, it was found that this proposed model is useful for estimating the feasibility of providing LMSS in urban areas.

  18. Systematic Analysis of Quantitative Logic Model Ensembles Predicts Drug Combination Effects on Cell Signaling Networks

    PubMed Central

    Morris, MK; Clarke, DC; Osimiri, LC

    2016-01-01

    A major challenge in developing anticancer therapies is determining the efficacies of drugs and their combinations in physiologically relevant microenvironments. We describe here our application of “constrained fuzzy logic” (CFL) ensemble modeling of the intracellular signaling network for predicting inhibitor treatments that reduce the phospho‐levels of key transcription factors downstream of growth factors and inflammatory cytokines representative of hepatocellular carcinoma (HCC) microenvironments. We observed that the CFL models successfully predicted the effects of several kinase inhibitor combinations. Furthermore, the ensemble predictions revealed ambiguous predictions that could be traced to a specific structural feature of these models, which we resolved with dedicated experiments, finding that IL‐1α activates downstream signals through TAK1 and not MEKK1 in HepG2 cells. We conclude that CFL‐Q2LM (Querying Quantitative Logic Models) is a promising approach for predicting effective anticancer drug combinations in cancer‐relevant microenvironments. PMID:27567007

  19. Identification of Potential Drug Targets in Cancer Signaling Pathways using Stochastic Logical Models.

    PubMed

    Zhu, Peican; Aliabadi, Hamidreza Montazeri; Uludağ, Hasan; Han, Jie

    2016-03-18

    The investigation of vulnerable components in a signaling pathway can contribute to development of drug therapy addressing aberrations in that pathway. Here, an original signaling pathway is derived from the published literature on breast cancer models. New stochastic logical models are then developed to analyze the vulnerability of the components in multiple signalling sub-pathways involved in this signaling cascade. The computational results are consistent with the experimental results, where the selected proteins were silenced using specific siRNAs and the viability of the cells were analyzed 72 hours after silencing. The genes elF4E and NFkB are found to have nearly no effect on the relative cell viability and the genes JAK2, Stat3, S6K, JUN, FOS, Myc, and Mcl1 are effective candidates to influence the relative cell growth. The vulnerabilities of some targets such as Myc and S6K are found to vary significantly depending on the weights of the sub-pathways; this will be indicative of the chosen target to require customization for therapy. When these targets are utilized, the response of breast cancers from different patients will be highly variable because of the known heterogeneities in signaling pathways among the patients. The targets whose vulnerabilities are invariably high might be more universally acceptable targets.

  20. An artificial network model for estimating the network structure underlying partially observed neuronal signals.

    PubMed

    Komatsu, Misako; Namikawa, Jun; Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka; Nakamura, Kiyohiko; Tani, Jun

    2014-01-01

    Many previous studies have proposed methods for quantifying neuronal interactions. However, these methods evaluated the interactions between recorded signals in an isolated network. In this study, we present a novel approach for estimating interactions between observed neuronal signals by theorizing that those signals are observed from only a part of the network that also includes unobserved structures. We propose a variant of the recurrent network model that consists of both observable and unobservable units. The observable units represent recorded neuronal activity, and the unobservable units are introduced to represent activity from unobserved structures in the network. The network structures are characterized by connective weights, i.e., the interaction intensities between individual units, which are estimated from recorded signals. We applied this model to multi-channel brain signals recorded from monkeys, and obtained robust network structures with physiological relevance. Furthermore, the network exhibited common features that portrayed cortical dynamics as inversely correlated interactions between excitatory and inhibitory populations of neurons, which are consistent with the previous view of cortical local circuits. Our results suggest that the novel concept of incorporating an unobserved structure into network estimations has theoretical advantages and could provide insights into brain dynamics beyond what can be directly observed.

  1. Bilinear modeling of EMG signals to extract user-independent features for multiuser myoelectric interface.

    PubMed

    Matsubara, Takamitsu; Morimoto, Jun

    2013-08-01

    In this study, we propose a multiuser myoelectric interface that can easily adapt to novel users. When a user performs different motions (e.g., grasping and pinching), different electromyography (EMG) signals are measured. When different users perform the same motion (e.g., grasping), different EMG signals are also measured. Therefore, designing a myoelectric interface that can be used by multiple users to perform multiple motions is difficult. To cope with this problem, we propose for EMG signals a bilinear model that is composed of two linear factors: 1) user dependent and 2) motion dependent. By decomposing the EMG signals into these two factors, the extracted motion-dependent factors can be used as user-independent features. We can construct a motion classifier on the extracted feature space to develop the multiuser interface. For novel users, the proposed adaptation method estimates the user-dependent factor through only a few interactions. The bilinear EMG model with the estimated user-dependent factor can extract the user-independent features from the novel user data. We applied our proposed method to a recognition task of five hand gestures for robotic hand control using four-channel EMG signals measured from subject forearms. Our method resulted in 73% accuracy, which was statistically significantly different from the accuracy of standard nonmultiuser interfaces, as the result of a two-sample t -test at a significance level of 1%.

  2. Dynamics of ubiquitin-mediated signalling: insights from mathematical modelling and experimental studies.

    PubMed

    Nguyen, Lan K

    2016-05-01

    Post-translational modification of cellular proteins by ubiquitin is a pivotal regulatory event that controls not only protein degradation, but also a variety of non-proteolytic functions. Ubiquitination is involved in a broad array of physiological processes, and its dysregulation has been associated with many human diseases, including neuronal disorders and cancers. Ubiquitin-mediated signalling has thus come to the forefront of biomedical research. It is increasingly apparent that ubiquitination is a highly complex and dynamic process, evidenced by a myriad of ways of ubiquitin chain formation, tightly regulatory mechanisms involving E3 ligases and deubiquitinating enzymes and extensive crosstalk with other post-translational modifications. To unravel the complexity of ubiquitination and understand the dynamic properties of ubiquitin-mediated signalling are challenging, but critical topics in ubiquitin research, which will undoubtedly benefit our effort in developing strategies that could target ubiquitin signalling for therapeutics. Computational modelling and model-based approaches are emerging as promising tools that help tackle the complexity and provide useful frameworks for quantitative and dynamical analysis of ubiquitin signalling. In this article, I will discuss recent advances in our understanding of the dynamic behaviour of ubiquitination from both theoretical and experimental studies, and aspects of ubiquitin signalling that may have major dynamical consequences. It is expected the discussed issues will be of relevant interest to both the ubiquitin and systems biology fields.

  3. Identification of Potential Drug Targets in Cancer Signaling Pathways using Stochastic Logical Models

    PubMed Central

    Zhu, Peican; Aliabadi, Hamidreza Montazeri; Uludağ, Hasan; Han, Jie

    2016-01-01

    The investigation of vulnerable components in a signaling pathway can contribute to development of drug therapy addressing aberrations in that pathway. Here, an original signaling pathway is derived from the published literature on breast cancer models. New stochastic logical models are then developed to analyze the vulnerability of the components in multiple signalling sub-pathways involved in this signaling cascade. The computational results are consistent with the experimental results, where the selected proteins were silenced using specific siRNAs and the viability of the cells were analyzed 72 hours after silencing. The genes elF4E and NFkB are found to have nearly no effect on the relative cell viability and the genes JAK2, Stat3, S6K, JUN, FOS, Myc, and Mcl1 are effective candidates to influence the relative cell growth. The vulnerabilities of some targets such as Myc and S6K are found to vary significantly depending on the weights of the sub-pathways; this will be indicative of the chosen target to require customization for therapy. When these targets are utilized, the response of breast cancers from different patients will be highly variable because of the known heterogeneities in signaling pathways among the patients. The targets whose vulnerabilities are invariably high might be more universally acceptable targets. PMID:26988076

  4. SPC toolbox: An interactive MATLAB (tm) package for signal modeling, analysis, and communications

    NASA Astrophysics Data System (ADS)

    Brown, Dennis W.; Fargues, Monique P.

    1993-10-01

    This report presents the Signal Processing and Communications (SPC) software package. SPC is an interactive package designed to provide the user with a series of data manipulation tools which use MATLAB version 4 graphical interface controls. SPC includes various filtering techniques, AutoRegressive (AR) and linear Moving Average AutoRegressive (ARMA) modeling methods, speech processing, and communication functions. SPC can be used in the classroom to illustrate and to reinforce basic concepts in signal processing and communications. It allows the user to concentrate on the principles presented in class instead of the details related to software usage. It can also be used as a basic analysis and modeling tool for research in signal processing. SPC was designed for Electrical Engineering applications. As a result, it is well suited to reinforce basic concepts presented in the following courses offered at the Naval Postgraduate School: EC 4410: Speech Processing, EC 4420: Modern Spectral Estimation, EC 3420: Statistical Digital Signal Processing, EC 3400: Digital Signal Processing, and EC 2500: Communication Theory. We hope that users will find this package useful, and we welcome any comments and suggestions regarding this software at browndw ece.nps.navy.mil (until 6/94), or fargues ece.nps.navy.mil.

  5. An Obstructive Sleep Apnea Detection Approach Using a Discriminative Hidden Markov Model From ECG Signals.

    PubMed

    Song, Changyue; Liu, Kaibo; Zhang, Xi; Chen, Lili; Xian, Xiaochen

    2016-07-01

    Obstructive sleep apnea (OSA) syndrome is a common sleep disorder suffered by an increasing number of people worldwide. As an alternative to polysomnography (PSG) for OSA diagnosis, the automatic OSA detection methods used in the current practice mainly concentrate on feature extraction and classifier selection based on collected physiological signals. However, one common limitation in these methods is that the temporal dependence of signals are usually ignored, which may result in critical information loss for OSA diagnosis. In this study, we propose a novel OSA detection approach based on ECG signals by considering temporal dependence within segmented signals. A discriminative hidden Markov model (HMM) and corresponding parameter estimation algorithms are provided. In addition, subject-specific transition probabilities within the model are employed to characterize the subject-to-subject differences of potential OSA patients. To validate our approach, 70 recordings obtained from the Physionet Apnea-ECG database were used. Accuracies of 97.1% for per-recording classification and 86.2% for per-segment OSA detection with satisfactory sensitivity and specificity were achieved. Compared with other existing methods that simply ignore the temporal dependence of signals, the proposed HMM-based detection approach delivers more satisfactory detection performance and could be extended to other disease diagnosis applications. PMID:26560867

  6. Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.

    PubMed

    Engemann, Denis A; Gramfort, Alexandre

    2015-03-01

    Magnetoencephalography and electroencephalography (M/EEG) measure non-invasively the weak electromagnetic fields induced by post-synaptic neural currents. The estimation of the spatial covariance of the signals recorded on M/EEG sensors is a building block of modern data analysis pipelines. Such covariance estimates are used in brain-computer interfaces (BCI) systems, in nearly all source localization methods for spatial whitening as well as for data covariance estimation in beamformers. The rationale for such models is that the signals can be modeled by a zero mean Gaussian distribution. While maximizing the Gaussian likelihood seems natural, it leads to a covariance estimate known as empirical covariance (EC). It turns out that the EC is a poor estimate of the true covariance when the number of samples is small. To address this issue the estimation needs to be regularized. The most common approach downweights off-diagonal coefficients, while more advanced regularization methods are based on shrinkage techniques or generative models with low rank assumptions: probabilistic PCA (PPCA) and factor analysis (FA). Using cross-validation all of these models can be tuned and compared based on Gaussian likelihood computed on unseen data. We investigated these models on simulations, one electroencephalography (EEG) dataset as well as magnetoencephalography (MEG) datasets from the most common MEG systems. First, our results demonstrate that different models can be the best, depending on the number of samples, heterogeneity of sensor types and noise properties. Second, we show that the models tuned by cross-validation are superior to models with hand-selected regularization. Hence, we propose an automated solution to the often overlooked problem of covariance estimation of M/EEG signals. The relevance of the procedure is demonstrated here for spatial whitening and source localization of MEG signals.

  7. Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.

    PubMed

    Engemann, Denis A; Gramfort, Alexandre

    2015-03-01

    Magnetoencephalography and electroencephalography (M/EEG) measure non-invasively the weak electromagnetic fields induced by post-synaptic neural currents. The estimation of the spatial covariance of the signals recorded on M/EEG sensors is a building block of modern data analysis pipelines. Such covariance estimates are used in brain-computer interfaces (BCI) systems, in nearly all source localization methods for spatial whitening as well as for data covariance estimation in beamformers. The rationale for such models is that the signals can be modeled by a zero mean Gaussian distribution. While maximizing the Gaussian likelihood seems natural, it leads to a covariance estimate known as empirical covariance (EC). It turns out that the EC is a poor estimate of the true covariance when the number of samples is small. To address this issue the estimation needs to be regularized. The most common approach downweights off-diagonal coefficients, while more advanced regularization methods are based on shrinkage techniques or generative models with low rank assumptions: probabilistic PCA (PPCA) and factor analysis (FA). Using cross-validation all of these models can be tuned and compared based on Gaussian likelihood computed on unseen data. We investigated these models on simulations, one electroencephalography (EEG) dataset as well as magnetoencephalography (MEG) datasets from the most common MEG systems. First, our results demonstrate that different models can be the best, depending on the number of samples, heterogeneity of sensor types and noise properties. Second, we show that the models tuned by cross-validation are superior to models with hand-selected regularization. Hence, we propose an automated solution to the often overlooked problem of covariance estimation of M/EEG signals. The relevance of the procedure is demonstrated here for spatial whitening and source localization of MEG signals. PMID:25541187

  8. Mathematical model of cAMP-dependent signaling pathway in constitutive and UV-induced melanogenesis

    NASA Astrophysics Data System (ADS)

    Stolnitz, Mikhail M.; Peshkova, Anna Y.

    2002-07-01

    Cascade of reactions of cAMP-dependent signaling pathway in melanocytes is investigated by mathematical modeling. Model takes into account (alpha) -melanocyte stimulating hormone binding to melanocortin-1 receptor, adenylate cyclase activation by G-protein, increase of the intracellular cAMP concentration, PKA activation by cAMP, CREB phosphorylation by PKA, microphthalmia gene expression, microphthalmia binding to tyrosinase gene promoter, increase of tyrosinase synthesis. Positive and negative feedback loops of this system are analyzed.

  9. Multichannel ECG and Noise Modeling: Application to Maternal and Fetal ECG Signals

    NASA Astrophysics Data System (ADS)

    Sameni, Reza; Clifford, Gari D.; Jutten, Christian; Shamsollahi, Mohammad B.

    2007-12-01

    A three-dimensional dynamic model of the electrical activity of the heart is presented. The model is based on the single dipole model of the heart and is later related to the body surface potentials through a linear model which accounts for the temporal movements and rotations of the cardiac dipole, together with a realistic ECG noise model. The proposed model is also generalized to maternal and fetal ECG mixtures recorded from the abdomen of pregnant women in single and multiple pregnancies. The applicability of the model for the evaluation of signal processing algorithms is illustrated using independent component analysis. Considering the difficulties and limitations of recording long-term ECG data, especially from pregnant women, the model described in this paper may serve as an effective means of simulation and analysis of a wide range of ECGs, including adults and fetuses.

  10. Evaluating the validity of spectral calibration models for quantitative analysis following signal preprocessing.

    PubMed

    Chen, Da; Grant, Edward

    2012-11-01

    When paired with high-powered chemometric analysis, spectrometric methods offer great promise for the high-throughput analysis of complex systems. Effective classification or quantification often relies on signal preprocessing to reduce spectral interference and optimize the apparent performance of a calibration model. However, less frequently addressed by systematic research is the affect of preprocessing on the statistical accuracy of a calibration result. The present work demonstrates the effectiveness of two criteria for validating the performance of signal preprocessing in multivariate models in the important dimensions of bias and precision. To assess the extent of bias, we explore the applicability of the elliptic joint confidence region (EJCR) test and devise a new means to evaluate precision by a bias-corrected root mean square error of prediction. We show how these criteria can effectively gauge the success of signal pretreatments in suppressing spectral interference while providing a straightforward means to determine the optimal level of model complexity. This methodology offers a graphical diagnostic by which to visualize the consequences of pretreatment on complex multivariate models, enabling optimization with greater confidence. To demonstrate the application of the EJCR criterion in this context, we evaluate the validity of representative calibration models using standard pretreatment strategies on three spectral data sets. The results indicate that the proposed methodology facilitates the reliable optimization of a well-validated calibration model, thus improving the capability of spectrophotometric analysis.

  11. Inflammatory prostaglandin E2 signaling in a mouse model of Alzheimer’s disease

    PubMed Central

    Shi, Ju; Wang, Qian; Johansson, Jenny U.; Liang, Xibin; Woodling, Nathaniel S.; Priyam, Prachi; Loui, Taylor M.; Merchant, Milton; Breyer, Richard M.; Montine, Thomas J.; Andreasson, Katrin

    2012-01-01

    Objective There is significant evidence for a central role of inflammation in the development of Alzheimer’s disease (AD). Epidemiological studies indicate that chronic use of non-steroidal anti-inflammatory drugs (NSAIDs) reduces the risk of developing AD in healthy aging populations. As NSAIDs inhibit the enzymatic activity of the inflammatory cyclooxygenases COX-1 and COX-2, these findings suggest that downstream prostaglandin signaling pathways function in the pre-clinical development of AD. Here, we investigate the function of prostaglandin E2 (PGE2) signaling through its EP3 receptor in the neuroinflammatory response to Aβ peptide. Methods The function of PGE2 signaling through its EP3 receptor was examined in vivo a model of subacute neuroinflammation induced by administration of Aβ42 peptides. Our findings were then confirmed in young adult APPSwe-PS1 ΔE9 transgenic mice. Results Deletion of the PGE2 EP3 receptor in a model of Aβ42 peptide-induced neuroinflammation reduced pro-inflammatory gene expression, cytokine production, and oxidative stress. In the APPSwe-PS1 ΔE9 model of Familial AD, deletion of the EP3 receptor blocked induction of pro-inflammatory gene and protein expression and lipid peroxidation. In addition, levels of Aβ peptides were significantly decreased, as were BACE-1 and β-CTF levels, suggesting that generation of Aβ peptides may be increased as a result of pro-inflammatory EP3 signaling. Finally, deletion of EP3 receptor significantly reversed the decline in pre-synaptic proteins seen in APPSwe-PS1 ΔE9 mice. Interpretation Our findings identify the PGE2 EP3 receptor as a novel pro-inflammatory, pro-amyloidogenic, and synaptotoxic signaling pathway, and suggest a role for COX-PGE2-EP3 signaling in the development of AD. PMID:22915243

  12. A signal integration model of thymic selection and natural regulatory T cell commitment.

    PubMed

    Khailaie, Sahamoddin; Robert, Philippe A; Toker, Aras; Huehn, Jochen; Meyer-Hermann, Michael

    2014-12-15

    The extent of TCR self-reactivity is the basis for selection of a functional and self-tolerant T cell repertoire and is quantified by repeated engagement of TCRs with a diverse pool of self-peptides complexed with self-MHC molecules. The strength of a TCR signal depends on the binding properties of a TCR to the peptide and the MHC, but it is not clear how the specificity to both components drives fate decisions. In this study, we propose a TCR signal-integration model of thymic selection that describes how thymocytes decide among distinct fates, not only based on a single TCR-ligand interaction, but taking into account the TCR stimulation history. These fates are separated based on sustained accumulated signals for positive selection and transient peak signals for negative selection. This spans up the cells into a two-dimensional space where they are either neglected, positively selected, negatively selected, or selected as natural regulatory T cells (nTregs). We show that the dynamics of the integrated signal can serve as a successful basis for extracting specificity of thymocytes to MHC and detecting the existence of cognate self-peptide-MHC. It allows to select a self-MHC-biased and self-peptide-tolerant T cell repertoire. Furthermore, nTregs in the model are enriched with MHC-specific TCRs. This allows nTregs to be more sensitive to activation and more cross-reactive than conventional T cells. This study provides a mechanistic model showing that time integration of TCR-mediated signals, as opposed to single-cell interaction events, is needed to gain a full view on the properties emerging from thymic selection. PMID:25392533

  13. Linking a neural mass model with a 3D model of the human brain to reproduce EEG signals.

    PubMed

    Petersen, Sabine; Zimmermann, Ulf; Schmidt, Christian; Schwabe, Lars; Warkentin, Mareike; Teipel, Stefan J

    2014-06-01

    Electroencephalography (EEG) is often employed to measure electrical activity in the living human brain. Simulation studies can help unravel how the brain electrical activity pattern generates the EEG signal, still a widely unresolved question. This article describes a method to simulate brain electrical activity by using neuronal populations of a neural mass model. Implementing these populations in a finite element model of the head offers the opportunity to investigate the influence of each group of neurons to the scalp potential. This model is based on structural magnetic resonance imaging data to specify tissue composition, and diffusion tensor imaging data to model local anisotropy. We simulated the EEG signals of five neuronal populations generating α waves in the visual cortex. Our results indicate that radially oriented sources dominate over tangential sources in the generation of the scalp signal. Investigating the influence of anisotropic conductivity, we found small differences in topography and phase and larger ones for the potential amplitude compared with an isotropic conductivity distribution. The outcome of this article is a fast method based on superposition of sources for simulating time-dependent EEG signals, which can be used for further studies of neurodegenerative diseases. PMID:24515994

  14. Computational modeling of calcium signaling from the nanoscale to multicellular systems

    NASA Astrophysics Data System (ADS)

    Ullah, Ghanim

    Calcium signaling is one of the most important signaling mechanisms controlling e.g. the contraction of muscle cells, the release of neurotransmitter from neurons and astrocytes, transcription inside the nucleus and metabolic processes in liver and pancreas [8, 44, 36]. Due to the general importance in cell biology, Ca2+ signals of a variety of forms have been the subject of much recent experimental research. A recent and particularly powerful approach towards the understanding of Ca2+ signaling is the combination of highly resolved fluorescent imaging methods and detailed mathematical modeling. Models for Ca2+ signaling are probably the most advanced and realistic modes in all areas of biological physics. Hence theoretical predictions are quantitative in nature and allow direct comparison with experiments. Ca2+ signaling patterns exhibit a hierarchical structure varying from single-channel release events (10's of nanometers) to Ca2+ waves sweeping over entire organs like the liver to globally orchestrate the efficient release of enzymes [48]. This multi-scale organization renders it an ideal tool for studying basic concepts of pattern formation, especially since access to the most important experimental parameters is given. The aim of this dissertation is to develop mathematical models that quantitatively describe the characteristics of elementary Ca2+ elements (called Ca2+ -puffs) on the nano-scale as well as the organization of global waves and oscillations on the cell and organ scale. We used oocytes, eggs and astrocytes as model cells for our theoretical studies. Particularly on the microscopic scale we report significant progress in modeling Ca 2+ release events that are accurate in time course and spatial shape. Experimental investigations have revealed recently that Ca 2+ signaling differentiates during the development of oocytes into mature eggs. The fertilization specific Ca2+ signal in mature eggs is characterized by a fast rise of intracellular Ca2+ and

  15. Ground motions and the infrasound signal: A new model and the discovery of a significant cavity rebound signal. Los Alamos Source Region Program

    SciTech Connect

    Jones, E.M.; App, F.N.; Whitaker, R.W.

    1993-03-01

    A model is presented that relates infrasound signals from underground nuclear tests to the peak vertical velocity at surface-ground-zero. For the most part, agreement between the model and observations is good, the exceptions being events conducted in shallow tuff layers in Yucca Flat. These events all have low values of the peak surface velocity. The authors have determined that the lack of agreement for these events is due to an unusual, second spall event. A stress-wave calculation is presented that reproduces the second-spall phenomenon and indicates that it is due to interference of cavity-rebound-associated signal with the initial ballistic motion of the surface layers. The effect of the rebound signal is to increase the amplitude of the infrasound signal and thus make low velocity events more detectable.

  16. Purely stochastic binary decisions in cell signaling models without underlying deterministic bistabilities

    NASA Astrophysics Data System (ADS)

    Artyomov, Maxim N.; Das, Jayajit; Kardar, Mehran; Chakraborty, Arup

    2009-03-01

    Detection of different extra-cellular stimuli leading to functionally distinct outcomes is common in cell biology, and is often mediated by differential regulation of positive and negative feedback loops that are a part of the signaling network. For cellular responses stimulated by small numbers of molecules, the stochastic effects are important. Therefore, we studied the influence of stochastic fluctuations on a simple signaling model with dueling positive and negative feedback loops. The class of models we have studied is characterized by single deterministic steady states for all parameter values, but the stochastic response is bimodal; a behavior that is distinctly different from models studied in the context of gene regulation. For small numbers of signaling molecules, stochastic effects result in a bimodal distribution for this quantity, with neither mode corresponding to the deterministic solution; i.e., cells are in ``on'' or ``off'' states, not in some intermediate state. For a large number of molecules, the stochastic solution converges to the mean-field result. When fluctuations are important, we find that signal output scales with control parameters ``anomalously'' compared to mean-field predictions.

  17. Collective polarization model for gradient sensing via Dachsous-Fat intercellular signaling.

    PubMed

    Mani, Madhav; Goyal, Sidhartha; Irvine, Kenneth D; Shraiman, Boris I

    2013-12-17

    Dachsous-Fat signaling via the Hippo pathway influences proliferation during Drosophila development, and some of its mammalian homologs are tumor suppressors, highlighting its role as a universal growth regulator. The Fat/Hippo pathway responds to morphogen gradients and influences the in-plane polarization of cells and orientation of divisions, linking growth with tissue patterning. Remarkably, the Fat pathway transduces a growth signal through the polarization of transmembrane complexes that responds to both morphogen level and gradient. Dissection of these complex phenotypes requires a quantitative model that provides a systematic characterization of the pathway. In the absence of detailed knowledge of molecular interactions, we take a phenomenological approach that considers a broad class of simple models, which are sufficiently constrained by observations to enable insight into possible mechanisms. We predict two modes of local/cooperative interactions among Fat-Dachsous complexes, which are necessary for the collective polarization of tissues and enhanced sensitivity to weak gradients. Collective polarization convolves level and gradient of input signals, reproducing known phenotypes while generating falsifiable predictions. Our construction of a simplified signal transduction map allows a generalization of the positional value model and emphasizes the important role intercellular interactions play in growth and patterning of tissues.

  18. Linear models of activation cascades: analytical solutions and coarse-graining of delayed signal transduction.

    PubMed

    Beguerisse-Díaz, Mariano; Desikan, Radhika; Barahona, Mauricio

    2016-08-01

    Cellular signal transduction usually involves activation cascades, the sequential activation of a series of proteins following the reception of an input signal. Here, we study the classic model of weakly activated cascades and obtain analytical solutions for a variety of inputs. We show that in the special but important case of optimal gain cascades (i.e. when the deactivation rates are identical) the downstream output of the cascade can be represented exactly as a lumped nonlinear module containing an incomplete gamma function with real parameters that depend on the rates and length of the cascade, as well as parameters of the input signal. The expressions obtained can be applied to the non-identical case when the deactivation rates are random to capture the variability in the cascade outputs. We also show that cascades can be rearranged so that blocks with similar rates can be lumped and represented through our nonlinear modules. Our results can be used both to represent cascades in computational models of differential equations and to fit data efficiently, by reducing the number of equations and parameters involved. In particular, the length of the cascade appears as a real-valued parameter and can thus be fitted in the same manner as Hill coefficients. Finally, we show how the obtained nonlinear modules can be used instead of delay differential equations to model delays in signal transduction.

  19. Linear models of activation cascades: analytical solutions and coarse-graining of delayed signal transduction.

    PubMed

    Beguerisse-Díaz, Mariano; Desikan, Radhika; Barahona, Mauricio

    2016-08-01

    Cellular signal transduction usually involves activation cascades, the sequential activation of a series of proteins following the reception of an input signal. Here, we study the classic model of weakly activated cascades and obtain analytical solutions for a variety of inputs. We show that in the special but important case of optimal gain cascades (i.e. when the deactivation rates are identical) the downstream output of the cascade can be represented exactly as a lumped nonlinear module containing an incomplete gamma function with real parameters that depend on the rates and length of the cascade, as well as parameters of the input signal. The expressions obtained can be applied to the non-identical case when the deactivation rates are random to capture the variability in the cascade outputs. We also show that cascades can be rearranged so that blocks with similar rates can be lumped and represented through our nonlinear modules. Our results can be used both to represent cascades in computational models of differential equations and to fit data efficiently, by reducing the number of equations and parameters involved. In particular, the length of the cascade appears as a real-valued parameter and can thus be fitted in the same manner as Hill coefficients. Finally, we show how the obtained nonlinear modules can be used instead of delay differential equations to model delays in signal transduction. PMID:27581482

  20. A common signal detection model accounts for both perception and discrimination of the watercolor effect.

    PubMed

    Devinck, Frédéric; Knoblauch, Kenneth

    2012-03-21

    Establishing the relation between perception and discrimination is a fundamental objective in psychophysics, with the goal of characterizing the neural mechanisms mediating perception. Here, we show that a procedure for estimating a perceptual scale based on a signal detection model also predicts discrimination performance. We use a recently developed procedure, Maximum Likelihood Difference Scaling (MLDS), to measure the perceptual strength of a long-range, color, filling-in phenomenon, the Watercolor Effect (WCE), as a function of the luminance ratio between the two components of its generating contour. MLDS is based on an equal-variance, gaussian, signal detection model and yields a perceptual scale with interval properties. The strength of the fill-in percept increased 10-15 times the estimate of the internal noise level for a 3-fold increase in the luminance ratio. Each observer's estimated scale predicted discrimination performance in a subsequent paired-comparison task. A common signal detection model accounts for both the appearance and discrimination data. Since signal detection theory provides a common metric for relating discrimination performance and neural response, the results have implications for comparing perceptual and neural response functions.

  1. Computational Complementation: A Modelling Approach to Study Signalling Mechanisms during Legume Autoregulation of Nodulation

    PubMed Central

    Han, Liqi

    2010-01-01

    Autoregulation of nodulation (AON) is a long-distance signalling regulatory system maintaining the balance of symbiotic nodulation in legume plants. However, the intricacy of internal signalling and absence of flux and biochemical data, are a bottleneck for investigation of AON. To address this, a new computational modelling approach called “Computational Complementation” has been developed. The main idea is to use functional-structural modelling to complement the deficiency of an empirical model of a loss-of-function (non-AON) mutant with hypothetical AON mechanisms. If computational complementation demonstrates a phenotype similar to the wild-type plant, the signalling hypothesis would be suggested as “reasonable”. Our initial case for application of this approach was to test whether or not wild-type soybean cotyledons provide the shoot-derived inhibitor (SDI) to regulate nodule progression. We predicted by computational complementation that the cotyledon is part of the shoot in terms of AON and that it produces the SDI signal, a result that was confirmed by reciprocal epicotyl-and-hypocotyl grafting in a real-plant experiment. This application demonstrates the feasibility of computational complementation and shows its usefulness for applications where real-plant experimentation is either difficult or impossible. PMID:20195551

  2. Linear models of activation cascades: analytical solutions and coarse-graining of delayed signal transduction

    PubMed Central

    Desikan, Radhika

    2016-01-01

    Cellular signal transduction usually involves activation cascades, the sequential activation of a series of proteins following the reception of an input signal. Here, we study the classic model of weakly activated cascades and obtain analytical solutions for a variety of inputs. We show that in the special but important case of optimal gain cascades (i.e. when the deactivation rates are identical) the downstream output of the cascade can be represented exactly as a lumped nonlinear module containing an incomplete gamma function with real parameters that depend on the rates and length of the cascade, as well as parameters of the input signal. The expressions obtained can be applied to the non-identical case when the deactivation rates are random to capture the variability in the cascade outputs. We also show that cascades can be rearranged so that blocks with similar rates can be lumped and represented through our nonlinear modules. Our results can be used both to represent cascades in computational models of differential equations and to fit data efficiently, by reducing the number of equations and parameters involved. In particular, the length of the cascade appears as a real-valued parameter and can thus be fitted in the same manner as Hill coefficients. Finally, we show how the obtained nonlinear modules can be used instead of delay differential equations to model delays in signal transduction. PMID:27581482

  3. Predicting electromyographic signals under realistic conditions using a multiscale chemo–electro–mechanical finite element model

    PubMed Central

    Mordhorst, Mylena; Heidlauf, Thomas; Röhrle, Oliver

    2015-01-01

    This paper presents a novel multiscale finite element-based framework for modelling electromyographic (EMG) signals. The framework combines (i) a biophysical description of the excitation–contraction coupling at the half-sarcomere level, (ii) a model of the action potential (AP) propagation along muscle fibres, (iii) a continuum-mechanical formulation of force generation and deformation of the muscle, and (iv) a model for predicting the intramuscular and surface EMG. Owing to the biophysical description of the half-sarcomere, the model inherently accounts for physiological properties of skeletal muscle. To demonstrate this, the influence of membrane fatigue on the EMG signal during sustained contractions is investigated. During a stimulation period of 500 ms at 100 Hz, the predicted EMG amplitude decreases by 40% and the AP propagation velocity decreases by 15%. Further, the model can take into account contraction-induced deformations of the muscle. This is demonstrated by simulating fixed-length contractions of an idealized geometry and a model of the human tibialis anterior muscle (TA). The model of the TA furthermore demonstrates that the proposed finite element model is capable of simulating realistic geometries, complex fibre architectures, and can include different types of heterogeneities. In addition, the TA model accounts for a distributed innervation zone, different fibre types and appeals to motor unit discharge times that are based on a biophysical description of the α motor neurons. PMID:25844148

  4. Rapid and stable measurement of respiratory rate from Doppler radar signals using time domain autocorrelation model.

    PubMed

    Sun, Guanghao; Matsui, Takemi

    2015-01-01

    Noncontact measurement of respiratory rate using Doppler radar will play a vital role in future clinical practice. Doppler radar remotely monitors the tiny chest wall movements induced by respiration activity. The most competitive advantage of this technique is to allow users fully unconstrained with no biological electrode attachments. However, the Doppler radar, unlike other contact-type sensors, is easily affected by the random body movements. In this paper, we proposed a time domain autocorrelation model to process the radar signals for rapid and stable estimation of the respiratory rate. We tested the autocorrelation model on 8 subjects in laboratory, and compared the respiratory rates detected by noncontact radar with reference contact-type respiratory effort belt. Autocorrelation model showed the effects of reducing the random body movement noise added to Doppler radar's respiration signals. Moreover, the respiratory rate can be rapidly calculated from the first main peak in the autocorrelation waveform within 10 s.

  5. A predictive model of bifunctional transcription factor signaling during embryonic tissue patterning.

    PubMed

    Junker, Jan Philipp; Peterson, Kevin A; Nishi, Yuichi; Mao, Junhao; McMahon, Andrew P; van Oudenaarden, Alexander

    2014-11-24

    Hedgehog signaling controls pattern formation in many vertebrate tissues. The downstream effectors of the pathway are the bifunctional Gli transcription factors, which, depending on hedgehog concentration, act as either transcriptional activators or repressors. Quantitatively understanding the interplay between Gli activator and repressor forms for patterning complex tissues is an open challenge. Here, we describe a reductionist mathematical model for how Gli activators and repressors are integrated in space and time to regulate transcriptional outputs of hedgehog signaling, using the pathway readouts Gli1 and Ptch1 as a model system. Spatially resolved measurements of absolute transcript numbers for these genes allow us to infer spatiotemporal variations of Gli activator and repressor levels. We validate our model by successfully predicting expression changes of Gli1 and Ptch1 in mutants at different developmental stages and in different tissues. Our results provide a starting point for understanding gene regulation by bifunctional transcription factors during mammalian development. PMID:25458012

  6. Rapid and stable measurement of respiratory rate from Doppler radar signals using time domain autocorrelation model.

    PubMed

    Sun, Guanghao; Matsui, Takemi

    2015-01-01

    Noncontact measurement of respiratory rate using Doppler radar will play a vital role in future clinical practice. Doppler radar remotely monitors the tiny chest wall movements induced by respiration activity. The most competitive advantage of this technique is to allow users fully unconstrained with no biological electrode attachments. However, the Doppler radar, unlike other contact-type sensors, is easily affected by the random body movements. In this paper, we proposed a time domain autocorrelation model to process the radar signals for rapid and stable estimation of the respiratory rate. We tested the autocorrelation model on 8 subjects in laboratory, and compared the respiratory rates detected by noncontact radar with reference contact-type respiratory effort belt. Autocorrelation model showed the effects of reducing the random body movement noise added to Doppler radar's respiration signals. Moreover, the respiratory rate can be rapidly calculated from the first main peak in the autocorrelation waveform within 10 s. PMID:26737655

  7. Modular and Stochastic Approaches to Molecular Pathway Models of ATM, TGF beta, and WNT Signaling

    NASA Technical Reports Server (NTRS)

    Cucinotta, Francis A.; O'Neill, Peter; Ponomarev, Artem; Carra, Claudio; Whalen, Mary; Pluth, Janice M.

    2009-01-01

    Deterministic pathway models that describe the biochemical interactions of a group of related proteins, their complexes, activation through kinase, etc. are often the basis for many systems biology models. Low dose radiation effects present a unique set of challenges to these models including the importance of stochastic effects due to the nature of radiation tracks and small number of molecules activated, and the search for infrequent events that contribute to cancer risks. We have been studying models of the ATM, TGF -Smad and WNT signaling pathways with the goal of applying pathway models to the investigation of low dose radiation cancer risks. Modeling challenges include introduction of stochastic models of radiation tracks, their relationships to more than one substrate species that perturb pathways, and the identification of a representative set of enzymes that act on the dominant substrates. Because several pathways are activated concurrently by radiation the development of modular pathway approach is of interest.

  8. Modeling of photocurrent and lag signals in amorphous selenium x-ray detectors

    SciTech Connect

    Siddiquee, Sinchita; Kabir, M. Z.

    2015-07-15

    A mathematical model for transient photocurrent and lag signal in x-ray imaging detectors has been developed by considering charge carrier trapping and detrapping in the energy distributed defect states under exponentially distributed carrier generation across the photoconductor. The model for the transient and steady-state carrier distributions and hence the photocurrent has been developed by solving the carrier continuity equation for both holes and electrons. The residual (commonly known as lag signal) current is modeled by solving the trapping rate equations considering the thermal release and trap filling effects. The model is applied to amorphous selenium (a-Se) detectors for both chest radiography and mammography. The authors analyze the dependence of the residual current on various factors, such as x-ray exposure, applied electric field, and temperature. The electron trapping and detrapping mostly determines the residual current in a-Se detectors. The lag signal is more prominent in chest radiographic detector than in mammographic detectors. The model calculations are compared with the published experimental data and show a very good agreement.

  9. Fractional motion model for characterization of anomalous diffusion from NMR signals.

    PubMed

    Fan, Yang; Gao, Jia-Hong

    2015-07-01

    Measuring molecular diffusion has been used to characterize the properties of living organisms and porous materials. NMR is able to detect the diffusion process in vivo and noninvasively. The fractional motion (FM) model is appropriate to describe anomalous diffusion phenomenon in crowded environments, such as living cells. However, no FM-based NMR theory has yet been established. Here, we present a general formulation of the FM-based NMR signal under the influence of arbitrary magnetic field gradient waveforms. An explicit analytic solution of the stretched exponential decay format for NMR signals with finite-width Stejskal-Tanner bipolar pulse magnetic field gradients is presented. Signals from a numerical simulation matched well with the theoretical prediction. In vivo diffusion-weighted brain images were acquired and analyzed using the proposed theory, and the resulting parametric maps exhibit remarkable contrasts between different brain tissues.

  10. Psychophysical Models for Signal Detection with Time Varying Uncertainty. Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Gai, E.

    1975-01-01

    Psychophysical models for the behavior of the human operator in detection tasks which include change in detectability, correlation between observations and deferred decisions are developed. Classical Signal Detection Theory (SDT) is discussed and its emphasis on the sensory processes is contrasted to decision strategies. The analysis of decision strategies utilizes detection tasks with time varying signal strength. The classical theory is modified to include such tasks and several optimal decision strategies are explored. Two methods of classifying strategies are suggested. The first method is similar to the analysis of ROC curves, while the second is based on the relation between the criterion level (CL) and the detectability. Experiments to verify the analysis of tasks with changes of signal strength are designed. The results show that subjects are aware of changes in detectability and tend to use strategies that involve changes in the CL's.

  11. Accelerometer signal-based human activity recognition using augmented autoregressive model coefficients and artificial neural nets.

    PubMed

    Khan, A M; Lee, Y K; Kim, T S

    2008-01-01

    Automatic recognition of human activities is one of the important and challenging research areas in proactive and ubiquitous computing. In this work, we present some preliminary results of recognizing human activities using augmented features extracted from the activity signals measured using a single triaxial accelerometer sensor and artificial neural nets. The features include autoregressive (AR) modeling coefficients of activity signals, signal magnitude areas (SMA), and title angles (TA). We have recognized four human activities using AR coefficients (ARC) only, ARC with SMA, and ARC with SMA and TA. With the last augmented features, we have achieved the recognition rate above 99% for all four activities including lying, standing, walking, and running. With our proposed technique, real time recognition of some human activities is possible.

  12. Signal detection by human observers: a cutoff reinforcement learning model of categorization decisions under uncertainty.

    PubMed

    Erev, I

    1998-04-01

    Previous experimental examinations of binary categorization decisions have documented robust behavioral regularities that cannot be predicted by signal detection theory (D.M. Green & J.A. Swets, 1966/1988). The present article reviews the known regularities and demonstrates that they can be accounted for by a minimal modification of signal detection theory: the replacement of the "ideal observer" cutoff placement rule with a cutoff reinforcement learning rule. This modification is derived from a cognitive game theoretic analysis (A.E. Roth & I. Erev, 1995). The modified model reproduces all 19 experimental regularities that have been considered. In all cases,it outperforms the original explanations. Some of these previous explanations are based on important concepts such as conservatism, probability matching, and "the gambler's fallacy" that receive new meanings given the current results. Implications for decision-making research and for applications of traditional signal detection theory are discussed.

  13. Fractional motion model for characterization of anomalous diffusion from NMR signals

    NASA Astrophysics Data System (ADS)

    Fan, Yang; Gao, Jia-Hong

    2015-07-01

    Measuring molecular diffusion has been used to characterize the properties of living organisms and porous materials. NMR is able to detect the diffusion process in vivo and noninvasively. The fractional motion (FM) model is appropriate to describe anomalous diffusion phenomenon in crowded environments, such as living cells. However, no FM-based NMR theory has yet been established. Here, we present a general formulation of the FM-based NMR signal under the influence of arbitrary magnetic field gradient waveforms. An explicit analytic solution of the stretched exponential decay format for NMR signals with finite-width Stejskal-Tanner bipolar pulse magnetic field gradients is presented. Signals from a numerical simulation matched well with the theoretical prediction. In vivo diffusion-weighted brain images were acquired and analyzed using the proposed theory, and the resulting parametric maps exhibit remarkable contrasts between different brain tissues.

  14. Theoretical and Experimental Study of Optical Coherence Tomography (OCT) Signals Using an Analytical Transport Model

    SciTech Connect

    Vazquez Villa, A.; Delgado Atencio, J. A.; Vazquez y Montiel, S.; Cunill Rodriguez, M.; Martinez Rodriguez, A. E.; Ramos, J. Castro; Villanueva, A.

    2010-12-07

    Optical coherence tomography (OCT) is a non-invasive low coherent interferometric technique that provides cross-sectional images of turbid media. OCT is based on the classical Michelson interferometer where the mirror of the reference arm is oscillating and the signal arm contains a biological sample. In this work, we analyzed theoretically the heterodyne optical signal adopting the so called extended Huygens-Fresnel principle (EHFP). We use simulated OCT images with known optical properties to test an algorithm developed by ourselves to recover the scattering coefficient and we recovered the scattering coefficient with a relative error less than 5% for noisy signals. In addition, we applied this algorithm to OCT images from phantoms of known optical properties; in this case curves were indistinguishable. A revision of the validity of the analytical model applied to our system should be done.

  15. The Emotion Recognition System Based on Autoregressive Model and Sequential Forward Feature Selection of Electroencephalogram Signals

    PubMed Central

    Hatamikia, Sepideh; Maghooli, Keivan; Nasrabadi, Ali Motie

    2014-01-01

    Electroencephalogram (EEG) is one of the useful biological signals to distinguish different brain diseases and mental states. In recent years, detecting different emotional states from biological signals has been merged more attention by researchers and several feature extraction methods and classifiers are suggested to recognize emotions from EEG signals. In this research, we introduce an emotion recognition system using autoregressive (AR) model, sequential forward feature selection (SFS) and K-nearest neighbor (KNN) classifier using EEG signals during emotional audio-visual inductions. The main purpose of this paper is to investigate the performance of AR features in the classification of emotional states. To achieve this goal, a distinguished AR method (Burg's method) based on Levinson-Durbin's recursive algorithm is used and AR coefficients are extracted as feature vectors. In the next step, two different feature selection methods based on SFS algorithm and Davies–Bouldin index are used in order to decrease the complexity of computing and redundancy of features; then, three different classifiers include KNN, quadratic discriminant analysis and linear discriminant analysis are used to discriminate two and three different classes of valence and arousal levels. The proposed method is evaluated with EEG signals of available database for emotion analysis using physiological signals, which are recorded from 32 participants during 40 1 min audio visual inductions. According to the results, AR features are efficient to recognize emotional states from EEG signals, and KNN performs better than two other classifiers in discriminating of both two and three valence/arousal classes. The results also show that SFS method improves accuracies by almost 10-15% as compared to Davies–Bouldin based feature selection. The best accuracies are %72.33 and %74.20 for two classes of valence and arousal and %61.10 and %65.16 for three classes, respectively. PMID:25298928

  16. A receptor state space model of the insulin signalling system in glucose transport.

    PubMed

    Gray, Catheryn W; Coster, Adelle C F

    2015-12-01

    Insulin is a potent peptide hormone that regulates glucose levels in the blood. Insulin-sensitive cells respond to insulin stimulation with the translocation of glucose transporter 4 (GLUT4) to the plasma membrane (PM), enabling the clearance of glucose from the blood. Defects in this process can give rise to insulin resistance and ultimately diabetes. One widely cited model of insulin signalling leading to glucose transport is that of Sedaghat et al. (2002) Am. J. Physiol. Endocrinol. Metab. 283, E1084-E1101. Consisting of 20 deterministic ordinary differential equations (ODEs), it is the most comprehensive model of insulin signalling to date. However, the model possesses some major limitations, including the non-conservation of key components. In the current work, we detail mathematical and sensitivity analyses of the Sedaghat model. Based on the results of these analyses, we propose a reduced state space model of the insulin receptor subsystem. This reduced model maintains the input-output relation of the original model but is computationally more efficient, analytically tractable and resolves some of the limitations of the Sedaghat model.

  17. Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry

    PubMed Central

    Polanski, Andrzej; Marczyk, Michal; Pietrowska, Monika; Widlak, Piotr; Polanska, Joanna

    2015-01-01

    Mixture - modeling of mass spectra is an approach with many potential applications including peak detection and quantification, smoothing, de-noising, feature extraction and spectral signal compression. However, existing algorithms do not allow for automated analyses of whole spectra. Therefore, despite highlighting potential advantages of mixture modeling of mass spectra of peptide/protein mixtures and some preliminary results presented in several papers, the mixture modeling approach was so far not developed to the stage enabling systematic comparisons with existing software packages for proteomic mass spectra analyses. In this paper we present an efficient algorithm for Gaussian mixture modeling of proteomic mass spectra of different types (e.g., MALDI-ToF profiling, MALDI-IMS). The main idea is automated partitioning of protein mass spectral signal into fragments. The obtained fragments are separately decomposed into Gaussian mixture models. The parameters of the mixture models of fragments are then aggregated to form the mixture model of the whole spectrum. We compare the elaborated algorithm to existing algorithms for peak detection and we demonstrate improvements of peak detection efficiency obtained by using Gaussian mixture modeling. We also show applications of the elaborated algorithm to real proteomic datasets of low and high resolution. PMID:26230717

  18. Models of signalling networks – what cell biologists can gain from them and give to them

    PubMed Central

    Janes, Kevin A.; Lauffenburger, Douglas A.

    2013-01-01

    Summary Computational models of cell signalling are perceived by many biologists to be prohibitively complicated. Why do math when you can simply do another experiment? Here, we explain how conceptual models, which have been formulated mathematically, have provided insights that directly advance experimental cell biology. In the past several years, models have influenced the way we talk about signalling networks, how we monitor them, and what we conclude when we perturb them. These insights required wet-lab experiments but would not have arisen without explicit computational modelling and quantitative analysis. Today, the best modellers are cross-trained investigators in experimental biology who work closely with collaborators but also undertake experimental work in their own laboratories. Biologists would benefit by becoming conversant in core principles of modelling in order to identify when a computational model could be a useful complement to their experiments. Although the mathematical foundations of a model are useful to appreciate its strengths and weaknesses, they are not required to test or generate a worthwhile biological hypothesis computationally. PMID:23720376

  19. Classical signal model reproducing quantum probabilities for single and coincidence detections

    NASA Astrophysics Data System (ADS)

    Khrennikov, Andrei; Nilsson, Börje; Nordebo, Sven

    2012-05-01

    We present a simple classical (random) signal model reproducing Born's rule. The crucial point of our approach is that the presence of detector's threshold and calibration procedure have to be treated not as simply experimental technicalities, but as the basic counterparts of the theoretical model. We call this approach threshold signal detection model (TSD). The experiment on coincidence detection which was done by Grangier in 1986 [22] played a crucial role in rejection of (semi-)classical field models in favour of quantum mechanics (QM): impossibility to resolve the wave-particle duality in favour of a purely wave model. QM predicts that the relative probability of coincidence detection, the coefficient g(2) (0), is zero (for one photon states), but in (semi-)classical models g(2)(0) >= 1. In TSD the coefficient g(2)(0) decreases as 1/ɛ2d, where ɛd > 0 is the detection threshold. Hence, by increasing this threshold an experimenter can make the coefficient g(2) (0) essentially less than 1. The TSD-prediction can be tested experimentally in new Grangier type experiments presenting a detailed monitoring of dependence of the coefficient g(2)(0) on the detection threshold. Structurally our model has some similarity with the prequantum model of Grossing et al. Subquantum stochasticity is composed of the two counterparts: a stationary process in the space of internal degrees of freedom and the random walk type motion describing the temporal dynamics.

  20. Cascaded analysis of signal and noise propagation through a heterogeneous breast model

    SciTech Connect

    Mainprize, James G.; Yaffe, Martin J.

    2010-10-15

    Purpose: The detectability of lesions in radiographic images can be impaired by patterns caused by the surrounding anatomic structures. The presence of such patterns is often referred to as anatomic noise. Others have previously extended signal and noise propagation theory to include variable background structure as an additional noise term and used in simulations for analysis by human and ideal observers. Here, the analytic forms of the signal and noise transfer are derived to obtain an exact expression for any input random distribution and the ''power law'' filter used to generate the texture of the tissue distribution. Methods: A cascaded analysis of propagation through a heterogeneous model is derived for x-ray projection through simulated heterogeneous backgrounds. This is achieved by considering transmission through the breast as a correlated amplification point process. The analytic forms of the cascaded analysis were compared to monoenergetic Monte Carlo simulations of x-ray propagation through power law structured backgrounds. Results: As expected, it was found that although the quantum noise power component scales linearly with the x-ray signal, the anatomic noise will scale with the square of the x-ray signal. There was a good agreement between results obtained using analytic expressions for the noise power and those from Monte Carlo simulations for different background textures, random input functions, and x-ray fluence. Conclusions: Analytic equations for the signal and noise properties of heterogeneous backgrounds were derived. These may be used in direct analysis or as a tool to validate simulations in evaluating detectability.

  1. A model for signal transduction during quorum sensing in Vibrio harveyi

    NASA Astrophysics Data System (ADS)

    Banik, Suman K.; Fenley, Andrew T.; Kulkarni, Rahul V.

    2009-12-01

    We present a framework for analyzing luminescence regulation during quorum sensing in the bioluminescent bacterium Vibrio harveyi. Using a simplified model for signal transduction in the quorum sensing pathway, we identify key dimensionless parameters that control the system's response. These parameters are estimated using experimental data on luminescence phenotypes for different mutant strains. The corresponding model predictions are consistent with results from other experiments which did not serve as input for determining model parameters. Furthermore, the proposed framework leads to novel testable predictions for luminescence phenotypes and for responses of the network to different perturbations.

  2. Purely stochastic binary decisions in cell signaling models without underlying deterministic bistabilities

    PubMed Central

    Artyomov, Maxim N.; Das, Jayajit; Kardar, Mehran; Chakraborty, Arup K.

    2007-01-01

    Detection of different extracellular stimuli leading to functionally distinct outcomes is ubiquitous in cell biology, and is often mediated by differential regulation of positive and negative feedback loops that are a part of the signaling network. In some instances, these cellular responses are stimulated by small numbers of molecules, and so stochastic effects could be important. Therefore, we studied the influence of stochastic fluctuations on a simple signaling model with dueling positive and negative feedback loops. The class of models we have studied is characterized by single deterministic steady states for all parameter values, but the stochastic response is bimodal; a behavior that is distinctly different from models studied in the context of gene regulation. For example, when positive and negative regulation is roughly balanced, a unique deterministic steady state with an intermediate value for the amount of a downstream signaling product is found. However, for small numbers of signaling molecules, stochastic effects result in a bimodal distribution for this quantity, with neither mode corresponding to the deterministic solution; i.e., cells are in “on” or “off” states, not in some intermediate state. For a large number of molecules, the stochastic solution converges to the mean-field result. When fluctuations are important, we find that signal output scales with control parameters “anomalously” compared with mean-field predictions. The necessary and sufficient conditions for the phenomenon we report are quite common. So, our findings are expected to be of broad relevance, and suggest that stochastic effects can enable binary cellular decisions. PMID:18025473

  3. The volcanic signal in Goddard Institute for Space Studies three-dimensional model simulations

    SciTech Connect

    Robock, A.; Liu, Y. )

    1994-01-01

    Transient calculations of the Goddard Institute for Space Studies general circulation model for the climatic signal of volcanic eruptions are analyzed. By compositing the output for two different volcanoes for scenario A and five different volcanos for scenario B, the natural variability is suppressed and the volcanic signals are extracted. Significant global means surface air temperature cooling and precipitation reduction are found for several years following the eruptions, with larger changes in the Northern Hemisphere (NH) than in the Southern Hemisphere. The global-average temperature response lasts for more than four years, but the precipitation response disappears after three years. The largest cooling in the model occurs in the NH summer of the year after spring eruptions. Significant zonal-average temperature reductions begin in the tropics immediately after the eruptions and extend to 45[degrees]S-45[degrees]N in the year after the eruptions. In the second year, cooling is still seen from 30[degrees]S to 30[degrees]N. Because of the low variability in this model as compared to the real world, these signals may appear more significant here than they would be attempting to isolate them using real data. The results suggest that volcanoes can enhance the drought in the Sahel. No evidence was found that stratospheric aerosols from the low-latitude volcanic eruptions can trigger ENSO events in this model.

  4. Model-based sediment classification using single-beam echosounder signals.

    PubMed

    Snellen, Mirjam; Siemes, Kerstin; Simons, Dick G

    2011-05-01

    Acoustic remote sensing techniques for mapping sediment properties are of interest due to their low costs and high coverage. Model-based approaches directly couple the acoustic signals to sediment properties. Despite the limited coverage of the single-beam echosounder (SBES), it is widely used. Having available model-based SBES classification tools, therefore, is important. Here, two model-based approaches of different complexity are compared to investigate their practical applicability. The first approach is based on matching the echo envelope. It maximally exploits the information available in the signal but requires complex modeling and optimization. To minimize computational costs, the efficient differential evolution method is used. The second approach reduces the information of the signal to energy only and directly relates this to the reflection coefficient to obtain quantitative information about the sediment parameters. The first approach provides information over a variety of sediment types. In addition to sediment mean grain size, it also provides estimates for the spectral strength and volume scattering parameter. The need to account for all three parameters is demonstrated, justifying computational expenses. In the second approach, the lack of information on these parameters and the limited SBES beamwidth are demonstrated to hamper the conversion of echo energy to reflection coefficient. PMID:21568391

  5. Model-based sediment classification using single-beam echosounder signals.

    PubMed

    Snellen, Mirjam; Siemes, Kerstin; Simons, Dick G

    2011-05-01

    Acoustic remote sensing techniques for mapping sediment properties are of interest due to their low costs and high coverage. Model-based approaches directly couple the acoustic signals to sediment properties. Despite the limited coverage of the single-beam echosounder (SBES), it is widely used. Having available model-based SBES classification tools, therefore, is important. Here, two model-based approaches of different complexity are compared to investigate their practical applicability. The first approach is based on matching the echo envelope. It maximally exploits the information available in the signal but requires complex modeling and optimization. To minimize computational costs, the efficient differential evolution method is used. The second approach reduces the information of the signal to energy only and directly relates this to the reflection coefficient to obtain quantitative information about the sediment parameters. The first approach provides information over a variety of sediment types. In addition to sediment mean grain size, it also provides estimates for the spectral strength and volume scattering parameter. The need to account for all three parameters is demonstrated, justifying computational expenses. In the second approach, the lack of information on these parameters and the limited SBES beamwidth are demonstrated to hamper the conversion of echo energy to reflection coefficient.

  6. Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies

    PubMed Central

    Kolch, Walter; Kholodenko, Boris N.; Ambrosi, Cristina De; Barla, Annalisa; Biganzoli, Elia M.; Nencioni, Alessio; Patrone, Franco; Ballestrero, Alberto; Zoppoli, Gabriele; Verri, Alessandro; Parodi, Silvio

    2015-01-01

    The interconnected network of pathways downstream of the TGFβ, WNT and EGF-families of receptor ligands play an important role in colorectal cancer pathogenesis. We studied and implemented dynamic simulations of multiple downstream pathways and described the section of the signaling network considered as a Molecular Interaction Map (MIM). Our simulations used Ordinary Differential Equations (ODEs), which involved 447 reactants and their interactions. Starting from an initial “physiologic condition”, the model can be adapted to simulate individual pathologic cancer conditions implementing alterations/mutations in relevant onco-proteins. We verified some salient model predictions using the mutated colorectal cancer lines HCT116 and HT29. We measured the amount of MYC and CCND1 mRNAs and AKT and ERK phosphorylated proteins, in response to individual or combination onco-protein inhibitor treatments. Experimental and simulation results were well correlated. Recent independently published results were also predicted by our model. Even in the presence of an approximate and incomplete signaling network information, a predictive dynamic modeling seems already possible. An important long term road seems to be open and can be pursued further, by incremental steps, toward even larger and better parameterized MIMs. Personalized treatment strategies with rational associations of signaling-proteins inhibitors, could become a realistic goal. PMID:25671297

  7. BrainSignals Revisited: Simplifying a Computational Model of Cerebral Physiology

    PubMed Central

    Caldwell, Matthew; Hapuarachchi, Tharindi; Highton, David; Elwell, Clare; Smith, Martin; Tachtsidis, Ilias

    2015-01-01

    Multimodal monitoring of brain state is important both for the investigation of healthy cerebral physiology and to inform clinical decision making in conditions of injury and disease. Near-infrared spectroscopy is an instrument modality that allows non-invasive measurement of several physiological variables of clinical interest, notably haemoglobin oxygenation and the redox state of the metabolic enzyme cytochrome c oxidase. Interpreting such measurements requires the integration of multiple signals from different sources to try to understand the physiological states giving rise to them. We have previously published several computational models to assist with such interpretation. Like many models in the realm of Systems Biology, these are complex and dependent on many parameters that can be difficult or impossible to measure precisely. Taking one such model, BrainSignals, as a starting point, we have developed several variant models in which specific regions of complexity are substituted with much simpler linear approximations. We demonstrate that model behaviour can be maintained whilst achieving a significant reduction in complexity, provided that the linearity assumptions hold. The simplified models have been tested for applicability with simulated data and experimental data from healthy adults undergoing a hypercapnia challenge, but relevance to different physiological and pathophysiological conditions will require specific testing. In conditions where the simplified models are applicable, their greater efficiency has potential to allow their use at the bedside to help interpret clinical data in near real-time. PMID:25961297

  8. Signal processing Model/Method for Recovering Acoustic Reflectivity of Spot Weld

    2005-09-08

    Until recently, U.S. auto manufacturers have inspected the veracity of welds in the auto bodies they build by using destructive tear-down, which typically results in more than $1 M of scrappage per plant per year. Much of this expense could possibly be avoided with a nondestructive technique (and 100% instead of 1% inspection could be achieved). Recent advances in ultrasound probes promise to provide a sufficiently accurate non-destructive evaluation technique, but the necessary signal processingmore » has not yet been developed. This disclosure describes a signal processing model and method useful for diagnosing the veracity of spot welds between two sheets of the same thickness from ultrasound signals Standard systems theory describes a signal as a convolution of a transducer function, h(t), and an impulse train (beta(t), tau(t)) [1] (see Eq. (1) attached). With a Gaussian wavelet as a transducer function, this model describes the signal from an ultrasound probe quite well, and the literature provides many methods for "deconvolution," for recovery of the impulse train from the signal [see e.g., 2-3]. What is novel about the technique disclosed is the model that describes the impulse train as a function of reflectivity, the share of energy incident on the interface that is reflected, and that allows the recovery of its estimated value. The reflectivity estimate provides an ideal indicator of weld veracity, compressing each signal into a single value between 0 and 1, which can then be displayed as a 2d greyscale or colormap of the weld. The model describing the system is attached as Eqs. (2). These equations account for the energy in the probe-side and opposite sheets. In each period, this energy is a sum of that reflected from the same sheet plus that transmitted from the opposite (dampened by material attenuation at rate a). This model is consistent with physical first principles (in particular the First and Second Laws of Thermodynamics) and has been verified

  9. Numerical study of a cylinder model of the diffusion MRI signal for neuronal dendrite trees.

    PubMed

    Van Nguyen, Dang; Grebenkov, Denis; Le Bihan, Denis; Li, Jing-Rebecca

    2015-03-01

    We study numerically how the neuronal dendrite tree structure can affect the diffusion magnetic resonance imaging (dMRI) signal in brain tissue. For a large set of randomly generated dendrite trees, synthetic dMRI signals are computed and fitted to a cylinder model to estimate the effective longitudinal diffusivity D(L) in the direction of neurites. When the dendrite branches are short compared to the diffusion length, D(L) depends significantly on the ratio between the average branch length and the diffusion length. In turn, D(L) has very weak dependence on the distribution of branch lengths and orientations of a dendrite tree, and the number of branches per node. We conclude that the cylinder model which ignores the connectivity of the dendrite tree, can still be adapted to describe the apparent diffusion coefficient in brain tissue. PMID:25681802

  10. Serotonergic signalling suppresses ataxin 3 aggregation and neurotoxicity in animal models of Machado-Joseph disease.

    PubMed

    Teixeira-Castro, Andreia; Jalles, Ana; Esteves, Sofia; Kang, Soosung; da Silva Santos, Liliana; Silva-Fernandes, Anabela; Neto, Mário F; Brielmann, Renée M; Bessa, Carlos; Duarte-Silva, Sara; Miranda, Adriana; Oliveira, Stéphanie; Neves-Carvalho, Andreia; Bessa, João; Summavielle, Teresa; Silverman, Richard B; Oliveira, Pedro; Morimoto, Richard I; Maciel, Patrícia

    2015-11-01

    Polyglutamine diseases are a class of dominantly inherited neurodegenerative disorders for which there is no effective treatment. Here we provide evidence that activation of serotonergic signalling is beneficial in animal models of Machado-Joseph disease. We identified citalopram, a selective serotonin reuptake inhibitor, in a small molecule screen of FDA-approved drugs that rescued neuronal dysfunction and reduced aggregation using a Caenorhabditis elegans model of mutant ataxin 3-induced neurotoxicity. MOD-5, the C. elegans orthologue of the serotonin transporter and cellular target of citalopram, and the serotonin receptors SER-1 and SER-4 were strong genetic modifiers of ataxin 3 neurotoxicity and necessary for therapeutic efficacy. Moreover, chronic treatment of CMVMJD135 mice with citalopram significantly reduced ataxin 3 neuronal inclusions and astrogliosis, rescued diminished body weight and strikingly ameliorated motor symptoms. These results suggest that small molecule modulation of serotonergic signalling represents a promising therapeutic target for Machado-Joseph disease.

  11. A comparison of signal detection theory to the objective threshold/strategic model of unconscious perception.

    PubMed

    Haase, Steven J; Fisk, Gary D

    2011-08-01

    A key problem in unconscious perception research is ruling out the possibility that weak conscious awareness of stimuli might explain the results. In the present study, signal detection theory was compared with the objective threshold/strategic model as explanations of results for detection and identification sensitivity in a commonly used unconscious perception task. In the task, 64 undergraduate participants detected and identified one of four briefly displayed, visually masked letters. Identification was significantly above baseline (i.e., proportion correct > .25) at the highest detection confidence rating. This result is most consistent with signal detection theory's continuum of sensory states and serves as a possible index of conscious perception. However, there was limited support for the other model in the form of a predicted "looker's inhibition" effect, which produced identification performance that was significantly below baseline. One additional result, an interaction between the target stimulus and type of mask, raised concerns for the generality of unconscious perception effects.

  12. Model-based synthesis of locally contingent responses to global market signals

    NASA Astrophysics Data System (ADS)

    Magliocca, N. R.

    2015-12-01

    Rural livelihoods and the land systems on which they depend are increasingly influenced by distant markets through economic globalization. Place-based analyses of land and livelihood system sustainability must then consider both proximate and distant influences on local decision-making. Thus, advancing land change theory in the context of economic globalization calls for a systematic understanding of the general processes as well as local contingencies shaping local responses to global signals. Synthesis of insights from place-based case studies of land and livelihood change is a path forward for developing such systematic knowledge. This paper introduces a model-based synthesis approach to investigating the influence of local socio-environmental and agent-level factors in mediating land-use and livelihood responses to changing global market signals. A generalized agent-based modeling framework is applied to six case-study sites that differ in environmental conditions, market access and influence, and livelihood settings. The largest modeled land conversions and livelihood transitions to market-oriented production occurred in sties with relatively productive agricultural land and/or with limited livelihood options. Experimental shifts in the distributions of agents' risk tolerances generally acted to attenuate or amplify responses to changes in global market signals. Importantly, however, responses of agents at different points in the risk tolerance distribution varied widely, with the wealth gap growing wider between agents with higher or lower risk tolerance. These results demonstrate model-based synthesis is a promising approach to overcome many of the challenges of current synthesis methods in land change science, and to identify generalized as well as locally contingent responses to global market signals.

  13. Automated Detection and Classification of Rockfall Induced Seismic Signals with Hidden-Markov-Models

    NASA Astrophysics Data System (ADS)

    Zeckra, M.; Hovius, N.; Burtin, A.; Hammer, C.

    2015-12-01

    Originally introduced in speech recognition, Hidden Markov Models are applied in different research fields of pattern recognition. In seismology, this technique has recently been introduced to improve common detection algorithms, like STA/LTA ratio or cross-correlation methods. Mainly used for the monitoring of volcanic activity, this study is one of the first applications to seismic signals induced by geomorphologic processes. With an array of eight broadband seismometers deployed around the steep Illgraben catchment (Switzerland) with high-level erosion, we studied a sequence of landslides triggered over a period of several days in winter. A preliminary manual classification led us to identify three main seismic signal classes that were used as a start for the HMM automated detection and classification: (1) rockslide signal, including a failure source and the debris mobilization along the slope, (2) rockfall signal from the remobilization of debris along the unstable slope, and (3) single cracking signal from the affected cliff observed before the rockslide events. Besides the ability to classify the whole dataset automatically, the HMM approach reflects the origin and the interactions of the three signal classes, which helps us to understand this geomorphic crisis and the possible triggering mechanisms for slope processes. The temporal distribution of crack events (duration > 5s, frequency band [2-8] Hz) follows an inverse Omori law, leading to the catastrophic behaviour of the failure mechanisms and the interest for warning purposes in rockslide risk assessment. Thanks to a dense seismic array and independent weather observations in the landslide area, this dataset also provides information about the triggering mechanisms, which exhibit a tight link between rainfall and freezing level fluctuations.

  14. A micro-pool model for decision-related signals in visual cortical areas.

    PubMed

    Parker, Andrew J

    2013-01-01

    The study of sensory signaling in the visual cortex has been greatly advanced by the recording of neural activity simultaneously with the performance of a specific psychophysical task. Individual nerve cells may also increase their firing leading up to the particular choice or decision made on a single psychophysical trial. Understanding these signals is important because they have been taken as evidence that a particular nerve cell or group of nerve cells in the cortex is involved in the formation of the perceptual decision ultimately signaled by the organism. However, recent analyses show that the size of a decision-related change in firing in a particular neuron is not a secure basis for concluding anything about the contribution of a single neuron to the formation of a decision: rather the size of the decision-related firing is expected to be dominated by the extent to which the activation of a single neuron is correlated with the firing of the pool of neurons. The critical question becomes what defines membership of a population of neurons. This article presents the proposal that groups of neurons are naturally linked together by their connectivity, which in turn reflects the previous history of sensory stimulations. When a new psychophysical task is performed, a group of neurons relevant to the judgment becomes involved because the firing of some neurons in that group is strongly relevant to the task. This group of neurons is called a micro-pool. This article examines the consequences of such a proposal within the visual nervous system. The main focus is on the signals available from single neurons, but it argued that models of choice-related signals must scale up to larger numbers of neurons because MRI and MEG studies also show evidence of similar choice signals.

  15. Key signalling nodes in mammary gland development and cancer. Mitogen-activated protein kinase signalling in experimental models of breast cancer progression and in mammary gland development.

    PubMed

    Whyte, Jacqueline; Bergin, Orla; Bianchi, Alessandro; McNally, Sara; Martin, Finian

    2009-01-01

    Seven classes of mitogen-activated protein kinase (MAPK) intracellular signalling cascades exist, four of which are implicated in breast disease and function in mammary epithelial cells. These are the extracellular regulated kinase (ERK)1/2 pathway, the ERK5 pathway, the p38 pathway and the c-Jun N-terminal kinase (JNK) pathway. In some forms of human breast cancer and in many experimental models of breast cancer progression, signalling through the ERK1/2 pathway, in particular, has been implicated as being important. We review the influence of ERK1/2 activity on the organised three-dimensional association of mammary epithelial cells, and in models of breast cancer cell invasion. We assess the importance of epidermal growth factor receptor family signalling through ERK1/2 in models of breast cancer progression and the influence of ERK1/2 on its substrate, the oestrogen receptor, in this context. In parallel, we consider the importance of these MAPK-centred signalling cascades during the cycle of mammary gland development. Although less extensively studied, we highlight the instances of signalling through the p38, JNK and ERK5 pathways involved in breast cancer progression and mammary gland development.

  16. Dysfunctional cardiac mitochondrial bioenergetic, lipidomic, and signaling in a murine model of Barth syndrome[S

    PubMed Central

    Kiebish, Michael A.; Yang, Kui; Liu, Xinping; Mancuso, David J.; Guan, Shaoping; Zhao, Zhongdan; Sims, Harold F.; Cerqua, Rebekah; Cade, W. Todd; Han, Xianlin; Gross, Richard W.

    2013-01-01

    Barth syndrome is a complex metabolic disorder caused by mutations in the mitochondrial transacylase tafazzin. Recently, an inducible tafazzin shRNA knockdown mouse model was generated to deconvolute the complex bioenergetic phenotype of this disease. To investigate the underlying cause of hemodynamic dysfunction in Barth syndrome, we interrogated the cardiac structural and signaling lipidome of this mouse model as well as its myocardial bioenergetic phenotype. A decrease in the distribution of cardiolipin molecular species and robust increases in monolysocardiolipin and dilysocardiolipin were demonstrated. Additionally, the contents of choline and ethanolamine glycerophospholipid molecular species containing precursors for lipid signaling at the sn-2 position were altered. Lipidomic analyses revealed specific dysregulation of HETEs and prostanoids, as well as oxidized linoleic and docosahexaenoic metabolites. Bioenergetic interrogation uncovered differential substrate utilization as well as decreases in Complex III and V activities. Transgenic expression of cardiolipin synthase or iPLA2γ ablation in tafazzin-deficient mice did not rescue the observed phenotype. These results underscore the complex nature of alterations in cardiolipin metabolism mediated by tafazzin loss of function. Collectively, we identified specific lipidomic, bioenergetic, and signaling alterations in a murine model that parallel those of Barth syndrome thereby providing novel insights into the pathophysiology of this debilitating disease. PMID:23410936

  17. Comparing signaling networks between normal and transformed hepatocytes using discrete logical models.

    PubMed

    Saez-Rodriguez, Julio; Alexopoulos, Leonidas G; Zhang, Mingsheng; Morris, Melody K; Lauffenburger, Douglas A; Sorger, Peter K

    2011-08-15

    Substantial effort in recent years has been devoted to constructing and analyzing large-scale gene and protein networks on the basis of "omic" data and literature mining. These interaction graphs provide valuable insight into the topologies of complex biological networks but are rarely context specific and cannot be used to predict the responses of cell signaling proteins to specific ligands or drugs. Conversely, traditional approaches to analyzing cell signaling are narrow in scope and cannot easily make use of network-level data. Here, we combine network analysis and functional experimentation by using a hybrid approach in which graphs are converted into simple mathematical models that can be trained against biochemical data. Specifically, we created Boolean logic models of immediate-early signaling in liver cells by training a literature-based prior knowledge network against biochemical data obtained from primary human hepatocytes and 4 hepatocellular carcinoma cell lines exposed to combinations of cytokines and small-molecule kinase inhibitors. Distinct families of models were recovered for each cell type, and these families clustered topologically into normal and diseased sets.

  18. Spectral models of additive and modulation noise in speech and phonatory excitation signals

    NASA Astrophysics Data System (ADS)

    Schoentgen, Jean

    2003-01-01

    The article presents spectral models of additive and modulation noise in speech. The purpose is to learn about the causes of noise in the spectra of normal and disordered voices and to gauge whether the spectral properties of the perturbations of the phonatory excitation signal can be inferred from the spectral properties of the speech signal. The approach to modeling consists of deducing the Fourier series of the perturbed speech, assuming that the Fourier series of the noise and of the clean monocycle-periodic excitation are known. The models explain published data, take into account the effects of supraglottal tremor, demonstrate the modulation distortion owing to vocal tract filtering, establish conditions under which noise cues of different speech signals may be compared, and predict the impossibility of inferring the spectral properties of the frequency modulating noise from the spectral properties of the frequency modulation noise (e.g., phonatory jitter and frequency tremor). The general conclusion is that only phonatory frequency modulation noise is spectrally relevant. Other types of noise in speech are either epiphenomenal, or their spectral effects are masked by the spectral effects of frequency modulation noise.

  19. Estimation of temporal gait parameters using Bayesian models on acceleration signals.

    PubMed

    López-Nava, I H; Muñoz-Meléndez, A; Pérez Sanpablo, A I; Alessi Montero, A; Quiñones Urióstegui, I; Núñez Carrera, L

    2016-01-01

    The purpose of this study is to develop a system capable of performing calculation of temporal gait parameters using two low-cost wireless accelerometers and artificial intelligence-based techniques as part of a larger research project for conducting human gait analysis. Ten healthy subjects of different ages participated in this study and performed controlled walking tests. Two wireless accelerometers were placed on their ankles. Raw acceleration signals were processed in order to obtain gait patterns from characteristic peaks related to steps. A Bayesian model was implemented to classify the characteristic peaks into steps or nonsteps. The acceleration signals were segmented based on gait events, such as heel strike and toe-off, of actual steps. Temporal gait parameters, such as cadence, ambulation time, step time, gait cycle time, stance and swing phase time, simple and double support time, were estimated from segmented acceleration signals. Gait data-sets were divided into two groups of ages to test Bayesian models in order to classify the characteristic peaks. The mean error obtained from calculating the temporal gait parameters was 4.6%. Bayesian models are useful techniques that can be applied to classification of gait data of subjects at different ages with promising results.

  20. Small signal modeling of AlGaN/GaN HEMTs with consideration of CPW capacitances

    NASA Astrophysics Data System (ADS)

    Jiangfeng, Du; Peng, Xu; Kang, Wang; Chenggong, Yin; Yang, Liu; Zhihong, Feng; Shaobo, Dun; Qi, Yu

    2015-03-01

    Given the coplanar waveguide (CPW) effect on AlGaN/GaN high electron mobility transistors at a high frequency, the traditional equivalent circuit model cannot accurately describe the electrical characteristics of the device. The admittance of CPW capacitances is large when the frequency is higher than 40 GHz; its impact on the device cannot be ignored. In this study, a small-signal equivalent circuit model considering CPW capacitance is provided. To verify the model, S-parameters are obtained from the modeling and measurements. A good agreement is observed between the simulation and measurement results, indicating the reliability of the model. Project supported by the National Natural Science Foundation of China (Nos. 61376078, 61274086) and the Fundamental Research Funds for the Central Universities of China (No. ZYGX2012J041).

  1. A Physiological Signal Transmission Model to be Used for Specific Diagnosis of Cochlear Impairments

    NASA Astrophysics Data System (ADS)

    Saremi, Amin; Stenfelt, Stefan

    2011-11-01

    Many of the sophisticated characteristics of human auditory system are attributed to cochlea. Also, most of patients with a hearing loss suffer from impairments that originate from cochlea (sensorineural). Despite this, today's clinical diagnosis methods do not probe the specific origins of such cochlear lesions. The aim of this research is to introduce a physiological signal transmission model to be clinically used as a tool for diagnosis of cochlear losses. This model enables simulation of different bio-mechano-electrical processes which occur in the auditory organ of Corti inside the cochlea. What makes this model different from many available computational models is its loyalty to physiology since the ultimate goal is to model each single physiological phenomenon. This includes passive BM vibration, outer hair cells' performances such as nonlinear mechanoelectrical transduction (MET), active amplifications by somatic motor, as well as vibration to neural conversion at the inner hair cells.

  2. Mathematical model to generate near-periodic human jumping force signals

    NASA Astrophysics Data System (ADS)

    Racic, V.; Pavic, A.

    2010-01-01

    A mathematical modelling procedure has been developed to generate synthetic vertical force signals induced by a single person jumping. The ability to replicate much of the temporal and spectral features of real jumping loads give this model a definite advantage over the conventional half-sine models coupled with Fourier series analysis. This includes modelling of the omnipresent lack of symmetry of individual jumping pulses and jump-by-jump variations in amplitudes and timing. The model therefore belongs to a new generation of synthetic narrowband jumping loads that simulate reality better. The proposed mathematical concept for characterisation of irregular jumping pulses may be utilised in vibration serviceability assessment of civil engineering assembly structures, such as grandstands, footbridges and concert or gym floors, to estimate realistic dynamic structural response due to people jumping.

  3. Multiple Drug Treatments That Increase cAMP Signaling Restore Long-Term Memory and Aberrant Signaling in Fragile X Syndrome Models.

    PubMed

    Choi, Catherine H; Schoenfeld, Brian P; Bell, Aaron J; Hinchey, Joseph; Rosenfelt, Cory; Gertner, Michael J; Campbell, Sean R; Emerson, Danielle; Hinchey, Paul; Kollaros, Maria; Ferrick, Neal J; Chambers, Daniel B; Langer, Steven; Sust, Steven; Malik, Aatika; Terlizzi, Allison M; Liebelt, David A; Ferreiro, David; Sharma, Ali; Koenigsberg, Eric; Choi, Richard J; Louneva, Natalia; Arnold, Steven E; Featherstone, Robert E; Siegel, Steven J; Zukin, R Suzanne; McDonald, Thomas V; Bolduc, Francois V; Jongens, Thomas A; McBride, Sean M J

    2016-01-01

    Fragile X is the most common monogenic disorder associated with intellectual disability (ID) and autism spectrum disorders (ASD). Additionally, many patients are afflicted with executive dysfunction, ADHD, seizure disorder and sleep disturbances. Fragile X is caused by loss of FMRP expression, which is encoded by the FMR1 gene. Both the fly and mouse models of fragile X are also based on having no functional protein expression of their respective FMR1 homologs. The fly model displays well defined cognitive impairments and structural brain defects and the mouse model, although having subtle behavioral defects, has robust electrophysiological phenotypes and provides a tool to do extensive biochemical analysis of select brain regions. Decreased cAMP signaling has been observed in samples from the fly and mouse models of fragile X as well as in samples derived from human patients. Indeed, we have previously demonstrated that strategies that increase cAMP signaling can rescue short term memory in the fly model and restore DHPG induced mGluR mediated long term depression (LTD) in the hippocampus to proper levels in the mouse model (McBride et al., 2005; Choi et al., 2011, 2015). Here, we demonstrate that the same three strategies used previously with the potential to be used clinically, lithium treatment, PDE-4 inhibitor treatment or mGluR antagonist treatment can rescue long term memory in the fly model and alter the cAMP signaling pathway in the hippocampus of the mouse model. PMID:27445731

  4. Multiple Drug Treatments That Increase cAMP Signaling Restore Long-Term Memory and Aberrant Signaling in Fragile X Syndrome Models

    PubMed Central

    Choi, Catherine H.; Schoenfeld, Brian P.; Bell, Aaron J.; Hinchey, Joseph; Rosenfelt, Cory; Gertner, Michael J.; Campbell, Sean R.; Emerson, Danielle; Hinchey, Paul; Kollaros, Maria; Ferrick, Neal J.; Chambers, Daniel B.; Langer, Steven; Sust, Steven; Malik, Aatika; Terlizzi, Allison M.; Liebelt, David A.; Ferreiro, David; Sharma, Ali; Koenigsberg, Eric; Choi, Richard J.; Louneva, Natalia; Arnold, Steven E.; Featherstone, Robert E.; Siegel, Steven J.; Zukin, R. Suzanne; McDonald, Thomas V.; Bolduc, Francois V.; Jongens, Thomas A.; McBride, Sean M. J.

    2016-01-01

    Fragile X is the most common monogenic disorder associated with intellectual disability (ID) and autism spectrum disorders (ASD). Additionally, many patients are afflicted with executive dysfunction, ADHD, seizure disorder and sleep disturbances. Fragile X is caused by loss of FMRP expression, which is encoded by the FMR1 gene. Both the fly and mouse models of fragile X are also based on having no functional protein expression of their respective FMR1 homologs. The fly model displays well defined cognitive impairments and structural brain defects and the mouse model, although having subtle behavioral defects, has robust electrophysiological phenotypes and provides a tool to do extensive biochemical analysis of select brain regions. Decreased cAMP signaling has been observed in samples from the fly and mouse models of fragile X as well as in samples derived from human patients. Indeed, we have previously demonstrated that strategies that increase cAMP signaling can rescue short term memory in the fly model and restore DHPG induced mGluR mediated long term depression (LTD) in the hippocampus to proper levels in the mouse model (McBride et al., 2005; Choi et al., 2011, 2015). Here, we demonstrate that the same three strategies used previously with the potential to be used clinically, lithium treatment, PDE-4 inhibitor treatment or mGluR antagonist treatment can rescue long term memory in the fly model and alter the cAMP signaling pathway in the hippocampus of the mouse model. PMID:27445731

  5. Source Term Estimates of Radioxenon Released from the BaTek Medical Isotope Production Facility Using External Measured Air Concentrations

    SciTech Connect

    Eslinger, Paul W.; Cameron, Ian M.; Dumais, Johannes R.; Imardjoko, Yudi; Marsoem, Pujadi; McIntyre, Justin I.; Miley, Harry S.; Stoehlker, Ulrich; Widodo, Susilo; Woods, Vincent T.

    2015-10-01

    Abstract Batan Teknologi (BaTek) operates an isotope production facility in Serpong, Indonesia that supplies 99mTc for use in medical procedures. Atmospheric releases of Xe-133 in the production process at BaTek are known to influence the measurements taken at the closest stations of the International Monitoring System (IMS). The purpose of the IMS is to detect evidence of nuclear explosions, including atmospheric releases of radionuclides. The xenon isotopes released from BaTek are the same as those produced in a nuclear explosion, but the isotopic ratios are different. Knowledge of the magnitude of releases from the isotope production facility helps inform analysts trying to decide whether a specific measurement result came from a nuclear explosion. A stack monitor deployed at BaTek in 2013 measured releases to the atmosphere for several isotopes. The facility operates on a weekly cycle, and the stack data for June 15-21, 2013 show a release of 1.84E13 Bq of Xe-133. Concentrations of Xe-133 in the air are available at the same time from a xenon sampler located 14 km from BaTek. An optimization process using atmospheric transport modeling and the sampler air concentrations produced a release estimate of 1.88E13 Bq. The same optimization process yielded a release estimate of 1.70E13 Bq for a different week in 2012. The stack release value and the two optimized estimates are all within 10 percent of each other. Weekly release estimates of 1.8E13 Bq and a 40 percent facility operation rate yields a rough annual release estimate of 3.7E13 Bq of Xe-133. This value is consistent with previously published estimates of annual releases for this facility, which are based on measurements at three IMS stations. These multiple lines of evidence cross-validate the stack release estimates and the release estimates from atmospheric samplers.

  6. On the processing pf piecewise-constant signals by hierarchical models with application to single ion channel currents

    SciTech Connect

    Djuric, P.M.; Fwu, Jong-Kae; Jovanovic, S.; Lynn, K.

    1996-03-01

    A new approach for processing of piecewise-constant signals is proposed. It is based on modeling the observed data as a sum of a random signal and noise. The random signal has a Gibbs distribution, and the noise is Gaussian. A MAP criterion in derived for joint estimation of the number of signal levels and reconstruction of signal. The criterion comprises of three terms, one corresponding to the likelihood of the data and two to penalties. One penalty term penalizes for unnecessary transitions, and the other, for unnecessary levels. The method has been tested on synthesized data and applied to single ion channel recording.

  7. Modeling neural immune signaling of episodic and chronic migraine using spreading depression in vitro.

    PubMed

    Pusic, Aya D; Grinberg, Yelena Y; Mitchell, Heidi M; Kraig, Richard P

    2011-06-13

    Migraine and its transformation to chronic migraine are healthcare burdens in need of improved treatment options. We seek to define how neural immune signaling modulates the susceptibility to migraine, modeled in vitro using spreading depression (SD), as a means to develop novel therapeutic targets for episodic and chronic migraine. SD is the likely cause of migraine aura and migraine pain. It is a paroxysmal loss of neuronal function triggered by initially increased neuronal activity, which slowly propagates within susceptible brain regions. Normal brain function is exquisitely sensitive to, and relies on, coincident low-level immune signaling. Thus, neural immune signaling likely affects electrical activity of SD, and therefore migraine. Pain perception studies of SD in whole animals are fraught with difficulties, but whole animals are well suited to examine systems biology aspects of migraine since SD activates trigeminal nociceptive pathways. However, whole animal studies alone cannot be used to decipher the cellular and neural circuit mechanisms of SD. Instead, in vitro preparations where environmental conditions can be controlled are necessary. Here, it is important to recognize limitations of acute slices and distinct advantages of hippocampal slice cultures. Acute brain slices cannot reveal subtle changes in immune signaling since preparing the slices alone triggers: pro-inflammatory changes that last days, epileptiform behavior due to high levels of oxygen tension needed to vitalize the slices, and irreversible cell injury at anoxic slice centers. In contrast, we examine immune signaling in mature hippocampal slice cultures since the cultures closely parallel their in vivo counterpart with mature trisynaptic function; show quiescent astrocytes, microglia, and cytokine levels; and SD is easily induced in an unanesthetized preparation. Furthermore, the slices are long-lived and SD can be induced on consecutive days without injury, making this preparation the

  8. Modeling Neural Immune Signaling of Episodic and Chronic Migraine Using Spreading Depression In Vitro

    PubMed Central

    Mitchell, Heidi M.; Kraig, Richard P.

    2011-01-01

    Migraine and its transformation to chronic migraine are healthcare burdens in need of improved treatment options. We seek to define how neural immune signaling modulates the susceptibility to migraine, modeled in vitro using spreading depression (SD), as a means to develop novel therapeutic targets for episodic and chronic migraine. SD is the likely cause of migraine aura and migraine pain. It is a paroxysmal loss of neuronal function triggered by initially increased neuronal activity, which slowly propagates within susceptible brain regions. Normal brain function is exquisitely sensitive to, and relies on, coincident low-level immune signaling. Thus, neural immune signaling likely affects electrical activity of SD, and therefore migraine. Pain perception studies of SD in whole animals are fraught with difficulties, but whole animals are well suited to examine systems biology aspects of migraine since SD activates trigeminal nociceptive pathways. However, whole animal studies alone cannot be used to decipher the cellular and neural circuit mechanisms of SD. Instead, in vitro preparations where environmental conditions can be controlled are necessary. Here, it is important to recognize limitations of acute slices and distinct advantages of hippocampal slice cultures. Acute brain slices cannot reveal subtle changes in immune signaling since preparing the slices alone triggers: pro-inflammatory changes that last days, epileptiform behavior due to high levels of oxygen tension needed to vitalize the slices, and irreversible cell injury at anoxic slice centers. In contrast, we examine immune signaling in mature hippocampal slice cultures since the cultures closely parallel their in vivo counterpart with mature trisynaptic function; show quiescent astrocytes, microglia, and cytokine levels; and SD is easily induced in an unanesthetized preparation. Furthermore, the slices are long-lived and SD can be induced on consecutive days without injury, making this preparation the

  9. A Model-Based Signal Processing Approach to Nuclear Explosion Monitoring

    SciTech Connect

    Rodgers, A; Harris, D; Pasyanos, M

    2007-03-14

    This report describes research performed under Laboratory Research and Development Project 05-ERD-019, entitled ''A New Capability for Regional High-Frequency Seismic Wave Simulation in Realistic Three-Dimensional Earth Models to Improve Nuclear Explosion Monitoring''. A more appropriate title for this project is ''A Model-Based Signal Processing Approach to Nuclear Explosion Monitoring''. This project supported research for a radically new approach to nuclear explosion monitoring as well as allowed the development new capabilities in computational seismology that can contribute to NNSA/NA-22 Programs.

  10. Travel time of impulsive signals in the magnetosphere: Modeling and observations

    NASA Astrophysics Data System (ADS)

    Chi, P. J.; Russell, C. T.; Angelopoulos, V.

    2007-12-01

    The calculation of travel time for impulsive signals has many uses in magneotspheric physics, such as understanding the propagation of sudden impulses, helping identify the causes of substorm onsets, and inferring the global plasma density and temperature from inverting the signal arrival time at multiple locations. Because impulsive signals can propagate rapidly as MHD waves, it is necessary for calculations and observations to have a time resolution of the order of one sec to yield useful results. To avoid time-consuming global simulations at this high cadence, we have developed a numerical model that focuses on wavefront construction to compute the travel time of impulsive signals. Following the Huygens principle, the algorithm allows the user to define the shape of the initial impulse and tracks the first arrival of wavefront in two dimensions. We will demonstrate, in both equatorial and meridian planes, how the wavefront of sudden impulses propagates tailward from the dayside magnetopause and how the wavefront of substorm onsets in the magnetotail evolves as it propagates earthward. We compare our calculations with the magnetic field observations from the armada of satellites, including Polar and THEMIS, in orbit, as well as the data from various ground magnetometer networks such as McMAC, THEMIS-GBO/EPO, and CARISMA.

  11. Signal-to-noise performance analysis of streak tube imaging lidar systems. I. Cascaded model.

    PubMed

    Yang, Hongru; Wu, Lei; Wang, Xiaopeng; Chen, Chao; Yu, Bing; Yang, Bin; Yuan, Liang; Wu, Lipeng; Xue, Zhanli; Li, Gaoping; Wu, Baoning

    2012-12-20

    Streak tube imaging lidar (STIL) is an active imaging system using a pulsed laser transmitter and a streak tube receiver to produce 3D range and intensity imagery. The STIL has recently attracted a great deal of interest and attention due to its advantages of wide azimuth field-of-view, high range and angle resolution, and high frame rate. This work investigates the signal-to-noise performance of STIL systems. A theoretical model for characterizing the signal-to-noise performance of the STIL system with an internal or external intensified streak tube receiver is presented, based on the linear cascaded systems theory of signal and noise propagation. The STIL system is decomposed into a series of cascaded imaging chains whose signal and noise transfer properties are described by the general (or the spatial-frequency dependent) noise factors (NFs). Expressions for the general NFs of the cascaded chains (or the main components) in the STIL system are derived. The work presented here is useful for the design and evaluation of STIL systems.

  12. A mouse model for Meckel syndrome reveals Mks1 is required for ciliogenesis and Hedgehog signaling

    PubMed Central

    Weatherbee, Scott D.; Niswander, Lee A.; Anderson, Kathryn V.

    2009-01-01

    Meckel syndrome (MKS) is a rare autosomal recessive disease causing perinatal lethality associated with a complex syndrome that includes occipital meningoencephalocele, hepatic biliary ductal plate malformation, postaxial polydactyly and polycystic kidneys. The gene mutated in type 1 MKS encodes a protein associated with the base of the cilium in vertebrates and nematodes. However, shRNA knockdown studies in cell culture have reported conflicting results on the role of Mks1 in ciliogenesis. Here we show that loss of function of mouse Mks1 results in an accurate model of human MKS, with structural abnormalities in the neural tube, biliary duct, limb patterning, bone development and the kidney that mirror the human syndrome. In contrast to cell culture studies, loss of Mks1 in vivo does not interfere with apical localization of epithelial basal bodies but rather leads to defective cilia formation in most, but not all, tissues. Analysis of patterning in the neural tube and the limb demonstrates altered Hedgehog (Hh) pathway signaling underlies some MKS defects, although both tissues show an expansion of the domain of response to Shh signaling, unlike the phenotypes seen in other mutants with cilia loss. Other defects in the skull, lung, rib cage and long bones are likely to be the result of the disruption of Hh signaling, and the basis of defects in the liver and kidney require further analysis. Thus the disruption of Hh signaling can explain many, but not all, of the defects caused by loss of Mks1. PMID:19776033

  13. Signal-to-noise performance analysis of streak tube imaging lidar systems. I. Cascaded model.

    PubMed

    Yang, Hongru; Wu, Lei; Wang, Xiaopeng; Chen, Chao; Yu, Bing; Yang, Bin; Yuan, Liang; Wu, Lipeng; Xue, Zhanli; Li, Gaoping; Wu, Baoning

    2012-12-20

    Streak tube imaging lidar (STIL) is an active imaging system using a pulsed laser transmitter and a streak tube receiver to produce 3D range and intensity imagery. The STIL has recently attracted a great deal of interest and attention due to its advantages of wide azimuth field-of-view, high range and angle resolution, and high frame rate. This work investigates the signal-to-noise performance of STIL systems. A theoretical model for characterizing the signal-to-noise performance of the STIL system with an internal or external intensified streak tube receiver is presented, based on the linear cascaded systems theory of signal and noise propagation. The STIL system is decomposed into a series of cascaded imaging chains whose signal and noise transfer properties are described by the general (or the spatial-frequency dependent) noise factors (NFs). Expressions for the general NFs of the cascaded chains (or the main components) in the STIL system are derived. The work presented here is useful for the design and evaluation of STIL systems. PMID:23262622

  14. From molecular model to sparse representation of chromatographic signals with an unknown number of peaks.

    PubMed

    Bertholon, F; Harant, O; Foan, L; Vignoud, S; Jutten, C; Grangeat, P

    2015-08-01

    Analysis of a fluid mixture using a chromatographic system is a standard technique for many biomedical applications such as in-vitro diagnostic of body fluids or air and water quality assessment. The analysis is often dedicated towards a set of molecules or biomarkers. However, due to the fluid complexity, the number of mixture components is often larger than the list of targeted molecules. In order to get an analysis as exhaustive as possible and also to take into account possible interferences, it is important to identify and to quantify all the components that are included in the chromatographic signal. Thus the signal processing aims to reconstruct a list of an unknown number of components and their relative concentrations. We address this question as a problem of sparse representation of a chromatographic signal. The innovative representation is based on a stochastic forward model describing the transport of elementary molecules in the chromatography column as a molecular random walk. We investigate three methods: two probabilistic Bayesian approaches, one parametric and one non-parametric, and a determinist approach based on a parsimonious decomposition on a dictionary basis. We examine the performances of these 3 approaches on an experimental case dedicated to the analysis of mixtures of the micro-pollutants Polycyclic Aromatic Hydrocarbons (PAH) in a methanol solution in two cases of high and low signal to noise ratio (SNR).

  15. Quantum gate circuit model of signal integration in bacterial quorum sensing.

    PubMed

    Karafyllidis, Ioannis G

    2012-01-01

    Bacteria evolved cell to cell communication processes to gain information about their environment and regulate gene expression. Quorum sensing is such a process in which signaling molecules, called autoinducers, are produced, secreted and detected. In several cases bacteria use more than one autoinducers and integrate the information conveyed by them. It has not yet been explained adequately why bacteria evolved such signal integration circuits and what can learn about their environments using more than one autoinducers since all signaling pathways merge in one. Here quantum information theory, which includes classical information theory as a special case, is used to construct a quantum gate circuit that reproduces recent experimental results. Although the conditions in which biosystems exist do not allow for the appearance of quantum mechanical phenomena, the powerful computation tools of quantum information processing can be carefully used to cope with signal and information processing by these complex systems. A simulation algorithm based on this model has been developed and numerical experiments that analyze the dynamical operation of the quorum sensing circuit were performed for various cases of autoinducer variations, which revealed that these variations contain significant information about the environment in which bacteria exist.

  16. The role of ROS signaling in cross-tolerance: from model to crop.

    PubMed

    Perez, Ilse Barrios; Brown, Patrick J

    2014-01-01

    Reactive oxygen species (ROS) are key signaling molecules produced in response to biotic and abiotic stresses that trigger a variety of plant defense responses. Cross-tolerance, the enhanced ability of a plant to tolerate multiple stresses, has been suggested to result partly from overlap between ROS signaling mechanisms. Cross-tolerance can manifest itself both as a positive genetic correlation between tolerance to different stresses (inherent cross-tolerance), and as the priming of systemic plant tolerance through previous exposure to another type of stress (induced cross-tolerance). Research in model organisms suggests that cross-tolerance could be used to benefit the agronomy and breeding of crop plants. However, research under field conditions has been scarce and critical issues including the timing, duration, and intensity of a stressor, as well as its interactions with other biotic and abiotic factors, remain to be addressed. Potential applications include the use of chemical stressors to screen for stress-resistant genotypes in breeding programs and the agronomic use of chemical inducers of plant defense for plant protection. Success of these applications will rely on improving our understanding of how ROS signals travel systemically and persist over time, and of how genetic correlations between resistance to ROS, biotic, and abiotic stresses are shaped by cooperative and antagonistic interactions within the underlying signaling pathways.

  17. Dysregulated intracellular signaling in the striatum in a pathophysiologically grounded model of Tourette syndrome.

    PubMed

    Rapanelli, Maximiliano; Frick, Luciana R; Pogorelov, Vladimir; Ota, Kristie T; Abbasi, Eeman; Ohtsu, Hiroshi; Pittenger, Christopher

    2014-12-01

    Tic disorders produce substantial morbidity, but their pathophysiology remains poorly understood. Convergent evidence suggests that dysregulation of the cortico-basal ganglia circuitry is central to the pathogenesis of tics. Tourette syndrome (TS), the most severe end of the continuum of tic disorders, is substantially genetic, but causative mutations have been elusive. We recently described a mouse model, the histidine decarboxylase (Hdc) knockout mouse, that recapitulates a rare, highly penetrant mutation found in a single family; these mice exhibit TS-like phenomenology. These animals have a global deficit in brain histamine and a consequent dysregulation of DA in the basal ganglia. Histamine modulation of DA effects is increasingly appreciated, but the mechanisms underlying this modulation remain unclear; the consequences of modest DA elevation in the context of profound HA deficiency are difficult to predict, but understanding them in the Hdc knockout mouse may provide generalizable insights into the pathophysiology of TS. Here we characterized signaling pathways in striatal cells in this model system, at baseline and after amphetamine challenge. In vivo microdialysis confirms elevated DA in Hdc-KO mice. We find dephosphorylation of Akt and its target GSK3β and activation of the MAPK signaling cascade and its target rpS6; these are characteristic of the effects of DA on D2- and D1-expressing striatal neurons, respectively. Strikingly, there is no alteration in mTOR signaling, which can be regulated by DA in both cell types. These cellular effects help elucidate striatal signaling abnormalities in a uniquely validated mouse model of TS and move towards the identification of new potential therapeutic targets for tic disorders. PMID:25464894

  18. Dysregulated intracellular signaling in the striatum in a pathophysiologically grounded model of Tourette syndrome

    PubMed Central

    Rapanelli, Maximiliano; Frick, Luciana R.; Pogorelov, Vladimir; Ota, Kristie T.; Abbasi, Eeman; Ohtsu, Hiroshi; Pittenger, Christopher

    2015-01-01

    Tic disorders produce substantial morbidity, but their pathophysiology remains poorly understood. Convergent evidence suggests that dysregulation of the cortico-basal ganglia circuitry is central to the pathogenesis of tics. Tourette syndrome (TS), the most severe end of the continuum of tic disorders, is substantially genetic, but causative mutations have been elusive. We recently described a mouse model, the histidine decarboxylase (Hdc) knockout mouse, that recapitulates a rare, highly penetrant mutation found in a single family; these mice exhibit TS-like phenomenology. These animals have a global deficit in brain histamine and a consequent dysregulation of DA in the basal ganglia. Histamine modulation of DA effects is increasingly appreciated, but the mechanisms underlying this modulation remain unclear; the consequences of modest DA elevation in the context of profound HA deficiency are difficult to predict, but understanding them in the Hdc knockout mouse may provide generalizable insights into the pathophysiology of TS. Here we characterized signaling pathways in striatal cells in this model system, at baseline and after amphetamine challenge. In vivo microdialysis confirms elevated DA in Hdc-KO mice. We find dephosphorylation of Akt and its target GSK3β and activation of the MAPK signaling cascade and its target rpS6; these are characteristic of the effects of DA on D2- and D1-expressing striatal neurons, respectively. Strikingly, there is no alteration in mTOR signaling, which can be regulated by DA in both cell types. These cellular effects help elucidate striatal signaling abnormalities in a uniquely validated mouse model of TS and move towards the identification of new potential therapeutic targets for tic disorders. PMID:25464894

  19. Challenges Handling Magnetospheric and Ionospheric Signals in Internal Geomagnetic Field Modelling

    NASA Astrophysics Data System (ADS)

    Finlay, C. C.; Lesur, V.; Thébault, E.; Vervelidou, F.; Morschhauser, A.; Shore, R.

    2016-09-01

    Measurements of the Earth's magnetic field collected by low-Earth-orbit satellites such as Swarm and CHAMP, as well as at ground observatories, are dominated by sources in the Earth's interior. However these measurements also contain significant contributions from more rapidly-varying current systems in the ionosphere and magnetosphere. In order to fully exploit magnetic data to probe the physical properties and dynamics of the Earth's interior, field models with suitable treatments of external sources, and their associated induced signals, are essential. Here we review the methods presently used to construct models of the internal field, focusing on techniques to handle magnetospheric and ionospheric signals. Shortcomings of these techniques often limit the quality, as well as spatial and temporal resolution, of internal field models. We document difficulties in using track-by-track analysis to characterize magnetospheric field fluctuations, differences in internal field models that result from alternative treatments of the quiet-time ionospheric field, and challenges associated with rapidly changing, but spatially correlated, magnetic signatures of polar cap current systems. Possible strategies for improving internal field models are discussed, many of which are described in more detail elsewhere in this volume.

  20. Numerical model a graphene component for the sensing of weak electromagnetic signals

    NASA Astrophysics Data System (ADS)

    Nasswettrova, A.; Fiala, P.; Nešpor, D.; Drexler, P.; Steinbauer, M.

    2015-05-01

    The paper discusses a numerical model and provides an analysis of a graphene coaxial line suitable for sub-micron sensors of magnetic fields. In relation to the presented concept, the target areas and disciplines include biology, medicine, prosthetics, and microscopic solutions for modern actuators or SMART elements. The proposed numerical model is based on an analysis of a periodic structure with high repeatability, and it exploits a graphene polymer having a basic dimension in nanometers. The model simulates the actual random motion in the structure as the source of spurious signals and considers the pulse propagation along the structure; furthermore, the model also examines whether and how the pulse will be distorted at the beginning of the line, given the various ending versions. The results of the analysis are necessary for further use of the designed sensing devices based on graphene structures.

  1. Removal of correlated noise by modeling the signal of interest in the wavelet domain.

    PubMed

    Goossens, Bart; Pizurica, Aleksandra; Philips, Wilfried

    2009-06-01

    Images, captured with digital imaging devices, often contain noise. In literature, many algorithms exist for the removal of white uncorrelated noise, but they usually fail when applied to images with correlated noise. In this paper, we design a new denoising method for the removal of correlated noise, by modeling the significance of the noise-free wavelet coefficients in a local window using a new significance measure that defines the "signal of interest" and that is applicable to correlated noise. We combine the intrascale model with a hidden Markov tree model to capture the interscale dependencies between the wavelet coefficients. We propose a denoising method based on the combined model and a less redundant wavelet transform. We present results that show that the new method performs as well as the state-of-the-art wavelet-based methods, while having a lower computational complexity.

  2. Climatic Signal and Climatic Noise in Lorenz's Low Order Model of the Atmospheric Circulation

    NASA Astrophysics Data System (ADS)

    Freire, J.; Dacamara, C.; Corte-Real, J.; Gallas, J. A. C.

    2003-04-01

    The climate state may be defined by a set of statistics computed over a very large number of replicas of the Atmosphere (ensemble), each replica evolving independently of each other, but all replicas subject to the same boundary conditions (external forcing). Such dynamic approach of the climate state is particulary adequate to define the concepts of climatic signal (linked to external forcing) and climatic noise (associated to distinct events of the same climatic state). Lorenz's low-order model of the general circulation is a useful tool to study the atmospheric signal and noise when the system is subject to prescribed forcing (e.g. seasonal forcing). This is due to the richness of the model as a dynamical system together with its low computacional cost that allows building ensembles with a large number of replicas. In our study we analyse the dynamical behavior of the atmospheric circulation based on a large set of numerical integrations (≈10000). The climate state is analysed and particular attention is devoted to the problem of separating the climatic signal from the climatic noise for different types of seasonal forcing.

  3. A cortical vascular model for examining the specificity of the laminar BOLD signal.

    PubMed

    Markuerkiaga, Irati; Barth, Markus; Norris, David G

    2016-05-15

    Blood oxygenation level dependent (BOLD) functional MRI has been used for inferring layer specific activation in humans. However, intracortical veins perpendicular to the cortical surface are suspected to degrade the laminar specificity as they drain blood from the microvasculature and BOLD signal is carried over from lower to upper cortical layers on its way to the pial surface. In this work, a vascular model of the cortex is developed to investigate the laminar specificity of the BOLD signal for Spin Echo (SE) and Gradient Echo (GE) following the integrative model presented by Uludağ et al. (2009). The results of the simulation show that the laminar point spread function (PSF) of the BOLD signal presents similar features across all layers. The PSF for SE is highly localised whereas for GE there is a flat tail running to the pial surface, with amplitude less than a quarter of the response from the layer itself. Consequently the GE response at any layer will also contain a contribution accumulated from all lower layers. PMID:26952195

  4. Modeling propagation of infrasound signals observed by a dense seismic network.

    PubMed

    Chunchuzov, I; Kulichkov, S; Popov, O; Hedlin, M

    2014-01-01

    The long-range propagation of infrasound from a surface explosion with an explosive yield of about 17.6 t TNT that occurred on June 16, 2008 at the Utah Test and Training Range (UTTR) in the western United States is simulated using an atmospheric model that includes fine-scale layered structure of the wind velocity and temperature fields. Synthetic signal parameters (waveforms, amplitudes, and travel times) are calculated using parabolic equation and ray-tracing methods for a number of ranges between 100 and 800 km from the source. The simulation shows the evolution of several branches of stratospheric and thermospheric signals with increasing range from the source. Infrasound signals calculated using a G2S (ground-to-space) atmospheric model perturbed by small-scale layered wind velocity and temperature fluctuations are shown to agree well with recordings made by the dense High Lava Plains seismic network located at an azimuth of 300° from UTTR. The waveforms of calculated infrasound arrivals are compared with those of seismic recordings. This study illustrates the utility of dense seismic networks for mapping an infrasound field with high spatial resolution. The parabolic equation calculations capture both the effect of scattering of infrasound into geometric acoustic shadow zones and significant temporal broadening of the arrivals. PMID:24437743

  5. Early Warning Signals for Regime Transition in the Stable Boundary Layer: A Model Study

    NASA Astrophysics Data System (ADS)

    van Hooijdonk, I. G. S.; Moene, A. F.; Scheffer, M.; Clercx, H. J. H.; van de Wiel, B. J. H.

    2016-10-01

    The evening transition is investigated in an idealized model for the nocturnal boundary layer. From earlier studies it is known that the nocturnal boundary layer may manifest itself in two distinct regimes, depending on the ambient synoptic conditions: strong-wind or overcast conditions typically lead to weakly stable, turbulent nights; clear-sky and weak-wind conditions, on the other hand, lead to very stable, weakly turbulent conditions. Previously, the dynamical behaviour near the transition between these regimes was investigated in an idealized setting, relying on Monin-Obukhov (MO) similarity to describe turbulent transport. Here, we investigate a similar set-up, using direct numerical simulation; in contrast to MO-based models, this type of simulation does not need to rely on turbulence closure assumptions. We show that previous predictions are verified, but now independent of turbulence parametrizations. Also, it appears that a regime shift to the very stable state is signaled in advance by specific changes in the dynamics of the turbulent boundary layer. Here, we show how these changes may be used to infer a quantitative estimate of the transition point from the weakly stable boundary layer to the very stable boundary layer. In addition, it is shown that the idealized, nocturnal boundary-layer system shares important similarities with generic non-linear dynamical systems that exhibit critical transitions. Therefore, the presence of other, generic early warning signals is tested as well. Indeed, indications are found that such signals are present in stably stratified turbulent flows.

  6. A cortical vascular model for examining the specificity of the laminar BOLD signal.

    PubMed

    Markuerkiaga, Irati; Barth, Markus; Norris, David G

    2016-05-15

    Blood oxygenation level dependent (BOLD) functional MRI has been used for inferring layer specific activation in humans. However, intracortical veins perpendicular to the cortical surface are suspected to degrade the laminar specificity as they drain blood from the microvasculature and BOLD signal is carried over from lower to upper cortical layers on its way to the pial surface. In this work, a vascular model of the cortex is developed to investigate the laminar specificity of the BOLD signal for Spin Echo (SE) and Gradient Echo (GE) following the integrative model presented by Uludağ et al. (2009). The results of the simulation show that the laminar point spread function (PSF) of the BOLD signal presents similar features across all layers. The PSF for SE is highly localised whereas for GE there is a flat tail running to the pial surface, with amplitude less than a quarter of the response from the layer itself. Consequently the GE response at any layer will also contain a contribution accumulated from all lower layers.

  7. Dynamics and stability of a three-dimensional model of cell signal transduction with delay

    NASA Astrophysics Data System (ADS)

    Levy, Chris; Iron, David

    2015-07-01

    In this paper, we consider a three-dimensional model of cell signal transduction with delay. The deactivation of signalling proteins occurs throughout the cytosol and activation is localized to specific sites in the cell. The enzyme kinetic functions employ a constant delay to model the time lapse during reactions and also the recovery times associated with conformational changes. We use matched asymptotic expansions to construct the dynamic solutions of signalling protein concentrations. The result of the asymptotic analysis is a system of delayed differential algebraic equations. This reduced system is compared to numerical simulations of the full three-dimensional system. As well, we consider the stability of equilibrium solutions. We find that the systems under consideration may undergo Hopf bifurcations for certain delay values. In these cases sustained oscillations are observed. The Poincaré-Lindstedt3 method is used to improve upon the asymptotic approximations. The simulations of the full three-dimensional system correspond well with simulations of the reduced delayed differential algebraic equations.

  8. Effects of neutrino oscillations on nucleosynthesis and neutrino signals for an 18 M⊙ supernova model

    NASA Astrophysics Data System (ADS)

    Wu, Meng-Ru; Qian, Yong-Zhong; Martínez-Pinedo, Gabriel; Fischer, Tobias; Huther, Lutz

    2015-03-01

    In this paper, we explore the effects of neutrino flavor oscillations on supernova nucleosynthesis and on the neutrino signals. Our study is based on detailed information about the neutrino spectra and their time evolution from a spherically symmetric supernova model for an 18 M⊙ progenitor. We find that collective neutrino oscillations are not only sensitive to the detailed neutrino energy and angular distributions at emission, but also to the time evolution of both the neutrino spectra and the electron density profile. We apply the results of neutrino oscillations to study the impact on supernova nucleosynthesis and on the neutrino signals from a Galactic supernova. We show that in our supernova model, collective neutrino oscillations enhance the production of rare isotopes 138La and 180Ta but have little impact on the ν p -process nucleosynthesis. In addition, the adiabatic Mikheyev-Smirnov-Wolfenstein flavor transformation, which occurs in the C /O and He shells of the supernova, may affect the production of light nuclei such as 7Li and 11B. For the neutrino signals, we calculate the rate of neutrino events in the Super-Kamiokande detector and in a hypothetical liquid argon detector. Our results suggest the possibility of using the time profiles of the events in both detectors, along with the spectral information of the detected neutrinos, to infer the neutrino mass hierarchy.

  9. Efficient computation of net analyte signal vector in inverse multivariate calibration models.

    PubMed

    Faber, N K

    1998-12-01

    The net analyte signal vector has been defined by Lorber as the part of a mixture spectrum that is unique for the analyte of interest; i.e., it is orthogonal to the spectra of the interferences. It plays a key role in the development of multivariate analytical figures of merit. Applications have been reported that imply its utility for spectroscopic wavelength selection as well as calibration method comparison. Currently available methods for computing the net analyte signal vector in inverse multivariate calibration models are based on the evaluation of projection matrices. Due to the size of these matrices (p × p, with p the number of wavelengths) the computation may be highly memory- and time-consuming. This paper shows that the net analyte signal vector can be obtained in a highly efficient manner by a suitable scaling of the regression vector. Computing the scaling factor only requires the evaluation of an inner product (p multiplications and additions). The mathematical form of the newly derived expression is discussed, and the generalization to multiway calibration models is briefly outlined.

  10. The CNP signal is able to silence a supra threshold neuronal model

    PubMed Central

    Camera, Francesca; Paffi, Alessandra; Thomas, Alex W.; Apollonio, Francesca; D'Inzeo, Guglielmo; Prato, Frank S.; Liberti, Micaela

    2015-01-01

    Several experimental results published in the literature showed that weak pulsed magnetic fields affected the response of the central nervous system. However, the specific biological mechanisms that regulate the observed behaviors are still unclear and further scientific investigation is required. In this work we performed simulations on a neuronal network model exposed to a specific pulsed magnetic field signal that seems to be very effective in modulating the brain activity: the Complex Neuroelectromagnetic Pulse (CNP). Results show that CNP can silence the neurons of a feed-forward network for signal intensities that depend on the strength of the bias current, the endogenous noise level and the specific waveforms of the pulses. Therefore, it is conceivable that a neuronal network model responds to the CNP signal with an inhibition of its activity. Further studies on more realistic neuronal networks are needed to clarify if such an inhibitory effect on neuronal tissue may be the basis of the induced analgesia seen in humans and the antinociceptive effects seen in animals when exposed to the CNP. PMID:25972807

  11. Modeling propagation of infrasound signals observed by a dense seismic network.

    PubMed

    Chunchuzov, I; Kulichkov, S; Popov, O; Hedlin, M

    2014-01-01

    The long-range propagation of infrasound from a surface explosion with an explosive yield of about 17.6 t TNT that occurred on June 16, 2008 at the Utah Test and Training Range (UTTR) in the western United States is simulated using an atmospheric model that includes fine-scale layered structure of the wind velocity and temperature fields. Synthetic signal parameters (waveforms, amplitudes, and travel times) are calculated using parabolic equation and ray-tracing methods for a number of ranges between 100 and 800 km from the source. The simulation shows the evolution of several branches of stratospheric and thermospheric signals with increasing range from the source. Infrasound signals calculated using a G2S (ground-to-space) atmospheric model perturbed by small-scale layered wind velocity and temperature fluctuations are shown to agree well with recordings made by the dense High Lava Plains seismic network located at an azimuth of 300° from UTTR. The waveforms of calculated infrasound arrivals are compared with those of seismic recordings. This study illustrates the utility of dense seismic networks for mapping an infrasound field with high spatial resolution. The parabolic equation calculations capture both the effect of scattering of infrasound into geometric acoustic shadow zones and significant temporal broadening of the arrivals.

  12. Applying the random effect negative binomial model to examine traffic accident occurrence at signalized intersections.

    PubMed

    Chin, Hoong Chor; Quddus, Mohammed Abdul

    2003-03-01

    Poisson and negative binomial (NB) models have been used to analyze traffic accident occurrence at intersections for several years. There are however, limitations in the use of such models. The Poisson model requires the variance-to-mean ratio of the accident data to be about 1. Both the Poisson and the NB models require the accident data to be uncorrelated in time. Due to unobserved heterogeneity and serial correlation in the accident data, both models seem to be inappropriate. A more suitable alternative is the random effect negative binomial (RENB) model, which by treating the data in a time-series cross-section panel, will be able to deal with the spatial and temporal effects in the data. This paper describes the use of RENB model to identify the elements that affect intersection safety. To establish the suitability of the model, several goodness-of-fit statistics are used. The model is then applied to investigate the relationship between accident occurrence and the geometric, traffic and control characteristics of signalized intersections in Singapore. The results showed that 11 variables significantly affected the safety at the intersections. The total approach volumes, the numbers of phases per cycle, the uncontrolled left-turn lane and the presence of a surveillance camera are among the variables that are the highly significant. PMID:12504146

  13. Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

    PubMed Central

    Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

    2013-01-01

    Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

  14. Neuroelectronics and modeling of electrical signals for monitoring and control of Parkinson's disease

    NASA Astrophysics Data System (ADS)

    Chintakuntla, Ritesh R.; Abraham, Jose K.; Varadan, Vijay K.

    2009-03-01

    The brain and the human nervous system are perhaps the most researched but least understood components of the human body. This is so because of the complex nature of its working and the high density of functions. The monitoring of neural signals could help one better understand the working of the brain and newer recording and monitoring methods have been developed ever since it was discovered that the brain communicates internally by means of electrical pulses. Neuroelectronics is the field which deals with the interface between electronics or semiconductors to living neurons. This includes monitoring of electrical activity from the brain as well as the development of feedback devices for stimulation of parts of the brain for treatment of disorders. In this paper these electrical signals are modeled through a nano/microelectrode arrays based on the electronic equivalent model using Cadence PSD 15.0. The results were compared with those previously published models such as Kupfmuller and Jenik's model, McGrogan's Neuron Model which are based on the Hodgkin and Huxley model. We have developed and equivalent circuit model using discrete passive components to simulate the electrical activity of the neurons. The simulated circuit can be easily be modified by adding some more ionic channels and the results can be used to predict necessary external stimulus needed for stimulation of neurons affected by the Parkinson's disease (PD). Implementing such a model in PD patients could predict the necessary voltages required for the electrical stimulation of the sub-thalamus region for the control tremor motion.

  15. The SNA analysis of a minimal model for bistability in the MAPK signaling cascade model

    NASA Astrophysics Data System (ADS)

    Hadač, O.; Schreiber, I.

    2013-12-01

    Successive phosphorylation cascades mediated by mitogen-activated protein kinases (MAPKs) are known to act as switches initiating various cellular processes. In addition, models of the MAPK reaction network are displaying other nonlinear phenomena including bistability and periodic oscillations. Recently bistability has been explained as a consequence of interaction between single and double phosphorylation/dephosphorylation pathways in the Stage 2 subsystem of the Huang-Ferrell model of the MAPK and a core bistable model has been proposed. Here we focus on a detailed stability analysis of the steady states of this minimal model. The analysis uses methods of convex analysis and stoichiometric network theory.

  16. Wnt signaling pathway improves central inhibitory synaptic transmission in a mouse model of Duchenne muscular dystrophy.

    PubMed

    Fuenzalida, Marco; Espinoza, Claudia; Pérez, Miguel Ángel; Tapia-Rojas, Cheril; Cuitino, Loreto; Brandan, Enrique; Inestrosa, Nibaldo C

    2016-02-01

    The dystrophin-associated glycoprotein complex (DGC) that connects the cytoskeleton, plasma membrane and the extracellular matrix has been related to the maintenance and stabilization of channels and synaptic receptors, which are both essential for synaptogenesis and synaptic transmission. The dystrophin-deficient (mdx) mouse model of Duchenne muscular dystrophy (DMD) exhibits a significant reduction in hippocampal GABA efficacy, which may underlie the altered synaptic function and abnormal hippocampal long-term plasticity exhibited by mdx mice. Emerging studies have implicated Wnt signaling in the modulation of synaptic efficacy, neuronal plasticity and cognitive function. We report here that the activation of the non-canonical Wnt-5a pathway and Andrographolide, improves hippocampal mdx GABAergic efficacy by increasing the number of inhibitory synapses and GABA(A) receptors or GABA release. These results indicate that Wnt signaling modulates GABA synaptic efficacy and could be a promising novel target for DMD cognitive therapy. PMID:26626079

  17. Elevation dependency of the surface climate change signal: A model study

    SciTech Connect

    Giorgi, F.; Hurrell, J.W.; Marinucci, M.R.

    1997-02-01

    Results are presented from a present-day and a doubled CO{sub 2} experiment over the Alpine region with a nested regional climate model. The simulated temperature change signal shows a substantial elevation dependency, mostly during the winter and spring seasons, resulting in more pronounced warming at high elevations than low elevations. This is caused by a depletion of snowpack in doubled CO{sub 2} conditions and further enhanced by the snow-albedo feedback. This result is consistent with some observed temperature trends for anomalously warm years over the Alpine region and suggests that high elevation temperature changes could be used as an early detection tool for global warming. Changes in precipitation, as well as other components of the surface energy and water budgets, also show an elevation signal, which may have important implications for impact assessments in high elevation regions. 22 refs., 10 figs., 2 tabs.

  18. Model-based spectral estimation of Doppler signals using parallel genetic algorithms.

    PubMed

    Solano González, J; Rodríguez Vázquez, K; García Nocetti, D F

    2000-05-01

    Conventional spectral analysis methods use a fast Fourier transform (FFT) on consecutive or overlapping windowed data segments. For Doppler ultrasound signals, this approach suffers from an inadequate frequency resolution due to the time segment duration and the non-stationarity characteristics of the signals. Parametric or model-based estimators can give significant improvements in the time-frequency resolution at the expense of a higher computational complexity. This work describes an approach which implements in real-time a parametric spectral estimator method using genetic algorithms (GAs) in order to find the optimum set of parameters for the adaptive filter that minimises the error function. The aim is to reduce the computational complexity of the conventional algorithm by using the simplicity associated to GAs and exploiting its parallel characteristics. This will allow the implementation of higher order filters, increasing the spectrum resolution, and opening a greater scope for using more complex methods. PMID:10767617

  19. Modeling common dynamics in multichannel signals with applications to artifact and background removal in EEG recordings.

    PubMed

    De Clercq, Wim; Vanrumste, Bart; Papy, Jean-Michel; Van Paesschen, Wim; Van Huffel, Sabine

    2005-12-01

    Removing artifacts and background electroencephaloraphy (EEG) from multichannel interictal and ictal EEG has become a major research topic in EEG signal processing in recent years. We applied for this purpose a recently developed subspace-based method for modeling the common dynamics in multichannel signals. When the epileptiform activity is common in the majority of channels and the artifacts appear only in a few channels the proposed method can be used to remove the latter. The performance of the method was tested on simulated data for different noise levels. For high noise levels the method was still able to identify the common dynamics. In addition, the method was applied to real life EEG recordings containing interictal and ictal activity contaminated with muscle artifact. The muscle artifacts were removed successfully. For both the synthetic data and the analyzed real life data the results were compared with the results obtained with principal component analysis (PCA). In both cases, the proposed method performed better than PCA.

  20. Modeling and estimation of signal-dependent noise in hyperspectral imagery.

    PubMed

    Meola, Joseph; Eismann, Michael T; Moses, Randolph L; Ash, Joshua N

    2011-07-20

    The majority of hyperspectral data exploitation algorithms are developed using statistical models for the data that include sensor noise. Hyperspectral data collected using charge-coupled devices or other photon detectors have sensor noise that is directly dependent on the amplitude of the signal collected. However, this signal dependence is often ignored. Additionally, the statistics of the noise can vary spatially and spectrally as a result of camera characteristics and the calibration process applied to the data. Here, we examine the expected noise characteristics of both raw and calibrated visible/near-infrared hyperspectral data and provide a method for estimating the noise statistics using calibration data or directly from the imagery if calibration data is unavailable.

  1. Model-based spectral estimation of Doppler signals using parallel genetic algorithms.

    PubMed

    Solano González, J; Rodríguez Vázquez, K; García Nocetti, D F

    2000-05-01

    Conventional spectral analysis methods use a fast Fourier transform (FFT) on consecutive or overlapping windowed data segments. For Doppler ultrasound signals, this approach suffers from an inadequate frequency resolution due to the time segment duration and the non-stationarity characteristics of the signals. Parametric or model-based estimators can give significant improvements in the time-frequency resolution at the expense of a higher computational complexity. This work describes an approach which implements in real-time a parametric spectral estimator method using genetic algorithms (GAs) in order to find the optimum set of parameters for the adaptive filter that minimises the error function. The aim is to reduce the computational complexity of the conventional algorithm by using the simplicity associated to GAs and exploiting its parallel characteristics. This will allow the implementation of higher order filters, increasing the spectrum resolution, and opening a greater scope for using more complex methods.

  2. Modeling random telegraph signal noise in CMOS image sensor under low light based on binomial distribution

    NASA Astrophysics Data System (ADS)

    Yu, Zhang; Xinmiao, Lu; Guangyi, Wang; Yongcai, Hu; Jiangtao, Xu

    2016-07-01

    The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result, the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated, and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures. Project supported by the National Natural Science Foundation of China (Grant Nos. 61372156 and 61405053) and the Natural Science Foundation of Zhejiang Province of China (Grant No. LZ13F04001).

  3. Planar Schottky varactor diode and corresponding large signal model for millimeter-wave applications

    NASA Astrophysics Data System (ADS)

    Jie, Huang; Qian, Zhao; Hao, Yang; Junrong, Dong; Haiying, Zhang

    2014-05-01

    A GaAs-based planar Schottky varactor diode (PSVD) is successfully developed to meet the demand of millimeter-wave harmonic generation. Based on the measured S-parameter, I-V and C-V characteristics, an accurate and reliable extraction method of the millimeter-wave large signal equivalent circuit model of the PSVD is proposed and used to extract the model parameters of two PSVDs with Schottky contact areas of 160 μm2 and 49 μm2, respectively. The simulated S-parameter, I-V and C-V performances of the proposed physics-based model are in good agreement with the measured one over the frequency range from 0.1 to 40 GHz for wide operation bias range from -10 to 0.6 V for these two PSVDs. The proposed equivalent large signal circuit model of this PSVD has been proven to be reliable and can potentially be used to design microwave circuits., planar Schottky varactor diode

  4. Noise analysis and signal-to-noise ratio model of gain modulation laser imaging

    NASA Astrophysics Data System (ADS)

    Tu, Zhipeng; Li, Sining; Zhang, Dayong; Lu, Wei

    2015-10-01

    Gain modulation imaging technique is one of the prominent schemes for scannerless lidar. By controlling the gate width, it's easy to suppress backscatter noise and make the image more accurately. Imaging range and accuracy of gain modulation laser imaging become a research focus at present. According to the principle of imaging, the signal energy and the noise energy reaching the imager can be found. Further signal-to-noise ratio can be obtained. Previous theoretical models consider only linear gain condition. However the influence of laser pulse width and other factors are less taken into consideration. These models will have a certain deviation with the actual one. By simulating the nonlinear gain with consideration of the laser pulse width and lambert spherical radiation, more accurate SNR model of gain modulation laser imaging is obtained. On this basis, the established SNR model can be used to estimate the experimental distance with good imaging effect. It provides the theoretical basis for subsequent experiment system parameter selection and image processing.

  5. Seesaw majoron model of neutrino mass and novel signals in Higgs boson production at LEP

    NASA Astrophysics Data System (ADS)

    Díaz, Marco A.; García-Jareño, M. A.; Restrepo, Diego A.; Valle, José W. F.

    1998-08-01

    We perform a careful study of the neutral scalar sector of a model which includes a singlet, a doublet, and a triplet scalar field under SU(2). This model is motivated by neutrino physics, since it is simply the most general version of the seesaw model of neutrino mass generation through spontaneous violation of lepton number. The neutral Higgs sector contains three CP-even and one massive CP-odd Higgs boson A, in addition to the massless CP-odd mojoron J. The weakly interacting majoron remains massless if the breaking of lepton number symmetry is purely spontaneous. We show that the massive CP-odd Higgs boson may invisibly decay to three majorons, as well as to a CP-even Higgs H boson plus a majoron. We consider the associated Higgs production e+e- → Z → HA followed by invisible decays A → JJJ and H → JJ and derive the corresponding limits on masses and coupling that follow from LEP I precision measurements of the invisible Z width. We also study a novel b overlinebb overlinebp T signal predicted by the model, analyze the background and perform a Monte Carlo simulation of the signal in order to illustrate the limits on Higgs boson mass, couplings and branching ratios that follow from that.

  6. Resource holding potential, subjective resource value, and game theoretical models of aggressiveness signalling.

    PubMed

    Hurd, Peter L

    2006-08-01

    Empirical evidence suggests that aggressiveness (willingness to enter into, or escalate an aggressive interaction) may be more important than the ability to win fights in some species. Both empirical and theoretical traditions treat aggressiveness as a distinct property from the ability (RHP) or motivation (subjective resource value) to win a fight. I examine how these three traits are clearly distinct when modelled using a simple strategic model of escalation. I then examine game theoretical models of agonistic communication and demonstrate that models in which aggressiveness is signalled require: (1) a trait, aggressiveness, which is neither a correlate, nor consequence of RHP or motivation, (2) a handicap which negates any benefit to be gained through the use of a particular signal, and (3) the absence of any other asymmetry which could be used to assign roles to players. I conclude that it is unlikely that these assumptions are ever met, and that empirical examples of "aggressiveness" are far more likely to represent long-term differences in subjective resource value.

  7. Responding to Vaccine Safety Signals during Pandemic Influenza: A Modeling Study

    PubMed Central

    Maro, Judith C.; Fryback, Dennis G.; Lieu, Tracy A.; Lee, Grace M.; Martin, David B.

    2014-01-01

    Background Managing emerging vaccine safety signals during an influenza pandemic is challenging. Federal regulators must balance vaccine risks against benefits while maintaining public confidence in the public health system. Methods We developed a multi-criteria decision analysis model to explore regulatory decision-making in the context of emerging vaccine safety signals during a pandemic. We simulated vaccine safety surveillance system capabilities and used an age-structured compartmental model to develop potential pandemic scenarios. We used an expert-derived multi-attribute utility function to evaluate potential regulatory responses by combining four outcome measures into a single measure of interest: 1) expected vaccination benefit from averted influenza; 2) expected vaccination risk from vaccine-associated febrile seizures; 3) expected vaccination risk from vaccine-associated Guillain-Barre Syndrome; and 4) expected change in vaccine-seeking behavior in future influenza seasons. Results Over multiple scenarios, risk communication, with or without suspension of vaccination of high-risk persons, were the consistently preferred regulatory responses over no action or general suspension when safety signals were detected during a pandemic influenza. On average, the expert panel valued near-term vaccine-related outcomes relative to long-term projected outcomes by 3∶1. However, when decision-makers had minimal ability to influence near-term outcomes, the response was selected primarily by projected impacts on future vaccine-seeking behavior. Conclusions The selected regulatory response depends on how quickly a vaccine safety signal is identified relative to the peak of the pandemic and the initiation of vaccination. Our analysis suggested two areas for future investment: efforts to improve the size and timeliness of the surveillance system and behavioral research to understand changes in vaccine-seeking behavior. PMID:25536228

  8. Epithelial EGF receptor signaling mediates airway hyperreactivity and remodeling in a mouse model of chronic asthma.

    PubMed

    Le Cras, Timothy D; Acciani, Thomas H; Mushaben, Elizabeth M; Kramer, Elizabeth L; Pastura, Patricia A; Hardie, William D; Korfhagen, Thomas R; Sivaprasad, Umasundari; Ericksen, Mark; Gibson, Aaron M; Holtzman, Michael J; Whitsett, Jeffrey A; Hershey, Gurjit K Khurana

    2011-03-01

    Increases in the epidermal growth factor receptor (EGFR) have been associated with the severity of airway thickening in chronic asthmatic subjects, and EGFR signaling is induced by asthma-related cytokines and inflammation. The goal of this study was to determine the role of EGFR signaling in a chronic allergic model of asthma and specifically in epithelial cells, which are increasingly recognized as playing an important role in asthma. EGFR activation was assessed in mice treated with intranasal house dust mite (HDM) for 3 wk. EGFR signaling was inhibited in mice treated with HDM for 6 wk, by using either the drug erlotinib or a genetic approach that utilizes transgenic mice expressing a mutant dominant negative epidermal growth factor receptor in the lung epithelium (EGFR-M mice). Airway hyperreactivity (AHR) was assessed by use of a flexiVent system after increasing doses of nebulized methacholine. Airway smooth muscle (ASM) thickening was measured by morphometric analysis. Sensitization to HDM (IgG and IgE), inflammatory cells, and goblet cell changes were also assessed. Increased EGFR activation was detected in HDM-treated mice, including in bronchiolar epithelial cells. In mice exposed to HDM for 6 wk, AHR and ASM thickening were reduced after erlotinib treatment and in EGFR-M mice. Sensitization to HDM and inflammatory cell counts were similar in all groups, except neutrophil counts, which were lower in the EGFR-M mice. Goblet cell metaplasia with HDM treatment was reduced by erlotinib, but not in EGFR-M transgenic mice. This study demonstrates that EGFR signaling, especially in the airway epithelium, plays an important role in mediating AHR and remodeling in a chronic allergic asthma model.

  9. Time-varying autoregressive modelling for nonstationary acoustic signal and its frequency analysis

    NASA Astrophysics Data System (ADS)

    Sodsri, Chukiet

    2003-06-01

    A time-varying autoregressive (TVAR) approach is used for modeling nonstationary signals, and frequency information is then extracted from the TVAR parameters. Two methods may be used for estimating the TVAR parameters: the adaptive algorithm approach and the basis function approach. Adaptive algorithms, such as the least mean square (LMS) and the recursive least square (RLS), use a dynamic model for adapting the TVAR parameters and are capable of tracking time-varying frequency, provided that the variation is slow. It is observed that, if the signals have a single time-frequency component, the RLS with a fixed pole on the unit circle yields the fastest convergence. The basis function method employs an explicit model for the TVAR parameter variation, and model parameters are estimated via a block calculation. We proposed a modification to the basis function method by utilizing both forward and backward predictors for estimating the time-varying spectral density of nonstationary signals. It is shown that our approach yields better accuracy than the existing basis function approach, which uses only the forward predictor. The selection of the basis functions and limitations are also discussed in this thesis. Finally, the proposed approach is applied to analyze violin vibrato. Our results showed superior frequency resolution and spectral line smoothness using the proposed approach, compared to conventional analysis with the short time Fourier transform (STFT) whose frequency resolution is very limited. It was also found that frequency modulation of vibrato occurs at the rate of 6 Hz, and the frequency variations for each partial are different and increase nonlinearly with the partial number.

  10. Modeling the Failure of Magmatic Foams and Application to Infrasonic Signals at Stromboli Volcano, Italy

    NASA Astrophysics Data System (ADS)

    Baker, D. R.; O'Shaughnessy, C. A.; Brun, F.; Mancini, L.; Fife, J.

    2014-12-01

    The failure of magmatic foams appears to be a fundamental eruption process at open-conduit, basaltic volcanoes. We applied the fiber bundle model using global load sharing to model the failure of magmatic foams. The fiber strengths in the model were taken from bubble wall widths measured in four computer-simulated foams and by X-ray tomographic microscopy in three foams produced in the laboratory by heating hydrated basaltic glasses at 1 atm. to 1200 °C. The strengths of the modeled foams were calibrated based upon the correlation of the strength of one foam with published experimental data. The fiber bundle model successfully reproduced measured tensile strengths of porous volcanic rocks studied by other researchers and confirms published findings of the primary importance of foam porosity, as well as the secondary importance of structural details that affect the number and size of bubble walls and permeability. The success of the fiber bundle model in reproducing foam strengths encouraged us to compare its predictions with infrasonic measurements associated with bubbles at Stromboli (Italy). We found that within uncertainty the power-law exponents of the infrasonic energies and of the fiber bundle model energies are in agreement. They both show a cross-over from an exponent of 5/2 associated with the bursting of small bubbles in the infrasonic measurements to an exponent of 3/2 for normal Strombolian eruptions associated with infrasonic signals from meter-scale bubbles. The infrasonic signals for major explosions and a paroxysmal eruption at Stromboli fall near the extrapolation of the power law defined by the low-amplitude, bubble bursting events. The measurement of small-amplitude infrasonic events at Stromboli thus appear useful in predicting the recurrence interval of paroxysmal eruptions at this volcano and may also provide a tool that uses common, small-amplitude infrasonic events to constrain the frequency of larger eruptions at other volcanoes.

  11. An accelerated failure time model for investigating pedestrian crossing behavior and waiting times at signalized intersections.

    PubMed

    Yang, Xiaobao; Abdel-Aty, Mohamed; Huan, Mei; Peng, Yichuan; Gao, Ziyou

    2015-09-01

    The waiting process is crucial to pedestrians in the street-crossing behavior. Once pedestrians terminate their waiting behavior during the red light period, they would cross against the red light and put themselves in danger. A joint hazard-based duration model is developed to investigate the effect of various covariates on pedestrian crossing behavior and to estimate pedestrian waiting times at signalized intersections. A total of 1181 pedestrians approaching the intersections during red light periods were observed in Beijing, China. Pedestrian crossing behaviors are classified into immediate crossing behavior and waiting behavior. The probability and effect of various covariates for pedestrians' immediate crossing behavior are identified by a logit model. Four accelerated failure time duration models based on the exponential, Weibull, lognormal and log-logistic distributions are proposed to examine the significant risk factors affecting duration times for pedestrians' waiting behavior. A joint duration model is developed to estimate pedestrian waiting times. Moreover, unobserved heterogeneity is considered in the proposed model. The results indicate that the Weibull AFT model with shared frailty is appropriate for modelling pedestrian waiting durations. Failure to account for heterogeneity would significantly underestimate the effects of covariates on waiting duration times. The proposed model provides a better understanding of pedestrian crossing behavior and more accurate estimation of pedestrian waiting times. It may be applicable in traffic system analysis in developing countries with high flow of mixed traffic.

  12. Multiple-model nonlinear filtering for low-signal ground target applications

    NASA Astrophysics Data System (ADS)

    Kreucher, Chris M.; Kastella, Keith D.

    2001-08-01

    This paper describes the design and implementation of multiple model nonlinear filters (MMNLF) for ground target tracking using Ground Moving Target Indicator (GMTI) radar measurements. The MMNLF is based on a general theory of hybrid continuous-discrete dynamics. The motion model state is discrete and its stochastic dynamics are a continuous- time Markov chain. For each motion model, the continuum dynamics are a continuous-state Markov process described here by appropriate Fokker-Plank equations. This is illustrated here by a specific two-model MMNLF in which one motion model incorporates terrain, road, and vehicle motion constraints derived from battlefield observations. The second model is slow diffusion in speed and heading. The target state conditional probability density is discretized on a moving grid and recursively updated with sensor measurements via Bayes' formula. The conditional density is time updated between sensor measurements using Alternating Direction Implicit (ADI) finite difference methods. In simulation testing against low signal to clutter + noise Ratio (SNCR) targets, the MMNLF is able to maintain track in situations where single model filters based on either of the component models fail. Potential applications of this work include detection and tracking of foliage-obscured moving targets.

  13. The aerodynamic costs of warning signals in palatable mimetic butterflies and their distasteful models.

    PubMed Central

    Srygley, Robert B.

    2004-01-01

    Bates hypothesized that some butterfly species that are palatable gain protection from predation by appearing similar to distasteful butterflies. When undisturbed, distasteful butterflies fly slowly and in a straight line, and palatable Batesian mimics also adopt this nonchalant behaviour. When seized by predators, distasteful butterflies are defended by toxic or nauseous chemicals. Lacking chemical defences, Batesian mimics depend on flight to escape attacks. Here, I demonstrate that flight in warning-coloured mimetic butterflies and their distasteful models is more costly than in closely related non-mimetic butterflies. The increased cost is the result of differences in both wing shape and kinematics. Batesian mimics and their models slow the angular velocity of their wings to enhance the colour signal but at an aerodynamic cost. Moreover, the design for flight in Batesian mimics has an additional energetic cost over that of its models. The added cost may cause Batesian mimics to be rare, explaining a general pattern that Bates first observed. PMID:15156916

  14. Nrf2 Signaling and the Slowed Aging Phenotype: Evidence from Long-Lived Models

    PubMed Central

    Bruns, Danielle R.; Drake, Joshua C.; Biela, Laurie M.; Peelor, Frederick F.; Miller, Benjamin F.; Hamilton, Karyn L.

    2015-01-01

    Studying long-lived animals provides novel insight into shared characteristics of aging and represents a unique model to elucidate approaches to prevent chronic disease. Oxidant stress underlies many chronic diseases and resistance to stress is a potential mechanism governing slowed aging. The transcription factor nuclear factor (erythroid-derived 2)-like 2 is the “master regulator” of cellular antioxidant defenses. Nrf2 is upregulated by some longevity promoting interventions and may play a role in regulating species longevity. However, Nrf2 expression and activity in long-lived models have not been well described. Here, we review evidence for altered Nrf2 signaling in a variety of slowed aging models that accomplish lifespan extension via pharmacological, nutritional, evolutionary, genetic, and presumably epigenetic means. PMID:26583062

  15. Modeling and analysis of early events in T-lymphocyte antigen-activated intracellular-signaling pathways

    NASA Astrophysics Data System (ADS)

    Zheng, Yanan; Balakrishnan, Venkataramanan; Buzzard, Greg; Geahlen, Robert; Harrison, Marietta; Rundell, Ann

    2005-12-01

    The T-cell antigen-activated signaling pathway is a highly regulated intracellular biochemical system that is crucial for initiating an appropriate adaptive immune response. To improve the understanding of the complex regulatory mechanisms controlling the early events in T-cell signaling, a detailed mathematical model was developed that utilizes ordinary differential equations to describe chemical reactions of the signaling pathway. The model parameter values were constrained by experimental data on the activation of a specific signaling intermediate and indicated an initial rapid cascade of phosphorylation events followed by a comparatively slow signal downregulation. Nonlinear analysis of the model suggested that thresholding and bistability occur as a result of the embedded positive and negative feedback loops within the model. These nonlinear system properties may enhance the T-cell receptor specificity and provide sub-threshold noise filtering with switch-like behavior to ensure proper cell response. Additional analysis using a reduced second-order model led to further understanding of the observed system behavior. Moreover, the interactions between the positive and negative feedback loops enabled the model to exhibit, among a variety of other feasible dynamics, a sustained oscillation that corresponds to a stable limit cycle in the two-dimensional phase plane. Quantitative analysis in this paper has helped identify potential regulatory mechanisms in the early T-cell signaling events. This integrated approach provides a framework to quantify and discover the ensemble of interconnected T-cell antigen-activated signaling pathways from limited experimental data.

  16. Inhibiting TGF-β signaling restores immune surveillance in the SMA-560 glioma model

    PubMed Central

    Tran, Thomas-Toan; Uhl, Martin; Ma, Jing Ying; Janssen, Lisa; Sriram, Venkataraman; Aulwurm, Steffen; Kerr, Irene; Lam, Andrew; Webb, Heather K.; Kapoun, Ann M.; Kizer, Darin E.; McEnroe, Glenn; Hart, Barry; Axon, Jonathan; Murphy, Alison; Chakravarty, Sarvajit; Dugar, Sundeep; Protter, Andrew A.; Higgins, Linda S.; Wick, Wolfgang; Weller, Michael; Wong, Darren H.

    2007-01-01

    Transforming growth factor-β (TGF-β) is a proinvasive and immunosuppressive cytokine that plays a major role in the malignant phenotype of gliomas. One novel strategy of disabling TGF-β activity in gliomas is to disrupt the signaling cascade at the level of the TGF-β receptor I (TGF-βRI) kinase, thus abrogating TGF-β–mediated invasiveness and immune suppression. SX-007, an orally active, small-molecule TGF-βRI kinase inhibitor, was evaluated for its therapeutic potential in cell culture and in an in vivo glioma model. The syngeneic, orthotopic glioma model SMA-560 was used to evaluate the efficacy of SX-007. Cells were implanted into the striatum of VM/ Dk mice. Dosing began three days after implantation and continued until the end of the study. Efficacy was established by assessing survival benefit. SX-007 dosed at 20 mg/kg p.o. once daily (q.d.) modulated TGF-β signaling in the tumor and improved the median survival. Strikingly, approximately 25% of the treated animals were disease-free at the end of the study. Increasing the dose to 40 mg/kg q.d. or 20 mg/kg twice daily did not further improve efficacy. The data suggest that SX-007 can exert a therapeutic effect by reducing TGF-β–mediated invasion and reversing immune suppression. SX-007 modulates the TGF-β signaling pathway and is associated with improved survival in this glioma model. Survival benefit is due to reduced tumor invasion and reversal of TGF-β–mediated immune suppression, allowing for rejection of the tumor. Together, these results suggest that treatment with a TGF-βRI inhibitor may be useful in the treatment of glioblastoma. PMID:17522330

  17. BDNF signaling contributes to oral cancer pain in a preclinical orthotopic rodent model

    PubMed Central

    Chodroff, Leah; Bendele, Michelle; Valenzuela, Vanessa; Henry, Michael

    2016-01-01

    The majority of patients with oral cancer report intense pain that is only partially managed by current analgesics. Thus, there is a strong need to study mechanisms as well as develop novel analgesics for oral cancer pain. Current study employed an orthotopic tongue cancer model with molecular and non-reflexive behavioral assays to determine possible mechanisms of oral cancer pain. Human oral squamous cell carcinoma cells line, HSC2, was injected into the tongue of male athymic mice and tumor growth was observed by day 6. Immunohistological analyses revealed a well-differentiated tumor with a localized immune response and pronounced sensory and sympathetic innervation and vascularization. The tumor expressed TMPRSS2, a protein previously reported with oral squamous cell carcinoma. ATF3 expression in trigeminal ganglia was not altered by tumor growth. Molecular characterization of the model demonstrated altered expression of several pain-related genes, out of which up-regulation of BDNF was most striking. Moreover, BDNF protein expression in trigeminal ganglia neurons was increased and inhibition of BDNF signaling with a tyrosine kinase B antagonist, ANA-12, reversed pain-like behaviors induced by the oral tumor. Oral squamous cell carcinoma tumor growth was also associated with a reduction in feeding, mechanical hypersensitivity in the face, as well as spontaneous pain behaviors as measured by the conditioned place preference test, all of which were reversed by analgesics. Interestingly, injection of HSC2 into the hindpaw did not reproduce this spectrum of pain behaviors; nor did injection of a colonic cancer cell line into the tongue. Taken together, this orthotopic oral cancer pain model reproduces the spectrum of pain reported by oral cancer patients, including higher order cognitive changes, and demonstrates that BDNF signaling constitutes a novel mechanism by which oral squamous cell carcinoma induces pain. Identification of the key role of tyrosine kinase B

  18. Modeling the intra- and extracellular cytokine signaling pathway under heat stroke in the liver.

    PubMed

    Rodriguez-Fernandez, Maria; Grosman, Benyamin; Yuraszeck, Theresa M; Helwig, Bryan G; Leon, Lisa R; Doyle, Francis J

    2013-01-01

    Heat stroke (HS) is a life-threatening illness induced by prolonged exposure to a hot environment that causes central nervous system abnormalities and severe hyperthermia. Current data suggest that the pathophysiological responses to heat stroke may not only be due to the immediate effects of heat exposure per se but also the result of a systemic inflammatory response syndrome (SIRS). The observation that pro- (e.g., IL-1) and anti-inflammatory (e.g., IL-10) cytokines are elevated concomitantly during recovery suggests a complex network of interactions involved in the manifestation of heat-induced SIRS. In this study, we measured a set of circulating cytokine/soluble cytokine receptor proteins and liver cytokine and receptor mRNA accumulation in wild-type and tumor necrosis factor (TNF) receptor knockout mice to assess the effect of neutralization of TNF signaling on the SIRS following HS. Using a systems approach, we developed a computational model describing dynamic changes (intra- and extracellular events) in the cytokine signaling pathways in response to HS that was fitted to novel genomic (liver mRNA accumulation) and proteomic (circulating cytokines and receptors) data using global optimization. The model allows integration of relevant biological knowledge and formulation of new hypotheses regarding the molecular mechanisms behind the complex etiology of HS that may serve as future therapeutic targets. Moreover, using our unique modeling framework, we explored cytokine signaling pathways with three in silico experiments (e.g. by simulating different heat insult scenarios and responses in cytokine knockout strains in silico). PMID:24039931

  19. Modeling the Intra- and Extracellular Cytokine Signaling Pathway under Heat Stroke in the Liver

    PubMed Central

    Rodriguez-Fernandez, Maria; Grosman, Benyamin; Yuraszeck, Theresa M.; Helwig, Bryan G.; Leon, Lisa R.; Doyle III, Francis J.

    2013-01-01

    Heat stroke (HS) is a life-threatening illness induced by prolonged exposure to a hot environment that causes central nervous system abnormalities and severe hyperthermia. Current data suggest that the pathophysiological responses to heat stroke may not only be due to the immediate effects of heat exposure per se but also the result of a systemic inflammatory response syndrome (SIRS). The observation that pro- (e.g., IL-1) and anti-inflammatory (e.g., IL-10) cytokines are elevated concomitantly during recovery suggests a complex network of interactions involved in the manifestation of heat-induced SIRS. In this study, we measured a set of circulating cytokine/soluble cytokine receptor proteins and liver cytokine and receptor mRNA accumulation in wild-type and tumor necrosis factor (TNF) receptor knockout mice to assess the effect of neutralization of TNF signaling on the SIRS following HS. Using a systems approach, we developed a computational model describing dynamic changes (intra- and extracellular events) in the cytokine signaling pathways in response to HS that was fitted to novel genomic (liver mRNA accumulation) and proteomic (circulating cytokines and receptors) data using global optimization. The model allows integration of relevant biological knowledge and formulation of new hypotheses regarding the molecular mechanisms behind the complex etiology of HS that may serve as future therapeutic targets. Moreover, using our unique modeling framework, we explored cytokine signaling pathways with three in silico experiments (e.g. by simulating different heat insult scenarios and responses in cytokine knockout strains in silico). PMID:24039931

  20. Encoding electric signals by Gymnotus omarorum: heuristic modeling of tuberous electroreceptor organs.

    PubMed

    Cilleruelo, Esteban R; Caputi, Angel Ariel

    2012-01-24

    The role of different substructures of electroreceptor organs in signal encoding was explored using a heuristic computational model. This model consists of four modules representing the pre-receptor structures, the transducer cells, the synapses and the afferent fiber, respectively. Simulations reproduced previously obtained experimental data. We showed that different electroreceptor types described in the literature can be qualitative modeled with the same set of equations by changing only two parameters, one affecting the filtering properties of the pre-receptor, and the other affecting the transducer module. We studied the responses of different electroreceptor types to natural stimuli using simulations derived from an experimentally-obtained database in which the fish were exposed to resistive or capacitive objects. Our results indicate that phase and frequency spectra are differentially encoded by different subpopulations of tuberous electroreceptors. A different type of receptor responses to the same input is a necessary condition for encoding a multidimensional space of stimuli as in the waveform of the EOD. Our simulation analysis suggested that the electroreceptive mosaic may perform a waveform analysis of electrosensory signals. As in color vision or tactile texture perception, a secondary attribute, "electric color" may be encoded as a parallel activity of various electroreceptor types. This article is part of a Special Issue entitled Neural Coding. PMID:21835395

  1. Methodologies for the modeling and simulation of biochemical networks, illustrated for signal transduction pathways: a primer.

    PubMed

    ElKalaawy, Nesma; Wassal, Amr

    2015-03-01

    Biochemical networks depict the chemical interactions that take place among elements of living cells. They aim to elucidate how cellular behavior and functional properties of the cell emerge from the relationships between its components, i.e. molecules. Biochemical networks are largely characterized by dynamic behavior, and exhibit high degrees of complexity. Hence, the interest in such networks is growing and they have been the target of several recent modeling efforts. Signal transduction pathways (STPs) constitute a class of biochemical networks that receive, process, and respond to stimuli from the environment, as well as stimuli that are internal to the organism. An STP consists of a chain of intracellular signaling processes that ultimately result in generating different cellular responses. This primer presents the methodologies used for the modeling and simulation of biochemical networks, illustrated for STPs. These methodologies range from qualitative to quantitative, and include structural as well as dynamic analysis techniques. We describe the different methodologies, outline their underlying assumptions, and provide an assessment of their advantages and disadvantages. Moreover, publicly and/or commercially available implementations of these methodologies are listed as appropriate. In particular, this primer aims to provide a clear introduction and comprehensive coverage of biochemical modeling and simulation methodologies for the non-expert, with specific focus on relevant literature of STPs.

  2. Bioelectrical Signals and Ion Channels in the Modeling of Multicellular Patterns and Cancer Biophysics.

    PubMed

    Cervera, Javier; Alcaraz, Antonio; Mafe, Salvador

    2016-02-04

    Bioelectrical signals and ion channels are central to spatial patterns in cell ensembles, a problem of fundamental interest in positional information and cancer processes. We propose a model for electrically connected cells based on simple biological concepts: i) the membrane potential of a single cell characterizes its electrical state; ii) the long-range electrical coupling of the multicellular ensemble is realized by a network of gap junction channels between neighboring cells; and iii) the spatial distribution of an external biochemical agent can modify the conductances of the ion channels in a cell membrane and the multicellular electrical state. We focus on electrical effects in small multicellular ensembles, ignoring slow diffusional processes. The spatio-temporal patterns obtained for the local map of cell electric potentials illustrate the normalization of regions with abnormal cell electrical states. The effects of intercellular coupling and blocking of specific channels on the electrical patterns are described. These patterns can regulate the electrically-induced redistribution of charged nanoparticles over small regions of a model tissue. The inclusion of bioelectrical signals provides new insights for the modeling of cancer biophysics because collective multicellular states show electrical coupling mechanisms that are not readily deduced from biochemical descriptions at the individual cell level.

  3. Bioelectrical Signals and Ion Channels in the Modeling of Multicellular Patterns and Cancer Biophysics

    PubMed Central

    Cervera, Javier; Alcaraz, Antonio; Mafe, Salvador

    2016-01-01

    Bioelectrical signals and ion channels are central to spatial patterns in cell ensembles, a problem of fundamental interest in positional information and cancer processes. We propose a model for electrically connected cells based on simple biological concepts: i) the membrane potential of a single cell characterizes its electrical state; ii) the long-range electrical coupling of the multicellular ensemble is realized by a network of gap junction channels between neighboring cells; and iii) the spatial distribution of an external biochemical agent can modify the conductances of the ion channels in a cell membrane and the multicellular electrical state. We focus on electrical effects in small multicellular ensembles, ignoring slow diffusional processes. The spatio-temporal patterns obtained for the local map of cell electric potentials illustrate the normalization of regions with abnormal cell electrical states. The effects of intercellular coupling and blocking of specific channels on the electrical patterns are described. These patterns can regulate the electrically-induced redistribution of charged nanoparticles over small regions of a model tissue. The inclusion of bioelectrical signals provides new insights for the modeling of cancer biophysics because collective multicellular states show electrical coupling mechanisms that are not readily deduced from biochemical descriptions at the individual cell level. PMID:26841954

  4. Bioelectrical Signals and Ion Channels in the Modeling of Multicellular Patterns and Cancer Biophysics.

    PubMed

    Cervera, Javier; Alcaraz, Antonio; Mafe, Salvador

    2016-01-01

    Bioelectrical signals and ion channels are central to spatial patterns in cell ensembles, a problem of fundamental interest in positional information and cancer processes. We propose a model for electrically connected cells based on simple biological concepts: i) the membrane potential of a single cell characterizes its electrical state; ii) the long-range electrical coupling of the multicellular ensemble is realized by a network of gap junction channels between neighboring cells; and iii) the spatial distribution of an external biochemical agent can modify the conductances of the ion channels in a cell membrane and the multicellular electrical state. We focus on electrical effects in small multicellular ensembles, ignoring slow diffusional processes. The spatio-temporal patterns obtained for the local map of cell electric potentials illustrate the normalization of regions with abnormal cell electrical states. The effects of intercellular coupling and blocking of specific channels on the electrical patterns are described. These patterns can regulate the electrically-induced redistribution of charged nanoparticles over small regions of a model tissue. The inclusion of bioelectrical signals provides new insights for the modeling of cancer biophysics because collective multicellular states show electrical coupling mechanisms that are not readily deduced from biochemical descriptions at the individual cell level. PMID:26841954

  5. Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model

    PubMed Central

    Minoarivelo, H. O.; Hui, C.; Terblanche, J. S.; Pond, S. L. Kosakovsky; Scheffler, K.

    2014-01-01

    Ecological interaction networks, such as those describing the mutualistic interactions between plants and their pollinators or between plants and their frugivores, exhibit non-random structural properties that cannot be explained by simple models of network formation. One factor affecting the formation and eventual structure of such a network is its evolutionary history. We argue that this, in many cases, is closely linked to the evolutionary histories of the species involved in the interactions. Indeed, empirical studies of interaction networks along with the phylogenies of the interacting species have demonstrated significant associations between phylogeny and network structure. To date, however, no generative model explaining the way in which the evolution of individual species affects the evolution of interaction networks has been proposed. We present a model describing the evolution of pairwise interactions as a branching Markov process, drawing on phylogenetic models of molecular evolution. Using knowledge of the phylogenies of the interacting species, our model yielded a significantly better fit to 21% of a set of plant – pollinator and plant – frugivore mutualistic networks. This highlights the importance, in a substantial minority of cases, of inheritance of interaction patterns without excluding the potential role of ecological novelties in forming the current network architecture. We suggest that our model can be used as a null model for controlling evolutionary signals when evaluating the role of other factors in shaping the emergence of ecological networks. PMID:25294947

  6. A pain-mediated neural signal induces relapse in murine autoimmune encephalomyelitis, a multiple sclerosis model

    PubMed Central

    Arima, Yasunobu; Kamimura, Daisuke; Atsumi, Toru; Harada, Masaya; Kawamoto, Tadafumi; Nishikawa, Naoki; Stofkova, Andrea; Ohki, Takuto; Higuchi, Kotaro; Morimoto, Yuji; Wieghofer, Peter; Okada, Yuka; Mori, Yuki; Sakoda, Saburo; Saika, Shizuya; Yoshioka, Yoshichika; Komuro, Issei; Yamashita, Toshihide; Hirano, Toshio; Prinz, Marco; Murakami, Masaaki

    2015-01-01

    Although pain is a common symptom of various diseases and disorders, its contribution to disease pathogenesis is not well understood. Here we show using murine experimental autoimmune encephalomyelitis (EAE), a model for multiple sclerosis (MS), that pain induces EAE relapse. Mechanistic analysis showed that pain induction activates a sensory-sympathetic signal followed by a chemokine-mediated accumulation of MHC class II+CD11b+ cells that showed antigen-presentation activity at specific ventral vessels in the fifth lumbar cord of EAE-recovered mice. Following this accumulation, various immune cells including pathogenic CD4+ T cells recruited in the spinal cord in a manner dependent on a local chemokine inducer in endothelial cells, resulting in EAE relapse. Our results demonstrate that a pain-mediated neural signal can be transformed into an inflammation reaction at specific vessels to induce disease relapse, thus making this signal a potential therapeutic target. DOI: http://dx.doi.org/10.7554/eLife.08733.001 PMID:26193120

  7. Coupling vs decoupling approaches for PDE/ODE systems modeling intercellular signaling

    NASA Astrophysics Data System (ADS)

    Carraro, Thomas; Friedmann, Elfriede; Gerecht, Daniel

    2016-06-01

    We consider PDE/ODE systems for the simulation of intercellular signaling in multicellular environments. The intracellular processes for each cell described here by ODEs determine the long-time dynamics, but the PDE part dominates the solving effort. Thus, it is not clear if commonly used decoupling methods can outperform a coupling approach. Based on a sensitivity analysis, we present a systematic comparison between coupling and decoupling approaches for this class of problems and show numerical results. For biologically relevant configurations of the model, our quantitative study shows that a coupling approach performs much better than a decoupling one.

  8. A discussion of observation model, error sources and signal size for spaceborne gravitational gradiometry

    NASA Technical Reports Server (NTRS)

    Rummel, R.; Koop, R.; Schrama, E. J. O.

    1989-01-01

    Various space concepts were discussed during the past 20 years for a global improvement of the knowledge of the earth's gravity field. The concepts reach from high-low and low-low satellite-to-satellite tracking via tethered satellite gradiometers to sophisticated superconducting gradiometers. The purpose is to show that starting from one basic equation three criteria are sufficient to typify the various concepts and define the underlying observation model. Furthermore the different error sources, in particular, the time varying part of self-gravitation, and the expected signal size of all six gravity gradient components shall be discussed.

  9. User's guide for a large signal computer model of the helical traveling wave tube

    NASA Technical Reports Server (NTRS)

    Palmer, Raymond W.

    1992-01-01

    The use is described of a successful large-signal, two-dimensional (axisymmetric), deformable disk computer model of the helical traveling wave tube amplifier, an extensively revised and operationally simplified version. We also discuss program input and output and the auxiliary files necessary for operation. Included is a sample problem and its input data and output results. Interested parties may now obtain from the author the FORTRAN source code, auxiliary files, and sample input data on a standard floppy diskette, the contents of which are described herein.

  10. Numerical modeling and characterization of rock avalanches and associated seismic signal

    NASA Astrophysics Data System (ADS)

    Moretti, L.; Mangeney, A.; Capdeville, Y.; Stutzmann, E.; Lucas, A.; Huggel, C.; Schneider, D.; Crosta, G. B.; Bouchut, F.

    2012-04-01

    recorded seismic signal depends on the characteristics of the landslide (volume, mass, friction coefficient…) and on the earth model (seismic waves velocity, number of layers…) used to calculate wave propagation. Favreau, P., Mangeney, A., Lucas, A., Crosta, G.B., and F. Bouchut, Numerical modeling of landquakes. Geophysical Research Letters, VOL. 37, L15305, doi:10.1029/2010GL043512, 2010 Huggel, C., Caplan-Auerbach, J., Molnia, B. and Wessels R. (2008), The 2005 Mt. Steller, Alaska, rock-ice avalanche: A large slope failure in cold permafrost, Proceedings of the Ninth International Conference on Permafrost, vol. 1., p. 747-752, Univ. of Alaska Fairbanks

  11. A Possible Source Model for VLP Signals in Bayou Corne, LA

    NASA Astrophysics Data System (ADS)

    Leidig, M.; Stroujkova, A. F.

    2013-12-01

    Very Long Period (VLP) signals have been recorded in the Bayou Corne area since the formation of a sinkhole resulting from failed a salt cavern. Sediment and/or water migration is hypothesized to be responsible for these signals. Some key observations regarding these signals include: 1. VLP signals are best recorded at an individual station (LA12) to the southwest of the sinkhole. 2. First VLP event detected 3 days after the sinkhole formed, months after the first seismic events. 3. VLP events increase dramatically in the days preceding sinkhole activity. 4. Natural gas migration potentially occurred for a period of time, possibly months, prior to first VLP event detection. 5. Area near LA12 has undergone at least 2 m of subsidence. 6. VLP activity has continued, even as the cavern has nearly filled with sediment. We have examined various possible source mechanisms in order to understand the origin of the VLP signals. A damped oscillator model in which a surface layer vibrates in response to external disturbances best describes the observed VLP events. The model likely represents the shallow Upper Aquitard (UA) oscillating on top of the Mississippi River Alluvial Aquifer (MRAA). In order for the clay layer of the UA to undulate, the sediments in the MRAA would need to be in a fluidized state, with a viscosity similar to tar or magma. The MRAA is fully saturated with water, and small injections of water into the MRAA could temporarily and locally fluidize the sands and disturb the UA creating a VLP event. In addition, small earthquakes can disturb the system and trigger the oscillations. Lateral movement of fluidized sediments could also disturb the UA and generate a VLP in addition to explaining subsidence near LA12. Lateral extrusion of material into the sinkhole also fits with the lack of detected VLP events prior to the sinkhole formation and the increase in VLP events prior to sinkhole activity. Repeated mappings of the sinkhole geometry indicate the maximum

  12. Palaeoclimate signal recorded by stable isotopes in cave ice: a modeling approach

    NASA Astrophysics Data System (ADS)

    Perşoiu, A.; Bojar, A.-V.

    2012-04-01

    Ice accumulations in caves preserve a large variety of geochemical information as candidate proxies for both past climate and environmental changes, one of the most significant being the stable isotopic composition of the ice. A series of recent studies have targeted oxygen and hydrogen stable isotopes in cave ice as proxies for past air temperatures, but the results are far from being as straightforward as they are in high latitude and altitude glaciers and ice caps. The main problems emerging from these studies are related to the mechanisms of cave ice formation (i.e., freezing of water) and post-formation processes (melting and refreezing), which both alter the original isotopic signal in water. Different methods have been put forward to solve these issues and a fair understanding of the present-day link between stable isotopes in precipitation and cave ice exists now. However, the main issues still lays unsolved: 1) is it possible to extend this link to older ice and thus reconstruct past changes in air temperature?; 2) to what extent are ice dynamics processes modifying the original climatic signal and 3) what is the best method to be used in extracting a climatic signal from stable isotopes in cave ice? To respond to these questions, we have conducted a modeling experiment, in which a theoretical cave ice stable isotope record was constructed using present-day observations on stable isotope behavior in cave ice and ice dynamics, and different methods (presently used for both polar and cave glaciers), were used to reconstruct the original, known, isotopic values. Our results show that it is possible to remove the effects of ice melting and refreezing on stable isotope composition of cave ice, and thus reconstruct the original isotopic signal, and further the climatic one.

  13. Vitamin D signaling in the bovine immune system: a model for understanding human vitamin D requirements.

    PubMed

    Nelson, Corwin D; Reinhardt, Timothy A; Lippolis, John D; Sacco, Randy E; Nonnecke, Brian J

    2012-03-01

    The endocrine physiology of vitamin D in cattle has been rigorously investigated and has yielded information on vitamin D requirements, endocrine function in health and disease, general metabolism, and maintenance of calcium homeostasis in cattle. These results are relevant to human vitamin D endocrinology. The current debate regarding vitamin D requirements is centered on the requirements for proper intracrine and paracrine vitamin D signaling. Studies in adult and young cattle can provide valuable insight for understanding vitamin D requirements as they relate to innate and adaptive immune responses during infectious disease. In cattle, toll-like receptor recognition activates intracrine and paracrine vitamin D signaling mechanism in the immune system that regulates innate and adaptive immune responses in the presence of adequate 25-hydroxyvitamin D. Furthermore, experiments with mastitis in dairy cattle have provided in vivo evidence for the intracrine vitamin D signaling mechanism in macrophages as well as vitamin D mediated suppression of infection. Epidemiological evidence indicates that circulating concentrations above 32 ng/mL of 25-hydroxyvitamin D are necessary for optimal vitamin D signaling in the immune system, but experimental evidence is lacking for that value. Experiments in cattle can provide that evidence as circulating 25-hydroxyvitamin D concentrations can be experimentally manipulated within ranges that are normal for humans and cattle. Additionally, young and adult cattle can be experimentally infected with bacteria and viruses associated with significant diseases in both cattle and humans. Utilizing the bovine model to further delineate the immunomodulatory role of vitamin D will provide potentially valuable insights into the vitamin D requirements of both humans and cattle, especially as they relate to immune response capacity and infectious disease resistance.

  14. Three-Dimensional Numerical Model of Cell Morphology during Migration in Multi-Signaling Substrates

    PubMed Central

    Mousavi, Seyed Jamaleddin; Hamdy Doweidar, Mohamed

    2015-01-01

    Cell Migration associated with cell shape changes are of central importance in many biological processes ranging from morphogenesis to metastatic cancer cells. Cell movement is a result of cyclic changes of cell morphology due to effective forces on cell body, leading to periodic fluctuations of the cell length and cell membrane area. It is well-known that the cell can be guided by different effective stimuli such as mechanotaxis, thermotaxis, chemotaxis and/or electrotaxis. Regulation of intracellular mechanics and cell’s physical interaction with its substrate rely on control of cell shape during cell migration. In this notion, it is essential to understand how each natural or external stimulus may affect the cell behavior. Therefore, a three-dimensional (3D) computational model is here developed to analyze a free mode of cell shape changes during migration in a multi-signaling micro-environment. This model is based on previous models that are presented by the same authors to study cell migration with a constant spherical cell shape in a multi-signaling substrates and mechanotaxis effect on cell morphology. Using the finite element discrete methodology, the cell is represented by a group of finite elements. The cell motion is modeled by equilibrium of effective forces on cell body such as traction, protrusion, electrostatic and drag forces, where the cell traction force is a function of the cell internal deformations. To study cell behavior in the presence of different stimuli, the model has been employed in different numerical cases. Our findings, which are qualitatively consistent with well-known related experimental observations, indicate that adding a new stimulus to the cell substrate pushes the cell to migrate more directionally in more elongated form towards the more effective stimuli. For instance, the presence of thermotaxis, chemotaxis and electrotaxis can further move the cell centroid towards the corresponding stimulus, respectively, diminishing the

  15. Fast generation model of high density surface EMG signals in a cylindrical conductor volume.

    PubMed

    Carriou, Vincent; Boudaoud, Sofiane; Laforet, Jeremy; Ayachi, Fouaz Sofiane

    2016-07-01

    In the course of the last decade, fast and qualitative computing power developments have undoubtedly permitted for a better and more realistic modeling of complex physiological processes. Due to this favorable environment, a fast, generic and reliable model for high density surface electromyographic (HD-sEMG) signal generation with a multilayered cylindrical description of the volume conductor is presented in this study. Its main peculiarity lies in the generation of a high resolution potential map over the skin related to active Motor Units (MUs). Indeed, the analytical calculus is fully performed in the frequency domain. HD-sEMG signals are obtained by surfacic numerical integration of the generated high resolution potential map following a variety of electrode shapes. The suggested model is implemented using parallel computing techniques as well as by using an object-oriented approach which is comprehensive enough to be fairly quickly understood, used and potentially upgraded. To illustrate the model abilities, several simulation analyses are put forward in the results section. These simulations have been performed on the same muscle anatomy while varying the number of processes in order to show significant speed improvement. Accuracy of the numerical integration method, illustrating electrode shape diversity, is also investigated in comparison to analytical transfer functions definition. An additional section provides an insight on the volume detection of a circular electrode according to its radius. Furthermore, a large scale simulation is introduced with 300MUs in the muscle and a HD-sEMG electrode grid composed of 16×16 electrodes for three constant isometric contractions in 12s. Finally, advantages and limitations of the proposed model are discussed with a focus on perspective works. PMID:27183535

  16. Fast generation model of high density surface EMG signals in a cylindrical conductor volume.

    PubMed

    Carriou, Vincent; Boudaoud, Sofiane; Laforet, Jeremy; Ayachi, Fouaz Sofiane

    2016-07-01

    In the course of the last decade, fast and qualitative computing power developments have undoubtedly permitted for a better and more realistic modeling of complex physiological processes. Due to this favorable environment, a fast, generic and reliable model for high density surface electromyographic (HD-sEMG) signal generation with a multilayered cylindrical description of the volume conductor is presented in this study. Its main peculiarity lies in the generation of a high resolution potential map over the skin related to active Motor Units (MUs). Indeed, the analytical calculus is fully performed in the frequency domain. HD-sEMG signals are obtained by surfacic numerical integration of the generated high resolution potential map following a variety of electrode shapes. The suggested model is implemented using parallel computing techniques as well as by using an object-oriented approach which is comprehensive enough to be fairly quickly understood, used and potentially upgraded. To illustrate the model abilities, several simulation analyses are put forward in the results section. These simulations have been performed on the same muscle anatomy while varying the number of processes in order to show significant speed improvement. Accuracy of the numerical integration method, illustrating electrode shape diversity, is also investigated in comparison to analytical transfer functions definition. An additional section provides an insight on the volume detection of a circular electrode according to its radius. Furthermore, a large scale simulation is introduced with 300MUs in the muscle and a HD-sEMG electrode grid composed of 16×16 electrodes for three constant isometric contractions in 12s. Finally, advantages and limitations of the proposed model are discussed with a focus on perspective works.

  17. Computationally efficient modeling of proprioceptive signals in the upper limb for prostheses: a simulation study

    PubMed Central

    Williams, Ian; Constandinou, Timothy G.

    2014-01-01

    Accurate models of proprioceptive neural patterns could 1 day play an important role in the creation of an intuitive proprioceptive neural prosthesis for amputees. This paper looks at combining efficient implementations of biomechanical and proprioceptor models in order to generate signals that mimic human muscular proprioceptive patterns for future experimental work in prosthesis feedback. A neuro-musculoskeletal model of the upper limb with 7 degrees of freedom and 17 muscles is presented and generates real time estimates of muscle spindle and Golgi Tendon Organ neural firing patterns. Unlike previous neuro-musculoskeletal models, muscle activation and excitation levels are unknowns in this application and an inverse dynamics tool (static optimization) is integrated to estimate these variables. A proprioceptive prosthesis will need to be portable and this is incompatible with the computationally demanding nature of standard biomechanical and proprioceptor modeling. This paper uses and proposes a number of approximations and optimizations to make real time operation on portable hardware feasible. Finally technical obstacles to mimicking natural feedback for an intuitive proprioceptive prosthesis, as well as issues and limitations with existing models, are identified and discussed. PMID:25009463

  18. Visual setup of logical models of signaling and regulatory networks with ProMoT

    PubMed Central

    Saez-Rodriguez, Julio; Mirschel, Sebastian; Hemenway, Rebecca; Klamt, Steffen; Gilles, Ernst Dieter; Ginkel, Martin

    2006-01-01

    Background The analysis of biochemical networks using a logical (Boolean) description is an important approach in Systems Biology. Recently, new methods have been proposed to analyze large signaling and regulatory networks using this formalism. Even though there is a large number of tools to set up models describing biological networks using a biochemical (kinetic) formalism, however, they do not support logical models. Results Herein we present a flexible framework for setting up large logical models in a visual manner with the software tool ProMoT. An easily extendible library, ProMoT's inherent modularity and object-oriented concept as well as adaptive visualization techniques provide a versatile environment. Both the graphical and the textual description of the logical model can be exported to different formats. Conclusion New features of ProMoT facilitate an efficient set-up of large Boolean models of biochemical interaction networks. The modeling environment is flexible; it can easily be adapted to specific requirements, and new extensions can be introduced. ProMoT is freely available from . PMID:17109765

  19. An analytical model for regular respiratory signals derived from the probability density function of Rayleigh distribution.

    PubMed

    Li, Xin; Li, Ye

    2015-01-01

    Regular respiratory signals (RRSs) acquired with physiological sensing systems (e.g., the life-detection radar system) can be used to locate survivors trapped in debris in disaster rescue, or predict the breathing motion to allow beam delivery under free breathing conditions in external beam radiotherapy. Among the existing analytical models for RRSs, the harmonic-based random model (HRM) is shown to be the most accurate, which, however, is found to be subject to considerable error if the RRS has a slowly descending end-of-exhale (EOE) phase. The defect of the HRM motivates us to construct a more accurate analytical model for the RRS. In this paper, we derive a new analytical RRS model from the probability density function of Rayleigh distribution. We evaluate the derived RRS model by using it to fit a real-life RRS in the sense of least squares, and the evaluation result shows that, our presented model exhibits lower error and fits the slowly descending EOE phases of the real-life RRS better than the HRM. PMID:26736208

  20. Information propagation from IP 3 to target protein: A combined model for encoding and decoding of Ca 2+ signal

    NASA Astrophysics Data System (ADS)

    Zhao, Qi; Yi, Ming; Xia, Kelin; Zhan, Meng

    2009-10-01

    It is well known that information is encoded in the frequency or amplitude of Ca 2+ signal and then decoded by target protein. However, few models considered both the encoding and decoding procedures of Ca 2+ signal. In this work, a minimal Li-Rinzel model is coupled with a phosphorylation-dephosphorylation cycle model, which is used to investigate information transmissions from inositol 1,4,5-trisphosphate (IP 3) to target proteins and their relations. We found that the mean target protein activity increases with the IP 3 concentration, and at a low level of stimulation, the target protein can be more efficiently activated by an oscillatory signal than a constant signal of the same average calcium if Ca 2+ acts cooperatively on the kinase. The internal noise resulting from the finite system size is also taken into account in the combined model.

  1. In vitro microemboli classification using neural network models and RF signals.

    PubMed

    Benoudjit, N; Ferroudji, K; Bahaz, M; Bouakaz, A

    2011-04-01

    Emboli classification is of high clinical importance for selecting appropriate treatment for patients. Several ultrasonic (US) methods using Doppler processing have been used for emboli detection and classification as solid or gaseous matter. We suggest in this experimental study exploiting the Radio-Frequency (RF) signal backscattered by the emboli since they contain additional information on the embolus than the Doppler signal. The aim of the study is the analysis of RF signals using Multilayer Perceptron (MLP) and Radial-Basis Function Network (RBFN) in order to classify emboli. Anthares scanner with RF access was used with a transmit frequency of 1.82MHz at two mechanical indices (MI) 0.2 and 0.6. The mechanical index is given as the peak negative pressure (in MPa) divided by the square root of the frequency (in MHz). A Doppler flow phantom was used containing a 0.8mm diameter vessel surrounded by a tissue mimicking material. To imitate gas emboli US behaviour, Sonovue microbubbles were injected at two different doses (10μl and 5μl) in a nonrecirculating at a constant flow. The surrounding tissue was assumed to behave as a solid emboli. In order to mimic real clinical pathological situations, Sonovue concentration was chosen such that the fundamental scattering from the tissue and from the contrast were identical. The amplitudes and bandwidths of the fundamental and the 2nd harmonic components were selected as input parameters to the MLP and RBFN models. Moreover the frequency bandwidths of the fundamental and the 2nd harmonic echoes were approximated by Gaussian functions and the coefficients were used as a third input parameter to the neural network models. The results show that the Gaussian coefficients provide the highest rate of classification in comparison to the amplitudes and the bandwidths of the fundamental and the 2nd harmonic components. The classification rates reached 89.28% and 92.85% with MLP and RBFN models respectively. This short

  2. Unmasking of a Protective TNFR1 Mediated Signal in the Collagen Arthritis Model

    PubMed Central

    Williams-Skipp, Cheryll; Raman, Thiagarajan; Valuck, Robert J.; Watkins, Herschel; Palmer, Brent E.; Scheinman, Robert I.

    2009-01-01

    OBJECTIVE: TNFR1 plays a major role in rheumatoid arthritis (RA). Here we explore the relative importance of TNFR1 signaling in the hematopoietic tissue compartment for disease progression. METHODS: DBA/1 mice were lethally irradiated and rescued with bone marrow derived from either DBA/1 or TNFR1−/− animals. The mice were then input into the collagen induced arthritis (CIA) model and disease progression characterized. RESULTS: Surprisingly, TNFR1−/− transplant mice input into the CIA model develop increased disease as compared to controls. This could not be attributed to either an increased primary response to collagen or to the contribution of a non-DBA genetic background. Histological markers of advanced disease were evident in TNFR1−/− transplant mice shortly after initiation of the immune response to collagen and long before clinical evidence of disease. Serum TNFα was undetectable while serum IL-12p40 levels were increased in TNFR1−/− transplant mice at the end point of the study. CONCLUSION: These data raise the intriguing possibility of the existence of an anti-inflammatory TNFR1 mediated circuit in the hematopoietic compartment. This circuit bears a resemblance to emerging data delineating a switch in TNFα function observed in the resolution of bacterial infections. These data suggest that TNFR1 mediated signals in the radio-resistant tissues contributes to disease progression while TNFR1 mediated signals in the radio-sensitive tissues can contribute to protection from disease. We thus put forward the hypothesis that the degree of responce to TNFα blockade in RA is dependent, in part, on the relative genetic strengths of these two pathways. PMID:19180511

  3. Theory of NMR Signal Dephasing in a Generalized Two-Compartment Model

    NASA Astrophysics Data System (ADS)

    Sukstanskii, Alexander; Yablonskiy, Dmitriy

    2001-03-01

    A new wave of interest into the theory of NMR signal dephasing in the presence of mesoscopic static field inhomogeneities has been generated by possible applications in MRI, mostly in fMRI. An exact solution of this problem has been found in a static dephasing regime for two geometrical models: randomly distributed spheres or infinitely long cylinders of a magnetic susceptibility \\chi i embedded in a given media with a susceptibility \\chi e [1,2]. In the present communication the theory is generalized by modeling the real objects (blood vessel, red blood cells, trabecular bone, etc) by ellipsoids of revolution (prolate and oblate spheroids). We found that the signal lineshape is not Gaussian. For prolate spheroids, the time domain FID signal, S, shows three characteristic time regimes: 1) t<= 4.5t_c, Ssymbol126exp [-\\varsigma b_1(t/t_c)^2]; 2) 4.5t_c> β t_c, Ssymbol126exp [-\\varsigma C(t/t_c)], where t_csymbol126[(\\chi _i-\\chi _e)B_0]-1, B0 is the external magnetic field, \\varsigma is the volume fraction of the objects; C is a universal constant, b_1,2 and β are functions of the spheroid axis ratio. 038

    038

    1. D.A.Yablonskiy, E.M.Haacke, Magnetic Resonance in Medicine, 32, 749 (1994) 038 2. D.A.Yablonskiy, ibid., 39, 417 (1998)

  4. Increased ghrelin signaling prolongs survival in mouse models of human aging through activation of sirtuin1

    PubMed Central

    Fujitsuka, N; Asakawa, A; Morinaga, A; Amitani, M S; Amitani, H; Katsuura, G; Sawada, Y; Sudo, Y; Uezono, Y; Mochiki, E; Sakata, I; Sakai, T; Hanazaki, K; Yada, T; Yakabi, K; Sakuma, E; Ueki, T; Niijima, A; Nakagawa, K; Okubo, N; Takeda, H; Asaka, M; Inui, A

    2016-01-01

    Caloric restriction (CR) is known to retard aging and delay functional decline as well as the onset of diseases in most organisms. Ghrelin is secreted from the stomach in response to CR and regulates energy metabolism. We hypothesized that in CR ghrelin has a role in protecting aging-related diseases. We examined the physiological mechanisms underlying the ghrelin system during the aging process in three mouse strains with different genetic and biochemical backgrounds as animal models of accelerated or normal human aging. The elevated plasma ghrelin concentration was observed in both klotho-deficient and senescence-accelerated mouse prone/8 (SAMP8) mice. Ghrelin treatment failed to stimulate appetite and prolong survival in klotho-deficient mice, suggesting the existence of ghrelin resistance in the process of aging. However, ghrelin antagonist hastened death and ghrelin signaling potentiators rikkunshito and atractylodin ameliorated several age-related diseases with decreased microglial activation in the brain and prolonged survival in klotho-deficient, SAMP8 and aged ICR mice. In vitro experiments, the elevated sirtuin1 (SIRT1) activity and protein expression through the cAMP–CREB pathway was observed after ghrelin and ghrelin potentiator treatment in ghrelin receptor 1a-expressing cells and human umbilical vein endothelial cells. Furthermore, rikkunshito increased hypothalamic SIRT1 activity and SIRT1 protein expression of the heart in the all three mouse models of aging. Pericarditis, myocardial calcification and atrophy of myocardial and muscle fiber were improved by treatment with rikkunshito. Ghrelin signaling may represent one of the mechanisms activated by CR, and potentiating ghrelin signaling may be useful to extend health and lifespan. PMID:26830139

  5. A two-dimensional model study of the QBO signal in SAGE II NO2 and O3

    NASA Technical Reports Server (NTRS)

    Chipperfield, M. P.; Gray, L. J.; Kinnersley, J. S.; Zawodny, J.

    1994-01-01

    Calculations of the quasi biennial oscillation (QBO) signal in Stratospheric Aerosol and Gas Experiment (SAGE) II O3 and NO2 data between 1984 and 1991 are presented and have been investigated by using a two-dimensional model. The isentropic 2D model is a fully interactive radiative-dynamical-chemical model in which the eddy fluxes of chemical species are calculated in a consistent manner. The QBO in the model has been forced by relaxing the equatorial zonal wind toward the observations at Singapore allowing the comparison of the model with observations from specific years. The model reproduces the observed vertical structure of the equatorial ozone anomaly with the well-known transition from dynamical to photochemical control at around 28km. The model also reproduces the observed vertical structure of the SAGE II observed NO2 anomaly. The model studies have shown that it is the QBO modulation of NO2 which the main cause of QBO signal in O3 above 30 km. The model also reproduces the observed latitudinal structure of the QBO signals in O3 and NO2. Due to the differing horizontal distribution of O3 and NO(y) the ozone signal shows a distinct phase change in the subtropics whereas the NO2 anomaly gives a broader signal.

  6. Chronic ethanol exposure inhibits distraction osteogenesis in a mouse model: Role of the TNF signaling axis

    SciTech Connect

    Wahl, Elizabeth C.; Aronson, James; Liu, Lichu; Liu, Zhendong; Perrien, Daniel S.; Skinner, Robert A.; Badger, Thomas M.; Ronis, Martin J.J.; Lumpkin, Charles K. . E-mail: lumpkincharlesk@uams.edu

    2007-05-01

    Tumor necrosis factor-alpha (TNF-{alpha}) is an inflammatory cytokine that modulates osteoblastogenesis. In addition, the demonstrated inhibitory effects of chronic ethanol exposure on direct bone formation in rats are hypothetically mediated by TNF-{alpha} signaling. The effects in mice are unreported. Therefore, we hypothesized that in mice (1) administration of a soluble TNF receptor 1 derivative (sTNF-R1) would protect direct bone formation during chronic ethanol exposure, and (2) administration of recombinant mouse TNF-{alpha} (rmTNF-{alpha}) to ethanol naive mice would inhibit direct bone formation. We utilized a unique model of limb lengthening (distraction osteogenesis, DO) combined with liquid diets to measure chronic ethanol's effects on direct bone formation. Chronic ethanol exposure resulted in increased marrow TNF, IL-1, and CYP 2E1 RNA levels in ethanol-treated vs. control mice, while no significant weight differences were noted. Systemic administration of sTNF-R1 during DO (8.0 mg/kg/2 days) to chronic ethanol-exposed mice resulted in enhanced direct bone formation as measured radiologically and histologically. Systemic rmTNF-{alpha} (10 {mu}g/kg/day) administration decreased direct bone formation measures, while no significant weight differences were noted. We conclude that chronic ethanol-associated inhibition of direct bone formation is mediated to a significant extent by the TNF signaling axis in a mouse model.

  7. Modelling colour constancy in fish: implications for vision and signalling in water.

    PubMed

    Wilkins, Lucas; Marshall, N Justin; Johnsen, Sönke; Osorio, D

    2016-06-15

    Colour vision and colour signals are important to aquatic animals, but light scattering and absorption by water distorts spectral stimuli. To investigate the performance of colour vision in water, and to suggest how photoreceptor spectral sensitivities and body colours might evolve for visual communication, we model the effects of changes in viewing distance and depth on the appearance of fish colours for three teleosts: a barracuda, Sphyraena helleri, which is dichromatic and two damselfishes, Chromis verater and Chromis hanui, which are trichromatic. We assume that photoreceptors light-adapt to the background, thereby implementing the von Kries transformation, which can largely account for observed colour constancy in humans and other animals, including fish. This transformation does not, however, compensate for light scattering over variable viewing distances, which in less than a metre seriously impairs dichromatic colour vision, and makes judgement of colour saturation unreliable for trichromats. The von Kries transformation does substantially offset colour shifts caused by changing depth, so that from depths of 0 to 30 m modelled colour changes (i.e. failures of colour constancy) are sometimes negligible. However, the magnitudes and directions of remaining changes are complex, depending upon the specific spectral sensitivities of the receptors and the reflectance spectra. This predicts that when judgement of colour is important, the spectra of signalling colours and photoreceptor spectral sensitivities should be evolutionarily linked, with the colours dependent on photoreceptor spectral sensitivities, and vice versa. PMID:27045090

  8. Cereal grass pulvini: agronomically significant models for studying gravitropism signaling and tissue polarity.

    PubMed

    Clore, Amy M

    2013-01-01

    Cereal grass pulvini have emerged as model systems that are not only valuable for the study of gravitropism, but are also of agricultural and economic significance. The pulvini are regions of tissue that are apical to each node and collectively return a reoriented stem to a more vertical position. They have proven to be useful for the study of gravisensing and response and are also providing clues about the establishment of polarity across tissues. This review will first highlight the agronomic significance of these stem regions and their benefits for use as model systems and provide a brief historical overview. A detailed discussion of the literature focusing on cell signaling and early changes in gene expression will follow, culminating in a temporal framework outlining events in the signaling and early growth phases of gravitropism in this tissue. Changes in cell wall composition and gene expression that occur well into the growth phase will be touched upon briefly. Finally, some ongoing research involving both maize and wheat pulvini will be introduced along with prospects for future investigations. PMID:23125431

  9. Modelling colour constancy in fish: implications for vision and signalling in water.

    PubMed

    Wilkins, Lucas; Marshall, N Justin; Johnsen, Sönke; Osorio, D

    2016-06-15

    Colour vision and colour signals are important to aquatic animals, but light scattering and absorption by water distorts spectral stimuli. To investigate the performance of colour vision in water, and to suggest how photoreceptor spectral sensitivities and body colours might evolve for visual communication, we model the effects of changes in viewing distance and depth on the appearance of fish colours for three teleosts: a barracuda, Sphyraena helleri, which is dichromatic and two damselfishes, Chromis verater and Chromis hanui, which are trichromatic. We assume that photoreceptors light-adapt to the background, thereby implementing the von Kries transformation, which can largely account for observed colour constancy in humans and other animals, including fish. This transformation does not, however, compensate for light scattering over variable viewing distances, which in less than a metre seriously impairs dichromatic colour vision, and makes judgement of colour saturation unreliable for trichromats. The von Kries transformation does substantially offset colour shifts caused by changing depth, so that from depths of 0 to 30 m modelled colour changes (i.e. failures of colour constancy) are sometimes negligible. However, the magnitudes and directions of remaining changes are complex, depending upon the specific spectral sensitivities of the receptors and the reflectance spectra. This predicts that when judgement of colour is important, the spectra of signalling colours and photoreceptor spectral sensitivities should be evolutionarily linked, with the colours dependent on photoreceptor spectral sensitivities, and vice versa.

  10. Ascidians as a vertebrate-like model organism for physiological studies of Rho GTPase signaling.

    PubMed

    Philips, Alexandre; Blein, Marion; Robert, Agnès; Chambon, Jean-Philippe; Baghdiguian, Stephen; Weill, Mylène; Fort, Philippe

    2003-07-01

    GTPases of the Rho family are evolutionarily conserved proteins that control cell shape dynamics during physiological processes as diverse as cell migration and polarity, axon outgrowth and guidance, apoptosis and phagocytosis. In mammals, 18 Rho proteins are distributed in 7 subfamilies. Rho, Rac and Cdc42 are the best-characterized ones, benefiting from the use of worm and drosophila, which only express these 3 subfamilies. An additional model would therefore help understand the physiological role of other mammalian subfamilies. We identified in genome databases the complete Rho family of two ascidians, Ciona intestinalis and Ciona savignyi, and showed that these families contain single ancestors of most mammalian Rho subfamilies. In Ciona intestinalis, all Rho genes are expressed and display specific developmental variations of mRNA expression during tadpole formation. Although C. intestinalis expresses five additional Rac compared to the closely related Ciona savignyi, only two appeared fully active in functional assays. Last, we identified in Ciona intestinalis database more than 50 Rho regulators (RhoGEFs and RhoGAPs) and 20 effector targets, whose analysis further supports the notion that Rho signaling components are of comparable complexity in mammals and ascidians. Since the tadpole of ascidians combines vertebrate-like developmental features with reduced cell number, particularly adapted to evolutionary and developmental biology studies, our data advocate this model for physiological studies of Rho signaling pathways.

  11. Spaced training rescues memory and ERK1/2 signaling in fragile X syndrome model mice.

    PubMed

    Seese, Ronald R; Wang, Kathleen; Yao, Yue Qin; Lynch, Gary; Gall, Christine M

    2014-11-25

    Recent studies have shown that short, spaced trains of afferent stimulation produce much greater long-term potentiation (LTP) than that obtained with a single, prolonged stimulation episode. The present studies demonstrate that spaced training regimens, based on these LTP timing rules, facilitate learning in wild-type (WT) mice and can offset learning and synaptic signaling impairments in the fragile X mental retardation 1 (Fmr1) knockout (KO) model of fragile X syndrome. We determined that 5 min of continuous training supports object location memory (OLM) in WT but not Fmr1 KO mice. However, the same amount of training distributed across three short trials, spaced by one hour, produced robust long-term memory in the KOs. At least three training trials were needed to realize the benefit of spacing, and intertrial intervals shorter or longer than 60 min were ineffective. Multiple short training trials also rescued novel object recognition in Fmr1 KOs. The spacing effect was surprisingly potent: just 1 min of OLM training, distributed across three trials, supported robust memory in both genotypes. Spacing also rescued training-induced activation of synaptic ERK1/2 in dorsal hippocampus of Fmr1 KO mice. These results show that a spaced training regimen designed to maximize synaptic potentiation facilitates recognition memory in WT mice and can offset synaptic signaling and memory impairments in a model of congenital intellectual disability.

  12. Differential Toll-Like Receptor-Signalling of Burkholderia pseudomallei Lipopolysaccharide in Murine and Human Models

    PubMed Central

    Weehuizen, Tassili A. F.; Prior, Joann L.; van der Vaart, Thomas W.; Ngugi, Sarah A.; Nepogodiev, Sergey A.; Field, Robert A.; Kager, Liesbeth M.; van ‘t Veer, Cornelis; de Vos, Alex F.; Wiersinga, W. Joost

    2015-01-01

    The Gram-negative bacterium Burkholderia pseudomallei causes melioidosis and is a CDC category B bioterrorism agent. Toll-like receptor (TLR)-2 impairs host defense during pulmonary B.pseudomallei infection while TLR4 only has limited impact. We investigated the role of TLRs in B.pseudomallei-lipopolysaccharide (LPS) induced inflammation. Purified B.pseudomallei-LPS activated only TLR2-transfected-HEK-cells during short stimulation but both HEK-TLR2 and HEK-TLR4-cells after 24 h. In human blood, an additive effect of TLR2 on TLR4-mediated signalling induced by B.pseudomallei-LPS was observed. In contrast, murine peritoneal macrophages recognized B.pseudomallei-LPS solely through TLR4. Intranasal inoculation of B.pseudomallei-LPS showed that both TLR4-knockout(-/-) and TLR2x4-/-, but not TLR2-/- mice, displayed diminished cytokine responses and neutrophil influx compared to wild-type controls. These data suggest that B.pseudomallei-LPS signalling occurs solely through murine TLR4, while in human models TLR2 plays an additional role, highlighting important differences between specificity of human and murine models that may have important consequences for B.pseudomallei-LPS sensing by TLRs and subsequent susceptibility to melioidosis. PMID:26689559

  13. Application of the normalized surface magnetic charge model to UXO discrimination in cases with overlapping signals

    NASA Astrophysics Data System (ADS)

    Shubitidze, F.; O'Neill, K.; Barrowes, B. E.; Shamatava, I.; Fernández, J. P.; Sun, K.; Paulsen, K. D.

    2007-03-01

    This paper presents an application of the normalized surface magnetic charge (NSMC) model to discriminate objects of interest, such as unexploded ordnance (UXO), from innocuous items in cases when UXO electromagnetic induction (EMI) responses are contaminated by signals from other objects. Over the entire EMI spectrum considered here (tens of Hertz up to several hundreds of kHz), the scattered magnetic field outside the object can be produced mathematically by equivalent magnetic charges. The amplitudes of these charges are determined from measurement data and normalized by the excitation field. The model takes into account the scatterer's heterogeneity and near- and far-field effects. For classification algorithms, the frequency spectrum of the total NSMC is proposed and investigated as a discriminant. The NSMC is combined with the differential evolution (DE) algorithm in a two-step inversion procedure. To illustrate the applicability of the DE-NSMC algorithm, blind test data are processed and analyzed for cases in which signals from nearby objects frequently overlap. The method was highly successful in distinguishing UXO from accompanying clutter.

  14. On Accuracy Order of Fourier Coefficients Computation for Periodic Signal Processing Models

    NASA Astrophysics Data System (ADS)

    Korytov, I. V.; Golosov, S. E.

    2016-08-01

    The article is devoted to construction piecewise constant functions for modelling periodic signal. The aim of the paper is to suggest a way to avoid discontinuity at points where waveform values are obtained. One solution is to introduce shifted step function whose middle points within its partial intervals coincide with points of observation. This means that large oscillations of Fourier partial sums move to new jump discontinuities where waveform values are not obtained. Furthermore, any step function chosen to model periodic continuous waveform determines a way to calculate Fourier coefficients. In this case, the technique is certainly a weighted rectangular quadrature rule. Here, the weight is either unit or trigonometric. Another effect of the solution consists in following. The shifted function leads to application midpoint quadrature rules for computing Fourier coefficients. As a result the formula for zero coefficient transforms into trapezoid rule. In the same time, the formulas for other coefficients remain of rectangular type.

  15. Validated Models for Radiation Response and Signal Generation in Scintillators: Final Report

    SciTech Connect

    Kerisit, Sebastien N.; Gao, Fei; Xie, YuLong; Campbell, Luke W.; Van Ginhoven, Renee M.; Wang, Zhiguo; Prange, Micah P.; Wu, Dangxin

    2014-12-01

    This Final Report presents work carried out at Pacific Northwest National Laboratory (PNNL) under the project entitled “Validated Models for Radiation Response and Signal Generation in Scintillators” (Project number: PL10-Scin-theor-PD2Jf) and led by Drs. Fei Gao and Sebastien N. Kerisit. This project was divided into four tasks: 1) Electronic response functions (ab initio data model) 2) Electron-hole yield, variance, and spatial distribution 3) Ab initio calculations of information carrier properties 4) Transport of electron-hole pairs and scintillation efficiency Detailed information on the results obtained in each of the four tasks is provided in this Final Report. Furthermore, published peer-reviewed articles based on the work carried under this project are included in Appendix. This work was supported by the National Nuclear Security Administration, Office of Nuclear Nonproliferation Research and Development (DNN R&D/NA-22), of the U.S. Department of Energy (DOE).

  16. Advanced models of targets and disturbances and related radar signal processors

    NASA Astrophysics Data System (ADS)

    Farina, A.; Russo, A.; Studer, F. A.

    The first part of the paper provides flexible and reliable stochastic models for the radar signals scattered by target and clutter sources. The models make it possible to consider any shape of autocorrelation function between consecutive pulse echoes and any probability density function for their in-phase and quadrature components. The second part of the paper revises the theory of detecting targets, with any type of probability density and autocorrelation function, embedded in a disturbance having any type of probability density and autocorrelation function. In the third part of the paper, the theory is applied to the cases in which target and/or disturbance may have a log-normal probability density for the amplitudes. Several processing schemes are suggested and corresponding detection performances evaluated. Finally, adaptive implementation schematics are suggested for some of the processors presented.

  17. ptk7 mutant zebrafish models of congenital and idiopathic scoliosis implicate dysregulated Wnt signalling in disease

    PubMed Central

    Hayes, Madeline; Gao, Xiaochong; Yu, Lisa X; Paria, Nandina; Henkelman, R. Mark; Wise, Carol A.; Ciruna, Brian

    2014-01-01

    Scoliosis is a complex genetic disorder of the musculoskeletal system, characterized by three-dimensional rotation of the spine. Curvatures caused by malformed vertebrae (congenital scoliosis (CS)) are apparent at birth. Spinal curvatures with no underlying vertebral abnormality (idiopathic scoliosis (IS)) most commonly manifest during adolescence. The genetic and biological mechanisms responsible for IS remain poorly understood due largely to limited experimental models. Here we describe zygotic ptk7 (Zptk7) mutant zebrafish, deficient in a critical regulator of Wnt signalling, as the first genetically defined developmental model of IS. We identify a novel sequence variant within a single IS patient that disrupts PTK7 function, consistent with a role for dysregulated Wnt activity in disease pathogenesis. Furthermore, we demonstrate that embryonic loss-of-gene function in maternal-zygotic ptk7 mutants (MZptk7) leads to vertebral anomalies associated with CS. Our data suggest novel molecular origins of, and genetic links between, congenital and idiopathic forms of disease. PMID:25182715

  18. Dynamic Performance Comparison of Two Kalman Filters for Rate Signal Direct Modeling and Differencing Modeling for Combining a MEMS Gyroscope Array to Improve Accuracy

    PubMed Central

    Yuan, Guangmin; Yuan, Weizheng; Xue, Liang; Xie, Jianbing; Chang, Honglong

    2015-01-01

    In this paper, the performance of two Kalman filter (KF) schemes based on the direct estimated model and differencing estimated model for input rate signal was thoroughly analyzed and compared for combining measurements of a sensor array to improve the accuracy of microelectromechanical system (MEMS) gyroscopes. The principles for noise reduction were presented and KF algorithms were designed to obtain the optimal rate signal estimates. The input rate signal in the direct estimated KF model was modeled with a random walk process and treated as the estimated system state. In the differencing estimated KF model, a differencing operation was established between outputs of the gyroscope array, and then the optimal estimation of input rate signal was achieved by compensating for the estimations of bias drifts for the component gyroscopes. Finally, dynamic simulations and experiments with a six-gyroscope array were implemented to compare the dynamic performance of the two KF models. The 1σ error of the gyroscopes was reduced from 1.4558°/s to 0.1203°/s by the direct estimated KF model in a constant rate test and to 0.5974°/s by the differencing estimated KF model. The estimated rate signal filtered by both models could reflect the amplitude variation of the input signal in the swing rate test and displayed a reduction factor of about three for the 1σ noise. Results illustrate that the performance of the direct estimated KF model is much higher than that of the differencing estimated KF model, with a constant input signal or lower dynamic variation. A similarity in the two KFs’ performance is observed if the input signal has a high dynamic variation. PMID:26528980

  19. Dynamic Performance Comparison of Two Kalman Filters for Rate Signal Direct Modeling and Differencing Modeling for Combining a MEMS Gyroscope Array to Improve Accuracy.

    PubMed

    Yuan, Guangmin; Yuan, Weizheng; Xue, Liang; Xie, Jianbing; Chang, Honglong

    2015-01-01

    In this paper, the performance of two Kalman filter (KF) schemes based on the direct estimated model and differencing estimated model for input rate signal was thoroughly analyzed and compared for combining measurements of a sensor array to improve the accuracy of microelectromechanical system (MEMS) gyroscopes. The principles for noise reduction were presented and KF algorithms were designed to obtain the optimal rate signal estimates. The input rate signal in the direct estimated KF model was modeled with a random walk process and treated as the estimated system state. In the differencing estimated KF model, a differencing operation was established between outputs of the gyroscope array, and then the optimal estimation of input rate signal was achieved by compensating for the estimations of bias drifts for the component gyroscopes. Finally, dynamic simulations and experiments with a six-gyroscope array were implemented to compare the dynamic performance of the two KF models. The 1σ error of the gyroscopes was reduced from 1.4558°/s to 0.1203°/s by the direct estimated KF model in a constant rate test and to 0.5974°/s by the differencing estimated KF model. The estimated rate signal filtered by both models could reflect the amplitude variation of the input signal in the swing rate test and displayed a reduction factor of about three for the 1σ noise. Results illustrate that the performance of the direct estimated KF model is much higher than that of the differencing estimated KF model, with a constant input signal or lower dynamic variation. A similarity in the two KFs' performance is observed if the input signal has a high dynamic variation. PMID:26528980

  20. Dynamic Performance Comparison of Two Kalman Filters for Rate Signal Direct Modeling and Differencing Modeling for Combining a MEMS Gyroscope Array to Improve Accuracy.

    PubMed

    Yuan, Guangmin; Yuan, Weizheng; Xue, Liang; Xie, Jianbing; Chang, Honglong

    2015-10-30

    In this paper, the performance of two Kalman filter (KF) schemes based on the direct estimated model and differencing estimated model for input rate signal was thoroughly analyzed and compared for combining measurements of a sensor array to improve the accuracy of microelectromechanical system (MEMS) gyroscopes. The principles for noise reduction were presented and KF algorithms were designed to obtain the optimal rate signal estimates. The input rate signal in the direct estimated KF model was modeled with a random walk process and treated as the estimated system state. In the differencing estimated KF model, a differencing operation was established between outputs of the gyroscope array, and then the optimal estimation of input rate signal was achieved by compensating for the estimations of bias drifts for the component gyroscopes. Finally, dynamic simulations and experiments with a six-gyroscope array were implemented to compare the dynamic performance of the two KF models. The 1σ error of the gyroscopes was reduced from 1.4558°/s to 0.1203°/s by the direct estimated KF model in a constant rate test and to 0.5974°/s by the differencing estimated KF model. The estimated rate signal filtered by both models could reflect the amplitude variation of the input signal in the swing rate test and displayed a reduction factor of about three for the 1σ noise. Results illustrate that the performance of the direct estimated KF model is much higher than that of the differencing estimated KF model, with a constant input signal or lower dynamic variation. A similarity in the two KFs' performance is observed if the input signal has a high dynamic variation.

  1. Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models Part I: Convective Signals

    SciTech Connect

    Lin, J; Kiladis, G N; Mapes, B E; Weickmann, K M; Sperber, K R; Lin, W; Wheeler, M; Schubert, S D; Genio, A D; Donner, L J; Emori, S; Gueremy, J; Hourdin, F; Rasch, P J; Roeckner, E; Scinocca, J F

    2005-05-06

    This study evaluates the tropical intraseasonal variability, especially the fidelity of Madden-Julian Oscillation (MJO) simulations, in 14 coupled general circulation models (GCMs) participating in the Inter-governmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Eight years of daily precipitation from each model's 20th century climate simulation are analyzed and compared with daily satellite retrieved precipitation. Space-time spectral analysis is used to obtain the variance and phase speed of dominant convectively coupled equatorial waves, including the MJO, Kelvin, equatorial Rossby (ER), mixed Rossby-gravity (MRG), and eastward inertio-gravity (EIG) and westward inertio-gravity (WIG) waves. The variance and propagation of the MJO, defined as the eastward wavenumbers 1-6, 30-70 day mode, are examined in detail. The results show that current state-of-the-art GCMs still have significant problems and display a wide range of skill in simulating the tropical intraseasonal variability. The total intraseasonal (2-128 day) variance of precipitation is too weak in most of the models. About half of the models have signals of convectively coupled equatorial waves, with Kelvin and MRG-EIG waves especially prominent. However, the variances are generally too weak for all wave modes except the EIG wave, and the phase speeds are generally too fast, being scaled to excessively deep equivalent depths. An interesting result is that this scaling is consistent within a given model across modes, in that both the symmetric and antisymmetric modes scale similarly to a certain equivalent depth. Excessively deep equivalent depths suggest that these models may not have a large enough reduction in their ''effective static stability'' due to diabatic heating. The MJO variance approaches the observed value in only two of the 14 models, but is less than half of the observed value in the other 12 models. The ratio between the eastward MJO variance and the variance of its

  2. Cryptosporidium parvum-induced ileo-caecal adenocarcinoma and Wnt signaling in a mouse model.

    PubMed

    Benamrouz, Sadia; Conseil, Valerie; Chabé, Magali; Praet, Marleen; Audebert, Christophe; Blervaque, Renaud; Guyot, Karine; Gazzola, Sophie; Mouray, Anthony; Chassat, Thierry; Delaire, Baptiste; Goetinck, Nathalie; Gantois, Nausicaa; Osman, Marwan; Slomianny, Christian; Dehennaut, Vanessa; Lefebvre, Tony; Viscogliosi, Eric; Cuvelier, Claude; Dei-Cas, Eduardo; Creusy, Colette; Certad, Gabriela

    2014-06-01

    Cryptosporidium species are apicomplexan protozoans that are found worldwide. These parasites constitute a large risk to human and animal health. They cause self-limited diarrhea in immunocompetent hosts and a life-threatening disease in immunocompromised hosts. Interestingly, Cryptosporidium parvum has been related to digestive carcinogenesis in humans. Consistent with a potential tumorigenic role of this parasite, in an original reproducible animal model of chronic cryptosporidiosis based on dexamethasone-treated or untreated adult SCID mice, we formerly reported that C. parvum (strains of animal and human origin) is able to induce digestive adenocarcinoma even in infections induced with very low inoculum. The aim of this study was to further characterize this animal model and to explore metabolic pathways potentially involved in the development of C. parvum-induced ileo-caecal oncogenesis. We searched for alterations in genes or proteins commonly involved in cell cycle, differentiation or cell migration, such as β-catenin, Apc, E-cadherin, Kras and p53. After infection of animals with C. parvum we demonstrated immunohistochemical abnormal localization of Wnt signaling pathway components and p53. Mutations in the selected loci of studied genes were not found after high-throughput sequencing. Furthermore, alterations in the ultrastructure of adherens junctions of the ileo-caecal neoplastic epithelia of C. parvum-infected mice were recorded using transmission electron microscopy. In conclusion, we found for the first time that the Wnt signaling pathway, and particularly the cytoskeleton network, seems to be pivotal for the development of the C. parvum-induced neoplastic process and cell migration of transformed cells. Furthermore, this model is a valuable tool in understanding the host-pathogen interactions associated with the intricate infection process of this parasite, which is able to modulate host cytoskeleton activities and several host-cell biological

  3. Neutrino and gravitational wave signal of a delayed-detonation model of type Ia supernovae

    NASA Astrophysics Data System (ADS)

    Seitenzahl, Ivo R.; Herzog, Matthias; Ruiter, Ashley J.; Marquardt, Kai; Ohlmann, Sebastian T.; Röpke, Friedrich K.

    2015-12-01

    The progenitor system(s) and the explosion mechanism(s) of type Ia supernovae (SNe Ia) are still under debate. Nonelectromagnetic observables, in particular, gravitational waves and neutrino emission, of thermoclear supernovae are a complementary window to light curves and spectra for studying these enigmatic objects. A leading model for SNe Ia is the thermonuclear incineration of a near-Chandrasekhar mass carbon-oxygen white dwarf star in a "delayed detonation." We calculate a three-dimensional hydrodynamic explosion for the N100 delayed-detonation model extensively discussed in the literature, taking the dynamical effects of neutrino emission from all important contributing source terms into account. Although neutrinos carry away 2 ×1049 erg of energy, we confirm the common view that neutrino energy losses are dynamically not very important, resulting in only a modest reduction of final kinetic energy by 2%. We then calculate the gravitational wave signal from the time evolution of the quadrupole moment. Our model radiates 7 ×1039 erg in gravitational waves and the spectrum has a pronounced peak around 0.4 Hz. Depending on viewing angle and polarization, we find that the future space-based gravitational wave missions DECIGO and BBO would be able to detect our source to a distance of ˜1.3 Mpc . We predict a clear signature of the deflagration-to-detonation transition in the neutrino and the gravitational wave signals. If observed, such a feature would be a strong indicator of the realization of delayed detonations in near-Chandrasekhar mass white dwarfs.

  4. Statistical Modeling of Large-Scale Signal Path Loss in Underwater Acoustic Networks

    PubMed Central

    Llor, Jesús; Malumbres, Manuel Perez

    2013-01-01

    In an underwater acoustic channel, the propagation conditions are known to vary in time, causing the deviation of the received signal strength from the nominal value predicted by a deterministic propagation model. To facilitate a large-scale system design in such conditions (e.g., power allocation), we have developed a statistical propagation model in which the transmission loss is treated as a random variable. By applying repetitive computation to the acoustic field, using ray tracing for a set of varying environmental conditions (surface height, wave activity, small node displacements around nominal locations, etc.), an ensemble of transmission losses is compiled and later used to infer the statistical model parameters. A reasonable agreement is found with log-normal distribution, whose mean obeys a log-distance increases, and whose variance appears to be constant for a certain range of inter-node distances in a given deployment location. The statistical model is deemed useful for higher-level system planning, where simulation is needed to assess the performance of candidate network protocols under various resource allocation policies, i.e., to determine the transmit power and bandwidth allocation necessary to achieve a desired level of performance (connectivity, throughput, reliability, etc.). PMID:23396190

  5. Modeling the Actions of β-Adrenergic Signaling on Excitation–Contraction Coupling Processes

    PubMed Central

    GREENSTEIN, JOSEPH L.; TANSKANEN, ANTTI J.; WINSLOW, RAIMOND L.

    2005-01-01

    Activation of the β-adrenergic (β-AR) signaling pathway enhances cardiac function through protein kinase A (PKA)–mediated phosphorylation of target proteins involved in the process of excitation–contraction (EC) coupling. Experimental studies of the effects of β-AR stimulation on EC coupling have yielded complex results, including increased, decreased, or unchanged EC coupling gain. In this study, we extend a previously developed model of the canine ventricular myocyte describing local control of sarcoplasmic reticulum (SR) calcium (Ca2+) release to include the effects of β-AR stimulation. Incorporation of phosphorylation-dependent effects on model membrane currents and Ca2+-cycling proteins yields changes of action potential (AP) and Ca2+ transients in agreement with those measured experimentally in response to the nonspecific β-AR agonist isoproterenol (ISO). The model reproduces experimentally observed alterations in EC coupling gain in response to β-AR agonists and predicts the specific roles of L-type Ca2+ channel (LCC) and SR Ca2+ release channel phosphorylation in altering the amplitude and shape of the EC coupling gain function. The model also indicates that factors that promote mode 2 gating of LCCs, such as β-AR stimulation or activation of the Ca2+/calmodulin-dependent protein kinase II (CaMKII), may increase the probability of occurrence of early after-depolarizations (EADs), due to the random, long-duration opening of LCC gating in mode 2. PMID:15201146

  6. Small signal modeling of high electron mobility transistors on silicon and silicon carbide substrate with consideration of substrate loss mechanism

    NASA Astrophysics Data System (ADS)

    Sahoo, A. K.; Subramani, N. K.; Nallatamby, J. C.; Sylvain, L.; Loyez, C.; Quere, R.; Medjdoub, F.

    2016-01-01

    In this paper, we present a comparative study on small-signal modeling of AlN/GaN/AlGaN double hetero-structure high electron mobility transistors (HEMTs) grown on silicon (Si) and silicon carbide (SiC) substrate. The traditional small signal equivalent circuit model is modified to take into account the transmission loss mechanism of coplanar waveguide (CPW) line which cannot be neglected at high frequencies. CPWs and HEMTs-on-AlN/GaN/AlGaN epitaxial layers are fabricated on both the Si and SiC substrates. S-parameter measurements at room temperature are performed over the frequency range from 0.5 GHz to 40 GHz. Transmission loss of CPW lines are modeled with a distributed transmission line (TL) network and an equivalent circuit model is included in the small-signal transistor model topology. Measurements and simulations are compared and found to be in good agreement.

  7. A VLSI field-programmable mixed-signal array to perform neural signal processing and neural modeling in a prosthetic system.

    PubMed

    Bamford, Simeon A; Hogri, Roni; Giovannucci, Andrea; Taub, Aryeh H; Herreros, Ivan; Verschure, Paul F M J; Mintz, Matti; Del Giudice, Paolo

    2012-07-01

    A very-large-scale integration field-programmable mixed-signal array specialized for neural signal processing and neural modeling has been designed. This has been fabricated as a core on a chip prototype intended for use in an implantable closed-loop prosthetic system aimed at rehabilitation of the learning of a discrete motor response. The chosen experimental context is cerebellar classical conditioning of the eye-blink response. The programmable system is based on the intimate mixing of switched capacitor analog techniques with low speed digital computation; power saving innovations within this framework are presented. The utility of the system is demonstrated by the implementation of a motor classical conditioning model applied to eye-blink conditioning in real time with associated neural signal processing. Paired conditioned and unconditioned stimuli were repeatedly presented to an anesthetized rat and recordings were taken simultaneously from two precerebellar nuclei. These paired stimuli were detected in real time from this multichannel data. This resulted in the acquisition of a trigger for a well-timed conditioned eye-blink response, and repetition of unpaired trials constructed from the same data led to the extinction of the conditioned response trigger, compatible with natural cerebellar learning in awake animals.

  8. Reference analysis of the signal + background model in counting experiments II. Approximate reference prior

    NASA Astrophysics Data System (ADS)

    Casadei, D.

    2014-10-01

    The objective Bayesian treatment of a model representing two independent Poisson processes, labelled as ``signal'' and ``background'' and both contributing additively to the total number of counted events, is considered. It is shown that the reference prior for the parameter of interest (the signal intensity) can be well approximated by the widely (ab)used flat prior only when the expected background is very high. On the other hand, a very simple approximation (the limiting form of the reference prior for perfect prior background knowledge) can be safely used over a large portion of the background parameters space. The resulting approximate reference posterior is a Gamma density whose parameters are related to the observed counts. This limiting form is simpler than the result obtained with a flat prior, with the additional advantage of representing a much closer approximation to the reference posterior in all cases. Hence such limiting prior should be considered a better default or conventional prior than the uniform prior. On the computing side, it is shown that a 2-parameter fitting function is able to reproduce extremely well the reference prior for any background prior. Thus, it can be useful in applications requiring the evaluation of the reference prior for a very large number of times.

  9. Modelling TFE renal cell carcinoma in mice reveals a critical role of WNT signaling

    PubMed Central

    Calcagnì, Alessia; kors, Lotte; Verschuren, Eric; De Cegli, Rossella; Zampelli, Nicolina; Nusco, Edoardo; Confalonieri, Stefano; Bertalot, Giovanni; Pece, Salvatore; Settembre, Carmine; Malouf, Gabriel G; Leemans, Jaklien C; de Heer, Emile; Salvatore, Marco; Peters, Dorien JM; Di Fiore, Pier Paolo; Ballabio, Andrea

    2016-01-01

    TFE-fusion renal cell carcinomas (TFE-fusion RCCs) are caused by chromosomal translocations that lead to overexpression of the TFEB and TFE3 genes (Kauffman et al., 2014). The mechanisms leading to kidney tumor development remain uncharacterized and effective therapies are yet to be identified. Hence, the need to model these diseases in an experimental animal system (Kauffman et al., 2014). Here, we show that kidney-specific TFEB overexpression in transgenic mice, resulted in renal clear cells, multi-layered basement membranes, severe cystic pathology, and ultimately papillary carcinomas with hepatic metastases. These features closely recapitulate those observed in both TFEB- and TFE3-mediated human kidney tumors. Analysis of kidney samples revealed transcriptional induction and enhanced signaling of the WNT β-catenin pathway. WNT signaling inhibitors normalized the proliferation rate of primary kidney cells and significantly rescued the disease phenotype in vivo. These data shed new light on the mechanisms underlying TFE-fusion RCCs and suggest a possible therapeutic strategy based on the inhibition of the WNT pathway. DOI: http://dx.doi.org/10.7554/eLife.17047.001

  10. Modeling the self-organized phosphatidylinositol lipid signaling system in chemotactic cells using quantitative image analysis.

    PubMed

    Shibata, Tatsuo; Nishikawa, Masatoshi; Matsuoka, Satomi; Ueda, Masahiro

    2012-11-01

    A key signaling event that is responsible for gradient sensing in eukaryotic cell chemotaxis is a phosphatidylinositol (PtdIns) lipid reaction system. The self-organization activity of this PtdIns lipid system induces an inherent polarity, even in the absence of an external chemoattractant gradient, by producing a localized PtdIns (3,4,5)-trisphosphate [PtdIns(3,4,5)P(3)]-enriched domain on the membrane. Experimentally, we found that such a domain could exhibit two types of behavior: (1) it could be persistent and travel on the membrane, or (2) be stochastic and transient. Taking advantage of the simultaneous visualization of PtdIns(3,4,5)P(3) and the enzyme phosphatase and tensin homolog (PTEN), for which PtdIns(3,4,5)P(3) is a substrate, we statistically demonstrated the inter-dependence of their spatiotemporal dynamics. On the basis of this statistical analysis, we developed a theoretical model for the self-organization of PtdIns lipid signaling that can accurately reproduce both persistent and transient domain formation; these types of formations can be explained by the oscillatory and excitability properties of the system, respectively. PMID:22899720

  11. Modelling TFE renal cell carcinoma in mice reveals a critical role of WNT signaling

    PubMed Central

    Calcagnì, Alessia; kors, Lotte; Verschuren, Eric; De Cegli, Rossella; Zampelli, Nicolina; Nusco, Edoardo; Confalonieri, Stefano; Bertalot, Giovanni; Pece, Salvatore; Settembre, Carmine; Malouf, Gabriel G; Leemans, Jaklien C; de Heer, Emile; Salvatore, Marco; Peters, Dorien JM; Di Fiore, Pier Paolo; Ballabio, Andrea

    2016-01-01

    TFE-fusion renal cell carcinomas (TFE-fusion RCCs) are caused by chromosomal translocations that lead to overexpression of the TFEB and TFE3 genes (Kauffman et al., 2014). The mechanisms leading to kidney tumor development remain uncharacterized and effective therapies are yet to be identified. Hence, the need to model these diseases in an experimental animal system (Kauffman et al., 2014). Here, we show that kidney-specific TFEB overexpression in transgenic mice, resulted in renal clear cells, multi-layered basement membranes, severe cystic pathology, and ultimately papillary carcinomas with hepatic metastases. These features closely recapitulate those observed in both TFEB- and TFE3-mediated human kidney tumors. Analysis of kidney samples revealed transcriptional induction and enhanced signaling of the WNT β-catenin pathway. WNT signaling inhibitors normalized the proliferation rate of primary kidney cells and significantly rescued the disease phenotype in vivo. These data shed new light on the mechanisms underlying TFE-fusion RCCs and suggest a possible therapeutic strategy based on the inhibition of the WNT pathway. DOI: http://dx.doi.org/10.7554/eLife.17047.001 PMID:27668431

  12. Proteomes of the barley aleurone layer: A model system for plant signalling and protein secretion.

    PubMed

    Finnie, Christine; Andersen, Birgit; Shahpiri, Azar; Svensson, Birte

    2011-05-01

    The cereal aleurone layer is of major importance due to its nutritional properties as well as its central role in seed germination and industrial malting. Cereal seed germination involves mobilisation of storage reserves in the starchy endosperm to support seedling growth. In response to gibberellic acid produced by the embryo, the aleurone layer synthesises hydrolases that are secreted to the endosperm for the degradation of storage products. The barley aleurone layer can be separated from the other seed tissues and maintained in culture, allowing the study of the effect of added signalling molecules in an isolated system. These properties have led to its use as a model system for the study of plant signalling and germination. More recently, proteome analysis of the aleurone layer has provided new insight into this unique tissue including identification of plasma membrane proteins and targeted analysis of germination-related changes and the thioredoxin system. Here, analysis of intracellular and secreted proteomes reveals features of the aleurone layer system that makes it promising for investigations of plant protein secretion mechanisms.

  13. Computer modeling of mild axonal injury: implications for axonal signal transmission.

    PubMed

    Volman, Vladislav; Ng, Laurel J

    2013-10-01

    Diffusion imaging and postmortem studies of patients with mild traumatic brain injury (mTBI) of the concussive type are consistent with the observations of diffuse axonal injury to the white matter axons. Mechanical trauma to axons affects the properties of tetrodotoxin-sensitive sodium channels at the nodes of Ranvier, leading to axonal degeneration through intra-axonal accumulation of calcium ions and activation of calcium proteases; however, the immediate implications of axonal trauma regarding axonal functionality and their relevance to transient impairment of function as observed in concussion remain elusive. A biophysically realistic computational model of a myelinated axon was developed to investigate how mTBI could immediately affect axonal function. Traumatized axons showed alterations in signal propagation properties that nonlinearly depended on the level of trauma; subthreshold traumatized axons had decreased spike propagation time, whereas suprathreshold traumatized axons exhibited a slowdown of spike propagation and spike propagation failure. Trauma had consistently reduced axonal spike amplitude. The susceptibility of an axon to trauma could be modulated by the function of an ATP-dependent sodium-potassium pump. The results suggest a mechanism by which concussive mTBI could lead to the immediate impairment of signal propagation through the axon and the emerging dysfunctional neuronal information exchange.

  14. On temporal connectivity of PFC via Gauss-Markov modeling of fNIRS signals.

    PubMed

    Aydöre, Sergül; Mihçak, M Kivanç; Ciftçi, Koray; Akin, Ata

    2010-03-01

    Functional near-infrared spectroscopy (fNIRS) is an optical imaging method, which monitors the brain activation by measuring the successive changes in the concentration of oxy- and deoxyhemoglobin in real time. In this study, we present a method to investigate the functional connectivity of prefrontal cortex (PFC) Sby applying a Gauss-Markov model to fNIRS signals. The hemodynamic changes on PFC during the performance of cognitive paradigm are measured by fNIRS for 17 healthy adults. The color-word matching Stroop task is performed to activate 16 different regions of PFC. There are three different types of stimuli in this task, which can be listed as incongruent stimulus (IS), congruent stimulus (CS), and neutral stimulus (NS), respectively. We introduce a new measure, called "information transfer metric" (ITM) for each time sample. The behavior of ITMs during IS are significantly different from the ITMs during CS and NS, which is consistent with the outcome of the previous research, which concentrated on fNIRS signal analysis via color-word matching Stroop task. Our analysis shows that the functional connectivity of PFC is highly relevant with the cognitive load, i.e., functional connectivity increases with the increasing cognitive load.

  15. Three-dimensional Mammary Epithelial Cell Morphogenesis Model for Analysis of TGFß Signaling.

    PubMed

    Rashidian, Juliet; Luo, Kunxin

    2016-01-01

    Culturing mammary epithelial cells in laminin-rich extracellular matrices (three dimensional or 3D culture) offers significant advantages over that in the conventional two-dimensional (2D) tissue culture system in that it takes into considetation the impact of extracellular matrix (ECM) microenvironment on the proliferation, survival, and differentiation of mammary epithelial cells. When grown in the 3D culture, untransformed mammary epithelial cells undergo morphogenesis to form a multicellular and polarized acini-like structure that functionally mimics the differentiated alveoli in the pregnancy mammary gland. This process is subjected to regulation by many growth factors and cytokines. The transforming growth factor-ß (TGFß) is a multipotent cytokine that regulates multiple aspects of development and tumorigenesis. In addition to its effects on epithelial cell proliferation, survival, and differentiation, it is also a potent regulator of the cell-matrix interaction. Thus, the 3D culture model may recapitulate the complex in vivo epithelial cell microenvironment and allow us to fully evaluate the role of TGFß signaling in multiple aspects of normal and cancerous cell behavior. In this chapter we provide detailed protocols for growing mammary epithelial cells in the 3D Matrigel for analysis of signaling pathways.

  16. C-kit signaling promotes proliferation and invasion of colorectal mucinous adenocarcinoma in a murine model

    PubMed Central

    Tan, Jun; Yang, Shu; Shen, Ping; Sun, Haimei; Xiao, Jie; Wang, Yaxi; Wu, Bo; Ji, Fengqing; Yan, Jihong; Xue, Hong; Zhou, Deshan

    2015-01-01

    It was reported that the receptor tyrosine kinase (RTK) family often highly expressed in several mucinous carcinomas. In the present study, we established a murine model of colorectal mucinous adenocardinoma (CRMAC) by treating C57 mice [both wild type (WT) and loss-of-function c-kit mutant type (Wads−/−)] with AOM+DSS for 37 weeks and found that c-kit, a member of RTK family, clearly enhanced the tumor cell proliferation by decreasing p53 and increasing cyclin D1 through AKT pathway. Significantly, c-kit strongly promoted tumor cell invasiveness by increasing ETV4, which induced MMP7 expression and epithelial-mesenchymal transition (EMT) via ERK pathway. In vitro up- or down-regulating c-kit activation in human colorectal cancer HCT-116 cells further consolidated these results. In conclusion, our data suggested that the c-kit signaling obviously promoted proliferation and invasion of CRMAC. Therefore, targeting the c-kit signaling and its downstream molecules might provide the potential strategies for treatment of patients suffering from CRMAC in the future. PMID:26356816

  17. Harnessing system models of cell death signalling for cytotoxic chemotherapy: towards personalised medicine approaches?

    PubMed

    Huber, Heinrich J; McKiernan, Ross G; Prehn, Jochen H M

    2014-03-01

    Most cytotoxic chemotherapeutics are believed to kill cancer cells by inducing apoptosis. Understanding the factors that contribute to impairment of apoptosis in cancer cells is therefore critical for the development of novel therapies that circumvent the widespread chemoresistance. Apoptosis, however, is a complex and tightly controlled process that can be induced by different classes of chemotherapeutics targeting different signalling nodes and pathways. Moreover, apoptosis initiation and apoptosis execution strongly depend on patient-specific, genomic and proteomic signatures. Here, we will review recent translational studies that suggest a critical link between the sensitivity of cancer cells to initiate apoptosis and clinical outcome. Next we will discuss recent advances in the field of system modelling of apoptosis pathways for the prediction of treatment responses. We propose that initiation of mitochondrial apoptosis, defined as the process of mitochondrial outer membrane permeabilisation (MOMP), is a dose-dependent decision process that allows for a prediction of individual therapy responses and therapeutic windows. We provide evidence in contrast that apoptosis execution post-MOMP may be a binary decision that dictates whether apoptosis is executed or not. We will discuss the implications of this concept for the future use of novel adjuvant therapeutics that specifically target apoptosis signalling pathways or which may be used to reduce the impact of cell-to-cell heterogeneity on therapy responses. Finally, we will discuss the technical and regulatory requirements surrounding the use and implications of system-based patient stratification tools for the future of personalised oncology. PMID:24477766

  18. Modeling fMRI signals can provide insights into neural processing in the cerebral cortex

    PubMed Central

    Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

    2015-01-01

    Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. PMID:25972586

  19. A spectral model for signal elements isolated from zebrafish photopic electroretinogram

    PubMed Central

    Nelson, Ralph; Singla, Nirmish

    2009-01-01

    The zebrafish photopic ERG sums isolatable elements. In each element red, blue, green and UV (r, g, b, u) cone signals combine in a way that reflects retinal organization. ERG responses to monochromatic stimuli of different wavelengths and irradiances were recorded on a white, rod suppressing background using superfused eyecups. Onset elements were isolated with glutamatergic blockers and response subtractions. CNQX blocked ionotropic (AMPA/kainate) glutamate receptors; L-AP4 or CPPG blocked metabotropic (mGluR6) glutamate receptors; TBOA blocked glutamate transporters; and L-Aspartate inactivated all glutamatergic mechanisms. Seven elements emerged: photopic PIII, the L-Aspartate-isolated cone response; b1, a CNQX-sensitive early b-wave element of inner retinal origin; PII, a photopic, CNQX-insensitive, composite b-wave element from ON bipolar cells; PIIm, an L-AP4/CPPG-sensitive, CNQX-insensitive metabotropic sub-element of PII; PIInm, an L-AP4/CPPG/CNQX-insensitive, non-metabotropic sub-element of PII; a1nm, a TBOA-sensitive, CNQX/L-AP4/CPPG-insensitive, non-metabotropic, post-photoreceptor a-wave element; and a2, a CNQX-sensitive a-wave element linked to OFF bipolar cells. The first five elements were fit with a spectral model that demonstrates independence of cone color pathways. From this Vmax and half-saturation values (k) for the contributing r- g- b- and u-cone signals were calculated. Two signal patterns emerged. For PIII or PIInm the Vmax order was Vr > Vg ≫ Vb ≈ Vu. For b1, PII, and PIIm the Vmax order was Vr ≈ Vb > Vg > Vu. In either pattern u-cone amplitude (Vu) was smallest, but u-cone sensitivity (ku362) was greatest, some 10-30 times greater than r-cone (kr570). The spectra of b1/PII/PIIm elements peaked near b-cone and u-cone absorbance maxima regardless of criteria, but the spectra of PIII/PIInm elements shifted from b- towards r-cone absorbance maxima as criterion levels increased. The greatest gains in Vmax relative to PIII occurred for

  20. Investigation of model based beamforming and Bayesian inversion signal processing methods for seismic localization of underground sources.

    PubMed

    Oh, Geok Lian; Brunskog, Jonas

    2014-08-01

    Techniques have been studied for the localization of an underground source with seismic interrogation signals. Much of the work has involved defining either a P-wave acoustic model or a dispersive surface wave model to the received signal and applying the time-delay processing technique and frequency-wavenumber processing to determine the location of the underground tunnel. Considering the case of determining the location of an underground tunnel, this paper proposed two physical models, the acoustic approximation ray tracing model and the finite difference time domain three-dimensional (3D) elastic wave model to represent the received seismic signal. Two localization algorithms, beamforming and Bayesian inversion, are developed for each physical model. The beam-forming algorithms implemented are the modified time-and-delay beamformer and the F-K beamformer. Inversion is posed as an optimization problem to estimate the unknown position variable using the described physical forward models. The proposed four methodologies are demonstrated and compared using seismic signals recorded by geophones set up on ground surface generated by a surface seismic excitation. The examples show that for field data, inversion for localization is most advantageous when the forward model completely describe all the elastic wave components as is the case of the FDTD 3D elastic model.

  1. Symmetry breaking in a bulk-surface reaction-diffusion model for signalling networks

    NASA Astrophysics Data System (ADS)

    Rätz, Andreas; Röger, Matthias

    2014-08-01

    Signalling molecules play an important role for many cellular functions. We investigate here a general system of two membrane reaction-diffusion equations coupled to a diffusion equation inside the cell by a Robin-type boundary condition and a flux term in the membrane equations. A specific model of this form was recently proposed by the authors for the GTPase cycle in cells. We investigate here a putative role of diffusive instabilities in cell polarization. By a linearized stability analysis, we identify two different mechanisms. The first resembles a classical Turing instability for the membrane subsystem and requires (unrealistically) large differences in the lateral diffusion of activator and substrate. On the other hand, the second possibility is induced by the difference in cytosolic and lateral diffusion and appears much more realistic. We complement our theoretical analysis by numerical simulations that confirm the new stability mechanism and allow us to investigate the evolution beyond the regime where the linearization applies.

  2. Signals induced by charge-trapping in EDELWEISS FID detectors: analytical modeling and applications

    NASA Astrophysics Data System (ADS)

    Arnaud, Q.; Armengaud, E.; Augier, C.; Benoît, A.; Bergé, L.; Billard, J.; Blümer, J.; de Boissière, T.; Broniatowski, A.; Camus, P.; Cazes, A.; Chapellier, M.; Charlieux, F.; Dumoulin, L.; Eitel, K.; Foerster, N.; Fourches, N.; Gascon, J.; Giuliani, A.; Gros, M.; Hehn, L.; Heuermann, G.; De Jésus, M.; Jin, Y.; Juillard, A.; Kleifges, M.; Kozlov, V.; Kraus, H.; Kéfélian, C.; Kudryavtsev, V. A.; Le-Sueur, H.; Marnieros, S.; Navick, X.-F.; Nones, C.; Olivieri, E.; Pari, P.; Paul, B.; Piro, M.-C.; Poda, D.; Queguiner, E.; Rozov, S.; Sanglard, V.; Schmidt, B.; Scorza, S.; Siebenborn, B.; Tcherniakhovski, D.; Vagneron, L.; Weber, M.; Yakushev, E.

    2016-10-01

    The EDELWEISS-III direct dark matter search experiment uses cryogenic HP-Ge detectors Fully covered with Inter-Digitized electrodes (FID). They are operated at low fields (< 1 V/cm), and as a consequence charge-carrier trapping significantly affects both the ionization and heat energy measurements. This paper describes an analytical model of the signals induced by trapped charges in FID detectors based on the Shockley-Ramo theorem. It is used to demonstrate that veto electrodes, initially designed for the sole purpose of surface event rejection, can be used to provide a sensitivity to the depth of the energy deposits, characterize the trapping in the crystals, perform heat and ionization energy corrections and improve the ionization baseline resolutions. These procedures are applied successfully to actual data.

  3. Sparsity: a ubiquitous but unexplored property of geophysical signals for multi-scale modeling and reconstruction

    NASA Astrophysics Data System (ADS)

    Fouofula-Georgiou, E.; Ebtehaj, A. M.

    2012-04-01

    Sparsity: a ubiquitous but unexplored property of geophysical signals for multi-scale modeling and reconstruction Efi Foufoula-Georgiou and Ardeshir Mohammad Ebtehaj Department of Civil Engineering and National Center for Earth-surface Dynamics University of Minnesota, Minneapolis, MN 55414 Many geophysical processes exhibit variability over a wide range of scales. Yet, in numerical modeling or remote sensing observations not all of this variability is explicitly resolved due to limitations in computational resources or sensor configurations. As a result, sub-grid scale parameterizations and downscaling/upscaling representations are essential. Such representations take advantage of scale invariance which has been theoretically or empirically documented in a wide range of geophysical processes, including precipitation, soil moisture, and topography. Here we present a new direction in the field of multi-scale analysis and reconstruction. It capitalizes on the fact that most geophysical signals are naturally redundant, due to spatial dependence and coherence over a range of scales, and thus when projected onto an appropriate space (e.g, Fourier or wavelet) only a few representation coefficients are non-zero -- this property is called sparsity. The sparsity can serve as a priori knowledge to properly regularize the otherwise ill-posed inverse problem of creating information at scales smaller than resolved, which is at the heart of sub-grid scale and downscaling parameterizations. The same property of sparsity is also shown to play a revolutionary role in revisiting the problem of optimal estimation of non-Gaussian processes. Theoretical concepts are borrowed from the new field of compressive sampling and super-resolution and the merits of the methodology are demonstrated using examples from precipitation downscaling, multi-scale data fusion and data assimilation.

  4. Prototyping scalable digital signal processing systems for radio astronomy using dataflow models

    NASA Astrophysics Data System (ADS)

    Sane, N.; Ford, J.; Harris, A. I.; Bhattacharyya, S. S.

    2012-05-01

    There is a growing trend toward using high-level tools for design and implementation of radio astronomy digital signal processing (DSP) systems. Such tools, for example, those from the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER), are usually platform-specific, and lack high-level, platform-independent, portable, scalable application specifications. This limits the designer's ability to experiment with designs at a high-level of abstraction and early in the development cycle. We address some of these issues using a model-based design approach employing dataflow models. We demonstrate this approach by applying it to the design of a tunable digital downconverter (TDD) used for narrow-bandwidth spectroscopy. Our design is targeted toward an FPGA platform, called the Interconnect Break-out Board (IBOB), that is available from the CASPER. We use the term TDD to refer to a digital downconverter for which the decimation factor and center frequency can be reconfigured without the need for regenerating the hardware code. Such a design is currently not available in the CASPER DSP library. The work presented in this paper focuses on two aspects. First, we introduce and demonstrate a dataflow-based design approach using the dataflow interchange format (DIF) tool for high-level application specification, and we integrate this approach with the CASPER tool flow. Secondly, we explore the trade-off between the flexibility of TDD designs and the low hardware cost of fixed-configuration digital downconverter (FDD) designs that use the available CASPER DSP library. We further explore this trade-off in the context of a two-stage downconversion scheme employing a combination of TDD or FDD designs.

  5. Cholinergic Signaling Exerts Protective Effects in Models of Sympathetic Hyperactivity-Induced Cardiac Dysfunction

    PubMed Central

    Gavioli, Mariana; Lara, Aline; Almeida, Pedro W. M.; Lima, Augusto Martins; Damasceno, Denis D.; Rocha-Resende, Cibele; Ladeira, Marina; Resende, Rodrigo R.; Martinelli, Patricia M.; Melo, Marcos Barrouin; Brum, Patricia C.; Fontes, Marco Antonio Peliky; Souza Santos, Robson A.; Prado, Marco A. M.; Guatimosim, Silvia

    2014-01-01

    Cholinergic control of the heart is exerted by two distinct branches; the autonomic component represented by the parasympathetic nervous system, and the recently described non-neuronal cardiomyocyte cholinergic machinery. Previous evidence has shown that reduced cholinergic function leads to deleterious effects on the myocardium. Yet, whether conditions of increased cholinergic signaling can offset the pathological remodeling induced by sympathetic hyperactivity, and its consequences for these two cholinergic axes are unknown. Here, we investigated two models of sympathetic hyperactivity: i) the chronic beta-adrenergic receptor stimulation evoked by isoproterenol (ISO), and ii) the α2A/α2C-adrenergic receptor knockout (KO) mice that lack pre-synaptic adrenergic receptors. In both models, cholinergic signaling was increased by administration of the cholinesterase inhibitor, pyridostigmine. First, we observed that isoproterenol produces an autonomic imbalance characterized by increased sympathetic and reduced parasympathetic tone. Under this condition transcripts for cholinergic proteins were upregulated in ventricular myocytes, indicating that non-neuronal cholinergic machinery is activated during adrenergic overdrive. Pyridostigmine treatment prevented the effects of ISO on autonomic function and on the ventricular cholinergic machinery, and inhibited cardiac remodeling. α2A/α2C-KO mice presented reduced ventricular contraction when compared to wild-type mice, and this dysfunction was also reversed by cholinesterase inhibition. Thus, the cardiac parasympathetic system and non-neuronal cardiomyocyte cholinergic machinery are modulated in opposite directions under conditions of increased sympathetic drive or ACh availability. Moreover, our data support the idea that pyridostigmine by restoring ACh availability is beneficial in heart disease. PMID:24992197

  6. Weighted calibration with reduced number of signals by weighing factor modelling: application to the identification of explosives by ion chromatography.

    PubMed

    Brasil, Beatriz; Bettencourt da Silva, Ricardo J N; Camões, M Filomena G F C; Salgueiro, Pedro A S

    2013-12-01

    The linear weighted regression model (LW) can be used to calibrate analytical instrumentation in a range of quantities (e.g. concentration or mass) wider than possible by the linear unweighted regression model, LuW (i.e. the least squares regression model), since this model can be applied when signals are not equally precise through the calibration range. If precision of signals varies within the calibration range, the regression line should be defined taking into account that more precise signals are more reliable and should count more to define regression parameters. Nevertheless, the LW requires the determination of the variation of signals precision through the calibration range. Typically, this information is collected experimentally for each calibration, requiring a large number of replicate collection of signals of calibrators. This work proposes reducing the number of signals needed to perform LW calibrations by developing models of weighing factors robust to daily variations of instrument sensibility. These models were applied to the determination of the ionic composition of the water soluble fraction of explosives. The adequacy of the developed models was tested through the analysis of control standards, certified reference materials and the ion balance of anions and cations in aqueous extracts of explosives, considering the measurement uncertainty estimated by detailed metrological models. The high success rate of the comparisons between estimated and known quantity values of reference solutions, considering results uncertainty, proves the validity of developed metrological models. The relative expanded measurement uncertainty of single determinations ranged from 1.93% to 35.7% for calibrations performed along 4 months. PMID:24267095

  7. Weighted calibration with reduced number of signals by weighing factor modelling: application to the identification of explosives by ion chromatography.

    PubMed

    Brasil, Beatriz; Bettencourt da Silva, Ricardo J N; Camões, M Filomena G F C; Salgueiro, Pedro A S

    2013-12-01

    The linear weighted regression model (LW) can be used to calibrate analytical instrumentation in a range of quantities (e.g. concentration or mass) wider than possible by the linear unweighted regression model, LuW (i.e. the least squares regression model), since this model can be applied when signals are not equally precise through the calibration range. If precision of signals varies within the calibration range, the regression line should be defined taking into account that more precise signals are more reliable and should count more to define regression parameters. Nevertheless, the LW requires the determination of the variation of signals precision through the calibration range. Typically, this information is collected experimentally for each calibration, requiring a large number of replicate collection of signals of calibrators. This work proposes reducing the number of signals needed to perform LW calibrations by developing models of weighing factors robust to daily variations of instrument sensibility. These models were applied to the determination of the ionic composition of the water soluble fraction of explosives. The adequacy of the developed models was tested through the analysis of control standards, certified reference materials and the ion balance of anions and cations in aqueous extracts of explosives, considering the measurement uncertainty estimated by detailed metrological models. The high success rate of the comparisons between estimated and known quantity values of reference solutions, considering results uncertainty, proves the validity of developed metrological models. The relative expanded measurement uncertainty of single determinations ranged from 1.93% to 35.7% for calibrations performed along 4 months.

  8. State and parameter estimation of a neural mass model from electrophysiological signals during the status epilepticus.

    PubMed

    López-Cuevas, Armando; Castillo-Toledo, Bernardino; Medina-Ceja, Laura; Ventura-Mejía, Consuelo

    2015-06-01

    Status epilepticus is an emergency condition in patients with prolonged seizure or recurrent seizures without full recovery between them. The pathophysiological mechanisms of status epilepticus are not well established. With this argument, we use a computational modeling approach combined with in vivo electrophysiological data obtained from an experimental model of status epilepticus to infer about changes that may lead to a seizure. Special emphasis is done to analyze parameter changes during or after pilocarpine administration. A cubature Kalman filter is utilized to estimate parameters and states of the model in real time from the observed electrophysiological signals. It was observed that during basal activity (before pilocarpine administration) the parameters presented a standard deviation below 30% of the mean value, while during SE activity, the parameters presented variations larger than 200% of the mean value with respect to basal state. The ratio of excitation-inhibition, increased during SE activity by 80% with respect to the transition state, and reaches the lowest value during cessation. In addition, a progression between low and fast inhibitions before or during this condition was found. This method can be implemented in real time, which is particularly important for the design of stimulation devices that attempt to stop seizures. These changes in the parameters analyzed during seizure activity can lead to better understanding of the mechanisms of epilepsy and to improve its treatments.

  9. A robust vector field correction method via a mixture statistical model of PIV signal

    NASA Astrophysics Data System (ADS)

    Lee, Yong; Yang, Hua; Yin, Zhouping

    2016-03-01

    Outlier (spurious vector) is a common problem in practical velocity field measurement using particle image velocimetry technology (PIV), and it should be validated and replaced by a reliable value. One of the most challenging problems is to correctly label the outliers under the circumstance that measurement noise exists or the flow becomes turbulent. Moreover, the outlier's cluster occurrence makes it difficult to pick out all the outliers. Most of current methods validate and correct the outliers using local statistical models in a single pass. In this work, a vector field correction (VFC) method is proposed directly from a mixture statistical model of PIV signal. Actually, this problem is formulated as a maximum a posteriori (MAP) estimation of a Bayesian model with hidden/latent variables, labeling the outliers in the original field. The solution of this MAP estimation, i.e., the outlier set and the restored flow field, is optimized iteratively using an expectation-maximization algorithm. We illustrated this VFC method on two kinds of synthetic velocity fields and two kinds of experimental data and demonstrated that it is robust to a very large number of outliers (even up to 60 %). Besides, the proposed VFC method has high accuracy and excellent compatibility for clustered outliers, compared with the state-of-the-art methods. Our VFC algorithm is computationally efficient, and corresponding Matlab code is provided for others to use it. In addition, our approach is general and can be seamlessly extended to three-dimensional-three-component (3D3C) PIV data.

  10. Signal-to-Noise Behavior for Matches to Gradient Direction Models of Corners in Images

    SciTech Connect

    Paglieroni, D W; Manay, S

    2007-02-09

    Gradient direction models for corners of prescribed acuteness, leg length, and leg thickness are constructed by generating fields of unit vectors emanating from leg pixels that point normal to the edges. A novel FFT-based algorithm that quickly matches models of corners at all possible positions and orientations in the image to fields of gradient directions for image pixels is described. The signal strength of a corner is discussed in terms of the number of pixels along the edges of a corner in an image, while noise is characterized by the coherence of gradient directions along those edges. The detection-false alarm rate behavior of our corner detector is evaluated empirically by manually constructing maps of corner locations in typical overhead images, and then generating different ROC curves for matches to models of corners with different leg lengths and thicknesses. We then demonstrate how corners found with our detector can be used to quickly and automatically find families of polygons of arbitrary position, size and orientation in overhead images.

  11. Self-deception as self-signalling: a model and experimental evidence.

    PubMed

    Mijović-Prelec, Danica; Prelec, Drazen

    2010-01-27

    Self-deception has long been the subject of speculation and controversy in psychology, evolutionary biology and philosophy. According to an influential 'deflationary' view, the concept is an over-interpretation of what is in reality an instance of motivationally biased judgement. The opposite view takes the interpersonal deception analogy seriously, and holds that some part of the self actively manipulates information so as to mislead the other part. Building on an earlier self-signalling model of Bodner and Prelec, we present a game-theoretic model of self-deception. We propose that two distinct mechanisms collaborate to produce overt expressions of belief: a mechanism responsible for action selection (including verbal statements) and an interpretive mechanism that draws inferences from actions and generates emotional responses consistent with the inferences. The model distinguishes between two modes of self-deception, depending on whether the self-deceived individual regards his own statements as fully credible. The paper concludes with a new experimental study showing that self-deceptive judgements can be reliably and repeatedly elicited with financial incentives in a categorization task, and that the degree of self-deception varies with incentives. The study also finds evidence of the two forms of self-deception. The psychological benefits of self-deception, as measured by confidence, peak at moderate levels.

  12. Computational modeling of chemotactic signaling and aggregation of microglia around implantation site during deep brain stimulation

    NASA Astrophysics Data System (ADS)

    Silchenko, A. N.; Tass, P. A.

    2013-10-01

    It is well established that prolonged electrical stimulation of brain tissue causes massive release of ATP in the extracellular space. The released ATP and the products of its hydrolysis, such as ADP and adenosine, become the main elements mediating chemotactic sensitivity and motility of microglial cells via subsequent activation of P2Y2,12 as well as A3A and A2A adenosine receptors. The size of the sheath around the electrode formed by the microglial cells is an important criterion for the optimization of the parameters of electrical current delivered to brain tissue. Here, we study a purinergic signaling pathway underlying the chemotactic motion of microglia towards the implanted electrode during deep brain stimulation. We present a computational model describing formation of a stable aggregate around the implantation site due to the joint chemo-attractive action of ATP and ADP together with a mixed influence of extracellular adenosine. The model was built in accordance with the classical Keller-Segel approach and includes an equation for the cells' density as well as equations describing the hydrolysis of extracellular ATP via successive reaction steps ATP →ADP →AMP →adenosine. The results of our modeling allowed us to reveal the dependence of the width of the encapsulating layer around the electrode on the amount of ATP released due to permanent electrical stimulation. The dependences of the aggregates' size on the parameter governing the nonlinearity of interaction between extracellular adenosine and adenosine receptors are also analyzed.

  13. Dynamic Modeling and Analysis of the Cross-Talk between Insulin/AKT and MAPK/ERK Signaling Pathways.

    PubMed

    Arkun, Yaman

    2016-01-01

    Feedback loops play a key role in the regulation of the complex interactions in signal transduction networks. By studying the network of interactions among the biomolecules present in signaling pathways at the systems level, it is possible to understand how the biological functions are regulated and how the diseases emerge from their deregulations. This paper identifies the key feedback loops involved in the cross-talk among the insulin-AKT and MAPK/ERK signaling pathways. We developed a mathematical model that can be used to study the steady-state and dynamic behavior of the interactions among these two important signaling pathways. Modeling analysis and simulation case studies identify the key interaction parameters and the feedback loops that determine the normal and disease phenotypes. PMID:26930065

  14. Dynamic Modeling and Analysis of the Cross-Talk between Insulin/AKT and MAPK/ERK Signaling Pathways

    PubMed Central

    Arkun, Yaman

    2016-01-01

    Feedback loops play a key role in the regulation of the complex interactions in signal transduction networks. By studying the network of interactions among the biomolecules present in signaling pathways at the systems level, it is possible to understand how the biological functions are regulated and how the diseases emerge from their deregulations. This paper identifies the key feedback loops involved in the cross-talk among the insulin-AKT and MAPK/ERK signaling pathways. We developed a mathematical model that can be used to study the steady-state and dynamic behavior of the interactions among these two important signaling pathways. Modeling analysis and simulation case studies identify the key interaction parameters and the feedback loops that determine the normal and disease phenotypes. PMID:26930065

  15. A computational model for early events in B cell antigen receptor signaling: analysis of the roles of Lyn and Fyn

    PubMed Central

    Barua, Dipak; Hlavacek, William S.; Lipniacki, Tomasz

    2012-01-01

    B cell antigen receptor (BCR) signaling regulates the activities and fates of B cells. BCR signaling encompasses two feedback loops emanating from Lyn and Fyn, which are Src-family protein tyrosine kinases (SFKs). Positive feedback arises from SFK-mediated trans phosphorylation of BCR and receptor-bound Lyn and Fyn, which increases the kinase activities of Lyn and Fyn. Negative feedback arises from SFK-mediated cis phosphorylation of the transmembrane adapter protein PAG1, which recruits the cytosolic protein tyrosine kinase Csk to the plasma membrane, where it acts to decrease the kinase activities of Lyn and Fyn. To study the effects of the positive and negative feedback loops on the dynamical stability of BCR signaling and the relative contributions of Lyn and Fyn to BCR signaling, we consider here a rule-based model for early events in BCR signaling that encompasses membrane-proximal interactions of six proteins: BCR, Lyn, Fyn, Csk, PAG1 and Syk, a cytosolic protein tyrosine kinase that is activated as a result of SFK-mediated phosphorylation of BCR. The model is consistent with known effects of Lyn and Fyn deletions. We find that BCR signaling can generate a single pulse or oscillations of Syk activation depending on the strength of antigen signal and the relative levels of Lyn and Fyn. We also show that bistability can arise in Lyn or Csk deficient cells. PMID:22711887

  16. Consistency of Crustal Loading Signals Derived from Models and GPS: A Re-examination

    NASA Astrophysics Data System (ADS)

    Collilieux, X.; Rebischung, P.; van Dam, T. M.; Ray, J.; Altamimi, Z.

    2011-12-01

    Various space geodetic studies over the past two decades have detected vertical displacements of the Earth's surface caused by temporal variations in the distribution of ocean, atmospheric, and continental water masses. Most past research has focused on a single component of the mass load and till now only vertical motions have been examined. Successively stronger correlations have been seen as improvements have been made in the load models as well as in measurements by the Gravity Recovery and Climate Experiment (GRACE) of surface mass changes and by the Global Positioning System (GPS) of station height variations. Initial comparisons of modeled surface mass load displacements with GPS heights were most successful for areas with large signals, such as the Amazon River basin, where the amplitude of annual height variations reaches ~13 mm. Following large-scale efforts to reprocess historic GPS data series with modern analysis methods, the most recent results find that mass load corrections reduce the WRMS scatter of GPS verticals for ~77% of global networks of more than 100 stations. We have re-examined this problem but included the horizontal, as well as vertical, components and used the most current station time series from the International GNSS Service (IGS) for a global set of 706 stations, each having more than 100 weekly observations. The long-term stacking of the weekly frame solutions has taken utmost care to minimize aliasing of local load signals into the frame parameters to ensure the most reliable time series of individual station motions. Using a combination of NCEP atmosphere, ECCO non-tidal ocean, and LDAS surface water load models (averaged to the middle of each GPS week) as a posteriori corrections, the WRMS GPS scatters are reduced for 72, 63, and 87% of station dN, dE, and dU components, respectively. Fitted annual amplitudes are correspondingly reduced for similar fractions of stations. The weighted mean dU annual amplitude drops from 3.9 to 1

  17. DC and small-signal physical models for the AlGaAs/GaAs high electron mobility transistor

    NASA Technical Reports Server (NTRS)

    Sarker, J. C.; Purviance, J. E.

    1991-01-01

    Analytical and numerical models are developed for the microwave small-signal performance, such as transconductance, gate-to-source capacitance, current gain cut-off frequency and the optimum cut-off frequency of the AlGaAs/GaAs High Electron Mobility Transistor (HEMT), in both normal and compressed transconductance regions. The validated I-V characteristics and the small-signal performances of four HeMT's are presented.

  18. Human fetal brain imaging by magnetoencephalography: verification of fetal brain signals by comparison with fetal brain models.

    PubMed

    Vrba, J; Robinson, S E; McCubbin, J; Murphy, P; Eswaran, H; Wilson, J D; Preissl, H; Lowery, C L

    2004-03-01

    Fetal magnetoencephalogram (fMEG) is measured in the presence of a large interference from maternal and fetal magnetocardiograms (mMCG and fMCG). This cardiac interference can be successfully removed by orthogonal projection of the corresponding spatial vectors. However, orthogonal projection redistributes the fMEG signal among channels. Such redistribution can be readily accounted for in the forward solution, and the signal topography can also be corrected. To assure that the correction has been done properly, and also to verify that the measured signal originates from within the fetal head, we have modeled the observed fMEG by two extreme models where the fetal head is assumed to be either electrically transparent or isolated from the abdominal tissue. Based on the measured spontaneous, sharp wave, and flash-evoked fMEG signals, we have concluded that the model of the electrically isolated fetal head is more appropriate for fMEG analysis. We show with the help of this model that the redistribution due to projection was properly corrected, and also, that the measured fMEG is consistent with the known position of the fetal head. The modeling provides additional confidence that the measured signals indeed originate from within the fetal head. PMID:15006668

  19. Analog and numerical modeling on the propagation of seismic electromagnetic signals (SEMS)

    NASA Astrophysics Data System (ADS)

    Huang, Q.; Lin, Y.; Wang, Q.

    2010-12-01

    Study on propagation of seismic electromagnetic signals (SEMS) plays an important role in understanding earthquake-related electromagnetic phenomena. Some laboratory analog experiments based on a geographical scaling model and a waveguide model were developed to simulate the propagation of SEMS. These experimental results showed that the geographical effect such as the distribution of ocean and land may lead to some aspect of the selectivity phenomenon. Some analytical and numerical works based on a conductive channel model were also presented as an explanation of the selectivity phenomenon. However, whether or not such conclusion holds for a more realistic 3D model deserves further investigation. In this paper, we simulate the propagation characteristics of SEMS in some typical 3-D models using COMSOL Multiphysics, a software of finite element method (FEM). After some validation tests of the above FEM software, we investigated the possible effects on the propagation characteristics of SEMS from the model parameters. Then, we considered a model with a conductive fault buried in a three-layered media, and an electric dipole source located close to the center of the fault. The simulation results indicated that the amplification effect of a conductive channel, which has been adopted as a possible explanation of some SEMS observations, can be expected only at a much lower frequency. We also simulated the possible ocean effect on the propagation of SEMS. As a case study, we modeled the Greek archipelago, in which numerious SEMS have been reported. The numerical results showed a decayed pattern of SEMS at a frequency lower than the cut-off frequency, and a rippled propagation pattern at a frequency higher than the cut-off frequency. These results are consistent with the previous analog experimental results. Further examples of analog and numerical simulations are investigated. The numerical simulations combined with the analog experiments may provide possible explanation

  20. Evaluation of different time domain peak models using extreme learning machine-based peak detection for EEG signal.

    PubMed

    Adam, Asrul; Ibrahim, Zuwairie; Mokhtar, Norrima; Shapiai, Mohd Ibrahim; Cumming, Paul; Mubin, Marizan

    2016-01-01

    Various peak models have been introduced to detect and analyze peaks in the time domain analysis of electroencephalogram (EEG) signals. In general, peak model in the time domain analysis consists of a set of signal parameters, such as amplitude, width, and slope. Models including those proposed by Dumpala, Acir, Liu, and Dingle are routinely used to detect peaks in EEG signals acquired in clinical studies of epilepsy or eye blink. The optimal peak model is the most reliable peak detection performance in a particular application. A fair measure of performance of different models requires a common and unbiased platform. In this study, we evaluate the performance of the four different peak models using the extreme learning machine (ELM)-based peak detection algorithm. We found that the Dingle model gave the best performance, with 72 % accuracy in the analysis of real EEG data. Statistical analysis conferred that the Dingle model afforded significantly better mean testing accuracy than did the Acir and Liu models, which were in the range 37-52 %. Meanwhile, the Dingle model has no significant difference compared to Dumpala model.

  1. Evaluation of different time domain peak models using extreme learning machine-based peak detection for EEG signal.

    PubMed

    Adam, Asrul; Ibrahim, Zuwairie; Mokhtar, Norrima; Shapiai, Mohd Ibrahim; Cumming, Paul; Mubin, Marizan

    2016-01-01

    Various peak models have been introduced to detect and analyze peaks in the time domain analysis of electroencephalogram (EEG) signals. In general, peak model in the time domain analysis consists of a set of signal parameters, such as amplitude, width, and slope. Models including those proposed by Dumpala, Acir, Liu, and Dingle are routinely used to detect peaks in EEG signals acquired in clinical studies of epilepsy or eye blink. The optimal peak model is the most reliable peak detection performance in a particular application. A fair measure of performance of different models requires a common and unbiased platform. In this study, we evaluate the performance of the four different peak models using the extreme learning machine (ELM)-based peak detection algorithm. We found that the Dingle model gave the best performance, with 72 % accuracy in the analysis of real EEG data. Statistical analysis conferred that the Dingle model afforded significantly better mean testing accuracy than did the Acir and Liu models, which were in the range 37-52 %. Meanwhile, the Dingle model has no significant difference compared to Dumpala model. PMID:27462484

  2. Control of IL-17 receptor signaling and tissue inflammation by the p38α–MKP-1 signaling axis in a mouse model of multiple sclerosis

    PubMed Central

    Vogel, Peter; Chi, Hongbo

    2015-01-01

    T helper 17 (TH17) cells are CD4+ T cells that secrete the proinflammatory cytokine interleukin-17 (IL-17) and that play a key pathogenic role in autoimmune diseases. Through inducible and tissue-specific deletion systems, we described the temporal and cell type–specific roles of the mitogen-activated protein kinase (MAPK) p38α in mediating TH17 cell–induced tissue inflammation. Inducible deletion of Mapk14 (which encodes p38α) after the onset of experimental autoimmune encephalomyelitis (EAE), a murine model for human multiple sclerosis, protected mice from inflammation. Furthermore, the severity of EAE was markedly reduced in mice with specific loss of p38α in neuroectoderm-derived cells, including astrocytes, an effect that was associated with defective production of chemokines and decreased infiltration of the target tissue by immune cells. p38α linked IL-17 receptor (IL-17R) signaling to the expression of genes encoding proinflammatory chemokines and cytokines. Mice that lacked MAPK phosphatase 1 (MKP-1), an inhibitor of p38α, had exacerbated EAE and enhanced expression of IL-17R–dependent genes. Our results suggest that the p38α–MKP-1 signaling axis links IL-17R signaling in tissue-resident cells to autoimmune inflammation dependent on infiltrating TH17 cells. PMID:25737586

  3. A Finite Element Model Approach to Determine the Influence of Electrode Design and Muscle Architecture on Myoelectric Signal Properties

    PubMed Central

    Teklemariam, A.; Hodson-Tole, E. F.; Reeves, N. D.; Costen, N. P.; Cooper, G.

    2016-01-01

    Introduction Surface electromyography (sEMG) is the measurement of the electrical activity of the skeletal muscle tissue detected at the skin’s surface. Typically, a bipolar electrode configuration is used. Most muscles have pennate and/or curved fibres, meaning it is not always feasible to align the bipolar electrodes along the fibres direction. Hence, there is a need to explore how different electrode designs can affect sEMG measurements. Method A three layer finite element (skin, fat, muscle) muscle model was used to explore different electrode designs. The implemented model used as source signal an experimentally recorded intramuscular EMG taken from the biceps brachii muscle of one healthy male. A wavelet based intensity analysis of the simulated sEMG signal was performed to analyze the power of the signal in the time and frequency domain. Results The model showed muscle tissue causing a bandwidth reduction (to 20-92- Hz). The inter-electrode distance (IED) and the electrode orientation relative to the fibres affected the total power but not the frequency filtering response. The effect of significant misalignment between the electrodes and the fibres (60°- 90°) could be reduced by increasing the IED (25–30 mm), which attenuates signal cancellation. When modelling pennated fibres, the muscle tissue started to act as a low pass filter. The effect of different IED seems to be enhanced in the pennated model, while the filtering response is changed considerably only when the electrodes are close to the signal termination within the model. For pennation angle greater than 20°, more than 50% of the source signal was attenuated, which can be compensated by increasing the IED to 25 mm. Conclusion Differences in tissue filtering properties, shown in our model, indicates that different electrode designs should be considered for muscle with different geometric properties (i.e. pennated muscles). PMID:26886908

  4. Insulin Signaling Misregulation underlies Circadian and Cognitive Deficits in a Drosophila Fragile X Model

    PubMed Central

    Monyak, Rachel E.; Emerson, Danielle; Schoenfeld, Brian P.; Zheng, Xiangzhong; Chambers, Daniel B.; Rosenfelt, Cory; Langer, Steven; Hinchey, Paul; Choi, Catherine H.; McDonald, Thomas V.; Bolduc, Francois V.; Sehgal, Amita; McBride, Sean M.J.; Jongens, Thomas A.

    2016-01-01

    Fragile X syndrome (FXS) is an undertreated neurodevelopmental disorder characterized by low IQ and a wide range of other symptoms including disordered sleep and autism. Although FXS is the most prevalent inherited cause of intellectual disability, its mechanistic underpinnings are not well understood. Using Drosophila as a model of FXS, we showed that select expression of dfmr1 in the insulin-producing cells (IPCs) of the brain was sufficient to restore normal circadian behavior and to rescue the memory deficits in the fragile X mutant fly. Examination of the insulin-signaling (IS) pathway revealed elevated levels of Drosophila insulin-like peptide 2 (Dilp2) in the IPCs and elevated IS in the dfmr1 mutant brain. Consistent with a causal role for elevated IS in dfmr1 mutant phenotypes, expression of dfmr1 specifically in the IPCs reduced IS, and genetic reduction of the insulin pathway also led to amelioration of circadian and memory defects. Furthermore we showed that treatment with the FDA approved drug metformin also rescued memory. Finally, we showed that reduction of IS is required at different time points to rescue circadian behavior and memory. Our results indicate that insulin misregulation underlies the circadian and cognitive phenotypes displayed by the Drosophila fragile X model, and thus reveal a metabolic pathway that can be targeted by new and already approved drugs to treat fragile X patients. PMID:27090306

  5. Computational Modeling of PI3K/AKT and MAPK Signaling Pathways in Melanoma Cancer

    PubMed Central

    Pappalardo, Francesco; Russo, Giulia; Candido, Saverio; Pennisi, Marzio; Cavalieri, Salvatore; Motta, Santo; McCubrey, James A.; Nicoletti, Ferdinando; Libra, Massimo

    2016-01-01

    Background Malignant melanoma is an aggressive tumor of the skin and seems to be resistant to current therapeutic approaches. Melanocytic transformation is thought to occur by sequential accumulation of genetic and molecular alterations able to activate the Ras/Raf/MEK/ERK (MAPK) and/or the PI3K/AKT (AKT) signalling pathways. Specifically, mutations of B-RAF activate MAPK pathway resulting in cell cycle progression and apoptosis prevention. According to these findings, MAPK and AKT pathways may represent promising therapeutic targets for an otherwise devastating disease. Result Here we show a computational model able to simulate the main biochemical and metabolic interactions in the PI3K/AKT and MAPK pathways potentially involved in melanoma development. Overall, this computational approach may accelerate the drug discovery process and encourages the identification of novel pathway activators with consequent development of novel antioncogenic compounds to overcome tumor cell resistance to conventional therapeutic agents. The source code of the various versions of the model are available as S1 Archive. PMID:27015094

  6. Neuroretinal hypoxic signaling in a new preclinical murine model for proliferative diabetic retinopathy

    PubMed Central

    Wert, Katherine J; Mahajan, Vinit B; Zhang, Lijuan; Yan, Yuanqing; Li, Yao; Tosi, Joaquin; Hsu, Chun Wei; Nagasaki, Takayuki; Janisch, Kerstin M; Grant, Maria B; Mahajan, MaryAnn; Bassuk, Alexander G; Tsang, Stephen H

    2016-01-01

    Diabetic retinopathy (DR) affects approximately one-third of diabetic patients and, if left untreated, progresses to proliferative DR (PDR) with associated vitreous hemorrhage, retinal detachment, iris neovascularization, glaucoma and irreversible blindness. In vitreous samples of human patients with PDR, we found elevated levels of hypoxia inducible factor 1 alpha (HIF1α). HIFs are transcription factors that promote hypoxia adaptation and have important functional roles in a wide range of ischemic and inflammatory diseases. To recreate the human PDR phenotype for a preclinical animal model, we generated a mouse with neuroretinal-specific loss of the von Hippel Lindau tumor suppressor protein, a protein that targets HIF1α for ubiquitination. We found that the neuroretinal cells in these mice overexpressed HIF1α and developed severe, irreversible ischemic retinopathy that has features of human PDR. Rapid progression of retinopathy in these mutant mice should facilitate the evaluation of therapeutic agents for ischemic and inflammatory blinding disorders. In addition, this model system can be used to manipulate the modulation of the hypoxia signaling pathways, for the treatment of non-ocular ischemic and inflammatory disorders. PMID:27195131

  7. Spontaneous oscillations, signal amplification and synchronization in a model of active hair bundle mechanics

    PubMed Central

    Han, Lijuan; Neiman, Alexander B.

    2010-01-01

    We study spontaneous dynamics and signal transduction in a model of active hair bundle mechanics of sensory hair cells. The hair bundle motion is subjected to internal noise resulted from thermal fluctuations and stochastic dynamics of mechano-electrical transduction ion channels. Similar to other studies we found that in the presence of noise the coherence of stochastic oscillations is maximal at a point on the bifurcation diagram away from the Andronov-Hopf bifurcation and is close to the point of maximum sensitivity of the system to weak periodic mechanical perturbations. Despite decoherent effect of noise the stochastic hair bundle oscillations can be synchronized by external periodic force of few pN amplitude in a finite range of control parameters. We then study effects of receptor potential oscillations on mechanics of the hair bundle and show that the hair bundle oscillations can be synchronized by oscillating receptor voltage. Moreover, using a linear model for the receptor potential we show that bi-directional coupling of the hair bundle and the receptor potential results in significant enhancement of the coherence of spontaneous oscillations and of the sensitivity to the external mechanical perturbations. PMID:20481759

  8. Redox Signaling in an In Vivo Murine Model of Low Magnitude Oscillatory Wall Shear Stress

    PubMed Central

    Willett, Nick J.; Kundu, Kousik; Knight, Sarah F.; Dikalov, Sergey; Murthy, Niren

    2011-01-01

    Abstract Wall Shear Stress (WSS) has been identified as an important factor in the pathogenesis of atherosclerosis. We utilized a novel murine aortic coarctation model to acutely create a region of low magnitude oscillatory WSS in vivo. We employed this model to test the hypothesis that acute changes in WSS in vivo induce upregulation of inflammatory proteins, mediated by reactive oxygen species (ROS). Superoxide generation and VCAM-1 expression both increased in regions of low magnitude oscillatory WSS. WSS-dependent superoxide formation was attenuated by tempol treatment, but was unchanged in p47 phox knockout (ko) mice. However, in both the p47 phox ko mice and the tempol-treated mice, low magnitude oscillatory WSS produced an increase in VCAM-1 expression comparable to control mice. Additionally, this same VCAM-1 expression was observed in ebselen-treated mice and catalase overexpressing mice. These results suggest that although the redox state is important to the overall pathogenesis of atherosclerosis, the initial WSS-dependent inflammatory response leading to lesion localization is not dependent on ROS. Antioxid. Redox Signal. 15, 1369–1378. PMID:20712414

  9. Calorie restriction alters physical performance but not cognition in two models of altered neuroendocrine signaling.

    PubMed

    Minor, Robin K; Villarreal, Julissa; McGraw, Michael; Percival, Susan S; Ingram, Donald K; de Cabo, Rafael

    2008-05-16

    A major neuroendocrinological effect of calorie restriction (CR) is induction of neuropeptide Y (NPY) in the arcuate nucleus (ARC). Aside from its appetite-stimulating effects, NPY is thought to be involved in the modulation of behavioral processes including anxiety and learning and memory. In the present study physical fitness, anxiety, and learning/memory-related tasks were assessed in mice lacking NPY or a functional ARC after dietary manipulation by CR. Physical fitness was improved by CR when measured by inclined screen and rotarod, and this diet effect was not affected by NPY or ARC status. As has been observed previously, the NPY knockout mice displayed heightened anxiety in an open field. This phenotype was not fully recapitulated in the ARC-lesioned model. CR affected neither total locomotor activity in the open field nor thigmotaxic behavior in these models. Neither NPY nor CR had a significant effect on Morris water maze performance; however, ARC-damaged mice were unable to learn the task, and this deficit was not corrected by CR. We conclude that despite established effects of CR on ARC signaling, our results suggest a mechanistic separation between the two where behavior is concerned.

  10. Modeling and signal processing of magneto-optic images for aviation applications

    NASA Astrophysics Data System (ADS)

    Ramuhalli, P.; Slade, James; Park, U.; Xuan, Liang; Udpa, L.

    2003-10-01

    Magneto-optic imaging (MOI) is a relatively new technology that produces analog images of magnetic flux leakage from surface and subsurface defects. An alternating current carrying foil serves as the excitation source and induces eddy currents in a conducting test specimen. Under normal conditions, the associated magnetic flux is tangential to specimen surface. Anomalies in the specimen result in generating a normal component of the magnetic flux density. The magneto-optic sensor produces a binary valued image of this anomalous magnetic field. The current system has two shortcomings. First, the presence of a textured background due to the domain structures in the sensor makes detection of third layer cracks and corrosion difficult. Second, the qualitative nature of the MO images does not provide a basis for making quantitative improvements to the MOI system. The availability of a theoretical model that can simulate the MOI system performance is extremely important for the optimization of the MOI sensor and hardware system. This paper presents a finite element model and its use in understanding the capabilities of the MOI system. In addition the paper also presents signal-processing methods for eliminating the background noise.

  11. Quantifying internally generated and externally forced climate signals at regional scales in CMIP5 models

    NASA Astrophysics Data System (ADS)

    Lyu, Kewei; Zhang, Xuebin; Church, John A.; Hu, Jianyu

    2015-11-01

    The Earth's climate evolves because of both internal variability and external forcings. Using Coupled Model Intercomparison Project Phase 5 (CMIP5) models, here we quantify the ratio of externally forced variance to total variance on interannual and longer time scales for regional surface air temperature (SAT) and sea l