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Sample records for modeling radioxenon signals

  1. 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

  2. Inverse modeling of April 2013 radioxenon detections

    NASA Astrophysics Data System (ADS)

    Hofman, Radek; Seibert, Petra; Philipp, Anne

    2014-05-01

    Significant concentrations of radioactive xenon isotopes (radioxenon) were detected by the International Monitoring System (IMS) for verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) in April 2013 in Japan. Particularly, three detections of Xe-133 made between 2013-04-07 18:00 UTC and 2013-04-09 06:00 UTC at the station JPX38 are quite notable with respect to the measurement history of the station. Our goal is to analyze the data and perform inverse modeling under different assumptions. This work is useful with respect to nuclear test monitoring as well as for the analysis of and response to nuclear emergencies. Two main scenarios will be pursued: (i) Source location is assumed to be known (DPRK test site). (ii) Source location is considered unknown. We attempt to estimate the source strength and the source strength along with its plausible location compatible with the data in scenario (i) and (ii), respectively. We are considering also the possibility of a vertically distributed source. Calculations of source-receptor sensitivity (SRS) fields and the subsequent inversion are aimed at going beyond routine calculations performed by the CTBTO. For SRS calculations, we employ the Lagrangian particle dispersion model FLEXPART with high resolution ECMWF meteorological data (grid cell sizes of 0.5, 0.25 and ca. 0.125 deg). This is important in situations where receptors or sources are located in complex terrain which is the case of the likely source of detections-the DPRK test site. SRS will be calculated with convection enabled in FLEXPART which will also increase model accuracy. In the variational inversion procedure attention will be paid not only to all significant detections and their uncertainties but also to non-detections which can have a large impact on inversion quality. We try to develop and implement an objective algorithm for inclusion of relevant data where samples from temporal and spatial vicinity of significant detections are added in an

  3. Measurement and modelling of radioxenon plumes in the Ottawa Valley.

    PubMed

    Stocki, T J; Armand, P; Heinrich, Ph; Ungar, R K; D'Amours, R; Korpach, E P; Bellivier, A; Taffary, T; Malo, A; Bean, M; Hoffman, I; Jean, M

    2008-11-01

    Since 2001 a real-time radiation monitoring network of Canadian nuclear facilities and major population centres has been implemented for response to nuclear incidents including a possible terrorist attack. Unshielded NaI(Tl) spectroscopic detectors are employed to measure gamma radiation from airborne radioactivity and radioactivity deposited on the ground. These detectors are composed of a standard 3''x3'' cylindrical NaI(Tl) spectrometers with data storage and integrated telemetry. Some of the detectors have been deployed in the Ottawa Valley near Chalk River Laboratories and Ottawa, which has a complex radioxenon environment due to the proximity of nuclear power reactors, and medical isotope facilities. Although not a health threat, these releases have provided an opportunity for the Canadian Meteorological Centre and the Commissariat à l'Energie Atomique to validate their meteorological models. The meteorological models of the two organizations are in good agreement on the origin and the source terms of these releases. PMID:18799247

  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. 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.

  7. 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

  8. DESIGN OF A PHOSWICH WELL DETECTOR FOR RADIOXENON MONITORING

    SciTech Connect

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

    2006-09-19

    The network of monitoring stations established through the Comprehensive Nuclear-Test-Ban Treaty includes systems to detect radioactive xenon released into the atmosphere from nuclear weapons testing. One such monitoring system is the Automated Radio-xenon Sampler/Analyzer (ARSA) developed at Pacific Northwest National Laboratory. For high sensitivity, the ARSA system currently uses a complex arrangement of separate beta and gamma detectors to detect beta-gamma coincidences from characteristic radioxenon isotopes in small samples of xenon extracted from large volumes of air. The coincidence measurement is very sensitive, but the large number of detectors and photomultiplier tubes requires careful calibration. A simplified approach is to use a single phoswich detector, consisting of optically coupled plastic and CsI scintillators. In the phoswich detector, most beta particles are absorbed in the plastic scintillator and most gamma rays are absorbed in the CsI, and pulse shape analysis of the detector signal is used to detect coincidences. As only a single detector and electronics readout channel is used, the complexity of the system is greatly reduced. Previous studies with a planar 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 the design of a phoswich well detector, consisting of a 1'' diameter plastic cell enclosed in a 3'' CsI crystal. Several variations of the well detector geometry have been studied using Monte Carlo modeling and evaluated for detection efficiency, effects on energy resolution, and ease of manufacturing. One prototype detector has been built and we will present here some preliminary experimental results characterizing the detector in terms of energy resolution and its ability to separate beta only, gamma only, and coincidence events.

  9. Impact of Monthly Radioxenon Source Time-Resolution on Atmospheric Concentration Predictions

    NASA Astrophysics Data System (ADS)

    Schöppner, Michael; Kalinowski, Martin; Plastino, Wolfango; Budano, Antonio; de Vincenzi, Mario; Ringbom, Anders; Ruggieri, Federico; Schlosser, Clemens

    2014-03-01

    The general characterisation of the global radioxenon background is of interest for the verification of the Comprehensive Nuclear-Test-Ban Treaty. Since the major background sources are only a few isotope production facilities, their source term has an emphasized influence on the worldwide monitoring process of radioxenon. In this work, two different datasets of source terms are applied through atmospheric transport modelling, to estimate the concentration at two radioxenon detection stations in Germany and Sweden. One dataset relies on estimated average annual emissions; the other includes monthly resolved measurements from an isotope production facility in Fleurus, Belgium. The quality of the estimations is then validated by comparing them to the radioxenon concentrations that have been sampled at two monitoring stations over the course of 1 year.

  10. 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.

  11. Application of Artificial Neural Network Modeling to the Analysis of the Automated Radioxenon Sampler-Analyzer State Of Health Sensors OF HEALTH SENSORS

    SciTech Connect

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

    2006-09-19

    The Automated Radioxenon Analyzer/Sampler (ARSA) is a radioxenon gas collection and analysis system operating autonomously under computer control. The ARSA systems are deployed as part of an international network of sensors, with individual stations feeding radioxenon concentration data to a central data center. Because the ARSA instrument is complex and is often deployed in remote areas, it requires constant self-monitoring to verify that it is operating according to specifications. System performance monitoring is accomplished by over 200 internal sensors, with some values reported to the data center. Several sensors are designated as safety sensors that can automatically shut down the ARSA when unsafe conditions arise. In this case, the data center is advised of the shutdown and the cause, so that repairs may be initiated. The other sensors, called state of health (SOH) sensors, also provide valuable information on the functioning of the ARSA and are particularly useful for detecting impending malfunctions before they occur to avoid unscheduled shutdowns. Any of the sensor readings can be displayed by an ARSA Data Viewer, but interpretation of the data is difficult without specialized technical knowledge not routinely available at the data center. Therefore it would be advantageous to have sensor data automatically evaluated for the precursors of malfunctions and the results transmitted to the data center. Artificial Neural Networks (ANN) are a class of data analysis methods that have shown wide application to monitoring systems with large numbers of information inputs, such as the ARSA. In this work supervised and unsupervised ANN methods were applied to ARSA SOH data recording during normal operation of the instrument, and the ability of ANN methods to predict system state is presented.

  12. 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.

  13. Gain calibration of a β/γ coincidence spectrometer for automated radioxenon analysis

    NASA Astrophysics Data System (ADS)

    Reeder, P. L.; Bowyer, T. W.; McIntyre, J. I.; Pitts, W. K.; Ringbom, A.; Johansson, C.

    2004-04-01

    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 β/γ coincidence spectrometer (BGCS). The β spectrometer is a plastic scintillator, manufactured as a cylindrical cell containing the separated xenon sample. This cell is surrounded by the NaI(Tl) γ 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 γ-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. In addition to gain calibration, this procedure determines the resolution of the β detector as a function of energy.

  14. 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

  15. 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

  16. Automatic radioxenon analyzer for CTBT monitoring

    SciTech Connect

    Bowyer, T.W.; Abel, K.H.; Hensley, W.K.

    1996-12-01

    Over the past 3 years, with support from US DOE`s NN-20 Comprehensive Test Ban Treaty (CTBT) R&D program, PNNL has developed and demonstrated a fully automatic analyzer for collecting and measuring the four Xe radionuclides, {sup 131m}Xe(11.9 d), {sup 133m}Xe(2.19 d), {sup 133}Xe (5.24 d), and {sup 135}Xe(9.10 h), in the atmosphere. These radionuclides are important signatures in monitoring for compliance to a CTBT. Activity ratios permit discriminating radioxenon from nuclear detonation and that from nuclear reactor operations, nuclear fuel reprocessing, or medical isotope production and usage. In the analyzer, Xe is continuously and automatically separated from the atmosphere at flow rates of about 7 m{sup 3}/h on sorption bed. Aliquots collected for 6-12 h are automatically analyzed by electron-photon coincidence spectrometry to produce sensitivities in the range of 20-100 {mu}Bq/m{sup 3} of air, about 100-fold better than with reported laboratory-based procedures for short time collection intervals. Spectral data are automatically analyzed and the calculated radioxenon concentrations and raw gamma- ray spectra automatically transmitted to data centers.

  17. 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.

  18. 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.

  19. 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

  20. 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

  1. 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

  2. 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.

  3. 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.

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

    PubMed

    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. PMID:6617033

  5. Radioxenon production through neutron irradiation of stable xenon gas

    SciTech Connect

    Haas, Derek A.; Biegalski, Steven R.; Foltz Biegalski, Kendra M.

    2009-12-01

    The Spectral Deconvolution Analysis Tool (SDAT) software was developed to improve counting statistics and detection limits for nuclear explosion radionuclide measurements. SDAT utilizes spectral deconvolution spectroscopy techniques and can analyze both β-γ coincidence spectra for radioxenon isotopes and high-resolution HPGe spectra from aerosol monitors. The deconvolution algorithm of the SDAT requires a library of β-γ coincidence spectra of individual radioxenon isotopes to determine isotopic ratios in a sample. In order to get experimentally produced spectra of the individual isotopes we have irradiated enriched samples of 130Xe, 132Xe, and 134Xe gas with a neutron beam from the TRIGA reactor at The University of Texas. The samples produced were counted in an Automated Radioxenon Sampler/Analyzer (ARSA) style β-γ coincidence detector. The spectra produced show that this method of radioxenon production yields samples with very high purity of the individual isotopes for 131mXe and 135Xe and a sample with a substantial 133mXe to 133Xe ratio.

  6. 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. PMID:24211671

  7. 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.

  8. Neural-network-based state of health diagnostics for an automated radioxenon sampler/analyzer

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

    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.

  9. 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.

  10. A Multi-Layer Phoswich Radioxenon Detection System, Reporting Period 07/01/07 - 09/30/07

    SciTech Connect

    David M. Hamby

    2007-10-25

    During this quarter, the detector manufacturer (Saint-Gobain) delivered one side of the prototype two-channel phoswich detector (XEPHWICH). Once received, our Digital Pulse Processor (DPP1, 12-bit/100 MHz) was employed to capture and digitally process phoswich pulses from laboratory radioactive sources. Our previous pulse shape discrimination algorithm was modified by utilizing three trapezoidal digital filters. This algorithm provides a two-dimensional plot in which the pulse shapes of interest are classified and then can be well identified. The preliminary experimental results will be presented at the 2007 Informal Xenon Monitoring Workshop. The DPP2 (two-channel, 12-bit/ 250 MHz Digital Pulse Processor) is at the prototyping stage. The analog sections have been designed, prototyped and tested. A 6-layer Printed Circuit Board (PCB) was designed, ordered and delivered. The board components were ordered and are now being assembled and examined for proper functionality. In addition, the related FPGA hardware description code (using VHDL) is under development and simulation. Additionally, our researchers have been studying materials regarding wavelet transforms for incorporation into the project. Wavelet transform is an interesting tool for signal processing; one use for our purpose would be to de-noise the detector signal and to express the signal in a few coefficients for signal compression and increased speed. Light capture efficiency modeling and analysis was performed on the XEPHWICH design. Increased understanding of the modeling software was obtained by the discovery of a bug and successful workaround techniques with the DETECT2000 software. Further modeling and plot generation experience was had by the continued use of CERN's ROOT and GEANT4 software packages. Simulations have been performed to compare the output of points versus planes in light capture efficiency. An additional simulation was made with a runtime that was an order-of-magnitude greater than

  11. 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).

  12. 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

  13. Radioxenon monitoring in Beijing following the Fukushima Daiichi NPP accident.

    PubMed

    Shilian, Wang; Qi, Li; Qinghua, Meng; Zhanying, Chen; Yungang, Zhao; Huijuan, Li; Huaimao, Jia; Yinzhong, Chang; Shujiang, Liu; Xinjun, Zhang; Yuanqing, Fan; Ling, Wan; Yun, Lou

    2013-11-01

    This paper reports the brief process and results of radioxenon monitoring and analysis in Beijing following the Fukushima Daiichi nuclear power plant accident. The accident and release of volatile radionuclides were caused by 9.0 magnitude earthquake and tsunami on March 11, 2011. The maximum concentrations of (133)Xe and (131 m)Xe were in excess of 0.90 Bq.m(-3) and 0.047 Bq.m(-3), respectively. The activity ratio of (131 m)Xe to (133)Xe and the dynamic trend of (133)Xe activity concentration were analyzed. PMID:23601858

  14. 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.

  15. A signal model for GPS

    NASA Technical Reports Server (NTRS)

    Braasch, Michael S.

    1991-01-01

    As the development of GPS continues, there will be an increasing need for a software-centered signal model. This model must accurately generate the observed pseudorange that would typically be encountered. The observed pseudorange varies from the true geometric range because of range measurement errors, which stem from a variety of hardware and environmental factors. In this paper, these errors are classified as either deterministic or random, and, where appropriate, their models are summarized. Of particular interest is the model for Selective Availability, which was derived from actual GPS data. The procedure for determination of this model, known as system identification theory, is briefly outlined. The synthesis of these error sources into the final signal model is given, along with simulation results.

  16. Diabetes: Models, Signals and control

    NASA Astrophysics Data System (ADS)

    Cobelli, C.

    2010-07-01

    Diabetes and its complications impose significant economic consequences on individuals, families, health systems, and countries. The control of diabetes is an interdisciplinary endeavor, which includes significant components of modeling, signal processing and control. Models: first, I will discuss the minimal (coarse) models which describe the key components of the system functionality and are capable of measuring crucial processes of glucose metabolism and insulin control in health and diabetes; then, the maximal (fine-grain) models which include comprehensively all available knowledge about system functionality and are capable to simulate the glucose-insulin system in diabetes, thus making it possible to create simulation scenarios whereby cost effective experiments can be conducted in silico to assess the efficacy of various treatment strategies - in particular I will focus on the first in silico simulation model accepted by FDA as a substitute to animal trials in the quest for optimal diabetes control. Signals: I will review metabolic monitoring, with a particular emphasis on the new continuous glucose sensors, on the crucial role of models to enhance the interpretation of their time-series signals, and on the opportunities that they present for automation of diabetes control. Control: I will 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, I will discuss a modular architecture for building closed-loop control systems, including insulin delivery and patient safety supervision layers.

  17. 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.

  18. 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.

  19. Subsurface mass transport affects the radioxenon signatures that are used to identify clandestine nuclear tests

    NASA Astrophysics Data System (ADS)

    Deinert, M. R.

    2012-12-01

    Underground nuclear tests produce anthropogenic isotopes that provide the only definitive means by which to determine whether a nuclear explosion has taken place. Verification of a suspected test under the Comprehensive Nuclear-Test-Ban Treaty often relies on ratios of radioxenon isotopes. Gas samples are gathered either on-site or off-site with certain ranges of xenon isotope ratios considered to be a signature of a weapons test. It is well established that below ground transport can affect the rate at which Noble gasses will reach the surface. However, the relative abundance of anthropogenic isotopes is has long been assumed to rely solely on fission yield and decay rate. By including in subsurface transport models the effects of mass dependent diffusion, and a time dependent source term for the decay of radioiodine precursors, we show here that this assumption is not true. In fact, certain combinations of geology and atmospheric conditions can alter xenon isotope ratios sufficiently for a weapons test going unconfirmed under the current standards.

  20. Validation studies for brain blood flow assessment by radioxenon tomography

    SciTech Connect

    Rezai, K.; Kirchner, P.T.; Armstrong, C.; Ehrhardt, J.C.; Heistad, D.

    1988-03-01

    A tomographic technique has been used recently for cerebral blood flow measurements with inhaled radioxenon. Based on experiments in a specially developed dynamic phantom and on studies in primates in vivo, we have analyzed the validity of this method for measurements of both regional and total blood flow in the brain. We have also examined the errors introduced into flow computations as a function of changes in such parameters as: rate of xenon input, size of region of interest, magnitude of regional flow rates, and inter-regional flow differences. Our findings indicate a reasonable degree of accuracy for flow measurements in gray matter regions that are 3 cm in diameter or larger, while white matter blood flow is generally overestimated. The accuracy for regional flow assessments degrades as a function of: diminishing region size, increasing inter-regional flow differences, and flow rates in excess of 100 ml/100 g/min. Measurements for brain regions 2 cm or smaller in diameter can be in error by 25-50% as a result of partial volume averaging. Although the technique is not ideal for accurate flow measurements in small regions of the brain, it nevertheless provides a convenient means of assessing perfusion in major vascular territories of the brain in routine clinical applications.

  1. Production of Samples of Individual Radioxenon Isotopes Through Neutron Irradiation of Stable Xenon Gas

    SciTech Connect

    Haas, Derek A.; Biegalski, Steven R.; Foltz Biegalski, Kendra M.

    2008-09-23

    The Spectral Deconvolution Analysis Tool (SDAT) software was developed to improve counting statistics and detection limits for nuclear explosion radionuclide measurements. SDAT utilizes spectral deconvolution spectroscopy techniques and can analyze both β-γ coincidence spectra for radioxenon isotopes and high-resolution HPGe spectra from aerosol monitors. The deconvolution algorithm of the SDAT requires a library of β-γ coincidence spectra of individual radioxenon isotopes to determine isotopic ratios in a sample. In order to get experimentally produced spectra of the individual isotopes we have irradiated enriched samples of 130Xe, 132Xe, and 134Xe gas with a neutron beam from the TRIGA reactor at The University of Texas. The samples produced were counted in an Automated Radioxenon Sampler/Analyzer (ARSA) style β-γ coincidence detector. The spectra produced show that this method of radioxenon production yields samples with very high purity of the individual isotopes for 131mXe and 135Xe and a sample with a substantial 133mXe to 133Xe ratio.

  2. 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.

  3. 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

  4. 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.

  5. Modeling Response Signal and Response Time Data

    ERIC Educational Resources Information Center

    Ratcliff, Roger

    2006-01-01

    The diffusion model (Ratcliff, 1978) and the leaky competing accumulator model (LCA, Usher & McClelland, 2001) were tested against two-choice data collected from the same subjects with the standard response time procedure and the response signal procedure. In the response signal procedure, a stimulus is presented and then, at one of a number of…

  6. Science Signaling Podcast for 7 June 2016: Modeling signal integration.

    PubMed

    Janes, Kevin A; VanHook, Annalisa M

    2016-01-01

    This Podcast features an interview with Kevin Janes, senior author of a Research Article that appears in the 7 June 2016 issue of Science Signaling, about a statistical modeling method that can extract useful information from complex data sets. Cells exist in very complex environments. They are constantly exposed to growth factors, hormones, nutrients, and many other factors that influence cellular behavior. When cells integrate information from multiple stimuli, the resulting output does not necessarily reflect a simple additive effect of the responses to each individual stimulus. Chitforoushzadeh et al employed a statistical modeling approach that maintained the multidimensional nature of the data to analyze the responses of colonic epithelial cells to various combinations of the proinflammatory cytokine TNF, the growth factor EGF, and insulin. As the model predicted, experiments confirmed that insulin suppressed TNF-induced proinflammatory signaling through a mechanism that involved the transcription factor GATA6.Listen to Podcast. PMID:27273095

  7. 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.

  8. A Multi-Layer Phoswich Radioxenon Detection System

    SciTech Connect

    David M. Hamby

    2007-07-01

    Further work was performed in optical modeling of the modified (dual planar) XEPHWICH design. Modeling capabilities and understanding were expanded through the performance of three additional simulations. The efficiency of the entire optical modeling process was increased by developing custom software to interface with both the input and output of the simulation program. Work continues on the design and implementation of the analog portion of the read-out system. This component is being prototyped and is nearing completion. The PCB (printed circuit board) is in its design phase for the two-channel digital pulse processor, necessary for the dual planar XEPHWICH. System components are being selected for the signal processor based on a balance of cost and our expectations of quality. Outside the scope of the grant, but entirely related, we continue to work on developing a source of fission-product xenon gases that will be produced in the OSU TRIGA reactor. The amount of HEU necessary to provide the needed activities of xenon fission products, as well as build-in times for each isotope of importance following irradiation, have been calculated. Irradiation times in the TRIGA have been determined. We've finalized our design of the xenon-fission-product collection chamber and initiated in-house fabrication. PNNL will be supplying the thin foils of enriched uranium necessary for xenon production.

  9. Computational Modeling of Mammalian Signaling Networks

    PubMed Central

    Hughey, Jacob J; Lee, Timothy K; Covert, Markus W

    2011-01-01

    One of the most exciting developments in signal transduction research has been the proliferation of studies in which a biological discovery was initiated by computational modeling. Here we review the major efforts that enable such studies. First, we describe the experimental technologies that are generally used to identify the molecular components and interactions in, and dynamic behavior exhibited by, a network of interest. Next, we review the mathematical approaches that are used to model signaling network behavior. Finally, we focus on three specific instances of “model-driven discovery”: cases in which computational modeling of a signaling network has led to new insights which have been verified experimentally. Signal transduction networks are the bridge between the extraordinarily complex extracellular environment and a carefully orchestrated cellular response. These networks are largely composed of proteins which can interact, move to specific cellular locations, or be modified or degraded. The integration of these events often leads to the activation or inactivation of transcription factors, which then induce or repress the expression of thousands of genes. Because of this critical role in translating environmental cues to cellular behaviors, malfunctioning signaling networks can lead to a variety of pathologies. One example is cancer, in which many of the key genes found to be involved in cancer onset and development are components of signaling pathways [1, 2]. A detailed understanding of the cellular signaling networks underlying such diseases would likely be extremely useful in developing new treatments. However, the complexity of signaling networks is such that their integrated functions cannot be determined without computational simulation. In recent years, mathematical modeling of signal transduction has led to some exciting new findings and biological discoveries. Here, we review the work that has enabled computational modeling of mammalian

  10. 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.

  11. Signalling in an International Cournot Model

    NASA Astrophysics Data System (ADS)

    Ferreira, Fernanda A.; Moreira, Humberto A.; Pinto, Alberto A.

    2009-09-01

    We consider a trade policy model, where the costs of the home firm are private information but can be signaled through the output levels of the firm to a foreign competitor and a home policymaker. We study the influences of the non-homogeneity of the goods and of the uncertainty on the production costs of the home firm in the signalling strategies by the home firm. We show that some results obtained for homogeneous goods are not robust under non-homogeneity.

  12. 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.

  13. 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.

  14. Dose response signal detection under model uncertainty.

    PubMed

    Dette, Holger; Titoff, Stefanie; Volgushev, Stanislav; Bretz, Frank

    2015-12-01

    We investigate likelihood ratio contrast tests for dose response signal detection under model uncertainty, when several competing regression models are available to describe the dose response relationship. The proposed approach uses the complete structure of the regression models, but does not require knowledge of the parameters of the competing models. Standard likelihood ratio test theory is applicable in linear models as well as in nonlinear regression models with identifiable parameters. However, for many commonly used nonlinear dose response models the regression parameters are not identifiable under the null hypothesis of no dose response and standard arguments cannot be used to obtain critical values. We thus derive the asymptotic distribution of likelihood ratio contrast tests in regression models with a lack of identifiability and use this result to simulate the quantiles based on Gaussian processes. The new method is illustrated with a real data example and compared to existing procedures using theoretical investigations as well as simulations. PMID:26228796

  15. Automated modelling of signal transduction networks

    PubMed Central

    2002-01-01

    Background Intracellular signal transduction is achieved by networks of proteins and small molecules that transmit information from the cell surface to the nucleus, where they ultimately effect transcriptional changes. Understanding the mechanisms cells use to accomplish this important process requires a detailed molecular description of the networks involved. Results We have developed a computational approach for generating static models of signal transduction networks which utilizes protein-interaction maps generated from large-scale two-hybrid screens and expression profiles from DNA microarrays. Networks are determined entirely by integrating protein-protein interaction data with microarray expression data, without prior knowledge of any pathway intermediates. In effect, this is equivalent to extracting subnetworks of the protein interaction dataset whose members have the most correlated expression profiles. Conclusion We show that our technique accurately reconstructs MAP Kinase signaling networks in Saccharomyces cerevisiae. This approach should enhance our ability to model signaling networks and to discover new components of known networks. More generally, it provides a method for synthesizing molecular data, either individual transcript abundance measurements or pairwise protein interactions, into higher level structures, such as pathways and networks. PMID:12413400

  16. Development of a phoswich detector system for radioxenon monitoring

    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.

    2009-12-03

    Abstract Measurement of radioactive xenon in the atmosphere is one of several techniques to detect nuclear weapons testing. For high sensitivity, some existing systems use beta/gamma coincidence detection to suppress background, which is very effective, but increases complexity due to separate beta and gamma detectors that require careful calibration and gain matching. In this paper, we will describe the development and evaluation of a simpler detector system, named PhosWatch, consisting of a CsI(Tl)/ BC-404 phoswich well detector, digital readout electronics, and pulse shape analysis algorithms implemented in a digital signal processor on the electronics, and compare its performance to existing multi-detector systems.

  17. 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.

  18. 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.

  19. Signal modeling of turbulence-distorted imagery

    NASA Astrophysics Data System (ADS)

    Young, S. Susan; Driggers, Ronald G.; Krapels, Keith; Espinola, Richard L.; Reynolds, Joseph P.; Cha, Jae

    2009-05-01

    Understanding turbulence effects on wave propagation and imaging systems has been an active research area for more than 50 years. Conventional atmospheric optics methods use statistical models to analyze image degradation effects that are caused by turbulence. In this paper, we intend to understand atmospheric turbulence effects using a deterministic signal processing and imaging theory point of view and modeling. The model simulates the formed imagery by a lens by tracing the optical rays from the target through a band of turbulence. We examine the nature of the turbulence-degraded image, and identify its characteristics as the parameters of the band of turbulence, e.g., its width, angle, and index of refraction, are varied. Image degradation effects due to turbulence, such as image blurring and image dancing, are revealed by this signal modeling. We show that in fact these phenomena can be related not only to phase errors in the frequency domain of the image but also a 2D modulation effect in the image spectrum. Results with simulated and realistic data are provided.

  20. Modeling of surface myoelectric signals--Part I: Model implementation.

    PubMed

    Merletti, R; Lo Conte, L; Avignone, E; Guglielminotti, P

    1999-07-01

    The relationships between the parameters of active motor units (MU's) and the features of surface electromyography (EMG) signals have been investigated using a mathematical model that represents the surface EMG as a summation of contributions from the single muscle fibers. Each MU has parallel fibers uniformly scattered within a cylindrical volume of specified radius embedded in an anisotropic medium. Two action potentials, each modeled as a current tripole, are generated at the neuromuscular junction, propagate in opposite directions and extinguish at the fiber-tendon endings. The neuromuscular junctions and fiber-tendon endings are uniformly scattered within regions of specified width. Muscle fiber conduction velocity and average fiber length to the right and left of the center of the innervation zone are also specified. The signal produced by MU's with different geometries and conduction velocities are superimposed. Monopolar, single differential and double differential signals are computed from electrodes placed in equally spaced locations on the surface of the muscle and are displayed as functions of any of the model's parameters. Spectral and amplitude variables and conduction velocity are estimated from the surface signals and displayed as functions of any of the model's parameters. The influence of fiber-end effects, electrode misalignment, tissue anisotropy, MU's location and geometry are discussed. Part II of this paper will focus on the simulation and interpretation of experimental signals. PMID:10396899

  1. 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.

  2. 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.

  3. 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. PMID:24316684

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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…

  9. Magnetic charge model for 3D MMM signals

    NASA Astrophysics Data System (ADS)

    Pengpeng, Shi; Xiaojing, Zheng

    2016-01-01

    Stress concentration is a major cause of metal structure failures. Based on the metal magnetic memory (MMM) technique, detailed information of stress concentration or defects on ferromagnetic materials can be obtained from the changed magnetic signals. The magnetic charge model of MMM signal is described, and simulations based on this model are performed for a sample with stress-concentration zone or a long elliptical defect. Some basic characteristics produced by present model are coincident with existed experimental measurements. The agreements between simulations and experimental results confirm that the present magnetic charge model can be used as an MMM signal forward technique.

  10. Emergency Locator Transmitter (ELT) signal models for Sarsat

    NASA Astrophysics Data System (ADS)

    Carter, C. R.; Casas, E.; Chung, T.

    1986-04-01

    For three Emergency Locator Translator (ELT) signal generation models for Sarsat, resulting spectra are computed and compared with those of actual signals. The Ideal Coherent Model ELT produces an idealized spectrum which does not exist in practice. The Non-Ideal Coherent Model ELT simulation, which produces a wide range of spectra closely related to actual ELT signals, predicts a design hazard, and suggests a new mandatory design specification. This hazard arises due to an interaction between the modulation and the short-term frequency instability of the carrier oscillator. The Non-Coherent Model demonstrates the degradation caused by not providing continuous operation of the ELT carrier oscillator.

  11. 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.

  12. 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.

  13. Model calibration and uncertainty analysis in signaling networks.

    PubMed

    Heinemann, Tim; Raue, Andreas

    2016-06-01

    For a long time the biggest challenges in modeling cellular signal transduction networks has been the inference of crucial pathway components and the qualitative description of their interactions. As a result of the emergence of powerful high-throughput experiments, it is now possible to measure data of high temporal and spatial resolution and to analyze signaling dynamics quantitatively. In addition, this increase of high-quality data is the basis for a better understanding of model limitations and their influence on the predictive power of models. We review established approaches in signal transduction network modeling with a focus on ordinary differential equation models as well as related developments in model calibration. As central aspects of the calibration process we discuss possibilities of model adaptation based on data-driven parameter optimization and the concomitant objective of reducing model uncertainties. PMID:27085224

  14. Signal Detection Models with Random Participant and Item Effects

    ERIC Educational Resources Information Center

    Rouder, Jeffrey N.; Lu, Jun; Sun, Dongchu; Speckman, Paul; Morey, Richard; Naveh-Benjamin, Moshe

    2007-01-01

    The theory of signal detection is convenient for measuring mnemonic ability in recognition memory paradigms. In these paradigms, randomly selected participants are asked to study randomly selected items. In practice, researchers aggregate data across items or participants or both. The signal detection model is nonlinear; consequently, analysis…

  15. 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

  16. Modelling of Ocean Induced Magnetic Signals in Swarm Satellite Data

    NASA Astrophysics Data System (ADS)

    Einspigel, D.; Velimsky, J.; Martinec, Z.; Sachl, L.

    2015-12-01

    It is well known that the motion of sea water in the Earth's main magnetic field induces the secondary magnetic field which can be measured by satellite, land-based or sea surface magnetic measurements, despite being rather weak, reaching intensities of up to a few nT. We focus on the extraction of ocean induced signals from Swarm satellite data and their interpretation by a comparison with synthetic signals. Results of our modeling and data processing efforts will be presented. We use two ocean circulation models: 1) DEBOT, a barotropic model of ocean tide flow and 2) LSOMG, a baroclinic model of global ocean circulation; and two different approaches for modelling the secondary magnetic field: 1) a single-layer approximation model and 2) a three-dimensional time-domain electromagnetic induction model. Swarm data are analyzed along night-time tracks of the satellites. Only a small amount of the data can be used for the analysis of ocean-induced signals because of permanently present strong signals from the magnetosphere and disruptive effects of polar electrojets. Nevertheless, the extracted signals from selected Swarm data tracks show a relatively good coincidence with predicted signals.

  17. 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

  18. A hemodynamic model for layered BOLD signals.

    PubMed

    Heinzle, Jakob; Koopmans, Peter J; den Ouden, Hanneke E M; Raman, Sudhir; Stephan, Klaas Enno

    2016-01-15

    High-resolution blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) at the sub-millimeter scale has become feasible with recent advances in MR technology. In principle, this would enable the study of layered cortical circuits, one of the fundaments of cortical computation. However, the spatial layout of cortical blood supply may become an important confound at such high resolution. In particular, venous blood draining back to the cortical surface perpendicularly to the layered structure is expected to influence the measured responses in different layers. Here, we present an extension of a hemodynamic model commonly used for analyzing fMRI data (in dynamic causal models or biophysical network models) that accounts for such blood draining effects by coupling local hemodynamics across layers. We illustrate the properties of the model and its inversion by a series of simulations and show that it successfully captures layered fMRI data obtained during a simple visual experiment. We conclude that for future studies of the dynamics of layered neuronal circuits with high-resolution fMRI, it will be pivotal to include effects of blood draining, particularly when trying to infer on the layer-specific connections in cortex--a theme of key relevance for brain disorders like schizophrenia and for theories of brain function such as predictive coding. PMID:26484827

  19. 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

  20. Discrete dynamic modeling of T cell survival signaling networks

    NASA Astrophysics Data System (ADS)

    Zhang, Ranran

    2009-03-01

    Biochemistry-based frameworks are often not applicable for the modeling of heterogeneous regulatory systems that are sparsely documented in terms of quantitative information. As an alternative, qualitative models assuming a small set of discrete states are gaining acceptance. This talk will present a discrete dynamic model of the signaling network responsible for the survival and long-term competence of cytotoxic T cells in the blood cancer T-LGL leukemia. We integrated the signaling pathways involved in normal T cell activation and the known deregulations of survival signaling in leukemic T-LGL, and formulated the regulation of each network element as a Boolean (logic) rule. Our model suggests that the persistence of two signals is sufficient to reproduce all known deregulations in leukemic T-LGL. It also indicates the nodes whose inactivity is necessary and sufficient for the reversal of the T-LGL state. We have experimentally validated several model predictions, including: (i) Inhibiting PDGF signaling induces apoptosis in leukemic T-LGL. (ii) Sphingosine kinase 1 and NFκB are essential for the long-term survival of T cells in T-LGL leukemia. (iii) T box expressed in T cells (T-bet) is constitutively activated in the T-LGL state. The model has identified potential therapeutic targets for T-LGL leukemia and can be used for generating long-term competent CTL necessary for tumor and cancer vaccine development. The success of this model, and of other discrete dynamic models, suggests that the organization of signaling networks has an determining role in their dynamics. Reference: R. Zhang, M. V. Shah, J. Yang, S. B. Nyland, X. Liu, J. K. Yun, R. Albert, T. P. Loughran, Jr., Network Model of Survival Signaling in LGL Leukemia, PNAS 105, 16308-16313 (2008).

  1. Early Warning Signals for Critical Transitions: A Generalized Modeling Approach

    PubMed Central

    Lade, Steven J.; Gross, Thilo

    2012-01-01

    Critical transitions are sudden, often irreversible, changes that can occur in a large variety of complex systems; signals that warn of critical transitions are therefore highly desirable. We propose a new method for early warning signals that integrates multiple sources of information and data about the system through the framework of a generalized model. We demonstrate our proposed approach through several examples, including a previously published fisheries model. We regard our method as complementary to existing early warning signals, taking an approach of intermediate complexity between model-free approaches and fully parameterized simulations. One potential advantage of our approach is that, under appropriate conditions, it may reduce the amount of time series data required for a robust early warning signal. PMID:22319432

  2. Computational modeling approaches in gonadotropin signaling.

    PubMed

    Ayoub, Mohammed Akli; Yvinec, Romain; Crépieux, Pascale; Poupon, Anne

    2016-07-01

    Follicle-stimulating hormone and LH play essential roles in animal reproduction. They exert their function through binding to their cognate receptors, which belong to the large family of G protein-coupled receptors. This recognition at the plasma membrane triggers a plethora of cellular events, whose processing and integration ultimately lead to an adapted biological response. Understanding the nature and the kinetics of these events is essential for innovative approaches in drug discovery. The study and manipulation of such complex systems requires the use of computational modeling approaches combined with robust in vitro functional assays for calibration and validation. Modeling brings a detailed understanding of the system and can also be used to understand why existing drugs do not work as well as expected, and how to design more efficient ones. PMID:27165991

  3. 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.

  4. Signal classification using global dynamical models, Part I: Theory

    SciTech Connect

    Kadtke, J.; Kremliovsky, M.

    1996-06-01

    Detection and classification of signals is one of the principal areas of signal processing, and the utilization of nonlinear information has long been considered as a way of improving performance beyond standard linear (e.g. spectral) techniques. Here, we develop a method for using global models of chaotic dynamical systems theory to define a signal classification processing chain, which is sensitive to nonlinear correlations in the data. We use it to demonstrate classification in high noise regimes (negative SNR), and argue that classification probabilities can be directly computed from ensemble statistics in the model coefficient space. We also develop a modification for non-stationary signals (i.e. transients) using non-autonomous ODEs. In Part II of this paper, we demonstrate the analysis on actual open ocean acoustic data from marine biologics. {copyright} {ital 1996 American Institute of Physics.}

  5. 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...

  6. Comparison of Tropospheric Signal Delay Models for GNSS Error Simulation

    NASA Astrophysics Data System (ADS)

    Kim, Hye-In; Ha, Jihyun; Park, Kwan-Dong; Lee, Sanguk; Kim, Jaehoon

    2009-06-01

    As one of the GNSS error simulation case studies, we computed tropospheric signal delays based on three well-known models (Hopfield, Modified Hopfield and Saastamoinen) and a simple model. In the computation, default meteorological values were used. The result was compared with the GIPSY result, which we assumed as truth. The RMS of a simple model with Marini mapping function was the largest, 31.0 cm. For the other models, the average RMS is 5.2 cm. In addition, to quantify the influence of the accuracy of meteorological information on the signal delay, we did sensitivity analysis of pressure and temperature. As a result, all models used this study were not very sensitive to pressure variations. Also all models, except for the modified Hopfield model, were not sensitive to temperature variations.

  7. Modeling low elevation GPS signal propagation in maritime atmospheric ducts

    NASA Astrophysics Data System (ADS)

    Zhang, Jinpeng; Wu, Zhensen; Wang, Bo; Wang, Hongguang; Zhu, Qinglin

    2012-05-01

    Using the parabolic wave equation (PWE) method, we model low elevation GPS L1 signal propagation in maritime atmospheric ducts. To consider sea surface impedance, roughness, and the effects of earth's curvature, we propose a new initial field model for the GPS PWE split-step solution. On the basis of the comparison between the proposed model and the conventional initial field model for a smooth, perfectly conducting sea surface on a planar earth, we conclude that both the amplitude and phase of the initial field are influenced by surface impedance and roughness, and that the interference behavior between direct and reflected GPS rays is affected by earth's curvature. The performance of the proposed model is illustrated with examples of low elevation GPS L1 signal propagation in three types of ducts: an evaporation duct, a surface-based duct, and an elevated duct. The GPS PWE is numerically implemented using the split-step discrete mixed Fourier transform algorithm to enforce impedance-type boundary conditions at the rough sea surface. Because the GPS signal is right hand circularly polarized, we calculate its power strength by combining the propagation predictions of the horizontally and the vertically polarized components. The effects of the maritime atmospheric ducts on low elevation GPS signal propagation are demonstrated according to the presented examples, and the potential applications of the GPS signals affected by ducts are discussed.

  8. Large-signal numerical and analytical HBT models

    SciTech Connect

    Teeter, D.A.; East, J.R.; Mains, R.K.; Haddad, G.I. )

    1993-05-01

    Several large-signal HBT models are investigated in this paper to determine their usefulness at millimeter-wave frequencies. The most detailed model involves numerically solving moments of the Boltzmann Transport Equation. A description of the numerical model is given along with several simulated results. The numerical model is then used to evaluate two analytical HBT models, the conventional Gummel-Poon model and a modified Ebers-Moll model. It is found that the commonly used Gummel-Poon model exhibits poor agreement with numerical and experimental data at millimeter-wave frequencies due to neglect of transit-time delays. Improved agreement between measured and modeled data result by including transit-time effects in an Ebers-Moll model. This simple model has direct application to millimeter-wave power amplifier and oscillator design. Several measured results are presented to help verify the simple model.

  9. 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

  10. 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

  11. 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.

  12. 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

  13. Model-Based Signal Processing: Correlation Detection With Synthetic Seismograms

    SciTech Connect

    Rodgers, A; Harris, D; Pasyanos, M; Blair, S; Matt, R

    2006-08-30

    Recent applications of correlation methods to seismological problems illustrate the power of coherent signal processing applied to seismic waveforms. Examples of these applications include detection of low amplitude signals buried in ambient noise and cross-correlation of sets of waveforms to form event clusters and accurately measure delay times for event relocation and/or earth structure. These methods rely on the exploitation of the similarity of individual waveforms and have been successfully applied to large sets of empirical observations. However, in cases with little or no empirical event data, such as aseismic regions or exotic event types, correlation methods with observed seismograms will not be possible due to the lack of previously observed similar waveforms. This study uses model-based signals computed for three-dimensional (3D) Earth models to form the basis for correlation detection. Synthetic seismograms are computed for fully 3D models estimated from the Markov Chain Monte-Carlo (MCMC) method. MCMC uses stochastic sampling to fit multiple seismological data sets. Rather than estimate a single ''optimal'' model, MCMC results in a suite of models that sample the model space and incorporates uncertainty through variability of the models. The variability reflects our ignorance of Earth structure, due to limited resolution, data and modeling errors, and produces variability in the seismic waveform response. Model-based signals are combined using a subspace method where the synthetic signals are decomposed into an orthogonal basis by singular-value decomposition (SVD) and the observed waveforms are represented with a linear combination of a sub-set of eigenvectors (signals) associated with the most significant eigenvalues. We have demonstrated the method by modeling long-period (80-10 seconds) regional seismograms for a moderate (M{approx}5) earthquake near the China-North Korea border. Synthetic seismograms are computed with the Spectral Element Method

  14. Modeling of cell signaling pathways in macrophages by semantic networks

    PubMed Central

    Hsing, Michael; Bellenson, Joel L; Shankey, Conor; Cherkasov, Artem

    2004-01-01

    Background Substantial amounts of data on cell signaling, metabolic, gene regulatory and other biological pathways have been accumulated in literature and electronic databases. Conventionally, this information is stored in the form of pathway diagrams and can be characterized as highly "compartmental" (i.e. individual pathways are not connected into more general networks). Current approaches for representing pathways are limited in their capacity to model molecular interactions in their spatial and temporal context. Moreover, the critical knowledge of cause-effect relationships among signaling events is not reflected by most conventional approaches for manipulating pathways. Results We have applied a semantic network (SN) approach to develop and implement a model for cell signaling pathways. The semantic model has mapped biological concepts to a set of semantic agents and relationships, and characterized cell signaling events and their participants in the hierarchical and spatial context. In particular, the available information on the behaviors and interactions of the PI3K enzyme family has been integrated into the SN environment and a cell signaling network in human macrophages has been constructed. A SN-application has been developed to manipulate the locations and the states of molecules and to observe their actions under different biological scenarios. The approach allowed qualitative simulation of cell signaling events involving PI3Ks and identified pathways of molecular interactions that led to known cellular responses as well as other potential responses during bacterial invasions in macrophages. Conclusions We concluded from our results that the semantic network is an effective method to model cell signaling pathways. The semantic model allows proper representation and integration of information on biological structures and their interactions at different levels. The reconstruction of the cell signaling network in the macrophage allowed detailed

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. Signalling Network Construction for Modelling Plant Defence Response

    PubMed Central

    Miljkovic, Dragana; Stare, Tjaša; Mozetič, Igor; Podpečan, Vid; Petek, Marko; Witek, Kamil; Dermastia, Marina; Lavrač, Nada; Gruden, Kristina

    2012-01-01

    Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the Arabidopsis thaliana model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of (component1, reaction, component2) triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at http://ropot.ijs.si/bio3graph/and can be utilised for

  1. 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

  2. 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

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

    PubMed Central

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

    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

  4. 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

  5. Smad Signaling Dynamics: Insights from a Parsimonious Model

    SciTech Connect

    Wiley, H. S.; Shankaran, Harish

    2008-09-09

    The molecular mechanisms that transmit information from cell surface receptors to the nucleus are exceedingly complex; thus, much effort has been expended in developing computational models to understand these processes. A recent study on modeling the nuclear-cytoplasmic shuttling of Smad2-Smad4 complexes in response to transforming growth factor β (TGF-β) receptor activation has provided substantial insight into how this signaling network translates the degree of TGF-β receptor activation (input) into the amount of nuclear Smad2-Smad4 complexes (output). The study addressed this question by combining a simple, mechanistic model with targeted experiments, an approach that proved particularly powerful for exploring the fundamental properties of a complex signaling network. The mathematical model revealed that Smad nuclear-cytoplasmic dynamics enables a proportional, but time-delayed coupling between the input and the output. As a result, the output can faithfully track gradual changes in the input, while the rapid input fluctuations that constitute signaling noise are dampened out.

  6. A logical model provides insights into T cell receptor signaling.

    PubMed

    Saez-Rodriguez, Julio; Simeoni, Luca; Lindquist, Jonathan A; Hemenway, Rebecca; Bommhardt, Ursula; Arndt, Boerge; Haus, Utz-Uwe; Weismantel, Robert; Gilles, Ernst D; Klamt, Steffen; Schraven, Burkhart

    2007-08-01

    Cellular decisions are determined by complex molecular interaction networks. Large-scale signaling networks are currently being reconstructed, but the kinetic parameters and quantitative data that would allow for dynamic modeling are still scarce. Therefore, computational studies based upon the structure of these networks are of great interest. Here, a methodology relying on a logical formalism is applied to the functional analysis of the complex signaling network governing the activation of T cells via the T cell receptor, the CD4/CD8 co-receptors, and the accessory signaling receptor CD28. Our large-scale Boolean model, which comprises 94 nodes and 123 interactions and is based upon well-established qualitative knowledge from primary T cells, reveals important structural features (e.g., feedback loops and network-wide dependencies) and recapitulates the global behavior of this network for an array of published data on T cell activation in wild-type and knock-out conditions. More importantly, the model predicted unexpected signaling events after antibody-mediated perturbation of CD28 and after genetic knockout of the kinase Fyn that were subsequently experimentally validated. Finally, we show that the logical model reveals key elements and potential failure modes in network functioning and provides candidates for missing links. In summary, our large-scale logical model for T cell activation proved to be a promising in silico tool, and it inspires immunologists to ask new questions. We think that it holds valuable potential in foreseeing the effects of drugs and network modifications. PMID:17722974

  7. Ocean acoustic signal processing: A model-based approach

    SciTech Connect

    Candy, J.V. ); Sullivan, E.J. )

    1992-12-01

    A model-based approach is proposed to solve the ocean acoustic signal processing problem that is based on a state-space representation of the normal-mode propagation model. It is shown that this representation can be utilized to spatially propagate both modal (depth) and range functions given the basic parameters (wave numbers, etc.) developed from the solution of the associated boundary value problem. This model is then generalized to the stochastic case where an approximate Gauss--Markov model evolves. The 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, detection and related parameter estimation problems. In particular, a modal/pressure field processor is designed that allows {ital in} {ital situ} recursive estimation of the sound velocity profile. 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 and also form the basis of a sequential detector.

  8. Simulation model for analyzing SPUDI with actuated signals

    SciTech Connect

    Shafahi, Y.; Haghani, A.; Carter, E.C.; Gupta, K.N.V.

    1998-09-01

    A time based microsimulation model is developed for analyzing the traffic operation at single point urban diamond interchanges. Features of the model include actuated signal operation, protected and permitted left turn phasing, right turn phasing with and without right turn on red, traffic in shared lanes, traffic in left turn and right turn storage lanes, car following, lane changing, gap acceptance behavior, primary and secondary queue formation and dissipation. The model accepts geometric, traffic, and signal data in an interactive mode. Input files may also be created separately without going through the interactive session. The model outputs include measures of effectiveness such as stopped delay, total delay, average speed, and maximum and average queue length. These measures of effectiveness are given for each turning movement for each approach, and for the intersection as a whole. The model outputs also show the total green time and the total yellow and all red times assigned by the actuated system to each phase during the simulation time. The model results are compared with the actual data collected in the field.

  9. Modeling of cortical signals using echo state networks

    NASA Astrophysics Data System (ADS)

    Zhou, Hanying; Wang, Yongji; Huang, Jiangshuai

    2009-10-01

    Diverse modeling frameworks have been utilized with the ultimate goal of translating brain cortical signals into prediction of visible behavior. The inputs to these models are usually multidimensional neural recordings collected from relevant regions of a monkey's brain while the outputs are the associated behavior which is typically the 2-D or 3-D hand position of a primate. Here our task is to set up a proper model in order to figure out the move trajectories by input the neural signals which are simultaneously collected in the experiment. In this paper, we propose to use Echo State Networks (ESN) to map the neural firing activities into hand positions. ESN is a newly developed recurrent neural network(RNN) model. Besides its dynamic property and short term memory just as other recurrent neural networks have, it has a special echo state property which endows it with the ability to model nonlinear dynamic systems powerfully. What distinguished it from transitional recurrent neural networks most significantly is its special learning method. In this paper we train this net with a refined version of its typical training method and get a better model.

  10. 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.

  11. 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.

  12. Higgs flavor violation as a signal to discriminate models

    NASA Astrophysics Data System (ADS)

    de Lima, L.; Machado, C. S.; Matheus, R. D.; do Prado, L. A. F.

    2015-11-01

    We consider the Higgs Lepton Flavor Violating process h → τμ, in which CMS found a 2 .5 σ excess of events, from a model independent perspective, and find that it is difficult to generate this operator without also obtaining a sizeable Wilson coefficient for the dipole operators responsible for tau radiative decay, constrained by BABAR to BR( τ → μγ) < 4 .4 × 10-8. We then survey a set of representative models for new physics, to determine which ones are capable of evading this problem. We conclude that, should this measurement persist as a signal, type-III Two Higgs Doublet Models and Higgs portal-like models are favored, while SUSY and Composite Higgs models are unlikely to explain it.

  13. 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. PMID:25333362

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

    NASA Astrophysics Data System (ADS)

    Medina, Leonel E.; Grill, Warren M.

    2014-12-01

    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.

  15. 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

  16. Modeling of acoustic emission signal propagation in waveguides.

    PubMed

    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

  17. 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

  18. An extended car-following model at signalized intersections

    NASA Astrophysics Data System (ADS)

    Yu, Shaowei; Shi, Zhongke

    2014-08-01

    To simulate car-following behaviors better when the traffic light is red, three successive car-following data at a signalized intersection of Jinan in China were collected by using a new proposed data acquisition method and then analyzed to select input variables of the extended car-following model. An extended car-following model considering two leading cars' accelerations was proposed, calibrated and verified with field data obtained on the basis of the full velocity difference model and then a comparative model used for comparative research was also proposed and calibrated in the light of the GM model. The results indicate that the extended car-following model could fit measured data well, and that the fitting precision of the extended model is prior to the comparative model, whose mean absolute error is reduced by 22.83%. Finally a theoretical car-following model considering multiple leading cars' accelerations was put forward which has potential applicable to vehicle automation system and vehicle safety early warning system, and then the linear stability analysis and numerical simulations were conducted to analyze some observed physical features existing in the realistic traffic.

  19. Inverse modeling of GPR signal for estimating soil water content

    NASA Astrophysics Data System (ADS)

    Lambot, S.; van den Bosch, I.; Slob, E. C.; Stockbroeckx, B.; Scheers, B.; Vanclooster, M.

    2003-04-01

    For a large variety of environmental and agricultural applications, the use of ground penetrating radar (GPR) for identifying soil water content is a matter of concern. However, the current state of technology still needs improvements and new developments. Research has focused on the development of an integrated inverse modeling approach including GPR design, GPR signal forward modeling, and GPR signal inversion to estimate simultaneously the depth dependent dielectric constant and electrical conductivity of the shallow subsurface. We propose to use as radar system a stepped frequency continuous wave radar with an ultrawide band dielectric filled TEM horn antenna used in monostatic mode. This configuration is appropriate for real time mapping and allows for a more realistic forward modeling of the radar-antenna-soil system. Forward modeling was based on the exact solution of Maxwell's equations and inversion was formulated by the classical least square problem. Given the inherent complex topography of the objective functions to optimize in electromagnetic inversion problems, we used for the inversion the recently developed global multilevel coordinate search algorithm that we combine sequentially with the local Nelder-Mead simplex algorithm. We applied the method in laboratory conditions on tank filled with sand subject to different water content levels considering a homogeneous water profile. The inverse estimation of the soil dielectric constant was remarkably well in accordance with each water content level and the corresponding theoretical values of the dielectric constant for the sand. Comparison of GPR measurements with estimations from time domain reflectometry (TDR) were also well in close agreement.

  20. Trichotomous noise controlled signal amplification in a generalized Verhulst model

    NASA Astrophysics Data System (ADS)

    Mankin, Romi; Soika, Erkki; Lumi, Neeme

    2014-10-01

    The long-time limit of the probability distribution and statistical moments for a population size are studied by means of a stochastic growth model with generalized Verhulst self-regulation. The effect of variable environment on the carrying capacity of a population is modeled by a multiplicative three-level Markovian noise and by a time periodic deterministic component. Exact expressions for the moments of the population size have been calculated. It is shown that an interplay of a small periodic forcing and colored noise can cause large oscillations of the mean population size. The conditions for the appearance of such a phenomenon are found and illustrated by graphs. Implications of the results on models of symbiotic metapopulations are also discussed. Particularly, it is demonstrated that the effect of noise-generated amplification of an input signal gets more pronounced as the intensity of symbiotic interaction increases.

  1. Stochastic model for detection of signals in noise.

    PubMed

    Klein, Stanley A; Levi, Dennis M

    2009-11-01

    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

  2. An iterative extension of Prony's method for ARMA signal modeling

    NASA Astrophysics Data System (ADS)

    Therrien, Charles W.; Velasco, Carlos H.

    1993-09-01

    A new iterative version of the Prony method is presented and shown to be exceptionally effective in finding ARMA models for acoustic data in the signal domain. The method is based on a quadratic type of gradient algorithm where it is shown that the gradient and Hessian are easily computed from the data. The new algorithm is found experimentally to have excellent convergence behavior. The performance of the algorithm is demonstrated and compared to that of the basic Prony method and to that of the Steiglitz and McBride iterative prefiltering algorithm on some recorded acoustic data.

  3. 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.

  4. Signal simulator model A-111. [signal source for Doppler tracking high data rate receivers

    NASA Technical Reports Server (NTRS)

    Flattau, T.; Mellars, J.

    1974-01-01

    A signal simulator designed to function as a signal source for Doppler tracking high data rate receivers is described. The simulator produces modulated signals whose carrier frequency can be varied between 200 and 900 MHz at rates greater than 20 MHz/sec. The modulation is phase shift keying with data rate up to 300 megabits per second.

  5. 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

  6. 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.

  7. Prostaglandin signaling suppresses beneficial microglial function in Alzheimer's disease models.

    PubMed

    Johansson, Jenny U; Woodling, Nathaniel S; Wang, Qian; Panchal, Maharshi; Liang, Xibin; Trueba-Saiz, Angel; Brown, Holden D; Mhatre, Siddhita D; Loui, Taylor; Andreasson, Katrin I

    2015-01-01

    Microglia, the innate immune cells of the CNS, perform critical inflammatory and noninflammatory functions that maintain normal neural function. For example, microglia clear misfolded proteins, elaborate trophic factors, and regulate and terminate toxic inflammation. In Alzheimer's disease (AD), however, beneficial microglial functions become impaired, accelerating synaptic and neuronal loss. Better understanding of the molecular mechanisms that contribute to microglial dysfunction is an important objective for identifying potential strategies to delay progression to AD. The inflammatory cyclooxygenase/prostaglandin E2 (COX/PGE2) pathway has been implicated in preclinical AD development, both in human epidemiology studies and in transgenic rodent models of AD. Here, we evaluated murine models that recapitulate microglial responses to Aβ peptides and determined that microglia-specific deletion of the gene encoding the PGE2 receptor EP2 restores microglial chemotaxis and Aβ clearance, suppresses toxic inflammation, increases cytoprotective insulin-like growth factor 1 (IGF1) signaling, and prevents synaptic injury and memory deficits. Our findings indicate that EP2 signaling suppresses beneficial microglia functions that falter during AD development and suggest that inhibition of the COX/PGE2/EP2 immune pathway has potential as a strategy to restore healthy microglial function and prevent progression to AD. PMID:25485684

  8. 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.

  9. 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.

  10. 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. PMID:26797793

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. Model for a neural network structure and signal transmission

    NASA Astrophysics Data System (ADS)

    Kotsavasiloglou, C.; Kalampokis, A.; Argyrakis, P.; Baloyannis, S.

    1997-10-01

    We present a model of a neural network that is based on the diffusion-limited-aggregation (DLA) structure from fractal physics. A single neuron is one DLA cluster, while a large number of clusters, in an interconnected fashion, make up the neural network. Using simulation techniques, a signal is randomly generated and traced through its transmission inside the neuron and from neuron to neuron through the synapses. The activity of the entire neural network is monitored as a function of time. The characteristics included in the model contain, among others, the threshold for firing, the excitatory or inhibitory character of the synapse, the synaptic delay, and the refractory period. The system activity results in ``noisy'' time series that exhibit an oscillatory character. Standard power spectra are evaluated and fractal analyses performed, showing that the system is not chaotic, but the varying parameters can be associated with specific values of fractal dimensions. It is found that the network activity is not linear with the system parameters, e.g., with the numbers of active synapses. The details of this behavior may have interesting repercussions from the neurological point of view.

  16. Differential auditory signal processing in an animal model

    NASA Astrophysics Data System (ADS)

    Lim, Dukhwan; Kim, Chongsun; Chang, Sun O.

    2002-05-01

    Auditory evoked responses were collected in male zebra finches (Poephila guttata) to objectively determine differential frequency selectivity. First, the mating call of the animal was recorded and analyzed for its frequency components through the customized program. Then, auditory brainstem responses and cortical responses of each anesthetized animal were routinely recorded in response to tone bursts of 1-8 kHz derived from the corresponding mating call spectrum. From the results, most mating calls showed relatively consistent spectral structures. The upper limit of the spectrum was well under 10 kHz. The peak energy bands were concentrated in the region less than 5 kHz. The assessment of auditory brainstem responses and cortical evoked potentials showed differential selectivity with a series of characteristic scales. This system appears to be an excellent model to investigate complex sound processing and related language behaviors. These data could also be used in designing effective signal processing strategies in auditory rehabilitation devices such as hearing aids and cochlear implants. [Work supported by Brain Science & Engineering Program from Korean Ministry of Science and Technology.

  17. 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.

  18. Transmembrane signaling in Saccharomyces cerevisiae as a model for signaling in metazoans: state of the art after 25 years.

    PubMed

    Engelberg, David; Perlman, Riki; Levitzki, Alexander

    2014-12-01

    In the very first article that appeared in Cellular Signalling, published in its inaugural issue in October 1989, we reviewed signal transduction pathways in Saccharomyces cerevisiae. Although this yeast was already a powerful model organism for the study of cellular processes, it was not yet a valuable instrument for the investigation of signaling cascades. In 1989, therefore, we discussed only two pathways, the Ras/cAMP and the mating (Fus3) signaling cascades. The pivotal findings concerning those pathways undoubtedly contributed to the realization that yeast is a relevant model for understanding signal transduction in higher eukaryotes. Consequently, the last 25 years have witnessed the discovery of many signal transduction pathways in S. cerevisiae, including the high osmotic glycerol (Hog1), Stl2/Mpk1 and Smk1 mitogen-activated protein (MAP) kinase pathways, the TOR, AMPK/Snf1, SPS, PLC1 and Pkr/Gcn2 cascades, and systems that sense and respond to various types of stress. For many cascades, orthologous pathways were identified in mammals following their discovery in yeast. Here we review advances in the understanding of signaling in S. cerevisiae over the last 25 years. When all pathways are analyzed together, some prominent themes emerge. First, wiring of signaling cascades may not be identical in all S. cerevisiae strains, but is probably specific to each genetic background. This situation complicates attempts to decipher and generalize these webs of reactions. Secondly, the Ras/cAMP and the TOR cascades are pivotal pathways that affect all processes of the life of the yeast cell, whereas the yeast MAP kinase pathways are not essential. Yeast cells deficient in all MAP kinases proliferate normally. Another theme is the existence of central molecular hubs, either as single proteins (e.g., Msn2/4, Flo11) or as multisubunit complexes (e.g., TORC1/2), which are controlled by numerous pathways and in turn determine the fate of the cell. It is also apparent that

  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. Isotopic noble gas signatures released from medical isotope production facilities - Simulations and measurements

    SciTech Connect

    Saey, Paul R.; Bowyer, Ted W.; Ringbom, Anders

    2010-09-09

    Journal article on the role that radioxenon isotopes play in confirming whether or not an underground explosion was nuclear in nature. Radioxenon isotopes play a major role in confirming whether or not an underground explosion was nuclear in nature. It is then of key importance to understand the sources of environmental radioxenon to be able to distinguish civil sources from those of a nuclear explosion. Based on several years of measurements, combined with advanced atmospheric transport model results, it was recently shown that the main source of radioxenon observations are strong and regular batch releases from a very limited number of medical isotope production facilities. This paper reviews production processes in different medical isotope facilities during which radioxenon is produced. Radioxenon activity concentrations and isotopic compositions are calculated for six large facilities. The results are compared with calculated signals from nuclear explosions. Further, the outcome is compared and found to be consistent with radioxenon measurements recently performed in and around three of these facilities. Some anomalies in measurements in which {sup 131m}Xe was detected were found and a possible explanation is proposed. It was also calculated that the dose rate of the releases is well below regulatory values. Based on these results, it should be possible to better understand, interpret and verify signals measured in the noble gas measurement systems in the International Monitoring of the Comprehensive Nuclear-Test-Ban Treaty.

  2. Monte Carlo modelling of the low-loss electron signal in scanning electron microscopy and comparison with the BSE signal

    NASA Astrophysics Data System (ADS)

    Bonet, C.; El-Gomati, M. M.; Matthew, J. A. D.; Tear, S. P.

    2010-02-01

    Nanotechnology places increasing demands on techniques for sample characterisation on the sub-100 nm length scale, and the low-loss electron (LLE) signal may provide one possible way of addressing this need. Simulations of the LLE signal from a line-scan across a semiconductor superlattice structure have been performed using two different Monte Carlo models in order to assess their effectiveness in predicting spatial resolution for compositional imaging. Additionally, experimental measurements of LLE data using a detector added to a scanning electron microscope were made to investigate compositional contrast.

  3. Assessing Low Frequency Climate Signals in Global Circulation Models using an Integrated Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Niswonger, R. G.; Huntington, J. L.

    2010-12-01

    Climate signals with periodicities of approximately one decade are pervasive in long-term streamflow records for streams in the western United States that receive significant baseflow. The driver of these signals is unknown but hypotheses have been presented, such as variations in solar input to the Earth, or harmonics of internal (i.e., processes in the ocean and troposphere) forcings like the Pacific Decadal Oscillation (PDO) and El Niño Southern Oscillation (ENSO). Climate signals of about 1 decade are important for several reasons, including their relation to climate extremes (i.e., droughts and floods), and because the drivers of these climate signals are clearly important for projecting future climate conditions. Furthermore, identifying the drivers of these climate signals is important for separating the relative impacts of human production of greenhouse gases on global warming verses external drivers of climate change, such as sunspot cycles. Studies using Global Circulation Models (GCMs) that do not incorporate solar forcings associated with sun spots have identified oscillations of about a decade long in certain model output. However, these oscillations can be difficult to identify in simulated precipitation data due to high frequency variations (less than 1 year) that obscure low frequency (decade) signals. We have found that simulations using an integrated hydrologic model (IHM) called GSFLOW reproduce decade-long oscillations in streamflow when driven by measured precipitation records, and that these oscillations are also present in simulated streamflow when driven by temperature and precipitation data projected by GCMs. Because the IHM acts as a low-pass filter that reveals low frequency signals (i.e. decadal oscillations), they can be used to assess GCMs in terms of their ability to reproduce important low-frequency climate oscillations. We will present results from GSFLOW applied to three basins in the eastern Sierra Nevada driven by 100 years of

  4. 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

  5. Detection of radioxenon in Darwin, Australia following the Fukushima Dai-ichi nuclear power plant accident.

    PubMed

    Orr, Blake; Schöppner, Michael; Tinker, Rick; Plastino, Wolfango

    2013-12-01

    A series of (133)Xe detections in April 2011 made at the Comprehensive Nuclear-Test-Ban Treaty Organisation (CTBTO) International Monitoring System noble gas station in Darwin, Australia, were analysed to determine the most likely source location. Forward and backwards atmospheric transport modelling simulations using FLEXPART were conducted. It was shown that the most likely source location was the Fukushima Dai-ichi nuclear power plant accident. Other potential sources in the southern hemisphere were analysed, including the Australian Nuclear Science and Technology Organisation (ANSTO) radiopharmaceutical facility, but it was shown that sources originating from these locations were highly unlikely to be the source of the observed (133)Xe Darwin detections. PMID:23933085

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

    PubMed

    Wu, Hau-Tieng; Wu, Han-Kuei; 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

  7. 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

  8. 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. PMID:26520127

  9. 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.

  10. 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…

  11. Representation of fluctuation features in pathological knee joint vibroarthrographic signals using kernel density modeling method.

    PubMed

    Yang, Shanshan; Cai, Suxian; Zheng, Fang; Wu, Yunfeng; Liu, Kaizhi; Wu, Meihong; Zou, Quan; Chen, Jian

    2014-10-01

    This article applies advanced signal processing and computational methods to study the subtle fluctuations in knee joint vibroarthrographic (VAG) signals. Two new features are extracted to characterize the fluctuations of VAG signals. The fractal scaling index parameter is computed using the detrended fluctuation analysis algorithm to describe the fluctuations associated with intrinsic correlations in the VAG signal. The averaged envelope amplitude feature measures the difference between the upper and lower envelopes averaged over an entire VAG signal. Statistical analysis with the Kolmogorov-Smirnov test indicates that both of the fractal scaling index (p=0.0001) and averaged envelope amplitude (p=0.0001) features are significantly different between the normal and pathological signal groups. The bivariate Gaussian kernels are utilized for modeling the densities of normal and pathological signals in the two-dimensional feature space. Based on the feature densities estimated, the Bayesian decision rule makes better signal classifications than the least-squares support vector machine, with the overall classification accuracy of 88% and the area of 0.957 under the receiver operating characteristic (ROC) curve. Such VAG signal classification results are better than those reported in the state-of-the-art literature. The fluctuation features of VAG signals developed in the present study can provide useful information on the pathological conditions of degenerative knee joints. Classification results demonstrate the effectiveness of the kernel feature density modeling method for computer-aided VAG signal analysis. PMID:25096412

  12. Downregulating Hedgehog Signaling Reduces Renal Cystogenic Potential of Mouse Models

    PubMed Central

    Talbott, George C.; Turbe-Doan, Annick; Jacobs, Damon T.; Schonfeld, Michael P.; Silva, Luciane M.; Chatterjee, Anindita; Prysak, Mary; Allard, Bailey A.; Beier, David R.

    2014-01-01

    Renal cystic diseases are a leading cause of renal failure. Mutations associated with renal cystic diseases reside in genes encoding proteins that localize to primary cilia. These cystoproteins can disrupt ciliary structure or cilia-mediated signaling, although molecular mechanisms connecting cilia function to renal cystogenesis remain unclear. The ciliary gene, Thm1(Ttc21b), negatively regulates Hedgehog signaling and is most commonly mutated in ciliopathies. We report that loss of murine Thm1 causes cystic kidney disease, with persistent proliferation of renal cells, elevated cAMP levels, and enhanced expression of Hedgehog signaling genes. Notably, the cAMP-mediated cystogenic potential of Thm1-null kidney explants was reduced by genetically deleting Gli2, a major transcriptional activator of the Hedgehog pathway, or by culturing with small molecule Hedgehog inhibitors. These Hedgehog inhibitors acted independently of protein kinase A and Wnt inhibitors. Furthermore, simultaneous deletion of Gli2 attenuated the renal cystic disease associated with deletion of Thm1. Finally, transcripts of Hedgehog target genes increased in cystic kidneys of two other orthologous mouse mutants, jck and Pkd1, and Hedgehog inhibitors reduced cystogenesis in jck and Pkd1 cultured kidneys. Thus, enhanced Hedgehog activity may have a general role in renal cystogenesis and thereby present a novel therapeutic target. PMID:24700869

  13. 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

  14. 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

  15. Radioxenon spiked air

    DOE PAGESBeta

    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. Supervised Single-Channel Speech Separation via Sparse Decomposition Using Periodic Signal Models

    NASA Astrophysics Data System (ADS)

    Nakashizuka, Makoto; Okumura, Hiroyuki; Iiguni, Youji

    In this paper, we propose a method for supervised single-channel speech separation through sparse decomposition using periodic signal models. The proposed separation method employs sparse decomposition, which decomposes a signal into a set of periodic signals under a sparsity penalty. In order to achieve separation through sparse decomposition, the decomposed periodic signals have to be assigned to the corresponding sources. For the assignment of the periodic signal, we introduce clustering using a K-means algorithm to group the decomposed periodic signals into as many clusters as the number of speakers. After the clustering, each cluster is assigned to its corresponding speaker using preliminarily learnt codebooks. Through separation experiments, we compare our method with MaxVQ, which performs separation on the frequency spectrum domain. The experimental results in terms of signal-to-distortion ratio show that the proposed sparse decomposition method is comparable to the frequency domain approach and has less computational costs for assignment of speech components.

  18. Signal-Response Modeling of Partial Hormone Feedback Networks

    PubMed Central

    Johnson, Michael L.; Veldhuis, Paula P.; Evans, William S.

    2009-01-01

    Background Endocrine feedback control networks are typically complex and contain multiple hormones, pools, and compartments. The hormones themselves commonly interact via multiple pathways and targets within the networks, and a complete description of such relationships may involve hundreds of parameters. In addition, it is often difficult, if not impossible, to collect experimental data pertaining to every component within the network. Therefore, the complete simultaneous analysis of such networks is challenging. Nevertheless, an understanding of these networks is critical for furthering our knowledge of hormonal regulation in both physiologic and pathophysiologic conditions. Methods We propose a novel approach for the analysis of dose-response relationships of subsets of hormonal feedback networks. The algorithm and signal-response quantification (SRQuant) software is based on convolution integrals, and tests whether several discretely measured input signals can be individually delayed, spread in time, transformed, combined, and discretely convolved with an elimination function to predict the time course of the concentration of an output hormone. Signal-response quantification is applied to examples from the endocrine literature to demonstrate its applicability to the analysis of the different endocrine networks. Results In one example, SRQuant determines the dose-response relationship by which one hormone regulates another, highlighting its advantages over other traditional methods. In a second example, for the first time (to the best of our knowledge), we show that the secretion of glucagon may be jointly controlled by the β and the δ cells. Conclusion We have developed a novel convolution integral-based approach, algorithm, and software (SRQuant) for the analysis of dose-response relationships within subsets of complex endocrine feedback control networks. PMID:20046649

  19. Newly Constructed Network Models of Different WNT Signaling Cascades Applied to Breast Cancer Expression Data

    PubMed Central

    Kramer, Frank; Pukrop, Tobias; Beißbarth, Tim; Bleckmann, Annalen

    2015-01-01

    Introduction WNT signaling is a complex process comprising multiple pathways: the canonical β-catenin-dependent pathway and several alternative non-canonical pathways that act in a β-catenin-independent manner. Representing these intricate signaling mechanisms through bioinformatic approaches is challenging. Nevertheless, a simplified but reliable bioinformatic WNT pathway model is needed, which can be further utilized to decipher specific WNT activation states within e.g. high-throughput data. Results In order to build such a model, we collected, parsed, and curated available WNT signaling knowledge from different pathway databases. The data were assembled to construct computationally suitable models of different WNT signaling cascades in the form of directed signaling graphs. This resulted in four networks representing canonical WNT signaling, non-canonical WNT signaling, the inhibition of canonical WNT signaling and the regulation of WNT signaling pathways, respectively. Furthermore, these networks were integrated with microarray and RNA sequencing data to gain deeper insight into the underlying biology of gene expression differences between MCF-7 and MDA-MB-231 breast cancer cell lines, representing weakly and highly invasive breast carcinomas, respectively. Differential genes up-regulated in the MDA-MB-231 compared to the MCF-7 cell line were found to display enrichment in the gene set originating from the non-canonical network. Moreover, we identified and validated differentially regulated modules representing canonical and non-canonical WNT pathway components specific for the aggressive basal-like breast cancer subtype. Conclusions In conclusion, we demonstrated that these newly constructed WNT networks reliably reflect distinct WNT signaling processes. Using transcriptomic data, we shaped these networks into comprehensive modules of the genes implicated in the aggressive basal-like breast cancer subtype and demonstrated that non-canonical WNT signaling is

  20. Semi-physical neural modeling for linear signal restoration.

    PubMed

    Bourgois, Laurent; Roussel, Gilles; Benjelloun, Mohammed

    2013-02-01

    This paper deals with the design methodology of an Inverse Neural Network (INN) model. The basic idea is to carry out a semi-physical model gathering two types of information: the a priori knowledge of the deterministic rules which govern the studied system and the observation of the actual conduct of this system obtained from experimental data. This hybrid model is elaborated by being inspired by the mechanisms of a neuromimetic network whose structure is constrained by the discrete reverse-time state-space equations. In order to validate the approach, some tests are performed on two dynamic models. The first suggested model is a dynamic system characterized by an unspecified r-order Ordinary Differential Equation (ODE). The second one concerns in particular the mass balance equation for a dispersion phenomenon governed by a Partial Differential Equation (PDE) discretized on a basic mesh. The performances are numerically analyzed in terms of generalization, regularization and training effort. PMID:23275139

  1. 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.

  2. Interference of Overlapping Insect Vibratory Communication Signals: An Eushistus heros Model

    PubMed Central

    Čokl, Andrej; Laumann, Raul Alberto; Žunič Kosi, Alenka; Blassioli-Moraes, Maria Carolina; Virant-Doberlet, Meta; Borges, Miguel

    2015-01-01

    Plants limit the range of insect substrate-borne vibratory communication by their architecture and mechanical properties that change transmitted signal time, amplitude and frequency characteristics. Stinkbugs gain higher signal-to-noise ratio and increase communication distance by emitting narrowband low frequency vibratory signals that are tuned with transmission properties of plants. The objective of the present study was to investigate hitherto overlooked consequences of duetting with mutually overlapped narrowband vibratory signals. The overlapped vibrations of the model stinkbug species Eushistus heros, produced naturally or induced artificially on different plants, have been analysed. They represent female and male strategies to preserve information within a complex masked signal. The brown stinkbugs E. heros communicate with species and gender specific vibratory signals that constitute characteristic duets in the calling, courtship and rivalry phases of mating behaviour. The calling female pulse overlaps the male vibratory response when the latency of the latter is shorter than the duration of the female triggering signal or when the male response does not inhibit the following female pulse. Overlapping of signals induces interference that changes their amplitude pattern to a sequence of regularly repeated pulses in which their duration and the difference between frequencies of overlapped vibrations are related inversely. Interference does not occur in overlapped narrow band female calling pulses and broadband male courtship pulse trains. In a duet with overlapped signals females and males change time parameters and increase the frequency difference between signals by changing the frequency level and frequency modulation pattern of their calls. PMID:26098637

  3. Interference of Overlapping Insect Vibratory Communication Signals: An Eushistus heros Model.

    PubMed

    Čokl, Andrej; Laumann, Raul Alberto; Žunič Kosi, Alenka; Blassioli-Moraes, Maria Carolina; Virant-Doberlet, Meta; Borges, Miguel

    2015-01-01

    Plants limit the range of insect substrate-borne vibratory communication by their architecture and mechanical properties that change transmitted signal time, amplitude and frequency characteristics. Stinkbugs gain higher signal-to-noise ratio and increase communication distance by emitting narrowband low frequency vibratory signals that are tuned with transmission properties of plants. The objective of the present study was to investigate hitherto overlooked consequences of duetting with mutually overlapped narrowband vibratory signals. The overlapped vibrations of the model stinkbug species Eushistus heros, produced naturally or induced artificially on different plants, have been analysed. They represent female and male strategies to preserve information within a complex masked signal. The brown stinkbugs E. heros communicate with species and gender specific vibratory signals that constitute characteristic duets in the calling, courtship and rivalry phases of mating behaviour. The calling female pulse overlaps the male vibratory response when the latency of the latter is shorter than the duration of the female triggering signal or when the male response does not inhibit the following female pulse. Overlapping of signals induces interference that changes their amplitude pattern to a sequence of regularly repeated pulses in which their duration and the difference between frequencies of overlapped vibrations are related inversely. Interference does not occur in overlapped narrow band female calling pulses and broadband male courtship pulse trains. In a duet with overlapped signals females and males change time parameters and increase the frequency difference between signals by changing the frequency level and frequency modulation pattern of their calls. PMID:26098637

  4. 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.

  5. 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.

  6. Model Predictive Control for Automobile Ecological Driving Using Traffic Signal Information

    NASA Astrophysics Data System (ADS)

    Yamaguchi, Daisuke; Kamal, M. A. S.; Mukai, Masakazu; Kawabe, Taketoshi

    This paper presents development of a control system for ecological driving of an automobile. Prediction using traffic signal information is considered to improve the fuel economy. It is assumed that the automobile receives traffic signal information from Intelligent Transportation Systems (ITS). Model predictive control is used to calculate optimal vehicle control inputs using traffic signal information. The performance of the proposed method was analyzed through computer simulation results. It was observed that fuel economy was improved compared with driving of a typical human driving model.

  7. A structured approach for the engineering of biochemical network models, illustrated for signalling pathways.

    PubMed

    Breitling, Rainer; Gilbert, David; Heiner, Monika; Orton, Richard

    2008-09-01

    Quantitative models of biochemical networks (signal transduction cascades, metabolic pathways, gene regulatory circuits) are a central component of modern systems biology. Building and managing these complex models is a major challenge that can benefit from the application of formal methods adopted from theoretical computing science. Here we provide a general introduction to the field of formal modelling, which emphasizes the intuitive biochemical basis of the modelling process, but is also accessible for an audience with a background in computing science and/or model engineering. We show how signal transduction cascades can be modelled in a modular fashion, using both a qualitative approach--qualitative Petri nets, and quantitative approaches--continuous Petri nets and ordinary differential equations (ODEs). We review the major elementary building blocks of a cellular signalling model, discuss which critical design decisions have to be made during model building, and present a number of novel computational tools that can help to explore alternative modular models in an easy and intuitive manner. These tools, which are based on Petri net theory, offer convenient ways of composing hierarchical ODE models, and permit a qualitative analysis of their behaviour. We illustrate the central concepts using signal transduction as our main example. The ultimate aim is to introduce a general approach that provides the foundations for a structured formal engineering of large-scale models of biochemical networks. PMID:18573813

  8. Small-signal modelling and control of photovoltaic based water pumping system.

    PubMed

    Ghosh, Arun; Ganesh Malla, Siva; Narayan Bhende, Chandrasekhar

    2015-07-01

    This paper studies small-signal modelling and control design for a photovoltaic (PV) based water pumping system without energy storage. First, the small-signal model is obtained and then, using this model, two proportional-integral (PI) controllers, where one controller is used to control the dc-link voltage and the other one to control the speed of induction motor, are designed to meet control goals such as settling time and peak overshoot of the closed loop responses. The loop robustness of the design is also studied. For a given set of system parameters, simulations are carried out to validate the modelling and the control design. PMID:25707717

  9. 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.

  10. 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

  11. Microeconomic co-evolution model for financial technical analysis signals

    NASA Astrophysics Data System (ADS)

    Rotundo, G.; Ausloos, M.

    2007-01-01

    Technical analysis (TA) has been used for a long time before the availability of more sophisticated instruments for financial forecasting in order to suggest decisions on the basis of the occurrence of data patterns. Many mathematical and statistical tools for quantitative analysis of financial markets have experienced a fast and wide growth and have the power for overcoming classical TA methods. This paper aims to give a measure of the reliability of some information used in TA by exploring the probability of their occurrence within a particular microeconomic agent-based model of markets, i.e., the co-evolution Bak-Sneppen model originally invented for describing species population evolutions. After having proved the practical interest of such a model in describing financial index so-called avalanches, in the prebursting bubble time rise, the attention focuses on the occurrence of trend line detection crossing of meaningful barriers, those that give rise to some usual TA strategies. The case of the NASDAQ crash of April 2000 serves as an illustration.

  12. 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

  13. Audibility of time-varying signals in time-varying backgrounds: Model and data

    NASA Astrophysics Data System (ADS)

    Moore, Brian C. J.; Glasberg, Brian R.

    2001-05-01

    We have described a model for calculating the partial loudness of a steady signal in the presence of a steady background sound [Moore et al., J. Audio Eng. Soc. 45, 224-240 (1997)]. We have also described a model for calculating the loudness of time-varying signals [B. R. Glasberg and B. C. J. Moore, J. Audio Eng. Soc. 50, 331-342 (2002)]. These two models have been combined to allow calculation of the partial loudness of a time-varying signal in the presence of a time-varying background. To evaluate the model, psychometric functions for the detection of a variety of time-varying signals (e.g., telephone ring tones) have been measured in a variety of background sounds sampled from everyday listening situations, using a two-alternative forced-choice task. The different signals and backgrounds were interleaved, to create stimulus uncertainty, as would occur in everyday life. The data are used to relate the detectability index, d', to the calculated partial loudness. In this way, the model can be used to predict the detectability of any signal, based on its calculated partial loudness. [Work supported by MRC (UK) and by Nokia.

  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. The continuous Sir Philip Sidney game: a simple model of biological signalling.

    PubMed

    Johnstone, R A; Grafen, A

    1992-05-21

    An analysis of Maynard Smith's two-player, ESS model of biological signalling, the "Sir Philip Sidney game", is presented. The stable strategies of the players in this game are shown to satisfy the conditions of Zahavi's handicap principle. At equilibrium, signals are honest, costly, and costly in a way that is related to the true quality revealed. Further analysis reveals that the level of cost required to maintain stability is inversely related to the degree of relatedness between the players. It therefore seems likely that stable biological signalling systems will feature lower signalling costs when communication occurs between relatives. A three-player, extended version of the model is investigated, in which signals are passed via an intermediate, or "messenger". It is shown that this destabilizes the signalling system, and leads to increased signalling costs. This result suggests that "kin conflict" theories of the evolution of the endosperm in flowering plants require further refinement. The introduction of a novel resource acquisition tissue, which mediates parent-offspring interaction during development, cannot be assumed to limit parent-offspring conflict simply because it carries an extra copy of the maternally inherited genes. The ability to add such complications to the Sir Philip Sidney game and still obtain solutions makes it a very useful modelling tool. PMID:1640723

  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. Stochasticity in the signalling network of a model microbe

    NASA Astrophysics Data System (ADS)

    Bischofs, Ilka; Foley, Jonathan; Battenberg, Eric; Fontaine-Bodin, Lisa; Price, Gavin; Wolf, Denise; Arkin, Adam

    2007-03-01

    The soil dwelling bacterium Bacillus subtilis is an excellent model organism for studying stochastic stress response induction in an isoclonal population. Subjected to the same stressor cells undergo different cell fates, including sporulation, competence, degradative enzyme synthesis and motility. For example, under conditions of nutrient deprivation and high cell density only a portion of the cell population forms an endospore. Here we use a combined experimental and theoretical approach to study stochastic sporulation induction in Bacillus subtilis. Using several fluorescent reporter strains we apply time lapse fluorescent microscopy in combination with quantitative image analysis to study cell fate progression on a single cell basis and elucidate key noise generators in the underlying cellular network.

  19. Classification of signaling proteins based on molecular star graph descriptors using Machine Learning models.

    PubMed

    Fernandez-Lozano, Carlos; Cuiñas, Rubén F; Seoane, José A; Fernández-Blanco, Enrique; Dorado, Julian; Munteanu, Cristian R

    2015-11-01

    Signaling proteins are an important topic in drug development due to the increased importance of finding fast, accurate and cheap methods to evaluate new molecular targets involved in specific diseases. The complexity of the protein structure hinders the direct association of the signaling activity with the molecular structure. Therefore, the proposed solution involves the use of protein star graphs for the peptide sequence information encoding into specific topological indices calculated with S2SNet tool. The Quantitative Structure-Activity Relationship classification model obtained with Machine Learning techniques is able to predict new signaling peptides. The best classification model is the first signaling prediction model, which is based on eleven descriptors and it was obtained using the Support Vector Machines-Recursive Feature Elimination (SVM-RFE) technique with the Laplacian kernel (RFE-LAP) and an AUROC of 0.961. Testing a set of 3114 proteins of unknown function from the PDB database assessed the prediction performance of the model. Important signaling pathways are presented for three UniprotIDs (34 PDBs) with a signaling prediction greater than 98.0%. PMID:26297890

  20. 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.

  1. 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.

  2. 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.

  3. A quantitative confidence signal detection model: 1. Fitting psychometric functions.

    PubMed

    Yi, Yongwoo; Merfeld, Daniel M

    2016-04-01

    Perceptual thresholds are commonly assayed in the laboratory and clinic. When precision and accuracy are required, thresholds are quantified by fitting a psychometric function to forced-choice data. The primary shortcoming of this approach is that it typically requires 100 trials or more to yield accurate (i.e., small bias) and precise (i.e., small variance) psychometric parameter estimates. We show that confidence probability judgments combined with a model of confidence can yield psychometric parameter estimates that are markedly more precise and/or markedly more efficient than conventional methods. Specifically, both human data and simulations show that including confidence probability judgments for just 20 trials can yield psychometric parameter estimates that match the precision of those obtained from 100 trials using conventional analyses. Such an efficiency advantage would be especially beneficial for tasks (e.g., taste, smell, and vestibular assays) that require more than a few seconds for each trial, but this potential benefit could accrue for many other tasks. PMID:26763777

  4. 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

  5. Estimation of ECG signal of closely separated bipolar electrodes using thorax models.

    PubMed

    Puurtinen, M; Hyttinen, J; Viik, J; Kauppinen, P; Malmivuo, J

    2004-01-01

    New miniaturized portable ECG measuring devices may require reduced electrode size and distance. Modeling tools can be useful in predicting the behavior of electric field between electrodes. This work introduces a project where the effect of interelectrode distance (IED) of ECG precordial electrodes was studied with a model of the thorax as a volume conductor and with body surface potential map (BSPM) data. The objective was to study how the IED affects the signal strength and how well the modeling data corresponds to the clinical data. 2D and 3D finite difference method (FDM) torso models based on visible human man data were used. On these FDM models, the electrodes9 sensitivity to measure the electric field of the heart was derived. The results were compared to clinical 120 channel BSPM data. It was found out that reducing the IED obviously decreases the signal strength. According to the clinical data, the magnitude of this effect depends on the electrode location. This study indicates that modeling the volume conductor can predict the signal strength obtained with given electrode configurations. 3D modeling is more accurate in predicting the signal strength from clinical recordings; however, also simple and fast 2D modeling results show comparable values. PMID:17271798

  6. 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...

  7. 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

  8. 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

  9. 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

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

    PubMed

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

    2015-08-01

    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. PMID:26737782

  11. 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

  12. 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

    2015-01-01

    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 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. PMID:25898351

  13. 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. PMID:23226239

  14. 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

  15. 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.

  16. 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. PMID:26559623

  17. Isotopic noble gas signatures released from medical isotope production facilities--simulations and measurements.

    PubMed

    Saey, Paul R J; Bowyer, Theodore W; Ringbom, Anders

    2010-09-01

    Radioxenon isotopes play a major role in confirming whether or not an underground explosion was nuclear in nature. It is then of key importance to understand the sources of environmental radioxenon to be able to distinguish civil sources from those of a nuclear explosion. Based on several years of measurements, combined with advanced atmospheric transport model results, it was recently shown that the main source of radioxenon observations are strong and regular batch releases from a very limited number of medical isotope production facilities. This paper reviews production processes in different medical isotope facilities during which radioxenon is produced. Radioxenon activity concentrations and isotopic compositions are calculated for six large facilities. The results are compared with calculated signals from nuclear explosions. Further, the outcome is compared and found to be consistent with radioxenon measurements recently performed in and around three of these facilities. Some anomalies in measurements in which (131m)Xe was detected were found and a possible explanation is proposed. It was also calculated that the dose rate of the releases is well below regulatory values. Based on these results, it should be possible to better understand, interpret and verify signals measured in the noble gas measurement systems in the International Monitoring of the Comprehensive Nuclear-Test-Ban Treaty. PMID:20447828

  18. 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.

  19. Multiple logistic regression model of signalling practices of drivers on urban highways

    NASA Astrophysics Data System (ADS)

    Puan, Othman Che; Ibrahim, Muttaka Na'iya; Zakaria, Rozana

    2015-05-01

    Giving signal is a way of informing other road users, especially to the conflicting drivers, the intention of a driver to change his/her movement course. Other users are exposed to hazard situation and risks of accident if the driver who changes his/her course failed to give signal as required. This paper describes the application of logistic regression model for the analysis of driver's signalling practices on multilane highways based on possible factors affecting driver's decision such as driver's gender, vehicle's type, vehicle's speed and traffic flow intensity. Data pertaining to the analysis of such factors were collected manually. More than 2000 drivers who have performed a lane changing manoeuvre while driving on two sections of multilane highways were observed. Finding from the study shows that relatively a large proportion of drivers failed to give any signals when changing lane. The result of the analysis indicates that although the proportion of the drivers who failed to provide signal prior to lane changing manoeuvre is high, the degree of compliances of the female drivers is better than the male drivers. A binary logistic model was developed to represent the probability of a driver to provide signal indication prior to lane changing manoeuvre. The model indicates that driver's gender, type of vehicle's driven, speed of vehicle and traffic volume influence the driver's decision to provide a signal indication prior to a lane changing manoeuvre on a multilane urban highway. In terms of types of vehicles driven, about 97% of motorcyclists failed to comply with the signal indication requirement. The proportion of non-compliance drivers under stable traffic flow conditions is much higher than when the flow is relatively heavy. This is consistent with the data which indicates a high degree of non-compliances when the average speed of the traffic stream is relatively high.

  20. 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.

  1. 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).

  2. 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

  3. 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.

  4. 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

  5. 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

  6. Finite Element Modeling of Pulsed Eddy Current Signals from Aluminum Plates Having Defects

    NASA Astrophysics Data System (ADS)

    Babbar, V. K.; Harlley, D.; Krause, T. W.

    2010-02-01

    The pulsed eddy current technique is being developed for detection of flaws located at depth within conducting structures. The present work investigates the pulsed eddy current response from flat-plate conductors having defects by using finite element modeling. Modeling revealed the optimum probe position with respect to a multilayer defect geometry. Models were also produced to investigate the effect of changing some probe parameters on pickup signal and penetration depth.

  7. The Dark Side of EDX Tomography: Modeling Detector Shadowing to Aid 3D Elemental Signal Analysis.

    PubMed

    Yeoh, Catriona S M; Rossouw, David; Saghi, Zineb; Burdet, Pierre; Leary, Rowan K; Midgley, Paul A

    2015-06-01

    A simple model is proposed to account for the loss of collected X-ray signal by the shadowing of X-ray detectors in the scanning transmission electron microscope. The model is intended to aid the analysis of three-dimensional elemental data sets acquired using energy-dispersive X-ray tomography methods where shadow-free specimen holders are unsuitable or unavailable. The model also provides a useful measure of the detection system geometry. PMID:25790959

  8. 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

  9. Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling

    PubMed Central

    Fröhlich, Holger; Bahamondez, Gloria; Götschel, Frank; Korf, Ulrike

    2015-01-01

    Aberrant activation of sonic Hegdehog (SHH) signaling has been found to disrupt cellular differentiation in many human cancers and to increase proliferation. The SHH pathway is known to cross-talk with EGFR dependent signaling. Recent studies experimentally addressed this interplay in Daoy cells, which are presumable a model system for medulloblastoma, a highly malignant brain tumor that predominately occurs in children. Currently ongoing are several clinical trials for different solid cancers, which are designed to validate the clinical benefits of targeting the SHH in combination with other pathways. This has motivated us to investigate interactions between EGFR and SHH dependent signaling in greater depth. To our knowledge, there is no mathematical model describing the interplay between EGFR and SHH dependent signaling in medulloblastoma so far. Here we come up with a fully probabilistic approach using Dynamic Bayesian Networks (DBNs). To build our model, we made use of literature based knowledge describing SHH and EGFR signaling and integrated gene expression (Illumina) and cellular location dependent time series protein expression data (Reverse Phase Protein Arrays). We validated our model by sub-sampling training data and making Bayesian predictions on the left out test data. Our predictions focusing on key transcription factors and p70S6K, showed a high level of concordance with experimental data. Furthermore, the stability of our model was tested by a parametric bootstrap approach. Stable network features were in agreement with published data. Altogether we believe that our model improved our understanding of the interplay between two highly oncogenic signaling pathways in Daoy cells. This may open new perspectives for the future therapy of Hedghog/EGF-dependent solid tumors. PMID:26571415

  10. Dynamic Bayesian Network Modeling of the Interplay between EGFR and Hedgehog Signaling.

    PubMed

    Fröhlich, Holger; Bahamondez, Gloria; Götschel, Frank; Korf, Ulrike

    2015-01-01

    Aberrant activation of sonic Hegdehog (SHH) signaling has been found to disrupt cellular differentiation in many human cancers and to increase proliferation. The SHH pathway is known to cross-talk with EGFR dependent signaling. Recent studies experimentally addressed this interplay in Daoy cells, which are presumable a model system for medulloblastoma, a highly malignant brain tumor that predominately occurs in children. Currently ongoing are several clinical trials for different solid cancers, which are designed to validate the clinical benefits of targeting the SHH in combination with other pathways. This has motivated us to investigate interactions between EGFR and SHH dependent signaling in greater depth. To our knowledge, there is no mathematical model describing the interplay between EGFR and SHH dependent signaling in medulloblastoma so far. Here we come up with a fully probabilistic approach using Dynamic Bayesian Networks (DBNs). To build our model, we made use of literature based knowledge describing SHH and EGFR signaling and integrated gene expression (Illumina) and cellular location dependent time series protein expression data (Reverse Phase Protein Arrays). We validated our model by sub-sampling training data and making Bayesian predictions on the left out test data. Our predictions focusing on key transcription factors and p70S6K, showed a high level of concordance with experimental data. Furthermore, the stability of our model was tested by a parametric bootstrap approach. Stable network features were in agreement with published data. Altogether we believe that our model improved our understanding of the interplay between two highly oncogenic signaling pathways in Daoy cells. This may open new perspectives for the future therapy of Hedghog/EGF-dependent solid tumors. PMID:26571415

  11. 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

  12. Large-Signal Characterization and Modeling of the Heterojunction Bipolar Transistor

    NASA Astrophysics Data System (ADS)

    Teeter, Douglas Andrew

    1992-01-01

    Rapid improvements in Heterojunction Bipolar Transistor (HBT) device performance have made power applications in the millimeter wave regime possible. Improved large-signal modeling and characterization techniques are required for designing circuits at these frequencies. Several large-signal modeling approaches are investigated in this thesis. The most detailed model involves numerically solving moments of the Boltzmann Transport Equation. Velocity overshoot and energy relaxation effects are included in this model. After a detailed description of the numerical techniques is given, the model is used to investigate HBT operation under large-signal steady state RF conditions. Internal device carrier concentrations, electric fields, electron temperature, and electron velocity are determined at various stages during the RF cycle. While the model is a valuable tool for studying the internal device physics, its use in circuit design applications is limited due to the computer time required. The fully numerical model is then used to investigate several simpler large-signal HBT models. It is found that the commonly used Gummel-Poon model exhibits poor agreement with numerical and experimental data at millimeter wave frequencies due to neglect of transit time delays. A modified Ebers-Moll model is described which overcomes this problem by implementing the transit time delay in the frequency domain. Two large-signal measurement systems covering 8 to 35 GHz were built to compare simulated results with experimental data. A commercial tuner system was used to make measurements from 8 to 16 GHz. However, to measure beyond 26 GHz, an active loadpull system was designed and constructed to circumvent problems created by component losses. Details of this measurement system, its accuracy, and error correction techniques are given. Good agreement between measured and modeled output power, gain compression, and efficiency is obtained using the modified Ebers-Moll model over a wide range

  13. 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

  14. 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

  15. 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

  16. 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. PMID:26092090

  17. 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

  18. 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

  19. An adaptive error modeling scheme for the lossless compression of EEG signals.

    PubMed

    Sriraam, N; Eswaran, C

    2008-09-01

    Lossless compression of EEG signal is of great importance for the neurological diagnosis as the specialists consider the exact reconstruction of the signal as a primary requirement. This paper discusses a lossless compression scheme for EEG signals that involves a predictor and an adaptive error modeling technique. The prediction residues are arranged based on the error count through an histogram computation. Two optimal regions are identified in the histogram plot through a heuristic search such that the bit requirement for encoding the two regions is minimum. Further improvement in the compression is achieved by removing the statistical redundancy that is present in the residue signal by using a context-based bias cancellation scheme. Three neural network predictors, namely, single-layer perceptron, multilayer perceptron, and Elman network and two linear predictors, namely, autoregressive model and finite impulse response filter are considered. Experiments are conducted using EEG signals recorded under different physiological conditions and the performances of the proposed methods are evaluated in terms of the compression ratio. It is shown that the proposed adaptive error modeling schemes yield better compression results compared to other known compression methods. PMID:18779073

  20. A real-time model of the synchronous machine based on digital signal processors

    SciTech Connect

    Do, Vanque; Barry, A.O. )

    1993-02-01

    A real-time digital model of a complete hydraulic synchronous machine is presented. The model is based on parallel processing using digital-signal processors (DSP) for fast calculation. The paper describes the modeling of the machine using block diagrams to represent the generator, voltage regulator, stabilizer, turbine, penstock and governor. Details of the hardware and software used to implement the real-time model of the machine are given. A first series of tests has been done and results are shown to evaluate the steady-state and transient performance of the model.

  1. 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

  2. A Model Based on Receptor Desensitization for Cyclic AMP Signaling in Dictyostelium Cells

    PubMed Central

    Martiel, Jean-Louis; Goldbeter, Albert

    1987-01-01

    We analyze a model based on receptor modification for the cAMP signaling system that controls aggregation of the slime mold Dictyostelium discoideum after starvation. The model takes into account both the desensitization of the cAMP receptor by reversible phosphorylation and the activation of adenylate cyclase that follows binding of extracellular cAMP to the unmodified receptor. The dynamics of the signaling system is studied in terms of three variables, namely, intracellular and extracellular cAMP, and the fraction of receptor in active state. Using parameter values collected from experimental studies on cAMP signaling and receptor phosphorylation, we show that the model accounts qualitatively and, in a large measure, quantitatively for the various modes of dynamic behavior observed in the experiments: (a) autonomous oscillations of cAMP, (b) relay of suprathreshold cAMP pulses, i.e., excitability, characterized by both an absolute and a relative refractory period, and (c) adaptation to constant cAMP stimuli. A two-variable version of the model is used to demonstrate the link between excitability and oscillations by phase plane analysis. The response of the model to repetitive stimulation allows comprehension, in terms of receptor desensitization, of the role of periodic signaling in Dictyostelium and, more generally, the function of pulsatile patterns of hormone secretion. PMID:19431710

  3. 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.

  4. 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

  5. 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

  6. Development of a new model system to dissect isoform specific Akt signalling in adipocytes.

    PubMed

    Kajno, Esi; McGraw, Timothy E; Gonzalez, Eva

    2015-06-15

    Protein kinase B (Akt) kinases are critical signal transducers mediating insulin action. Genetic studies revealed that Akt1 and Akt2 signalling differentially contribute to sustain lipid and glucose homoeostasis; however Akt isoform-specific effectors remain elusive due to the lack of a suitable model system to mechanistically interrogate Akt isoform-specific signalling. To overcome those technical limitations we developed a novel model system that provides acute and specific control of signalling by Akt isoforms. We generated mutants of Akt1 and Akt2 resistant to the allosteric Akt inhibitor MK-2206. We then developed adipocyte cell lines, in which endogenous Akt1 or Akt2 has been replaced by their corresponding drug-resistant Akt mutant. Treatment of those cells with MK-2206 allowed for acute and specific control of either Akt1 or Akt2 function. Our data showed that Akt1(W80A) and Akt2(W80A) mutants are resistant to MK-2206, dynamically regulated by insulin and able to signal to Akt downstream effectors. Analyses of insulin action in this cellular system showed that Akt1 and Akt2 are both able to mediate insulin regulation of the transcription factor forkhead box O1 (FoxO1) and the glucose transporter 4 (GLUT4), revealing a redundant role for these Akt kinases in the control of glucose transport into fat cells. In contrast, Akt1 signalling is uniquely required for adipogenesis, by controlling the mitotic clonal expansion (MCE) of pre-adipocytes that precedes white adipose cell differentiation. Our data provide new insights into the role of Akt kinases in glucose transport and adipogenesis and support our model system as a valuable tool for the biochemical characterization of signalling by specific Akt isoforms. PMID:25856301

  7. 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

  8. Noise Cancelling of Multichannel MRS Signals with a Time Dependent Harmonic Model

    NASA Astrophysics Data System (ADS)

    Larsen, J.; Dalgaard, E.; Auken, E.

    2013-12-01

    Magnetic resonance sounding (MRS) is a non-invasive geophysical technique applicable to groundwater investigations and provides a direct quantification of the subsurface water content from surface measurements. The technique is susceptible to electromagnetic noise and signal processing must be employed to retrieve the NMR signal from noisy measurements. The latest generation of MRS equipment is multichannel systems where a primary coil records the noisy NMR signal. Additional coils, physically displaced from the primary coil, synchronously measure the noise which is then subtracted from the primary coil with multichannel Wiener filtering. Unfortunately, this approach fails to take into account that noise can originate from several sources and as a result the noise cancelling is not always optimum. To remedy this problem it can be utilized that one of the major noise components in MRS signals is powerline harmonics, i.e. the noise is a sum of sinusoidal signals all harmonically related to the same fundamental powerline frequency. This implies that it is possible to create a model of the powerline harmonic noise that can be fitted to the MRS recordings and subtracted from these before employing multichannel Wiener filtering as we have recently demonstrated. A fundamental assumption in that work was that the powerline frequency and the amplitude and phase of each harmonic remained constant throughout a signal record of approximately 1 s duration. This assumption is often valid, but not always. In this study we present an extension of this method where the variations in the powerline signal are accounted for by a time dependent model. The signal records from each coil are divided into short overlapping segments, with a typical duration of 100 ms, and a harmonic model with time independent parameters is fitted to each segment. The fitting parameters from each segment are subsequently splined to a full harmonic model where all parameters; fundamental powerline frequency

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. Extraction of temperature dependences of small-signal model parameters in SiGe HBT HICUM model

    NASA Astrophysics Data System (ADS)

    Ya-Bin, Sun; Jun, Fu; Yu-Dong, Wang; Wei, Zhou; Wei, Zhang; Zhi-Hong, Liu

    2016-04-01

    In this work, temperature dependences of small-signal model parameters in the SiGe HBT HICUM model are presented. Electrical elements in the small-signal equivalent circuit are first extracted at each temperature, then the temperature dependences are determined by the series of extracted temperature coefficients, based on the established temperature formulas for corresponding model parameters. The proposed method is validated by a 1 × 0.2 × 16 μm2 SiGe HBT over a wide temperature range (from 218 K to 473 K), and good matching is obtained between the extracted and modeled results. Therefore, we believe that the proposed extraction flow of model parameter temperature dependence is reliable for characterizing the transistor performance and guiding the circuit design over a wide temperature range. Project supported partially by the Important National Science & Technology Specific Projects, China (Grant No. 2013ZX02503003).

  16. 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.

  17. 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. PMID:10641671

  18. 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...

  19. A signal subspace approach for modeling the hemodynamic response function in fMRI.

    PubMed

    Hossein-Zadeh, Gholam-Ali; Ardekani, Babak A; Soltanian-Zadeh, Hamid

    2003-10-01

    Many fMRI analysis methods use a model for the hemodynamic response function (HRF). Common models of the HRF, such as the Gaussian or Gamma functions, have parameters that are usually selected a priori by the data analyst. A new method is presented that characterizes the HRF over a wide range of parameters via three basis signals derived using principal component analysis (PCA). Covering the HRF variability, these three basis signals together with the stimulation pattern define signal subspaces which are applicable to both linear and nonlinear modeling and identification of the HRF and for various activation detection strategies. Analysis of simulated fMRI data using the proposed signal subspace showed increased detection sensitivity compared to the case of using a previously proposed trigonometric subspace. The methodology was also applied to activation detection in both event-related and block design experimental fMRI data using both linear and nonlinear modeling of the HRF. The activated regions were consistent with previous studies, indicating the ability of the proposed approach in detecting brain activation without a priori assumptions about the shape parameters of the HRF. The utility of the proposed basis functions in identifying the HRF is demonstrated by estimating the HRF in different activated regions. PMID:14599533

  20. Global dynamical modeling of time series and application to restoration of broadband signal characteristics

    SciTech Connect

    Gribkov, D.A.; Gribkova, V.V.; Kuznetsov, Y.I.; Rzhanov, A.G.

    1996-06-01

    We show the principle possibility of the external complex action restoring using the nonlinear dynamics inverse problem solution. It is shown that broadband signal can be restored from the time series of the process generated by nonstationary chaotic system using the reconstructed model as the nonlinear filter. {copyright} {ital 1996 American Institute of Physics.}

  1. Transient high frequency signal estimation: A model-based processing approach

    SciTech Connect

    Barnes, F.L.

    1985-03-22

    By utilizing the superposition property of linear systems a method of estimating the incident signal from reflective nondispersive data is developed. One of the basic merits of this approach is that, the reflections were removed by direct application of a Weiner type estimation algorithm, after the appropriate input was synthesized. The structure of the nondispersive signal model is well documented, and thus its' credence is established. The model is stated and more effort is devoted to practical methods of estimating the model parameters. Though a general approach was developed for obtaining the reflection weights, a simpler approach was employed here, since a fairly good reflection model is available. The technique essentially consists of calculating ratios of the autocorrelation function at lag zero and that lag where the incident and first reflection coincide. We initially performed our processing procedure on a measurement of a single signal. Multiple application of the processing procedure was required when we applied the reflection removal technique on a measurement containing information from the interaction of two physical phenomena. All processing was performed using SIG, an interactive signal processing package. One of the many consequences of using SIG was that repetitive operations were, for the most part, automated. A custom menu was designed to perform the deconvolution process.

  2. 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

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

    PubMed

    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 (Ca((2+)))-dependent enzymes (adenylyl cyclase (AC), phosphodiesterase 1 (PDE1), and calcineurin (CaN)) differentially detect Ca((2+)) transients in a hippocampal dendritic spine. The balance among AC, PDE1 and CaN might determine the occurrence of opposite Ca((2+))-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 Ca((2+)) signals demonstrated that AC and CaN have Ca((2+)) requirements modulated dynamically by different properties of the signals used to stimulate them, because their interactions with Ca((2+)) often occur under kinetic control. Contrarily, PDE1 responds to the immediate amplitude of different Ca((2+)) transients and usually with the same Ca((2+)) requirements observed under steady state. Therefore, AC, PDE1 and CaN decode different dynamic properties of Ca((2+)) signals. PMID:27033299

  4. Exploring signal transduction in heteromultimeric protein based on energy dissipation model.

    PubMed

    Ma, Cheng-Wei; Xiu, Zhi-Long; Zeng, An-Ping

    2015-01-01

    Dynamic intersubunit interactions are key elements in the regulation of many biological systems. A better understanding of how subunits interact with each other and how their interactions are related to dynamic protein structure is a fundamental task in biology. In this paper, a heteromultimeric allosteric protein, Corynebacterium glutamicum aspartokinase, is used as a model system to explore the signal transduction involved in intersubunit interactions and allosteric communication with an emphasis on the intersubunit signaling process. For this purpose, energy dissipation simulation and network construction are conducted for each subunit and the whole protein. Comparison with experimental results shows that the new approach is able to predict all the mutation sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. Additionally, analysis revealed that the function of the effector threonine is to facilitate the binding of the two subunits without contributing to the allosteric communication. During the allosteric regulation upon the binding of the effector lysine, signals can be transferred from the β-subunit to the catalytic site of the α-subunit through both a direct way of intersubunit signal transduction, and an indirect way: first, to the regulatory region of the α-subunit by intersubunit signal transduction and then to the catalytic region by intramolecular signal transduction. Therefore, the new approach is able to illustrate the diversity of the underlying mechanisms when the strength of feedback inhibition by the effector(s) is modulated, providing useful information that has potential applications in engineering heteromultimeric allosteric regulation. PMID:24279729

  5. Signaling individual identity versus quality: a model and case studies with ruffs, queleas, and house finches.

    PubMed

    Dale, J; Lank, D B; Reeve, H K

    2001-07-01

    We develop an evolutionary model that predicts that characters selected to signal individual identity will have properties differing from those expected for indicator signals of quality. Traits signaling identity should be highly variable, often display polymodal distributions, not be condition dependent (i.e., be cheap to produce and/or maintain), not be associated with fitness differences, exhibit independent assortment of component characters, and often occur as fixed phenotypes with a high degree of genetic determination. We illustrate the existence of traits with precisely these attributes in the ornamental, conspicuously variable, and sexually dimorphic breeding plumages of ruff sandpipers Philomachus pugnax and red-billed queleas Quelea quelea. Although ruffs lek and queleas are monogamous, both species breed in high-density aggregations with high rates of social interactions (e.g., aggression and territory defense). Under these socioecological conditions, individual recognition based on visual cues may be unusually important. In contrast to these species, we also review plumage characteristics in house finches Carpodacus mexicanus, a nonterritorial, dispersed-breeding species in which plumage ornamentation is thought to signal quality. In keeping with expectations for quality signals, house finch plumage is relatively less variable, unimodally distributed, condition dependent, correlated with fitness measures, has positively correlated component characters, and is a plastic, environmentally determined trait. We briefly discuss signals of identity in other animals. PMID:18707316

  6. 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.

  7. Capacity Estimation Model for Signalized Intersections under the Impact of Access Point.

    PubMed

    Zhao, Jing; Li, Peng; Zhou, Xizhao

    2016-01-01

    Highway Capacity Manual 2010 provides various factors to adjust the base saturation flow rate for the capacity analysis of signalized intersections. No factors, however, is considered for the potential change of signalized intersections capacity caused by the access point closeing to the signalized intersection. This paper presented a theoretical model to estimate the lane group capacity at signalized intersections with the consideration of the effects of access points. Two scenarios of access point locations, upstream or downstream of the signalized intersection, and impacts of six types of access traffic flow are taken into account. The proposed capacity model was validated based on VISSIM simulation. Results of extensive numerical analysis reveal the substantial impact of access point on the capacity, which has an inverse correlation with both the number of major street lanes and the distance between the intersection and access point. Moreover, among the six types of access traffic flows, the access traffic flow 1 (right-turning traffic from major street), flow 4 (left-turning traffic from access point), and flow 5 (left-turning traffic from major street) cause a more significant effect on lane group capacity than others. Some guidance on the mitigation of the negative effect is provided for practitioners. PMID:26726998

  8. 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

  9. 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.

  10. Capacity Estimation Model for Signalized Intersections under the Impact of Access Point

    PubMed Central

    Zhao, Jing; Li, Peng; Zhou, Xizhao

    2016-01-01

    Highway Capacity Manual 2010 provides various factors to adjust the base saturation flow rate for the capacity analysis of signalized intersections. No factors, however, is considered for the potential change of signalized intersections capacity caused by the access point closeing to the signalized intersection. This paper presented a theoretical model to estimate the lane group capacity at signalized intersections with the consideration of the effects of access points. Two scenarios of access point locations, upstream or downstream of the signalized intersection, and impacts of six types of access traffic flow are taken into account. The proposed capacity model was validated based on VISSIM simulation. Results of extensive numerical analysis reveal the substantial impact of access point on the capacity, which has an inverse correlation with both the number of major street lanes and the distance between the intersection and access point. Moreover, among the six types of access traffic flows, the access traffic flow 1 (right-turning traffic from major street), flow 4 (left-turning traffic from access point), and flow 5 (left-turning traffic from major street) cause a more significant effect on lane group capacity than others. Some guidance on the mitigation of the negative effect is provided for practitioners. PMID:26726998