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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. 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.

  18. 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.

  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 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.

  5. 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

  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. 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.

  19. 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.

  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. 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.

  10. 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.

  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. 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

  19. 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

  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 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

  3. 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

  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. 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.

  14. 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

  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. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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

  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. 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

  5. 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

  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 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

  8. 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

  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. 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

  13. 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

  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. 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.

  19. 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.

  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. 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

  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. 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.

  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. 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

  18. 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

  19. 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

  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. 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

  2. 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.

  3. 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

  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. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  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. 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

  19. 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.}

  20. 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.

  1. 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...

  2. 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

  3. 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

  4. 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

  5. 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

  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

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

    PubMed

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

    2016-07-01

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

  12. Remote Field Eddy Curent Signal Modeling for the Gap Measurement of Neighboring Tubes

    SciTech Connect

    Jung, H.K.; Lee, D.H.; Lee, Y.S.

    2005-04-09

    The fuel channels in the Canadian Deuterium Uranium (CANDU) reactor consist of the coaxial pressure tube (PT) and the calandria tube (CT). The Liquid injection nozzle (LIN) is cross aligned with the fuel channel to control the reactor by injecting poison. For a safe operation, the gap between the LIN and CT should be maintained in order to prevent a contact of the neighboring tubes. The remote field eddy current (RFEC) method was applied to measure the gap between a nonmagnetic Zircaloy-2 liquid injection nozzle (LIN) and a Zircaloy-2 calandria tube. Under the condition of inserting the RFEC probe into the coaxial tubes and of crossing a LIN above or under the CT, the modeling of a LIN signal is needed to check the possibility of a gap measurement. The Volume Integral Code S/W which covers the axi-symmetric 3D configuration has been very rarely applied to obtain a LIN signal. This problem was solved by assuming a LIN as a flaw which can be described as a complete 3D object. This simulated LIN signal was verified by performing the laboratory experiment. The gap between the LIN and CT can be correlated with the amplitude of the LIN signals in the voltage plane. Typical noises in the fuel channel were the relative constriction, the change in the pressure tube diameter (fill-factor), thickness variation, and so on. These noise signals were simulated by using the modeling and were analyzed by considering their dependency on the phase angle and amplitude of the voltage plane in order to separate the gap signal from them. It could be concluded that the voltage plane analysis of the simulated RFEC signals were effective for obtaining the gap measurement of the neighboring tube.

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

    NASA Astrophysics Data System (ADS)

    Stolnitz, Mikhail M.; Peshkova, Anna Y.

    2002-07-01

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

  14. A model for the spatial integration and differentiation of velocity signals.

    PubMed

    Gurney, K N; Wright, M J

    1996-09-01

    We present a model of optic flow processing which is able to reconcile the integrative, cooperative phenomena of motion capture and coherence with the differentiation of velocity signals in motion segmentation and transparency. The model uses a Markov random field to compute the behaviour of coextensive topographic neural maps of retinotopy and velocity. We have used the model to simulate the psychophysics of motion coherence, motion capture and transparency. Further, it exhibits motion segmentation without extra postulates. The model is robust and able to display all types of motion percept with the same parameter set. PMID:8917795

  15. A model for the analysis of fault-tolerant signal processing architectures

    NASA Technical Reports Server (NTRS)

    Nair, V. S. S.; Abraham, J. A.

    1989-01-01

    This paper develops a new model, using matrices, for the analysis of fault-tolerant multiprocessor systems. The relationship between processors computing useful data, the output data, and the check processors is defined in terms of matrix entries. Unlike the matrix-based models proposed previously for the analysis of digital systems, this model uses only numerical computations rather than logical operations for the analysis of a system. Algorithms to evaluate the fault detection and location capability of the system are proposed which are much less complex than the existing ones. The new model is used to analyze some fault-tolerant architectures proposed for signal-processing applications.

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

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  17. Bayesian Approach to Model CD137 Signaling in Human M. tuberculosis In Vitro Responses

    PubMed Central

    Fernández Do Porto, Darío A.; Auzmendi, Jerónimo; Peña, Delfina; García, Verónica E.; Moffatt, Luciano

    2013-01-01

    Immune responses are qualitatively and quantitatively influenced by a complex network of receptor-ligand interactions. Among them, the CD137:CD137L pathway is known to modulate innate and adaptive human responses against Mycobacterium tuberculosis. However, the underlying mechanisms of this regulation remain unclear. In this work, we developed a Bayesian Computational Model (BCM) of in vitro CD137 signaling, devised to fit previously gathered experimental data. The BCM is fed with the data and the prior distribution of the model parameters and it returns their posterior distribution and the model evidence, which allows comparing alternative signaling mechanisms. The BCM uses a coupled system of non-linear differential equations to describe the dynamics of Antigen Presenting Cells, Natural Killer and T Cells together with the interpheron (IFN)-γ and tumor necrosis factor (TNF)-α levels in the media culture. Fast and complete mixing of the media is assumed. The prior distribution of the parameters that describe the dynamics of the immunological response was obtained from the literature and theoretical considerations Our BCM applies successively the Levenberg-Marquardt algorithm to find the maximum a posteriori likelihood (MAP); the Metropolis Markov Chain Monte Carlo method to approximate the posterior distribution of the parameters and Thermodynamic Integration to calculate the evidence of alternative hypothesis. Bayes factors provided decisive evidence favoring direct CD137 signaling on T cells. Moreover, the posterior distribution of the parameters that describe the CD137 signaling showed that the regulation of IFN-γ levels is based more on T cells survival than on direct induction. Furthermore, the mechanisms that account for the effect of CD137 signaling on TNF-α production were based on a decrease of TNF-α production by APC and, perhaps, on the increase in APC apoptosis. BCM proved to be a useful tool to gain insight on the mechanisms of CD137 signaling

  18. Bayesian approach to model CD137 signaling in human M. tuberculosis in vitro responses.

    PubMed

    Fernández Do Porto, Darío A; Auzmendi, Jerónimo; Peña, Delfina; García, Verónica E; Moffatt, Luciano

    2013-01-01

    Immune responses are qualitatively and quantitatively influenced by a complex network of receptor-ligand interactions. Among them, the CD137:CD137L pathway is known to modulate innate and adaptive human responses against Mycobacterium tuberculosis. However, the underlying mechanisms of this regulation remain unclear. In this work, we developed a Bayesian Computational Model (BCM) of in vitro CD137 signaling, devised to fit previously gathered experimental data. The BCM is fed with the data and the prior distribution of the model parameters and it returns their posterior distribution and the model evidence, which allows comparing alternative signaling mechanisms. The BCM uses a coupled system of non-linear differential equations to describe the dynamics of Antigen Presenting Cells, Natural Killer and T Cells together with the interpheron (IFN)-γ and tumor necrosis factor (TNF)-α levels in the media culture. Fast and complete mixing of the media is assumed. The prior distribution of the parameters that describe the dynamics of the immunological response was obtained from the literature and theoretical considerations Our BCM applies successively the Levenberg-Marquardt algorithm to find the maximum a posteriori likelihood (MAP); the Metropolis Markov Chain Monte Carlo method to approximate the posterior distribution of the parameters and Thermodynamic Integration to calculate the evidence of alternative hypothesis. Bayes factors provided decisive evidence favoring direct CD137 signaling on T cells. Moreover, the posterior distribution of the parameters that describe the CD137 signaling showed that the regulation of IFN-γ levels is based more on T cells survival than on direct induction. Furthermore, the mechanisms that account for the effect of CD137 signaling on TNF-α production were based on a decrease of TNF-α production by APC and, perhaps, on the increase in APC apoptosis. BCM proved to be a useful tool to gain insight on the mechanisms of CD137 signaling

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

    PubMed

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

    2014-12-15

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

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

    PubMed

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

    2014-06-01

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

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

    PubMed

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

    2016-08-01

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

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

    PubMed Central

    Desikan, Radhika

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-03-01

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

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

    PubMed Central

    Han, Liqi

    2010-01-01

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

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

    PubMed

    Devinck, Frédéric; Knoblauch, Kenneth

    2012-01-01

    Establishing the relation between perception and discrimination is a fundamental objective in psychophysics, with the goal of characterizing the neural mechanisms mediating perception. Here, we show that a procedure for estimating a perceptual scale based on a signal detection model also predicts discrimination performance. We use a recently developed procedure, Maximum Likelihood Difference Scaling (MLDS), to measure the perceptual strength of a long-range, color, filling-in phenomenon, the Watercolor Effect (WCE), as a function of the luminance ratio between the two components of its generating contour. MLDS is based on an equal-variance, gaussian, signal detection model and yields a perceptual scale with interval properties. The strength of the fill-in percept increased 10-15 times the estimate of the internal noise level for a 3-fold increase in the luminance ratio. Each observer's estimated scale predicted discrimination performance in a subsequent paired-comparison task. A common signal detection model accounts for both the appearance and discrimination data. Since signal detection theory provides a common metric for relating discrimination performance and neural response, the results have implications for comparing perceptual and neural response functions. PMID:22438468

  6. GPS Signal Scattering from Sea Surface: Wind Speed Retrieval Using Experimental Data and Theoretical Model

    NASA Technical Reports Server (NTRS)

    Komjathy, Attila; Zavorotny, Valery U.; Axelrad, Penina; Born, George H.; Garrison, James L.

    2000-01-01

    Global Positioning System (GPS) signals reflected from the ocean surface have potential use for various remote sensing purposes. Some possibilities arc measurements of surface roughness characteristics from which ware height, wind speed, and direction could be determined. For this paper, GPS-reflected signal measurements collected at aircraft altitudes of 2 km to 5 km with a delay-Doppler mapping GPS receiver arc used to explore the possibility of determining wind speed. To interpret the GPS data, a theoretical model has been developed that describes the power of the reflected GPS signals for different time delays and Doppler frequencies as a function of geometrical and environmental parameters. The results indicate a good agreement between the measured and the modeled normalized signal power waveforms during changing surface wind conditions. The estimated wind speed using surface- reflected GPS data, obtained by comparing actual and modeled waveforms, shows good agreement (within 2 m/s) with data obtained from a nearby buoy and independent wind speed measurements derived from the TOPEX/Poseidon altimetric satellite.

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

    PubMed Central

    Mordhorst, Mylena; Heidlauf, Thomas; Röhrle, Oliver

    2015-01-01

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

  8. Experimental Verification of Model-Based ECT Signal Interpretation for Quantitative Flaw Characterization in Steam Generator Tubes

    NASA Astrophysics Data System (ADS)

    Song, Sung-Jin; Kim, Young H.; Kim, Eui-Lae; Chung, Tae-Eon; Yim, Chang-Jae

    2003-03-01

    The model-based inversion tools for eddy current signals have been developed by the novel combination of neural networks and finite element modeling for quantitative flaw characterization in steam generator tubes. In the present work, interpretation of experimental eddy current signals was carried out in order to validate the developed inversion tools. A database was constructed using the synthetic flaw signals generated by the finite element modeling. The hybrid neural networks of a PNN classifier and BPNN size estimators were trained using the synthetic signals. Experimental eddy current signals were obtained from axisymmetric artificial flaws. Interpretations of flaws were carried out by feeding experimental signals into the neural networks. The results of interpretations were excellent, so that the developed inversion tools would be applicable to the interpretation of experimental eddy current signals.

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

    SciTech Connect

    Siddiquee, Sinchita; Kabir, M. Z.

    2015-07-15

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

  10. Integration of radio-frequency transmission and radar in general software for multimodal battlefield signal modeling

    NASA Astrophysics Data System (ADS)

    Yamamoto, Kenneth K.; Reznicek, Nathan J.; Wilson, D. Keith

    2013-05-01

    The Environmental Awareness for Sensor and Emitter Employment (EASEE) software, being developed by the U. S. Army Engineer Research and Development Center (ERDC), provides a general platform for predicting sensor performance and optimizing sensor selection and placement in complex terrain and weather conditions. It incorporates an extensive library of target signatures, signal propagation models, and sensor systems. A flexible object-oriented design supports efficient integration and simulation of diverse signal modalities. This paper describes the integration of modeling capabilities for radio-frequency (RF) transmission and radar systems from the U. S. Navy Electromagnetic Propagation Integrated Resource Environment (EMPIRE), which contains nearly twenty different realistic RF propagation models. The integration utilizes an XML-based interface between EASEE and EMPIRE to set inputs for and run propagation models. To accommodate radars, fundamental improvements to the EASEE software architecture were made to support active-sensing scenarios with forward and backward propagation of the RF signals between the radar and target. Models for reflecting targets were defined to apply a target-specific, directionally dependent reflection coefficient (i.e., scattering cross section) to the incident wavefields.

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

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

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

    SciTech Connect

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

    2010-12-07

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

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

    NASA Technical Reports Server (NTRS)

    Gai, E.

    1975-01-01

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

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

    PubMed

    Gray, Catheryn W; Coster, Adelle C F

    2015-12-01

    Insulin is a potent peptide hormone that regulates glucose levels in the blood. Insulin-sensitive cells respond to insulin stimulation with the translocation of glucose transporter 4 (GLUT4) to the plasma membrane (PM), enabling the clearance of glucose from the blood. Defects in this process can give rise to insulin resistance and ultimately diabetes. One widely cited model of insulin signalling leading to glucose transport is that of Sedaghat et al. (2002) Am. J. Physiol. Endocrinol. Metab. 283, E1084-E1101. Consisting of 20 deterministic ordinary differential equations (ODEs), it is the most comprehensive model of insulin signalling to date. However, the model possesses some major limitations, including the non-conservation of key components. In the current work, we detail mathematical and sensitivity analyses of the Sedaghat model. Based on the results of these analyses, we propose a reduced state space model of the insulin receptor subsystem. This reduced model maintains the input-output relation of the original model but is computationally more efficient, analytically tractable and resolves some of the limitations of the Sedaghat model. PMID:25673317

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

    PubMed Central

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

    2015-01-01

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

  16. INTERPRETING THE GLOBAL 21 cm SIGNAL FROM HIGH REDSHIFTS. I. MODEL-INDEPENDENT CONSTRAINTS

    SciTech Connect

    Mirocha, Jordan; Harker, Geraint J. A.; Burns, Jack O.

    2013-11-10

    The sky-averaged (global) 21 cm signal is a powerful probe of the intergalactic medium (IGM) prior to the completion of reionization. However, so far it has been unclear whether it will provide more than crude estimates of when the universe's first stars and black holes formed, even in the best case scenario in which the signal is accurately extracted from the foregrounds. In contrast to previous work, which has focused on predicting the 21 cm signatures of the first luminous objects, we investigate an arbitrary realization of the signal and attempt to translate its features to the physical properties of the IGM. Within a simplified global framework, the 21 cm signal yields quantitative constraints on the Lyα background intensity, net heat deposition, ionized fraction, and their time derivatives without invoking models for the astrophysical sources themselves. The 21 cm absorption signal is most easily interpreted, setting strong limits on the heating rate density of the universe with a measurement of its redshift alone, independent of the ionization history or details of the Lyα background evolution. In a companion paper, we extend these results, focusing on the confidence with which one can infer source emissivities from IGM properties.

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  18. Multi-area neural mass modeling of EEG and MEG signals.

    PubMed

    Babajani-Feremi, Abbas; Soltanian-Zadeh, Hamid

    2010-09-01

    We previously proposed an integrated electroencephalography (EEG), magnetoencephalography (MEG), and functional Magnetic Resonance Imaging (fMRI) model based on an extended neural mass model (ENMM) within a single cortical area. In the ENMM, a cortical area contains several minicolumns where strengths of their connections diminish exponentially with their distances. The ENMM was derived based on the physiological principles of the cortical minicolumns and their connections within a single cortical area to generate EEG, MEG, and fMRI signals. The purpose of this paper is to further extend the ENMM model from a single-area to a multi-area model to develop a neural mass model of the entire brain that generates EEG and MEG signals. For multi-area modeling, two connection types are considered: short-range connections (SRCs) and long-range connections (LRCs). The intra-area SRCs among the minicolumns within the areas were previously modeled in the ENMM. To define inter-area LRCs among the cortical areas, we consider that the cell populations of all minicolumns in the destination area are affected by the excitatory afferent of the pyramidal cells of all minicolumns in the source area. The state-space representation of the multi-area model is derived considering the intra-minicolumn, SRCs', and LRCs' parameters. Using simulations, we evaluate effects of parameters of the model on its dynamics and, based on stability analysis, find valid ranges for parameters of the model. In addition, we evaluate reducing redundancy of the model parameters using simulation results and conclude that the parameters of the model can be limited to the LRCs and SRCs while the intra-minicolumn parameters stay at their physiological mean values. The proposed multi-area integrated E/MEG model provides an efficient neuroimaging technique for effective connectivity analysis in healthy subjects as well as neurological and psychiatric patients. PMID:20080193

  19. Exhaustively characterizing feasible logic models of a signaling network using Answer Set Programming

    PubMed Central

    Guziolowski, Carito; Videla, Santiago; Eduati, Federica; Thiele, Sven; Cokelaer, Thomas; Siegel, Anne; Saez-Rodriguez, Julio

    2013-01-01

    Motivation: Logic modeling is a useful tool to study signal transduction across multiple pathways. Logic models can be generated by training a network containing the prior knowledge to phospho-proteomics data. The training can be performed using stochastic optimization procedures, but these are unable to guarantee a global optima or to report the complete family of feasible models. This, however, is essential to provide precise insight in the mechanisms underlaying signal transduction and generate reliable predictions. Results: We propose the use of Answer Set Programming to explore exhaustively the space of feasible logic models. Toward this end, we have developed caspo, an open-source Python package that provides a powerful platform to learn and characterize logic models by leveraging the rich modeling language and solving technologies of Answer Set Programming. We illustrate the usefulness of caspo by revisiting a model of pro-growth and inflammatory pathways in liver cells. We show that, if experimental error is taken into account, there are thousands (11 700) of models compatible with the data. Despite the large number, we can extract structural features from the models, such as links that are always (or never) present or modules that appear in a mutual exclusive fashion. To further characterize this family of models, we investigate the input–output behavior of the models. We find 91 behaviors across the 11 700 models and we suggest new experiments to discriminate among them. Our results underscore the importance of characterizing in a global and exhaustive manner the family of feasible models, with important implications for experimental design. Availability: caspo is freely available for download (license GPLv3) and as a web service at http://caspo.genouest.org/. Supplementary information: Supplementary materials are available at Bioinformatics online. Contact: santiago.videla@irisa.fr PMID:23853063

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

    PubMed Central

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

    2007-01-01

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

  1. A Gaussian process framework for modelling stellar activity signals in radial velocity data

    NASA Astrophysics Data System (ADS)

    Rajpaul, V.; Aigrain, S.; Osborne, M. A.; Reece, S.; Roberts, S.

    2015-09-01

    To date, the radial velocity (RV) method has been one of the most productive techniques for detecting and confirming extrasolar planetary candidates. Unfortunately, stellar activity can induce RV variations which can drown out or even mimic planetary signals - and it is notoriously difficult to model and thus mitigate the effects of these activity-induced nuisance signals. This is expected to be a major obstacle to using next-generation spectrographs to detect lower mass planets, planets with longer periods, and planets around more active stars. Enter Gaussian processes (GPs) which, we note, have a number of attractive features that make them very well suited to disentangling stellar activity signals from planetary signals. We present here a GP framework we developed to model RV time series jointly with ancillary activity indicators (e.g. bisector velocity spans, line widths, chromospheric activity indices), allowing the activity component of RV time series to be constrained and disentangled from e.g. planetary components. We discuss the mathematical details of our GP framework, and present results illustrating its encouraging performance on both synthetic and real RV data sets, including the publicly available Alpha Centauri B data set.

  2. Early Embryonic Vascular Patterning by Matrix-Mediated Paracrine Signalling: A Mathematical Model Study

    PubMed Central

    Köhn-Luque, Alvaro; de Back, Walter; Starruß, Jörn; Mattiotti, Andrea; Deutsch, Andreas; Pérez-Pomares, José María; Herrero, Miguel A.

    2011-01-01

    During embryonic vasculogenesis, endothelial precursor cells of mesodermal origin known as angioblasts assemble into a characteristic network pattern. Although a considerable amount of markers and signals involved in this process have been identified, the mechanisms underlying the coalescence of angioblasts into this reticular pattern remain unclear. Various recent studies hypothesize that autocrine regulation of the chemoattractant vascular endothelial growth factor (VEGF) is responsible for the formation of vascular networks in vitro. However, the autocrine regulation hypothesis does not fit well with reported data on in vivo early vascular development. In this study, we propose a mathematical model based on the alternative assumption that endodermal VEGF signalling activity, having a paracrine effect on adjacent angioblasts, is mediated by its binding to the extracellular matrix (ECM). Detailed morphometric analysis of simulated networks and images obtained from in vivo quail embryos reveals the model mimics the vascular patterns with high accuracy. These results show that paracrine signalling can result in the formation of fine-grained cellular networks when mediated by angioblast-produced ECM. This lends additional support to the theory that patterning during early vascular development in the vertebrate embryo is regulated by paracrine signalling. PMID:21949696

  3. Strategies for testing the irritation-signaling model for chronic lung effects of fine acid particles

    SciTech Connect

    Hattis, D.; Abdollahzadeh, S.; Franklin, C.A. )

    1990-03-01

    The irritation signaling model proposed that a long term contribution to chronic bronchitis might result from the repeated delivery of signals resulting from temporary localized acidification of the bronchial epithelium by the action of individual particles. This led to a prediction that the effectiveness of particles in inducing changes in mucus secreting cell numbers/types should depend on the number of particles deposited that contained a particular amount of acid--implying that particles below a certain size cutoff (and therefore lacking a minimum amount of acid) should be ineffective; and that particle potency per unit weight should be greatest at the cutoff and decline strongly above the cutoff. Since the development of this hypothesis both epidemiological observations and some experimental studies have tended to reinforce the notion that acid particles can make a contribution to relatively long lasting bronchitic-like changes, and enhance the desirability of more direct testing of the model. In this paper we develop a general theoretical framework for the contributions of environmental agents to chronic obstructive lung disease, and a series of alternative hypotheses against which the predictions of the irritant signaling model can be compared. Based on this, we suggest a research program that could be used to further develop and test the model and reasonable alternatives. 82 references.

  4. A novel tensor distribution model for the diffusion-weighted MR signal.

    PubMed

    Jian, Bing; Vemuri, Baba C; Ozarslan, Evren; Carney, Paul R; Mareci, Thomas H

    2007-08-01

    Diffusion MRI is a non-invasive imaging technique that allows the measurement of water molecule diffusion through tissue in vivo. The directional features of water diffusion allow one to infer the connectivity patterns prevalent in tissue and possibly track changes in this connectivity over time for various clinical applications. In this paper, we present a novel statistical model for diffusion-weighted MR signal attenuation which postulates that the water molecule diffusion can be characterized by a continuous mixture of diffusion tensors. An interesting observation is that this continuous mixture and the MR signal attenuation are related through the Laplace transform of a probability distribution over symmetric positive definite matrices. We then show that when the mixing distribution is a Wishart distribution, the resulting closed form of the Laplace transform leads to a Rigaut-type asymptotic fractal expression, which has been phenomenologically used in the past to explain the MR signal decay but never with a rigorous mathematical justification until now. Our model not only includes the traditional diffusion tensor model as a special instance in the limiting case, but also can be adjusted to describe complex tissue structure involving multiple fiber populations. Using this new model in conjunction with a spherical deconvolution approach, we present an efficient scheme for estimating the water molecule displacement probability functions on a voxel-by-voxel basis. Experimental results on both simulations and real data are presented to demonstrate the robustness and accuracy of the proposed algorithms. PMID:17570683

  5. Explaining neural signals in human visual cortex with an associative learning model.

    PubMed

    Jiang, Jiefeng; Schmajuk, Nestor; Egner, Tobias

    2012-08-01

    "Predictive coding" models posit a key role for associative learning in visual cognition, viewing perceptual inference as a process of matching (learned) top-down predictions (or expectations) against bottom-up sensory evidence. At the neural level, these models propose that each region along the visual processing hierarchy entails one set of processing units encoding predictions of bottom-up input, and another set computing mismatches (prediction error or surprise) between predictions and evidence. This contrasts with traditional views of visual neurons operating purely as bottom-up feature detectors. In support of the predictive coding hypothesis, a recent human neuroimaging study (Egner, Monti, & Summerfield, 2010) showed that neural population responses to expected and unexpected face and house stimuli in the "fusiform face area" (FFA) could be well-described as a summation of hypothetical face-expectation and -surprise signals, but not by feature detector responses. Here, we used computer simulations to test whether these imaging data could be formally explained within the broader framework of a mathematical neural network model of associative learning (Schmajuk, Gray, & Lam, 1996). Results show that FFA responses could be fit very closely by model variables coding for conditional predictions (and their violations) of stimuli that unconditionally activate the FFA. These data document that neural population signals in the ventral visual stream that deviate from classic feature detection responses can formally be explained by associative prediction and surprise signals. PMID:22845706

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

    PubMed Central

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

    2015-01-01

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

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

    SciTech Connect

    Robock, A.; Liu, Y. )

    1994-01-01

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

  8. Uncertainty quantification of voice signal production mechanical model and experimental updating

    NASA Astrophysics Data System (ADS)

    Cataldo, E.; Soize, C.; Sampaio, R.

    2013-11-01

    The aim of this paper is to analyze the uncertainty quantification in a voice production mechanical model and update the probability density function corresponding to the tension parameter using the Bayes method and experimental data. Three parameters are considered uncertain in the voice production mechanical model used: the tension parameter, the neutral glottal area and the subglottal pressure. The tension parameter of the vocal folds is mainly responsible for the changing of the fundamental frequency of a voice signal, generated by a mechanical/mathematical model for producing voiced sounds. The three uncertain parameters are modeled by random variables. The probability density function related to the tension parameter is considered uniform and the probability density functions related to the neutral glottal area and the subglottal pressure are constructed using the Maximum Entropy Principle. The output of the stochastic computational model is the random voice signal and the Monte Carlo method is used to solve the stochastic equations allowing realizations of the random voice signals to be generated. For each realization of the random voice signal, the corresponding realization of the random fundamental frequency is calculated and the prior pdf of this random fundamental frequency is then estimated. Experimental data are available for the fundamental frequency and the posterior probability density function of the random tension parameter is then estimated using the Bayes method. In addition, an application is performed considering a case with a pathology in the vocal folds. The strategy developed here is important mainly due to two things. The first one is related to the possibility of updating the probability density function of a parameter, the tension parameter of the vocal folds, which cannot be measured direct and the second one is related to the construction of the likelihood function. In general, it is predefined using the known pdf. Here, it is

  9. Identification and utilization of arbitrary correlations in models of recombination signal sequences

    PubMed Central

    Cowell, Lindsay G; Davila, Marco; Kepler, Thomas B; Kelsoe, Garnett

    2002-01-01

    Background A significant challenge in bioinformatics is to develop methods for detecting and modeling patterns in variable DNA sequence sites, such as protein-binding sites in regulatory DNA. Current approaches sometimes perform poorly when positions in the site do not independently affect protein binding. We developed a statistical technique for modeling the correlation structure in variable DNA sequence sites. The method places no restrictions on the number of correlated positions or on their spatial relationship within the site. No prior empirical evidence for the correlation structure is necessary. Results We applied our method to the recombination signal sequences (RSS) that direct assembly of B-cell and T-cell antigen-receptor genes via V(D)J recombination. The technique is based on model selection by cross-validation and produces models that allow computation of an information score for any signal-length sequence. We also modeled RSS using order zero and order one Markov chains. The scores from all models are highly correlated with measured recombination efficiencies, but the models arising from our technique are better than the Markov models at discriminating RSS from non-RSS. Conclusions Our model-development procedure produces models that estimate well the recombinogenic potential of RSS and are better at RSS recognition than the order zero and order one Markov models. Our models are, therefore, valuable for studying the regulation of both physiologic and aberrant V(D)J recombination. The approach could be equally powerful for the study of promoter and enhancer elements, splice sites, and other DNA regulatory sites that are highly variable at the level of individual nucleotide positions. PMID:12537561

  10. A MULTI-LAYER PHOSWICH RADIOXENON DETECTION SYSTEM, REPORTING PERIOD 11/01/06 - 01/31/07

    SciTech Connect

    David M. Hamby, P.I.

    2007-01-31

    During the third quarter of our research we continued development of our two-channel digital pulse processor, and finalized/optimized our XEPHWICH design. We have completed a number of simulations (using MCNP) on potential design features of a two-channel phoswich detector, and have come to agreement on the most efficient design for the ARSA framework. This design will encompass two planar, triple-layer phoswich detectors positioned parallel to each other such that the gas-counting volume is a very thin disk. This approach creates a counting geometry that is very close to 4{pi}, while simplifying the manufacturing process. For the DPP2, a two-channel fast preamplifier is being designed. The preamplifier will have DC-offset and gain adjustments. As described in the proposal, valid signal pulses from two PMTs are identified and captured in the FPGA and then digitally processed in a dedicated Digital Signal Processor (DSP). The MicroBlaze processor from Xilinx is intended to be replaced with the DSP. The processor is a soft core, meaning that it is implemented using general logic primitives rather than a hard core such as DSP.

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

    Energy Science and Technology Software Center (ESTSC)

    2005-09-08

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

  12. Architecture-dependent signal conduction in model networks of endothelial cells

    NASA Astrophysics Data System (ADS)

    Deymier, Pierre A.; Eray, Mete; Deymier, Martin J.; Runge, Keith; Hoying, James B.; Vasseur, Jérome O.

    2010-04-01

    Signal conduction between endothelial cells along the walls of vessels appears to play an important role in circulatory function. A recently developed approach to calculate analytically the spectrum of propagating compositional waves in models of multicellular architectures is extended to study putative signal conduction dynamics across networks of endothelial cells. Here, compositional waves originate from negative feedback loops, such as between Ca2+ and inositol triphosphate (IP3) in endothelial cells, and are shaped by their connection topologies. We consider models of networks constituted of a main chain of endothelial cells and multiple side chains. The resulting transmission spectra encode information concerning the position and size of the side branches in the form of gaps. This observation suggests that endothelial cell networks may be able to “communicate” information regarding long-range order in their architecture.

  13. Spontaneous calcium signals induced by gap junctions in a network model of astrocytes

    NASA Astrophysics Data System (ADS)

    Kazantsev, V. B.

    2009-01-01

    The dynamics of a network model of astrocytes coupled by gap junctions is investigated. Calcium dynamics of the single cell is described by the biophysical model comprising the set of three nonlinear differential equations. Intercellular dynamics is provided by the diffusion of inositol 1,4,5-trisphosphate (IP3) through gap junctions between neighboring astrocytes. It is found that the diffusion induces the appearance of spontaneous activity patterns in the network. Stability of the network steady state is analyzed. It is proved that the increase of the diffusion coefficient above a certain critical value yields the generation of low-amplitude subthreshold oscillatory signals in a certain frequency range. It is shown that such spontaneous oscillations can facilitate calcium pulse generation and provide a certain time scale in astrocyte signaling.

  14. Signal-to-noise ratio for temporal integrated drifting images: a model for perceived image sharpening.

    PubMed

    Power, G J; Sturtz, K E

    2000-12-10

    A formulation of signal-to-noise ratio is constructed that uses temporal integrated images from image sequences. Given a blurred image that drifts horizontally at various speeds and at various linear blurs, we prove that this formulation of the signal-to-noise ratio consistently increases with an increase in speed. This increase is shown to model the trends in the human vision system by which drifting blurred images are perceived with increased sharpness. The existing widely used objective quality techniques fail to model the perceptual increase in sharpness. This new formulation, along with other objective quality measures, is tested on several blurred drifting image sequences. The new formulation reflects the theoretically predicted increase in perceived sharpness. PMID:18354675

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

    PubMed

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

    2015-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Magliocca, N. R.

    2015-12-01

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

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

    PubMed Central

    Parker, Andrew J.

    2013-01-01

    The study of sensory signaling in the visual cortex has been greatly advanced by the recording of neural activity simultaneously with the performance of a specific psychophysical task. Individual nerve cells may also increase their firing leading up to the particular choice or decision made on a single psychophysical trial. Understanding these signals is important because they have been taken as evidence that a particular nerve cell or group of nerve cells in the cortex is involved in the formation of the perceptual decision ultimately signaled by the organism. However, recent analyses show that the size of a decision-related change in firing in a particular neuron is not a secure basis for concluding anything about the contribution of a single neuron to the formation of a decision: rather the size of the decision-related firing is expected to be dominated by the extent to which the activation of a single neuron is correlated with the firing of the pool of neurons. The critical question becomes what defines membership of a population of neurons. This article presents the proposal that groups of neurons are naturally linked together by their connectivity, which in turn reflects the previous history of sensory stimulations. When a new psychophysical task is performed, a group of neurons relevant to the judgment becomes involved because the firing of some neurons in that group is strongly relevant to the task. This group of neurons is called a micro-pool. This article examines the consequences of such a proposal within the visual nervous system. The main focus is on the signals available from single neurons, but it argued that models of choice-related signals must scale up to larger numbers of neurons because MRI and MEG studies also show evidence of similar choice signals. PMID:23986690

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  2. Reversible Parallel Discrete Event Formulation of a TLM-based Radio Signal Propagation Model

    SciTech Connect

    Seal, Sudip K; Perumalla, Kalyan S

    2011-01-01

    Radio signal strength estimation is essential in many applications, including the design of military radio communications and industrial wireless installations. For scenarios with large or richly- featured geographical volumes, parallel processing is required to meet the memory and computa- tion time demands. Here, we present a scalable and efficient parallel execution of the sequential model for radio signal propagation recently developed by Nutaro et al. Starting with that model, we (a) provide a vector-based reformulation that has significantly lower computational overhead for event handling, (b) develop a parallel decomposition approach that is amenable to reversibility with minimal computational overheads, (c) present a framework for transparently mapping the conservative time-stepped model into an optimistic parallel discrete event execution, (d) present a new reversible method, along with its analysis and implementation, for inverting the vector-based event model to be executed in an optimistic parallel style of execution, and (e) present performance results from implementation on Cray XT platforms. We demonstrate scalability, with the largest runs tested on up to 127,500 cores of a Cray XT5, enabling simulation of larger scenarios and with faster execution than reported before on the radio propagation model. This also represents the first successful demonstration of the ability to efficiently map a conservative time-stepped model to an optimistic discrete-event execution.

  3. Investigating irregularly patterned deep brain stimulation signal design using biophysical models

    PubMed Central

    Summerson, Samantha R.; Aazhang, Behnaam; Kemere, Caleb

    2015-01-01

    Parkinson's disease (PD) is a neurodegenerative disorder which follows from cell loss of dopaminergic neurons in the substantia nigra pars compacta (SNc), a nucleus in the basal ganglia (BG). Deep brain stimulation (DBS) is an electrical therapy that modulates the pathological activity to treat the motor symptoms of PD. Although this therapy is currently used in clinical practice, the sufficient conditions for therapeutic efficacy are unknown. In this work we develop a model of critical motor circuit structures in the brain using biophysical cell models as the base components and then evaluate performance of different DBS signals in this model to perform comparative studies of their efficacy. Biological models are an important tool for gaining insights into neural function and, in this case, serve as effective tools for investigating innovative new DBS paradigms. Experiments were performed using the hemi-parkinsonian rodent model to test the same set of signals, verifying the obedience of the model to physiological trends. We show that antidromic spiking from DBS of the subthalamic nucleus (STN) has a significant impact on cortical neural activity, which is frequency dependent and additionally modulated by the regularity of the stimulus pulse train used. Irregular spacing between stimulus pulses, where the amount of variability added is bounded, is shown to increase diversification of response of basal ganglia neurons and reduce entropic noise in cortical neurons, which may be fundamentally important to restoration of information flow in the motor circuit. PMID:26167150

  4. Boolean approach to signalling pathway modelling in HGF-induced keratinocyte migration

    PubMed Central

    Singh, Amit; Nascimento, Juliana M.; Kowar, Silke; Busch, Hauke; Boerries, Melanie

    2012-01-01

    Motivation: Cell migration is a complex process that is controlled through the time-sequential feedback regulation of protein signalling and gene regulation. Based on prior knowledge and own experimental data, we developed a large-scale dynamic network describing the onset and maintenance of hepatocyte growth factor-induced migration of primary human keratinocytes. We applied Boolean logic to capture the qualitative behaviour as well as short-and long-term dynamics of the complex signalling network involved in this process, comprising protein signalling, gene regulation and autocrine feedback. Results: A Boolean model has been compiled from time-resolved transcriptome data and literature mining, incorporating the main pathways involved in migration from initial stimulation to phenotype progress. Steady-state analysis under different inhibition and stimulation conditions of known key molecules reproduces existing data and predicts novel interactions based on our own experiments. Model simulations highlight for the first time the necessity of a temporal sequence of initial, transient MET receptor (met proto-oncogene, hepatocyte growth factor receptor) and subsequent, continuous epidermal growth factor/integrin signalling to trigger and sustain migration by autocrine signalling that is integrated through the Focal adhesion kinase protein. We predicted in silico and verified in vitro that long-term cell migration is stopped if any of the two feedback loops are inhibited. Availability: The network file for analysis with the R BoolNet library is available in the Supplementary Information. Contact: melanie.boerries@frias.uni-freiburg.de or hauke.busch@frias.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22962472

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

    PubMed

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

    2016-01-01

    The purpose of this study is to develop a system capable of performing calculation of temporal gait parameters using two low-cost wireless accelerometers and artificial intelligence-based techniques as part of a larger research project for conducting human gait analysis. Ten healthy subjects of different ages participated in this study and performed controlled walking tests. Two wireless accelerometers were placed on their ankles. Raw acceleration signals were processed in order to obtain gait patterns from characteristic peaks related to steps. A Bayesian model was implemented to classify the characteristic peaks into steps or nonsteps. The acceleration signals were segmented based on gait events, such as heel strike and toe-off, of actual steps. Temporal gait parameters, such as cadence, ambulation time, step time, gait cycle time, stance and swing phase time, simple and double support time, were estimated from segmented acceleration signals. Gait data-sets were divided into two groups of ages to test Bayesian models in order to classify the characteristic peaks. The mean error obtained from calculating the temporal gait parameters was 4.6%. Bayesian models are useful techniques that can be applied to classification of gait data of subjects at different ages with promising results. PMID:25876180

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

    PubMed Central

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

    2013-01-01

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

  7. Impact of signal model on data compression for TDOA/FDOA emitter location

    NASA Astrophysics Data System (ADS)

    Fowler, Mark L.; Hu, Xi

    2008-08-01

    Early work in source location using time-difference-of-arrival/frequency-difference-of-arrival (TDOA/FDOA) focused on locating acoustic sources while later work focused on locating electromagnetic sources. The key difference is the signal model assumptions: WSS Gaussian process is widely used in the acoustic case but is not appropriate in the electromagnetic case. The Fisher information (FI) is fundamentally different for the two scenarios and leads to different distortion metrics for data compression algorithms that seek to maximize the FI for a given data rate. We discuss the philosophical impacts of this relevant to the following question: having collected a single set of data and wanting to do the best "job" for that data, should it matter if the data is viewed as coming from a WSS random process? This work shows that one must be careful when using a random signal model. If one takes the operational rate-distortion view, the goal of compression is to adapt the algorithm to the specific data observed. This is a modern view that contrasts with classical rate-distortion where the distortion measure includes an averaging over the ensemble. We assert that for the operational rate-distortion approach with FI as distortion measure, one should not use a random signal model.

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Saremi, Amin; Stenfelt, Stefan

    2011-11-01

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

  10. Modeling Neural Immune Signaling of Episodic and Chronic Migraine Using Spreading Depression In Vitro

    PubMed Central

    Mitchell, Heidi M.; Kraig, Richard P.

    2011-01-01

    Migraine and its transformation to chronic migraine are healthcare burdens in need of improved treatment options. We seek to define how neural immune signaling modulates the susceptibility to migraine, modeled in vitro using spreading depression (SD), as a means to develop novel therapeutic targets for episodic and chronic migraine. SD is the likely cause of migraine aura and migraine pain. It is a paroxysmal loss of neuronal function triggered by initially increased neuronal activity, which slowly propagates within susceptible brain regions. Normal brain function is exquisitely sensitive to, and relies on, coincident low-level immune signaling. Thus, neural immune signaling likely affects electrical activity of SD, and therefore migraine. Pain perception studies of SD in whole animals are fraught with difficulties, but whole animals are well suited to examine systems biology aspects of migraine since SD activates trigeminal nociceptive pathways. However, whole animal studies alone cannot be used to decipher the cellular and neural circuit mechanisms of SD. Instead, in vitro preparations where environmental conditions can be controlled are necessary. Here, it is important to recognize limitations of acute slices and distinct advantages of hippocampal slice cultures. Acute brain slices cannot reveal subtle changes in immune signaling since preparing the slices alone triggers: pro-inflammatory changes that last days, epileptiform behavior due to high levels of oxygen tension needed to vitalize the slices, and irreversible cell injury at anoxic slice centers. In contrast, we examine immune signaling in mature hippocampal slice cultures since the cultures closely parallel their in vivo counterpart with mature trisynaptic function; show quiescent astrocytes, microglia, and cytokine levels; and SD is easily induced in an unanesthetized preparation. Furthermore, the slices are long-lived and SD can be induced on consecutive days without injury, making this preparation the

  11. A Model-Based Signal Processing Approach to Nuclear Explosion Monitoring

    SciTech Connect

    Rodgers, A; Harris, D; Pasyanos, M

    2007-03-14

    This report describes research performed under Laboratory Research and Development Project 05-ERD-019, entitled ''A New Capability for Regional High-Frequency Seismic Wave Simulation in Realistic Three-Dimensional Earth Models to Improve Nuclear Explosion Monitoring''. A more appropriate title for this project is ''A Model-Based Signal Processing Approach to Nuclear Explosion Monitoring''. This project supported research for a radically new approach to nuclear explosion monitoring as well as allowed the development new capabilities in computational seismology that can contribute to NNSA/NA-22 Programs.

  12. The role of ROS signaling in cross-tolerance: from model to crop.

    PubMed

    Perez, Ilse Barrios; Brown, Patrick J

    2014-01-01

    Reactive oxygen species (ROS) are key signaling molecules produced in response to biotic and abiotic stresses that trigger a variety of plant defense responses. Cross-tolerance, the enhanced ability of a plant to tolerate multiple stresses, has been suggested to result partly from overlap between ROS signaling mechanisms. Cross-tolerance can manifest itself both as a positive genetic correlation between tolerance to different stresses (inherent cross-tolerance), and as the priming of systemic plant tolerance through previous exposure to another type of stress (induced cross-tolerance). Research in model organisms suggests that cross-tolerance could be used to benefit the agronomy and breeding of crop plants. However, research under field conditions has been scarce and critical issues including the timing, duration, and intensity of a stressor, as well as its interactions with other biotic and abiotic factors, remain to be addressed. Potential applications include the use of chemical stressors to screen for stress-resistant genotypes in breeding programs and the agronomic use of chemical inducers of plant defense for plant protection. Success of these applications will rely on improving our understanding of how ROS signals travel systemically and persist over time, and of how genetic correlations between resistance to ROS, biotic, and abiotic stresses are shaped by cooperative and antagonistic interactions within the underlying signaling pathways. PMID:25566313

  13. Ethylene Signaling Modulates Herbivore-Induced Defense Responses in the Model Legume Medicago truncatula.

    PubMed

    Paudel, Jamuna Risal; Bede, Jacqueline C

    2015-05-01

    One or more effectors in the labial saliva (LS) of generalist Noctuid caterpillars activate plant signaling pathways to modulate jasmonate (JA)-dependent defense responses; however, the exact mechanisms involved have yet to be elucidated. A potential candidate in this phytohormone interplay is the ethylene (ET) signaling pathway. We compared the biochemical and molecular responses of the model legume Medicago truncatula and the ET-insensitive skl mutant to herbivory by fourth instar Spodoptera exigua (Hübner) caterpillars with intact or impaired LS secretions. Cellular oxidative stress increases rapidly after herbivory, as evidenced by changes in oxidized-to-reduced ascorbate (ASC) and glutathione (GSH) ratios. The caterpillar-specific increase in GSH ratios and the LS-specific increase in ASC ratios are alleviated in the skl mutant, indicating that ET signaling is required. Ten hours postherbivory, markers of the JA and JA/ET pathways are differentially expressed; MtVSP is induced and MtHEL is repressed in a caterpillar LS- and ET-independent manner. In contrast, expression of the classic marker of the systemic acquired resistance pathway, MtPR1, is caterpillar LS-dependent and requires ET signaling. Caterpillar LS further suppresses the induction of JA-related trypsin inhibitor activity in an ET-dependent manner. Findings suggest that ET is involved in the caterpillar LS-dependent, salicylic acid/NPR1-mediated attenuation of JA-dependent induced responses. PMID:25608182

  14. Classification of Internal Carotid Artery Doppler Signals Using Hidden Markov Model and Wavelet Transform with Entropy

    NASA Astrophysics Data System (ADS)

    Uğuz, Harun; Kodaz, Halife

    Doppler ultrasound has been usually preferred for investigation of the artery conditions in the last two decade, since it is a non-invasive method which is not risky. In this study, a biomedical system based on Discrete Hidden Markov Model (DHMM) has been developed in order to classify the internal carotid artery Doppler signals recorded from 191 subjects (136 of them had suffered from internal carotid artery stenosis and rest of them had been healthy subjects). Developed system comprises of three stages. In the first stage, for feature extraction, obtained Doppler signals were separated to its sub-bands using Discrete Wavelet Transform (DWT). In the second stage, entropy of each sub-band was calculated using Shannon entropy algorithm to reduce the dimensionality of the feature vectors via DWT. In the third stage, the reduced features of carotid artery Doppler signals were used as input patterns of the DHMM classifier. Our proposed method reached 97.38% classification accuracy with 5 fold cross validation (CV) technique. The classification results showed that purposed method is effective for classification of internal carotid artery Doppler signals.

  15. The role of ROS signaling in cross-tolerance: from model to crop

    PubMed Central

    Perez, Ilse Barrios; Brown, Patrick J.

    2014-01-01

    Reactive oxygen species (ROS) are key signaling molecules produced in response to biotic and abiotic stresses that trigger a variety of plant defense responses. Cross-tolerance, the enhanced ability of a plant to tolerate multiple stresses, has been suggested to result partly from overlap between ROS signaling mechanisms. Cross-tolerance can manifest itself both as a positive genetic correlation between tolerance to different stresses (inherent cross-tolerance), and as the priming of systemic plant tolerance through previous exposure to another type of stress (induced cross-tolerance). Research in model organisms suggests that cross-tolerance could be used to benefit the agronomy and breeding of crop plants. However, research under field conditions has been scarce and critical issues including the timing, duration, and intensity of a stressor, as well as its interactions with other biotic and abiotic factors, remain to be addressed. Potential applications include the use of chemical stressors to screen for stress-resistant genotypes in breeding programs and the agronomic use of chemical inducers of plant defense for plant protection. Success of these applications will rely on improving our understanding of how ROS signals travel systemically and persist over time, and of how genetic correlations between resistance to ROS, biotic, and abiotic stresses are shaped by cooperative and antagonistic interactions within the underlying signaling pathways. PMID:25566313

  16. Dysregulated intracellular signaling in the striatum in a pathophysiologically grounded model of Tourette syndrome

    PubMed Central

    Rapanelli, Maximiliano; Frick, Luciana R.; Pogorelov, Vladimir; Ota, Kristie T.; Abbasi, Eeman; Ohtsu, Hiroshi; Pittenger, Christopher

    2015-01-01

    Tic disorders produce substantial morbidity, but their pathophysiology remains poorly understood. Convergent evidence suggests that dysregulation of the cortico-basal ganglia circuitry is central to the pathogenesis of tics. Tourette syndrome (TS), the most severe end of the continuum of tic disorders, is substantially genetic, but causative mutations have been elusive. We recently described a mouse model, the histidine decarboxylase (Hdc) knockout mouse, that recapitulates a rare, highly penetrant mutation found in a single family; these mice exhibit TS-like phenomenology. These animals have a global deficit in brain histamine and a consequent dysregulation of DA in the basal ganglia. Histamine modulation of DA effects is increasingly appreciated, but the mechanisms underlying this modulation remain unclear; the consequences of modest DA elevation in the context of profound HA deficiency are difficult to predict, but understanding them in the Hdc knockout mouse may provide generalizable insights into the pathophysiology of TS. Here we characterized signaling pathways in striatal cells in this model system, at baseline and after amphetamine challenge. In vivo microdialysis confirms elevated DA in Hdc-KO mice. We find dephosphorylation of Akt and its target GSK3β and activation of the MAPK signaling cascade and its target rpS6; these are characteristic of the effects of DA on D2- and D1-expressing striatal neurons, respectively. Strikingly, there is no alteration in mTOR signaling, which can be regulated by DA in both cell types. These cellular effects help elucidate striatal signaling abnormalities in a uniquely validated mouse model of TS and move towards the identification of new potential therapeutic targets for tic disorders. PMID:25464894

  17. Control of Streptococcus pyogenes virulence: modeling of the CovR/S signal transduction system.

    PubMed

    Mitrophanov, Alexander Y; Churchward, Gordon; Borodovsky, Mark

    2007-05-01

    The CovR/S system in Streptococcus pyogenes (Group A Streptococcus, or GAS), a two-component signal transduction/transcription regulation system, controls the expression of major virulence factors. The presence of a negative feedback loop distinguishes the CovR/S system from the majority of bacterial two-component systems. We developed a deterministic model of the CovR/S system consisting of eight delay differential equations. Computational experiments showed that the system possessed a unique stable steady state. The dynamical behavior of the system showed a tendency for oscillations becoming more pronounced for longer but still biochemically realistic delays resulting from reductions in the rates of translation elongation. We have devised an efficient procedure for computing the system's steady state. Further, we have shown that the signal-response curves are hyperbolic for the default parameter values. However, in experiments with randomized parameters we demonstrated that sigmoidality of signal-response curves, implying a response threshold, is not only possible, but seems to be rather typical for CovR/S-like systems even when binding of the CovR response regulator protein to a promoter is non-cooperative. We used sensitivity analysis to simplify the model in order to make it analytically tractable. The existence and uniqueness of the steady state and hyperbolicity of signal-response curves for the majority of the variables was proved for the simplified model. Also, we found that provided CovS was active, the system was insensitive to changes in the concentration of any other phosphoryl donor such as acetyl phosphate. PMID:17240398

  18. Kalman filter-based microphone array signal processing using the equivalent source model

    NASA Astrophysics Data System (ADS)

    Bai, Mingsian R.; Chen, Ching-Cheng

    2012-10-01

    This paper demonstrates that microphone array signal processing can be implemented by using adaptive model-based filtering approaches. Nearfield and farfield sound propagation models are formulated into state-space forms in light of the Equivalent Source Method (ESM). In the model, the unknown source amplitudes of the virtual sources are adaptively estimated by using Kalman filters (KFs). The nearfield array aimed at noise source identification is based on a Multiple-Input-Multiple-Output (MIMO) state-space model with minimal realization, whereas the farfield array technique aimed at speech quality enhancement is based on a Single-Input-Multiple-Output (SIMO) state-space model. Performance of the nearfield array is evaluated in terms of relative error of the velocity reconstructed on the actual source surface. Numerical simulations for the nearfield array were conducted with a baffled planar piston source. From the error metric, the proposed KF algorithm proved effective in identifying noise sources. Objective simulations and subjective experiments are undertaken to validate the proposed farfield arrays in comparison with two conventional methods. The results of objective tests indicated that the farfield arrays significantly enhanced the speech quality and word recognition rate. The results of subjective tests post-processed with the analysis of variance (ANOVA) and a post-hoc Fisher's least significant difference (LSD) test have shown great promise in the KF-based microphone array signal processing techniques.

  19. Simultaneous estimation of both hydrological and ecological parameters in an ecohydrological model by assimilating microwave signal

    NASA Astrophysics Data System (ADS)

    Sawada, Yohei; Koike, Toshio

    2014-07-01

    To improve the skill of reproducing land-atmosphere interactions in weather, seasonal, and climate prediction systems, it is necessary to simulate correctly and simultaneously the surface soil moisture (SSM) and terrestrial biomass in land surface models. Despite the performance of hydrological and ecosystem models depends highly on parameter calibration, a method for parameter estimation in ungauged areas has yet to be established. We develop an autocalibration system that can simultaneously estimate both hydrological and ecological parameters by assimilating a microwave signal that is sensitive to both SSM and terrestrial biomass. This system comprises a hydrological model that has a physically based, sophisticated soil hydrology scheme, a dynamic vegetation model that can estimate vegetation growth and senescence, and a radiative transfer model that can convert land surface condition into brightness temperatures in the microwave region. By assimilating microwave signals from the Advanced Microwave Scanning Radiometer for Earth Observing System, the system simultaneously optimizes the parameters of these models. We test this approach at three in situ observation sites under different hydroclimatic conditions. Estimated SSM exhibits good agreement with ground-based in situ observed SSM, and estimated leaf area index (LAI) is also improved by the optimization, compared with satellite-observed LAI. The root-mean-square error of SSM and LAI at all sites, estimated by the model with optimized parameters, is much less than that estimated by the model with default parameters. Using microwave satellite brightness temperature data sets, this system offers the potential to calibrate parameters of both hydrological and ecosystem models globally.

  20. Signal modeling in low coherence interference microscopy on example of rectangular grating.

    PubMed

    Xie, Weichang; Lehmann, Peter; Niehues, Jan; Tereschenko, Stanislav

    2016-06-27

    Besides the illumination wavelength also the numerical aperture (NA) of a microscope objective affects the fringe spacing in interference microscopy. Therefore, at high NA values an effective wavelength should be obtained by calibration. At step height structures both, the effective wavelength and the batwing effect strongly depend on the height-to-wavelength-ratio (HWR). Therefore, changes of the effective wavelength considering temporal and spatial coherence enable us to estimate the batwing effect in measurement results. For high NA systems and broadband illumination two different theoretical approaches for signal modeling are introduced to study the influence of the center wavelength, the temporal, and the spatial coherence of the illuminating light on measurement results of a rectangular grating. In both models diffraction is considered. While the first simulation model (Kirchhoff) is mostly analytical the second one (Richards-Wolf) is primarily numerical. Simulation results of both models show a good agreement with experimental measurement results. PMID:27410584

  1. BAYESIAN HIERARCHICAL MODELING FOR SIGNALING PATHWAY INFERENCE FROM SINGLE CELL INTERVENTIONAL DATA1

    PubMed Central

    Luo, Ruiyan; Zhao, Hongyu

    2011-01-01

    Recent technological advances have made it possible to simultaneously measure multiple protein activities at the single cell level. With such data collected under different stimulatory or inhibitory conditions, it is possible to infer the causal relationships among proteins from single cell interventional data. In this article we propose a Bayesian hierarchical modeling framework to infer the signaling pathway based on the posterior distributions of parameters in the model. Under this framework, we consider network sparsity and model the existence of an association between two proteins both at the overall level across all experiments and at each individual experimental level. This allows us to infer the pairs of proteins that are associated with each other and their causal relationships. We also explicitly consider both intrinsic noise and measurement error. Markov chain Monte Carlo is implemented for statistical inference. We demonstrate that this hierarchical modeling can effectively pool information from different interventional experiments through simulation studies and real data analysis. PMID:22162986

  2. Numerical model a graphene component for the sensing of weak electromagnetic signals

    NASA Astrophysics Data System (ADS)

    Nasswettrova, A.; Fiala, P.; Nešpor, D.; Drexler, P.; Steinbauer, M.

    2015-05-01

    The paper discusses a numerical model and provides an analysis of a graphene coaxial line suitable for sub-micron sensors of magnetic fields. In relation to the presented concept, the target areas and disciplines include biology, medicine, prosthetics, and microscopic solutions for modern actuators or SMART elements. The proposed numerical model is based on an analysis of a periodic structure with high repeatability, and it exploits a graphene polymer having a basic dimension in nanometers. The model simulates the actual random motion in the structure as the source of spurious signals and considers the pulse propagation along the structure; furthermore, the model also examines whether and how the pulse will be distorted at the beginning of the line, given the various ending versions. The results of the analysis are necessary for further use of the designed sensing devices based on graphene structures.

  3. A millimeter wave large-signal model of GaAs planar Schottky varactor diodes

    NASA Astrophysics Data System (ADS)

    Junrong, Dong; Jie, Huang; Chao, Tian; Hao, Yang; Haiying, Zhang

    2011-03-01

    A millimeter wave large-signal model of GaAs planar Schottky varactor diodes based on a physical analysis is presented. The model consists of nonlinear resistances and capacitances of the junction region and external parasitic parameters. By analyzing the characteristics of the diode under reverse and forward bias, an extraction procedure of all of the parameters is addressed. To validate the newly proposed model, the PSVDs were fabricated based on a planar process and were measured using an automatic network analyzer. Measurement shows that the model exactly represents the behavior of GaAs PSVDs under a wide bias condition from -10 to 0.6 V and for frequencies up to 40 GHz.

  4. Effects of neutrino oscillations on nucleosynthesis and neutrino signals for an 18 M⊙ supernova model

    NASA Astrophysics Data System (ADS)

    Wu, Meng-Ru; Qian, Yong-Zhong; Martínez-Pinedo, Gabriel; Fischer, Tobias; Huther, Lutz

    2015-03-01

    In this paper, we explore the effects of neutrino flavor oscillations on supernova nucleosynthesis and on the neutrino signals. Our study is based on detailed information about the neutrino spectra and their time evolution from a spherically symmetric supernova model for an 18 M⊙ progenitor. We find that collective neutrino oscillations are not only sensitive to the detailed neutrino energy and angular distributions at emission, but also to the time evolution of both the neutrino spectra and the electron density profile. We apply the results of neutrino oscillations to study the impact on supernova nucleosynthesis and on the neutrino signals from a Galactic supernova. We show that in our supernova model, collective neutrino oscillations enhance the production of rare isotopes 138La and 180Ta but have little impact on the ν p -process nucleosynthesis. In addition, the adiabatic Mikheyev-Smirnov-Wolfenstein flavor transformation, which occurs in the C /O and He shells of the supernova, may affect the production of light nuclei such as 7Li and 11B. For the neutrino signals, we calculate the rate of neutrino events in the Super-Kamiokande detector and in a hypothetical liquid argon detector. Our results suggest the possibility of using the time profiles of the events in both detectors, along with the spectral information of the detected neutrinos, to infer the neutrino mass hierarchy.

  5. A cortical vascular model for examining the specificity of the laminar BOLD signal.

    PubMed

    Markuerkiaga, Irati; Barth, Markus; Norris, David G

    2016-05-15

    Blood oxygenation level dependent (BOLD) functional MRI has been used for inferring layer specific activation in humans. However, intracortical veins perpendicular to the cortical surface are suspected to degrade the laminar specificity as they drain blood from the microvasculature and BOLD signal is carried over from lower to upper cortical layers on its way to the pial surface. In this work, a vascular model of the cortex is developed to investigate the laminar specificity of the BOLD signal for Spin Echo (SE) and Gradient Echo (GE) following the integrative model presented by Uludağ et al. (2009). The results of the simulation show that the laminar point spread function (PSF) of the BOLD signal presents similar features across all layers. The PSF for SE is highly localised whereas for GE there is a flat tail running to the pial surface, with amplitude less than a quarter of the response from the layer itself. Consequently the GE response at any layer will also contain a contribution accumulated from all lower layers. PMID:26952195

  6. Thermo-elastic wave model of the photothermal and photoacoustic signal

    SciTech Connect

    Meja, P.; Steiger, B.; Delsanto, P.P.

    1996-12-31

    By means of the thermo-elastic wave equation the dynamical propagation of mechanical stress and temperature can be described and applied to model the photothermal and photoacoustic signal. Analytical solutions exist only in particular cases. Using massively parallel computers it is possible to simulate the photothermal and photoacoustic signal in a most sufficient way. In this paper the method of local interaction simulation approach (LISA) is presented and selected examples of its application are given. The advantages of this method, which is particularly suitable for parallel processing, consist in reduced computation time and simple description of the photoacoustic signal in optical materials. The present contribution introduces the authors model, the formalism and some results in the 1 D case for homogeneous nonattenuative materials. The photoacoustic wave can be understood as a wave with locally limited displacement. This displacement corresponds to a temperature variation. Both variables are usually measured in photoacoustics and photothermal measurements. Therefore the temperature and displacement dependence on optical, elastic and thermal constants is analysed.

  7. The CNP signal is able to silence a supra threshold neuronal model

    PubMed Central

    Camera, Francesca; Paffi, Alessandra; Thomas, Alex W.; Apollonio, Francesca; D'Inzeo, Guglielmo; Prato, Frank S.; Liberti, Micaela

    2015-01-01

    Several experimental results published in the literature showed that weak pulsed magnetic fields affected the response of the central nervous system. However, the specific biological mechanisms that regulate the observed behaviors are still unclear and further scientific investigation is required. In this work we performed simulations on a neuronal network model exposed to a specific pulsed magnetic field signal that seems to be very effective in modulating the brain activity: the Complex Neuroelectromagnetic Pulse (CNP). Results show that CNP can silence the neurons of a feed-forward network for signal intensities that depend on the strength of the bias current, the endogenous noise level and the specific waveforms of the pulses. Therefore, it is conceivable that a neuronal network model responds to the CNP signal with an inhibition of its activity. Further studies on more realistic neuronal networks are needed to clarify if such an inhibitory effect on neuronal tissue may be the basis of the induced analgesia seen in humans and the antinociceptive effects seen in animals when exposed to the CNP. PMID:25972807

  8. Nonlinear model for condition monitoring of non-stationary vibration signals in ship driveline application

    NASA Astrophysics Data System (ADS)

    Cardona-Morales, O.; Avendaño, L. D.; Castellanos-Domínguez, G.

    2014-02-01

    Condition monitoring of mechanical systems is an important topic for industry since it improves machine maintenance and reduce the total associated operational cost. In this sense, vibration analysis is a useful tool for failure prevention in rotating machines, and its main challenge is to perform on-line estimation of dynamic behavior, due to non-stationary operating conditions. To this, estimation of both, amplitude and instantaneous frequency, holding most of process information should be carried out. Nevertheless, approaches for estimating those parameters require to have the shaft speed reference signal, which is not always provided in several industrial applications. In this paper, a novel Order Tracking (OT) scheme of estimation is proposed that is based on the state space model that avoids the shaft speed reference signal. The nonlinear oscillatory model designed as frequency tracker is adapted for estimating the phase and the amplitude of each particular harmonic component. Specifically, nonlinear filtering (namely, the Square-Root Cubature Kalman Filter) is used to estimate the spectral components from the vibration signal. The proposed approach is tested and compared with baseline Vold-Kalman Filtering over four different datasets. The obtained results show that proposed approach is robust and it performs with high accuracy estimation of the order component and the instantaneous frequency under different operating conditions; both allow capturing machine dynamic behavior.

  9. Reliability estimation for cutting tools based on logistic regression model using vibration signals

    NASA Astrophysics Data System (ADS)

    Chen, Baojia; Chen, Xuefeng; Li, Bing; He, Zhengjia; Cao, Hongrui; Cai, Gaigai

    2011-10-01

    As an important part of CNC machine, the reliability of cutting tools influences the whole manufacturing effectiveness and stability of equipment. The present study proposes a novel reliability estimation approach to the cutting tools based on logistic regression model by using vibration signals. The operation condition information of the CNC machine is incorporated into reliability analysis to reflect the product time-varying characteristics. The proposed approach is superior to other degradation estimation methods in that it does not necessitate any assumption about degradation paths and probability density functions of condition parameters. The three steps of new reliability estimation approach for cutting tools are as follows. First, on-line vibration signals of cutting tools are measured during the manufacturing process. Second, wavelet packet (WP) transform is employed to decompose the original signals and correlation analysis is employed to find out the feature frequency bands which indicate tool wear. Third, correlation analysis is also used to select the salient feature parameters which are composed of feature band energy, energy entropy and time-domain features. Finally, reliability estimation is carried out based on logistic regression model. The approach has been validated on a NC lathe. Under different failure threshold, the reliability and failure time of the cutting tools are all estimated accurately. The positive results show the plausibility and effectiveness of the proposed approach, which can facilitate machine performance and reliability estimation.

  10. Modeling propagation of infrasound signals observed by a dense seismic network.

    PubMed

    Chunchuzov, I; Kulichkov, S; Popov, O; Hedlin, M

    2014-01-01

    The long-range propagation of infrasound from a surface explosion with an explosive yield of about 17.6 t TNT that occurred on June 16, 2008 at the Utah Test and Training Range (UTTR) in the western United States is simulated using an atmospheric model that includes fine-scale layered structure of the wind velocity and temperature fields. Synthetic signal parameters (waveforms, amplitudes, and travel times) are calculated using parabolic equation and ray-tracing methods for a number of ranges between 100 and 800 km from the source. The simulation shows the evolution of several branches of stratospheric and thermospheric signals with increasing range from the source. Infrasound signals calculated using a G2S (ground-to-space) atmospheric model perturbed by small-scale layered wind velocity and temperature fluctuations are shown to agree well with recordings made by the dense High Lava Plains seismic network located at an azimuth of 300° from UTTR. The waveforms of calculated infrasound arrivals are compared with those of seismic recordings. This study illustrates the utility of dense seismic networks for mapping an infrasound field with high spatial resolution. The parabolic equation calculations capture both the effect of scattering of infrasound into geometric acoustic shadow zones and significant temporal broadening of the arrivals. PMID:24437743

  11. Neuroelectronics and modeling of electrical signals for monitoring and control of Parkinson's disease

    NASA Astrophysics Data System (ADS)

    Chintakuntla, Ritesh R.; Abraham, Jose K.; Varadan, Vijay K.

    2009-03-01

    The brain and the human nervous system are perhaps the most researched but least understood components of the human body. This is so because of the complex nature of its working and the high density of functions. The monitoring of neural signals could help one better understand the working of the brain and newer recording and monitoring methods have been developed ever since it was discovered that the brain communicates internally by means of electrical pulses. Neuroelectronics is the field which deals with the interface between electronics or semiconductors to living neurons. This includes monitoring of electrical activity from the brain as well as the development of feedback devices for stimulation of parts of the brain for treatment of disorders. In this paper these electrical signals are modeled through a nano/microelectrode arrays based on the electronic equivalent model using Cadence PSD 15.0. The results were compared with those previously published models such as Kupfmuller and Jenik's model, McGrogan's Neuron Model which are based on the Hodgkin and Huxley model. We have developed and equivalent circuit model using discrete passive components to simulate the electrical activity of the neurons. The simulated circuit can be easily be modified by adding some more ionic channels and the results can be used to predict necessary external stimulus needed for stimulation of neurons affected by the Parkinson's disease (PD). Implementing such a model in PD patients could predict the necessary voltages required for the electrical stimulation of the sub-thalamus region for the control tremor motion.

  12. Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

    PubMed Central

    Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

    2013-01-01

    Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

  13. Molecular therapy targeting Sonic hedgehog and hepatocyte growth factor signaling in a mouse model of medulloblastoma.

    PubMed

    Coon, Valerie; Laukert, Tamara; Pedone, Carolyn A; Laterra, John; Kim, K Jin; Fults, Daniel W

    2010-09-01

    The use of genetically engineered mice has provided insights into the molecular pathogenesis of the pediatric brain tumor medulloblastoma and revealed promising therapeutic targets. Ectopic expression of Sonic hedgehog (Shh) in cerebellar neural progenitor cells induces medulloblastomas in mice, and coexpression of hepatocyte growth factor (HGF) enhances Shh-induced tumor formation. To determine whether Shh + HGF-driven medulloblastomas were responsive to Shh signaling blockade and whether treatment response could be enhanced by combination therapy targeting both HGF and Shh signaling pathways, we carried out a survival study in mice. We induced medulloblastomas by retrovirus-mediated expression of Shh and HGF, after which we treated the mice systemically with (a) HGF-neutralizing monoclonal antibody L2G7, (b) Shh signaling inhibitor cyclopamine, (c) Shh-neutralizing monoclonal antibody 5E1, (d) L2G7 + cyclopamine, or (e) L2G7 + 5E1. We report that monotherapy targeting either HGF signaling or Shh signaling prolonged survival and that anti-HGF therapy had a more durable response than Shh-targeted therapy. The effect of L2G7 + 5E1 combination therapy on cumulative survival was equivalent to that of L2G7 monotherapy and that of L2G7 + cyclopamine therapy was worse. The principal mechanism by which Shh- and HGF-targeted therapies inhibited tumor growth was a potent apoptotic death response in tumor cells, supplemented by a weaker suppressive effect on proliferation. Our observation that combination therapy either failed to improve or even reduced survival in mice bearing Shh + HGF-induced medulloblastomas compared with monotherapy underscores the importance of preclinical testing of molecular-targeted therapies in animal models of tumors in which the targeted pathways are known to be active. PMID:20807782

  14. Molecular Therapy Targeting Sonic Hedgehog and Hepatocyte Growth Factor Signaling in a Mouse Model of Medulloblastoma

    PubMed Central

    Coon, Valerie; Laukert, Tamara; Pedone, Carolyn A.; Laterra, John; Kim, K. Jin; Fults, Daniel W.

    2010-01-01

    The use of genetically engineered mice has provided insights into the molecular pathogenesis of the pediatric brain tumor medulloblastoma and revealed promising therapeutic targets. Ectopic expression of Sonic Hedgehog (Shh) in cerebellar neural progenitor cells induces medulloblastomas in mice, and coexpression of hepatocyte growth factor (HGF) enhances Shh-induced tumor formation. To determine whether Shh+HGF–driven medulloblastomas were responsive to Shh signaling blockade and whether treatment response could be enhanced by combination therapy targeting both HGF and Shh signaling pathways, we carried out a survival study in mice. We induced medulloblastomas by retrovirus-mediated expression of Shh and HGF, after which we treated the mice systemically with (a) HGF-neutralizing monoclonal antibody L2G7, (b) Shh signaling inhibitor cyclopamine, (c) Shh-neutralizing monoclonal antibody 5E1, (d) L2G7+cyclopamine, or (e) L2G7+5E1. We report that monotherapy targeting either HGF signaling or Shh signaling prolonged survival and that anti-HGF therapy had a more durable response than Shh-targeted therapy. The effect of L2G7+5E1 combination therapy on cumulative survival was equivalent to that of L2G7 monotherapy and that of L2G7+cyclopamine therapy was worse. The principal mechanism by which Shh- and HGF-targeted therapies inhibited tumor growth was a potent apoptotic death response in tumor cells, supplemented by a weaker suppressive effect on proliferation. Our observation that combination therapy either failed to improve or even reduced survival in mice bearing Shh+HGF induced medulloblastomas compared with monotherapy underscores the importance of preclinical testing of molecular-targeted therapies in animal models of tumors in which the targeted pathways are known to be active. PMID:20807782

  15. Improving medical diagnostic accuracy of ultrasound Doppler signals by combining neural network models.

    PubMed

    Ubeyli, Elif Derya; Güler, Inan

    2005-07-01

    There are a number of different quantitative models that can be used in a medical diagnostic decision support system including parametric methods (linear discriminant analysis or logistic regression), nonparametric models (k nearest neighbor or kernel density) and several neural network models. The complexity of the diagnostic task is thought to be one of the prime determinants of model selection. Unfortunately, there is no theory available to guide model selection. This paper illustrates the use of combined neural network models to guide model selection for diagnosis of ophthalmic and internal carotid arterial disorders. The ophthalmic and internal carotid arterial Doppler signals were decomposed into time-frequency representations using discrete wavelet transform and statistical features were calculated to depict their distribution. The first-level networks were implemented for the diagnosis of ophthalmic and internal carotid arterial disorders using the statistical features as inputs. To improve diagnostic accuracy, the second-level networks were trained using the outputs of the first-level networks as input data. The combined neural network models achieved accuracy rates which were higher than that of the stand-alone neural network models. PMID:15780863

  16. Wnt signaling pathway improves central inhibitory synaptic transmission in a mouse model of Duchenne muscular dystrophy.

    PubMed

    Fuenzalida, Marco; Espinoza, Claudia; Pérez, Miguel Ángel; Tapia-Rojas, Cheril; Cuitino, Loreto; Brandan, Enrique; Inestrosa, Nibaldo C

    2016-02-01

    The dystrophin-associated glycoprotein complex (DGC) that connects the cytoskeleton, plasma membrane and the extracellular matrix has been related to the maintenance and stabilization of channels and synaptic receptors, which are both essential for synaptogenesis and synaptic transmission. The dystrophin-deficient (mdx) mouse model of Duchenne muscular dystrophy (DMD) exhibits a significant reduction in hippocampal GABA efficacy, which may underlie the altered synaptic function and abnormal hippocampal long-term plasticity exhibited by mdx mice. Emerging studies have implicated Wnt signaling in the modulation of synaptic efficacy, neuronal plasticity and cognitive function. We report here that the activation of the non-canonical Wnt-5a pathway and Andrographolide, improves hippocampal mdx GABAergic efficacy by increasing the number of inhibitory synapses and GABA(A) receptors or GABA release. These results indicate that Wnt signaling modulates GABA synaptic efficacy and could be a promising novel target for DMD cognitive therapy. PMID:26626079

  17. Modeling and estimation of signal-dependent noise in hyperspectral imagery.

    PubMed

    Meola, Joseph; Eismann, Michael T; Moses, Randolph L; Ash, Joshua N

    2011-07-20

    The majority of hyperspectral data exploitation algorithms are developed using statistical models for the data that include sensor noise. Hyperspectral data collected using charge-coupled devices or other photon detectors have sensor noise that is directly dependent on the amplitude of the signal collected. However, this signal dependence is often ignored. Additionally, the statistics of the noise can vary spatially and spectrally as a result of camera characteristics and the calibration process applied to the data. Here, we examine the expected noise characteristics of both raw and calibrated visible/near-infrared hyperspectral data and provide a method for estimating the noise statistics using calibration data or directly from the imagery if calibration data is unavailable. PMID:21772364

  18. Modeling random telegraph signal noise in CMOS image sensor under low light based on binomial distribution

    NASA Astrophysics Data System (ADS)

    Yu, Zhang; Xinmiao, Lu; Guangyi, Wang; Yongcai, Hu; Jiangtao, Xu

    2016-07-01

    The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result, the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated, and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures. Project supported by the National Natural Science Foundation of China (Grant Nos. 61372156 and 61405053) and the Natural Science Foundation of Zhejiang Province of China (Grant No. LZ13F04001).

  19. Seesaw majoron model of neutrino mass and novel signals in Higgs boson production at LEP

    NASA Astrophysics Data System (ADS)

    Díaz, Marco A.; García-Jareño, M. A.; Restrepo, Diego A.; Valle, José W. F.

    1998-08-01

    We perform a careful study of the neutral scalar sector of a model which includes a singlet, a doublet, and a triplet scalar field under SU(2). This model is motivated by neutrino physics, since it is simply the most general version of the seesaw model of neutrino mass generation through spontaneous violation of lepton number. The neutral Higgs sector contains three CP-even and one massive CP-odd Higgs boson A, in addition to the massless CP-odd mojoron J. The weakly interacting majoron remains massless if the breaking of lepton number symmetry is purely spontaneous. We show that the massive CP-odd Higgs boson may invisibly decay to three majorons, as well as to a CP-even Higgs H boson plus a majoron. We consider the associated Higgs production e+e- → Z → HA followed by invisible decays A → JJJ and H → JJ and derive the corresponding limits on masses and coupling that follow from LEP I precision measurements of the invisible Z width. We also study a novel b overlinebb overlinebp T signal predicted by the model, analyze the background and perform a Monte Carlo simulation of the signal in order to illustrate the limits on Higgs boson mass, couplings and branching ratios that follow from that.

  20. Increased visceral fat mass and insulin signaling in colitis-related colon carcinogenesis model mice.

    PubMed

    Miyamoto, Shingo; Tanaka, Takuji; Murakami, Akira

    2010-01-27

    Leptin, a pleiotropic hormone regulating food intake and metabolism, plays an important role in the regulation of inflammation and immunity. We previously demonstrated that serum leptin levels are profoundly increased in mice which received azoxymethane (AOM) and dextran sulfate sodium (DSS) as tumor-initiator and -promoter, respectively, in a colon carcinogenesis model. In this study, we attempted to address underlying mechanism whereby leptin is up-regulated in this rodent model. Five-week-old male ICR mice were given a single intraperitoneal injection of AOM (week 0), followed by 1% DSS in drinking water for 7 days. Thereafter, the weights of visceral fats and the serum concentration of leptin were determined at week 20. Of interest, the relative epididymal fat pad and mesenteric fat weights, together with serum leptin levels in the AOM and/or DSS-treated mice were markedly increased compared to that in untreated mice. In addition, leptin protein production in epididymal fat pad with AOM/DSS-treated mice was 4.7-fold higher than that of control. Further, insulin signaling molecules, such as protein kinase B (Akt), S6, mitogen-activate protein kinase/extracellular signaling-regulated kinase 1/2, and extracellular signaling-regulated kinase 1/2, were concomitantly activated in epididymal fat of AOM/DSS-treated mice. This treatment also increased the serum insulin and IGF-1 levels. Taken together, our results suggest that higher levels of serum insulin and IGF-1 promote the insulin signaling in epididymal fat and thereby increasing serum leptin, which may play an crucial role in, not only obesity-related, but also -independent colon carcinogenesis. PMID:19931517

  1. Modeling the Failure of Magmatic Foams and Application to Infrasonic Signals at Stromboli Volcano, Italy

    NASA Astrophysics Data System (ADS)

    Baker, D. R.; O'Shaughnessy, C. A.; Brun, F.; Mancini, L.; Fife, J.

    2014-12-01

    The failure of magmatic foams appears to be a fundamental eruption process at open-conduit, basaltic volcanoes. We applied the fiber bundle model using global load sharing to model the failure of magmatic foams. The fiber strengths in the model were taken from bubble wall widths measured in four computer-simulated foams and by X-ray tomographic microscopy in three foams produced in the laboratory by heating hydrated basaltic glasses at 1 atm. to 1200 °C. The strengths of the modeled foams were calibrated based upon the correlation of the strength of one foam with published experimental data. The fiber bundle model successfully reproduced measured tensile strengths of porous volcanic rocks studied by other researchers and confirms published findings of the primary importance of foam porosity, as well as the secondary importance of structural details that affect the number and size of bubble walls and permeability. The success of the fiber bundle model in reproducing foam strengths encouraged us to compare its predictions with infrasonic measurements associated with bubbles at Stromboli (Italy). We found that within uncertainty the power-law exponents of the infrasonic energies and of the fiber bundle model energies are in agreement. They both show a cross-over from an exponent of 5/2 associated with the bursting of small bubbles in the infrasonic measurements to an exponent of 3/2 for normal Strombolian eruptions associated with infrasonic signals from meter-scale bubbles. The infrasonic signals for major explosions and a paroxysmal eruption at Stromboli fall near the extrapolation of the power law defined by the low-amplitude, bubble bursting events. The measurement of small-amplitude infrasonic events at Stromboli thus appear useful in predicting the recurrence interval of paroxysmal eruptions at this volcano and may also provide a tool that uses common, small-amplitude infrasonic events to constrain the frequency of larger eruptions at other volcanoes.

  2. An accelerated failure time model for investigating pedestrian crossing behavior and waiting times at signalized intersections.

    PubMed

    Yang, Xiaobao; Abdel-Aty, Mohamed; Huan, Mei; Peng, Yichuan; Gao, Ziyou

    2015-09-01

    The waiting process is crucial to pedestrians in the street-crossing behavior. Once pedestrians terminate their waiting behavior during the red light period, they would cross against the red light and put themselves in danger. A joint hazard-based duration model is developed to investigate the effect of various covariates on pedestrian crossing behavior and to estimate pedestrian waiting times at signalized intersections. A total of 1181 pedestrians approaching the intersections during red light periods were observed in Beijing, China. Pedestrian crossing behaviors are classified into immediate crossing behavior and waiting behavior. The probability and effect of various covariates for pedestrians' immediate crossing behavior are identified by a logit model. Four accelerated failure time duration models based on the exponential, Weibull, lognormal and log-logistic distributions are proposed to examine the significant risk factors affecting duration times for pedestrians' waiting behavior. A joint duration model is developed to estimate pedestrian waiting times. Moreover, unobserved heterogeneity is considered in the proposed model. The results indicate that the Weibull AFT model with shared frailty is appropriate for modelling pedestrian waiting durations. Failure to account for heterogeneity would significantly underestimate the effects of covariates on waiting duration times. The proposed model provides a better understanding of pedestrian crossing behavior and more accurate estimation of pedestrian waiting times. It may be applicable in traffic system analysis in developing countries with high flow of mixed traffic. PMID:26072184

  3. Heterogeneous cellular automata model for straight-through bicycle traffic at signalized intersection

    NASA Astrophysics Data System (ADS)

    Ren, Gang; Jiang, Hang; Chen, Jingxu; Huang, Zhengfeng; Lu, Lili

    2016-06-01

    This paper presents a cellular automata (CA) model to elucidate the straight-through movements of the heterogeneous bicycle traffic at signalized intersection. The CA model, via simulation, particularly exposits the dispersion phenomenon existing in the straight-through bicycle traffic. The nonlane-based cycling behavior and diverse bicycle properties are also incorporated in the CA model. A series of simulations are conducted to reveal the travel process, bicycles interaction and influence of the dispersion phenomenon. The simulation results show that the dispersion phenomenon significantly results in more bicycles interactions in terms of spilling maneuvers and overtaking maneuvers during the straight-through movements. Meanwhile, the dispersion phenomenon could contribute to the efficiency of the bicycle traffic, and straight-through bicycles need less time to depart the intersection under the circumstance of dispersion phenomenon. The simulation results are able to provide specific guideline for reasonably utilizing the dispersion phenomenon to improve the operational efficiency of straight-through bicycle traffic.

  4. The aerodynamic costs of warning signals in palatable mimetic butterflies and their distasteful models.

    PubMed Central

    Srygley, Robert B.

    2004-01-01

    Bates hypothesized that some butterfly species that are palatable gain protection from predation by appearing similar to distasteful butterflies. When undisturbed, distasteful butterflies fly slowly and in a straight line, and palatable Batesian mimics also adopt this nonchalant behaviour. When seized by predators, distasteful butterflies are defended by toxic or nauseous chemicals. Lacking chemical defences, Batesian mimics depend on flight to escape attacks. Here, I demonstrate that flight in warning-coloured mimetic butterflies and their distasteful models is more costly than in closely related non-mimetic butterflies. The increased cost is the result of differences in both wing shape and kinematics. Batesian mimics and their models slow the angular velocity of their wings to enhance the colour signal but at an aerodynamic cost. Moreover, the design for flight in Batesian mimics has an additional energetic cost over that of its models. The added cost may cause Batesian mimics to be rare, explaining a general pattern that Bates first observed. PMID:15156916

  5. Modeling and analysis of early events in T-lymphocyte antigen-activated intracellular-signaling pathways

    NASA Astrophysics Data System (ADS)

    Zheng, Yanan; Balakrishnan, Venkataramanan; Buzzard, Greg; Geahlen, Robert; Harrison, Marietta; Rundell, Ann

    2005-12-01

    The T-cell antigen-activated signaling pathway is a highly regulated intracellular biochemical system that is crucial for initiating an appropriate adaptive immune response. To improve the understanding of the complex regulatory mechanisms controlling the early events in T-cell signaling, a detailed mathematical model was developed that utilizes ordinary differential equations to describe chemical reactions of the signaling pathway. The model parameter values were constrained by experimental data on the activation of a specific signaling intermediate and indicated an initial rapid cascade of phosphorylation events followed by a comparatively slow signal downregulation. Nonlinear analysis of the model suggested that thresholding and bistability occur as a result of the embedded positive and negative feedback loops within the model. These nonlinear system properties may enhance the T-cell receptor specificity and provide sub-threshold noise filtering with switch-like behavior to ensure proper cell response. Additional analysis using a reduced second-order model led to further understanding of the observed system behavior. Moreover, the interactions between the positive and negative feedback loops enabled the model to exhibit, among a variety of other feasible dynamics, a sustained oscillation that corresponds to a stable limit cycle in the two-dimensional phase plane. Quantitative analysis in this paper has helped identify potential regulatory mechanisms in the early T-cell signaling events. This integrated approach provides a framework to quantify and discover the ensemble of interconnected T-cell antigen-activated signaling pathways from limited experimental data.

  6. The role of TWEAK/Fn14 signaling in the MPTP-model of Parkinson's disease.

    PubMed

    Mustafa, S; Martin, H L; Burkly, L; Costa, A; Martins, M L; Schwaninger, M; Teismann, P

    2016-04-01

    The tumor necrosis factor like weak inducer of apoptosis (TWEAK) and its receptor, fibroblast growth factor-inducible 14 (Fn14), mediate inflammation and neuronal apoptosis in cerebral edema, ischemic stroke and multiple sclerosis. The downstream effectors and pathways linked to TWEAK-Fn14 signaling are strongly implicated in the pathology of Parkinson's disease (PD), thus indicating a putative role for TWEAK/Fn14 signaling in PD neurodegeneration. Using the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) mouse model, we aimed to determine whether genetic ablation or pharmacologic mitigation of the TWEAK protein and its Fn14 receptor affected substantia nigra and striatum Parkinsonian pathology. Changes in endogenous TWEAK protein expression were also quantified in tissue from both MPTP-treated mice and PD human samples. TWEAK protein expression was transiently increased in the striatal tissue but remained unaltered in substantia nigra tissue of MPTP-treated mice. There was also no change of TWEAK protein levels in the substantia nigra or the striatum of human PD patients as compared to matched control subjects. Mitigating the effects of endogenous TWEAK protein using neutralizing antibody did affect MPTP-mediated neurotoxicity in the substantia nigra using the sub-acute model of MPTP (30mg/kg i.p. over five consecutive days). Neither TWEAK nor Fn14 genetic ablation led to attenuation of MPTP-toxicity in the acute model. These findings suggest that TWEAK signaling might be an aspect of MPTP-mediated neuropathology and be involved in the overall neurodegenerative pathology of PD. PMID:26808775

  7. BDNF signaling contributes to oral cancer pain in a preclinical orthotopic rodent model

    PubMed Central

    Chodroff, Leah; Bendele, Michelle; Valenzuela, Vanessa; Henry, Michael

    2016-01-01

    The majority of patients with oral cancer report intense pain that is only partially managed by current analgesics. Thus, there is a strong need to study mechanisms as well as develop novel analgesics for oral cancer pain. Current study employed an orthotopic tongue cancer model with molecular and non-reflexive behavioral assays to determine possible mechanisms of oral cancer pain. Human oral squamous cell carcinoma cells line, HSC2, was injected into the tongue of male athymic mice and tumor growth was observed by day 6. Immunohistological analyses revealed a well-differentiated tumor with a localized immune response and pronounced sensory and sympathetic innervation and vascularization. The tumor expressed TMPRSS2, a protein previously reported with oral squamous cell carcinoma. ATF3 expression in trigeminal ganglia was not altered by tumor growth. Molecular characterization of the model demonstrated altered expression of several pain-related genes, out of which up-regulation of BDNF was most striking. Moreover, BDNF protein expression in trigeminal ganglia neurons was increased and inhibition of BDNF signaling with a tyrosine kinase B antagonist, ANA-12, reversed pain-like behaviors induced by the oral tumor. Oral squamous cell carcinoma tumor growth was also associated with a reduction in feeding, mechanical hypersensitivity in the face, as well as spontaneous pain behaviors as measured by the conditioned place preference test, all of which were reversed by analgesics. Interestingly, injection of HSC2 into the hindpaw did not reproduce this spectrum of pain behaviors; nor did injection of a colonic cancer cell line into the tongue. Taken together, this orthotopic oral cancer pain model reproduces the spectrum of pain reported by oral cancer patients, including higher order cognitive changes, and demonstrates that BDNF signaling constitutes a novel mechanism by which oral squamous cell carcinoma induces pain. Identification of the key role of tyrosine kinase B

  8. Modeling the Intra- and Extracellular Cytokine Signaling Pathway under Heat Stroke in the Liver

    PubMed Central

    Rodriguez-Fernandez, Maria; Grosman, Benyamin; Yuraszeck, Theresa M.; Helwig, Bryan G.; Leon, Lisa R.; Doyle III, Francis J.

    2013-01-01

    Heat stroke (HS) is a life-threatening illness induced by prolonged exposure to a hot environment that causes central nervous system abnormalities and severe hyperthermia. Current data suggest that the pathophysiological responses to heat stroke may not only be due to the immediate effects of heat exposure per se but also the result of a systemic inflammatory response syndrome (SIRS). The observation that pro- (e.g., IL-1) and anti-inflammatory (e.g., IL-10) cytokines are elevated concomitantly during recovery suggests a complex network of interactions involved in the manifestation of heat-induced SIRS. In this study, we measured a set of circulating cytokine/soluble cytokine receptor proteins and liver cytokine and receptor mRNA accumulation in wild-type and tumor necrosis factor (TNF) receptor knockout mice to assess the effect of neutralization of TNF signaling on the SIRS following HS. Using a systems approach, we developed a computational model describing dynamic changes (intra- and extracellular events) in the cytokine signaling pathways in response to HS that was fitted to novel genomic (liver mRNA accumulation) and proteomic (circulating cytokines and receptors) data using global optimization. The model allows integration of relevant biological knowledge and formulation of new hypotheses regarding the molecular mechanisms behind the complex etiology of HS that may serve as future therapeutic targets. Moreover, using our unique modeling framework, we explored cytokine signaling pathways with three in silico experiments (e.g. by simulating different heat insult scenarios and responses in cytokine knockout strains in silico). PMID:24039931

  9. Calculation of signal-to-noise ratio (SNR) of infrared detection system based on MODTRAN model

    NASA Astrophysics Data System (ADS)

    Lu, Xue; Li, Chuang; Fan, Xuewu

    2013-09-01

    Signal-to-noise ratio (SNR) is an important parameter of infrared detection system. SNR of infrared detection system is determined by the target infrared radiation, atmospheric transmittance, background infrared radiation and the detector noise. The infrared radiation flux in the atmosphere is determined by the selective absorption of the gas molecules, the atmospheric environment, and the transmission distance of the radiation, etc, so the atmospheric transmittance and infrared radiance flux are intricate parameters. A radiometric model for the calculation of SNR of infrared detection system is developed and used to evaluate the effects of various parameters on signal-to-noise ratio (SNR). An atmospheric modeling tool, MODTRAN, is used to model wavelength-dependent atmospheric transmission and sky background radiance. Then a new expression of SNR is deduced. Instead of using constants such as average atmospheric transmission and average wavelength in traditional method, it uses discrete values for atmospheric transmission and sky background radiance. The integrals in general expression of SNR are converted to summations. The accuracy of SNR obtained from the new method can be improved. By adopting atmospheric condition of the 1976 US standard, no clouds urban aerosols, fall-winter aerosol profiles, the typical spectrum characters of sky background radiance and transmittance are computed by MODTRON. Then the operating ranges corresponding to the threshold quantity of SNR are calculated with the new method. The calculated operating ranges are more close to the measured operating range than those calculated with the traditional method.

  10. Model-free approach to optimal signal light timing for system-wide traffic control

    SciTech Connect

    Spall, J.C.; Chin, D.C.

    1994-12-31

    A long-standing problem in traffic engineering is to optimize the flow of vehicles through a given road network. Improving the timing of the traffic signals at intersections in the network is generally the most powerful and cost-effective means of achieving this goal. However, because of the many complex aspects of a traffic system-human behavioral considerations, vehicle flow interactions within the network, weather effects, traffic accidents, long-term (e.g., seasonal) variation, etc.-it has been notoriously difficult to determine the optimal signal light timing. This is especially the case on a system- wide (multiple intersection) basis. Much of this difficulty has stemmed from the need to build extremely complex open-loop models of the traffic dynamics as a component of the control strategy. This paper presents a fundamentally different approach for optimal light timing that eliminates the need for such an open-loop model. The approach is based on a neural network (or other function approximator) serving as the basis for the control law, with the weight estimation occurring in closed-loop mode via the simultaneous perturbation stochastic approximation (SPSA) algorithm. Since the SPSA algorithm requires only loss function measurements (no gradients of the loss function), there is no open-loop model required for the weight estimation. The approach is illustrated by simulation on a six-intersection network with moderate congestion and stochastic, nonlinear effects.

  11. Bioelectrical Signals and Ion Channels in the Modeling of Multicellular Patterns and Cancer Biophysics

    PubMed Central

    Cervera, Javier; Alcaraz, Antonio; Mafe, Salvador

    2016-01-01

    Bioelectrical signals and ion channels are central to spatial patterns in cell ensembles, a problem of fundamental interest in positional information and cancer processes. We propose a model for electrically connected cells based on simple biological concepts: i) the membrane potential of a single cell characterizes its electrical state; ii) the long-range electrical coupling of the multicellular ensemble is realized by a network of gap junction channels between neighboring cells; and iii) the spatial distribution of an external biochemical agent can modify the conductances of the ion channels in a cell membrane and the multicellular electrical state. We focus on electrical effects in small multicellular ensembles, ignoring slow diffusional processes. The spatio-temporal patterns obtained for the local map of cell electric potentials illustrate the normalization of regions with abnormal cell electrical states. The effects of intercellular coupling and blocking of specific channels on the electrical patterns are described. These patterns can regulate the electrically-induced redistribution of charged nanoparticles over small regions of a model tissue. The inclusion of bioelectrical signals provides new insights for the modeling of cancer biophysics because collective multicellular states show electrical coupling mechanisms that are not readily deduced from biochemical descriptions at the individual cell level. PMID:26841954

  12. Bioelectrical Signals and Ion Channels in the Modeling of Multicellular Patterns and Cancer Biophysics.

    PubMed

    Cervera, Javier; Alcaraz, Antonio; Mafe, Salvador

    2016-01-01

    Bioelectrical signals and ion channels are central to spatial patterns in cell ensembles, a problem of fundamental interest in positional information and cancer processes. We propose a model for electrically connected cells based on simple biological concepts: i) the membrane potential of a single cell characterizes its electrical state; ii) the long-range electrical coupling of the multicellular ensemble is realized by a network of gap junction channels between neighboring cells; and iii) the spatial distribution of an external biochemical agent can modify the conductances of the ion channels in a cell membrane and the multicellular electrical state. We focus on electrical effects in small multicellular ensembles, ignoring slow diffusional processes. The spatio-temporal patterns obtained for the local map of cell electric potentials illustrate the normalization of regions with abnormal cell electrical states. The effects of intercellular coupling and blocking of specific channels on the electrical patterns are described. These patterns can regulate the electrically-induced redistribution of charged nanoparticles over small regions of a model tissue. The inclusion of bioelectrical signals provides new insights for the modeling of cancer biophysics because collective multicellular states show electrical coupling mechanisms that are not readily deduced from biochemical descriptions at the individual cell level. PMID:26841954

  13. Synthesis of the System Modeling and Signal Detecting Circuit of a Novel Vacuum Microelectronic Accelerometer

    PubMed Central

    Li, Dongling; Wen, Zhiyu; Wen, Zhongquan; He, Xuefeng; Yang, Yinchuan; Shang, Zhengguo

    2009-01-01

    A novel high-precision vacuum microelectronic accelerometer has been successfully fabricated and tested in our laboratory. This accelerometer has unique advantages of high sensitivity, fast response, and anti-radiation stability. It is a prototype intended for navigation applications and is required to feature micro-g resolution. This paper briefly describes the structure and working principle of our vacuum microelectronic accelerometer, and the mathematical model is also established. The performances of the accelerometer system are discussed after Matlab modeling. The results show that, the dynamic response of the accelerometer system is significantly improved by choosing appropriate parameters of signal detecting circuit, and the signal detecting circuit is designed. In order to attain good linearity and performance, the closed-loop control mode is adopted. Weak current detection technology is studied, and integral T-style feedback network is used in I/V conversion, which will eliminate high-frequency noise at the front of the circuit. According to the modeling parameters, the low-pass filter is designed. This circuit is simple, reliable, and has high precision. Experiments are done and the results show that the vacuum microelectronic accelerometer exhibits good linearity over -1 g to +1 g, an output sensitivity of 543 mV/g, and a nonlinearity of 0.94 %. PMID:22408515

  14. Numerical focusing methods for full field OCT: a comparison based on a common signal model.

    PubMed

    Kumar, Abhishek; Drexler, Wolfgang; Leitgeb, Rainer A

    2014-06-30

    In this paper a theoretical model of the full field swept source (FF SS) OCT signal is presented based on the angular spectrum wave propagation approach which accounts for the defocus error with imaging depth. It is shown that using the same theoretical model of the signal, numerical defocus correction methods based on a simple forward model (FM) and inverse scattering (IS), the latter being similar to interferometric synthetic aperture microscopy (ISAM), can be derived. Both FM and IS are compared quantitatively with sub-aperture based digital adaptive optics (DAO). FM has the least numerical complexity, and is the fastest in terms of computational speed among the three. SNR improvement of more than 10 dB is shown for all the three methods over a sample depth of 1.5 mm. For a sample with non-uniform refractive index with depth, FM and IS both improved the depth of focus (DOF) by a factor of 7x for an imaging NA of 0.1. DAO performs the best in case of non-uniform refractive index with respect to DOF improvement by 11x. PMID:24977860

  15. Shared signaling networks active in B cells isolated from genetically distinct mouse models of lupus

    PubMed Central

    Wu, Tianfu; Qin, Xiangmei; Kurepa, Zoran; Kumar, Kirthi Raman; Liu, Kui; Kanta, Hasna; Zhou, Xin J.; Satterthwaite, Anne B.; Davis, Laurie S.; Mohan, Chandra

    2007-01-01

    Though B cells play key roles in lupus pathogenesis, the molecular circuitry and its dysregulation in these cells as disease evolves remain poorly understood. To address this, a comprehensive scan of multiple signaling axes using multiplexed Western blotting was undertaken in several different murine lupus strains. PI3K/AKT/mTOR (mTOR, mammalian target of rapamycin), MEK1/Erk1/2, p38, NF-κB, multiple Bcl-2 family members, and cell-cycle molecules were observed to be hyperexpressed in lupus B cells in an age-dependent and lupus susceptibility gene–dose–dependent manner. Therapeutic targeting of the AKT/mTOR axis using a rapamycin (sirolimus) derivative ameliorated the serological, cellular, and pathological phenotypes associated with lupus. Surprisingly, the targeting of this axis was associated with the crippling of several other signaling axes. These studies reveal that lupus pathogenesis is contingent upon the activation of an elaborate network of signaling cascades that is shared among genetically distinct mouse models and raise hope that targeting pivotal nodes in these networks may offer therapeutic benefit. PMID:17641780

  16. Coupling vs decoupling approaches for PDE/ODE systems modeling intercellular signaling

    NASA Astrophysics Data System (ADS)

    Carraro, Thomas; Friedmann, Elfriede; Gerecht, Daniel

    2016-06-01

    We consider PDE/ODE systems for the simulation of intercellular signaling in multicellular environments. The intracellular processes for each cell described here by ODEs determine the long-time dynamics, but the PDE part dominates the solving effort. Thus, it is not clear if commonly used decoupling methods can outperform a coupling approach. Based on a sensitivity analysis, we present a systematic comparison between coupling and decoupling approaches for this class of problems and show numerical results. For biologically relevant configurations of the model, our quantitative study shows that a coupling approach performs much better than a decoupling one.

  17. A discussion of observation model, error sources and signal size for spaceborne gravitational gradiometry

    NASA Technical Reports Server (NTRS)

    Rummel, R.; Koop, R.; Schrama, E. J. O.

    1989-01-01

    Various space concepts were discussed during the past 20 years for a global improvement of the knowledge of the earth's gravity field. The concepts reach from high-low and low-low satellite-to-satellite tracking via tethered satellite gradiometers to sophisticated superconducting gradiometers. The purpose is to show that starting from one basic equation three criteria are sufficient to typify the various concepts and define the underlying observation model. Furthermore the different error sources, in particular, the time varying part of self-gravitation, and the expected signal size of all six gravity gradient components shall be discussed.

  18. User's guide for a large signal computer model of the helical traveling wave tube

    NASA Technical Reports Server (NTRS)

    Palmer, Raymond W.

    1992-01-01

    The use is described of a successful large-signal, two-dimensional (axisymmetric), deformable disk computer model of the helical traveling wave tube amplifier, an extensively revised and operationally simplified version. We also discuss program input and output and the auxiliary files necessary for operation. Included is a sample problem and its input data and output results. Interested parties may now obtain from the author the FORTRAN source code, auxiliary files, and sample input data on a standard floppy diskette, the contents of which are described herein.

  19. Retinoic acid signalling in gastrointestinal parasite infections: lessons from mouse models.

    PubMed

    Hurst, R J M; Else, K J

    2012-07-01

    Retinoic acid or vitamin A is important for an extensive range of biological processes, including immunomodulatory functions, however, its role in gastrointestinal parasite infections is not yet clear. Despite this, parasite infected individuals are often supplemented with vitamin A, given the co-localised prevalence of parasitic infections and vitamin deficiencies. Therefore, it is important to understand the impact of this vitamin on the immune responses to gastrointestinal parasites. Here, we review data regarding the role of retinoic acid signalling in mouse models of intestinal nematode infection, with a view to understanding better the practice of giving vitamin A supplements to worm-infected people. PMID:22443219

  20. Modeling and detection of external signals from small apertures in wire shields

    NASA Astrophysics Data System (ADS)

    Jones, Brian Allen

    Detecting, locating, and identifying wire faults are problems that have been studied from many approaches. The effects of wiring faults are widely seen in aging aircraft, where wiring faults can cause tragic outcomes. Common tools such as reflectometry work well to reveal short and open circuits. In some cases, reflectometry can also detect areas where the cable has significant cable damage. As a fault becomes smaller, reflectometry methods cannot discriminate between the return signal and noise. Faults in cable shields are one type of fault that is often difficult to detect. New techniques and approaches are needed for detecting these small shield faults, which are the focus of this dissertation. This dissertation presents a method of externally detecting electromagnetic fields that leak out of holes in cable shields. The significant contributions of this project are expanding the understanding of the fields that leak from damaged shields, analysis of a toroid sensor that can be used to detect and locate these fields, and use of analytic expressions to approximate fields down the length of the cable. The analysis of the fields escaping from the hole in the shield is based on previous work, and is expanded in this dissertation using numerical simulation. It is shown that a small fault in a cable shield resembles a high-pass filter, and that those fields within or near the fault are copies of the excitation signal, but the far fields exhibit a derivative effect from the filtering. The fields directly over the fault are a combination of the original input signal and fringing fields. Moving away from the fault, the signal stabilizes and becomes nearly constant. In this work, analytic expressions for the inductance and capacitance for a small fault are used in conjunction with approximations from simulations to predict the external signal as it propagates down the cable. Once the signal is propagating on the outside of the cable, a toroid is used to pick it up. The

  1. Numerical modeling and characterization of rock avalanches and associated seismic signal

    NASA Astrophysics Data System (ADS)

    Moretti, L.; Mangeney, A.; Capdeville, Y.; Stutzmann, E.; Lucas, A.; Huggel, C.; Schneider, D.; Crosta, G. B.; Bouchut, F.

    2012-04-01

    recorded seismic signal depends on the characteristics of the landslide (volume, mass, friction coefficient…) and on the earth model (seismic waves velocity, number of layers…) used to calculate wave propagation. Favreau, P., Mangeney, A., Lucas, A., Crosta, G.B., and F. Bouchut, Numerical modeling of landquakes. Geophysical Research Letters, VOL. 37, L15305, doi:10.1029/2010GL043512, 2010 Huggel, C., Caplan-Auerbach, J., Molnia, B. and Wessels R. (2008), The 2005 Mt. Steller, Alaska, rock-ice avalanche: A large slope failure in cold permafrost, Proceedings of the Ninth International Conference on Permafrost, vol. 1., p. 747-752, Univ. of Alaska Fairbanks

  2. A Possible Source Model for VLP Signals in Bayou Corne, LA

    NASA Astrophysics Data System (ADS)

    Leidig, M.; Stroujkova, A. F.

    2013-12-01

    Very Long Period (VLP) signals have been recorded in the Bayou Corne area since the formation of a sinkhole resulting from failed a salt cavern. Sediment and/or water migration is hypothesized to be responsible for these signals. Some key observations regarding these signals include: 1. VLP signals are best recorded at an individual station (LA12) to the southwest of the sinkhole. 2. First VLP event detected 3 days after the sinkhole formed, months after the first seismic events. 3. VLP events increase dramatically in the days preceding sinkhole activity. 4. Natural gas migration potentially occurred for a period of time, possibly months, prior to first VLP event detection. 5. Area near LA12 has undergone at least 2 m of subsidence. 6. VLP activity has continued, even as the cavern has nearly filled with sediment. We have examined various possible source mechanisms in order to understand the origin of the VLP signals. A damped oscillator model in which a surface layer vibrates in response to external disturbances best describes the observed VLP events. The model likely represents the shallow Upper Aquitard (UA) oscillating on top of the Mississippi River Alluvial Aquifer (MRAA). In order for the clay layer of the UA to undulate, the sediments in the MRAA would need to be in a fluidized state, with a viscosity similar to tar or magma. The MRAA is fully saturated with water, and small injections of water into the MRAA could temporarily and locally fluidize the sands and disturb the UA creating a VLP event. In addition, small earthquakes can disturb the system and trigger the oscillations. Lateral movement of fluidized sediments could also disturb the UA and generate a VLP in addition to explaining subsidence near LA12. Lateral extrusion of material into the sinkhole also fits with the lack of detected VLP events prior to the sinkhole formation and the increase in VLP events prior to sinkhole activity. Repeated mappings of the sinkhole geometry indicate the maximum

  3. Influence of subthreshold nonlinearities on signal-to-noise ratio and timing precision for small signals in neurons: minimal model analysis.

    PubMed

    Svirskis, Gytis; Rinzel, John

    2003-02-01

    Subthreshold voltage- and time-dependent conductances can subserve different roles in signal integration and action potential generation. Here, we use minimal models to demonstrate how a non-inactivating low-threshold outward current (I(KLT)) can enhance the precision of small-signal integration. Our integrate-and-fire models have only a few biophysical parameters, enabling a parametric study of I(KLT) effects. I(KLT) increases the signal-to-noise ratio (SNR) for firing when a subthreshold 'signal' EPSP is delivered in the presence of weak random input. The increased SNR is due to the suppression of spontaneous firings to random input. In accordance, SNR grows as the EPSP amplitude increases. SNR also grows as the unitary synaptic current's time constant increases, leading to more effective suppression of spontaneous activity. Spike-triggered reverse correlation of the injected current indicates that, to reach spike threshold, a cell with I(KLT) requires a briefer time course of injected current. Consistent with this narrowed integration time window, I(KI.T) enhances phase-locking. measured as vector strength, to a weak noisy and periodically modulated stimulus. Thus subthreshold negative feedback mediated by I(KLT) enhances temporal processing. An alternative suppression mechanism is voltage- and time-dependent inactivation of a low-threshold inward current. This feature in an integrate-and-fire model also shows SNR enhancement, in comparison with a case when the inward current is non-inactivating. Small-signal detection can be significantly improved in noisy neuronal systems by subthreshold negative feedback, serving to suppress false positives. PMID:12613555

  4. Vitamin D signaling in the bovine immune system: a model for understanding human vitamin D requirements.

    PubMed

    Nelson, Corwin D; Reinhardt, Timothy A; Lippolis, John D; Sacco, Randy E; Nonnecke, Brian J

    2012-03-01

    The endocrine physiology of vitamin D in cattle has been rigorously investigated and has yielded information on vitamin D requirements, endocrine function in health and disease, general metabolism, and maintenance of calcium homeostasis in cattle. These results are relevant to human vitamin D endocrinology. The current debate regarding vitamin D requirements is centered on the requirements for proper intracrine and paracrine vitamin D signaling. Studies in adult and young cattle can provide valuable insight for understanding vitamin D requirements as they relate to innate and adaptive immune responses during infectious disease. In cattle, toll-like receptor recognition activates intracrine and paracrine vitamin D signaling mechanism in the immune system that regulates innate and adaptive immune responses in the presence of adequate 25-hydroxyvitamin D. Furthermore, experiments with mastitis in dairy cattle have provided in vivo evidence for the intracrine vitamin D signaling mechanism in macrophages as well as vitamin D mediated suppression of infection. Epidemiological evidence indicates that circulating concentrations above 32 ng/mL of 25-hydroxyvitamin D are necessary for optimal vitamin D signaling in the immune system, but experimental evidence is lacking for that value. Experiments in cattle can provide that evidence as circulating 25-hydroxyvitamin D concentrations can be experimentally manipulated within ranges that are normal for humans and cattle. Additionally, young and adult cattle can be experimentally infected with bacteria and viruses associated with significant diseases in both cattle and humans. Utilizing the bovine model to further delineate the immunomodulatory role of vitamin D will provide potentially valuable insights into the vitamin D requirements of both humans and cattle, especially as they relate to immune response capacity and infectious disease resistance. PMID:22666545

  5. Effect of coherence length and numerical aperture on the formation of OCT signals from model biotissues

    NASA Astrophysics Data System (ADS)

    Kirillin, Mikhail Y.; Priezzhev, Alexander V.; Myllyla, Risto

    2007-05-01

    Maximal depth of non-distorted imaging is an important characteristic, which shows the efficiency of an application of a certain OCT setup for imaging the given object. This characteristic depends on the setup parameters and the properties of the studied object. The definition of the maximal depth of non-distorted imaging based on the classifications of photons contributing to the signal in dependence on the relations of their optical travel pathlength in the object and maximal reached depth was used in this work. We studied the effect of the coherence length and the detection angle on the formation of OCT signals and images from model biotissues as well as on the maximal depth of non-distorted imaging. The signals and images were obtained by implementing the Monte Carlo technique developed in our earlier works. The following single- and multilayer biotissue phantoms were considered as the studied objects: erythrocyte suspension at physiological hematocrit (35%), 2% intralipid solution reported to have optical properties close to those of skin in optical and NIR range, and multilayer human skin phantoms. For the simulations, the parameters of the OCT setup were chosen in accordance with real ones. The wavelengths of the light sources were chosen 820 and 910 nm. The conducted simulations show that a decrease in the detection angle and an increase in the coherence length increase the maximal probing depth in the studied objects due to smaller role of multiple scattering photons in the formation of the OCT signals. The obtained value of maximal depth of non-distorted imaging varies in the range from 50 to 600 μm depending on the values of the setup parameters.

  6. Recording and investigation of the seismic signal generated by hypervelocity impact experiments and numerical models

    NASA Astrophysics Data System (ADS)

    Güldemeister, N.; Moser, D.; Wünnemann, K.; Hoerth, T.; Schäfer, F.

    2013-09-01

    Meteorite impacts can cause environmental consequences, one of which is the generation of ground motions that may exceed the magnitude of the largest earthquakes [1]. Impacts generate shock waves that attenuate with distance until they even tually turn into seismic waves. Thus, meteorite impact may be considered as a source for seismic shaking similar to earthquakes. Seismic signals have been recorded in explosion experiments [2] and in hydrocode models of large impact events such as the Chicxulub crater [3]. To determine how much of the kinetic energy Ekin of the impactoris turned into seismic energy Eseis can be investigated experimentally (by recording the acoustic emission) or by numerical models. The ratio of Eseis/Ekin is the so called seismic efficiency k. The seismic efficiency depends on material properties (porosity) and is usually estimated to range between 10-2 and 10-6 [2,4]. In the framework of the "MEMIN" (multidisciplinary experimental and modeling impact crater research network) project a suite of hypervelocity impact experiments on a decimeter scale have been carried out [5]. We use acoustic emission (AE) technique and pressure gauges in high spatiotemporal Meteorite impacts can cause environmental consequences, one of which is the generation of ground motions that may exceed the magnitude of the largest earthquakes [1]. Impacts generate shock waves that attenuate with distance until they even tually turn into seismic waves. Thus, meteorite impact may be considered as a source for seismic shaking similar to earthquakes. Seismic signals have been recorded in explosion experiments [2] and in hydrocode models of large impact events such as the Chicxulub crater [3]. To determine how much of the kinetic energy Ekin of the impactoris turned into seismic energy Eseis can be investigated experimentally (by recording the acoustic emission) or by numerical models. The ratio of Eseis/Ekin is the so called seismic efficiency k. The seismic efficiency depends

  7. Three-Dimensional Numerical Model of Cell Morphology during Migration in Multi-Signaling Substrates

    PubMed Central

    Mousavi, Seyed Jamaleddin; Hamdy Doweidar, Mohamed

    2015-01-01

    Cell Migration associated with cell shape changes are of central importance in many biological processes ranging from morphogenesis to metastatic cancer cells. Cell movement is a result of cyclic changes of cell morphology due to effective forces on cell body, leading to periodic fluctuations of the cell length and cell membrane area. It is well-known that the cell can be guided by different effective stimuli such as mechanotaxis, thermotaxis, chemotaxis and/or electrotaxis. Regulation of intracellular mechanics and cell’s physical interaction with its substrate rely on control of cell shape during cell migration. In this notion, it is essential to understand how each natural or external stimulus may affect the cell behavior. Therefore, a three-dimensional (3D) computational model is here developed to analyze a free mode of cell shape changes during migration in a multi-signaling micro-environment. This model is based on previous models that are presented by the same authors to study cell migration with a constant spherical cell shape in a multi-signaling substrates and mechanotaxis effect on cell morphology. Using the finite element discrete methodology, the cell is represented by a group of finite elements. The cell motion is modeled by equilibrium of effective forces on cell body such as traction, protrusion, electrostatic and drag forces, where the cell traction force is a function of the cell internal deformations. To study cell behavior in the presence of different stimuli, the model has been employed in different numerical cases. Our findings, which are qualitatively consistent with well-known related experimental observations, indicate that adding a new stimulus to the cell substrate pushes the cell to migrate more directionally in more elongated form towards the more effective stimuli. For instance, the presence of thermotaxis, chemotaxis and electrotaxis can further move the cell centroid towards the corresponding stimulus, respectively, diminishing the

  8. Three-dimensional numerical model of cell morphology during migration in multi-signaling substrates.

    PubMed

    Mousavi, Seyed Jamaleddin; Doweidar, Mohamed Hamdy

    2015-01-01

    Cell Migration associated with cell shape changes are of central importance in many biological processes ranging from morphogenesis to metastatic cancer cells. Cell movement is a result of cyclic changes of cell morphology due to effective forces on cell body, leading to periodic fluctuations of the cell length and cell membrane area. It is well-known that the cell can be guided by different effective stimuli such as mechanotaxis, thermotaxis, chemotaxis and/or electrotaxis. Regulation of intracellular mechanics and cell's physical interaction with its substrate rely on control of cell shape during cell migration. In this notion, it is essential to understand how each natural or external stimulus may affect the cell behavior. Therefore, a three-dimensional (3D) computational model is here developed to analyze a free mode of cell shape changes during migration in a multi-signaling micro-environment. This model is based on previous models that are presented by the same authors to study cell migration with a constant spherical cell shape in a multi-signaling substrates and mechanotaxis effect on cell morphology. Using the finite element discrete methodology, the cell is represented by a group of finite elements. The cell motion is modeled by equilibrium of effective forces on cell body such as traction, protrusion, electrostatic and drag forces, where the cell traction force is a function of the cell internal deformations. To study cell behavior in the presence of different stimuli, the model has been employed in different numerical cases. Our findings, which are qualitatively consistent with well-known related experimental observations, indicate that adding a new stimulus to the cell substrate pushes the cell to migrate more directionally in more elongated form towards the more effective stimuli. For instance, the presence of thermotaxis, chemotaxis and electrotaxis can further move the cell centroid towards the corresponding stimulus, respectively, diminishing the

  9. Fast generation model of high density surface EMG signals in a cylindrical conductor volume.

    PubMed

    Carriou, Vincent; Boudaoud, Sofiane; Laforet, Jeremy; Ayachi, Fouaz Sofiane

    2016-07-01

    In the course of the last decade, fast and qualitative computing power developments have undoubtedly permitted for a better and more realistic modeling of complex physiological processes. Due to this favorable environment, a fast, generic and reliable model for high density surface electromyographic (HD-sEMG) signal generation with a multilayered cylindrical description of the volume conductor is presented in this study. Its main peculiarity lies in the generation of a high resolution potential map over the skin related to active Motor Units (MUs). Indeed, the analytical calculus is fully performed in the frequency domain. HD-sEMG signals are obtained by surfacic numerical integration of the generated high resolution potential map following a variety of electrode shapes. The suggested model is implemented using parallel computing techniques as well as by using an object-oriented approach which is comprehensive enough to be fairly quickly understood, used and potentially upgraded. To illustrate the model abilities, several simulation analyses are put forward in the results section. These simulations have been performed on the same muscle anatomy while varying the number of processes in order to show significant speed improvement. Accuracy of the numerical integration method, illustrating electrode shape diversity, is also investigated in comparison to analytical transfer functions definition. An additional section provides an insight on the volume detection of a circular electrode according to its radius. Furthermore, a large scale simulation is introduced with 300MUs in the muscle and a HD-sEMG electrode grid composed of 16×16 electrodes for three constant isometric contractions in 12s. Finally, advantages and limitations of the proposed model are discussed with a focus on perspective works. PMID:27183535

  10. Mathematical modeling of perifusion cell culture experiments on GnRH signaling.

    PubMed

    Temamogullari, N Ezgi; Nijhout, H Frederik; C Reed, Michael

    2016-06-01

    The effects of pulsatile GnRH stimulation on anterior pituitary cells are studied using perifusion cell cultures, where constantly moving culture medium over the immobilized cells allows intermittent GnRH delivery. The LH content of the outgoing medium serves as a readout of the GnRH signaling pathway activation in the cells. The challenge lies in relating the LH content of the medium leaving the chamber to the cellular processes producing LH secretion. To investigate this relation we developed and analyzed a mathematical model consisting of coupled partial differential equations describing LH secretion in a perifusion cell culture. We match the mathematical model to three different data sets and give cellular mechanisms that explain the data. Our model illustrates the importance of the negative feedback in the signaling pathway and receptor desensitization. We demonstrate that different LH outcomes in oxytocin and GnRH stimulations might originate from different receptor dynamics and concentration. We analyze the model to understand the influence of parameters, like the velocity of the medium flow or the fraction collection time, on the LH outcomes. We show that slow velocities lead to high LH outcomes. Also, we show that fraction collection times, which do not divide the GnRH pulse period evenly, lead to irregularities in the data. We examine the influence of the rate of binding and dissociation of GnRH on the GnRH movement down the chamber. Our model serves as an important tool that can help in the design of perifusion experiments and the interpretation of results. PMID:27067630

  11. Computationally efficient modeling of proprioceptive signals in the upper limb for prostheses: a simulation study

    PubMed Central

    Williams, Ian; Constandinou, Timothy G.

    2014-01-01

    Accurate models of proprioceptive neural patterns could 1 day play an important role in the creation of an intuitive proprioceptive neural prosthesis for amputees. This paper looks at combining efficient implementations of biomechanical and proprioceptor models in order to generate signals that mimic human muscular proprioceptive patterns for future experimental work in prosthesis feedback. A neuro-musculoskeletal model of the upper limb with 7 degrees of freedom and 17 muscles is presented and generates real time estimates of muscle spindle and Golgi Tendon Organ neural firing patterns. Unlike previous neuro-musculoskeletal models, muscle activation and excitation levels are unknowns in this application and an inverse dynamics tool (static optimization) is integrated to estimate these variables. A proprioceptive prosthesis will need to be portable and this is incompatible with the computationally demanding nature of standard biomechanical and proprioceptor modeling. This paper uses and proposes a number of approximations and optimizations to make real time operation on portable hardware feasible. Finally technical obstacles to mimicking natural feedback for an intuitive proprioceptive prosthesis, as well as issues and limitations with existing models, are identified and discussed. PMID:25009463

  12. A Hierarchical Rater Model for Constructed Responses, with a Signal Detection Rater Model

    ERIC Educational Resources Information Center

    DeCarlo, Lawrence T.; Kim, YoungKoung; Johnson, Matthew S.

    2011-01-01

    The hierarchical rater model (HRM) recognizes the hierarchical structure of data that arises when raters score constructed response items. In this approach, raters' scores are not viewed as being direct indicators of examinee proficiency but rather as indicators of essay quality; the (latent categorical) quality of an examinee's essay in turn…

  13. In vitro microemboli classification using neural network models and RF signals.

    PubMed

    Benoudjit, N; Ferroudji, K; Bahaz, M; Bouakaz, A

    2011-04-01

    Emboli classification is of high clinical importance for selecting appropriate treatment for patients. Several ultrasonic (US) methods using Doppler processing have been used for emboli detection and classification as solid or gaseous matter. We suggest in this experimental study exploiting the Radio-Frequency (RF) signal backscattered by the emboli since they contain additional information on the embolus than the Doppler signal. The aim of the study is the analysis of RF signals using Multilayer Perceptron (MLP) and Radial-Basis Function Network (RBFN) in order to classify emboli. Anthares scanner with RF access was used with a transmit frequency of 1.82MHz at two mechanical indices (MI) 0.2 and 0.6. The mechanical index is given as the peak negative pressure (in MPa) divided by the square root of the frequency (in MHz). A Doppler flow phantom was used containing a 0.8mm diameter vessel surrounded by a tissue mimicking material. To imitate gas emboli US behaviour, Sonovue microbubbles were injected at two different doses (10μl and 5μl) in a nonrecirculating at a constant flow. The surrounding tissue was assumed to behave as a solid emboli. In order to mimic real clinical pathological situations, Sonovue concentration was chosen such that the fundamental scattering from the tissue and from the contrast were identical. The amplitudes and bandwidths of the fundamental and the 2nd harmonic components were selected as input parameters to the MLP and RBFN models. Moreover the frequency bandwidths of the fundamental and the 2nd harmonic echoes were approximated by Gaussian functions and the coefficients were used as a third input parameter to the neural network models. The results show that the Gaussian coefficients provide the highest rate of classification in comparison to the amplitudes and the bandwidths of the fundamental and the 2nd harmonic components. The classification rates reached 89.28% and 92.85% with MLP and RBFN models respectively. This short

  14. Source term estimates of radioxenon released from the BaTek medical isotope production facility using external measured air concentrations.

    PubMed

    Eslinger, Paul W; Cameron, Ian M; Dumais, Johannes Robert; Imardjoko, Yudi; Marsoem, Pujadi; McIntyre, Justin I; Miley, Harry S; Stoehlker, Ulrich; Widodo, Susilo; Woods, Vincent T

    2015-10-01

    BATAN Teknologi (BaTek) operates an isotope production facility in Serpong, Indonesia that supplies (99m)Tc for use in medical procedures. Atmospheric releases of (133)Xe in the production process at BaTek are known to influence the measurements taken at the closest stations of the radionuclide network of the International Monitoring System (IMS). The purpose of the IMS is to detect evidence of nuclear explosions, including atmospheric releases of radionuclides. The major xenon isotopes released from BaTek are also produced in a nuclear explosion, but the isotopic ratios are different. Knowledge of the magnitude of releases from the isotope production facility helps inform analysts trying to decide if a specific measurement result could have originated from a nuclear explosion. A stack monitor deployed at BaTek in 2013 measured releases to the atmosphere for several isotopes. The facility operates on a weekly cycle, and the stack data for June 15-21, 2013 show a release of 1.84 × 10(13) Bq of (133)Xe. Concentrations of (133)Xe in the air are available at the same time from a xenon sampler located 14 km from BaTek. An optimization process using atmospheric transport modeling and the sampler air concentrations produced a release estimate of 1.88 × 10(13) Bq. The same optimization process yielded a release estimate of 1.70 × 10(13) Bq for a different week in 2012. The stack release value and the two optimized estimates are all within 10% of each other. Unpublished production data and the release estimate from June 2013 yield a rough annual release estimate of 8 × 10(14) Bq of (133)Xe in 2014. These multiple lines of evidence cross-validate the stack release estimates and the release estimates based on atmospheric samplers. PMID:26093852

  15. Source Term Estimates of Radioxenon Released from the BaTek Medical Isotope Production Facility Using External Measured Air Concentrations

    SciTech Connect

    Eslinger, Paul W.; Cameron, Ian M.; Dumais, Johannes R.; Imardjoko, Yudi; Marsoem, Pujadi; McIntyre, Justin I.; Miley, Harry S.; Stoehlker, Ulrich; Widodo, Susilo; Woods, Vincent T.

    2015-10-01

    Abstract Batan Teknologi (BaTek) operates an isotope production facility in Serpong, Indonesia that supplies 99mTc for use in medical procedures. Atmospheric releases of Xe-133 in the production process at BaTek are known to influence the measurements taken at the closest stations of the International Monitoring System (IMS). The purpose of the IMS is to detect evidence of nuclear explosions, including atmospheric releases of radionuclides. The xenon isotopes released from BaTek are the same as those produced in a nuclear explosion, but the isotopic ratios are different. Knowledge of the magnitude of releases from the isotope production facility helps inform analysts trying to decide whether a specific measurement result came from a nuclear explosion. A stack monitor deployed at BaTek in 2013 measured releases to the atmosphere for several isotopes. The facility operates on a weekly cycle, and the stack data for June 15-21, 2013 show a release of 1.84E13 Bq of Xe-133. Concentrations of Xe-133 in the air are available at the same time from a xenon sampler located 14 km from BaTek. An optimization process using atmospheric transport modeling and the sampler air concentrations produced a release estimate of 1.88E13 Bq. The same optimization process yielded a release estimate of 1.70E13 Bq for a different week in 2012. The stack release value and the two optimized estimates are all within 10 percent of each other. Weekly release estimates of 1.8E13 Bq and a 40 percent facility operation rate yields a rough annual release estimate of 3.7E13 Bq of Xe-133. This value is consistent with previously published estimates of annual releases for this facility, which are based on measurements at three IMS stations. These multiple lines of evidence cross-validate the stack release estimates and the release estimates from atmospheric samplers.

  16. Unmasking of a Protective TNFR1 Mediated Signal in the Collagen Arthritis Model

    PubMed Central

    Williams-Skipp, Cheryll; Raman, Thiagarajan; Valuck, Robert J.; Watkins, Herschel; Palmer, Brent E.; Scheinman, Robert I.

    2009-01-01

    OBJECTIVE: TNFR1 plays a major role in rheumatoid arthritis (RA). Here we explore the relative importance of TNFR1 signaling in the hematopoietic tissue compartment for disease progression. METHODS: DBA/1 mice were lethally irradiated and rescued with bone marrow derived from either DBA/1 or TNFR1−/− animals. The mice were then input into the collagen induced arthritis (CIA) model and disease progression characterized. RESULTS: Surprisingly, TNFR1−/− transplant mice input into the CIA model develop increased disease as compared to controls. This could not be attributed to either an increased primary response to collagen or to the contribution of a non-DBA genetic background. Histological markers of advanced disease were evident in TNFR1−/− transplant mice shortly after initiation of the immune response to collagen and long before clinical evidence of disease. Serum TNFα was undetectable while serum IL-12p40 levels were increased in TNFR1−/− transplant mice at the end point of the study. CONCLUSION: These data raise the intriguing possibility of the existence of an anti-inflammatory TNFR1 mediated circuit in the hematopoietic compartment. This circuit bears a resemblance to emerging data delineating a switch in TNFα function observed in the resolution of bacterial infections. These data suggest that TNFR1 mediated signals in the radio-resistant tissues contributes to disease progression while TNFR1 mediated signals in the radio-sensitive tissues can contribute to protection from disease. We thus put forward the hypothesis that the degree of responce to TNFα blockade in RA is dependent, in part, on the relative genetic strengths of these two pathways. PMID:19180511

  17. Forward model of thermally-induced acoustic signal specific to intralumenal detection geometry

    NASA Astrophysics Data System (ADS)

    Mukherjee, Sovanlal; Bunting, Charles F.; Piao, Daqing

    2011-03-01

    This work investigates a forward model associated with intra-lumenal detection of acoustic signal originated from transient thermal-expansion of the tissue. The work is specific to intra-lumenal thermo-acoustic tomography (TAT) which detects the contrast of tissue dielectric properties with ultrasonic resolution, but it is also extendable to intralumenal photo-acoustic tomography (PAT) which detects the contrast of light absorption properties of tissue with ultrasound resolution. Exact closed-form frequency-domain or time-domain forward model of thermally-induced acoustic signal have been studied rigorously for planar geometry and two other geometries, including cylindrical and spherical geometries both of which is specific to external-imaging, i.e. breast or brain imaging using an externally-deployed applicator. This work extends the existing studies to the specific geometry of internal or intra-lumenal imaging, i.e., prostate imaging by an endo-rectally deployed applicator. In this intra-lumenal imaging geometry, both the source that excites the transient thermal-expansion of the tissue and the acoustic transducer that acquires the thermally-induced acoustic signal are assumed enclosed by the tissue and on the surface of a long cylindrical applicator. The Green's function of the frequency-domain thermo-acoustic equation in spherical coordinates is expanded to cylindrical coordinates associated with intra-lumenal geometry. Inverse Fourier transform is then applied to obtain a time-domain solution of the thermo-acoustic pressure wave for intra-lumenal geometry. Further employment of the boundary condition to the "convex" applicator-tissue interface would render an exact forward solution toward accurate reconstruction for intra-lumenal thermally-induced acoustic imaging.

  18. Extraction of Desired Signal Based on AR Model with Its Application to Atrial Activity Estimation in Atrial Fibrillation

    NASA Astrophysics Data System (ADS)

    Wang, Gang; Rao, Ni-ni; Shepherd, Simon J.; Beggs, Clive B.

    2008-12-01

    The use of electrocardiograms (ECGs) to diagnose and analyse atrial fibrillation (AF) has received much attention recently. When studying AF, it is important to isolate the atrial activity (AA) component of the ECG plot. We present a new autoregressive (AR) model for semiblind source extraction of the AA signal. Previous researchers showed that one could extract a signal with the smallest normalized mean square prediction error (MSPE) as the first output from linear mixtures by minimizing the MSPE. However the extracted signal will be not always the desired one even if the AR model parameters of one source signal are known. We introduce a new cost function, which caters for the specific AR model parameters, to extract the desired source. Through theoretical analysis and simulation we demonstrate that this algorithm can extract any desired signal from mixtures provided that its AR parameters are first obtained. We use this approach to extract the AA signal from 12-lead surface ECG signals for hearts undergoing AF. In our methodology we roughly estimated the AR parameters from the fibrillatory wave segment in the V1 lead, and then used this algorithm to extract the AA signal. We validate our approach using real-world ECG data.

  19. New model for gain control of signal intensity to object distance in echolocating bats.

    PubMed

    Nørum, Ulrik; Brinkløv, Signe; Surlykke, Annemarie

    2012-09-01

    Echolocating bats emit ultrasonic calls and listen for the returning echoes to orient and localize prey in darkness. The emitted source level, SL (estimated signal intensity 10 cm from the mouth), is adjusted dynamically from call to call in response to sensory feedback as bats approach objects. A logarithmic relationship of SL=20 log(10)(x), i.e. 6 dB output reduction per halving of distance, x, has been proposed as a model for the relationship between emitted intensity and object distance, not only for bats but also for echolocating toothed whales. This logarithmic model suggests that the approaching echolocator maintains a constant intensity impinging upon the object, but it also implies ever-increasing source levels with distance, a physical and biological impossibility. We developed a new model for intensity compensation with an exponential rise to the maximum source level: SL=SL(max)-ae(-)(bx). In addition to providing a method for estimating maximum output, the new model also offers a tool for estimating a minimum detection distance where intensity compensation starts. We tested the new exponential model against the 'conventional' logarithmic model on data from five bat species. The new model performed better in 77% of the trials and as good as the conventional model in the rest (23%). We found much steeper rates of compensation when fitting the model to individual rather than pooled data, with slopes often steeper than -20 dB per halving of distance. This emphasizes the importance of analyzing individual events. The results are discussed in light of habitat constraints and the interaction between bats and their eared prey. PMID:22875770

  20. Chronic ethanol exposure inhibits distraction osteogenesis in a mouse model: Role of the TNF signaling axis

    SciTech Connect

    Wahl, Elizabeth C.; Aronson, James; Liu, Lichu; Liu, Zhendong; Perrien, Daniel S.; Skinner, Robert A.; Badger, Thomas M.; Ronis, Martin J.J.; Lumpkin, Charles K. . E-mail: lumpkincharlesk@uams.edu

    2007-05-01

    Tumor necrosis factor-alpha (TNF-{alpha}) is an inflammatory cytokine that modulates osteoblastogenesis. In addition, the demonstrated inhibitory effects of chronic ethanol exposure on direct bone formation in rats are hypothetically mediated by TNF-{alpha} signaling. The effects in mice are unreported. Therefore, we hypothesized that in mice (1) administration of a soluble TNF receptor 1 derivative (sTNF-R1) would protect direct bone formation during chronic ethanol exposure, and (2) administration of recombinant mouse TNF-{alpha} (rmTNF-{alpha}) to ethanol naive mice would inhibit direct bone formation. We utilized a unique model of limb lengthening (distraction osteogenesis, DO) combined with liquid diets to measure chronic ethanol's effects on direct bone formation. Chronic ethanol exposure resulted in increased marrow TNF, IL-1, and CYP 2E1 RNA levels in ethanol-treated vs. control mice, while no significant weight differences were noted. Systemic administration of sTNF-R1 during DO (8.0 mg/kg/2 days) to chronic ethanol-exposed mice resulted in enhanced direct bone formation as measured radiologically and histologically. Systemic rmTNF-{alpha} (10 {mu}g/kg/day) administration decreased direct bone formation measures, while no significant weight differences were noted. We conclude that chronic ethanol-associated inhibition of direct bone formation is mediated to a significant extent by the TNF signaling axis in a mouse model.

  1. Food Reconstruction Using Isotopic Transferred Signals (FRUITS): A Bayesian Model for Diet Reconstruction

    PubMed Central

    Fernandes, Ricardo; Millard, Andrew R.; Brabec, Marek; Nadeau, Marie-Josée; Grootes, Pieter

    2014-01-01

    Human and animal diet reconstruction studies that rely on tissue chemical signatures aim at providing estimates on the relative intake of potential food groups. However, several sources of uncertainty need to be considered when handling data. Bayesian mixing models provide a natural platform to handle diverse sources of uncertainty while allowing the user to contribute with prior expert information. The Bayesian mixing model FRUITS (Food Reconstruction Using Isotopic Transferred Signals) was developed for use in diet reconstruction studies. FRUITS incorporates the capability to account for dietary routing, that is, the contribution of different food fractions (e.g. macronutrients) towards a dietary proxy signal measured in the consumer. FRUITS also provides relatively straightforward means for the introduction of prior information on the relative dietary contributions of food groups or food fractions. This type of prior may originate, for instance, from physiological or metabolic studies. FRUITS performance was tested using simulated data and data from a published controlled animal feeding experiment. The feeding experiment data was selected to exemplify the application of the novel capabilities incorporated into FRUITS but also to illustrate some of the aspects that need to be considered when handling data within diet reconstruction studies. FRUITS accurately predicted dietary intakes, and more precise estimates were obtained for dietary scenarios in which expert prior information was included. FRUITS represents a useful tool to achieve accurate and precise food intake estimates in diet reconstruction studies within different scientific fields (e.g. ecology, forensics, archaeology, and dietary physiology). PMID:24551057

  2. Cereal grass pulvini: agronomically significant models for studying gravitropism signaling and tissue polarity.

    PubMed

    Clore, Amy M

    2013-01-01

    Cereal grass pulvini have emerged as model systems that are not only valuable for the study of gravitropism, but are also of agricultural and economic significance. The pulvini are regions of tissue that are apical to each node and collectively return a reoriented stem to a more vertical position. They have proven to be useful for the study of gravisensing and response and are also providing clues about the establishment of polarity across tissues. This review will first highlight the agronomic significance of these stem regions and their benefits for use as model systems and provide a brief historical overview. A detailed discussion of the literature focusing on cell signaling and early changes in gene expression will follow, culminating in a temporal framework outlining events in the signaling and early growth phases of gravitropism in this tissue. Changes in cell wall composition and gene expression that occur well into the growth phase will be touched upon briefly. Finally, some ongoing research involving both maize and wheat pulvini will be introduced along with prospects for future investigations. PMID:23125431

  3. An automated method for generating analogic signals that embody the Markov kinetics of model ionic channels.

    PubMed

    Luchian, Tudor

    2005-08-30

    In this work we present an automated method for generating electrical signals which reflect the kinetics of ionic channels that have custom-tailored intermediate sub-states and intermediate reaction constants. The concept of our virtual single-channel waveform generator makes use of two software platforms, one for the numerical generation of single channel traces stemming from a pre-defined model and another for the digital-to-analog conversion of such numerical generated single channel traces. This technique of continuous generation and recording of the activity of a model ionic channel provides an efficient protocol to teach neophytes in the field of single-channel electrophysiology about its major phenomenological facets. Random analogic signals generated by using our technique can be successfully employed in a number of applications, such us: assisted learning of the single-molecule kinetic investigation via electrical recordings, impedance spectroscopy, the evaluation of linear frequency response of neurons and the study of stochastic resonance of ion channels. PMID:16054511

  4. Improving oral implant osseointegration in a murine model via Wnt signal amplification

    PubMed Central

    Mouraret, Sylvain; Hunter, Daniel J.; Bardet, Claire; Popelut, Antoine; Brunski, John B.; Chaussain, Catherine; Bouchard, Philippe; Helms, Jill A.

    2016-01-01

    Aim To determine the key biological events occurring during implant failure and then we use this knowledge to develop new biology-based strategies that improve osseointegration. Materials and Methods Wild-type and Axin2LacZ/LacZ adult male mice underwent oral implant placement, with and without primary stability. Peri-implant tissues were evaluated using histology, alkaline phosphatase (ALP) activity, tartrate resistant acid phosphatase (TRAP) activity and TUNEL staining. In addition, mineralization sites, collagenous matrix organization and the expression of bone markers in the peri-implant tissues were assessed. Results Maxillary implants lacking primary stability show histological evidence of persistent fibrous encapsulation and mobility, which recapitulates the clinical problems of implant failure. Despite histological and molecular evidence of fibrous encapsulation, osteoblasts in the gap interface exhibit robust ALP activity. This mineralization activity is counteracted by osteoclast activity that resorbs any new bony matrix and consequently, the fibrous encapsulation remains. Using a genetic mouse model, we show that implants lacking primary stability undergo osseointegration, provided that Wnt signalling is amplified. Conclusions In a mouse model of oral implant failure caused by a lack of primary stability, we find evidence of active mineralization. This mineralization, however, is outpaced by robust bone resorption, which culminates in persistent fibrous encapsulation of the implant. Fibrous encapsulation can be prevented and osseointegration assured if Wnt signalling is elevated at the time of implant placement. PMID:24164629

  5. Modelling colour constancy in fish: implications for vision and signalling in water.

    PubMed

    Wilkins, Lucas; Marshall, N Justin; Johnsen, Sönke; Osorio, D

    2016-06-15

    Colour vision and colour signals are important to aquatic animals, but light scattering and absorption by water distorts spectral stimuli. To investigate the performance of colour vision in water, and to suggest how photoreceptor spectral sensitivities and body colours might evolve for visual communication, we model the effects of changes in viewing distance and depth on the appearance of fish colours for three teleosts: a barracuda, Sphyraena helleri, which is dichromatic and two damselfishes, Chromis verater and Chromis hanui, which are trichromatic. We assume that photoreceptors light-adapt to the background, thereby implementing the von Kries transformation, which can largely account for observed colour constancy in humans and other animals, including fish. This transformation does not, however, compensate for light scattering over variable viewing distances, which in less than a metre seriously impairs dichromatic colour vision, and makes judgement of colour saturation unreliable for trichromats. The von Kries transformation does substantially offset colour shifts caused by changing depth, so that from depths of 0 to 30 m modelled colour changes (i.e. failures of colour constancy) are sometimes negligible. However, the magnitudes and directions of remaining changes are complex, depending upon the specific spectral sensitivities of the receptors and the reflectance spectra. This predicts that when judgement of colour is important, the spectra of signalling colours and photoreceptor spectral sensitivities should be evolutionarily linked, with the colours dependent on photoreceptor spectral sensitivities, and vice versa. PMID:27045090

  6. Differential Toll-Like Receptor-Signalling of Burkholderia pseudomallei Lipopolysaccharide in Murine and Human Models

    PubMed Central

    Weehuizen, Tassili A. F.; Prior, Joann L.; van der Vaart, Thomas W.; Ngugi, Sarah A.; Nepogodiev, Sergey A.; Field, Robert A.; Kager, Liesbeth M.; van ‘t Veer, Cornelis; de Vos, Alex F.; Wiersinga, W. Joost

    2015-01-01

    The Gram-negative bacterium Burkholderia pseudomallei causes melioidosis and is a CDC category B bioterrorism agent. Toll-like receptor (TLR)-2 impairs host defense during pulmonary B.pseudomallei infection while TLR4 only has limited impact. We investigated the role of TLRs in B.pseudomallei-lipopolysaccharide (LPS) induced inflammation. Purified B.pseudomallei-LPS activated only TLR2-transfected-HEK-cells during short stimulation but both HEK-TLR2 and HEK-TLR4-cells after 24 h. In human blood, an additive effect of TLR2 on TLR4-mediated signalling induced by B.pseudomallei-LPS was observed. In contrast, murine peritoneal macrophages recognized B.pseudomallei-LPS solely through TLR4. Intranasal inoculation of B.pseudomallei-LPS showed that both TLR4-knockout(-/-) and TLR2x4-/-, but not TLR2-/- mice, displayed diminished cytokine responses and neutrophil influx compared to wild-type controls. These data suggest that B.pseudomallei-LPS signalling occurs solely through murine TLR4, while in human models TLR2 plays an additional role, highlighting important differences between specificity of human and murine models that may have important consequences for B.pseudomallei-LPS sensing by TLRs and subsequent susceptibility to melioidosis. PMID:26689559

  7. A two-dimensional model study of the QBO signal in SAGE II NO2 and O3

    NASA Technical Reports Server (NTRS)

    Chipperfield, M. P.; Gray, L. J.; Kinnersley, J. S.; Zawodny, J.

    1994-01-01

    Calculations of the quasi biennial oscillation (QBO) signal in Stratospheric Aerosol and Gas Experiment (SAGE) II O3 and NO2 data between 1984 and 1991 are presented and have been investigated by using a two-dimensional model. The isentropic 2D model is a fully interactive radiative-dynamical-chemical model in which the eddy fluxes of chemical species are calculated in a consistent manner. The QBO in the model has been forced by relaxing the equatorial zonal wind toward the observations at Singapore allowing the comparison of the model with observations from specific years. The model reproduces the observed vertical structure of the equatorial ozone anomaly with the well-known transition from dynamical to photochemical control at around 28km. The model also reproduces the observed vertical structure of the SAGE II observed NO2 anomaly. The model studies have shown that it is the QBO modulation of NO2 which the main cause of QBO signal in O3 above 30 km. The model also reproduces the observed latitudinal structure of the QBO signals in O3 and NO2. Due to the differing horizontal distribution of O3 and NO(y) the ozone signal shows a distinct phase change in the subtropics whereas the NO2 anomaly gives a broader signal.

  8. ptk7 mutant zebrafish models of congenital and idiopathic scoliosis implicate dysregulated Wnt signalling in disease

    PubMed Central

    Hayes, Madeline; Gao, Xiaochong; Yu, Lisa X; Paria, Nandina; Henkelman, R. Mark; Wise, Carol A.; Ciruna, Brian

    2014-01-01

    Scoliosis is a complex genetic disorder of the musculoskeletal system, characterized by three-dimensional rotation of the spine. Curvatures caused by malformed vertebrae (congenital scoliosis (CS)) are apparent at birth. Spinal curvatures with no underlying vertebral abnormality (idiopathic scoliosis (IS)) most commonly manifest during adolescence. The genetic and biological mechanisms responsible for IS remain poorly understood due largely to limited experimental models. Here we describe zygotic ptk7 (Zptk7) mutant zebrafish, deficient in a critical regulator of Wnt signalling, as the first genetically defined developmental model of IS. We identify a novel sequence variant within a single IS patient that disrupts PTK7 function, consistent with a role for dysregulated Wnt activity in disease pathogenesis. Furthermore, we demonstrate that embryonic loss-of-gene function in maternal-zygotic ptk7 mutants (MZptk7) leads to vertebral anomalies associated with CS. Our data suggest novel molecular origins of, and genetic links between, congenital and idiopathic forms of disease. PMID:25182715

  9. Decomposition of a mixture of signals in a model of the olfactory bulb.

    PubMed

    Hendin, O; Horn, D; Hopfield, J J

    1994-06-21

    We describe models for the olfactory bulb which perform separation and decomposition of mixed odor inputs from different sources. The odors are unknown to the system; hence this is an analog and extension of the engineering problem of blind separation of signals. The separation process makes use of the different temporal fluctuations of the input odors which occur under natural conditions. We discuss two possibilities, one relying on a specific architecture connecting modules with the same sensory inputs and the other assuming that the modules (e.g., glomeruli) have different receptive fields in odor space. We compare the implications of these models for the testing of mixed odors from a single source. PMID:8016093

  10. Validated Models for Radiation Response and Signal Generation in Scintillators: Final Report

    SciTech Connect

    Kerisit, Sebastien N.; Gao, Fei; Xie, YuLong; Campbell, Luke W.; Van Ginhoven, Renee M.; Wang, Zhiguo; Prange, Micah P.; Wu, Dangxin

    2014-12-01

    This Final Report presents work carried out at Pacific Northwest National Laboratory (PNNL) under the project entitled “Validated Models for Radiation Response and Signal Generation in Scintillators” (Project number: PL10-Scin-theor-PD2Jf) and led by Drs. Fei Gao and Sebastien N. Kerisit. This project was divided into four tasks: 1) Electronic response functions (ab initio data model) 2) Electron-hole yield, variance, and spatial distribution 3) Ab initio calculations of information carrier properties 4) Transport of electron-hole pairs and scintillation efficiency Detailed information on the results obtained in each of the four tasks is provided in this Final Report. Furthermore, published peer-reviewed articles based on the work carried under this project are included in Appendix. This work was supported by the National Nuclear Security Administration, Office of Nuclear Nonproliferation Research and Development (DNN R&D/NA-22), of the U.S. Department of Energy (DOE).

  11. Fractalkine Signaling Regulates the Inflammatory Response in an α-Synuclein Model of Parkinson Disease

    PubMed Central

    Thome, Aaron D.; Standaert, David G.; Harms, Ashley S.

    2015-01-01

    Background Parkinson disease (PD) is a progressive neurodegenerative disorder characterized by loss of dopamine neurons in the substantia nigra pars compacta (SNpc) and widespread aggregates of the protein alpha-synuclein (α-syn). Increasing evidence points to inflammation as a chief mediator; however, the role of α-syn in triggering and sustaining inflammation remains unclear. In models of Alzheimer’s disease (AD), multiple sclerosis (MS) and neurotoxin models of PD, the chemokine CX3CL1 (fractalkine) and its receptor (CX3CR1) have important roles in modulating neuroinflammation. Methods To examine the role of fractalkine signaling in α-syn-induced-neuroinflammation and neurodegeneration, we used an in vivo mouse model in which human α-syn is overexpressed by an adeno associated viral vector serotype 2 (AAV2) and in vitro phagocytosis and protein internalization assays with primary microglia treated with aggregated α-syn. Results We observed that loss of CX3CR1 expression led to a reduced inflammatory response, with reduced IgG deposition and expression of MHCII 4 weeks post-transduction. Six months post transduction, AAV2 mediated overexpression of α-syn leads to loss of dopaminergic neurons, and this loss was not exacerbated in animals with deletion of CX3CR1. To determine the mechanism by which CX3CR1affects inflammatory responses in α-syn-induced inflammation, phagocytosis was assessed using a fluorescent microsphere assay as well as by microglial uptake of aggregated α-syn. CX3CR1-/- microglia showed reduced uptake of fluorescent beads and aggregated α-syn. Conclusion Our results suggest that one mechanism by which CX3CR1-/- attenuates inflammation is at the level of phagocytosis of aggregated α-syn by microglia. These data implicate fractalkine signaling as a potential therapeutic target for regulating inflammatory response in α-syn models PD. PMID:26469270

  12. Exploring phospholipase C-coupled Ca(2+) signalling networks using Boolean modelling.

    PubMed

    Bhardwaj, G; Wells, C P; Albert, R; van Rossum, D B; Patterson, R L

    2011-05-01

    In this study, the authors explored the utility of a descriptive and predictive bionetwork model for phospholipase C-coupled calcium signalling pathways, built with non-kinetic experimental information. Boolean models generated from these data yield oscillatory activity patterns for both the endoplasmic reticulum resident inositol-1,4,5-trisphosphate receptor (IP(3)R) and the plasma-membrane resident canonical transient receptor potential channel 3 (TRPC3). These results are specific as randomisation of the Boolean operators ablates oscillatory pattern formation. Furthermore, knock-out simulations of the IP(3)R, TRPC3 and multiple other proteins recapitulate experimentally derived results. The potential of this approach can be observed by its ability to predict previously undescribed cellular phenotypes using in vitro experimental data. Indeed, our cellular analysis of the developmental and calcium-regulatory protein, DANGER1a, confirms the counter-intuitive predictions from our Boolean models in two highly relevant cellular models. Based on these results, the authors theorise that with sufficient legacy knowledge and/or computational biology predictions, Boolean networks can provide a robust method for predictive modelling of any biological system. [Includes supplementary material]. PMID:21639591

  13. Dynamic Performance Comparison of Two Kalman Filters for Rate Signal Direct Modeling and Differencing Modeling for Combining a MEMS Gyroscope Array to Improve Accuracy

    PubMed Central

    Yuan, Guangmin; Yuan, Weizheng; Xue, Liang; Xie, Jianbing; Chang, Honglong

    2015-01-01

    In this paper, the performance of two Kalman filter (KF) schemes based on the direct estimated model and differencing estimated model for input rate signal was thoroughly analyzed and compared for combining measurements of a sensor array to improve the accuracy of microelectromechanical system (MEMS) gyroscopes. The principles for noise reduction were presented and KF algorithms were designed to obtain the optimal rate signal estimates. The input rate signal in the direct estimated KF model was modeled with a random walk process and treated as the estimated system state. In the differencing estimated KF model, a differencing operation was established between outputs of the gyroscope array, and then the optimal estimation of input rate signal was achieved by compensating for the estimations of bias drifts for the component gyroscopes. Finally, dynamic simulations and experiments with a six-gyroscope array were implemented to compare the dynamic performance of the two KF models. The 1σ error of the gyroscopes was reduced from 1.4558°/s to 0.1203°/s by the direct estimated KF model in a constant rate test and to 0.5974°/s by the differencing estimated KF model. The estimated rate signal filtered by both models could reflect the amplitude variation of the input signal in the swing rate test and displayed a reduction factor of about three for the 1σ noise. Results illustrate that the performance of the direct estimated KF model is much higher than that of the differencing estimated KF model, with a constant input signal or lower dynamic variation. A similarity in the two KFs’ performance is observed if the input signal has a high dynamic variation. PMID:26528980

  14. Dynamic Performance Comparison of Two Kalman Filters for Rate Signal Direct Modeling and Differencing Modeling for Combining a MEMS Gyroscope Array to Improve Accuracy.

    PubMed

    Yuan, Guangmin; Yuan, Weizheng; Xue, Liang; Xie, Jianbing; Chang, Honglong

    2015-01-01

    In this paper, the performance of two Kalman filter (KF) schemes based on the direct estimated model and differencing estimated model for input rate signal was thoroughly analyzed and compared for combining measurements of a sensor array to improve the accuracy of microelectromechanical system (MEMS) gyroscopes. The principles for noise reduction were presented and KF algorithms were designed to obtain the optimal rate signal estimates. The input rate signal in the direct estimated KF model was modeled with a random walk process and treated as the estimated system state. In the differencing estimated KF model, a differencing operation was established between outputs of the gyroscope array, and then the optimal estimation of input rate signal was achieved by compensating for the estimations of bias drifts for the component gyroscopes. Finally, dynamic simulations and experiments with a six-gyroscope array were implemented to compare the dynamic performance of the two KF models. The 1σ error of the gyroscopes was reduced from 1.4558°/s to 0.1203°/s by the direct estimated KF model in a constant rate test and to 0.5974°/s by the differencing estimated KF model. The estimated rate signal filtered by both models could reflect the amplitude variation of the input signal in the swing rate test and displayed a reduction factor of about three for the 1σ noise. Results illustrate that the performance of the direct estimated KF model is much higher than that of the differencing estimated KF model, with a constant input signal or lower dynamic variation. A similarity in the two KFs' performance is observed if the input signal has a high dynamic variation. PMID:26528980

  15. Neutrino and gravitational wave signal of a delayed-detonation model of type Ia supernovae

    NASA Astrophysics Data System (ADS)

    Seitenzahl, Ivo R.; Herzog, Matthias; Ruiter, Ashley J.; Marquardt, Kai; Ohlmann, Sebastian T.; Röpke, Friedrich K.

    2015-12-01

    The progenitor system(s) and the explosion mechanism(s) of type Ia supernovae (SNe Ia) are still under debate. Nonelectromagnetic observables, in particular, gravitational waves and neutrino emission, of thermoclear supernovae are a complementary window to light curves and spectra for studying these enigmatic objects. A leading model for SNe Ia is the thermonuclear incineration of a near-Chandrasekhar mass carbon-oxygen white dwarf star in a "delayed detonation." We calculate a three-dimensional hydrodynamic explosion for the N100 delayed-detonation model extensively discussed in the literature, taking the dynamical effects of neutrino emission from all important contributing source terms into account. Although neutrinos carry away 2 ×1049 erg of energy, we confirm the common view that neutrino energy losses are dynamically not very important, resulting in only a modest reduction of final kinetic energy by 2%. We then calculate the gravitational wave signal from the time evolution of the quadrupole moment. Our model radiates 7 ×1039 erg in gravitational waves and the spectrum has a pronounced peak around 0.4 Hz. Depending on viewing angle and polarization, we find that the future space-based gravitational wave missions DECIGO and BBO would be able to detect our source to a distance of ˜1.3 Mpc . We predict a clear signature of the deflagration-to-detonation transition in the neutrino and the gravitational wave signals. If observed, such a feature would be a strong indicator of the realization of delayed detonations in near-Chandrasekhar mass white dwarfs.

  16. Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models Part I: Convective Signals

    SciTech Connect

    Lin, J; Kiladis, G N; Mapes, B E; Weickmann, K M; Sperber, K R; Lin, W; Wheeler, M; Schubert, S D; Genio, A D; Donner, L J; Emori, S; Gueremy, J; Hourdin, F; Rasch, P J; Roeckner, E; Scinocca, J F

    2005-05-06

    This study evaluates the tropical intraseasonal variability, especially the fidelity of Madden-Julian Oscillation (MJO) simulations, in 14 coupled general circulation models (GCMs) participating in the Inter-governmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Eight years of daily precipitation from each model's 20th century climate simulation are analyzed and compared with daily satellite retrieved precipitation. Space-time spectral analysis is used to obtain the variance and phase speed of dominant convectively coupled equatorial waves, including the MJO, Kelvin, equatorial Rossby (ER), mixed Rossby-gravity (MRG), and eastward inertio-gravity (EIG) and westward inertio-gravity (WIG) waves. The variance and propagation of the MJO, defined as the eastward wavenumbers 1-6, 30-70 day mode, are examined in detail. The results show that current state-of-the-art GCMs still have significant problems and display a wide range of skill in simulating the tropical intraseasonal variability. The total intraseasonal (2-128 day) variance of precipitation is too weak in most of the models. About half of the models have signals of convectively coupled equatorial waves, with Kelvin and MRG-EIG waves especially prominent. However, the variances are generally too weak for all wave modes except the EIG wave, and the phase speeds are generally too fast, being scaled to excessively deep equivalent depths. An interesting result is that this scaling is consistent within a given model across modes, in that both the symmetric and antisymmetric modes scale similarly to a certain equivalent depth. Excessively deep equivalent depths suggest that these models may not have a large enough reduction in their ''effective static stability'' due to diabatic heating. The MJO variance approaches the observed value in only two of the 14 models, but is less than half of the observed value in the other 12 models. The ratio between the eastward MJO variance and the variance of its

  17. Statistical Modeling of Large-Scale Signal Path Loss in Underwater Acoustic Networks

    PubMed Central

    Llor, Jesús; Malumbres, Manuel Perez

    2013-01-01

    In an underwater acoustic channel, the propagation conditions are known to vary in time, causing the deviation of the received signal strength from the nominal value predicted by a deterministic propagation model. To facilitate a large-scale system design in such conditions (e.g., power allocation), we have developed a statistical propagation model in which the transmission loss is treated as a random variable. By applying repetitive computation to the acoustic field, using ray tracing for a set of varying environmental conditions (surface height, wave activity, small node displacements around nominal locations, etc.), an ensemble of transmission losses is compiled and later used to infer the statistical model parameters. A reasonable agreement is found with log-normal distribution, whose mean obeys a log-distance increases, and whose variance appears to be constant for a certain range of inter-node distances in a given deployment location. The statistical model is deemed useful for higher-level system planning, where simulation is needed to assess the performance of candidate network protocols under various resource allocation policies, i.e., to determine the transmit power and bandwidth allocation necessary to achieve a desired level of performance (connectivity, throughput, reliability, etc.). PMID:23396190

  18. Model-based inversion algorithm for ground penetration radar signal processing with correlation for target classification

    NASA Astrophysics Data System (ADS)

    Patz, Mark David

    A non-intrusive buried object classifier for a ground penetrating radar (GPR) system is developed. Various GPR data sets and the implemented processing are described. A model based inversion algorithm that utilizes correlation methodology for target classification is introduced. Experimental data was collected with a continuous wave GPR. Synthetic data was generated with a newly developed software package that implements mathematical models to predict the electromagnetic returns from an underground object. Sample targets and geometries were chosen to produce nine configurations/scenarios for analysis. The real measurement sets for each configuration and the synthetic sets for a family of similar configurations were imaged with the same state-of-the-art signal processing algorithms. The imaged results for the real data measurements were correlated with the imaged results for the synthetic data sets to produce performance measurements, thus producing a procedure that provides a non-invasive assessment of the object and medium determined by the synthetic data set that maximally correlated with the real data return. Synthetic results and experiment results showed good correlations. For the synthetic data, a mathematical model was developed for electromagnetic returns from an object shape (i.e., cylinder, parallelepiped, sphere) composed of a uniform construction (i.e., metal, wood, plastic, clay) within a uniform dielectric material (i.e., air, sand, loam, clay, water). This model was then implemented within a software package, thus providing the ability to generate simulated measurements from any combination of object, construction, and dielectric.

  19. Statistical modeling of large-scale signal path loss in underwater acoustic networks.

    PubMed

    Llor, Jesús; Malumbres, Manuel Perez

    2013-01-01

    In an underwater acoustic channel, the propagation conditions are known to vary in time, causing the deviation of the received signal strength from the nominal value predicted by a deterministic propagation model. To facilitate a large-scale system design in such conditions (e.g., power allocation), we have developed a statistical propagation model in which the transmission loss is treated as a random variable. By applying repetitive computation to the acoustic field, using ray tracing for a set of varying environmental conditions (surface height, wave activity, small node displacements around nominal locations, etc.), an ensemble of transmission losses is compiled and later used to infer the statistical model parameters. A reasonable agreement is found with log-normal distribution, whose mean obeys a log-distance increases, and whose variance appears to be constant for a certain range of inter-node distances in a given deployment location. The statistical model is deemed useful for higher-level system planning, where simulation is needed to assess the performance of candidate network protocols under various resource allocation policies, i.e., to determine the transmit power and bandwidth allocation necessary to achieve a desired level of performance (connectivity, throughput, reliability, etc.). PMID:23396190

  20. Small signal modeling of high electron mobility transistors on silicon and silicon carbide substrate with consideration of substrate loss mechanism

    NASA Astrophysics Data System (ADS)

    Sahoo, A. K.; Subramani, N. K.; Nallatamby, J. C.; Sylvain, L.; Loyez, C.; Quere, R.; Medjdoub, F.

    2016-01-01

    In this paper, we present a comparative study on small-signal modeling of AlN/GaN/AlGaN double hetero-structure high electron mobility transistors (HEMTs) grown on silicon (Si) and silicon carbide (SiC) substrate. The traditional small signal equivalent circuit model is modified to take into account the transmission loss mechanism of coplanar waveguide (CPW) line which cannot be neglected at high frequencies. CPWs and HEMTs-on-AlN/GaN/AlGaN epitaxial layers are fabricated on both the Si and SiC substrates. S-parameter measurements at room temperature are performed over the frequency range from 0.5 GHz to 40 GHz. Transmission loss of CPW lines are modeled with a distributed transmission line (TL) network and an equivalent circuit model is included in the small-signal transistor model topology. Measurements and simulations are compared and found to be in good agreement.

  1. A VLSI field-programmable mixed-signal array to perform neural signal processing and neural modeling in a prosthetic system.

    PubMed

    Bamford, Simeon A; Hogri, Roni; Giovannucci, Andrea; Taub, Aryeh H; Herreros, Ivan; Verschure, Paul F M J; Mintz, Matti; Del Giudice, Paolo

    2012-07-01

    A very-large-scale integration field-programmable mixed-signal array specialized for neural signal processing and neural modeling has been designed. This has been fabricated as a core on a chip prototype intended for use in an implantable closed-loop prosthetic system aimed at rehabilitation of the learning of a discrete motor response. The chosen experimental context is cerebellar classical conditioning of the eye-blink response. The programmable system is based on the intimate mixing of switched capacitor analog techniques with low speed digital computation; power saving innovations within this framework are presented. The utility of the system is demonstrated by the implementation of a motor classical conditioning model applied to eye-blink conditioning in real time with associated neural signal processing. Paired conditioned and unconditioned stimuli were repeatedly presented to an anesthetized rat and recordings were taken simultaneously from two precerebellar nuclei. These paired stimuli were detected in real time from this multichannel data. This resulted in the acquisition of a trigger for a well-timed conditioned eye-blink response, and repetition of unpaired trials constructed from the same data led to the extinction of the conditioned response trigger, compatible with natural cerebellar learning in awake animals. PMID:22481832

  2. Harnessing system models of cell death signalling for cytotoxic chemotherapy: towards personalised medicine approaches?

    PubMed

    Huber, Heinrich J; McKiernan, Ross G; Prehn, Jochen H M

    2014-03-01

    Most cytotoxic chemotherapeutics are believed to kill cancer cells by inducing apoptosis. Understanding the factors that contribute to impairment of apoptosis in cancer cells is therefore critical for the development of novel therapies that circumvent the widespread chemoresistance. Apoptosis, however, is a complex and tightly controlled process that can be induced by different classes of chemotherapeutics targeting different signalling nodes and pathways. Moreover, apoptosis initiation and apoptosis execution strongly depend on patient-specific, genomic and proteomic signatures. Here, we will review recent translational studies that suggest a critical link between the sensitivity of cancer cells to initiate apoptosis and clinical outcome. Next we will discuss recent advances in the field of system modelling of apoptosis pathways for the prediction of treatment responses. We propose that initiation of mitochondrial apoptosis, defined as the process of mitochondrial outer membrane permeabilisation (MOMP), is a dose-dependent decision process that allows for a prediction of individual therapy responses and therapeutic windows. We provide evidence in contrast that apoptosis execution post-MOMP may be a binary decision that dictates whether apoptosis is executed or not. We will discuss the implications of this concept for the future use of novel adjuvant therapeutics that specifically target apoptosis signalling pathways or which may be used to reduce the impact of cell-to-cell heterogeneity on therapy responses. Finally, we will discuss the technical and regulatory requirements surrounding the use and implications of system-based patient stratification tools for the future of personalised oncology. PMID:24477766

  3. Modeling the self-organized phosphatidylinositol lipid signaling system in chemotactic cells using quantitative image analysis.

    PubMed

    Shibata, Tatsuo; Nishikawa, Masatoshi; Matsuoka, Satomi; Ueda, Masahiro

    2012-11-01

    A key signaling event that is responsible for gradient sensing in eukaryotic cell chemotaxis is a phosphatidylinositol (PtdIns) lipid reaction system. The self-organization activity of this PtdIns lipid system induces an inherent polarity, even in the absence of an external chemoattractant gradient, by producing a localized PtdIns (3,4,5)-trisphosphate [PtdIns(3,4,5)P(3)]-enriched domain on the membrane. Experimentally, we found that such a domain could exhibit two types of behavior: (1) it could be persistent and travel on the membrane, or (2) be stochastic and transient. Taking advantage of the simultaneous visualization of PtdIns(3,4,5)P(3) and the enzyme phosphatase and tensin homolog (PTEN), for which PtdIns(3,4,5)P(3) is a substrate, we statistically demonstrated the inter-dependence of their spatiotemporal dynamics. On the basis of this statistical analysis, we developed a theoretical model for the self-organization of PtdIns lipid signaling that can accurately reproduce both persistent and transient domain formation; these types of formations can be explained by the oscillatory and excitability properties of the system, respectively. PMID:22899720

  4. Geochronological models based on quantitative signal processing of chemical stratigraphic data

    SciTech Connect

    Williams, D.F.; Trainor, D.M.; Lerche, I.

    1989-03-01

    Chemical stratigraphy is becoming an increasingly important tool in chronostratigraphic interpretations of exploration wells. Chemical stratigraphy data are well suited to modeling in the time and frequency domains with quantitative signal processing and data-dependent filtering techniques, such as power spectral analysis, autocorrelation, cross-correlation, cross power spectral analysis, phase-sensitive detection, and matched filters. Properly analyzed quantitatively, chemical stratigraphy data provide an ideal framework for stratigraphic correlation of thick sedimentary sections with a high degree of resolution, chronostratigraphic interpretations with a high degree of reliability, as well as mapping and timing of diagenetic trends and gradients. In this presentation, the authors use a combination of these techniques to compare several recently developed types of chemical stratigraphies. One type record is based on global changes in the stable isotopic composition of seawater. The other type records are based on composite stable isotope and geochemical records for Pliocene-Pleistocene exploration wells from the northwestern Gulf of Mexico. Coherency analysis was used to subtract the global portion of the signal from the Gulf sections due to freshwater discharge vents, paleotemperature changes, diagenesis, and hydrocarbon migration.

  5. C-kit signaling promotes proliferation and invasion of colorectal mucinous adenocarcinoma in a murine model

    PubMed Central

    Tan, Jun; Yang, Shu; Shen, Ping; Sun, Haimei; Xiao, Jie; Wang, Yaxi; Wu, Bo; Ji, Fengqing; Yan, Jihong; Xue, Hong; Zhou, Deshan

    2015-01-01

    It was reported that the receptor tyrosine kinase (RTK) family often highly expressed in several mucinous carcinomas. In the present study, we established a murine model of colorectal mucinous adenocardinoma (CRMAC) by treating C57 mice [both wild type (WT) and loss-of-function c-kit mutant type (Wads−/−)] with AOM+DSS for 37 weeks and found that c-kit, a member of RTK family, clearly enhanced the tumor cell proliferation by decreasing p53 and increasing cyclin D1 through AKT pathway. Significantly, c-kit strongly promoted tumor cell invasiveness by increasing ETV4, which induced MMP7 expression and epithelial-mesenchymal transition (EMT) via ERK pathway. In vitro up- or down-regulating c-kit activation in human colorectal cancer HCT-116 cells further consolidated these results. In conclusion, our data suggested that the c-kit signaling obviously promoted proliferation and invasion of CRMAC. Therefore, targeting the c-kit signaling and its downstream molecules might provide the potential strategies for treatment of patients suffering from CRMAC in the future. PMID:26356816

  6. Modeling fMRI signals can provide insights into neural processing in the cerebral cortex

    PubMed Central

    Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

    2015-01-01

    Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. PMID:25972586

  7. Symmetry breaking in a bulk-surface reaction-diffusion model for signalling networks

    NASA Astrophysics Data System (ADS)

    Rätz, Andreas; Röger, Matthias

    2014-08-01

    Signalling molecules play an important role for many cellular functions. We investigate here a general system of two membrane reaction-diffusion equations coupled to a diffusion equation inside the cell by a Robin-type boundary condition and a flux term in the membrane equations. A specific model of this form was recently proposed by the authors for the GTPase cycle in cells. We investigate here a putative role of diffusive instabilities in cell polarization. By a linearized stability analysis, we identify two different mechanisms. The first resembles a classical Turing instability for the membrane subsystem and requires (unrealistically) large differences in the lateral diffusion of activator and substrate. On the other hand, the second possibility is induced by the difference in cytosolic and lateral diffusion and appears much more realistic. We complement our theoretical analysis by numerical simulations that confirm the new stability mechanism and allow us to investigate the evolution beyond the regime where the linearization applies.

  8. Reversing excitatory GABAAR signaling restores synaptic plasticity and memory in a mouse model of Down syndrome.

    PubMed

    Deidda, Gabriele; Parrini, Martina; Naskar, Shovan; Bozarth, Ignacio F; Contestabile, Andrea; Cancedda, Laura

    2015-04-01

    Down syndrome (DS) is the most frequent genetic cause of intellectual disability, and altered GABAergic transmission through Cl(-)-permeable GABAA receptors (GABAARs) contributes considerably to learning and memory deficits in DS mouse models. However, the efficacy of GABAergic transmission has never been directly assessed in DS. Here GABAAR signaling was found to be excitatory rather than inhibitory, and the reversal potential for GABAAR-driven Cl(-) currents (ECl) was shifted toward more positive potentials in the hippocampi of adult DS mice. Accordingly, hippocampal expression of the cation Cl(-) cotransporter NKCC1 was increased in both trisomic mice and individuals with DS. Notably, NKCC1 inhibition by the FDA-approved drug bumetanide restored ECl, synaptic plasticity and hippocampus-dependent memory in adult DS mice. Our findings demonstrate that GABA is excitatory in adult DS mice and identify a new therapeutic approach for the potential rescue of cognitive disabilities in individuals with DS. PMID:25774849

  9. Computational models of reinforcement learning: the role of dopamine as a reward signal

    PubMed Central

    Samson, R. D.; Frank, M. J.

    2010-01-01

    Reinforcement learning is ubiquitous. Unlike other forms of learning, it involves the processing of fast yet content-poor feedback information to correct assumptions about the nature of a task or of a set of stimuli. This feedback information is often delivered as generic rewards or punishments, and has little to do with the stimulus features to be learned. How can such low-content feedback lead to such an efficient learning paradigm? Through a review of existing neuro-computational models of reinforcement learning, we suggest that the efficiency of this type of learning resides in the dynamic and synergistic cooperation of brain systems that use different levels of computations. The implementation of reward signals at the synaptic, cellular, network and system levels give the organism the necessary robustness, adaptability and processing speed required for evolutionary and behavioral success. PMID:21629583

  10. Signal detection and threshold modeling of confidence-rating ROCs: A critical test with minimal assumptions.

    PubMed

    Kellen, David; Klauer, Karl Christoph

    2015-07-01

    An ongoing discussion in the recognition-memory literature concerns the question of whether recognition judgments reflect a direct mapping of graded memory representations (a notion that is instantiated by signal detection theory) or whether they are mediated by a discrete-state representation with the possibility of complete information loss (a notion that is instantiated by threshold models). These 2 accounts are usually evaluated by comparing their (penalized) fits to receiver operating characteristic data, a procedure that is predicated on substantial auxiliary assumptions, which if violated can invalidate results. We show that the 2 accounts can be compared on the basis of critical tests that invoke only minimal assumptions. Using previously published receiver operating characteristic data, we show that confidence-rating judgments are consistent with a discrete-state account. (PsycINFO Database Record PMID:26120910

  11. Sparsity: a ubiquitous but unexplored property of geophysical signals for multi-scale modeling and reconstruction

    NASA Astrophysics Data System (ADS)

    Fouofula-Georgiou, E.; Ebtehaj, A. M.

    2012-04-01

    Sparsity: a ubiquitous but unexplored property of geophysical signals for multi-scale modeling and reconstruction Efi Foufoula-Georgiou and Ardeshir Mohammad Ebtehaj Department of Civil Engineering and National Center for Earth-surface Dynamics University of Minnesota, Minneapolis, MN 55414 Many geophysical processes exhibit variability over a wide range of scales. Yet, in numerical modeling or remote sensing observations not all of this variability is explicitly resolved due to limitations in computational resources or sensor configurations. As a result, sub-grid scale parameterizations and downscaling/upscaling representations are essential. Such representations take advantage of scale invariance which has been theoretically or empirically documented in a wide range of geophysical processes, including precipitation, soil moisture, and topography. Here we present a new direction in the field of multi-scale analysis and reconstruction. It capitalizes on the fact that most geophysical signals are naturally redundant, due to spatial dependence and coherence over a range of scales, and thus when projected onto an appropriate space (e.g, Fourier or wavelet) only a few representation coefficients are non-zero -- this property is called sparsity. The sparsity can serve as a priori knowledge to properly regularize the otherwise ill-posed inverse problem of creating information at scales smaller than resolved, which is at the heart of sub-grid scale and downscaling parameterizations. The same property of sparsity is also shown to play a revolutionary role in revisiting the problem of optimal estimation of non-Gaussian processes. Theoretical concepts are borrowed from the new field of compressive sampling and super-resolution and the merits of the methodology are demonstrated using examples from precipitation downscaling, multi-scale data fusion and data assimilation.

  12. Prototyping scalable digital signal processing systems for radio astronomy using dataflow models

    NASA Astrophysics Data System (ADS)

    Sane, N.; Ford, J.; Harris, A. I.; Bhattacharyya, S. S.

    2012-05-01

    There is a growing trend toward using high-level tools for design and implementation of radio astronomy digital signal processing (DSP) systems. Such tools, for example, those from the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER), are usually platform-specific, and lack high-level, platform-independent, portable, scalable application specifications. This limits the designer's ability to experiment with designs at a high-level of abstraction and early in the development cycle. We address some of these issues using a model-based design approach employing dataflow models. We demonstrate this approach by applying it to the design of a tunable digital downconverter (TDD) used for narrow-bandwidth spectroscopy. Our design is targeted toward an FPGA platform, called the Interconnect Break-out Board (IBOB), that is available from the CASPER. We use the term TDD to refer to a digital downconverter for which the decimation factor and center frequency can be reconfigured without the need for regenerating the hardware code. Such a design is currently not available in the CASPER DSP library. The work presented in this paper focuses on two aspects. First, we introduce and demonstrate a dataflow-based design approach using the dataflow interchange format (DIF) tool for high-level application specification, and we integrate this approach with the CASPER tool flow. Secondly, we explore the trade-off between the flexibility of TDD designs and the low hardware cost of fixed-configuration digital downconverter (FDD) designs that use the available CASPER DSP library. We further explore this trade-off in the context of a two-stage downconversion scheme employing a combination of TDD or FDD designs.

  13. Weighted calibration with reduced number of signals by weighing factor modelling: application to the identification of explosives by ion chromatography.

    PubMed

    Brasil, Beatriz; Bettencourt da Silva, Ricardo J N; Camões, M Filomena G F C; Salgueiro, Pedro A S

    2013-12-01

    The linear weighted regression model (LW) can be used to calibrate analytical instrumentation in a range of quantities (e.g. concentration or mass) wider than possible by the linear unweighted regression model, LuW (i.e. the least squares regression model), since this model can be applied when signals are not equally precise through the calibration range. If precision of signals varies within the calibration range, the regression line should be defined taking into account that more precise signals are more reliable and should count more to define regression parameters. Nevertheless, the LW requires the determination of the variation of signals precision through the calibration range. Typically, this information is collected experimentally for each calibration, requiring a large number of replicate collection of signals of calibrators. This work proposes reducing the number of signals needed to perform LW calibrations by developing models of weighing factors robust to daily variations of instrument sensibility. These models were applied to the determination of the ionic composition of the water soluble fraction of explosives. The adequacy of the developed models was tested through the analysis of control standards, certified reference materials and the ion balance of anions and cations in aqueous extracts of explosives, considering the measurement uncertainty estimated by detailed metrological models. The high success rate of the comparisons between estimated and known quantity values of reference solutions, considering results uncertainty, proves the validity of developed metrological models. The relative expanded measurement uncertainty of single determinations ranged from 1.93% to 35.7% for calibrations performed along 4 months. PMID:24267095

  14. Signal-to-Noise Behavior for Matches to Gradient Direction Models of Corners in Images

    SciTech Connect

    Paglieroni, D W; Manay, S

    2007-02-09

    Gradient direction models for corners of prescribed acuteness, leg length, and leg thickness are constructed by generating fields of unit vectors emanating from leg pixels that point normal to the edges. A novel FFT-based algorithm that quickly matches models of corners at all possible positions and orientations in the image to fields of gradient directions for image pixels is described. The signal strength of a corner is discussed in terms of the number of pixels along the edges of a corner in an image, while noise is characterized by the coherence of gradient directions along those edges. The detection-false alarm rate behavior of our corner detector is evaluated empirically by manually constructing maps of corner locations in typical overhead images, and then generating different ROC curves for matches to models of corners with different leg lengths and thicknesses. We then demonstrate how corners found with our detector can be used to quickly and automatically find families of polygons of arbitrary position, size and orientation in overhead images.

  15. Self-deception as self-signalling: a model and experimental evidence

    PubMed Central

    Mijović-Prelec, Danica; Prelec, Draz̆en

    2010-01-01

    Self-deception has long been the subject of speculation and controversy in psychology, evolutionary biology and philosophy. According to an influential ‘deflationary’ view, the concept is an over-interpretation of what is in reality an instance of motivationally biased judgement. The opposite view takes the interpersonal deception analogy seriously, and holds that some part of the self actively manipulates information so as to mislead the other part. Building on an earlier self-signalling model of Bodner and Prelec, we present a game-theoretic model of self-deception. We propose that two distinct mechanisms collaborate to produce overt expressions of belief: a mechanism responsible for action selection (including verbal statements) and an interpretive mechanism that draws inferences from actions and generates emotional responses consistent with the inferences. The model distinguishes between two modes of self-deception, depending on whether the self-deceived individual regards his own statements as fully credible. The paper concludes with a new experimental study showing that self-deceptive judgements can be reliably and repeatedly elicited with financial incentives in a categorization task, and that the degree of self-deception varies with incentives. The study also finds evidence of the two forms of self-deception. The psychological benefits of self-deception, as measured by confidence, peak at moderate levels. PMID:20026461

  16. Finite-difference time-domain modelling of through-the-Earth radio signal propagation

    NASA Astrophysics Data System (ADS)

    Ralchenko, M.; Svilans, M.; Samson, C.; Roper, M.

    2015-12-01

    This research seeks to extend the knowledge of how a very low frequency (VLF) through-the-Earth (TTE) radio signal behaves as it propagates underground, by calculating and visualizing the strength of the electric and magnetic fields for an arbitrary geology through numeric modelling. To achieve this objective, a new software tool has been developed using the finite-difference time-domain method. This technique is particularly well suited to visualizing the distribution of electromagnetic fields in an arbitrary geology. The frequency range of TTE radio (400-9000 Hz) and geometrical scales involved (1 m resolution for domains a few hundred metres in size) involves processing a grid composed of millions of cells for thousands of time steps, which is computationally expensive. Graphics processing unit acceleration was used to reduce execution time from days and weeks, to minutes and hours. Results from the new modelling tool were compared to three cases for which an analytic solution is known. Two more case studies were done featuring complex geologic environments relevant to TTE communications that cannot be solved analytically. There was good agreement between numeric and analytic results. Deviations were likely caused by numeric artifacts from the model boundaries; however, in a TTE application in field conditions, the uncertainty in the conductivity of the various geologic formations will greatly outweigh these small numeric errors.

  17. A robust vector field correction method via a mixture statistical model of PIV signal

    NASA Astrophysics Data System (ADS)

    Lee, Yong; Yang, Hua; Yin, Zhouping

    2016-03-01

    Outlier (spurious vector) is a common problem in practical velocity field measurement using particle image velocimetry technology (PIV), and it should be validated and replaced by a reliable value. One of the most challenging problems is to correctly label the outliers under the circumstance that measurement noise exists or the flow becomes turbulent. Moreover, the outlier's cluster occurrence makes it difficult to pick out all the outliers. Most of current methods validate and correct the outliers using local statistical models in a single pass. In this work, a vector field correction (VFC) method is proposed directly from a mixture statistical model of PIV signal. Actually, this problem is formulated as a maximum a posteriori (MAP) estimation of a Bayesian model with hidden/latent variables, labeling the outliers in the original field. The solution of this MAP estimation, i.e., the outlier set and the restored flow field, is optimized iteratively using an expectation-maximization algorithm. We illustrated this VFC method on two kinds of synthetic velocity fields and two kinds of experimental data and demonstrated that it is robust to a very large number of outliers (even up to 60 %). Besides, the proposed VFC method has high accuracy and excellent compatibility for clustered outliers, compared with the state-of-the-art methods. Our VFC algorithm is computationally efficient, and corresponding Matlab code is provided for others to use it. In addition, our approach is general and can be seamlessly extended to three-dimensional-three-component (3D3C) PIV data.

  18. Dynamic Modeling and Analysis of the Cross-Talk between Insulin/AKT and MAPK/ERK Signaling Pathways

    PubMed Central

    Arkun, Yaman

    2016-01-01

    Feedback loops play a key role in the regulation of the complex interactions in signal transduction networks. By studying the network of interactions among the biomolecules present in signaling pathways at the systems level, it is possible to understand how the biological functions are regulated and how the diseases emerge from their deregulations. This paper identifies the key feedback loops involved in the cross-talk among the insulin-AKT and MAPK/ERK signaling pathways. We developed a mathematical model that can be used to study the steady-state and dynamic behavior of the interactions among these two important signaling pathways. Modeling analysis and simulation case studies identify the key interaction parameters and the feedback loops that determine the normal and disease phenotypes. PMID:26930065

  19. DC and small-signal physical models for the AlGaAs/GaAs high electron mobility transistor

    NASA Technical Reports Server (NTRS)

    Sarker, J. C.; Purviance, J. E.

    1991-01-01

    Analytical and numerical models are developed for the microwave small-signal performance, such as transconductance, gate-to-source capacitance, current gain cut-off frequency and the optimum cut-off frequency of the AlGaAs/GaAs High Electron Mobility Transistor (HEMT), in both normal and compressed transconductance regions. The validated I-V characteristics and the small-signal performances of four HeMT's are presented.

  20. Control of IL-17 receptor signaling and tissue inflammation by the p38α–MKP-1 signaling axis in a mouse model of multiple sclerosis

    PubMed Central

    Vogel, Peter; Chi, Hongbo

    2015-01-01

    T helper 17 (TH17) cells are CD4+ T cells that secrete the proinflammatory cytokine interleukin-17 (IL-17) and that play a key pathogenic role in autoimmune diseases. Through inducible and tissue-specific deletion systems, we described the temporal and cell type–specific roles of the mitogen-activated protein kinase (MAPK) p38α in mediating TH17 cell–induced tissue inflammation. Inducible deletion of Mapk14 (which encodes p38α) after the onset of experimental autoimmune encephalomyelitis (EAE), a murine model for human multiple sclerosis, protected mice from inflammation. Furthermore, the severity of EAE was markedly reduced in mice with specific loss of p38α in neuroectoderm-derived cells, including astrocytes, an effect that was associated with defective production of chemokines and decreased infiltration of the target tissue by immune cells. p38α linked IL-17 receptor (IL-17R) signaling to the expression of genes encoding proinflammatory chemokines and cytokines. Mice that lacked MAPK phosphatase 1 (MKP-1), an inhibitor of p38α, had exacerbated EAE and enhanced expression of IL-17R–dependent genes. Our results suggest that the p38α–MKP-1 signaling axis links IL-17R signaling in tissue-resident cells to autoimmune inflammation dependent on infiltrating TH17 cells. PMID:25737586

  1. Evaluation of different time domain peak models using extreme learning machine-based peak detection for EEG signal.

    PubMed

    Adam, Asrul; Ibrahim, Zuwairie; Mokhtar, Norrima; Shapiai, Mohd Ibrahim; Cumming, Paul; Mubin, Marizan

    2016-01-01

    Various peak models have been introduced to detect and analyze peaks in the time domain analysis of electroencephalogram (EEG) signals. In general, peak model in the time domain analysis consists of a set of signal parameters, such as amplitude, width, and slope. Models including those proposed by Dumpala, Acir, Liu, and Dingle are routinely used to detect peaks in EEG signals acquired in clinical studies of epilepsy or eye blink. The optimal peak model is the most reliable peak detection performance in a particular application. A fair measure of performance of different models requires a common and unbiased platform. In this study, we evaluate the performance of the four different peak models using the extreme learning machine (ELM)-based peak detection algorithm. We found that the Dingle model gave the best performance, with 72 % accuracy in the analysis of real EEG data. Statistical analysis conferred that the Dingle model afforded significantly better mean testing accuracy than did the Acir and Liu models, which were in the range 37-52 %. Meanwhile, the Dingle model has no significant difference compared to Dumpala model. PMID:27462484

  2. cAMP/PKA signaling inhibits osteogenic differentiation and bone formation in rodent models.

    PubMed

    Siddappa, Ramakrishnaiah; Mulder, Winfried; Steeghs, Ilse; van de Klundert, Christine; Fernandes, Hugo; Liu, Jun; Arends, Roel; van Blitterswijk, Clemens; de Boer, Jan

    2009-08-01

    We previously demonstrated that cAMP-mediated protein kinase A (PKA) activation induces in vitro osteogenesis and in vivo bone formation by human mesenchymal stem cells (hMSCs). To analyze the species-specific response of this phenomenon and to translate our findings into a clinical trial, suitable animal models and cell lines are desirable. In this report, we assessed whether PKA plays a similar proosteogenic role played by two commonly used PKA activators-N6,2'-O-dibutyryl-cAMP (db-cAMP) and 8-bromo cAMP (8b-cAMP)-in a number of model systems. To this end, we treated MC3T3-E1 cells, mouse calvarial osteoblasts, mouse MSCs, and rat MSCs with cAMP. We demonstrate that cAMP inhibits osteogenesis in rodent cell types, evidenced by inhibition of osteogenic markers such as alkaline phosphatase (ALP), osteocalcin (BGLAP), and collagen type 1 (COL1A1). In support of this, ex vivo-cultured mouse calvaria exposed to db-cAMP showed a reduction in bone volume. Interestingly, cAMP even stimulated adipogenic differentiation in rat MSCs. Taken together, our data demonstrate that cAMP inhibits osteogenesis in vitro and bone formation ex vivo in rodent models in contrast to our earlier findings in hMSCs. The species discrepancy in response to various osteogenic signals is a critical need to be tested in clinically relevant models to translate the fundamental findings in lower species level to clinical applications. PMID:19231969

  3. Model selection reveals control of cold signalling by evening-phased components of the plant circadian clock

    PubMed Central

    Keily, Jack; MacGregor, Dana R; Smith, Robert W; Millar, Andrew J; Halliday, Karen J; Penfield, Steven

    2013-01-01

    Circadian clocks confer advantages by restricting biological processes to certain times of day through the control of specific phased outputs. Control of temperature signalling is an important function of the plant oscillator, but the architecture of the gene network controlling cold signalling by the clock is not well understood. Here we use a model ensemble fitted to time-series data and a corrected Akaike Information Criterion (AICc) analysis to extend a dynamic model to include the control of the key cold-regulated transcription factors C-REPEAT BINDING FACTORs 1–3 (CBF1, CBF2, CBF3). AICc was combined with in silico analysis of genetic perturbations in the model ensemble, and selected a model that predicted mutant phenotypes and connections between evening-phased circadian clock components and CBF3 transcriptional control, but these connections were not shared by CBF1 and CBF2. In addition, our model predicted the correct gating of CBF transcription by cold only when the cold signal originated from the clock mechanism itself, suggesting that the clock has an important role in temperature signal transduction. Our data shows that model selection could be a useful method for the expansion of gene network models. PMID:23909712

  4. A Finite Element Model Approach to Determine the Influence of Electrode Design and Muscle Architecture on Myoelectric Signal Properties

    PubMed Central

    Teklemariam, A.; Hodson-Tole, E. F.; Reeves, N. D.; Costen, N. P.; Cooper, G.

    2016-01-01

    Introduction Surface electromyography (sEMG) is the measurement of the electrical activity of the skeletal muscle tissue detected at the skin’s surface. Typically, a bipolar electrode configuration is used. Most muscles have pennate and/or curved fibres, meaning it is not always feasible to align the bipolar electrodes along the fibres direction. Hence, there is a need to explore how different electrode designs can affect sEMG measurements. Method A three layer finite element (skin, fat, muscle) muscle model was used to explore different electrode designs. The implemented model used as source signal an experimentally recorded intramuscular EMG taken from the biceps brachii muscle of one healthy male. A wavelet based intensity analysis of the simulated sEMG signal was performed to analyze the power of the signal in the time and frequency domain. Results The model showed muscle tissue causing a bandwidth reduction (to 20-92- Hz). The inter-electrode distance (IED) and the electrode orientation relative to the fibres affected the total power but not the frequency filtering response. The effect of significant misalignment between the electrodes and the fibres (60°- 90°) could be reduced by increasing the IED (25–30 mm), which attenuates signal cancellation. When modelling pennated fibres, the muscle tissue started to act as a low pass filter. The effect of different IED seems to be enhanced in the pennated model, while the filtering response is changed considerably only when the electrodes are close to the signal termination within the model. For pennation angle greater than 20°, more than 50% of the source signal was attenuated, which can be compensated by increasing the IED to 25 mm. Conclusion Differences in tissue filtering properties, shown in our model, indicates that different electrode designs should be considered for muscle with different geometric properties (i.e. pennated muscles). PMID:26886908

  5. Modeling TGF-β signaling pathway in epithelial-mesenchymal transition

    NASA Astrophysics Data System (ADS)

    Laise, Pasquale; Fanelli, Duccio; Lió, Pietro; Arcangeli, Annarosa

    2012-03-01

    The epithelial-mesenchymal transition (EMT) consists in a morphological change in epithelial cells characterized by the loss of the cell adhesion and the acquisition of mesenchymal phenotype. This process plays a crucial role in the embryonic development and in regulating the tissue homeostasis in the adult, but it proves also fundamental for the development of cancer metastasis. Experimental evidences have shown that the EMT depends on the TGF-β signaling pathway, which in turn regulates the transcriptional cellular activity. In this work, a dynamical model of the TGF-β pathway is proposed and calibrated versus existing experimental data on lung cancer A549 cells. The analysis combines Bayesian Markov Chain Monte Carlo (MCMC) and standard Ordinary Differential Equations (ODEs) techniques to interpolate the gene expression data via an iterative adjustments of the parameters involved. The kinetic of the Smad proteins phosphorylation, as predicted within the model is found in excellent agreement with available experiments, an observation that confirms the adequacy of the proposed mathematical picture.

  6. Spontaneous oscillations, signal amplification and synchronization in a model of active hair bundle mechanics

    PubMed Central

    Han, Lijuan; Neiman, Alexander B.

    2010-01-01

    We study spontaneous dynamics and signal transduction in a model of active hair bundle mechanics of sensory hair cells. The hair bundle motion is subjected to internal noise resulted from thermal fluctuations and stochastic dynamics of mechano-electrical transduction ion channels. Similar to other studies we found that in the presence of noise the coherence of stochastic oscillations is maximal at a point on the bifurcation diagram away from the Andronov-Hopf bifurcation and is close to the point of maximum sensitivity of the system to weak periodic mechanical perturbations. Despite decoherent effect of noise the stochastic hair bundle oscillations can be synchronized by external periodic force of few pN amplitude in a finite range of control parameters. We then study effects of receptor potential oscillations on mechanics of the hair bundle and show that the hair bundle oscillations can be synchronized by oscillating receptor voltage. Moreover, using a linear model for the receptor potential we show that bi-directional coupling of the hair bundle and the receptor potential results in significant enhancement of the coherence of spontaneous oscillations and of the sensitivity to the external mechanical perturbations. PMID:20481759

  7. Inhibition of CXCR2 signaling promotes recovery in models of Multiple Sclerosis

    PubMed Central

    Kerstetter, AE; Padovani-Claudio, DA; Bai, L; Miller, RH

    2009-01-01

    Multiple sclerosis (MS) is a neurodegenerative disease characterized by demyelination/remyelination episodes that ultimately fail. Chemokines and their receptors have been implicated in both myelination and remyelination failure. Chemokines regulate migration, proliferation and differentiation of immune and neural cells during development and pathology. Previous studies have demonstrated that the absence of the chemokine receptor CXCR2 results in both disruption of early oligodendrocyte development and long term structural alterations in myelination. Histological studies suggest CXCL1, the primary ligand for CXCR2, is upregulated around the peripheral areas of demyelination suggesting this receptor/ligand combination modulates responses to injury. Here we show that in focal LPC induced demyelinating lesions, localized inhibition of CXCR2 signaling reduced lesion size and enhanced remyelination while systemic treatments were relatively less effective. Treatment of spinal cord cultures with CXCR2 antagonists reduced CXCL1 induced A2B5+ cell proliferation and increased differentiation of myelin producing cells. More critically, treatment of myelin oligodendrocyte glycoprotein peptide 35-55-induced EAE mice, an animal model of multiple sclerosis, with small molecule antagonists against CXCR2 results in increased functionality, decreased lesion load, and enhanced remyelination. Our findings demonstrate the importance of antagonizing CXCR2 in enhancing myelin repair by reducing lesion load and functionality in models of multiple sclerosis and thus provide a therapeutic target for demyelinating diseases. PMID:19616545

  8. Fractional modeling of the AC large-signal frequency response in magnetoresistive current sensors.

    PubMed

    Ravelo Arias, Sergio Iván; Ramírez Muñoz, Diego; Moreno, Jaime Sánchez; Cardoso, Susana; Ferreira, Ricardo; de Freitas, Paulo Jorge Peixeiro

    2013-01-01

    Fractional calculus is considered when derivatives and integrals of non-integer order are applied over a specific function. In the electrical and electronic domain, the transfer function dependence of a fractional filter not only by the filter order n, but additionally, of the fractional order α is an example of a great number of systems where its input-output behavior could be more exactly modeled by a fractional behavior. Following this aim, the present work shows the experimental ac large-signal frequency response of a family of electrical current sensors based in different spintronic conduction mechanisms. Using an ac characterization set-up the sensor transimpedance function Z(t)(JF) is obtained considering it as the relationship between sensor output voltage and input sensing current, Z(t)(jf)= V(o, sensor)(jf)/I(sensor)(jf). The study has been extended to various magnetoresistance sensors based in different technologies like anisotropic magnetoresistance (AMR), giant magnetoresistance (GMR), spin-valve (GMR-SV) and tunnel magnetoresistance (TMR). The resulting modeling shows two predominant behaviors, the low-pass and the inverse low-pass with fractional index different from the classical integer response. The TMR technology with internal magnetization offers the best dynamic and sensitivity properties opening the way to develop actual industrial applications. PMID:24351648

  9. Computational Modeling of PI3K/AKT and MAPK Signaling Pathways in Melanoma Cancer

    PubMed Central

    Pappalardo, Francesco; Russo, Giulia; Candido, Saverio; Pennisi, Marzio; Cavalieri, Salvatore; Motta, Santo; McCubrey, James A.; Nicoletti, Ferdinando; Libra, Massimo

    2016-01-01

    Background Malignant melanoma is an aggressive tumor of the skin and seems to be resistant to current therapeutic approaches. Melanocytic transformation is thought to occur by sequential accumulation of genetic and molecular alterations able to activate the Ras/Raf/MEK/ERK (MAPK) and/or the PI3K/AKT (AKT) signalling pathways. Specifically, mutations of B-RAF activate MAPK pathway resulting in cell cycle progression and apoptosis prevention. According to these findings, MAPK and AKT pathways may represent promising therapeutic targets for an otherwise devastating disease. Result Here we show a computational model able to simulate the main biochemical and metabolic interactions in the PI3K/AKT and MAPK pathways potentially involved in melanoma development. Overall, this computational approach may accelerate the drug discovery process and encourages the identification of novel pathway activators with consequent development of novel antioncogenic compounds to overcome tumor cell resistance to conventional therapeutic agents. The source code of the various versions of the model are available as S1 Archive. PMID:27015094

  10. Bi-exponential magnetic resonance signal model for partial volume computation.

    PubMed

    Duché, Quentin; Acosta, Oscar; Gambarota, Giulio; Merlet, Isabelle; Salvado, Olivier; Saint-Jalmes, Hervé

    2012-01-01

    Accurate quantification of small structures in magnetic resonance (MR) images is often limited by partial volume (PV) effects which arise when more than one tissue type is present in a voxel. PV may be critical when dealing with changes in brain anatomy as the considered structures such as gray matter (GM) are of similar size as the MR spatial resolution. To overcome the limitations imposed by PV effects and achieve subvoxel accuracy different methods have been proposed. Here, we describe a method to compute PV by modeling the MR signal with a biexponential linear combination representing the contribution of at most two tissues in each voxel. In a first step, we estimated the parameters (T1, T2 and proton density) per tissue. Then, based on the bi-exponential formulation one can retrieve fractional contents by solving a linear system of two equations with two unknowns, namely tissue magnetizations. Preliminary tests were conducted on images acquired on a specially designed physical phantom for the study of PV effects. Further, the model was tested on BrainWeb simulated brain images to estimate GM and white matter (WM) PV effects. Root mean squared error was computed between the BrainWeb ground truth and the obtained GM and WM PV maps. The proposed method outperformed traditionally used methods by 33% and 34% in GM and WM, respectively. PMID:23285556

  11. Automatic sleep staging based on ECG signals using hidden Markov models.

    PubMed

    Ying Chen; Xin Zhu; Wenxi Chen

    2015-08-01

    This study is designed to investigate the feasibility of automatic sleep staging using features only derived from electrocardiography (ECG) signal. The study was carried out using the framework of hidden Markov models (HMMs). The mean, and SD values of heart rates (HRs) computed from each 30-second epoch served as the features. The two feature sequences were first detrended by ensemble empirical mode decomposition (EEMD), formed as a two-dimensional feature vector, and then converted into code vectors by vector quantization (VQ) method. The output VQ indexes were utilized to estimate parameters for HMMs. The proposed model was tested and evaluated on a group of healthy individuals using leave-one-out cross-validation. The automatic sleep staging results were compared with PSG estimated ones. Results showed accuracies of 82.2%, 76.0%, 76.1% and 85.5% for deep, light, REM and wake sleep, respectively. The findings proved that HRs-based HMM approach is feasible for automatic sleep staging and can pave a way for developing more efficient, robust, and simple sleep staging system suitable for home application. PMID:26736316

  12. Quantifying internally generated and externally forced climate signals at regional scales in CMIP5 models

    NASA Astrophysics Data System (ADS)

    Lyu, Kewei; Zhang, Xuebin; Church, John A.; Hu, Jianyu

    2015-11-01

    The Earth's climate evolves because of both internal variability and external forcings. Using Coupled Model Intercomparison Project Phase 5 (CMIP5) models, here we quantify the ratio of externally forced variance to total variance on interannual and longer time scales for regional surface air temperature (SAT) and sea level, which depends on the relative strength of externally forced signal compared to internal variability. The highest ratios are found in tropical areas for SAT but at high latitudes for sea level over the historical period when ocean dynamics and global mean thermosteric contributions are considered. Averaged globally, the ratios over a fixed time interval (e.g., 30 years) are projected to increase during the 21st century under the business-as-usual scenario (RCP8.5). In contrast, under two mitigation scenarios (RCP2.6 and RCP4.5), the ratio declines sharply by the end of the 21st century for SAT, but only declines slightly or stabilizes for sea level, indicating a slower response of sea level to climate mitigation.

  13. Type-1 interferon signaling mediates neuro-inflammatory events in models of Alzheimer's disease.

    PubMed

    Taylor, Juliet M; Minter, Myles R; Newman, Andrew G; Zhang, Moses; Adlard, Paul A; Crack, Peter J

    2014-05-01

    A neuro-inflammatory response has been implicated in human patients and animal models of Alzheimer's disease (AD). Type-1 interferons are pleiotropic cytokines involved in the initiation and regulation of the pro-inflammatory response; however, their role in AD is unknown. This study investigated the contribution of type-1 IFN signaling in the neuro-inflammatory response to amyloid-beta (Aβ) in vitro and in the APP/PS1 transgenic mouse model of AD. Enzyme-linked immunosorbent assay confirmed a 2-fold increase in IFNα in APP/PS1 brains compared with control brains. Quantitative polymerase chain reaction also identified increased IFNα and IFNβ expression in human pre-frontal cortex from AD patients. In vitro studies in primary neurons demonstrated Aβ-induced type-1 IFN expression preceded that of other classical pro-inflammatory cytokines, IL1-β, and IL-6. Significantly, ablation of type-1 interferon-α receptor 1 expression in BE(2)M17 neuroblastoma cells and primary neurons afforded protection against Aβ-induced toxicity. This study supports a role for type-1 interferons in the pro-inflammatory response and neuronal cell death in AD and suggests that blocking type-1 interferon-α receptor 1 maybe a therapeutic target to limit the disease progression. PMID:24262201

  14. Local Signaling Environments and Human Male Infertility: What Can Be Learned from Mouse Models

    PubMed Central

    Nalam, Roopa L.; Matzuk, Martin M.

    2011-01-01

    Infertility is one of the most prevalent public health problems facing young adult males in today’s society. A clear, treatable cause of infertility cannot be determined in a large number of these patients, and a growing body of evidence suggests that infertility in many of these men may be due to genetic causes. Studies utilizing animal models, and most importantly, mouse knockout technology, have been integral not only for the study of normal spermatogenesis but also for identifying proteins essential for this process, which in turn are candidate genes for causing human male infertility. Successful spermatogenesis depends on a delicate balance of local signaling factors, and this review focuses specifically on the genes that encode these factors. Normal functioning of all testicular cell types is not only essential for normal fertility but, as recently hypothesized, may also be crucial to prevent germ cell oncogenesis. Analysis of these processes using mouse models in vivo has provided investigators with an invaluable tool to effectively translate basic science research to the research of human disease and infertility. PMID:20456819

  15. A model for food and stimulus changes that signal time-based contingency changes.

    PubMed

    Cowie, Sarah; Davison, Michael; Elliffe, Douglas

    2014-11-01

    When the availability of reinforcers depends on time since an event, time functions as a discriminative stimulus. Behavioral control by elapsed time is generally weak, but may be enhanced by added stimuli that act as additional time markers. The present paper assessed the effect of brief and continuous added stimuli on control by time-based changes in the reinforcer differential, using a procedure in which the local reinforcer ratio reversed at a fixed time after the most recent reinforcer delivery. Local choice was enhanced by the presentation of the brief stimuli, even when the stimulus change signalled only elapsed time, but not the local reinforcer ratio. The effect of the brief stimulus presentations on choice decreased as a function of time since the most recent stimulus change. We compared the ability of several versions of a model of local choice to describe these data. The data were best described by a model which assumed that error in discriminating the local reinforcer ratio arose from imprecise discrimination of reinforcers in both time and space, suggesting that timing behavior is controlled not only by discrimination elapsed time, but by discrimination of the reinforcer differential in time. PMID:25219928

  16. Fractional Modeling of the AC Large-Signal Frequency Response in Magnetoresistive Current Sensors

    PubMed Central

    Arias, Sergio Iván Ravello; Muñoz, Diego Ramírez; Moreno, Jaime Sánchez; Cardoso, Susana; Ferreira, Ricardo; de Freitas, Paulo Jorge Peixeiro

    2013-01-01

    Fractional calculus is considered when derivatives and integrals of non-integer order are applied over a specific function. In the electrical and electronic domain, the transfer function dependence of a fractional filter not only by the filter order n, but additionally, of the fractional order α is an example of a great number of systems where its input-output behavior could be more exactly modeled by a fractional behavior. Following this aim, the present work shows the experimental ac large-signal frequency response of a family of electrical current sensors based in different spintronic conduction mechanisms. Using an ac characterization set-up the sensor transimpedance function Zt(if) is obtained considering it as the relationship between sensor output voltage and input sensing current, Zt(jf)=Vo,sensor(jf)/Isensor(jf). The study has been extended to various magnetoresistance sensors based in different technologies like anisotropic magnetoresistance (AMR), giant magnetoresistance (GMR), spin-valve (GMR-SV) and tunnel magnetoresistance (TMR). The resulting modeling shows two predominant behaviors, the low-pass and the inverse low-pass with fractional index different from the classical integer response. The TMR technology with internal magnetization offers the best dynamic and sensitivity properties opening the way to develop actual industrial applications. PMID:24351648

  17. Neuroretinal hypoxic signaling in a new preclinical murine model for proliferative diabetic retinopathy

    PubMed Central

    Wert, Katherine J; Mahajan, Vinit B; Zhang, Lijuan; Yan, Yuanqing; Li, Yao; Tosi, Joaquin; Hsu, Chun Wei; Nagasaki, Takayuki; Janisch, Kerstin M; Grant, Maria B; Mahajan, MaryAnn; Bassuk, Alexander G; Tsang, Stephen H

    2016-01-01

    Diabetic retinopathy (DR) affects approximately one-third of diabetic patients and, if left untreated, progresses to proliferative DR (PDR) with associated vitreous hemorrhage, retinal detachment, iris neovascularization, glaucoma and irreversible blindness. In vitreous samples of human patients with PDR, we found elevated levels of hypoxia inducible factor 1 alpha (HIF1α). HIFs are transcription factors that promote hypoxia adaptation and have important functional roles in a wide range of ischemic and inflammatory diseases. To recreate the human PDR phenotype for a preclinical animal model, we generated a mouse with neuroretinal-specific loss of the von Hippel Lindau tumor suppressor protein, a protein that targets HIF1α for ubiquitination. We found that the neuroretinal cells in these mice overexpressed HIF1α and developed severe, irreversible ischemic retinopathy that has features of human PDR. Rapid progression of retinopathy in these mutant mice should facilitate the evaluation of therapeutic agents for ischemic and inflammatory blinding disorders. In addition, this model system can be used to manipulate the modulation of the hypoxia signaling pathways, for the treatment of non-ocular ischemic and inflammatory disorders. PMID:27195131

  18. Developmental maturation of dynamic causal control signals in higher-order cognition: a neurocognitive network model.

    PubMed

    Supekar, Kaustubh; Menon, Vinod

    2012-02-01

    Cognitive skills undergo protracted developmental changes resulting in proficiencies that are a hallmark of human cognition. One skill that develops over time is the ability to problem solve, which in turn relies on cognitive control and attention abilities. Here we use a novel multimodal neurocognitive network-based approach combining task-related fMRI, resting-state fMRI and diffusion tensor imaging (DTI) to investigate the maturation of control processes underlying problem solving skills in 7-9 year-old children. Our analysis focused on two key neurocognitive networks implicated in a wide range of cognitive tasks including control: the insula-cingulate salience network, anchored in anterior insula (AI), ventrolateral prefrontal cortex and anterior cingulate cortex, and the fronto-parietal central executive network, anchored in dorsolateral prefrontal cortex and posterior parietal cortex (PPC). We found that, by age 9, the AI node of the salience network is a major causal hub initiating control signals during problem solving. Critically, despite stronger AI activation, the strength of causal regulatory influences from AI to the PPC node of the central executive network was significantly weaker and contributed to lower levels of behavioral performance in children compared to adults. These results were validated using two different analytic methods for estimating causal interactions in fMRI data. In parallel, DTI-based tractography revealed weaker AI-PPC structural connectivity in children. Our findings point to a crucial role of AI connectivity, and its causal cross-network influences, in the maturation of dynamic top-down control signals underlying cognitive development. Overall, our study demonstrates how a unified neurocognitive network model when combined with multimodal imaging enhances our ability to generalize beyond individual task-activated foci and provides a common framework for elucidating key features of brain and cognitive development. The

  19. Inflammation-mediated abrogation of androgen signaling: an in vitro model of prostate cell inflammation.

    PubMed

    Debelec-Butuner, Bilge; Alapinar, Cansu; Varisli, Lokman; Erbaykent-Tepedelen, Burcu; Hamid, Syed Muhammad; Gonen-Korkmaz, Ceren; Korkmaz, Kemal Sami

    2014-02-01

    As a link between inflammation and cancer has been reported in many studies, we established an in vitro model of prostatic inflammation to investigate the loss of androgen receptor (AR)-mediated signaling in androgen responsive prostate cell lines. First, the U937 monocyte cell line was differentiated into macrophages using phorbol acetate (PMA), and cells were induced with lipopolysaccharide (LPS) for cytokine secretion. Next, the cytokine levels (TNFα, IL-6, and IL1β) in conditioned media (CM) were analyzed. Prostate cells were then fed with CM containing varying concentrations of TNFα, and IkB degradation, nuclear factor kappa B (NFκB) translocation and transactivation, and the expression of matrix metalloproteinase-8 (MMP8) and matrix metalloproteinase-9 (MMP9) were then assessed. As a result of CM treatment, ubiquitin-mediated AR degradation, which was restored using anti-TNFα antibody neutralization, led to both a decrease in KLK4, PSA, and NKX3.1 expression levels and the upregulation of GPX2. In addition to the loss of AR, acute and chronic CM exposure resulted in p53 degradation and consequent p21 downregulation, which was also restored by either androgen administration or ectopic NKX3.1 expression via the stabilization of MDM2 levels in LNCaP cells. Additionally, CM treatment enhanced H2AX((S139)) phosphorylation (a hallmark of DNA damage) and genetic heterogeneity in the absence of androgens in prostate cells without activating mitochondrial apoptosis. Thus, the data suggest that inflammatory cytokine exposure results in the loss of AR and p53 signaling in prostate cells and facilitates genetic heterogeneity via ROS accumulation to promote prostate carcinogenesis. PMID:22911881

  20. Modelling discontinuous well log signal to identify lithological boundaries via wavelet analysis: An example from KTB borehole data

    NASA Astrophysics Data System (ADS)

    Singh, Amrita; Maiti, Saumen; Tiwari, R. K.

    2016-06-01

    Identification of sharp and discontinuous lithological boundaries from well log signal stemming from heterogeneous subsurface structures assumes a special significance in geo-exploration studies. Well log data acquired from various geological settings generally display nonstationary/nonlinear characteristics with varying wavelengths and frequencies. Modelling of such complex well-log signals using the conventional signal processing techniques either fails to catch-up abrupt boundaries or at the best, do not provide precise information on insidious lithological discontinuities. In this paper, we have proposed a new wavelet transform-based algorithm to model the abrupt discontinuous changes from well log data by taking care of nonstationary characteristics of the signal. Prior to applying the algorithm on the geophysical well data, we analyzed the distribution of wavelet coefficients using synthetic signal generated by the first order nonstationary auto-regressive model and then applied the method on actual well log dataset obtained from the KTB bore hole, Germany. Besides identifying the formation of layered boundaries, the underlying method also maps some additional formation boundaries, which were hitherto undetected at the KTB site. The results match well with known geological lithostratigraphy and will be useful for constraining the future model of KTB bore hole data.

  1. A multi-level model accounting for the effects of JAK2-STAT5 signal modulation in erythropoiesis.

    PubMed

    Lai, Xin; Nikolov, Svetoslav; Wolkenhauer, Olaf; Vera, Julio

    2009-08-01

    We develop a multi-level model, using ordinary differential equations, based on quantitative experimental data, accounting for murine erythropoiesis. At the sub-cellular level, the model includes a description of the regulation of red blood cell differentiation through Epo-stimulated JAK2-STAT5 signalling activation, while at the cell population level the model describes the dynamics of (STAT5-mediated) red blood cell differentiation from their progenitors. Furthermore, the model includes equations depicting the hypoxia-mediated regulation of hormone erythropoietin blood levels. Take all together, the model constitutes a multi-level, feedback loop-regulated biological system, involving processes in different organs and at different organisational levels. We use our model to investigate the effect of deregulation in the proteins involved in the JAK2-STAT5 signalling pathway in red blood cells. Our analysis results suggest that down-regulation in any of the three signalling system components affects the hematocrit level in an individual considerably. In addition, our analysis predicts that exogenous Epo injection (an already existing treatment for several blood diseases) may compensate the effects of single down-regulation of Epo hormone level, STAT5 or EpoR/JAK2 expression level, and that it may be insufficient to counterpart a combined down-regulation of all the elements in the JAK2-STAT5 signalling cascade. PMID:19660986

  2. Modeling miRNA regulation in cancer signaling systems: miR-34a regulation of the p53/Sirt1 signaling module.

    PubMed

    Lai, Xin; Wolkenhauer, Olaf; Vera, Julio

    2012-01-01

    MicroRNAs (miRNAs) are a family of small regulatory RNAs whose function is to regulate the activity and stability of specific messenger RNA targets through posttranscriptional regulatory mechanisms. Most of the times signaling systems involving miRNA modulation are not linear pathways in which a certain transcription factor activate the expression of miRNAs that posttranscriptionally represses targeting proteins, but complex regulatory structures involving a variety of feedback-loop architectures.In this book chapter, we define, discuss, and apply a Systems Biology approach to investigate dynamical features of miRNA regulation, based on the integration of experimental evidences, hypotheses, and quantitative data through mathematical modeling. We further illustrate the approach using as case study the signaling module composed by the proteins p53, Sirt1, and the regulatory miRNA miR-34a. The model was used not only to investigate different possible designs of the silencing mechanism exerted by miR-34a on Sirt1 but also to simulate the dynamics of the system under conditions of (pathological) deregulation of its compounds. PMID:23361983

  3. Heart beat detection in multimodal physiological data using a hidden semi-Markov model and signal quality indices.

    PubMed

    A F Pimentel, Marco; Santos, Mauro D; Springer, David B; Clifford, Gari D

    2015-08-01

    Accurate heart beat detection in signals acquired from intensive care unit (ICU) patients is necessary for establishing both normality and detecting abnormal events. Detection is normally performed by analysing the electrocardiogram (ECG) signal, and alarms are triggered when parameters derived from this signal exceed preset or variable thresholds. However, due to noisy and missing data, these alarms are frequently deemed to be false positives, and therefore ignored by clinical staff. The fusion of features derived from other signals, such as the arterial blood pressure (ABP) or the photoplethysmogram (PPG), has the potential to reduce such false alarms. In order to leverage the highly correlated temporal nature of the physiological signals, a hidden semi-Markov model (HSMM) approach, which uses the intra- and inter-beat depolarization interval, was designed to detect heart beats in such data. Features based on the wavelet transform, signal gradient and signal quality indices were extracted from the ECG and ABP waveforms for use in the HSMM framework. The presented method achieved an overall score of 89.13% on the hidden/test data set provided by the Physionet/Computing in Cardiology Challenge 2014: Robust Detection of Heart Beats in Multimodal Data. PMID:26218536

  4. Numerical Calculation of LP Seismic Signals Modeling the Fluid-Rock Interaction in Simulated Volcanic Conduits

    NASA Astrophysics Data System (ADS)

    Arciniega-Ceballos, Alejandra; Corona-Romero, Pedro; Sanchez-Sesma, Francisco

    2010-05-01

    We present an investigation of the fluid-solid dynamic interaction of a fluid-driven cylindrical conduit embedded within an infinite, homogeneous elastic space with physical properties similar to those encountered in volcanic environments. In our model, a pressure transient is applied at the bottom of the conduit, which perturbs the steady flow of incompressible viscous fluid, driven by a pressure gradient. The model includes radial variation of a cylindrical fluid-filled conduit driven by changes in the flow velocity of a Newtonian fluid and a pressure gradient. Both fluid and solid are dynamically coupled by the continuity of radial velocities and shear and radial stresses at the conduit wall. The conduit dynamics are governed by three ordinary non-linear differential equations of second order, which are solved numerically by applying a fifth-order Runge-Kutta scheme. Our model allows for any number of pipe segments of different sizes coupled in series, thus representing an extended source region, which closely mimics the geometry of realistic volcanic conduits. Various examples of fluid-filled pipe-systems, starting from the simplest penny-shape geometries up to conduits of hundreds of meters in length, are presented. The values assumed for the fluid density and viscosity are in the mean range of basaltic and andesitic composition. Far-field velocity synthetics radiated by the motion of the conduit and fluid flows ascending to the surface display characteristic waveforms and frequency contents that closely resemble those of long-period (LP) signals observed at active volcanoes.

  5. Modeling Analysis of Signal Sensitivity and Specificity by Vibrio fischeri LuxR Variants

    PubMed Central

    Colton, Deanna M.; Stabb, Eric V.; Hagen, Stephen J.

    2015-01-01

    The LuxR protein of the bacterium Vibrio fischeri belongs to a family of transcriptional activators that underlie pheromone-mediated signaling by responding to acyl-homoserine lactones (-HSLs) or related molecules. V. fischeri produces two acyl-HSLs, N-3-oxo-hexanoyl-HSL (3OC6-HSL) and N-octanoyl-HSL (C8-HSL), each of which interact with LuxR to facilitate its binding to a “lux box” DNA sequence, thereby enabling LuxR to activate transcription of the lux operon responsible for bioluminescence. We have investigated the HSL sensitivity of four different variants of V. fischeri LuxR: two derived from wild-type strains ES114 and MJ1, and two derivatives of LuxRMJ1 generated by directed evolution. For each LuxR variant, we measured the bioluminescence induced by combinations of C8-HSL and 3OC6-HSL. We fit these data to a model in which the two HSLs compete with each other to form multimeric LuxR complexes that directly interact with lux to activate bioluminescence. The model reproduces the observed effects of HSL combinations on the bioluminescence responses directed by LuxR variants, including competition and non-monotonic responses to C8-HSL and 3OC6-HSL. The analysis yields robust estimates for the underlying dissociation constants and cooperativities (Hill coefficients) of the LuxR-HSL complexes and their affinities for the lux box. It also reveals significant differences in the affinities of LuxRMJ1 and LuxRES114 for 3OC6-HSL. Further, LuxRMJ1 and LuxRES114 differed sharply from LuxRs retrieved by directed evolution in the cooperativity of LuxR-HSL complex formation and the affinity of these complexes for lux. These results show how computational modeling of in vivo experimental data can provide insight into the mechanistic consequences of directed evolution. PMID:25962099

  6. Model predictions for the WAXS signals of healthy and malignant breast duct biopsies

    NASA Astrophysics Data System (ADS)

    LeClair, R. J.

    2014-03-01

    A wide-angle x-ray scatter (WAXS) measurement could potentially be used to determine whether a biopsy of a breast duct is healthy or malignant. A ductal carcinoma in situ (DCIS) occurs when the epithelial cells lining the wall start to replicate and invade the duct interior. Since cells are composed mainly of water a WAXS signal of DCIS could contain a larger component due to water. A model approximates that a breast duct biopsy consists of connective tissue (c.t.) and cells. For a 2 mm diameter 3.81 mm thick healthy duct biopsy, the volumes in cubic mm are 11.56 c.t. and 0.41 cells whereas 6.64 c.t. and 5.33 cells for DCIS. The differential linear scattering coefficients (μs) for both types of biopsies were calculated using the sum vc.t.μsc.t. + vcellμscell where v denotes fractional volume. The cell was assumed to be composed of water, lipids (fat), and other atoms associated with RNA, DNA, proteins, and carbohydrates. The μscell was calculated using the sum 0.771μswater + 0.023μsfat + 0.206μsother. The μs of c.t., water, and fat were available from literature whereas the independent atomic model approximation was used to calculate values for μsother. A WAXS model provided predictions of the number of 6 degree scattered photons Ns for incident 50 kV beams on healthy and malignant ducts. The sum of Ns between 31.5 <= E <= 45 keV were 1402 and 1529 for respectively the healthy and malignant biopsies. Using Poisson statistics, two Gaussian distributions, and a descision threshold set at their intersection, the false positive and false negative probabilities were 4.7% and 5.0%. This work suggests that DCIS could potentially be diagnosed via energy dispersive WAXS measurements.

  7. A neural network model with dopamine-like reinforcement signal that learns a spatial delayed response task.

    PubMed

    Suri, R E; Schultz, W

    1999-01-01

    This study investigated how the simulated response of dopamine neurons to reward-related stimuli could be used as reinforcement signal for learning a spatial delayed response task. Spatial delayed response tasks assess the functions of frontal cortex and basal ganglia in short-term memory, movement preparation and expectation of environmental events. In these tasks, a stimulus appears for a short period at a particular location, and after a delay the subject moves to the location indicated. Dopamine neurons are activated by unpredicted rewards and reward-predicting stimuli, are not influenced by fully predicted rewards, and are depressed by omitted rewards. Thus, they appear to report an error in the prediction of reward, which is the crucial reinforcement term in formal learning theories. Theoretical studies on reinforcement learning have shown that signals similar to dopamine responses can be used as effective teaching signals for learning. A neural network model implementing the temporal difference algorithm was trained to perform a simulated spatial delayed response task. The reinforcement signal was modeled according to the basic characteristics of dopamine responses to novel stimuli, primary rewards and reward-predicting stimuli. A Critic component analogous to dopamine neurons computed a temporal error in the prediction of reinforcement and emitted this signal to an Actor component which mediated the behavioral output. The spatial delayed response task was learned via two subtasks introducing spatial choices and temporal delays, in the same manner as monkeys in the laboratory. In all three tasks, the reinforcement signal of the Critic developed in a similar manner to the responses of natural dopamine neurons in comparable learning situations, and the learning curves of the Actor replicated the progress of learning observed in the animals. Several manipulations demonstrated further the efficacy of the particular characteristics of the dopamine

  8. Excitation and Adaptation in Bacteria–a Model Signal Transduction System that Controls Taxis and Spatial Pattern Formation

    PubMed Central

    Othmer, Hans G.; Xin, Xiangrong; Xue, Chuan

    2013-01-01

    The machinery for transduction of chemotactic stimuli in the bacterium E. coli is one of the most completely characterized signal transduction systems, and because of its relative simplicity, quantitative analysis of this system is possible. Here we discuss models which reproduce many of the important behaviors of the system. The important characteristics of the signal transduction system are excitation and adaptation, and the latter implies that the transduction system can function as a “derivative sensor” with respect to the ligand concentration in that the DC component of a signal is ultimately ignored if it is not too large. This temporal sensing mechanism provides the bacterium with a memory of its passage through spatially- or temporally-varying signal fields, and adaptation is essential for successful chemotaxis. We also discuss some of the spatial patterns observed in populations and indicate how cell-level behavior can be embedded in population-level descriptions. PMID:23624608

  9. Conditional ablation of TGF-β signaling inhibits tumor progression and invasion in an induced mouse bladder cancer model

    PubMed Central

    Liang, Yu; Zhu, Fengyu; Zhang, Haojie; Chen, Demeng; Zhang, Xiuhong; Gao, Qian; Li, Yang

    2016-01-01

    The role of transforming growth factor-β (TGF-β) signaling in cancer progression is still under debate. To determine the function of TGF-β signaling in bladder cancer progression, we conditionally knocked out the Tgfbr2 in mouse model after a N-butyl-N-4-hydroxybutyl Nitrosamine induced bladder carcinogenesis. We found the ablation of TGF-β signaling could inhibit the cancer cell proliferation, cancer stem cell population and EMT, hence suppressed the invasive cancer progression, which is similar with the result of TGF-β receptor I inhibitor treatment. These findings recognize the roles and mechanisms of TGF-β signaling in bladder cancer progression in vivo for the first time. PMID:27378170

  10. A Large Signal Model for CMUT Arrays with Arbitrary Membrane Geometries Operating in Non-Collapsed Mode

    PubMed Central

    Satir, Sarp; Zahorian, Jaime; Degertekin, F. Levent

    2014-01-01

    A large signal, transient model has been developed to predict the output characteristics of a CMUT array operated in the non-collapse mode. The model is based on separation of the nonlinear electrostatic voltage-to-force relation and the linear acoustic array response. For linear acoustic radiation and crosstalk effects, the boundary element method is used. The stiffness matrix in the vibroacoustics calculations is obtained using static finite element analysis of a single membrane which can have arbitrary geometry and boundary conditions. A lumped modeling approach is used to reduce the order of the system for modeling the transient nonlinear electrostatic actuation. To accurately capture the dynamics of the non-uniform electrostatic force distribution over the CMUT electrode during large deflections, the membrane electrode is divided into patches shaped to match higher order membrane modes, each introducing a variable to the system model. This reduced order nonlinear lumped model is solved in the time domain using Simulink. The model has two linear blocks to calculate the displacement profile of the electrode patches and the output pressure for a given force distribution over the array, respectively. The force to array displacement block uses the linear acoustic model, and the Rayleigh integral is evaluated to calculate the pressure at any field point. Using the model, the transient transmitted pressure can be simulated for different large signal drive signal configurations. The acoustic model is verified by comparison to harmonic FEA in vacuum and fluid for high and low aspect ratio membranes as well as mass-loaded membranes. The overall Simulink model is verified by comparison to transient 3D FEA and experimental results for different large drive signals; and an example for a phased array simulation is given. PMID:24158297

  11. T3_MM: A Markov Model Effectively Classifies Bacterial Type III Secretion Signals

    PubMed Central

    Wang, Yejun; Sun, Ming'an; Bao, Hongxia; White, Aaron P.

    2013-01-01

    Motivation Type III Secretion Systems (T3SSs) play important roles in the interaction between gram-negative bacteria and their hosts. T3SSs function by translocating a group of bacterial effector proteins into the host cytoplasm. The details of specific type III secretion process are yet to be clarified. This research focused on comparing the amino acid composition within the N-terminal 100 amino acids from type III secretion (T3S) signal sequences or non-T3S proteins, specifically whether each residue exerts a constraint on residues found in adjacent positions. We used these comparisons to set up a statistic model to quantitatively model and effectively distinguish T3S effectors. Results In this study, the amino acid composition (Aac) probability profiles conditional on its sequentially preceding position and corresponding amino acids were compared between N-terminal sequences of T3S and non-T3S proteins. The profiles are generally different. A Markov model, namely T3_MM, was consequently designed to calculate the total Aac conditional probability difference, i.e., the likelihood ratio of a sequence being a T3S or a non-T3S protein. With T3_MM, known T3S and non-T3S proteins were found to well approximate two distinct normal distributions. The model could distinguish validated T3S and non-T3S proteins with a 5-fold cross-validation sensitivity of 83.9% at a specificity of 90.3%. T3_MM was also shown to be more robust, accurate, simple, and statistically quantitative, when compared with other T3S protein prediction models. The high effectiveness of T3_MM also indicated the overall Aac difference between N-termini of T3S and non-T3S proteins, and the constraint of Aac exerted by its preceding position and corresponding Aac. Availability An R package for T3_MM is freely downloadable from: http://biocomputer.bio.cuhk.edu.hk/softwares/T3_MM. T3_MM web server: http://biocomputer.bio.cuhk.edu.hk/T3DB/T3_MM.php. PMID:23472154

  12. Hydrological Modeling of Groundwater Disturbance to Gravity Signal for High-accuracy Monitoring of Volcanic Activity

    NASA Astrophysics Data System (ADS)

    Kazama, T.; Okubo, S.

    2007-12-01

    Gravity observation is one of the effective methods to detect magma movements in volcanic eruptions [e.g., Furuya et al., J. Geoph. Res., 2003]. Groundwater-derived disturbances have to be corrected from gravity variations for highly accurate monitoring of volcanic activities. They have been corrected with empirical methods, such as tank models and regression curves [e.g., Imanishi et al., J. Geodyn., 2006]. These methods, however, are not based on hydrological background, and are very likely to eliminate volcanic signals excessively. The correction method of groundwater disturbance has to be developed with hydrological and quantitative approach. We thus estimate the gravity disturbance arising from groundwater as follows. (1) Groundwater distributions are simulated on a hydrological model, utilizing groundwater flow equations. (2) Groundwater-derived gravity value is estimated for each instant of time, by integrating groundwater distributions spatially. (3) The groundwater-derived gravity, as the correction value, is subtracted from observed gravity data. In this study, we simulated groundwater flow and groundwater-derived gravity value on the east part of the Asama volcano, central Japan. A simple hydrological model was supposed, consisting of homogeneous soil, lying on a flat impermeable basement. Hydraulic conductivity, which defines groundwater velocity, was set as 2.0×10-6[m/s], which is consistent with typical volcanic soils. We also observed time variations of watertable height, soil moisture and gravity simultaneously during the summer of 2006 at Asama volcano, and compared the observations with the theoretical values. Both simulated groundwater distributions and gravity changes agree fairly well with observed values. On variations of water level and moisture content, rapid increase at the time of rainfalls and exponential decrease after rainfalls were illustrated. Theoretical gravity changes explained 90% of the observed gravity increase (+20μgals) for

  13. Measuring and Modeling Xenon Uptake in Plastic Beta-Cells

    NASA Astrophysics Data System (ADS)

    Suarez, R.; Hayes, J. C.; Harper, W. W.; Humble, P.; Ripplinger, M. D.; Stephenson, D. E.; Williams, R. M.

    2013-12-01

    The precision of the stable xenon volume measurement in atmospheric monitoring radio-xenon systems is a critical parameter used to determine the activity concentration of a radio-xenon sample. Typically these types of systems use a plastic scintillating beta-cell as part of a beta-gamma detection scheme to measure the radioactivity present in the gas sample. Challenges arise when performing the stable xenon calculation during or after radioactive counting of the sample due to xenon uptake into the plastic beta-cells. Plastic beta cells can adsorb as much as 5% of the sample during counting. If quantification is performed after counting, the uptake of xenon into the plastic results in an underestimation of the xenon volume measurement. This behavior also causes what is typically known as 'memory effect' in the cell. Experiments were conducted using a small volume low pressure range thermal conductivity sensor to quantify the amount of xenon uptake into the cell over a given period of time. Understanding the xenon uptake in the cell provides a better estimate of the stable volume which improves the overall measurement capability of the system. The results from these experiments along with modeling will be presented.

  14. Retinal Intrinsic Optical Signals in a Cat Model of Primary Congenital Glaucoma

    PubMed Central

    Schallek, Jesse B.; McLellan, Gillian J.; Viswanathan, Suresh; Ts'o, Daniel Y.

    2012-01-01

    Purpose. To examine the impact of reduced inner retinal function and breed on intrinsic optical signals in cats. Methods. Retinal intrinsic optical signals were recorded from anesthetized cats with a modified fundus camera. Near infrared light (NIR, 700–900 nm) was used to illuminate the retina while a charge-coupled device (CCD) camera captured the NIR reflectance of the retina. Visible stimuli (540 nm) evoked patterned changes in NIR retinal reflectance. NIR intrinsic signals were compared across three subject groups: two Siamese cats with primary congenital glaucoma (PCG), a control Siamese cat without glaucoma, and a control group of seven normally pigmented cats. Intraocular pressure (IOP), pattern electroretinogram, and optical coherence tomography measurements were evaluated to confirm the inner retinal deficit in PCG cats. Results. Stimulus-evoked, NIR retinal reflectance signals were observed in PCG cats despite severe degeneration of the nerve fiber layer and inner retinal function. The time course, spectral dependence, and spatial profile of signals imaged in PCG cats were similar to signals measured from normal and Siamese control cats. Conclusions. Despite increased IOP, reduced nerve fiber layer thickness and ganglion cell function, intrinsic optical signals persist in cats affected with PCG. The mechanisms giving rise to intrinsic signals remain despite inner retinal damage. Signal strength was reduced in all Siamese cats compared to controls, suggesting that reduced intrinsic signals in PCG cats represent a difference between breeds rather than loss of ganglion cells. These results corroborated previous findings that retinal ganglion cells are not the dominant source of intrinsic optical signals of the retina. PMID:22395886

  15. Bystander signalling: exploring clinical relevance through new approaches and new models.

    PubMed

    Butterworth, K T; McMahon, S J; Hounsell, A R; O'Sullivan, J M; Prise, K M

    2013-10-01

    Classical radiation biology research has centred on nuclear DNA as the main target of radiation-induced damage. Over the past two decades, this has been challenged by a significant amount of scientific evidence clearly showing radiation-induced cell signalling effects to have important roles in mediating overall radiobiological response. These effects, generally termed radiation-induced bystander effects (RIBEs) have challenged the traditional DNA targeted theory in radiation biology and highlighted an important role for cells not directly traversed by radiation. The multiplicity of experimental systems and exposure conditions in which RIBEs have been observed has hindered precise definitions of these effects. However, RIBEs have recently been classified for different relevant human radiation exposure scenarios in an attempt to clarify their role in vivo. Despite significant research efforts in this area, there is little direct evidence for their role in clinically relevant exposure scenarios. In this review, we explore the clinical relevance of RIBEs from classical experimental approaches through to novel models that have been used to further determine their potential implications in the clinic. PMID:23849503

  16. Sources of dynamic variability in NF-κB signal transduction: A mechanistic model

    PubMed Central

    Mothes, Janina; Busse, Dorothea; Kofahl, Bente; Wolf, Jana

    2015-01-01

    The transcription factor NF-κB (p65/p50) plays a central role in the coordination of cellular responses by activating the transcription of numerous target genes. The precise role of the dynamics of NF-κB signalling in regulating gene expression is still an open question. Here, we show that besides external stimulation intracellular parameters can influence the dynamics of NF-κB. By applying mathematical modelling and bifurcation analyses, we show that NF-κB is capable of exhibiting different types of dynamics in response to the same stimulus. We identified the total NF-κB concentration and the IκBα transcription rate constant as two critical parameters that modulate the dynamics and the fold change of NF-κB. Both parameters might vary as a result of cell-to-cell variability. The regulation of the IκBα transcription rate constant, e.g. by co-factors, provides the possibility of regulating the NF-κB dynamics by crosstalk. PMID:25640005

  17. Nitric oxide signaling is disrupted in the yeast model for Batten disease.

    PubMed

    Osório, Nuno S; Carvalho, Agostinho; Almeida, Agostinho J; Padilla-Lopez, Sérgio; Leão, Cecília; Laranjinha, João; Ludovico, Paula; Pearce, David A; Rodrigues, Fernando

    2007-07-01

    The juvenile form of neuronal ceroid lipofuscinoses (JNCLs), or Batten disease, results from mutations in the CLN3 gene, and it is characterized by the accumulation of lipopigments in the lysosomes of several cell types and by extensive neuronal death. We report that the yeast model for JNCL (btn1-Delta) that lacks BTN1, the homologue to human CLN3, has increased resistance to menadione-generated oxidative stress. Expression of human CLN3 complemented the btn1-Delta phenotype, and equivalent Btn1p/Cln3 mutations correlated with JNCL severity. We show that the previously reported decreased levels of L-arginine in btn1-Delta limit the synthesis of nitric oxide (.NO) in both physiological and oxidative stress conditions. This defect in .NO synthesis seems to suppress the signaling required for yeast menadione-induced apoptosis, thus explaining btn1-Delta phenotype of increased resistance. We propose that in JNCL, a limited capacity to synthesize .NO directly caused by the absence of Cln3 function may contribute to the pathology of the disease. PMID:17475770

  18. Focused attention vs. crossmodal signals paradigm: deriving predictions from the time-window-of-integration model.

    PubMed

    Colonius, Hans; Diederich, Adele

    2012-01-01

    In the crossmodal signals paradigm (CSP) participants are instructed to respond to a set of stimuli from different modalities, presented more or less simultaneously, as soon as a stimulus from any modality has been detected. In the focused attention paradigm (FAP), on the other hand, responses should only be made to a stimulus from a pre-defined target modality and stimuli from non-target modalities should be ignored. Whichever paradigm is being applied, a typical result is that responses tend to be faster to crossmodal stimuli than to unimodal stimuli, a phenomenon often referred to as "crossmodal interaction." Here, we investigate predictions of the time-window-of-integration (TWIN) modeling framework previously proposed by the authors. It is shown that TWIN makes specific qualitative and quantitative predictions on how the two paradigms differ with respect to the probability of multisensory integration and the amount of response enhancement, including the effect of stimulus intensity ("inverse effectiveness"). Introducing a decision-theoretic framework for TWIN further allows comparing the two paradigms with respect to the predicted optimal time window size and its dependence on the prior probability that the crossmodal stimulus information refers to the same event. In order to test these predictions, experimental studies that systematically compare crossmodal effects under stimulus conditions that are identical except for the CSP-FAP instruction should be performed in the future. PMID:22952460

  19. A new ECG biomarker for drug toxicity: a combined signal processing and computational modeling study.

    PubMed

    Jie, Xiao; Rodriguez, Blanca; Pueyo, Esther

    2010-01-01

    QT prolongation is the only clinically proven, yet insufficient, electrocardiogram (ECG) biomarker for drug-induced cardiac toxicity. The goal of this study is to evaluate whether JT area, i.e., total area of the T-wave, can serve as an ECG biomarker for drug-induced cardiac toxicity using both signal processing and computational modeling approaches. An ECG dataset that contained recordings from patients under control and sotalol condition was analyzed. In order to relate sotalol-induced ECG changes to its effect on ion channel level, i.e., blockade of the rapid component of the delayed rectifier potassium channel (I(Kr)), varied degrees of I(Kr) blockade were simulated in a slab of ventricular tissue. The mean JT area increased by 36.5% following the administration of sotalol in patients. Simulations in the slab tissue showed that sotalol increased action potential duration preferentially in the midmyocardium, which led to increased transmural dispersion of repolarization and JT area. In conclusion, JT area reflects the transmural dispersion of repolarization and may be a potentially useful surrogate/supplemental ECG biomarker to assess drug safety. PMID:21096447

  20. Modelling c-Abl Signalling in Activated Neutrophils: the Anti-inflammatory Effect of Seliciclib.

    PubMed

    Jackson, Robert C; Radivoyevitch, Tomas

    2013-03-01

    When mammalian tissues are infected by bacteria or fungi, inflammatory cytokines are released that cause circulating neutrophils to invade the infected tissue. The cytosolic tyrosine kinase, c-Abl, in these tissue neutrophils is activated by TNFα. c-Abl then phosphorylates STAT transcription factors, which results in production of the antiapoptotic protein Mcl-1. The normally short-lived tissue neutrophils are then unable to enter apoptosis. c-Abl also causes release of reactive oxygen species (ROS) from the mitochondria of the activated neutrophils. These ROS, and ROS generated by NADPH oxidase, are bactericidal agents of the innate immune system. In some inflammatory diseases, such as chronic obstructive pulmonary disease (COPD), the invading neutrophils become permanently activated, and the resulting ROS overproduction causes severe tissue damage. The cyclin-dependent kinase inhibitor, seliciclib, blocks transcription through inhibition of cdk9. This results in a relatively rapid decline of antiapoptotic Mcl-1 transcripts in activated neutrophils, an increase in neutrophil apoptosis, and less ROS leakage and oxidative damage. We present here a model of neutrophil kinetics that simulates the principal pathways of c-Abl signalling and use it to explore possible treatment options for inflammatory lung disease. PMID:24765523

  1. A Monte Carlo model reveals independent signaling at central glutamatergic synapses.

    PubMed Central

    Franks, Kevin M; Bartol, Thomas M; Sejnowski, Terrence J

    2002-01-01

    We have developed a biophysically realistic model of receptor activation at an idealized central glutamatergic synapse that uses Monte Carlo techniques to simulate the stochastic nature of transmission following release of a single synaptic vesicle. For the a synapse with 80 AMPA and 20 NMDA receptors, a single quantum, with 3000 glutamate molecules, opened approximately 3 NMDARs and 20 AMPARs. The number of open receptors varied directly with the total number of receptors, and the fraction of open receptors did not depend on the ratio of co-localized AMPARs and NMDARs. Variability decreased with increases in either total receptor number or quantal size, and differences between the variability of AMPAR and NMDAR responses were due solely to unequal numbers of receptors at the synapse. Despite NMDARs having a much higher affinity for glutamate than AMPARs, quantal release resulted in similar occupancy levels in both receptor types. Receptor activation increased with number of transmitter molecules released or total receptor number, whereas occupancy levels were only dependent on quantal size. Tortuous diffusion spaces reduced the extent of spillover and the activation of extrasynaptic receptors. These results support the conclusion that signaling is spatially independent within and between central glutamatergic synapses. PMID:12414671

  2. Loss of Signal Transduction and Inhibition of Lymphocyte Locomotion in a Ground-Based Model of Microgravity

    NASA Technical Reports Server (NTRS)

    Sundaresan, Alamelu; Risin, Diana; Pellis, Neal R.

    1999-01-01

    Inflammatory adherence to, and locomotion through the interstitium is an important component of the immune response. Conditions such as true gravity (TG) and modeled microgravity (MMG) severely inhibit lymphocyte locomotion in vitro through gelled Type I collagen (Pellis et al., 1994, 1997). We used the rotating-wall vessel bioreactor (RWV) as a prototype for modeled microgravity. After observing that lymphocyte locomotion was severely affected in modeled microgravity, we found that polyclonal activation of lymphocytes before exposure to modeled microgravity reversed the locomotion inhibition. Phorbol myristate acetate (PMA) treatment of normal peripheral blood lymphocytes, after exposure to modeled microgravity, restored lymphocyte locomotion by 84%. Calcium ionophore had no effect on modeled microgravity-exposed lymphocytes. Therefore, the signal pathways involving calcium may not be affected by modeled microgravity. However, direct activation of Protein Kinase C (PKC) with PMA was effective in restoring locomotion in modeled microgravity almost comparable to normal levels in lymphocytes cultured in static T flasks. Thus, events either at the level of PKC or upstream are affected by modeled microgravity. Treatment of lymphocytes with mitomycin C prior to exposure to modeled microgravity, followed by PMA, restored locomotion to the same extent as nonmitomycin C-treated lymphocytes exposed to modeled microgravity (80-85%). Therefore 1) new DNA synthesis is not necessary to restore locomotion and 2) traditional activation and locomotion share common pathways up to PKC. Thereafter the signals diverge. Furthermore PMA added immediately before or after initiation of modeled microgravity prevents the loss of lymphocyte locomotion.

  3. Echistatin prevents posterior capsule opacification in diabetic rabbit model via integrin linked kinase signaling pathway

    PubMed Central

    Lin, Fengbin; Chen, Yingying; Liang, Hao; Tan, Shaojian

    2015-01-01

    Purpose: To investigate the effect of disintegrin echistatin on integrin linked kinase (ILK) and subsequent PI3-K/Akt and ERK1/2 signaling pathways in the posterior capsule opacification (PCO) model of diabetic rabbit. Methods: 56 rabbits were injected alloxan to model diabetic. Then they accepted lens extraction surgery and randomly and intraoperatively injected distilled water (control group; n = 28) or 10.0 mg·L-1 echistatin (echistatin-treated group; n = 28) into the anterior chamber. Each group was subdivided into ten days group (n = 14) and six weeks group (n = 14) respectively. The PCO severity was evaluated with a slit lamp microscope and light microscope for 10 days and 6 weeks postoperatively. The levels of ILK in the posterior capsule were determined by Q-PCR, Western blotting and Immunohistochemistry. Akt and ERK1/2 phosphorylation were analyzed by Western blotting. Results: 10 days and 6 weeks after surgery, the grades of PCO in the echistatin-treated group were lower than the control group. The lens epithelial cells (LECs) in the posterior capsule of echistatin-treated eyes had decreased degrees of proliferation and migration than the control group. And no significant side effects appeared after treated with echistatin. Echistatin could significantly reduce the expression of ILK in terms of both mRNA and protein levels. The phosphorylation levels of Akt and ERK1/2 were decreased in the echistatin-treated group compared with the control group. Conclusions: Echistatin could inhibit postoperative PCO occurrence and development in diabetic rabbit eyes, which may be related to down-regulation the expression of ILK and inhibition the PI3-K/Akt and ERK1/2 pathways. PMID:26823745

  4. Search for the Trilepton Signal of the Minimal Supergravity Model in D0 Run II

    SciTech Connect

    Binder, Meta; /Munich U.

    2005-06-01

    A search for associated chargino neutralino pair production is performed in the trilepton decay channel q{bar q} {yields} {tilde {chi}}{sub 1}{sup {+-}} {tilde {chi}}{sub 2}{sup 0} {yields} {ell}{sup {+-}} {nu} {tilde {chi}}{sub 1}{sup 0} {mu}{sup {+-}} {mu}{sup {-+}} {tilde {chi}}{sub 1}{sup 0}, using data collected with the D0 detector at a center-of-mass energy of 1.96 TeV at the Fermilab Tevatron Collider. The data sample corresponds to an integrated luminosity of {approx}300 pb{sup -1}. A dedicated event selection is applied to all samples including the data sample and the Monte Carlo simulated samples for the Standard Model background and the Supersymmetry signal. Events with two muons plus an additional isolated track, replacing the requirement of a third charged lepton in the event, are analyzed. Additionally, selected events must have a large amount of missing transverse energy due to the neutrino and the two {tilde {chi}}{sub 1}{sup 0}. After all selection cuts are applied, 2 data events are found, with an expected number of background events of 1.75 {+-} 0.34 (stat.) {+-} 0.46 (syst.). No evidence for Supersymmetry is found and limits on the production cross section times leptonic branching fraction are set. When the presented analysis is considered in combination with three other decay channels, no evidence for Supersymmetry is found. Limits on the production cross section times leptonic branching fraction are set. A lower chargino mass limit of 117 GeV at 95% CL is then derived for the mSUGRA model in a region of parameter space with enhanced leptonic branching fractions.

  5. Noise cancelling of MRS signals combining model-based removal of powerline harmonics and multichannel Wiener filtering

    NASA Astrophysics Data System (ADS)

    Larsen, Jakob Juul; Dalgaard, Esben; Auken, Esben

    2014-02-01

    The fidelity of magnetic resonance sounding signals is often severely degraded by noise, primarily electrical interference from powerline harmonics and short electromagnetic discharges. In many circumstances, the noise originates from multiple sources. We show that noise cancelling can be improved if the multiple origins of noise are taken into account. In particular, a method is developed where powerline harmonics are efficiently removed through a model-based approach. Subsequently, standard multichannel Wiener filtering can be used to provide a further noise reduction. The performance of the method depends on the distribution of noise on the particular site of measurement. Simulations on synthetic signals embedded in real noise recordings show that the combined approach can improve the signal-to-noise ratio with an accompanying improvement in retrieval of model parameters.

  6. Caenorhabditis elegans as Model System in Pharmacology and Toxicology: Effects of Flavonoids on Redox-Sensitive Signalling Pathways and Ageing

    PubMed Central

    Koch, Karoline; Havermann, Susannah; Büchter, Christian

    2014-01-01

    Flavonoids are secondary plant compounds that mediate diverse biological activities, for example, by scavenging free radicals and modulating intracellular signalling pathways. It has been shown in various studies that distinct flavonoid compounds enhance stress resistance and even prolong the life span of organisms. In the last years the model organism C. elegans has gained increasing importance in pharmacological and toxicological sciences due to the availability of various genetically modified nematode strains, the simplicity of modulating genes by RNAi, and the relatively short life span. Several studies have been performed demonstrating that secondary plant compounds influence ageing, stress resistance, and distinct signalling pathways in the nematode. Here we present an overview of the modulating effects of different flavonoids on oxidative stress, redox-sensitive signalling pathways, and life span in C. elegans introducing the usability of this model system for pharmacological and toxicological research. PMID:24895670

  7. Scalable Parallel Execution of an Event-based Radio Signal Propagation Model for Cluttered 3D Terrains

    SciTech Connect

    Seal, Sudip K; Perumalla, Kalyan S

    2009-01-01

    Radio signal strength estimation is essential in many applications, including the design of military radio communications and industrial wireless installations. Whil