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Sample records for modeling radioxenon signals

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  3. Evaluation of radioxenon releases in Australia using atmospheric dispersion modelling tools.

    PubMed

    Tinker, Rick; Orr, Blake; Grzechnik, Marcus; Hoffmann, Emmy; Saey, Paul; Solomon, Stephen

    2010-05-01

    The origin of a series of atmospheric radioxenon events detected at the Comprehensive Test Ban Treaty Organisation (CTBTO) International Monitoring System site in Melbourne, Australia, between November 2008 and February 2009 was investigated. Backward tracking analyses indicated that the events were consistent with releases associated with hot commission testing of the Australian Nuclear Science Technology Organisation (ANSTO) radiopharmaceutical production facility in Sydney, Australia. Forward dispersion analyses were used to estimate release magnitudes and transport times. The estimated (133)Xe release magnitude of the largest event (between 0.2 and 34 TBq over a 2 d window), was in close agreement with the stack emission releases estimated by the facility for this time period (between 0.5 and 2 TBq). Modelling of irradiation conditions and theoretical radioxenon emission rates were undertaken and provided further evidence that the Melbourne detections originated from this radiopharmaceutical production facility. These findings do not have public health implications. This is the first comprehensive study of atmospheric radioxenon measurements and releases in Australia.

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

    PubMed

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

    2014-09-01

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

  5. 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.

  6. 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.

  7. Generation of Radioxenon Isotopes

    DTIC Science & Technology

    2008-09-01

    container. Quartz Wool Aluminum Bottle Filter Paper U3O8 Powder Figure 1-A. Schematic of the RXG. The overall length...the detector calibration and was considered the superior approach. Radioxenon from Fissioning of U-235 The RXG is composed of 10.1 grams of U3O8 ...uranium oxide) powder , with the uranium being 95% U-235. A diagram of the RXG is shown in Figure 1-A. The uranium-oxide powder is double sealed in 3

  8. Triple Coincidence Radioxenon Detector

    SciTech Connect

    McIntyre, Justin I.; Aalseth, Craig E.; Bowyer, Ted W.; Hayes, James C.; Heimbigner, Tom R.; Morris, Scott J.; Reeder, Paul L.

    2004-09-22

    The Automated Radioxenon Sampler/Analyzer (ARSA) built by Pacific Northwest National Laboratory (PNNL) is on e of the world’s most sensitive systems for monitoring the four radioxenon isotopes 133Xe, 133mXE, 131mXe and 135Xe. However, due to size, weight and power specifications appropriate to meet treaty-monitoring requirements; the ARSA is unsuitable for rapid deployment using modest transportation means. To transition this technology to a portable unit can be easily and rapidly deployed can be achieved by significant reductions in size, weight and power consumption if concentration were not required. As part of an exploratory effort to reduce both the size of the air sample and the gas processing requirement PNNL has developed an experimental nuclear detector to test and qualify the use of triple coincidence signatures (beta, conversion electron, x-ray) from two of the radioxenon isotopes (135Xe and 133Xe) as well as the more traditional beta-gamma coincidence signatures used by the ARSA system. The additional coincidence requirement allows for reduced passive shielding, and makes it possible for unambiguous detection of 133Xe and 153Xe in the presence of high 222Rn backgrounds. This paper will discuss the experimental setup and the results obtained for a 133Xe sample with and without 222Rn as an interference signature.

  9. 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

  10. Design and Modeling of a Compton-Suppressed Phoswich Detector for Radioxenon Monitoring

    DTIC Science & Technology

    2010-09-01

    modeled using MCNPX Version 2.5.0. The Compton suppression mechanism is integrated into the phoswich design to effectively reduce the Compton continuum...background radiation was modeled using MCNPX Version 2.5.0. The Compton suppression mechanism is integrated into the phoswich design to effectively reduce...be calculated through regions of interest corresponding to the four xenon radioisotopes in the 2D spectrum. An alternative solution to measure

  11. 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.

  12. Comparison of new and existing algorithms for the analysis of 2D radioxenon beta gamma spectra

    DOE PAGES

    Deshmukh, Nikhil; Prinke, Amanda; Miller, Brian; ...

    2017-01-13

    The aim of this study is to compare radioxenon beta–gamma analysis algorithms using simulated spectra with experimentally measured background, where the ground truth of the signal is known. We believe that this is among the largest efforts to date in terms of the number of synthetic spectra generated and number of algorithms compared using identical spectra. We generate an estimate for the minimum detectable counts for each isotope using each algorithm. The paper also points out a conceptual model to put the various algorithms into a continuum. Finally, our results show that existing algorithms can be improved and some newermore » algorithms can be better than the ones currently used.« less

  13. Progress in Advanced Spectral Analysis of Radioxenon

    SciTech Connect

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

    2010-09-21

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

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

    PubMed

    Kalinowski, Martin B; Tuma, Matthias P

    2009-01-01

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

  17. 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.

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

    SciTech Connect

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

    2009-09-24

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

  19. Understanding radioxenon isotopical ratios originating from radiopharmaceutical facilities

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Annewandter, Robert

    2014-05-01

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

  1. Radioxenon detector calibration spike production and delivery systems

    SciTech Connect

    Foxe, Michael P.; Cameron, Ian M.; Cooper, Matthew W.; Haas, Derek A.; Hayes, James C.; Kriss, Aaron A.; Lidey, Lance S.; Mendez, Jennifer M.; Prinke, Amanda M.; Riedmann, Robin A.

    2016-03-01

    Abstract Beta-Gamma coincidence radioxenon detectors must be calibrated for each of the four-radioxenon isotopes (135Xe, 133Xe, 133mXe, and 131mXe). Without a proper calibration, there is potential for the misidentification of the amount of each isotope detected. It is important to accurately determine the amount of each radioxenon isotope, as the ratios can be used to distinguish between an anthropogenic source and a nuclear explosion. We have developed a xenon calibration system (XeCalS) that produces calibration spikes of known activity and pressure for field calibration of detectors. The activity concentrations of these calibration spikes are measured using a beta-gamma coincidence detector and a high purity germanium (HPGe) detector. We will present the results from the development and commissioning of XeCalS, along with the future plans for a portable spike implementation system.

  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. A program to generate simulated radioxenon beta–gamma data for concentration verification and validation and training exercises

    SciTech Connect

    McIntyre, Justin I.; Schrom, Brian T.; Cooper, Matthew W.; Prinke, Amanda M.; Suckow, Thomas J.; Ringbom, Anders; Warren, Glen A.

    2016-03-08

    Abstract Several hundred simulated radioxenon beta-gamma data files were developed to assist in evaluating the performance and results from radioxenon concentration calculation analysis at the International Data Center (IDC) and other National Data Centers (NDC). PNNL developed a Beta-Gamma Simulator (BGSim) that incorporated GEANT-modeled data sets from radioxenon decay chains, as well as functionality to use nuclear detector-acquired data sets to create new beta-gamma spectra with varying amounts of background, 133Xe, 131mXe, 133mXe, 135Xe, and 222Rn and its decay products. The program has been implemented on a web-based applications platform and allows the user to create very specific data sets that incorporate most of the operational parameters for the current beta-gamma systems deployed in the International Monitoring System (IMS) and the On-site Inspection (OSI) equipment. After an initial beta-gamma simulations program was developed, additional uses began to be identified for the program output: training sets of two-dimensional spectra for data analysts at the IDC and other NDC, spectra for exercises such as the Integrated Field Exercise 2014 (IFE14) held in Jordan at the Dead Sea, and testing new analysis methods and algorithms

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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).

  9. 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

  10. 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.

  11. Monitoring of reported sudden emission rate changes of major radioxenon emitters in the northern and southern hemispheres in 2008 to assess their contribution to the respective radioxenon backgrounds

    NASA Astrophysics Data System (ADS)

    Saey, P. R. J.; Auer, M.; Becker, A.; Colmanet, S.; Hoffmann, E.; Nikkinen, M.; Schlosser, C.; Sonck, M.

    2009-04-01

    Atmospheric radioxenon monitoring is a key component of the verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Radiopharmaceutical production facilities (RPF) have recently been identified of emitting the major part of the environmental radioxenon measured at globally distributed monitoring sites deployed to strengthen the radionuclide part of the CTBT verification regime. Efforts to raise a global radioxenon emission inventory revealed that the global total emission from RPF's is 2-3 orders of magnitude higher than the respective emissions related to maintenance of all nuclear power plants (NPP). Given that situation we have seen in 2008 two peculiar hemisphere-specific situations: 1) In the northern hemisphere, a joint shutdown of the global largest four radiopharmaceutical facilities revealed the contribution of the normally 'masked' NPP related emissions. Due to an incident, the Molybdenum production at the "Institut des Radioéléments" (IRE) in Fleurus, Belgium, was shut down between Monday 25 August and 2 December 2008. IRE is the third largest global producer of medical isotopes. In the same period, but for different reasons, the other three worldwide largest producers (CRL in Canada, HFR in The Netherlands and NTP in South Africa) also had scheduled and unscheduled shutdowns. The activity concentrations of 133Xe measured at the Schauinsland Mountain station near Freiburg in Germany (situated 380 km SW of Fleurus) which have a mean of 4.8 mBq/m3 for the period February 2004 - August 2008, went down to 0.87 mBq/m3 for the period September - November 2008. 2) In the southern hemisphere, after a long break, the only radiopharmaceutical facility in Australia started up test production in late November 2008. In the period before the start-up, the background of radioxenon in Australia (Melbourne and Darwin) was below measurable quantities. During six test runs of the renewed RPF at ANSTO in Lucas Heights, up to 6 mBq/m3 of 133Xe were measured in

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

    SciTech Connect

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

    1998-07-01

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

  13. Operations of the Automated Radioxenon Sampler/Analyzer - ARSA

    SciTech Connect

    Hayes, James C.; Abel, Keith H.; Bowyer, Ted W.; Heimbigner, Tom R.; Panisko, Mark E.; Reeder, Paul L.; McIntyre, Justin I.; Thompson, Robert C.; Todd, Lindsay C.; Warner, Ray A.

    1999-09-01

    The Automated Radioxenon Sampler/ Analyzer (ARSA), designed and built by Pacific Northwest National Laboratory (PNNL), for the Department of Energy, has exceeded measurement requirements for noble gas measurement systems established by the Comprehensive Nuclear-Test-Ban Treaty. Two units, one at PNNL and a second, sent to DME Corp. of Florida, were built and extensively tested. Both systems have successfully demonstrated stable xenon yields greater than 1.5 cm3 for an eight-hour collection period, corresponding to minimum detectable concentrations for 133Xe on the order of 0.1 mBq/m3 three times per day. High stable xenon yields are critical in obtaining these low minimum detectable concentrations. A history of testing and results that led to the high xenon yields of the ARSA system is presented. A compilation of field tests, laboratory tests and baseline tests that led to cost reduction, power savings and size reduction of the ARSA are also discussed. Lastly, the type of data generated from the ARSA of interest to data center personnel are discussed.

  14. 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.

  15. Calculation of Minimum-Detectable-Concentration Levels of Radioxenon Isotopes Using the PNNL ARSA System

    SciTech Connect

    McIntyre, Justin I.; Bowyer, Ted W.; Reeder, Paul L.

    2006-03-11

    Measurement of xenon fission product isotopes is a key element in the global network being established to monitor the Comprehensive Nuclear-Test-Ban Treaty. The automated Radio-xenon Analyzer/Sampler (ARSA), built by Pacific Northwest National Laboratory, can detect 131mXe, 133mXe, 133Xe, and 135Xe via a beta-gamma counting system. Due to the variable background and sources of these four radio-xenon isotopes, it is important to have as sensitive a detection system as possible and to quantify the Minimum-Detectable-Concentrations (MDC) that such a system will be able to detect to preclude false negative and false positive results. From data obtained from IAR in Germany MDC values for 133Xe were well below the 1 mBq/SCMA as required by the PTS for the Comprehensive Test BAn Treaty [WGB TL-11,1999].

  16. 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.

  17. 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.

  18. Mathematical model for classification of EEG signals

    NASA Astrophysics Data System (ADS)

    Ortiz, Victor H.; Tapia, Juan J.

    2015-09-01

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

  19. Reconstructing Boolean Models of Signaling

    PubMed Central

    Karp, Richard M.

    2013-01-01

    Abstract Since the first emergence of protein–protein interaction networks more than a decade ago, they have been viewed as static scaffolds of the signaling–regulatory events taking place in cells, and their analysis has been mainly confined to topological aspects. Recently, functional models of these networks have been suggested, ranging from Boolean to constraint-based methods. However, learning such models from large-scale data remains a formidable task, and most modeling approaches rely on extensive human curation. Here we provide a generic approach to learning Boolean models automatically from data. We apply our approach to growth and inflammatory signaling systems in humans and show how the learning phase can improve the fit of the model to experimental data, remove spurious interactions, and lead to better understanding of the system at hand. PMID:23286509

  20. Existing Data Format for Two-Parameter Beta-Gamma Histograms for Radioxenon

    SciTech Connect

    TW Bowyer; TR Heimbigner; JI McIntyre; AD McKinnon; PL Reeder; E Wittinger

    1999-03-23

    There is a need to establish a commonly acceptable format for storing beta-gated coincidence data for stations in the International Monitoring System (IMS) for the Comprehensive Nuclear-Test-Ban Treaty (CTBT). The current aerosol RMS type data format is not applicable for radioxenon in that the current format contains implicit assumptions specific to conventional gamma-ray spectrometry. Some assumptions in the current RMS format are not acceptable for the beta-gated spectra expected from the U.S. Department of Energy PNNL Automated Radioxenon Sampler-Analyzer (ARSA) and other similar systems under use or development from various countries. The RMS data format is not generally applicable for radioxenon measurements in the CTBT for one or more of the following main reasons: 1) The RMS format does not currently support 2-dimensional data. That is, the RMS data format is setup for a simple l-dimensional gamma-ray energy histogram. Current data available from the ARSA system and planned for other radioxenon monitors includes spectral information from gamma-rays and betas/conversion electrons. It is worth noting that the beta/conversion electron energy information will be used to separate the contributions from the different radioxenons. 2) The RMS data format assumes that the conversion between counts and activity can be calculated based (in part) on a simple calibration curve (detector efficiency curve) that depends only on energy of the gamma-ray. In the case of beta-gated gamma-ray spectra and for 2-dimensional spectra, there are generally two detector calibration curves that must be convoluted, the lower energy cutoff for the betas must be considered, and the energy acceptance window must be taken into account to convert counts into activity. . 3) The RMS format has header information that contains aerosol-specific information that allows the activity (Bq) calculated to be converted into a concentration (Bq/SCM). This calculation is performed by dividing the

  1. 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.

  2. Diabetes: Models, Signals, and Control.

    PubMed

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

    2009-01-01

    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.

  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. 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…

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

    PubMed

    Janes, Kevin A; VanHook, Annalisa M

    2016-06-07

    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.

  6. Predictive mathematical models of cancer signalling pathways.

    PubMed

    Bachmann, J; Raue, A; Schilling, M; Becker, V; Timmer, J; Klingmüller, U

    2012-02-01

    Complex intracellular signalling networks integrate extracellular signals and convert them into cellular responses. In cancer cells, the tightly regulated and fine-tuned dynamics of information processing in signalling networks is altered, leading to uncontrolled cell proliferation, survival and migration. Systems biology combines mathematical modelling with comprehensive, quantitative, time-resolved data and is most advanced in addressing dynamic properties of intracellular signalling networks. Here, we introduce different modelling approaches and their application to medical systems biology, focusing on the identifiability of parameters in ordinary differential equation models and their importance in network modelling to predict cellular decisions. Two related examples are given, which include processing of ligand-encoded information and dual feedback regulation in erythropoietin (Epo) receptor signalling. Finally, we review the current understanding of how systems biology could foster the development of new treatment strategies in the context of lung cancer and anaemia.

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

    PubMed

    Culver, R Lee; Camin, H John

    2008-12-01

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

  8. State-of-Health Software for the Automated Radioxenon Sampler/Analyzer

    SciTech Connect

    Heimbigner, Tom R.; Bowyer, Ted W.; Hayes, James C.; Hubbard, Charles W.; McIntyre, Justin I.; Panisko, Mark E.; Ripplinger, Mike D.; Suarez, Reynold

    2004-09-22

    The Automated Radioxenon Analyzer/Sampler (ARSA) is a complex gas-collection and analysis system that requires constant online monitoring of system operations and overall system health. The software-control system records and monitors and over 100 different system sensors (temperature, pressures, voltages, etc.) A real-time record of the system state allows the system to monitor for unsafe conditions and maintain the system in a safe state regardless of external or internal failures (vacuum pump, valve or power failures, and runaway temperatures are a few examples). Another function of real-time monitoring allows the user to troubleshoot the system when a problem arises, should a minor sensor or a major system failure occur. This paper will outline the general scheme used by the state-of-health program to monitor and assess the system, the graphical user interface program and the alert message system, and give specific examples of proper system performance and some system failures.

  9. Large Signal Evaluation of Nonlinear HBT Model

    NASA Astrophysics Data System (ADS)

    Angelov, Iltcho; Inoue, Akira; Watanabe, Shinsuke

    The performance of recently developed Large Signal (LS) HBT model was evaluated with extensive LS measurements like Power spectrum, Load pull and Inter-modulation investigations. Proposed model has adopted temperature dependent leakage resistance and a simplified capacitance models. The model was implemented in ADS as SDD. Important feature of the model is that the main model parameters are taken directly from measurements in rather simple and understandable way. Results show good accuracy despite the simplicity of the model. To our knowledge the HBT model is one of a few HBT models which can handle high current & Power HBT devices, with significantly less model parameters with good accuracy.

  10. Modeling of spatially-restricted intracellular signaling.

    PubMed

    Neves, Susana R

    2012-01-01

    Understanding the signaling capabilities of a cell presents a major challenge, not only due to the number of molecules involved, but also because of the complex network connectivity of intracellular signaling. Recently, the proliferation of quantitative imaging techniques has led to the discovery of the vast spatial organization of intracellular signaling. Computational modeling has emerged as a powerful tool for understanding how inhomogeneous signaling originates and is maintained. This article covers the current imaging techniques used to obtain quantitative spatial data and the mathematical approaches used to model spatial cell biology. Modeling-derived hypotheses have been experimentally tested and the integration of modeling and imaging approaches has led to non-intuitive mechanistic insights.

  11. 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.

  12. Pedestrian crash estimation models for signalized intersections.

    PubMed

    Pulugurtha, Srinivas S; Sambhara, Venkata R

    2011-01-01

    The focus of this paper is twofold: (1) to examine the non-linear relationship between pedestrian crashes and predictor variables such as demographic characteristics (population and household units), socio-economic characteristics (mean income and total employment), land use characteristics, road network characteristics (the number of lanes, speed limit, presence of median, and pedestrian and vehicular volume) and accessibility to public transit systems, and (2) to develop generalized linear pedestrian crash estimation models (based on negative binomial distribution to accommodate for over-dispersion of data) by the level of pedestrian activity and spatial proximity to extract site specific data at signalized intersections. Data for 176 randomly selected signalized intersections in the City of Charlotte, North Carolina were used to examine the non-linear relationships and develop pedestrian crash estimation models. The average number of pedestrian crashes per year within 200 feet of each intersection was considered as the dependent variable whereas the demographic characteristics, socio-economic characteristics, land use characteristics, road network characteristics and the number of transit stops were considered as the predictor variables. The Pearson correlation coefficient was used to eliminate predictor variables that were correlated to each other. Models were then developed separately for all signalized intersections, high pedestrian activity signalized intersections and low pedestrian activity signalized intersections. The use of 0.25mile, 0.5mile and 1mile buffer widths to extract data and develop models was also evaluated.

  13. 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.

  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.

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

    PubMed

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

    2013-01-01

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

  16. 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

  17. Model for neural signaling leap statistics

    NASA Astrophysics Data System (ADS)

    Chevrollier, Martine; Oriá, Marcos

    2011-03-01

    We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T = 37.5°C, awaken regime) and Lévy statistics (T = 35.5°C, sleeping period), characterized by rare events of long range connections.

  18. (135)Xe measurements with a two-element CZT-based radioxenon detector for nuclear explosion monitoring.

    PubMed

    Ranjbar, Lily; Farsoni, Abi T; Becker, Eric M

    2017-04-01

    Measurement of elevated concentrations of xenon radioisotopes ((131m)Xe, (133m)Xe, (133)Xe and (135)Xe) in the atmosphere has been shown to be a very powerful method for verifying whether or not a detected explosion is nuclear in nature. These isotopes are among the few with enough mobility and with half-lives long enough to make their detection at long distances realistic. Existing radioxenon detection systems used by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) suffer from problems such as complexity, need for high maintenance and memory effect. To study the response of CdZnTe (CZT) detectors to xenon radioisotopes and investigate whether it is capable of mitigating the aforementioned issues with the current radioxenon detection systems, a prototype detector utilizing two coplanar CZT detectors was built and tested at Oregon State University. The detection system measures xenon radioisotopes through beta-gamma coincidence technique by detecting coincidence events between the two detectors. In this paper, we introduce the detector design and report our measurement results with radioactive lab sources and (135)Xe produced in the OSU TRIGA reactor. Minimum Detectable Concentration (MDC) for (135)Xe was calculated to be 1.47 ± 0.05 mBq/m(3).

  19. 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.

  20. 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.

  1. Modeling of surface myoelectric signals--Part II: Model-based signal interpretation.

    PubMed

    Merletti, R; Roy, S H; Kupa, E; Roatta, S; Granata, A

    1999-07-01

    Experimental electromyogram (EMG) data from the human biceps brachii were simulated using the model described in [10] of this work. A multichannel linear electrode array, spanning the length of the biceps, was used to detect monopolar and bipolar signals, from which double differential signals were computed, during either voluntary or electrically elicited isometric contractions. For relatively low-level voluntary contractions (10%-30% of maximum force) individual firings of three to four-different motor units were identified and their waveforms were closely approximated by the model. Motor unit parameters such as depth, size, fiber orientation and length, location of innervation and tendonous zones, propagation velocity, and source width were estimated using the model. Two applications of the model are described. The first analyzes the effects of electrode rotation with respect to the muscle fiber direction and shows the possibility of conduction velocity (CV) over- and under-estimation. The second focuses on the myoelectric manifestations of fatigue during a sustained electrically elicited contraction and the interrelationship between muscle fiber CV, spectral and amplitude variables, and the length of the depolarization zone. It is concluded that a) surface EMG detection using an electrode array, when combined with a model of signal propagation, provides a useful method for understanding the physiological and anatomical determinants of EMG waveform characteristics and b) the model provides a way for the interpretation of fatigue plots.

  2. 16. FRONT VIEW, MODEL 15 VANE RELAY, NEW HAVEN SIGNAL ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    16. FRONT VIEW, MODEL 15 VANE RELAY, NEW HAVEN SIGNAL SHOP - New York, New Haven & Hartford Railroad, Automatic Signalization System, Long Island Sound shoreline between Stamford & New Haven, Stamford, Fairfield County, CT

  3. 18. SIDE VIEW, MODEL 15 VANE RELAY, NEW HAVEN SIGNAL ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    18. SIDE VIEW, MODEL 15 VANE RELAY, NEW HAVEN SIGNAL SHOP - New York, New Haven & Hartford Railroad, Automatic Signalization System, Long Island Sound shoreline between Stamford & New Haven, Stamford, Fairfield County, CT

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

    SciTech Connect

    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

    Abstract 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 (Bowyer et al., 2013). Fission-based production of 99Mo for medical purposes also releases radioxenon isotopes to the atmosphere (Saey, 2009). One of the ways to mitigate the effect of emissions from medical isotope production is the use of stack monitoring data, if it were available, so that the effect of radioactive xenon emissions could be subtracted from the effect from a presumed nuclear explosion, when detected at an IMS station location. To date, no studies have addressed the impacts the time resolution or data accuracy of stack monitoring data have on predicted concentrations at an IMS station location. Recently, participants from seven nations used atmospheric transport modeling to predict the time-history of 133Xe concentration measurements at an IMS 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 high composite statistical model comparison rank or a small mean square error with the measured values). The results suggest release data on a 15 min time spacing is best. The model comparison rank and ensemble analysis suggests that combining multiple models may provide more accurate predicted concentrations than any single model. Further research is needed to identify optimal methods for selecting ensemble members and those methods may depend on the specific transport problem. None of the submissions based only

  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. Ontology based standardization of petri net modeling for signaling pathways.

    PubMed

    Takai-Igarashi, Takako

    2011-01-01

    Taking account of the great availability of Petri nets in modeling and analyzing large complicated signaling networks, semantics of Petri nets is in need of systematization for the purpose of consistency and reusability of the models. This paper reports on standardization of units of Petri nets on the basis of an ontology that gives an intrinsic definition to the process of signaling in signaling pathways.

  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".

  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. Model reference adaptive control with an augmented error signal

    NASA Technical Reports Server (NTRS)

    Monopoli, R. V.

    1974-01-01

    It is shown how globally stable model reference adaptive control systems may be designed when one has access to only the plant's input and output signals. Controllers for single input-single output, nonlinear, nonautonomous plants are developed based on Lyapunov's direct method and the Meyer-Kalman-Yacubovich lemma. Derivatives of the plant output are not required, but are replaced by filtered derivative signals. An augmented error signal replaces the error normally used, which is defined as the difference between the model and plant outputs. However, global stability is assured in the sense that the normally used error signal approaches zero asymptotically.

  10. Angiogenic Signaling in Living Breast Tumor Models

    DTIC Science & Technology

    2010-06-01

    angle will fall between +/−6 degrees. We then counted the number of photons which escape from the air-tissue surface in the backward direction and...the case of the Fluoview 300) whose radius is far from the initial sharp curvature due to the Gaussian distribution of direct back-propagating SHG...SHG emission from collagen. 15. SUBJECT TERMS Angiogenesis, microscopy, signaling, VEGF, permeability 16. SECURITY CLASSIFICATION OF : 17

  11. Angiogenic Signaling in Living Breast Tumor Models

    DTIC Science & Technology

    2007-06-01

    network of vessels with labeled ECs is visible in the lower right. Image is 600 microns across. Figure 11. Dose-response curve of fura -loaded BAECs to...least one group engaged in cationic blockade studies that levels as high as 2 mM are required for successful block of plasmalemmal calcium channels9...Task 2 , in its entirety, is: Task 2 . To determine the role of diacylglycerol (DAG) in translation of VEGFR2 activation to TEC calcium signals

  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. Pathway logic modeling of protein functional domains in signal transduction.

    PubMed

    Talcott, C; Eker, S; Knapp, M; Lincoln, P; Laderoute, K

    2004-01-01

    Protein functional domains (PFDs) are consensus sequences within signaling molecules that recognize and assemble other signaling components into complexes. Here we describe the application of an approach called Pathway Logic to the symbolic modeling signal transduction networks at the level of PFDs. These models are developed using Maude, a symbolic language founded on rewriting logic. Models can be queried (analyzed) using the execution, search and model-checking tools of Maude. We show how signal transduction processes can be modeled using Maude at very different levels of abstraction involving either an overall state of a protein or its PFDs and their interactions. The key insight for the latter is our algebraic representation of binding interactions as a graph.

  14. Colored Petri net modeling and simulation of signal transduction pathways.

    PubMed

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

    2006-03-01

    Presented herein is a methodology for quantitatively analyzing the complex signaling network by resorting to colored Petri nets (CPN). The mathematical as well as Petri net models for two basic reaction types were established, followed by the extension to a large signal transduction system stimulated by epidermal growth factor (EGF) in an application study. The CPN models based on the Petri net representation and the conservation and kinetic equations were used to examine the dynamic behavior of the EGF signaling pathway. The usefulness of Petri nets is demonstrated for the quantitative analysis of the signal transduction pathway. Moreover, the trade-offs between modeling capability and simulation efficiency of this pathway are explored, suggesting that the Petri net model can be invaluable in the initial stage of building a dynamic model.

  15. Discrete model reference adaptive control with an augmented error signal

    NASA Technical Reports Server (NTRS)

    Ionescu, T.; Monopoli, R.

    1975-01-01

    A method for designing discrete model reference adaptive control systems when one has access to only the plant's input and output signals is given. Controllers for single-input, single-output, nonlinear, nonautonomous plants are developed via Liapunov's second method. Anticipative values of the plant output are not required, but are replaced by signals easily obtained from a low-pass filter operating on the plant's output. The augmented error signal method is employed, ensuring finally that the normally used error signal also approaches zero asymptotically.

  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. 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

  18. 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).

  19. Multiplexing signals in reinforcement learning with internal models and dopamine.

    PubMed

    Nakahara, Hiroyuki

    2014-04-01

    A fundamental challenge for computational and cognitive neuroscience is to understand how reward-based learning and decision-making are made and how accrued knowledge and internal models of the environment are incorporated. Remarkable progress has been made in the field, guided by the midbrain dopamine reward prediction error hypothesis and the underlying reinforcement learning framework, which does not involve internal models ('model-free'). Recent studies, however, have begun not only to address more complex decision-making processes that are integrated with model-free decision-making, but also to include internal models about environmental reward structures and the minds of other agents, including model-based reinforcement learning and using generalized prediction errors. Even dopamine, a classic model-free signal, may work as multiplexed signals using model-based information and contribute to representational learning of reward structure.

  20. Echo signal modeling of imaging LADAR target simulator

    NASA Astrophysics Data System (ADS)

    Xu, Rui; Shi, Rui; Wang, Xin; Li, Zhuo

    2014-11-01

    LADAR guidance technology is one of the most promising precision guidance technologies. In the aim of simulating the return waveform of the target, a 3D geometrical model of a target is built and mathematical model of target echo signal for imaging LADAR target simulator is established by using the coordinate transformation, radar equation and ranging equation. First, the 3D geometrical data of the object model is obtained by 3D geometrical modeling. Then, target coordinate system and viewpoint coordinate system are created respectively. 3D geometrical model is built in the target coordinate system. The 3D geometrical model is transformed to the viewpoint coordinate system based on the derived relationship between the two coordinate systems. Furthermore, the range information of the target could be obtained under viewpoint coordinate system. Thus, the data of the target echo signal can be obtained by using radar equation and ranging equation. Finally, the echo signal can be exported through corresponding data interface. In order to validate the method proposed in this paper, the echo signal generated by a typical target is computed and compared with the theory solutions. The signals can be applied to drive target simulator to generate a physical target LADAR image.

  1. Multi-photon signals from composite models at LHC

    NASA Astrophysics Data System (ADS)

    Freitas, A.; Schwaller, P.

    2011-01-01

    We analyze the collider signals of composite scalars that emerge in certain little Higgs models and models of vectorlike confinement. Similar to the decay of the pion into photon pairs, these scalars mainly decay through anomaly-induced interactions into electroweak gauge bosons, leading to a distinct signal with three or more photons in the final state. We study the standard model backgrounds for these signals, and find that the LHC can discover these models over a large range of parameter space with 30 fb-1 at 14 TeV. An early discovery at the current 7 TeV run is possible in some regions of parameter space. We also discuss possibilities to measure the spin of the particles in the γγ and Zγ decay channels.

  2. 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...

  3. 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.

  4. Frogs model man: In vivo thyroid hormone signaling during development.

    PubMed

    Sachs, Laurent M; Buchholz, Daniel R

    2017-01-01

    Thyroid hormone (TH) signaling comprises TH transport across cell membranes, metabolism by deiodinases, and molecular mechanisms of gene regulation. Proper TH signaling is essential for normal perinatal development, most notably for neurogenesis and fetal growth. Knowledge of perinatal TH endocrinology needs improvement to provide better treatments for premature infants and endocrine diseases during gestation and to counteract effects of endocrine disrupting chemicals. Studies in amphibians have provided major insights to understand in vivo mechanisms of TH signaling. The frog model boasts dramatic TH-dependent changes directly observable in free-living tadpoles with precise and easy experimental control of the TH response at developmental stages comparable to fetal stages in mammals. The hormones, their receptors, molecular mechanisms, and developmental roles of TH signaling are conserved to a high degree in humans and amphibians, such that with respect to developmental TH signaling "frogs are just little people that hop." The frog model is exceptionally illustrative of fundamental molecular mechanisms of in vivo TH action involving TH receptors, transcriptional cofactors, and chromatin remodeling. This review highlights the current need, recent successes, and future prospects using amphibians as a model to elucidate molecular mechanisms and functional roles of TH signaling during post-embryonic development.

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

    PubMed

    Oliva, Marina; Farcot, Etienne; Vernoux, Teva

    2013-02-01

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

  6. PREDICTIVE MODELING OF ACOUSTIC SIGNALS FROM THERMOACOUSTIC POWER SENSORS (TAPS)

    SciTech Connect

    Dumm, Christopher M.; Vipperman, Jeffrey S.

    2016-06-30

    Thermoacoustic Power Sensor (TAPS) technology offers the potential for self-powered, wireless measurement of nuclear reactor core operating conditions. TAPS are based on thermoacoustic engines, which harness thermal energy from fission reactions to generate acoustic waves by virtue of gas motion through a porous stack of thermally nonconductive material. TAPS can be placed in the core, where they generate acoustic waves whose frequency and amplitude are proportional to the local temperature and radiation flux, respectively. TAPS acoustic signals are not measured directly at the TAPS; rather, they propagate wirelessly from an individual TAPS through the reactor, and ultimately to a low-power receiver network on the vessel’s exterior. In order to rely on TAPS as primary instrumentation, reactor-specific models which account for geometric/acoustic complexities in the signal propagation environment must be used to predict the amplitude and frequency of TAPS signals at receiver locations. The reactor state may then be derived by comparing receiver signals to the reference levels established by predictive modeling. In this paper, we develop and experimentally benchmark a methodology for predictive modeling of the signals generated by a TAPS system, with the intent of subsequently extending these efforts to modeling of TAPS in a liquid sodium environmen

  7. SEM++: A particle model of cellular growth, signaling and migration

    NASA Astrophysics Data System (ADS)

    Milde, Florian; Tauriello, Gerardo; Haberkern, Hannah; Koumoutsakos, Petros

    2014-06-01

    We present a discrete particle method to model biological processes from the sub-cellular to the inter-cellular level. Particles interact through a parametrized force field to model cell mechanical properties, cytoskeleton remodeling, growth and proliferation as well as signaling between cells. We discuss the guiding design principles for the selection of the force field and the validation of the particle model using experimental data. The proposed method is integrated into a multiscale particle framework for the simulation of biological systems.

  8. Detailed signal model of coherent wind measurement lidar

    NASA Astrophysics Data System (ADS)

    Ma, Yuechao; Li, Sining; Lu, Wei

    2016-11-01

    Lidar is short for light detection and ranging, which is a tool to help measuring some useful information of atmosphere. In the recent years, more and more attention was paid to the research of wind measurement by lidar. Because the accurate wind information can be used not only in weather report, but also the safety guarantee of the airplanes. In this paper, a more detailed signal model of wind measurement lidar is proposed. It includes the laser transmitting part which describes the broadening of the spectral, the laser attenuation in the atmosphere, the backscattering signal and the detected signal. A Voigt profile is used to describe the broadening of the transmitting laser spectral, which is the most common situation that is the convolution of different broadening line shapes. The laser attenuation includes scattering and absorption. We use a Rayleigh scattering model and partially-Correlated quadratic-Velocity-Dependent Hard-Collision (pCqSDHC) model to describe the molecule scattering and absorption. When calculate the particles scattering and absorption, the Gaussian particles model is used to describe the shape of particles. Because of the Doppler Effect occurred between the laser and atmosphere, the wind velocity can be calculated by the backscattering signal. Then, a two parameter Weibull distribution is used to describe the wind filed, so that we can use it to do the future work. After all the description, the signal model of coherent wind measurement lidar is decided. And some of the simulation is given by MATLAB. This signal model can describe the system more accurate and more detailed, so that the following work will be easier and more efficient.

  9. Model reference adaptive control using only input and output signals

    NASA Technical Reports Server (NTRS)

    Monopoli, R. V.

    1973-01-01

    It is shown how globally stable model reference adaptive control systems may be designed using only the plant's input and output signals. Controllers for single input-single output, nonlinear, nonautonomous plants are developed based on Liapunov's direct method and the Meyer-Kalman-Yacubovich lemma. Filtered derivatives of the plant output replace pure derivatives which are normally required in these systems. An augmented error signal replaces the error previously used which is the difference between the model and plant outputs. However, global stability is assured in the sense that this difference approaches zero asymptotically.

  10. 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

  11. Predictive Modeling of Signaling Crosstalk during C. elegans Vulval Development

    PubMed Central

    Fisher, Jasmin; Piterman, Nir; Hajnal, Alex; Henzinger, Thomas A

    2007-01-01

    Caenorhabditis elegans vulval development provides an important paradigm for studying the process of cell fate determination and pattern formation during animal development. Although many genes controlling vulval cell fate specification have been identified, how they orchestrate themselves to generate a robust and invariant pattern of cell fates is not yet completely understood. Here, we have developed a dynamic computational model incorporating the current mechanistic understanding of gene interactions during this patterning process. A key feature of our model is the inclusion of multiple modes of crosstalk between the epidermal growth factor receptor (EGFR) and LIN-12/Notch signaling pathways, which together determine the fates of the six vulval precursor cells (VPCs). Computational analysis, using the model-checking technique, provides new biological insights into the regulatory network governing VPC fate specification and predicts novel negative feedback loops. In addition, our analysis shows that most mutations affecting vulval development lead to stable fate patterns in spite of variations in synchronicity between VPCs. Computational searches for the basis of this robustness show that a sequential activation of the EGFR-mediated inductive signaling and LIN-12 / Notch-mediated lateral signaling pathways is key to achieve a stable cell fate pattern. We demonstrate experimentally a time-delay between the activation of the inductive and lateral signaling pathways in wild-type animals and the loss of sequential signaling in mutants showing unstable fate patterns; thus, validating two key predictions provided by our modeling work. The insights gained by our modeling study further substantiate the usefulness of executing and analyzing mechanistic models to investigate complex biological behaviors. PMID:17511512

  12. 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.

  13. Signalling network construction for modelling plant defence response.

    PubMed

    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

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

    NASA Astrophysics Data System (ADS)

    Hu, Cheng

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

  15. Switched linear model predictive controllers for periodic exogenous signals

    NASA Astrophysics Data System (ADS)

    Wang, Liuping; Gawthrop, Peter; Owens, David. H.; Rogers, Eric

    2010-04-01

    This article develops switched linear controllers for periodic exogenous signals using the framework of a continuous-time model predictive control. In this framework, the control signal is generated by an algorithm that uses receding horizon control principle with an on-line optimisation scheme that permits inclusion of operational constraints. Unlike traditional repetitive controllers, applying this method in the form of switched linear controllers ensures bumpless transfer from one controller to another. Simulation studies are included to demonstrate the efficacy of the design with or without hard constraints.

  16. 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

  17. Vibration signal models for fault diagnosis of planetary gearboxes

    NASA Astrophysics Data System (ADS)

    Feng, Zhipeng; Zuo, Ming J.

    2012-10-01

    A thorough understanding of the spectral structure of planetary gear system vibration signals is helpful to fault diagnosis of planetary gearboxes. Considering both the amplitude modulation and the frequency modulation effects due to gear damage and periodically time variant working condition, as well as the effect of vibration transfer path, signal models of gear damage for fault diagnosis of planetary gearboxes are given and the spectral characteristics are summarized in closed form. Meanwhile, explicit equations for calculating the characteristic frequency of local and distributed gear fault are deduced. The theoretical derivations are validated using both experimental and industrial signals. According to the theoretical basis derived, manually created local gear damage of different levels and naturally developed gear damage in a planetary gearbox can be detected and located.

  18. 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

  19. 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.

  20. A Signal Detection Model of Compound Decision Tasks

    DTIC Science & Technology

    2006-12-01

    A signal detection model of compound decision tasks Matthew Duncan Defence R& D Canada Technical Report DRDC Toronto TR 2006-256 December 2006...tasks Matthew Duncan Defence R& D Canada – Toronto Technical Report DRDC Toronto TR 2006-256 December 2006 Author Original approved by...la prise de décision, il faut une méthode formelle pour distinguer (clarifier) les effets des divers facteurs, et pour simplifier l’évaluation des

  1. 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

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

    PubMed Central

    Medina, Leonel E.; Grill, Warren M.

    2014-01-01

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

    Gardner, Trevor

    2003-03-01

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

  5. Spatio-temporal modeling of signaling protein recruitment to EGFR

    PubMed Central

    2010-01-01

    Background A stochastic simulator was implemented to study EGFR signal initiation in 3D with single molecule detail. The model considers previously unexplored contributions to receptor-adaptor coupling, such as receptor clustering and diffusive properties of both receptors and binding partners. The agent-based and rule-based approach permits consideration of combinatorial complexity, a problem associated with multiple phosphorylation sites and the potential for simultaneous binding of adaptors. Results The model was used to simulate recruitment of four different signaling molecules (Grb2, PLCγ1, Stat5, Shc) to the phosphorylated EGFR tail, with rules based on coarse-grained prediction of spatial constraints. Parameters were derived in part from quantitative immunoblotting, immunoprecipitation and electron microscopy data. Results demonstrate that receptor clustering increases the efficiency of individual adaptor retainment on activated EGFR, an effect that is overridden if crowding is imposed by receptor overexpression. Simultaneous docking of multiple proteins is highly dependent on receptor-adaptor stability and independent of clustering. Conclusions Overall, we propose that receptor density, reaction kinetics and membrane spatial organization all contribute to signaling efficiency and influence the carcinogenesis process. PMID:20459599

  6. 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

  7. 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.

  8. Computational modeling of apoptotic signaling pathways induced by cisplatin

    PubMed Central

    2012-01-01

    Background Apoptosis is an essential property of all higher organisms that involves extremely complex signaling pathways. Mathematical modeling provides a rigorous integrative approach for analyzing and understanding such intricate biological systems. Results Here, we constructed a large-scale, literature-based model of apoptosis pathways responding to an external stimulus, cisplatin. Our model includes the key elements of three apoptotic pathways induced by cisplatin: death receptor-mediated, mitochondrial, and endoplasmic reticulum-stress pathways. We showed that cisplatin-induced apoptosis had dose- and time-dependent characteristics, and the level of apoptosis was saturated at higher concentrations of cisplatin. Simulated results demonstrated that the effect of the mitochondrial pathway on apoptosis was the strongest of the three pathways. The cross-talk effect among pathways accounted for approximately 25% of the total apoptosis level. Conclusions Using this model, we revealed a novel mechanism by which cisplatin induces dose-dependent cell death. Our finding that the level of apoptosis was affected by not only cisplatin concentration, but also by cross talk among pathways provides in silico evidence for a functional impact of system-level characteristics of signaling pathways on apoptosis. PMID:22967854

  9. Novel Higgs decay signals in R-parity violating models

    SciTech Connect

    Sierra, D. Aristizabal; Porod, W.; Restrepo, D.; Yaguna, Carlos E.

    2008-07-01

    In supersymmetric models the lightest Higgs boson may decay with a sizable branching ratio into a pair of light neutralinos. We analyze such decays within the context of the minimal supersymmetric standard model with R-parity violation, where the neutralino itself is unstable and decays into standard model fermions. We show that the R-parity violating couplings induce novel Higgs decay signals that might facilitate the discovery of the Higgs boson at colliders. At the LHC, the Higgs may be observed, for instance, through its decay--via two neutralinos--into final states containing missing energy and isolated charged leptons such as l{sup {+-}}l{sup {+-}}, l{sup {+-}}l{sup {+-}}, 3l, and 4l. Another promising possibility is the search for the displaced vertices associated with the neutralino decay. We also point out that Higgs searches at the LHC might additionally provide the first evidence of R-parity violation.

  10. Bayesian analysis. II. Signal detection and model selection

    NASA Astrophysics Data System (ADS)

    Bretthorst, G. Larry

    In the preceding. paper, Bayesian analysis was applied to the parameter estimation problem, given quadrature NMR data. Here Bayesian analysis is extended to the problem of selecting the model which is most probable in view of the data and all the prior information. In addition to the analytic calculation, two examples are given. The first example demonstrates how to use Bayesian probability theory to detect small signals in noise. The second example uses Bayesian probability theory to compute the probability of the number of decaying exponentials in simulated T1 data. The Bayesian answer to this question is essentially a microcosm of the scientific method and a quantitative statement of Ockham's razor: theorize about possible models, compare these to experiment, and select the simplest model that "best" fits the data.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

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

    PubMed Central

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

    2016-01-01

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

  17. 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.

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

    NASA Technical Reports Server (NTRS)

    Bassiri, S.; Hajj, G. A.

    1992-01-01

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

  19. An Improved Signal Model for Axion Dark Matter Searches

    NASA Astrophysics Data System (ADS)

    Lentz, Erik; ADMX Collaboration

    2017-01-01

    To date, most direct detection searches for axion dark matter, such as those by the Axion Dark Matter eXperiment (ADMX) microwave cavity search, have assumed a signal shape based on an isothermal spherical model of the Milky Way halo. Such a model is not capable of capturing contributions from realistic infall, nor from a baryonic disk. Modern N-Body simulations of structure formation can produce realistic Milky Way-like halos which include the influences of baryons, infall, and environmental influences. This talk presents an analysis of the Romulus25 N-Body simulation in the context of direct dark matter axion searches. An improved signal shape and an account of the relevant halo dynamics are given. Supported by DOE Grants DE-SC0010280, DE-FG02-96ER40956, DE-AC52-07NA27344, DE-AC03-76SF00098, the Heising-Simons Foundation and the LLNL, FNAL and PNNL LDRD program.

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

    PubMed

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

    2016-09-30

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

  1. Modeling of signal transduction in bacterial quorum-sensing

    NASA Astrophysics Data System (ADS)

    Fenley, Andrew; Banik, Suman; Kulkarni, Rahul

    2006-03-01

    Several species of bacteria are able to coordinate gene regulation in response to population density, a process known as ``quorum-sensing''. Quorum-sensing bacteria produce, secrete, and detect signal molecules called autoinducers. For several species of bacteria in the Vibrio genus, recent results have shown that the external autoinducer concentrations control the expression of regulatory small RNA(s) which are critical to the process of quorum-sensing. We present a theoretical analysis of the network which relates the rate of small RNA expression to the external autoinducer concentrations. We relate the results from our modeling to previous experimental observations and suggest new experiments based on testable predictions of the model.

  2. 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.

  3. Optimal sinusoidal modelling of gear mesh vibration signals for gear diagnosis and prognosis

    NASA Astrophysics Data System (ADS)

    Man, Zhihong; Wang, Wenyi; Khoo, Suiyang; Yin, Juliang

    2012-11-01

    In this paper, the synchronous signal average of gear mesh vibration signals is modelled with the multiple modulated sinusoidal representations. The signal model parameters are optimised against the measured signal averages by using the batch learning of the least squares technique. With the optimal signal model, all components of a gear mesh vibration signal, including the amplitude modulations, the phase modulations and the impulse vibration component induced by gear tooth cracking, are identified and analysed with insight of the gear tooth crack development and propagation. In particular, the energy distribution of the impulse vibration signal, extracted from the optimal signal model, provides sufficient information for monitoring and diagnosing the evolution of the tooth cracking process, leading to the prognosis of gear tooth cracking. The new methodologies for gear mesh signal modelling and the diagnosis of the gear tooth fault development and propagation are validated with a set of rig test data, which has shown excellent performance.

  4. 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.

  5. 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.

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

    PubMed

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

    2012-01-01

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

  7. Modeling and processing of laser Doppler reactive hyperaemia signals

    NASA Astrophysics Data System (ADS)

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

    2003-07-01

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

  8. Modeling Very Oscillating Signals. Application to Image Processing

    SciTech Connect

    Aubert, Gilles Aujol, Jean-Francois

    2005-03-15

    This article is a companion paper of a previous work where we have developed the numerical analysis of a variational model first introduced by Rudin et al. and revisited by Meyer for removing the noise and capturing textures in an image. The basic idea in this model is to decompose an image f into two components (u + v) and then to search for (u,v) as a minimizer of an energy functional. The first component u belongs to BV and contains geometrical information, while the second one v is sought in a space G which contains signals with large oscillations, i.e. noise and textures. In Meyer carried out his study in the whole R{sup 2} and his approach is rather built on harmonic analysis tools. We place ourselves in the case of a bounded set{omega} of R{sup 2} which is the proper setting for image processing and our approach is based upon functional analysis arguments. We define in this context the space G, give some of its properties, and then study in this continuous setting the energy functional which allows us to recover the components u and v. We present some numerical experiments to show the relevance of the model for image decomposition and for image denoising.

  9. Radioxenon spiked air

    DOE PAGES

    Watrous, Matthew G.; Delmore, James E.; Hague, Robert K.; ...

    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

  10. 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.

  11. Spectral Analysis of Radioxenon

    DTIC Science & Technology

    2008-09-01

    reasons for spectral fitting being a supplement to the standard energy spectrum ROI method. Fermi- Kurie plot Given the difficulty in fitting a beta...continuum, it is important to find an alternative method. A Fermi- Kurie plot (Krane 1988) is one method, which allows a beta spectrum to be plotted ...corrective function takes into account the initial and final spin and polarity states. A rb itr ar y un its Figure 6. Fermi- Kurie plot . T (MeV

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

    PubMed

    Ganesan, Ambhighainath; Levchenko, Andre

    2012-01-01

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

  13. Discussion on the Modelling and Processing of Signals fom an Acousto-Optic Spectrum Analyzer.

    DTIC Science & Technology

    1987-06-01

    AD-AIBS 639 DISCUSSION ON THE MODELLING AND PROCESSIN OF SIGNALS 1/1 FOR RN ACOUSTO - OPTIC SPECTRUM ANALYZER(U)G DFENCE RESERCH ESTABGLISHMENT OTTANA...8217’~ AV - I National DefenseI Defence nationale DISCUSSION ON THE MODELLING AND PROCESSING OF SIGNALS FROM AN ACOUSTO - OPTIC SPECTRUM ANALYZER by Guy...signals generated by an Acousto - Optic Spectrum Analyzer (AOSA). It also shows how this calculation can be related to pulse modu- lated signals. In its

  14. 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.

  15. 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.

  16. Sequential Markov chain Monte Carlo filter with simultaneous model selection for electrocardiogram signal modeling.

    PubMed

    Edla, Shwetha; Kovvali, Narayan; Papandreou-Suppappola, Antonia

    2012-01-01

    Constructing statistical models of electrocardiogram (ECG) signals, whose parameters can be used for automated disease classification, is of great importance in precluding manual annotation and providing prompt diagnosis of cardiac diseases. ECG signals consist of several segments with different morphologies (namely the P wave, QRS complex and the T wave) in a single heart beat, which can vary across individuals and diseases. Also, existing statistical ECG models exhibit a reliance upon obtaining a priori information from the ECG data by using preprocessing algorithms to initialize the filter parameters, or to define the user-specified model parameters. In this paper, we propose an ECG modeling technique using the sequential Markov chain Monte Carlo (SMCMC) filter that can perform simultaneous model selection, by adaptively choosing from different representations depending upon the nature of the data. Our results demonstrate the ability of the algorithm to track various types of ECG morphologies, including intermittently occurring ECG beats. In addition, we use the estimated model parameters as the feature set to classify between ECG signals with normal sinus rhythm and four different types of arrhythmia.

  17. Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction

    PubMed Central

    Saez-Rodriguez, Julio; Alexopoulos, Leonidas G; Epperlein, Jonathan; Samaga, Regina; Lauffenburger, Douglas A; Klamt, Steffen; Sorger, Peter K

    2009-01-01

    Large-scale protein signalling networks are useful for exploring complex biochemical pathways but do not reveal how pathways respond to specific stimuli. Such specificity is critical for understanding disease and designing drugs. Here we describe a computational approach—implemented in the free CNO software—for turning signalling networks into logical models and calibrating the models against experimental data. When a literature-derived network of 82 proteins covering the immediate-early responses of human cells to seven cytokines was modelled, we found that training against experimental data dramatically increased predictive power, despite the crudeness of Boolean approximations, while significantly reducing the number of interactions. Thus, many interactions in literature-derived networks do not appear to be functional in the liver cells from which we collected our data. At the same time, CNO identified several new interactions that improved the match of model to data. Although missing from the starting network, these interactions have literature support. Our approach, therefore, represents a means to generate predictive, cell-type-specific models of mammalian signalling from generic protein signalling networks. PMID:19953085

  18. A Three Signal Model of T-cell Lymphoma Pathogenesis

    PubMed Central

    Wilcox, Ryan A.

    2015-01-01

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

  19. 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

  20. 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.

  1. 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.

  2. Model based separation of transmitted and received signal for single transducer distance measurement applications

    NASA Astrophysics Data System (ADS)

    Schröder, A.; Henning, B.

    2012-05-01

    Single transducer distance measurement systems have a blind zone which is increased if the transmitted signals are coded to reduce errors due to crosstalk. A method to reduce this blind zone is a model based separation of the transmitted and received signal. This contribution compares two systems, one working with the measured band pass signals, and another one which is based on I/Q-demodulated base band signals.

  3. Bigger, better, faster: principles and models of AKAP anchoring protein signaling.

    PubMed

    Greenwald, Eric C; Saucerman, Jeffrey J

    2011-11-01

    A kinase anchoring proteins (AKAPs) bind multiple signaling proteins and have subcellular targeting domains that allow them to greatly impact cellular signaling. AKAPs localize, specify, amplify, and accelerate signal transduction within the cell by bringing signaling proteins together in space and time. AKAPs also organize higher-order network motifs such as feed forward and feedback loops that may create complex network responses, including adaptation, oscillation, and ultrasensitivity. Computational models have begun to provide an insight into how AKAPs regulate signaling dynamics and cardiovascular pathophysiology. Models of mitogen-activated protein kinase and epidermal growth factor receptor scaffolds have revealed additional design principles and new methods for representing signaling scaffolds mathematically. Coupling computational modeling with quantitative experimental approaches will be increasingly necessary for dissecting the diverse information processing functions performed by AKAP signaling complexes.

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

    PubMed

    Xue, Chuan; Yang, Xige

    2016-10-01

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

  5. 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

  6. 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.

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

    PubMed

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

    2013-05-01

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

  8. Computational models reduce complexity and accelerate insight into cardiac signaling networks.

    PubMed

    Yang, Jason H; Saucerman, Jeffrey J

    2011-01-07

    Cardiac signaling networks exhibit considerable complexity in size and connectivity. The intrinsic complexity of these networks complicates the interpretation of experimental findings. This motivates new methods for investigating the mechanisms regulating cardiac signaling networks and the consequences these networks have on cardiac physiology and disease. Next-generation experimental techniques are also generating a wealth of genomic and proteomic data that can be difficult to analyze or interpret. Computational models are poised to play a key role in addressing these challenges. Computational models have a long history in contributing to the understanding of cardiac physiology and are useful for identifying biological mechanisms, inferring multiscale consequences to cell signaling activities and reducing the complexity of large data sets. Models also integrate well with experimental studies to explain experimental observations and generate new hypotheses. Here, we review the contributions computational modeling approaches have made to the analysis of cardiac signaling networks and forecast opportunities for computational models to accelerate cardiac signaling research.

  9. Modeling and Characterization of Microbarom Signals in the Pacific

    DTIC Science & Technology

    2006-09-01

    wake region microbarom generation theory is discussed in Pnomaryov et al. ( 1998 ) and converging wave trains of opposite directions were also observed in...the wake of Hurricane Bonnie in the Northwest Atlantic Ocean (Wright et al., 1998 ). In the case of the eastward moving middle latitude storm, the...lag-closure relation r,k = At + Atjk + Atki, (1) where Atij is the time delay between the arrival of a signal at sensors i andj (Cansi and Klinger , 1997

  10. Signal-tuned Gabor functions as models for stimulus-dependent cortical receptive fields.

    PubMed

    Torreão, José R A; Victer, Silvia M C; Amaral, Marcos S

    2014-05-01

    We propose and analyze a model, based on signal-tuned Gabor functions, for the receptive fields and responses of V1 cells. Signal-tuned Gabor functions are gaussian-modulated sinusoids whose parameters are obtained from a given, spatial, or spectral "tuning" signal. These functions can be proven to yield exact representations of their tuning signals and have recently been proposed as the kernels of a variant Gabor transform-the signal-tuned Gabor transform (STGT)-which allows the accurate detection of spatial and spectral events. Here we show that by modeling the receptive fields of simple and complex cells as signal-tuned Gabor functions and expressing their responses as STGTs, we are able to replicate the properties of these cells when tested with standard grating and slit inputs, at the same time emulating their stimulus-dependent character as revealed by recent neurophysiological studies.

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

    PubMed Central

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

    2016-01-01

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

  12. 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

  13. Living ordered neural networks as model systems for signal processing

    NASA Astrophysics Data System (ADS)

    Villard, C.; Amblard, P. O.; Becq, G.; Gory-Fauré, S.; Brocard, J.; Roth, S.

    2007-06-01

    Neural circuit architecture is a fundamental characteristic of the brain, and how architecture is bound to biological functions is still an open question. Some neuronal geometries seen in the retina or the cochlea are intriguing: information is processed in parallel by several entities like in "pooling" networks which have recently drawn the attention of signal processing scientists. These systems indeed exhibit the noise-enhanced processing effect, which is also actively discussed in the neuroscience community at the neuron scale. The aim of our project is to use in-vitro ordered neuron networks as living paradigms to test ideas coming from the computational science. The different technological bolts that have to be solved are enumerated and the first results are presented. A neuron is a polarised cell, with an excitatory axon and a receiving dendritic tree. We present how soma confinement and axon differentiation can be induced by surface functionalization techniques. The recording of large neuron networks, ordered or not, is also detailed and biological signals shown. The main difficulty to access neural noise in the case of weakly connected networks grown on micro electrode arrays is explained. This open the door to a new detection technology suitable for sub-cellular analysis and stimulation, whose development will constitute the next step of this project.

  14. A Framework for Non-Gaussian Signal Modeling and Estimation

    DTIC Science & Technology

    1999-06-01

    1993. [38] B. P. Carlin , N. G. Polson, and D. S. Stoffer, "A Monte Carlo approach to nonnormal and nonlinear state-space modeling," Journal of the...NJ: Prentice-Hall, 1992. [198] J. R. Thompson, Empirical Model Building. New York: John Wiley & Sons, 1989. [199] J. R. Thompson and R. A. Tapia

  15. BioSignalML--a meta-model for biosignals.

    PubMed

    Brooks, David J; Hunter, Peter J; Smaill, Bruce H; Titchener, Mark R

    2011-01-01

    The multitude of biosignal file formats used in research has hampered the easy exchange of biosignals and their use with physiological modelling software. We describe an abstract data model that accommodates the diversity of formats, along with a software implementation which links biosignal data into the Semantic Web, using existing data formats. Initial application of our work is to sleep study research.

  16. 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.

  17. Effects of signal light on the fuel consumption and emissions under car-following model

    NASA Astrophysics Data System (ADS)

    Tang, Tie-Qiao; Yi, Zhi-Yan; Lin, Qing-Feng

    2017-03-01

    In this paper, a car-following model is utilized to study the effects of signal light on each vehicle's fuel consumption, CO, HC and NOX. The numerical results show that each vehicle's fuel consumption and emissions are influenced by the signal light and that the effects are related to the green split of the signal light and the vehicle's time headway at the origin, which can help drivers adjust their micro driving behavior on the road with a signal light to reduce their fuel consumption and emissions.

  18. Modelling and simulation of signal transductions in an apoptosis pathway by using timed Petri nets.

    PubMed

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

    2007-01-01

    This paper first presents basic Petri net components representing molecular interactions and mechanisms of signalling pathways, and introduces a method to construct a Petri net model of a signalling pathway with these components. Then a simulation method of determining the delay time of transitions, by using timed Petri nets - i.e. the time taken in fi ring of each transition - is proposed based on some simple principles that the number of tokens flowed into a place is equivalent to the number of tokens fl owed out. Finally, the availability of proposed method is confirmed by observing signalling transductions in biological pathways through simulation experiments of the apoptosis signalling pathways as an example.

  19. Systematic modeling for the insulin signaling network mediated by IRS(1) and IRS(2).

    PubMed

    Huang, Can; Wu, Ming; Du, Jun; Liu, Di; Chan, Christina

    2014-08-21

    The hepatic insulin signaling mediated by insulin receptor substrates IRS1 and IRS2 plays a central role in maintaining glucose homeostasis under different physiological conditions. Although functions of individual components in the signaling network have been extensively studied, our knowledge is still limited with regard to how the signals are integrated and coordinated in the complex network to render their functional roles. In this study, we construct systematic models for the insulin signaling network mediated by IRS1 and IRS2, through the integration of current knowledge in the literature into mathematical models of insulin signaling pathways. We hypothesize that the specificity of the IRS signaling mechanisms emerges from the wiring and kinetics of the entire network. A discrete dynamic model is first constructed to account for the numerous dynamic features in the system, i.e., complex feedback circuits, different regulatory time-scales and cross-talks between pathways. Our simulation shows that the wiring of the network determines different functions of IRS1 and IRS2. We further collate and reconstruct a kinetic model of the network as a system of ordinary differential equations to provide an informative model for predicting phenotypes. A sensitivity analysis is applied to identify essential regulators for the signaling process.

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

    PubMed Central

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  2. 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.

  3. Large-signal model of a resonating cantilever-based transducer for system level electrical simulation

    NASA Astrophysics Data System (ADS)

    Verd, Jaume; Teva, Jordi; Abadal, Gabriel; Perez-Murano, Francesc; Esteve, Jaume; Barniol, Nuria

    2005-07-01

    In this work, we present a non-linear electromechanical model of an electrostatically excited cantilever that can be used to perform system level electrical simulations. This model is implemented by using an analog hardware description language (VHDL-AMS) that allows its use in a common IC CAD environment like CADENCE. Small-signal and large-signal simulations are performed and the results are compared with a simple linear model (RLC//C) showing the benefits of this model. This model is validated by its fit with the experimental results obtained from a monolithic sub-micrometer cantilever based sensor

  4. Visual modeling of laser Doppler anemometer signals by moiré fringes.

    PubMed

    Durst, F; Stevenson, W H

    1976-01-01

    This report describes the employment of moiré patterns to model visually interference phenomena in general and laser Doppler anemometer signals in particular. The modeling includes signals created in dual beam and reference beam anemometers by both single particles and particle pairs. The considerations are extended to visual modeling of multiparticle signals and the decay of signal quality in the presence of many particles. The fringe model of the laser Doppler anemometer is also considered, and moiré patterns are employed to demonstrate the interference fringes in the crossover region of two intersecting laser beams. Gaussian beam properties are taken into account to allow the effects of improperly designed optical systems to be studied. Instructions for using computer generated transparencies to produce the different moiré patterns are provided to allow the reader to study in detail the various interference phenomena described.

  5. Signal Delay in Leaky RC Mesh Models for Bipolar Interconnect,

    DTIC Science & Technology

    1985-10-01

    Mesh Networks," IEEE Trans. Circuits and Systems, vol. CAS-32, no. 5, pp. 507-510, May 1985. (3] Desoer , Charles A., and Ernest S. Kuh, Basic Circuit ...is appropriate for * modelling interconnect in digital bipolar circuits . This paper is intended to serve as a tutorial as well as a research report...class of networks that is appropriate for modelling interconnect in digital bipolar circuits . This paper is intended *" to serve as a tutorial as well

  6. Statistical Signal Models and Algorithms for Image Analysis

    DTIC Science & Technology

    1984-10-25

    In this report, two-dimensional stochastic linear models are used in developing algorithms for image analysis such as classification, segmentation, and object detection in images characterized by textured backgrounds. These models generate two-dimensional random processes as outputs to which statistical inference procedures can naturally be applied. A common thread throughout our algorithms is the interpretation of the inference procedures in terms of linear prediction

  7. 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

  8. Model observer design for multi-signal detection in the presence of anatomical noise

    NASA Astrophysics Data System (ADS)

    Wen, Gezheng; Markey, Mia K.; Park, Subok

    2017-02-01

    As psychophysical studies are resource-intensive to conduct, model observers are commonly used to assess and optimize medical imaging quality. Model observers are typically designed to detect at most one signal. However, in clinical practice, there may be multiple abnormalities in a single image set (e.g. multifocal multicentric (MFMC) breast cancer), which can impact treatment planning. Prevalence of signals can be different across anatomical regions, and human observers do not know the number or location of signals a priori. As new imaging techniques have the potential to improve multiple-signal detection (e.g. digital breast tomosynthesis may be more effective for diagnosis of MFMC than mammography), image quality assessment approaches addressing such tasks are needed. In this study, we present a model observer to detect multiple signals in an image dataset. A novel implementation of partial least squares (PLS) was developed to estimate different sets of efficient channels directly from the images. The PLS channels are adaptive to the characteristics of signals and the background, and they capture the interactions among signal locations. Corresponding linear decision templates are employed to generate both image-level and location-specific scores on the presence of signals. Our results show that: (1) the model observer can achieve high performance with a reasonably small number of channels; (2) the model observer with PLS channels outperforms that with benchmark modified Laguerre–Gauss channels, especially when realistic signal shapes and complex background statistics are involved; (3) the tasks of clinical interest, and other constraints such as sample size would alter the optimal design of the model observer.

  9. 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.

  10. 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.

  11. Adaptive modeling and spectral estimation of nonstationary biomedical signals based on Kalman filtering.

    PubMed

    Aboy, Mateo; Márquez, Oscar W; McNames, James; Hornero, Roberto; Trong, Tran; Goldstein, Brahm

    2005-08-01

    We describe an algorithm to estimate the instantaneous power spectral density (PSD) of nonstationary signals. The algorithm is based on a dual Kalman filter that adaptively generates an estimate of the autoregressive model parameters at each time instant. The algorithm exhibits superior PSD tracking performance in nonstationary signals than classical nonparametric methodologies, and does not assume local stationarity of the data. Furthermore, it provides better time-frequency resolution, and is robust to model mismatches. We demonstrate its usefulness by a sample application involving PSD estimation of intracranial pressure signals (ICP) from patients with traumatic brain injury (TBI).

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

    PubMed

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

    2014-01-01

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

  13. Model benchmarking and reference signals for angled-beam shear wave ultrasonic nondestructive evaluation (NDE) inspections

    NASA Astrophysics Data System (ADS)

    Aldrin, John C.; Hopkins, Deborah; Datuin, Marvin; Warchol, Mark; Warchol, Lyudmila; Forsyth, David S.; Buynak, Charlie; Lindgren, Eric A.

    2017-02-01

    For model benchmark studies, the accuracy of the model is typically evaluated based on the change in response relative to a selected reference signal. The use of a side drilled hole (SDH) in a plate was investigated as a reference signal for angled beam shear wave inspection for aircraft structure inspections of fastener sites. Systematic studies were performed with varying SDH depth and size, and varying the ultrasonic probe frequency, focal depth, and probe height. Increased error was observed with the simulation of angled shear wave beams in the near-field. Even more significant, asymmetry in real probes and the inherent sensitivity of signals in the near-field to subtle test conditions were found to provide a greater challenge with achieving model agreement. To achieve quality model benchmark results for this problem, it is critical to carefully align the probe with the part geometry, to verify symmetry in probe response, and ideally avoid using reference signals from the near-field response. Suggested reference signals for angled beam shear wave inspections include using the `through hole' corner specular reflection signal and the full skip' signal off of the far wall from the side drilled hole.

  14. Modeling of Terahertz Ray Signals for Nde Applications

    NASA Astrophysics Data System (ADS)

    Chiou, Chien-Ping; Thompson, R. Bruce; Blackshire, James L.

    2008-02-01

    Recently, terahertz ray (T-ray) imaging has emerged as one of the most promising new techniques for NDE applications. This technique, however, is still in its early development, and requires further studies. This work explores the use of state-of-the-art computer modeling technologies to study T-ray radiation in media. A series of point source synthesis models have been developed, using both the classic Fresnel-Kirchhoff and the refined Rayleigh-Sommerfeld formulations. The flexibility of these models enables us to investigate T-ray propagation through interfaces of various geometry and morphology. That in turn allows us to simulate T-ray interaction with flaws and hence to predict the flaw responses. In this paper, we present preliminary results of simulating T-ray inspection of space shuttle's spray-on foam insulation structure. Included are comparisons with experimental data of drilled holes embedded in foam sample.

  15. Effect of image compression for model and human observers in signal-known-statistically tasks

    NASA Astrophysics Data System (ADS)

    Eckstein, Miguel P.; Pham, Binh; Abbey, Craig K.

    2002-04-01

    Previous studies have shown that model observers can be used for automated evaluation and optimization of image compression with respect to human visual performance in a task where the signal does not vary and is known a priori by the observer (signal known exactly, SKE). Here, we extend previous work to two tasks that are intended to more realistically represent the day-to-day visual diagnostic decision in the clinical setting. In the signal known exactly but variable task (SKEV), the signal varies from trial to trial (e.g., size, shape, etc) but is known to the observer. In the signal known statistically task (SKS) the signal varies from trial to trial and the observer does not have knowledge of which signal is present in that trial. We compare SKEV/SKS human and model observer performance detecting simulated arterial filling defects embedded in real coronary angiographic backgrounds in images that have undergone different amounts of JPEG and JPEG 2000 image compression. Our results show that both human and model performance at low compression ratios is better for the JPEG algorithm than the JPEG 2000 algorithm. Metrics of image quality such as the root mean square error (or the related peak signal to noise ratio) incorrectly predict a JPEG 2000 superiority. Results also show that although model and to a lesser extent human performance improves with the trial to trial knowledge of the signal present (SKEV vs. SKS task), conclusions about which compression algorithm is better (JPEG vs. JPEG 2000) for the current task would not change whether one used an SKEV or SKS task. These findings might suggest that the computationally more tractable SKEV models could be used as a good first approximation for automated evaluation of the more clinically realistic SKS task.

  16. 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.

  17. Modeling Associative Recognition: A Comparison of Two-High-Threshold, Two-High-Threshold Signal Detection, and Mixture Distribution Models

    ERIC Educational Resources Information Center

    Macho, Siegfried

    2004-01-01

    A 2-high-threshold signal detection (HTSDT) model, a mixture distribution (SON) model, and 2-highthreshold (HT) models with responses distributed over 1 or several response categories were fit to results of 6 experiments from 2 studies on associative recognition: R. Kelley and J. T. Wixted (2001) and A. P. Yonelinas (1997). HTSDT assumes that…

  18. 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.

  19. Computational Models of Reactive Oxygen Species as Metabolic Byproducts and Signal-Transduction Modulators

    PubMed Central

    Pereira, Elizabeth J.; Smolko, Christian M.; Janes, Kevin A.

    2016-01-01

    Reactive oxygen species (ROS) are widely involved in intracellular signaling and human pathologies, but their precise roles have been difficult to enumerate and integrate holistically. The context- and dose-dependent intracellular effects of ROS can lead to contradictory experimental results and confounded interpretations. For example, lower levels of ROS promote cell signaling and proliferation, whereas abundant ROS cause overwhelming damage to biomolecules and cellular apoptosis or senescence. These complexities raise the question of whether the many facets of ROS biology can be joined under a common mechanistic framework using computational modeling. Here, we take inventory of some current models for ROS production or ROS regulation of signaling pathways. Several models captured non-intuitive observations or made predictions that were later verified by experiment. There remains a need for systems-level analyses that jointly incorporate ROS production, handling, and modulation of multiple signal-transduction cascades. PMID:27965578

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

    NASA Astrophysics Data System (ADS)

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

    2004-05-01

    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.

  1. Objective models of EMG signals for cyclic processes such as a human gait

    NASA Astrophysics Data System (ADS)

    Babska, Luiza; Selegrat, Monika; Dusza, Jacek J.

    2016-09-01

    EMG signals are small potentials appearing at the surface of human skin during muscle work. They arise due to changes in the physiological state of cell membranes in the muscle fibers. They are characterized by a relatively low frequency range (500 Hz) and a low amplitude signal (of the order of μV), making it difficult to record. Raw EMG signal is inherently random shape. However we can distinguish certain features related to the activation of the muscles of a deterministic or quasi-deterministic associated with the movement and its parametric description. Objective models of EMG signals were created on the base of actual data obtained from the VICON system installed at the University of Physical Education in Warsaw. The object of research (healthy woman) moved repeatedly after a fixed track. On her body 35 reflective markers to record the gait kinematics and 8 electrodes to record EMG signals were placed. We obtained research data included more than 1,000 EMG signals synchronized with the phases of gait. Test result of the work is an algorithm for obtaining the average EMG signal received from the multiple registration gait cycles carried out in the same reproducible conditions. The method described in the article is essentially a pre-finding measurement data from the two quasi-synchronous signals at different sampling frequencies for further processing. This signal is characterized by a significant reduction of high frequency noise and emphasis on the specific characteristics of individual records found in muscle activity.

  2. Extracting harmonic signal from a chaotic background with local linear model

    NASA Astrophysics Data System (ADS)

    Li, Chenlong; Su, Liyun

    2017-02-01

    In this paper, the problems of blind detection and estimation of harmonic signal in strong chaotic background are analyzed, and new methods by using local linear (LL) model are put forward. The LL model has been exhaustively researched and successfully applied for fitting and forecasting chaotic signal in many chaotic fields. We enlarge the modeling capacity substantially. Firstly, we can predict the short-term chaotic signal and obtain the fitting error based on the LL model. Then we detect the frequencies from the fitting error by periodogram, a property on the fitting error is proposed which has not been addressed before, and this property ensures that the detected frequencies are similar to that of harmonic signal. Secondly, we establish a two-layer LL model to estimate the determinate harmonic signal in strong chaotic background. To estimate this simply and effectively, we develop an efficient backfitting algorithm to select and optimize the parameters that are hard to be exhaustively searched for. In the method, based on sensitivity to initial value of chaos motion, the minimum fitting error criterion is used as the objective function to get the estimation of the parameters of the two-layer LL model. Simulation shows that the two-layer LL model and its estimation technique have appreciable flexibility to model the determinate harmonic signal in different chaotic backgrounds (Lorenz, Henon and Mackey-Glass (M-G) equations). Specifically, the harmonic signal can be extracted well with low SNR and the developed background algorithm satisfies the condition of convergence in repeated 3-5 times.

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

    PubMed

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

    2016-01-01

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

  4. 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

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

    PubMed

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

    2006-10-01

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

  6. Modeling of Ultrasonic Signals from a Side-Drilled Hole Captured By a Rectangular Transducer

    NASA Astrophysics Data System (ADS)

    Kim, Hak-Joon; Song, Sung-Jin; Schmerr, Lester W.

    2006-03-01

    In ultrasonic nondestructive testing an angle beam transducer with a rectangular piezoelectric element is often adopted in practice to detect flaws. Also, a side-drilled hole (SDH) is very widely used as a standard reflector in ultrasonic testing. For proper interpretation of the measurement results from a SDH using a rectangular transducer, it is very helpful to have a complete ultrasonic measurement model including an ultrasonic beam model of the rectangular transducer, a scattering model of the SDH, and an ultrasonic system model. Recently, a highly efficient ultrasonic beam model of the rectangular transducer and an accurate scattering model of the SDH have been proposed. Thus, in this study, by combining those components with a system efficiency factor for a rectangular transducer, we develop a complete ultrasonic measurement model to predict ultrasonic signals from a SDH. Based on this model, we have calculated the ultrasonic signals from a SDH at different transducer orientations. The predicted results are compared with the experiments.

  7. 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.

  8. 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.

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

    PubMed

    Wilcox, Ryan A

    2016-01-01

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

  10. Modeling the Adaptive Role of Negative Signaling in Honey Bee Intraspecific Competition

    PubMed Central

    Nieh, James C.

    2010-01-01

    Collective decision making in the social insects often proceeds via feedback cycles based on positive signaling. Negative signals have, however, been found in a few contexts in which costs exist for paying attention to no longer useful information. Here we incorporate new research on the specificity and context of the negative stop signal into an agent based model of honey bee foraging to explore the adaptive basis of negative signaling in the dance language. Our work suggests that the stop signal, by acting as a counterbalance to the waggle dance, allows colonies to rapidly shut down attacks on other colonies. This could be a key adaptation, as the costs of attacking a colony strong enough to defend itself are significant. Electronic supplementary material The online version of this article (doi:10.1007/s10905-010-9229-5) contains supplementary material, which is available to authorized users. PMID:21037953

  11. 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.

  12. 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.

  13. Numerical study of a macroscopic finite pulse model of the diffusion MRI signal.

    PubMed

    Li, Jing-Rebecca; Nguyen, Hang Tuan; Nguyen, Dang Van; Haddar, Houssem; Coatléven, Julien; Le Bihan, Denis

    2014-11-01

    Diffusion magnetic resonance imaging (dMRI) is an imaging modality that probes the diffusion characteristics of a sample via the application of magnetic field gradient pulses. The dMRI signal from a heterogeneous sample includes the contribution of the water proton magnetization from all spatial positions in a voxel. If the voxel can be spatially divided into different Gaussian diffusion compartments with inter-compartment exchange governed by linear kinetics, then the dMRI signal can be approximated using the macroscopic Karger model, which is a system of coupled ordinary differential equations (ODEs), under the assumption that the duration of the diffusion-encoding gradient pulses is short compared to the diffusion time (the narrow pulse assumption). Recently, a new macroscopic model of the dMRI signal, without the narrow pulse restriction, was derived from the Bloch-Torrey partial differential equation (PDE) using periodic homogenization techniques. When restricted to narrow pulses, this new homogenized model has the same form as the Karger model. We conduct a numerical study of the new homogenized model for voxels that are made up of periodic copies of a representative volume that contains spherical and cylindrical cells of various sizes and orientations and show that the signal predicted by the new model approaches the reference signal obtained by solving the full Bloch-Torrey PDE in O(ε(2)), where ε is the ratio between the size of the representative volume and a measure of the diffusion length. When the narrow gradient pulse assumption is not satisfied, the new homogenized model offers a much better approximation of the full PDE signal than the Karger model. Finally, preliminary results of applying the new model to a voxel that is not made up of periodic copies of a representative volume are shown and discussed.

  14. Simultaneous powerline interference and baseline wander removal from ECG and EMG signals by sinusoidal modeling.

    PubMed

    Zivanovic, Miroslav; González-Izal, Miriam

    2013-10-01

    We present a compact approach to joint modeling of powerline interference (PLI) and baseline wonder (BW) for denoising of biopotential signals. Both PLI and BW are modeled by a set of harmonically related sinusoids modulated by low-order time polynomials. The sinusoids account on the harmonicity and mean instantaneous frequency of the PLI in the analysis window, while the polynomials capture the frequency and amplitude deviations from their nominal values and characterize the BW at the same time. The resulting model is linear-in-parameters and the solution to the corresponding linear system is estimated in a simple and efficient way through linear least-squares. The proposed modeling method was evaluated on real electrocardiographic (ECG) and electromyographic (EMG) signals against three reference methods for different analysis scenarios. The comparative study suggests that the proposed method outperforms the reference methods in terms of residual interference energy in the denoised biopotential signals.

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

    PubMed Central

    Kirana, Firman Ahmad; Husein, Irzaman Sulaiman

    2016-01-01

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

  16. An original traffic additional emission model and numerical simulation on a signalized road

    NASA Astrophysics Data System (ADS)

    Zhu, Wen-Xing; Zhang, Jing-Yu

    2017-02-01

    Based on VSP (Vehicle Specific Power) model traffic real emissions were theoretically classified into two parts: basic emission and additional emission. An original additional emission model was presented to calculate the vehicle's emission due to the signal control effects. Car-following model was developed and used to describe the traffic behavior including cruising, accelerating, decelerating and idling at a signalized intersection. Simulations were conducted under two situations: single intersection and two adjacent intersections with their respective control policy. Results are in good agreement with the theoretical analysis. It is also proved that additional emission model may be used to design the signal control policy in our modern traffic system to solve the serious environmental problems.

  17. A global sensitivity tool for cardiac cell modeling: Application to ionic current balance and hypertrophic signaling.

    PubMed

    Sher, Anna A; Cooling, Michael T; Bethwaite, Blair; Tan, Jefferson; Peachey, Tom; Enticott, Colin; Garic, Slavisa; Gavaghan, David J; Noble, Denis; Abramson, David; Crampin, Edmund J

    2010-01-01

    Cardiovascular diseases are the major cause of death in the developed countries. Identifying key cellular processes involved in generation of the electrical signal and in regulation of signal transduction pathways is essential for unraveling the underlying mechanisms of heart rhythm behavior. Computational cardiac models provide important insights into cardiovascular function and disease. Sensitivity analysis presents a key tool for exploring the large parameter space of such models, in order to determine the key factors determining and controlling the underlying physiological processes. We developed a new global sensitivity analysis tool which implements the Morris method, a global sensitivity screening algorithm, onto a Nimrod platform, which is a distributed resources software toolkit. The newly developed tool has been validated using the model of IP3-calcineurin signal transduction pathway model which has 30 parameters. The key driving factors of the IP3 transient behaviour have been calculated and confirmed to agree with previously published data. We next demonstrated the use of this method as an assessment tool for characterizing the structure of cardiac ionic models. In three latest human ventricular myocyte models, we examined the contribution of transmembrane currents to the shape of the electrical signal (i.e. on the action potential duration). The resulting profiles of the ionic current balance demonstrated the highly nonlinear nature of cardiac ionic models and identified key players in different models. Such profiling suggests new avenues for development of methodologies to predict drug action effects in cardiac cells.

  18. 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...

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

    PubMed Central

    Yi, Yongwoo

    2016-01-01

    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

  20. Modeling the time course of attention signals in human primary visual cortex

    NASA Astrophysics Data System (ADS)

    Silver, Michael A.

    2006-02-01

    Previous neuroimaging studies have documented the existence of attention signals in human visual cortex, but little is known about the time course of these signals. A recent study reported persistent activity in early visual cortex whose duration was correlated with the duration of sustained attention1. The present study extends these findings by modeling the time course of sustained attention signals with a linear function with duration equal to the period of sustained attention but with variable amplitude and slope. Subjects performed a visual detection task in which a variable-duration delay period occurred before every target presentation. This design required the subjects to allocate visuospatial attention throughout the delay period. Functional magnetic resonance imaging (fMRI) was used to record activity in primary visual cortex (cortical area V1) during performance of the task. There were significant individual differences in the time course of attention signals, with some subjects displaying time courses consistent with constant amplitude attention signals, while others showed decreasing amplitude of attention-related activity during the delay period. These individual differences in time course of attention signals were correlated with behavioral response bias, suggesting that they may reflect differences in the types of attention used by the subjects to perform the detection task. In particular, those subjects who had constant amplitude sustained attention signals may have been employing relatively more endogenous, or top-down attention, while the subjects who exhibited attention signals that decreased over time may have been using relatively more exogenous, or bottom-up attention.

  1. Modeling and simulation of atmosphere interference signal based on FTIR spectroscopy technique

    NASA Astrophysics Data System (ADS)

    Zhang, Yugui; Li, Qiang; Yu, Zhengyang; Liu, Zhengmin

    2016-09-01

    Fourier Transform Infrared spectroscopy technique, featured with large frequency range and high spectral resolution, is becoming the research focus in spectrum analysis area, and is spreading in atmosphere detection applications in the aerospace field. In this paper, based on FTIR spectroscopy technique, the principle of atmosphere interference signal generation is deduced in theory, and also its mathematical model and simulation are carried out. Finally, the intrinsic characteristics of the interference signal in time domain and frequency domain, which give a theoretical foundation to the performance parameter design of electrical signal processing, are analyzed.

  2. Model-based speech enhancement using a bone-conducted signal.

    PubMed

    Kechichian, Patrick; Srinivasan, Sriram

    2012-03-01

    Codebook-based single-microphone noise suppressors, which exploit prior knowledge about speech and noise statistics, provide better performance in nonstationary noise. However, as the enhancement involves a joint optimization over speech and noise codebooks, this results in high computational complexity. A codebook-based method is proposed that uses a reference signal observed by a bone-conduction microphone, and a mapping between air- and bone-conduction codebook entries generated during an offline training phase. A smaller subset of air-conducted speech codebook entries that accurately models the clean speech signal is selected using this reference signal. Experiments support the expected improvement in performance at low computational complexity.

  3. 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

  4. 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

  5. Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways

    PubMed Central

    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

  6. 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.

  7. 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

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

    PubMed

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

    2015-04-21

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

  9. Dynamic pathway modeling of signal transduction networks: a domain-oriented approach.

    PubMed

    Conzelmann, Holger; Gilles, Ernst-Dieter

    2008-01-01

    Mathematical models of biological processes become more and more important in biology. The aim is a holistic understanding of how processes such as cellular communication, cell division, regulation, homeostasis, or adaptation work, how they are regulated, and how they react to perturbations. The great complexity of most of these processes necessitates the generation of mathematical models in order to address these questions. In this chapter we provide an introduction to basic principles of dynamic modeling and highlight both problems and chances of dynamic modeling in biology. The main focus will be on modeling of s transduction pathways, which requires the application of a special modeling approach. A common pattern, especially in eukaryotic signaling systems, is the formation of multi protein signaling complexes. Even for a small number of interacting proteins the number of distinguishable molecular species can be extremely high. This combinatorial complexity is due to the great number of distinct binding domains of many receptors and scaffold proteins involved in signal transduction. However, these problems can be overcome using a new domain-oriented modeling approach, which makes it possible to handle complex and branched signaling pathways.

  10. 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.

  11. 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.

  12. 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.

  13. Secret Key Agreement by Soft-Decision of Signals in Gaussian Maurer's Model

    NASA Astrophysics Data System (ADS)

    Naito, Masashi; Watanabe, Shun; Matsumoto, Ryutaroh; Uyematsu, Tomohiko

    We consider the problem of secret key agreement in Gaussian Maurer's Model. In Gaussian Maurer's model, legitimate receivers, Alice and Bob, and a wire-tapper, Eve, receive signals randomly generated by a satellite through three independent memoryless Gaussian channels respectively. Then Alice and Bob generate a common secret key from their received signals. In this model, we propose a protocol for generating a common secret key by using the result of soft-decision of Alice and Bob's received signals. Then, we calculate a lower bound on the secret key rate in our proposed protocol. As a result of comparison with the protocol that only uses hard-decision, we found that the higher rate is obtained by using our protocol.

  14. A mathematical model of pulse-coded hormone signal responses in pituitary gonadotroph cells

    PubMed Central

    Magill, John C.; Ciccone, Nick A.; Kaiser, Ursula B.

    2014-01-01

    Cells in the pituitary that synthesize luteinizing and follicle-stimulating hormones regulate the relative production of these two key reproductive hormones in response to signals from the hypothalamus. These signals are encoded in the frequency of gonadotrophin-releasing-hormone pulses. In vitro experiments with a murine-derived cell line have identified key elements of the processes that decode the signal to regulate transcription of the subunits encoding these hormones. The mathematical model described in this paper is based on the results of those experiments and advances quantitative understanding of the biochemical decoder. The model consists of non-linear differential equations for each of six processes that lead to the synthesis of follicle-stimulating hormone. Simulations of the model exhibit key characteristics found in the experiments, including a preference for follicle-stimulating hormone synthesis at low pulse frequencies and a loss of this characteristic when a mutation is introduced. PMID:24095971

  15. 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

    2014-12-08

    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.

  16. 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.

  17. Modeling log-compressed ultrasound images for radio frequency signal recovery.

    PubMed

    Seabra, José; Sanches, João

    2008-01-01

    This paper presents an algorithm for recovering the radio frequency (RF) signal provided by the ultrasound probe from the log-compressed ultrasound images displayed in ultrasound equipment. Commercial ecographs perform nonlinear image compression to reduce the dynamic range of the Ultrasound (US) signal in order to improve image visualization. Moreover, the clinician may adjust other parameters, such as brightness, gain and contrast, to improve image quality of a given anatomical detail. These operations significantly change the statistical distribution of the original RF raw signal, which is assumed, based on physical considerations on the signal formation process, to be Rayleigh distributed. Therefore, the image pixels are no longer Rayleigh distributed and the RF signal is not usually available in the common ultrasound equipment. For statistical data processing purposes, more important than having "good looking" images, it is important to have realistic models to describe the data. In this paper, a nonlinear compression parametric function is used to model the pre-processed image in order to recover the original RF image as well the contrast and brightness parameters. Tests using synthetic and real data and statistical measures such as the Kolmogorov-Smirnov and Kullback-Leibler divergences are used to assess the results. It is shown that the proposed estimation model clearly represents better the observed data than by taking the general assumption of the data being modeled by a Rayleigh distribution.

  18. 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

  19. 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

  20. 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.

  1. 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

  2. Dissecting Cell-Fate Determination Through Integrated Mathematical Modeling of the ERK/MAPK Signaling Pathway.

    PubMed

    Shin, Sung-Young; Nguyen, Lan K

    2017-01-01

    The past three decades have witnessed an enormous progress in the elucidation of the ERK/MAPK signaling pathway and its involvement in various cellular processes. Because of its importance and complex wiring, the ERK pathway has been an intensive subject for mathematical modeling, which facilitates the unraveling of key dynamic properties and behaviors of the pathway. Recently, however, it became evident that the pathway does not act in isolation but closely interacts with many other pathways to coordinate various cellular outcomes under different pathophysiological contexts. This has led to an increasing number of integrated, large-scale models that link the ERK pathway to other functionally important pathways. In this chapter, we first discuss the essential steps in model development and notable models of the ERK pathway. We then use three examples of integrated, multipathway models to investigate how crosstalk of ERK signaling with other pathways regulates cell-fate decision-making in various physiological and disease contexts. Specifically, we focus on ERK interactions with the phosphoinositide-3 kinase (PI3K), c-Jun N-terminal kinase (JNK), and β-adrenergic receptor (β-AR) signaling pathways. We conclude that integrated modeling in combination with wet-lab experimentation have been and will be instrumental in gaining an in-depth understanding of ERK signaling in multiple biological contexts.

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

    PubMed

    Kalauzi, Aleksandar; Bojić, Tijana; Vuckovic, Aleksandra

    2012-07-01

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

  4. Coordinated photomorphogenic UV-B signaling network captured by mathematical modeling

    PubMed Central

    Ouyang, Xinhao; Huang, Xi; Jin, Xiao; Chen, Zheng; Yang, Panyu; Ge, Hao; Li, Shigui; Deng, Xing Wang

    2014-01-01

    Long-wavelength and low-fluence UV-B light is an informational signal known to induce photomorphogenic development in plants. Using the model plant Arabidopsis thaliana, a variety of factors involved in UV-B–specific signaling have been experimentally characterized over the past decade, including the UV-B light receptor UV resistance locus 8; the positive regulators constitutive photomorphogenesis 1 and elongated hypocotyl 5; and the negative regulators cullin4, repressor of UV-B photomorphogenesis 1 (RUP1), and RUP2. Individual genetic and molecular studies have revealed that these proteins function in either positive or negative regulatory capacities for the sufficient and balanced transduction of photomorphogenic UV-B signal. Less is known, however, regarding how these signaling events are systematically linked. In our study, we use a systems biology approach to investigate the dynamic behaviors and correlations of multiple signaling components involved in Arabidopsis UV-B–induced photomorphogenesis. We define a mathematical representation of photomorphogenic UV-B signaling at a temporal scale. Supplemented with experimental validation, our computational modeling demonstrates the functional interaction that occurs among different protein complexes in early and prolonged response to photomorphogenic UV-B. PMID:25049395

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

    PubMed

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

    2012-11-19

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

  6. An Iterative Extension of Prony’s Method for ARMA Signal Modeling

    DTIC Science & Technology

    1993-09-15

    for ARMA Signal Modeling by Charles W. Therrien Carlos H. Velasco 94-13278iIlHII~Iil~lIilIIIlllI~IIllllhlIII• • . ,, September 15, 1993,, Approved for...of all or part of this report is authorized. This report was prepared by: CHARLES W. THERRIEN Professor, Department of Electrical and Computer...TITLE AND SUBTITLE 5. FUNDING N4UMBERS An Iterative Extension of Prony’s Method for ARMA Signal Modeling 6. AUTHOR(S) Charles W. Therrien and Carlos

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

    PubMed

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

    2012-08-27

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

  8. Wavelet detection of weak far-magnetic signal based on adaptive ARMA model threshold

    NASA Astrophysics Data System (ADS)

    Zhang, Ning; Lin, Chun-sheng; Fang, Shi

    2009-10-01

    Based on Mallat algorithm, a de-noising algorithm of adaptive wavelet threshold is applied for weak magnetic signal detection of far moving target in complex magnetic environment. The choice of threshold is the key problem. With the spectrum analysis of the magnetic field target, a threshold algorithm on the basis of adaptive ARMA model filter is brought forward to improve the wavelet filtering performance. The simulation of this algorithm on measured data is carried out. Compared to Donoho threshold algorithm, it shows that adaptive ARMA model threshold algorithm significantly improved the capability of weak magnetic signal detection in complex magnetic environment.

  9. 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

  10. Body charge modelling for accurate simulation of small-signal behaviour in floating body SOI

    NASA Astrophysics Data System (ADS)

    Benson, James; Redman-White, William; D'Halleweyn, Nele V.; Easson, Craig A.; Uren, Michael J.

    2002-04-01

    We show that careful modelling of body node elements in floating body PD-SOI MOSFET compact models is required in order to obtain accurate small-signal simulation results in the saturation region. The body network modifies the saturation output conductance of the device via the body-source transconductance, resulting in a pole/zero pair being introduced in the conductance-frequency response. We show that neglecting the presence of body charge in the saturation region can often yield inaccurate values for the body capacitances, which in turn can adversely affect the modelling of the output conductance above the pole/zero frequency. We conclude that the underlying cause of this problem is the use of separate models for the intrinsic and extrinsic capacitances. Finally, we present a simple saturation body charge model which can greatly improve small-signal simulation accuracy for floating body devices.

  11. 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.

  12. 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

  13. 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

  14. Sibling competition stabilizes signalling resolution models of parent-offspring conflict.

    PubMed Central

    Rodríguez-Gironés, M A

    1999-01-01

    Young of altricial birds use conspicuous displays to solicit food from their parents. There is experimental evidence that the intensity of these displays is correlated with the level of food deprivation of young, and that parents respond to increased levels of solicitation by increasing the rate of food delivery to the nest. Game-theoretical models based on the handicap principle show that, when solicitation is costly, there is a signalling equilibrium at which there is a one-to-one correspondence between the condition of the young and the intensity of their display. Parents use this information to adjust their levels of investment on the current offspring. However, the models also have a non-signalling equilibrium, and computer simulations show that only the non-signalling equilibrium is stable. Here I show that when direct sibling competition is introduced into the model, in such a way that parents have control on the amount of food provided to the nest, but not on the way the food is allocated among siblings, the non-signalling equilibrium disappears and the signalling equilibrium becomes stable. PMID:10643084

  15. 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.

  16. Models of response inhibition in the stop-signal and stop-change paradigms.

    PubMed

    Verbruggen, Frederick; Logan, Gordon D

    2009-05-01

    The stop-signal paradigm is very useful for the study of response inhibition. Stop-signal performance is typically described as a race between a go process, triggered by a go stimulus, and a stop process, triggered by the stop signal. Response inhibition depends on the relative finishing time of these two processes. Numerous studies have shown that the independent horse-race model of Logan and Cowan [Logan, G.D., Cowan, W.B., 1984. On the ability to inhibit thought and action: a theory of an act of control. Psychological Review 91, 295-327] accounts for the data very well. In the present article, we review the independent horse-race model and related models, such as the interactive horse-race model [Boucher, L., Palmeri, T.J., Logan, G.D., Schall, J.D., 2007. Inhibitory control in mind and brain: an interactive race model of countermanding saccades. Psychological Review 114, 376-397]. We present evidence that favors the independent horse-race model but also some evidence that challenges the model. We end with a discussion of recent models that elaborate the role of a stop process in inhibiting a response.

  17. An agent-based model of signal transduction in bacterial chemotaxis.

    PubMed

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

    2010-05-13

    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.

  18. A Novel Richardson-Lucy Model with Dictionary Basis and Spatial Regularization for Isolating Isotropic Signals

    PubMed Central

    Feng, Yuanjing; Wu, Ye; Zeng, Qingrun; Zhang, Jun; He, Jianzhong; Zhuge, Qichuan

    2017-01-01

    Diffusion-weighted magnetic resonance imaging is a non-invasive imaging method that has been increasingly used in neuroscience imaging over the last decade. Partial volume effects (PVEs) exist in sampling signal for many physical and actual reasons, which lead to inaccurate fiber imaging. We overcome the influence of PVEs by separating isotropic signal from diffusion-weighted signal, which can provide more accurate estimation of fiber orientations. In this work, we use a novel response function (RF) and the correspondent fiber orientation distribution function (fODF) to construct different signal models, in which case the fODF is represented using dictionary basis function. We then put forward a new index Piso, which is a part of fODF to quantify white and gray matter. The classic Richardson-Lucy (RL) model is usually used in the field of digital image processing to solve the problem of spherical deconvolution caused by highly ill-posed least-squares algorithm. In this case, we propose an innovative model integrating RL model with spatial regularization to settle the suggested double-models, which improve noise resistance and accuracy of imaging. Experimental results of simulated and real data show that the proposal method, which we call iRL, can robustly reconstruct a more accurate fODF and the quantitative index Piso performs better than fractional anisotropy and general fractional anisotropy. PMID:28081561

  19. 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.

  20. 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

  1. PATHLOGIC-S: A Scalable Boolean Framework for Modelling Cellular Signalling

    PubMed Central

    Fearnley, Liam G.; Nielsen, Lars K.

    2012-01-01

    Curated databases of signal transduction have grown to describe several thousand reactions, and efficient use of these data requires the development of modelling tools to elucidate and explore system properties. We present PATHLOGIC-S, a Boolean specification for a signalling model, with its associated GPL-licensed implementation using integer programming techniques. The PATHLOGIC-S specification has been designed to function on current desktop workstations, and is capable of providing analyses on some of the largest currently available datasets through use of Boolean modelling techniques to generate predictions of stable and semi-stable network states from data in community file formats. PATHLOGIC-S also addresses major problems associated with the presence and modelling of inhibition in Boolean systems, and reduces logical incoherence due to common inhibitory mechanisms in signalling systems. We apply this approach to signal transduction networks including Reactome and two pathways from the Panther Pathways database, and present the results of computations on each along with a discussion of execution time. A software implementation of the framework and model is freely available under a GPL license. PMID:22879903

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

    PubMed Central

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

    2011-01-01

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

  3. 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

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

    NASA Astrophysics Data System (ADS)

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

    2008-03-01

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

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

    PubMed Central

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

    2016-01-01

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

  6. 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.

  7. Analysis of Signal Propagation in an Elastic-Tube Flow Model

    NASA Astrophysics Data System (ADS)

    Waggy, Scott; Akman, Ozgur; Biringen, Sedat

    2009-11-01

    We combine linear and nonlinear signal analysis techniques to investigate the transmission of pressure signals along a one-dimensional model of fluid flow in an elastic tube. We derive a simple measure for the robustness of a simulated vessel against in vivo fluctuations in the pressure, based on quantifying the degree of synchronization between proximal and distal pressure pulses. The practical use of this measure will be in its application to simulated pulses generated in response to a stochastic forcing term mimicking biological variations of root pressure in arterial blood flow. Using spectral analysis methods based on synchronization theory, we introduce a novel nonlinear index for measuring the robustness of the model against fluctuations in the forcing signal, based on a general scheme for deriving low-dimensional measures of (biological) performance from higher-dimensional systems of equations.

  8. 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.

  9. 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.

  10. A system-based approach to modeling the ultrasound signal backscattered by red blood cells

    PubMed Central

    Fontaine, I; Bertrand, M; Cloutier, G

    1999-01-01

    A system-based model is proposed to describe and simulate the ultrasound signal backscattered by red blood cells (RBCs). The model is that of a space-invariant linear system that takes into consideration important biological tissue stochastic scattering properties as well as the characteristics of the ultrasound system. The formation of the ultrasound signal is described by a convolution integral involving a transducer transfer function, a scatterer prototype function, and a function representing the spatial arrangement of the scatterers. The RBCs are modeled as nonaggregating spherical scatterers, and the spatial distribution of the RBCs is determined using the Percus-Yevick packing factor. Computer simulations of the model are used to study the power backscattered by RBCs as a function of the hematocrit, the volume of the scatterers, and the frequency of the incident wave (2-500 MHz). Good agreement is obtained between the simulations and theoretical and experimental data for both Rayleigh and non-Rayleigh scattering conditions. In addition to these results, the renewal process theory is proposed to model the spatial arrangement of the scatterers. The study demonstrates that the system-based model is capable of accurately predicting important characteristics of the ultrasound signal backscattered by blood. The model is simple and flexible, and it appears to be superior to previous one- and two-dimensional simulation studies. PMID:10545342

  11. Modeling of the Expected Lidar Return Signal for Wake Vortex Experiments

    NASA Technical Reports Server (NTRS)

    Kruschwitz, Craig A.

    1995-01-01

    A computer program that models the Lidar return signal for Wake Vortex experiments conducted by the Aerosol Research Branch was written. The specifications of the program and basic theory behind the calculations are briefly discussed. Results of the research and possible future improvements on it are also discussed.

  12. Evaluation of laser Doppler flowmetry system with fast signal processing using an autoregressive process model

    NASA Astrophysics Data System (ADS)

    Elter, Peter; Stork, Wilhelm; Mueller-Glaser, Klaus-Dieter; Lutter, Norbert O.

    1999-05-01

    This report describes the evaluation of a noninvasive laser Doppler system comprising a sensor, a digital signal processor (DSP) unit and a visualizing PC for continuous blood flow measurements. The first weighted moment of the power spectrum density of the laser Doppler sensor signal is a linear measure for blood flow. In order to estimate the power spectrum densities in real time, a first order autoregressive process model was developed. Due to this very fast signal processing, the system allows measurements both in microcirculation and of higher blood flows in larger vessels with a signal bandwidth of up to 200 kHz, e.g. in superficial arteries. Since the analytical dependency of blood flow and first spectral moment is only valid for tissue perfusion, Monte Carlo simulations were performed to evaluate this dependency also for higher blood flow velocities in larger vessels. A multilayered, semi- infinite tissue model essentially comprising epidermis, dermis and a blood vessel with a parabolic profile of constant blood flow was used varying different parameter like vessel diameter and skin thickness. Furthermore, model measurements were performed using a Delrine slab with a drilling through which constant flow of whole blood was provided. Both the Monte Carlo simulations and model measurements prove very high linear correlations between the calculated spectral moments and flow velocities.

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

    PubMed Central

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

    2010-01-01

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

  14. 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.

  15. Notch Signaling and Schwann Cell Transformation: Development of a Model System and Application to Human MPNSTs

    DTIC Science & Technology

    2006-03-01

    MPNSTs PRINCIPAL INVESTIGATOR: Tom R. Kadesch, Ph.D...Signaling and Schwann Cell Tranformation: Development of a Model System and Application to Human MPNSTs 6. AUTHOR(S) Tom R. Kadesch, Ph.D. W81XWH-04-1...the malignant transformation of neurofibromas to MPNSTs in patients with NF1. Our previous work has shown that constitutive expression of Notch can

  16. Mono-W dark matter signals at the LHC: simplified model analysis

    SciTech Connect

    Bell, Nicole F.; Cai, Yi; Leane, Rebecca K. E-mail: yi.cai@unimelb.edu.au

    2016-01-01

    We study mono-W signals of dark matter (DM) production at the LHC, in the context of gauge invariant renormalizable models. We analyze two simplified models, one involving an s-channel Z' mediator and the other a t-channel colored scalar mediator, and consider examples in which the DM-quark couplings are either isospin conserving or isospin violating after electroweak symmetry breaking. While previous work on mono-W signals have focused on isospin violating EFTs, obtaining very strong limits, we find that isospin violating effects are small once such physics is embedded into a gauge invariant simplified model. We thus find that the 8 TeV mono-W results are much less constraining than those arising from mono-jet searches. Considering both the leptonic (mono-lepton) and hadronic (mono fat jet) decays of the W, we determine the 14 TeV LHC reach of the mono-W searches with 3000 fb{sup −1} of data. While a mono-W signal would provide an important complement to a mono-jet discovery channel, existing constraints on these models imply it will be a challenging signal to observe at the 14 TeV LHC.

  17. 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

  18. Modeling of signaling crosstalk-mediated drug resistance and its implications on drug combination

    PubMed Central

    Sun, Xiaoqiang; Bao, Jiguang; You, Zhuhong; Chen, Xing; Cui, Jun

    2016-01-01

    The efficacy of pharmacological perturbation to the signaling transduction network depends on the network topology. However, whether and how signaling dynamics mediated by crosstalk contributes to the drug resistance are not fully understood and remain to be systematically explored. In this study, motivated by a realistic signaling network linked by crosstalk between EGF/EGFR/Ras/MEK/ERK pathway and HGF/HGFR/PI3K/AKT pathway, we develop kinetic models for several small networks with typical crosstalk modules to investigate the role of the architecture of crosstalk in inducing drug resistance. Our results demonstrate that crosstalk inhibition diminishes the response of signaling output to the external stimuli. Moreover, we show that signaling crosstalk affects the relative sensitivity of drugs, and some types of crosstalk modules that could yield resistance to the targeted drugs were identified. Furthermore, we quantitatively evaluate the relative efficacy and synergism of drug combinations. For the modules that are resistant to the targeted drug, we identify drug targets that can not only increase the relative drug efficacy but also act synergistically. In addition, we analyze the role of the strength of crosstalk in switching a module between drug-sensitive and drug-resistant. Our study provides mechanistic insights into the signaling crosstalk-mediated mechanisms of drug resistance and provides implications for the design of synergistic drug combinations to reduce drug resistance. PMID:27590512

  19. CHIRP-Like Signals: Estimation, Detection and Processing A Sequential Model-Based Approach

    SciTech Connect

    Candy, J. V.

    2016-08-04

    Chirp signals have evolved primarily from radar/sonar signal processing applications specifically attempting to estimate the location of a target in surveillance/tracking volume. The chirp, which is essentially a sinusoidal signal whose phase changes instantaneously at each time sample, has an interesting property in that its correlation approximates an impulse function. It is well-known that a matched-filter detector in radar/sonar estimates the target range by cross-correlating a replicant of the transmitted chirp with the measurement data reflected from the target back to the radar/sonar receiver yielding a maximum peak corresponding to the echo time and therefore enabling the desired range estimate. In this application, we perform the same operation as a radar or sonar system, that is, we transmit a “chirp-like pulse” into the target medium and attempt to first detect its presence and second estimate its location or range. Our problem is complicated by the presence of disturbance signals from surrounding broadcast stations as well as extraneous sources of interference in our frequency bands and of course the ever present random noise from instrumentation. First, we discuss the chirp signal itself and illustrate its inherent properties and then develop a model-based processing scheme enabling both the detection and estimation of the signal from noisy measurement data.

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

    PubMed

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

    2015-08-01

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

  1. Testing Signal-Detection Models of Yes/No and Two-Alternative Forced-Choice Recognition Memory

    ERIC Educational Resources Information Center

    Jang, Yoonhee; Wixted, John T.; Huber, David E.

    2009-01-01

    The current study compared 3 models of recognition memory in their ability to generalize across yes/no and 2-alternative forced-choice (2AFC) testing. The unequal-variance signal-detection model assumes a continuous memory strength process. The dual-process signal-detection model adds a thresholdlike recollection process to a continuous…

  2. 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.

  3. 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

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

    PubMed

    Engemann, Denis A; Gramfort, Alexandre

    2015-03-01

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

  5. 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.

  6. Operator Alertness/Workload Assessment Using Stochastic Model-Based Analysis of Myoelectric Signals.

    DTIC Science & Technology

    1985-11-01

    a three-year program -. ]° j of research and development directed toward the analysis and evaluation of myoelectric , signals (MES) as indicators of...summarizes the activities in the second phase of a three-year program of research and development directed toward the analysis and evaluation of...are: (1) the model development (2) the system implementation and (3) preliminary experimental evaluation of ARIMA model-based analysis of myoelectric

  7. Notch Signaling and Schwann Cell Transformation: Development of a Model System and Application to Human MPNSTs

    DTIC Science & Technology

    2008-09-01

    TITLE: Notch Signaling and Schwann Cell Transformation: Development of a Model System and Application to Human MPNSTs PRINCIPAL INVESTIGATOR...Schwann cell transformation: Development of a model system and 5a. CONTRACT NUMBER application to human MPNSTs . 5b. GRANT NUMBER W81XWH-04-1-0209...of neurofibromas to MPNSTs in patients with NF1. Our previous work has shown that constitutive expression of Notch can transform rat Schwann cells

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  10. On the usage of linear regression models to reconstruct limb kinematics from low frequency EEG signals.

    PubMed

    Antelis, Javier M; Montesano, Luis; Ramos-Murguialday, Ander; Birbaumer, Niels; Minguez, Javier

    2013-01-01

    Several works have reported on the reconstruction of 2D/3D limb kinematics from low-frequency EEG signals using linear regression models based on positive correlation values between the recorded and the reconstructed trajectories. This paper describes the mathematical properties of the linear model and the correlation evaluation metric that may lead to a misinterpretation of the results of this type of decoders. Firstly, the use of a linear regression model to adjust the two temporal signals (EEG and velocity profiles) implies that the relevant component of the signal used for decoding (EEG) has to be in the same frequency range as the signal to be decoded (velocity profiles). Secondly, the use of a correlation to evaluate the fitting of two trajectories could lead to overly-optimistic results as this metric is invariant to scale. Also, the correlation has a non-linear nature that leads to higher values for sinus/cosinus-like signals at low frequencies. Analysis of these properties on the reconstruction results was carried out through an experiment performed in line with previous studies, where healthy participants executed predefined reaching movements of the hand in 3D space. While the correlations of limb velocity profiles reconstructed from low-frequency EEG were comparable to studies in this domain, a systematic statistical analysis revealed that these results were not above the chance level. The empirical chance level was estimated using random assignments of recorded velocity profiles and EEG signals, as well as combinations of randomly generated synthetic EEG with recorded velocity profiles and recorded EEG with randomly generated synthetic velocity profiles. The analysis shows that the positive correlation results in this experiment cannot be used as an indicator of successful trajectory reconstruction based on a neural correlate. Several directions are herein discussed to address the misinterpretation of results as well as the implications on previous

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

    PubMed Central

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Ullah, Ghanim

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

  13. 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

  14. 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.

  15. 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.

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

    PubMed

    Devinck, Frédéric; Knoblauch, Kenneth

    2012-03-21

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

  17. 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

  18. 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.

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

    PubMed

    Sun, Guanghao; Matsui, Takemi

    2015-01-01

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

  20. 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.

  1. Higgs couplings and new signals from Flavon-Higgs mixing effects within multi-scalar models

    NASA Astrophysics Data System (ADS)

    Diaz-Cruz, J. Lorenzo; Saldaña-Salazar, Ulises J.

    2016-12-01

    Testing the properties of the Higgs particle discovered at the LHC and searching for new physics signals, are some of the most important tasks of Particle Physics today. Current measurements of the Higgs couplings to fermions and gauge bosons, seem consistent with the Standard Model, and when taken as a function of the particle mass, should lay on a single line. However, in models with an extended Higgs sector the diagonal Higgs couplings to up-quarks, down-quarks and charged leptons, could lay on different lines, while non-diagonal flavor-violating Higgs couplings could appear too. We describe these possibilities within the context of multi-Higgs doublet models that employ the Froggatt-Nielsen (FN) mechanism to generate the Yukawa hierarchies. Furthermore, one of the doublets can be chosen to be of the inert type, which provides a viable dark matter candidate. The mixing of the Higgs doublets with the flavon field, can provide plenty of interesting signals, including: i) small corrections to the couplings of the SM-like Higgs, ii) exotic signals from the flavon fields, iii) new signatures from the heavy Higgs bosons. These aspects are studied within a specific model with 3 + 1 Higgs doublets and a singlet FN field. Constraints on the model are derived from the study of K and D mixing and the Higgs search at the LHC. For last, the implications from the latter aforementioned constraints to the FCNC top decay t → ch are presented too.

  2. 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.

  3. γ-Ray emission signals in the massive graviton mediated dark matter model

    NASA Astrophysics Data System (ADS)

    Zhang, Cun; Cui, Ming-Yang; Feng, Lei; Fan, Yi-Zhong; Ren, Zhong-Zhou

    2017-03-01

    Dark matter may interact with Standard Model (SM) particle through the exchange of a massive spin-2 graviton producing signals that can be detected. In this work we examine the γ-ray emission signals, including the line emission and the continuous spectrum component in such a massive graviton-mediated dark matter model. The constraints of LHC data, dark matter relic density as well as the dark matter indirect detection data have been applied to narrow down the parameter space. We focus on the vector dark matter model which could produce detectable γ-ray line signal. It is found that the γ-ray line data is effective on constraining the model parameters and the ongoing and upcoming space or ground-based γ-ray experiments can constrain the model further. As for the continuous γ-ray emission, the total effective annihilation cross section is ∼10-26 cm3s-1 except at the region where dark matter mass is around the graviton mass or half of it, which is consistent with current observational data and will be reliably probed by the upcoming CTA.

  4. 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.

  5. A study of the spectral broadening of simulated Doppler signals using FFT and AR modelling.

    PubMed

    Keeton, P I; Schlindwein, F S; Evans, D H

    1997-01-01

    Doppler ultrasound is used clinically to detect stenosis in the carotid artery. The presence of stenosis may be identified by disturbed flow patterns distal to the stenosis that cause spectral broadening in the spectrum of the Doppler signal around peak systole. This paper investigates the behaviour of the spectral broadening index (SBI) derived from wide-band spectra obtained using autoregressive modelling (AR), compared with the SBI based on the fast-Fourier transform (FFT) spectra. Simulated Doppler signals were created using white noise and shaped filters to analyse spectra typically found around the systolic peak and to assess the magnitude and variance of AR and FFT-SBI for a range of signal-to-noise ratios. The results of the analysis show a strong correlation between the indices calculated using the FFT and AR algorithms. Despite the qualitative improvement of the AR spectra over the FFT, the estimation of SBI for short data frames is not significantly improved using AR.

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

    PubMed

    Fan, Yang; Gao, Jia-Hong

    2015-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Fan, Yang; Gao, Jia-Hong

    2015-07-01

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

  8. 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.

  9. The emotion recognition system based on autoregressive model and sequential forward feature selection of electroencephalogram signals.

    PubMed

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

    2014-07-01

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

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

    PubMed Central

    Janes, Kevin A.; Lauffenburger, Douglas A.

    2013-01-01

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

  11. 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.

  12. FGFR1-WNT-TGF-β signaling in prostate cancer mouse models recapitulates human reactive stroma

    PubMed Central

    Carstens, Julienne L.; Shahi, Payam; Van Tsang, Susan; Smith, Billie; Creighton, Chad J.; Zhang, Yiqun; Seamans, Amber; Seethammagari, Mamatha; Vedula, Indira; Levitt, Jonathan M.; Ittmann, Michael M.; Rowley, David R.; Spencer, David M.

    2014-01-01

    The reactive stroma surrounding tumor lesions performs critical roles ranging from supporting tumor cell proliferation to inducing tumorigenesis and metastasis. Therefore, it is critical to understand the cellular components and signaling control mechanisms that underlay the etiology of reactive stroma. Previous studies have individually implicated fibroblast growth factor receptor 1 (FGFR1) and canonical WNT/β-catenin signaling in prostate cancer progression and the initiation and maintenance of a reactive stroma; however, both pathways are frequently found co-activated in cancer tissue. Using autochthonous transgenic mouse models for inducible FGFR1 (JOCK1) and prostate-specific and ubiquitously expressed inducible β-catenin (Pro-Cat and Ubi-Cat, respectively) and bigenic crosses between these lines (Pro-Cat × JOCK1 and Ubi-Cat × JOCK1), we describe WNT-induced synergistic acceleration of FGFR1-driven adenocarcinoma, associated with a pronounced fibroblastic reactive stroma activation surrounding prostatic intraepithelial neoplasia (mPIN) lesions found both in situ and reconstitution assays. Both mouse and human reactive stroma exhibited increased transforming growth factor-beta (TGF-β) signaling adjacent to pathologic lesions likely contributing to invasion. Furthermore, elevated stromal TGF-β signaling was associated with higher Gleason scores in archived human biopsies, mirroring murine patterns. Our findings establish the importance of the FGFR1-WNT-TGF-β signaling axes as driving forces behind reactive stroma in aggressive prostate adenocarcinomas, deepening their relevance as therapeutic targets. PMID:24305876

  13. 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.

  14. 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

  15. Compartment models of the diffusion MR signal in brain white matter: a taxonomy and comparison.

    PubMed

    Panagiotaki, Eleftheria; Schneider, Torben; Siow, Bernard; Hall, Matt G; Lythgoe, Mark F; Alexander, Daniel C

    2012-02-01

    This paper aims to identify the minimum requirements for an accurate model of the diffusion MR signal in white matter of the brain. We construct a taxonomy of multi-compartment models of white matter from combinations of simple models for the intra- and the extra-axonal spaces. We devise a new diffusion MRI protocol that provides measurements with a wide range of imaging parameters for diffusion sensitization both parallel and perpendicular to white matter fibres. We use the protocol to acquire data from two fixed rat brains, which allows us to fit, study and compare the different models. The study examines a total of 47 analytic models, including several well-used models from the literature, which we place within the taxonomy. The results show that models that incorporate intra-axonal restriction, such as ball and stick or CHARMED, generally explain the data better than those that do not, such as the DT or the biexponential models. However, three-compartment models which account for restriction parallel to the axons and incorporate pore size explain the measurements most accurately. The best fit comes from combining a full diffusion tensor (DT) model of the extra-axonal space with a cylindrical intra-axonal component of single radius and a third spherical compartment of non-zero radius. We also measure the stability of the non-zero radius intra-axonal models and find that single radius intra-axonal models are more stable than gamma distributed radii models with similar fitting performance.

  16. 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.

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

    NASA Technical Reports Server (NTRS)

    Robock, Alan; Liu, Yuhe

    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 volcanoes for scenario B, the natural variability is suppressed and the volcanic signals are extracted. Significant global mean 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 deg S - 45 deg N in the year after the eruptions. In the second year, cooling is still seen from 30 deg S to 30 deg 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 by 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-atitude volcanic eruptions can trigger El Nino-Southern Oscillation (ENSO) events in this model.

  18. The Volcanic Signal in Goddard Institute for Space Studies Three-Dimensional Model Simulations.

    NASA Astrophysics Data System (ADS)

    Robock, Alan; Liu, Yuhe

    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 volcanoes for scenario B, the natural variability is suppressed and the volcanic signals am extracted.Significant global mean 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°S45°N in the year after the eruptions. In the second year, cooling is still seen from 30°S to 30°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 by attempting to isolate them using real data. The results suggest that volcanoes can enhance the drought in the Sahel. No evidence was found that atmospheric aerosols from the low-latitude volcanic eruptions can trigger ENSO events in this model.

  19. 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

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

    PubMed

    Tortolina, Lorenzo; Duffy, David J; Maffei, Massimo; Castagnino, Nicoletta; Carmody, Aimée M; Kolch, Walter; Kholodenko, Boris N; De Ambrosi, Cristina; Barla, Annalisa; Biganzoli, Elia M; Nencioni, Alessio; Patrone, Franco; Ballestrero, Alberto; Zoppoli, Gabriele; Verri, Alessandro; Parodi, Silvio

    2015-03-10

    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.

  1. 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

  2. The Role of TGFβ Signaling in Squamous Cell Cancer: Lessons from Mouse Models

    PubMed Central

    Glick, Adam B.

    2012-01-01

    TGFβ1 is a member of a large growth factor family including activins/inhibins and bone morphogenic proteins (BMPs) that have a potent growth regulatory and immunomodulatory functions in normal skin homeostasis, regulation of epidermal stem cells, extracellular matrix production, angiogenesis, and inflammation. TGFβ signaling is tightly regulated in normal tissues and becomes deregulated during cancer development in cutaneous SCC and many other solid tumors. Because of these diverse biological processes regulated by TGFβ1, this cytokine and its signaling pathway appear to function at multiple points during carcinogenesis with distinct effects. The mouse skin carcinogenesis model has been a useful tool to dissect the function of this pathway in cancer pathogenesis, with transgenic and null mice as well as small molecule inhibitors to alter the function of the TGFβ1 pathway and assess the effects on cancer development. This paper will review data on changes in TGFβ1 signaling in human SCC primarily HNSCC and cutaneous SCC and different mouse models that have been generated to investigate the relevance of these changes to cancer. A better understanding of the mechanisms underlying the duality of TGFβ1 action in carcinogenesis will inform potential use of this signaling pathway for targeted therapies. PMID:23326666

  3. Oncogenic Kit signaling and therapeutic intervention in a mouse model of gastrointestinal stromal tumor

    PubMed Central

    Rossi, Ferdinand; Ehlers, Imke; Agosti, Valter; Socci, Nicholas D.; Viale, Agnes; Sommer, Gunhild; Yozgat, Yasemin; Manova, Katia; Antonescu, Cristina R.; Besmer, Peter

    2006-01-01

    Kit receptor-activating mutations are critical in the pathogenesis of gastrointestinal stromal tumors (GIST). We investigated mechanisms of oncogenic Kit signaling and the consequences of therapeutic intervention in a mouse model of human GIST. Treatment of GIST mice with imatinib decreased cell proliferation and increased apoptosis in the tumor. Analysis of tumor tissue from imatinib-treated mice showed diminished phosphatidylinositol 3-kinase (PI3-kinase) and mammalian target of rapamycin (mTOR) signaling suggesting that oncogenic Kit signaling critically contributes to the translational response in GIST. Treatment with RAD001 (everolimus), an mTOR inhibitor, diminished the translational response and cell proliferation in tumor lesions, pointing to mTOR inhibition as a therapeutic approach for imatinib-resistant GIST. Analysis of RNA expression profiles in GIST lesions with and without imatinib treatment showed changes in expression of IFN-inducible genes and cell cycle regulators. These results convincingly show that KitV558Δ/+ mice represent a unique faithful mouse model of human familial GIST, and they demonstrate the utility of these mice for preclinical investigations and to elucidate oncogenic signaling mechanisms by using genetic approaches and targeted pharmacological intervention. PMID:16908864

  4. Modeling Local X-ROS and Calcium Signaling in the Heart.

    PubMed

    Limbu, Sarita; Hoang-Trong, Tuan M; Prosser, Benjamin L; Lederer, W Jonathan; Jafri, M Saleet

    2015-11-17

    Stretching single ventricular cardiac myocytes has been shown experimentally to activate transmembrane nicotinamide adenine dinucleotide phosphate oxidase type 2 to produce reactive oxygen species (ROS) and increase the Ca2+ spark rate in a process called X-ROS signaling. The increase in Ca2+ spark rate is thought to be due to an increase in ryanodine receptor type 2 (RyR2) open probability by direct oxidation of the RyR2 protein complex. In this article, a computational model is used to examine the regulation of ROS and calcium homeostasis by local, subcellular X-ROS signaling and its role in cardiac excitation-contraction coupling. To this end, a four-state RyR2 model was developed that includes an X-ROS-dependent RyR2 mode switch. When activated, [Ca2+]i-sensitive RyR2 open probability increases, and the Ca2+ spark rate changes in a manner consistent with experimental observations. This, to our knowledge, new model is used to study the transient effects of diastolic stretching and subsequent ROS production on RyR2 open probability, Ca2+ sparks, and the myoplasmic calcium concentration ([Ca2+]i) during excitation-contraction coupling. The model yields several predictions: 1) [ROS] is produced locally near the RyR2 complex during X-ROS signaling and increases by an order of magnitude more than the global ROS signal during myocyte stretching; 2) X-ROS activation just before the action potential, corresponding to ventricular filling during diastole, increases the magnitude of the Ca2+ transient; 3) during prolonged stretching, the X-ROS-induced increase in Ca2+ spark rate is transient, so that long-sustained stretching does not significantly increase sarcoplasmic reticulum Ca2+ leak; and 4) when the chemical reducing capacity of the cell is decreased, activation of X-ROS signaling increases sarcoplasmic reticulum Ca2+ leak and contributes to global oxidative stress, thereby increases the possibility of arrhythmia. The model provides quantitative information not

  5. 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.

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

    PubMed

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

    2015-11-01

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

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

    PubMed Central

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

    2015-01-01

    Polyglutamine diseases are a class of dominantly inherited neurodegenerative disorders for which there is no effective treatment. Here we provide evidence that activation of serotonergic signalling is beneficial in animal models of Machado-Joseph disease. We identified citalopram, a selective serotonin reuptake inhibitor, in a small molecule screen of FDA-approved drugs that rescued neuronal dysfunction and reduced aggregation using a Caenorhabditis elegans model of mutant ataxin 3-induced neurotoxicity. MOD-5, the C. elegans orthologue of the serotonin transporter and cellular target of citalopram, and the serotonin receptors SER-1 and SER-4 were strong genetic modifiers of ataxin 3 neurotoxicity and necessary for therapeutic efficacy. Moreover, chronic treatment of CMVMJD135 mice with citalopram significantly reduced ataxin 3 neuronal inclusions and astrogliosis, rescued diminished body weight and strikingly ameliorated motor symptoms. These results suggest that small molecule modulation of serotonergic signalling represents a promising therapeutic target for Machado-Joseph disease. PMID:26373603

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

    SciTech Connect

    Davis, William B.

    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 processing has not yet been developed. This disclosure describes a signal processing model and method useful for diagnosing the veracity of spot welds between two sheets of the same thickness from ultrasound signals Standard systems theory describes a signal as a convolution of a transducer function, h(t), and an impulse train (beta(t), tau(t)) [1] (see Eq. (1) attached). With a Gaussian wavelet as a transducer function, this model describes the signal from an ultrasound probe quite well, and the literature provides many methods for "deconvolution," for recovery of the impulse train from the signal [see e.g., 2-3]. What is novel about the technique disclosed is the model that describes the impulse train as a function of reflectivity, the share of energy incident on the interface that is reflected, and that allows the recovery of its estimated value. The reflectivity estimate provides an ideal indicator of weld veracity, compressing each signal into a single value between 0 and 1, which can then be displayed as a 2d greyscale or colormap of the weld. The model describing the system is attached as Eqs. (2). These equations account for the energy in the probe-side and opposite sheets. In each period, this energy is a sum of that reflected from the same sheet plus that transmitted from the opposite (dampened by material attenuation at rate a). This model is consistent with physical first principles (in particular the First and Second Laws of Thermodynamics) and has been verified

  9. Notch Signaling and Schwann Cell Transformation: Development of a Model System and Application to Human MPNSTs

    DTIC Science & Technology

    2007-03-01

    Transformation: Development of a Model System and Application to Human MPNSTs PRINCIPAL INVESTIGATOR: Tom Kadesch, Ph.D... MPNSTs 5b. GRANT NUMBER W81XWH-04-1-0209 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Tom Kadesch, Ph.D. 5d. PROJECT NUMBER 5e. TASK...potential role of Notch signaling in the malignant transformation of neurofibromas to MPNSTs in patients with NF1. Our previous work has shown that

  10. Notch Signaling and Schwann Cell Transformation: Development of a Model System and Application to Human MPNSTs

    DTIC Science & Technology

    2008-03-01

    Transformation: Development of a Model System and Application to Human MPNSTs PRINCIPAL INVESTIGATOR: Tom Kadesch, Ph.D...and Application to Human MPNSTs 5b. GRANT NUMBER W81XWH-04-1-0209 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Tom Kadesch, Ph.D. 5d. PROJECT...grant addresses the potential role of Notch signaling in the malignant transformation of neurofibromas to MPNSTs in patients with NF1. Our previous

  11. 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.

  12. Signal modeling of charge sharing effect in simple pixelated CdZnTe detector

    NASA Astrophysics Data System (ADS)

    Kim, Jae Cheon; Kaye, William R.; He, Zhong

    2014-05-01

    In order to study the energy resolution degradation in 3D position-sensitive pixelated CdZnTe (CZT) detectors, a detailed detector system modeling package has been developed and used to analyze the detector performance. A 20 × 20 × 15 mm3 CZT crystal with an 11 × 11 simple-pixel anode array and a 1.72 mm pixel pitch was modeled. The VAS UM/TAT4 Application Specific Integrated Circuitry (ASIC) was used for signal read-out. Components of the simulation package include gamma-ray interactions with the CZT crystal, charge induction, electronic noise, pulse shaping, and ASIC triggering procedures. The charge induction model considers charge drift, trapping, diffusion, and sharing between pixels. This system model is used to determine the effects of electron cloud sharing, weighting potential non-uniformity, and weighting potential cross-talk which produce non-uniform signal responses for different gamma-ray interaction positions and ultimately degrade energy resolution. The effect of the decreased weighting potential underneath the gap between pixels on the total pulse amplitude of events has been studied. The transient signals induced by electron clouds collected near the gap between pixels may generate false signals, and the measured amplitude can be even greater than the photopeak. As the number of pixels that collect charge increases, the probability of side-neighbor events due to charge sharing significantly increases. If side-neighbor events are not corrected appropriately, the energy resolution of pixelated CZT detectors in multiple-pixel events degrades rapidly.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  14. Modeling Cellular Noise Underlying Heterogeneous Cell Responses in the Epidermal Growth Factor Signaling Pathway

    PubMed Central

    Iwamoto, Kazunari; Shindo, Yuki; Takahashi, Koichi

    2016-01-01

    Cellular heterogeneity, which plays an essential role in biological phenomena, such as drug resistance and migration, is considered to arise from intrinsic (i.e., reaction kinetics) and extrinsic (i.e., protein variability) noise in the cell. However, the mechanistic effects of these types of noise to determine the heterogeneity of signal responses have not been elucidated. Here, we report that the output of epidermal growth factor (EGF) signaling activity is modulated by cellular noise, particularly by extrinsic noise of particular signaling components in the pathway. We developed a mathematical model of the EGF signaling pathway incorporating regulation between extracellular signal-regulated kinase (ERK) and nuclear pore complex (NPC), which is necessary for switch-like activation of the nuclear ERK response. As the threshold of switch-like behavior is more sensitive to perturbations than the graded response, the effect of biological noise is potentially critical for cell fate decision. Our simulation analysis indicated that extrinsic noise, but not intrinsic noise, contributes to cell-to-cell heterogeneity of nuclear ERK. In addition, we accurately estimated variations in abundance of the signal proteins between individual cells by direct comparison of experimental data with simulation results using Apparent Measurement Error (AME). AME was constant regardless of whether the protein levels varied in a correlated manner, while covariation among proteins influenced cell-to-cell heterogeneity of nuclear ERK, suppressing the variation. Simulations using the estimated protein abundances showed that each protein species has different effects on cell-to-cell variation in the nuclear ERK response. In particular, variability of EGF receptor, Ras, Raf, and MEK strongly influenced cellular heterogeneity, while others did not. Overall, our results indicated that cellular heterogeneity in response to EGF is strongly driven by extrinsic noise, and that such heterogeneity

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

    PubMed

    Parker, Andrew J

    2013-01-01

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

  16. Delay modeling of high-speed distributed interconnect for the signal integrity prediction

    NASA Astrophysics Data System (ADS)

    Raveloa, B.

    2012-02-01

    A relevant modeling-method of distributed interconnect line for the high-speed signal integrity (SI) application is introduced in this paper. By using the microwave and transmission line (TL) theory, the interconnect lines are assumed as its distributed RLC-model. Then, based on the transfer matrix analysis, the second-order global transfer function of the interconnect network comprised of the TL driven by voltage source including its internal resistance and the impedance load is expressed. Thus, mathematical analysis enabling the physical SI-parameters' extraction was established by using the transient response of the loaded line. To verify the relevance of the developed model, RC- and RLC-lines excited by square-wavepulse with 10-Gbits/s-rate were investigated. So, comparisons with SPICE-computations were performed. As results, transient responses perfectly well correlated to the reference SPICE-models were evidenced. As application of the introduced model, evaluations of rise-/fall-times, propagation delays, signal attenuations and even the settling times were realized for different values of TL-parameters. Compared to other methods, the computation execution time and data memory consumed by the program implementing the proposed delay modeling-method algorithm are much better.

  17. 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).

  18. APG: an Active Protein-Gene network model to quantify regulatory signals in complex biological systems.

    PubMed

    Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

    2013-01-01

    Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Schoentgen, Jean

    2003-01-01

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

  1. 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.

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

    PubMed

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

    2009-01-01

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

  3. 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

  4. Effects of Shen'an granules on Wnt signaling pathway in mouse models of diabetic nephropathy

    PubMed Central

    Zou, Xin-Rong; Wang, Xiao-Qin; Hu, Ying-Lin; Zhou, Hui-Lan

    2016-01-01

    The effect of Shen'an granules on the Wnt signaling pathway in renal tissues of mouse models of streptozotocin (STZ)-induced diabetic nephropathy was investigated in the present study. A total of 62 BALB/c mice were randomly divided into the normal control (A group), model (B group), losartan (C group), low-dose Shen'an granules (D group), and high-dose Shen'an granules (E group) groups. The mouse model of diabetic nephropathy was established by a single intraperitoneal injection of STZ (150 mg/kg). The animals were treated with drugs for 8 weeks, and blood creatinine, blood urea nitrogen, triglycerides (TG), and total cholesterol (CHOL) were measured prior to and after treatment. PAS staining was performed for observation of glomerular microstructure by light microscope, and western blot analysis was performed to detect Wnt1 protein and β-catenin protein. The results indicated that the quantification of 24-h microalbuminuria, and levels of blood creatinine, urea nitrogen, TG, and CHOL were significantly lower in the high- and low-dose Shen'an granules groups than those in the model group (p<0.05). The expression levels of Wnt1 protein and β-catenin protein in the high- and low-dose Shen'an granules groups were significantly lower than those in the model group (p<0.05). In conclusion, proteinuria, renal dysfunction, and dyslipidemias are closely associated with the abnormal activation of the Wnt signaling pathway in the mouse model of diabetic nephropathy. The mechanism by which Shen'an granules regulate proteinuria, renal function, and blood lipids may be associated with inhibition of the abnormally activated Wnt signaling pathway. PMID:28105085

  5. A pedagogical walkthrough of computational modeling and simulation of Wnt signaling pathway using static causal models in MATLAB.

    PubMed

    Sinha, Shriprakash

    2016-12-01

    Simulation study in systems biology involving computational experiments dealing with Wnt signaling pathways abound in literature but often lack a pedagogical perspective that might ease the understanding of beginner students and researchers in transition, who intend to work on the modeling of the pathway. This paucity might happen due to restrictive business policies which enforce an unwanted embargo on the sharing of important scientific knowledge. A tutorial introduction to computational modeling of Wnt signaling pathway in a human colorectal cancer dataset using static Bayesian network models is provided. The walkthrough might aid biologists/informaticians in understanding the design of computational experiments that is interleaved with exposition of the Matlab code and causal models from Bayesian network toolbox. The manuscript elucidates the coding contents of the advance article by Sinha (Integr. Biol. 6:1034-1048, 2014) and takes the reader in a step-by-step process of how (a) the collection and the transformation of the available biological information from literature is done, (b) the integration of the heterogeneous data and prior biological knowledge in the network is achieved, (c) the simulation study is designed, (d) the hypothesis regarding a biological phenomena is transformed into computational framework, and (e) results and inferences drawn using d-connectivity/separability are reported. The manuscript finally ends with a programming assignment to help the readers get hands-on experience of a perturbation project. Description of Matlab files is made available under GNU GPL v3 license at the Google code project on https://code.google.com/p/static-bn-for-wnt-signaling-pathway and https: //sites.google.com/site/shriprakashsinha/shriprakashsinha/projects/static-bn-for-wnt-signaling-pathway. Latest updates can be found in the latter website.

  6. 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.

  7. Modeling and characterization of multipath in global navigation satellite system ranging signals

    NASA Astrophysics Data System (ADS)

    Weiss, Jan Peter

    The Global Positioning System (GPS) provides position, velocity, and time information to users in anywhere near the earth in real-time and regardless of weather conditions. Since the system became operational, improvements in many areas have reduced systematic errors affecting GPS measurements such that multipath, defined as any signal taking a path other than the direct, has become a significant, if not dominant, error source for many applications. This dissertation utilizes several approaches to characterize and model multipath errors in GPS measurements. Multipath errors in GPS ranging signals are characterized for several receiver systems and environments. Experimental P(Y) code multipath data are analyzed for ground stations with multipath levels ranging from minimal to severe, a C-12 turboprop, an F-18 jet, and an aircraft carrier. Comparisons between receivers utilizing single patch antennas and multi-element arrays are also made. In general, the results show significant reductions in multipath with antenna array processing, although large errors can occur even with this kind of equipment. Analysis of airborne platform multipath shows that the errors tend to be small in magnitude because the size of the aircraft limits the geometric delay of multipath signals, and high in frequency because aircraft dynamics cause rapid variations in geometric delay. A comprehensive multipath model is developed and validated. The model integrates 3D structure models, satellite ephemerides, electromagnetic ray-tracing algorithms, and detailed antenna and receiver models to predict multipath errors. Validation is performed by comparing experimental and simulated multipath via overall error statistics, per satellite time histories, and frequency content analysis. The validation environments include two urban buildings, an F-18, an aircraft carrier, and a rural area where terrain multipath dominates. The validated models are used to identify multipath sources, characterize signal

  8. Linear Models for Large Signal Control of High Power Factor AC-DC Converters

    DTIC Science & Technology

    1989-11-01

    PI controller , but some modeling aspects are left unclear. Williams [3] designs a controller using the small signal ’transfer function’ between...models for the dynamics of the outer voltage control loop. Finally Section 4 discusses the design of the outer control loop, including PI control , and...dy(t)/dt = -2y(t)/RC’ + (Vl2 k(t) - 2P)/(’ (6) This form already suffices to design controllers (e.g. PI controllers ) for large deviations in y(t

  9. 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

  10. VSV oncolytic virotherapy in the B16 model depends upon intact MyD88 signaling.

    PubMed

    Wongthida, Phonphimon; Diaz, Rosa M; Galivo, Feorillo; Kottke, Timothy; Thompson, Jill; Melcher, Alan; Vile, Richard

    2011-01-01

    We show here, for the first time to our knowledge, that the antitumor therapy of oncolytic vesicular stomatitis virus (VSV) in the B16ova model depends upon signaling through myeloid differentiation primary response gene 88 (MyD88) in host cells. VSV-mediated therapy of B16ova tumors was abolished in MyD88(-/-) mice despite generation of antigen-specific T cell responses similar to those in immune-competent mice. Mice defective in only toll-like receptor 4 (TLR4), TLR7, or interleukin 1 (IL-1) signaling retained VSV-induced therapy, suggesting that multiple, redundant pathways of innate immune activation by the virus contribute to antitumor immune reactivity. Lack of MyD88 signaling was associated with decreased expression of proinflammatory cytokines and neutrophil infiltration in response to intratumoral virus, as well as decreased infiltration of draining lymph nodes (LN) with plasmacytoid dendritic cells (pDCs) (CD11b(-)GR1(+)B220(+)) and myeloid-derived suppressor cells (CD11b(+)GR1(+)F4/80(+)). MyD88 signaling in response to VSV was also closely associated with a type I interferon (IFN) response. This inhibited virus replication within the tumor but also protected the host from viral dissemination from the tumor. Therefore, the innate immune response to oncolytic viruses can be, simultaneously, protherapeutic, antioncolytic, and systemically protective. These paradoxically conflicting roles need to be carefully considered in future strategies designed to improve the efficacy of oncolytic virotherapy.

  11. Identification of osteopontin-dependent signaling pathways in a mouse model of human breast cancer

    PubMed Central

    Mi, Zhiyong; Guo, Hongtao; Kuo, Paul C

    2009-01-01

    Background Osteopontin (OPN) is a secreted phosphoprotein which functions as a cell attachment protein and cytokine that signals through two cell adhesion molecules, αvβ3-integrin and CD44, to regulate cancer growth and metastasis. However, the signaling pathways associated with OPN have not been extensively characterized. In an in vivo xenograft model of MDA-MB-231 human breast cancer, we have previously demonstrated that ablation of circulating OPN with an RNA aptamer blocks interaction with its cell surface receptors to significantly inhibit adhesion, migration and invasion in vitro and local progression and distant metastases. Findings In this study, we performed microarray analysis to compare the transcriptomes of primary tumor in the presence and absence of aptamer ablation of OPN. The results were corroborated with RT-PCR and Western blot analysis. Our results demonstrate that ablation of OPN cell surface receptor binding is associated with significant alteration in gene and protein expression critical in apoptosis, vascular endothelial growth factor (VEGF), platelet derived growth factor (PDGF), interleukin-10 (IL-10), granulocyte-macrophage colony stimulating factor (GM-CSF) and proliferation signaling pathways. Many of these proteins have not been previously associated with OPN. Conclusion We conclude that secreted OPN regulates multiple signaling pathways critical for local tumor progression. PMID:19570203

  12. Epidermal Growth Factor Signaling towards Proliferation: Modeling and Logic Inference Using Forward and Backward Search.

    PubMed

    Riesco, Adrián; Santos-Buitrago, Beatriz; De Las Rivas, Javier; Knapp, Merrill; Santos-García, Gustavo; Talcott, Carolyn

    2017-01-01

    In biological systems, pathways define complex interaction networks where multiple molecular elements are involved in a series of controlled reactions producing responses to specific biomolecular signals. These biosystems are dynamic and there is a need for mathematical and computational methods able to analyze the symbolic elements and the interactions between them and produce adequate readouts of such systems. In this work, we use rewriting logic to analyze the cellular signaling of epidermal growth factor (EGF) and its cell surface receptor (EGFR) in order to induce cellular proliferation. Signaling is initiated by binding the ligand protein EGF to the membrane-bound receptor EGFR so as to trigger a reactions path which have several linked elements through the cell from the membrane till the nucleus. We present two different types of search for analyzing the EGF/proliferation system with the help of Pathway Logic tool, which provides a knowledge-based development environment to carry out the modeling of the signaling. The first one is a standard (forward) search. The second one is a novel approach based on narrowing, which allows us to trace backwards the causes of a given final state. The analysis allows the identification of critical elements that have to be activated to provoke proliferation.

  13. Global phosphoproteomic profiling reveals perturbed signaling in a mouse model of dilated cardiomyopathy.

    PubMed

    Kuzmanov, Uros; Guo, Hongbo; Buchsbaum, Diana; Cosme, Jake; Abbasi, Cynthia; Isserlin, Ruth; Sharma, Parveen; Gramolini, Anthony O; Emili, Andrew

    2016-11-01

    Phospholamban (PLN) plays a central role in Ca(2+) homeostasis in cardiac myocytes through regulation of the sarco(endo)plasmic reticulum Ca(2+)-ATPase 2A (SERCA2A) Ca(2+) pump. An inherited mutation converting arginine residue 9 in PLN to cysteine (R9C) results in dilated cardiomyopathy (DCM) in humans and transgenic mice, but the downstream signaling defects leading to decompensation and heart failure are poorly understood. Here we used precision mass spectrometry to study the global phosphorylation dynamics of 1,887 cardiac phosphoproteins in early affected heart tissue in a transgenic R9C mouse model of DCM compared with wild-type littermates. Dysregulated phosphorylation sites were quantified after affinity capture and identification of 3,908 phosphopeptides from fractionated whole-heart homogenates. Global statistical enrichment analysis of the differential phosphoprotein patterns revealed selective perturbation of signaling pathways regulating cardiovascular activity in early stages of DCM. Strikingly, dysregulated signaling through the Notch-1 receptor, recently linked to cardiomyogenesis and embryonic cardiac stem cell development and differentiation but never directly implicated in DCM before, was a prominently perturbed pathway. We verified alterations in Notch-1 downstream components in early symptomatic R9C transgenic mouse cardiomyocytes compared with wild type by immunoblot analysis and confocal immunofluorescence microscopy. These data reveal unexpected connections between stress-regulated cell signaling networks, specific protein kinases, and downstream effectors essential for proper cardiac function.

  14. Signal-to-noise performance analysis of streak tube imaging lidar systems. I. Cascaded model.

    PubMed

    Yang, Hongru; Wu, Lei; Wang, Xiaopeng; Chen, Chao; Yu, Bing; Yang, Bin; Yuan, Liang; Wu, Lipeng; Xue, Zhanli; Li, Gaoping; Wu, Baoning

    2012-12-20

    Streak tube imaging lidar (STIL) is an active imaging system using a pulsed laser transmitter and a streak tube receiver to produce 3D range and intensity imagery. The STIL has recently attracted a great deal of interest and attention due to its advantages of wide azimuth field-of-view, high range and angle resolution, and high frame rate. This work investigates the signal-to-noise performance of STIL systems. A theoretical model for characterizing the signal-to-noise performance of the STIL system with an internal or external intensified streak tube receiver is presented, based on the linear cascaded systems theory of signal and noise propagation. The STIL system is decomposed into a series of cascaded imaging chains whose signal and noise transfer properties are described by the general (or the spatial-frequency dependent) noise factors (NFs). Expressions for the general NFs of the cascaded chains (or the main components) in the STIL system are derived. The work presented here is useful for the design and evaluation of STIL systems.

  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. Epidermal Growth Factor Signaling towards Proliferation: Modeling and Logic Inference Using Forward and Backward Search

    PubMed Central

    Riesco, Adrián; Santos-Buitrago, Beatriz; De Las Rivas, Javier; Knapp, Merrill; Talcott, Carolyn

    2017-01-01

    In biological systems, pathways define complex interaction networks where multiple molecular elements are involved in a series of controlled reactions producing responses to specific biomolecular signals. These biosystems are dynamic and there is a need for mathematical and computational methods able to analyze the symbolic elements and the interactions between them and produce adequate readouts of such systems. In this work, we use rewriting logic to analyze the cellular signaling of epidermal growth factor (EGF) and its cell surface receptor (EGFR) in order to induce cellular proliferation. Signaling is initiated by binding the ligand protein EGF to the membrane-bound receptor EGFR so as to trigger a reactions path which have several linked elements through the cell from the membrane till the nucleus. We present two different types of search for analyzing the EGF/proliferation system with the help of Pathway Logic tool, which provides a knowledge-based development environment to carry out the modeling of the signaling. The first one is a standard (forward) search. The second one is a novel approach based on narrowing, which allows us to trace backwards the causes of a given final state. The analysis allows the identification of critical elements that have to be activated to provoke proliferation. PMID:28191459

  17. Global phosphoproteomic profiling reveals perturbed signaling in a mouse model of dilated cardiomyopathy

    PubMed Central

    Kuzmanov, Uros; Guo, Hongbo; Buchsbaum, Diana; Cosme, Jake; Abbasi, Cynthia; Isserlin, Ruth; Sharma, Parveen; Gramolini, Anthony O.; Emili, Andrew

    2016-01-01

    Phospholamban (PLN) plays a central role in Ca2+ homeostasis in cardiac myocytes through regulation of the sarco(endo)plasmic reticulum Ca2+-ATPase 2A (SERCA2A) Ca2+ pump. An inherited mutation converting arginine residue 9 in PLN to cysteine (R9C) results in dilated cardiomyopathy (DCM) in humans and transgenic mice, but the downstream signaling defects leading to decompensation and heart failure are poorly understood. Here we used precision mass spectrometry to study the global phosphorylation dynamics of 1,887 cardiac phosphoproteins in early affected heart tissue in a transgenic R9C mouse model of DCM compared with wild-type littermates. Dysregulated phosphorylation sites were quantified after affinity capture and identification of 3,908 phosphopeptides from fractionated whole-heart homogenates. Global statistical enrichment analysis of the differential phosphoprotein patterns revealed selective perturbation of signaling pathways regulating cardiovascular activity in early stages of DCM. Strikingly, dysregulated signaling through the Notch-1 receptor, recently linked to cardiomyogenesis and embryonic cardiac stem cell development and differentiation but never directly implicated in DCM before, was a prominently perturbed pathway. We verified alterations in Notch-1 downstream components in early symptomatic R9C transgenic mouse cardiomyocytes compared with wild type by immunoblot analysis and confocal immunofluorescence microscopy. These data reveal unexpected connections between stress-regulated cell signaling networks, specific protein kinases, and downstream effectors essential for proper cardiac function. PMID:27742792

  18. States versus Rewards: Dissociable neural prediction error signals underlying model-based and model-free reinforcement learning

    PubMed Central

    Gläscher, Jan; Daw, Nathaniel; Dayan, Peter; O’Doherty, John P.

    2010-01-01

    Reinforcement learning (RL) uses sequential experience with situations (“states”) and outcomes to assess actions. Whereas model-free RL uses this experience directly, in the form of a reward prediction error (RPE), model-based RL uses it indirectly, building a model of the state transition and outcome structure of the environment, and evaluating actions by searching this model. A state prediction error (SPE) plays a central role, reporting discrepancies between the current model and the observed state transitions. Using functional magnetic resonance imaging in humans solving a probabilistic Markov decision task we found the neural signature of an SPE in the intraparietal sulcus and lateral prefrontal cortex, in addition to the previously well-characterized RPE in the ventral striatum. This finding supports the existence of two unique forms of learning signal in humans, which may form the basis of distinct computational strategies for guiding behavior. PMID:20510862

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

    PubMed

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

    2014-12-01

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

  20. Zero-inflated Poisson model based likelihood ratio test for drug safety signal detection.

    PubMed

    Huang, Lan; Zheng, Dan; Zalkikar, Jyoti; Tiwari, Ram

    2017-02-01

    In recent decades, numerous methods have been developed for data mining of large drug safety databases, such as Food and Drug Administration's (FDA's) Adverse Event Reporting System, where data matrices are formed by drugs such as columns and adverse events as rows. Often, a large number of cells in these data matrices have zero cell counts and some of them are "true zeros" indicating that the drug-adverse event pairs cannot occur, and these zero counts are distinguished from the other zero counts that are modeled zero counts and simply indicate that the drug-adverse event pairs have not occurred yet or have not been reported yet. In this paper, a zero-inflated Poisson model based likelihood ratio test method is proposed to identify drug-adverse event pairs that have disproportionately high reporting rates, which are also called signals. The maximum likelihood estimates of the model parameters of zero-inflated Poisson model based likelihood ratio test are obtained using the expectation and maximization algorithm. The zero-inflated Poisson model based likelihood ratio test is also modified to handle the stratified analyses for binary and categorical covariates (e.g. gender and age) in the data. The proposed zero-inflated Poisson model based likelihood ratio test method is shown to asymptotically control the type I error and false discovery rate, and its finite sample performance for signal detection is evaluated through a simulation study. The simulation results show that the zero-inflated Poisson model based likelihood ratio test method performs similar to Poisson model based likelihood ratio test method when the estimated percentage of true zeros in the database is small. Both the zero-inflated Poisson model based likelihood ratio test and likelihood ratio test methods are applied to six selected drugs, from the 2006 to 2011 Adverse Event Reporting System database, with varying percentages of observed zero-count cells.

  1. Challenges Handling Magnetospheric and Ionospheric Signals in Internal Geomagnetic Field Modelling

    NASA Astrophysics Data System (ADS)

    Finlay, C. C.; Lesur, V.; Thébault, E.; Vervelidou, F.; Morschhauser, A.; Shore, R.

    2016-09-01

    Measurements of the Earth's magnetic field collected by low-Earth-orbit satellites such as Swarm and CHAMP, as well as at ground observatories, are dominated by sources in the Earth's interior. However these measurements also contain significant contributions from more rapidly-varying current systems in the ionosphere and magnetosphere. In order to fully exploit magnetic data to probe the physical properties and dynamics of the Earth's interior, field models with suitable treatments of external sources, and their associated induced signals, are essential. Here we review the methods presently used to construct models of the internal field, focusing on techniques to handle magnetospheric and ionospheric signals. Shortcomings of these techniques often limit the quality, as well as spatial and temporal resolution, of internal field models. We document difficulties in using track-by-track analysis to characterize magnetospheric field fluctuations, differences in internal field models that result from alternative treatments of the quiet-time ionospheric field, and challenges associated with rapidly changing, but spatially correlated, magnetic signatures of polar cap current systems. Possible strategies for improving internal field models are discussed, many of which are described in more detail elsewhere in this volume.

  2. Challenges Handling Magnetospheric and Ionospheric Signals in Internal Geomagnetic Field Modelling

    NASA Astrophysics Data System (ADS)

    Finlay, C. C.; Lesur, V.; Thébault, E.; Vervelidou, F.; Morschhauser, A.; Shore, R.

    2017-03-01

    Measurements of the Earth's magnetic field collected by low-Earth-orbit satellites such as Swarm and CHAMP, as well as at ground observatories, are dominated by sources in the Earth's interior. However these measurements also contain significant contributions from more rapidly-varying current systems in the ionosphere and magnetosphere. In order to fully exploit magnetic data to probe the physical properties and dynamics of the Earth's interior, field models with suitable treatments of external sources, and their associated induced signals, are essential. Here we review the methods presently used to construct models of the internal field, focusing on techniques to handle magnetospheric and ionospheric signals. Shortcomings of these techniques often limit the quality, as well as spatial and temporal resolution, of internal field models. We document difficulties in using track-by-track analysis to characterize magnetospheric field fluctuations, differences in internal field models that result from alternative treatments of the quiet-time ionospheric field, and challenges associated with rapidly changing, but spatially correlated, magnetic signatures of polar cap current systems. Possible strategies for improving internal field models are discussed, many of which are described in more detail elsewhere in this volume.

  3. Understanding Dynamic Patterns of NF-κB Signaling: Derivation and Analysis of a Minimal Model through Sensitivity Analysis

    NASA Astrophysics Data System (ADS)

    Joo, Jaewook; Plimpton, Steve; Martin, Shawn; Swiler, Laura; Faulon, Jean-Loup

    2007-03-01

    Understanding the pleiotropism of NF-κB signal transduction is a challenge of clear medical importance and systems biology. Current mathematical modeling frameworks for NF-κB signal transduction, though limited to a small signaling module located in a downstream of IKK, heavily rely on the parameterizations and the numerical studies of ODE models and doubtless lack intuitive explanations about underlying mechanisms of the dynamic patterns of the NF-κB signaling. Here we present a systematic way to derive a minimal model from an up-to-dated and detailed NF-κB signaling network by means of sensitivity analysis. Using analysis of the minimal model, we predict a dose-response curve shape, existence of Hopf-bifurcation, and underlying mechanisms of all possible dynamic patterns of NF-κB signaling. Simulating the detailed ODE model for NF-κB signaling network with large sets of the parameter values that are sampled from the biologically feasible parameter space, we present an ensemble of all possible dynamic patterns of NF-κB signaling and verify the predictions from the minimal model.

  4. Developing Itô stochastic differential equation models for neuronal signal transduction pathways.

    PubMed

    Manninen, Tiina; Linne, Marja-Leena; Ruohonen, Keijo

    2006-08-01

    Mathematical modeling and simulation of dynamic biochemical systems are receiving considerable attention due to the increasing availability of experimental knowledge of complex intracellular functions. In addition to deterministic approaches, several stochastic approaches have been developed for simulating the time-series behavior of biochemical systems. The problem with stochastic approaches, however, is the larger computational time compared to deterministic approaches. It is therefore necessary to study alternative ways to incorporate stochasticity and to seek approaches that reduce the computational time needed for simulations, yet preserve the characteristic behavior of the system in question. In this work, we develop a computational framework based on the Itô stochastic differential equations for neuronal signal transduction networks. There are several different ways to incorporate stochasticity into deterministic differential equation models and to obtain Itô stochastic differential equations. Two of the developed models are found most suitable for stochastic modeling of neuronal signal transduction. The best models give stable responses which means that the variances of the responses with time are not increasing and negative concentrations are avoided. We also make a comparative analysis of different kinds of stochastic approaches, that is the Itô stochastic differential equations, the chemical Langevin equation, and the Gillespie stochastic simulation algorithm. Different kinds of stochastic approaches can be used to produce similar responses for the neuronal protein kinase C signal transduction pathway. The fine details of the responses vary slightly, depending on the approach and the parameter values. However, when simulating great numbers of chemical species, the Gillespie algorithm is computationally several orders of magnitude slower than the Itô stochastic differential equations and the chemical Langevin equation. Furthermore, the chemical

  5. Cerebral Processing of Prosodic Emotional Signals: Evaluation of a Network Model Using rTMS

    PubMed Central

    Plewnia, Christian; Wildgruber, Dirk

    2014-01-01

    A great number of functional imaging studies contributed to developing a cerebral network model illustrating the processing of prosody in the brain. According to this model, the processing of prosodic emotional signals is divided into three main steps, each related to different brain areas. The present study sought to evaluate parts of the aforementioned model by using low-frequency repetitive transcranial magnetic stimulation (rTMS) over two important brain regions identified by the model: the superior temporal cortex (Experiment 1) and the inferior frontal cortex (Experiment 2). The aim of both experiments was to reduce cortical activity in the respective brain areas and evaluate whether these reductions lead to measurable behavioral effects during prosody processing. However, results obtained in this study revealed no rTMS effects on the acquired behavioral data. Possible explanations for these findings are discussed in the paper. PMID:25171220

  6. 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.

  7. Modelling the 21-cm Signal from the Epoch of Reionization and Cosmic Dawn

    NASA Astrophysics Data System (ADS)

    Choudhury, T. Roy; Datta, Kanan; Majumdar, Suman; Ghara, Raghunath; Paranjape, Aseem; Mondal, Rajesh; Bharadwaj, Somnath; Samui, Saumyadip

    2016-12-01

    Studying the cosmic dawn and the epoch of reionization through the redshifted 21-cm line are among the major science goals of the SKA1. Their significance lies in the fact that they are closely related to the very first stars in the Universe. Interpreting the upcoming data would require detailed modelling of the relevant physical processes. In this article, we focus on the theoretical models of reionization that have been worked out by various groups working in India with the upcoming SKA in mind. These models include purely analytical and semi-numerical calculations as well as fully numerical radiative transfer simulations. The predictions of the 21-cm signal from these models would be useful in constraining the properties of the early galaxies using the SKA data.

  8. 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

  9. 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.

  10. An improved model of motion-related signal changes in fMRI.

    PubMed

    Patriat, Rémi; Reynolds, Richard C; Birn, Rasmus M

    2017-01-01

    Head motion is a significant source of noise in the estimation of functional connectivity from resting-state functional MRI (rs-fMRI). Current strategies to reduce this noise include image realignment, censoring time points corrupted by motion, and including motion realignment parameters and their derivatives as additional nuisance regressors in the general linear model. However, this nuisance regression approach assumes that the motion-induced signal changes are linearly related to the estimated realignment parameters, which is not always the case. In this study we develop an improved model of motion-related signal changes, where nuisance regressors are formed by first rotating and translating a single brain volume according to the estimated motion, re-registering the data, and then performing a principal components analysis (PCA) on the resultant time series of both moved and re-registered data. We show that these "Motion Simulated (MotSim)" regressors account for significantly greater fraction of variance, result in higher temporal signal-to-noise, and lead to functional connectivity estimates that are less affected by motion compared to the most common current approach of using the realignment parameters and their derivatives as nuisance regressors. This improvement should lead to more accurate estimates of functional connectivity, particularly in populations where motion is prevalent, such as patients and young children.

  11. Early Warning Signals for Regime Transition in the Stable Boundary Layer: A Model Study

    NASA Astrophysics Data System (ADS)

    van Hooijdonk, I. G. S.; Moene, A. F.; Scheffer, M.; Clercx, H. J. H.; van de Wiel, B. J. H.

    2017-02-01

    The evening transition is investigated in an idealized model for the nocturnal boundary layer. From earlier studies it is known that the nocturnal boundary layer may manifest itself in two distinct regimes, depending on the ambient synoptic conditions: strong-wind or overcast conditions typically lead to weakly stable, turbulent nights; clear-sky and weak-wind conditions, on the other hand, lead to very stable, weakly turbulent conditions. Previously, the dynamical behaviour near the transition between these regimes was investigated in an idealized setting, relying on Monin-Obukhov (MO) similarity to describe turbulent transport. Here, we investigate a similar set-up, using direct numerical simulation; in contrast to MO-based models, this type of simulation does not need to rely on turbulence closure assumptions. We show that previous predictions are verified, but now independent of turbulence parametrizations. Also, it appears that a regime shift to the very stable state is signaled in advance by specific changes in the dynamics of the turbulent boundary layer. Here, we show how these changes may be used to infer a quantitative estimate of the transition point from the weakly stable boundary layer to the very stable boundary layer. In addition, it is shown that the idealized, nocturnal boundary-layer system shares important similarities with generic non-linear dynamical systems that exhibit critical transitions. Therefore, the presence of other, generic early warning signals is tested as well. Indeed, indications are found that such signals are present in stably stratified turbulent flows.

  12. Modulation of aberrant CDK5 signaling rescues impaired neurogenesis in models of Alzheimer's disease.

    PubMed

    Crews, L; Patrick, C; Adame, A; Rockenstein, E; Masliah, E

    2011-02-10

    Recent studies show that in Alzheimer's disease (AD), alterations in neurogenesis contribute to the neurodegenerative process. Neurodegeneration in AD has been associated with aberrant signaling through the cyclin-dependent kinase-5 (CDK5) pathway via its activators p35/p25; however, the role of CDK5 in the mechanisms of defective adult neurogenesis in AD is unknown. First, to study AD-like abnormal activation of CDK5 signaling in an in vitro model of neurogenesis, neuronal progenitor cells (NPCs) were infected with a viral vector expressing p35, and exposed to amyloid-β protein (Aβ(1-42)). These conditions resulted in impaired maturation and neurite outgrowth in vitro, and these effects were reversed by pharmacological or genetic inhibition of CDK5. Similarly, neurogenesis was impaired in a transgenic mouse model of AD that expresses high levels of amyloid precursor protein (APP), and this effect was reversed in transgenic mice crossed with a CDK5 heterozygous-deficient mouse line. A similar rescue effect was observed in APP transgenic mice treated with Roscovitine, a pharmacological inhibitor of CDK5. Taken together, these data suggest that the CDK5 signaling pathway has a critical role in maintaining the integrity of NPCs and neuronal maturation in the adult hippocampus. Moreover, potential therapeutic approaches could focus on modulating the aberrant activity of CDK5 to target the neurogenic and neurodegenerative alterations in AD.

  13. RAGE/NF-κB signaling mediates lipopolysaccharide induced acute lung injury in neonate rat model.

    PubMed

    Li, Yuhong; Wu, Rong; Tian, Yian; Yu, Min; Tang, Yun; Cheng, Huaipin; Tian, Zhaofang

    2015-01-01

    Lipopolysaccharide (LPS) is known to induce acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). Accumulating data suggest the crucial role of RAGE in the pathogenesis of ALI/ARDS. However, the mechanism by which RAGE mediates inflammatory lung injury in the neonates remains elusive. In this study we established LPS-induced ALI model in neonate rats, and investigated the role of RAGE/NF-κB signaling in mediating ALI. We found that RAGE antibody or bortezomib reduced LPS-induced histopathological abnormalities in the lung and lung damage score. RAGE antibody or bortezomib also reduced TNF-α level in both serum and BALF of the rats. Furthermore, RAGE antibody or bortezomib significantly reduced LPS-induced upregulation of RAGE and NF-κB expression in the lung. In conclusion, we established ALI model in neonate rats to demonstrate that LPS induced inflammatory lung injury via RAGE/NF-κB signaling. Interference with RAGE/NF-κB signaling is a potential approach to prevent and treat sepsis-related ALI/ARDS.

  14. Exploiting Magnetic Resonance Angiography Imaging Improves Model Estimation of BOLD Signal

    PubMed Central

    Hu, Zhenghui; Liu, Cong; Shi, Pengcheng; Liu, Huafeng

    2012-01-01

    The change of BOLD signal relies heavily upon the resting blood volume fraction () associated with regional vasculature. However, existing hemodynamic data assimilation studies pretermit such concern. They simply assign the value in a physiologically plausible range to get over ill-conditioning of the assimilation problem and fail to explore actual . Such performance might lead to unreliable model estimation. In this work, we present the first exploration of the influence of on fMRI data assimilation, where actual within a given cortical area was calibrated by an MR angiography experiment and then was augmented into the assimilation scheme. We have investigated the impact of on single-region data assimilation and multi-region data assimilation (dynamic cause modeling, DCM) in a classical flashing checkerboard experiment. Results show that the employment of an assumed in fMRI data assimilation is only suitable for fMRI signal reconstruction and activation detection grounded on this signal, and not suitable for estimation of unobserved states and effective connectivity study. We thereby argue that introducing physically realistic in the assimilation process may provide more reliable estimation of physiological information, which contributes to a better understanding of the underlying hemodynamic processes. Such an effort is valuable and should be well appreciated. PMID:22384043

  15. Layer-Dependent Attentional Processing by Top-down Signals in a Visual Cortical Microcircuit Model

    PubMed Central

    Wagatsuma, Nobuhiko; Potjans, Tobias C.; Diesmann, Markus; Fukai, Tomoki

    2011-01-01

    A vast amount of information about the external world continuously flows into the brain, whereas its capacity to process such information is limited. Attention enables the brain to allocate its resources of information processing to selected sensory inputs for reducing its computational load, and effects of attention have been extensively studied in visual information processing. However, how the microcircuit of the visual cortex processes attentional information from higher areas remains largely unknown. Here, we explore the complex interactions between visual inputs and an attentional signal in a computational model of the visual cortical microcircuit. Our model not only successfully accounts for previous experimental observations of attentional effects on visual neuronal responses, but also predicts contrasting differences in the attentional effects of top-down signals between cortical layers: attention to a preferred stimulus of a column enhances neuronal responses of layers 2/3 and 5, the output stations of cortical microcircuits, whereas attention suppresses neuronal responses of layer 4, the input station of cortical microcircuits. We demonstrate that the specific modulation pattern of layer-4 activity, which emerges from inter-laminar synaptic connections, is crucial for a rapid shift of attention to a currently unattended stimulus. Our results suggest that top-down signals act differently on different layers of the cortical microcircuit. PMID:21779240

  16. Modeling Ca2+ Signaling in the Microcirculation: Intercellular Communication and Vasoreactivity

    PubMed Central

    Kapela, Adam; Nagaraja, Sridevi; Parikh, Jaimit; Tsoukias, Nikolaos M.

    2013-01-01

    A network of intracellular signaling pathways and complex intercellular interactions regulate calcium mobilization in vascular cells, arteriolar tone, and blood flow. Different endothelium-derived vasoreactive factors have been identified and the importance of myoendothelial communication in vasoreactivity is now well appreciated. The ability of many vascular networks to conduct signals upstream also is established. This phenomenon is critical for both short-term changes in blood perfusion as well as long-term adaptations of a vascular network. In addition, in a phenomenon termed vasomotion, arterioles often exhibit spontaneous oscillations in diameter. This is thought to improve tissue oxygenation and enhance blood flow. Experimentation has begun to reveal important aspects of the regulatory machinery and the significance of these phenomena for the regulation of local perfusion and oxygenation. Mathematical modeling can assist in elucidating the complex signaling mechanisms that participate in these phenomena. This review highlights some of the important experimental studies and relevant mathematical models that provide the current understanding of these mechanisms in vasoreactivity. PMID:22196162

  17. 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

  18. 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.

  19. Insulin Signaling, Resistance, and the Metabolic Syndrome: Insights from Mouse Models to Disease Mechanisms

    PubMed Central

    Guo, Shaodong

    2014-01-01

    Insulin resistance is a major underlying mechanism for the “metabolic syndrome”, which is also known as insulin resistance syndrome. Metabolic syndrome is increasing at an alarming rate, becoming a major public and clinical problem worldwide. Metabolic syndrome is represented by a group of interrelated disorders, including obesity, hyperglycemia, hyperlipidemia, and hypertension. It is also a significant risk factor for cardiovascular disease and increased morbidity and mortality. Animal studies demonstrate that insulin and its signaling cascade normally control cell growth, metabolism and survival through activation of mitogen-activated protein kinases (MAPKs) and phosphotidylinositide-3-kinase (PI3K), of which activation of PI-3K-associated with insulin receptor substrate-1 and -2 (IRS1, 2) and subsequent Akt→Foxo1 phosphorylation cascade has a central role in control of nutrient homeostasis and organ survival. Inactivation of Akt and activation of Foxo1, through suppression IRS1 and IRS2 in different organs following hyperinsulinemia, metabolic inflammation, and over nutrition may provide the underlying mechanisms for metabolic syndrome in humans. Targeting the IRS→Akt→Foxo1 signaling cascade will likely provide a strategy for therapeutic intervention in the treatment of type 2 diabetes and its complications. This review discusses the basis of insulin signaling, insulin resistance in different mouse models, and how a deficiency of insulin signaling components in different organs contributes to the feature of the metabolic syndrome. Emphasis will be placed on the role of IRS1, IRS2, and associated signaling pathways that couple to Akt and the forkhead/winged helix transcription factor Foxo1. PMID:24281010

  20. Insulin signaling, resistance, and the metabolic syndrome: insights from mouse models into disease mechanisms.

    PubMed

    Guo, Shaodong

    2014-02-01

    Insulin resistance is a major underlying mechanism responsible for the 'metabolic syndrome', which is also known as insulin resistance syndrome. The incidence of the metabolic syndrome is increasing at an alarming rate, becoming a major public and clinical problem worldwide. The metabolic syndrome is represented by a group of interrelated disorders, including obesity, hyperglycemia, hyperlipidemia, and hypertension. It is also a significant risk factor for cardiovascular disease and increased morbidity and mortality. Animal studies have demonstrated that insulin and its signaling cascade normally control cell growth, metabolism, and survival through the activation of MAPKs and activation of phosphatidylinositide-3-kinase (PI3K), in which the activation of PI3K associated with insulin receptor substrate 1 (IRS1) and IRS2 and subsequent Akt→Foxo1 phosphorylation cascade has a central role in the control of nutrient homeostasis and organ survival. The inactivation of Akt and activation of Foxo1, through the suppression IRS1 and IRS2 in different organs following hyperinsulinemia, metabolic inflammation, and overnutrition, may act as the underlying mechanisms for the metabolic syndrome in humans. Targeting the IRS→Akt→Foxo1 signaling cascade will probably provide a strategy for therapeutic intervention in the treatment of type 2 diabetes and its complications. This review discusses the basis of insulin signaling, insulin resistance in different mouse models, and how a deficiency of insulin signaling components in different organs contributes to the features of the metabolic syndrome. Emphasis is placed on the role of IRS1, IRS2, and associated signaling pathways that are coupled to Akt and the forkhead/winged helix transcription factor Foxo1.

  1. Modulation of phytochrome signaling networks for improved biomass accumulation using a bioenergy crop model

    SciTech Connect

    Mockler, Todd C.

    2016-11-07

    Plant growth and development, including stem elongation, flowering time, and shade-avoidance habits, are affected by wavelength composition (i.e., light quality) of the light environment. the molecular mechanisms underlying light perception and signaling pathways in plants have been best characterized in Arabidopsis thaliana where dozens of genes have been implicated in converging, complementary, and antagonistic pathways communicating light quality cues perceived by the phytochrome (red/far-red) cryptochrome (blue) and phototropin (blue) photorecptors. Light perception and signaling have been studied in grasses, including rice and sorghum but in much less detail than in Arabidopsis. During the course of the Mocker lab's DOE-funded wrok generating a gene expression atlas in Brachypodium distachyon we observed that Brachypodium plants grown in continuous monochromatic red light or continuous white light enriched in far-red light accumulated significantly more biomass and exhibited significantly greater seed yield than plants grown in monochromatic blue light or white light. This phenomenon was also observed in two other grasses, switchgrass and rice. We will systematically manipulate the expression of genes predicted to function in Brachypodium phytochrome signaling and assess the phenotypic consequences in transgenic Brachypodium plants in terms of morphology, stature, biomass accumulation, and cell wall composition. We will also interrogate direct interactions between candidate phytochrome signaling transcription factors and target promoters using a high-throughput yeast one-hybrid system. Brachypodium distachyon has emerged as a model grass species and is closely related to candidate feedstock crops for bioethanol production. Identification of genes capable of modifying growth characteristics of Brachypodium, when misexpressed, in particular increasing biomass accumulation, by modulating photoreceptor signaling will provide valuable candidates for manipulation in

  2. A yeast model system for functional analysis of β-catenin signaling

    PubMed Central

    Lee, Margaret S.; D'Amour, Karen A.; Papkoff, Jackie

    2002-01-01

    We have developed a novel Saccharomyces cerevisiae model system to dissect the molecular events of β-catenin (β-cat) signaling. Coexpression of mammalian β-cat with TCF4 or LEF1 results in nuclear accumulation of these proteins and a functional complex that activates reporter gene transcription from constructs containing leukocyte enhancer factor (LEF)/T cell factor (TCF) response elements. Reporter transcription is constitutive, requires expression of both β-cat and TCF4 or LEF1, and is not supported by mutated LEF/TCF binding elements or by TCF4 or LEF1 mutants. A cytoplasmic domain of E-cadherin or a functional fragment of adenomatous polyposis coli (APC) protein (APC-25) complexes with β-cat, reduces β-cat binding to TCF4, and leads to increased cytoplasmic localization of β-cat and a reduction in reporter activation. Systematic mutation of putative nuclear export signal sequences in APC-25 decreases APC-25 binding to β-cat and restores reporter gene transcription. Additional β-cat signaling components, Axin and glycogen synthase kinase 3β, form a multisubunit complex similar to that found in mammalian cells. Coexpression of the F-box protein β-transducin repeat-containing protein reduces the stability of β-cat and decreases reporter activation. Thus, we have reconstituted a functional β-cat signal transduction pathway in yeast and show that β-cat signaling can be regulated at multiple levels, including protein subcellular localization, protein complex formation, and protein stability. PMID:12235124

  3. Dynamic modeling of biochemical reactions with application to signal transduction: principles and tools using Mathematica.

    PubMed

    Tóth, János; Rospars, Jean-Pierre

    2005-01-01

    Modeling of biochemical phenomena is based on formal reaction kinetics. This requires the translation of the original reaction systems into sets of differential equations expressing the effects of the various reaction steps. The temporal behavior of the system is obtained by solving the differential equations. We present the main concepts on which the formal approach of these two problems is based and we show how the amount of work needed to treat them can be significantly reduced by using a mathematical program package (Mathematica). Symbolic and numerical calculations can be performed with the programs presented and graphic presentations of the behavior of the system be obtained. The basic ideas are illustrated with three examples taken from the area of signal transduction and ion signaling.

  4. 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.

  5. Model-guided optogenetic study of PKA signaling in budding yeast

    PubMed Central

    Stewart-Ornstein, Jacob; Chen, Susan; Bhatnagar, Rajat; Weissman, Jonathan S.; El-Samad, Hana

    2017-01-01

    In eukaryotes, protein kinase A (PKA) is a master regulator of cell proliferation and survival. The activity of PKA is subject to elaborate control and exhibits complex time dynamics. To probe the quantitative attributes of PKA dynamics in the yeast Saccharomyces cerevisiae, we developed an optogenetic strategy that uses a photoactivatable adenylate cyclase to achieve real-time regulation of cAMP and the PKA pathway. We capitalize on the precise and rapid control afforded by this optogenetic tool, together with quantitative computational modeling, to study the properties of feedback in the PKA signaling network and dissect the nonintuitive dynamic effects that ensue from perturbing its components. Our analyses reveal that negative feedback channeled through the Ras1/2 GTPase is delayed, pinpointing its time scale and its contribution to the dynamic features of the cAMP/PKA signaling network. PMID:28035051

  6. Elevation dependency of the surface climate change signal: A model study

    SciTech Connect

    Giorgi, F.; Hurrell, J.W.; Marinucci, M.R.

    1997-02-01

    Results are presented from a present-day and a doubled CO{sub 2} experiment over the Alpine region with a nested regional climate model. The simulated temperature change signal shows a substantial elevation dependency, mostly during the winter and spring seasons, resulting in more pronounced warming at high elevations than low elevations. This is caused by a depletion of snowpack in doubled CO{sub 2} conditions and further enhanced by the snow-albedo feedback. This result is consistent with some observed temperature trends for anomalously warm years over the Alpine region and suggests that high elevation temperature changes could be used as an early detection tool for global warming. Changes in precipitation, as well as other components of the surface energy and water budgets, also show an elevation signal, which may have important implications for impact assessments in high elevation regions. 22 refs., 10 figs., 2 tabs.

  7. Model-based spectral estimation of Doppler signals using parallel genetic algorithms.

    PubMed

    Solano González, J; Rodríguez Vázquez, K; García Nocetti, D F

    2000-05-01

    Conventional spectral analysis methods use a fast Fourier transform (FFT) on consecutive or overlapping windowed data segments. For Doppler ultrasound signals, this approach suffers from an inadequate frequency resolution due to the time segment duration and the non-stationarity characteristics of the signals. Parametric or model-based estimators can give significant improvements in the time-frequency resolution at the expense of a higher computational complexity. This work describes an approach which implements in real-time a parametric spectral estimator method using genetic algorithms (GAs) in order to find the optimum set of parameters for the adaptive filter that minimises the error function. The aim is to reduce the computational complexity of the conventional algorithm by using the simplicity associated to GAs and exploiting its parallel characteristics. This will allow the implementation of higher order filters, increasing the spectrum resolution, and opening a greater scope for using more complex methods.

  8. 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).

  9. Modelling of infectious diseases for providing signal of epidemics: a measles case study in Bangladesh.

    PubMed

    Sharmin, Sifat; Rayhan, Israt

    2011-12-01

    The detection of unusual patterns in the occurrence of diseases is an important challenge to health workers interested in early identification of epidemics. The objective of this study was to provide an early signal of infectious disease epidemics by analyzing the disease dynamics. A two-stage monitoring system was applied, which consists of univariate Box-Jenkins model or autoregressive integrated moving average model and subsequent tracking signals from several statistical process-control charts. The analyses were illustrated on January 2000-August 2009 national measles data reported monthly to the Expanded Programme on Immunization (EPI) in Bangladesh. The results of this empirical study revealed that the most adequate model for the occurrences of measles in Bangladesh was the seasonal autoregressive integrated moving average (3, 1, 0) (0, 1, 1)12 model, and the statistical process-control charts detected no measles epidemics during September 2007-August 2009. The two-stage monitoring system performed well to capture the measles dynamics in Bangladesh without detection of an epidemic because of high measles-vaccination coverage.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  11. Removal of Nuisance Signals from Limited and Sparse 1H MRSI Data Using a Union-of-Subspaces Model

    PubMed Central

    Ma, Chao; Lam, Fan; Johnson, Curtis L.; Liang, Zhi-Pei

    2015-01-01

    Purpose To remove nuisance signals (e.g., water and lipid signals) for 1H MRSI data collected from the brain with limited and/or sparse (k, t)-space coverage. Methods A union-of-subspace model is proposed for removing nuisance signals. The model exploits the partial separability of both the nuisance signals and the metabolite signal, and decomposes an MRSI dataset into several sets of generalized voxels that share the same spectral distributions. This model enables the estimation of the nuisance signals from an MRSI dataset that has limited and/or sparse (k, t)-space coverage. Results The proposed method has been evaluated using in vivo MRSI data. For conventional CSI data with limited k-space coverage, the proposed method produced “lipid-free” spectra without lipid suppression during data acquisition at 130 ms echo time. For sparse (k, t)-space data acquired with conventional pulses for water and lipid suppression, the proposed method was also able to remove the remaining water and lipid signals with negligible residuals. Conclusions Nuisance signals in 1H MRSI data reside in low-dimensional subspaces. This property can be utilized for estimation and removal of nuisance signals from 1H MRSI data even when they have limited and/or sparse coverage of (k, t)-space. The proposed method should prove useful especially for accelerated high-resolution 1H MRSI of the brain. PMID:25762370

  12. Functional structure of the cryogenic optical sensor and mathematical models of signal

    NASA Astrophysics Data System (ADS)

    Yatsenko, Vitaliy A.

    2003-10-01

    Today, remote sensing is one of the fastest growing technologies around. It is a multibillion-dollar industry and remote thematic images are routinely used in an increasing number of fields. The solution of many important practical problems depends on a large-scale usage of the measurement systems and underlying physical principles. These problems include monitoring of the natural resources based on the analysis of the gravity anomalies, studying of global geodynamic processes and evolution of the Earth gravity field, analysis of movement of the Earth poles, etc. In spite of the existence of the considerable achievements in the area of gravity measurements, some important aspects of the problem have not been solved yet due to the absence of appropriate sensitive elements (SE) and sensors with the relevant parameters. The author of the report has proposed a functional structure of the cryogenic-optical sensor based on magnetic bearing phenomenon. A functional structure of the sensitive element consists of a controlled magnetic suspension, a high-precision optical system for registration of levitating body mechanical coordinates, and a signal processing toolbox. This toolbox contents the adaptive compensator, digital filters, inverse mathematical models of the SE, the Kalman filter, the control system, the dynamical analysis system, the mathematical modeling system, the simulation system, the information statistical system, the wavelet analysis system, a neural network, and data base. Mathematical models of the signal and noise are conventionally based on the principles of nonlinear electro-mechanics. Such models explains most basic features of the superconducting sensitive element. We will also discuss a new theoretical framework for adaptive estimation of gravitation perturbations and compare program models to conventional robust estimation models.

  13. Genetic analysis, structural modeling, and direct coupling analysis suggest a mechanism for phosphate signaling in Escherichia coli

    PubMed Central

    2015-01-01

    Background Proper phosphate signaling is essential for robust growth of Escherichia coli and many other bacteria. The phosphate signal is mediated by a classic two component signal system composed of PhoR and PhoB. The PhoR histidine kinase is responsible for phosphorylating/dephosphorylating the response regulator, PhoB, which controls the expression of genes that aid growth in low phosphate conditions. The mechanism by which PhoR receives a signal of environmental phosphate levels has remained elusive. A transporter complex composed of the PstS, PstC, PstA, and PstB proteins as well as a negative regulator, PhoU, have been implicated in signaling environmental phosphate to PhoR. Results This work confirms that PhoU and the PstSCAB complex are necessary for proper signaling of high environmental phosphate. Also, we identify residues important in PhoU/PhoR interaction with genetic analysis. Using protein modeling and docking methods, we show an interaction model that points to a potential mechanism for PhoU mediated signaling to PhoR to modify its activity. This model is tested with direct coupling analysis. Conclusions These bioinformatics tools, in combination with genetic and biochemical analysis, help to identify and test a model for phosphate signaling and may be applicable to several other systems. PMID:25953406

  14. Inference Method for Developing Mathematical Models of Cell Signaling Pathways Using Proteomic Datasets.

    PubMed

    Tian, Tianhai; Song, Jiangning

    2017-01-01

    The progress in proteomics technologies has led to a rapid accumulation of large-scale proteomic datasets in recent years, which provides an unprecedented opportunity and valuable resources to understand how living organisms perform necessary functions at systems levels. This work presents a computational method for designing mathematical models based on proteomic datasets. Using the mitogen-activated protein (MAP) kinase pathway as the test system, we first develop a mathematical model including the cytosolic and nuclear subsystems. A key step of modeling is to apply a genetic algorithm to infer unknown model parameters. Then the robustness property of mathematical models is used as a criterion to select appropriate rate constants from the estimated candidates. Moreover, quantitative information such as the absolute protein concentrations is used to further refine the mathematical model. The successful application of this inference method to the MAP kinase pathway suggests that it is a useful and powerful approach for developing accurate mathematical models to gain important insights into the regulatory mechanisms of cell signaling pathways.

  15. 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

  16. Modeling left-turn crash occurrence at signalized intersections by conflicting patterns.

    PubMed

    Wang, Xuesong; Abdel-Aty, Mohamed

    2008-01-01

    In order to better understand the underlying crash mechanisms, left-turn crashes occurring at 197 four-legged signalized intersections over 6 years were classified into nine patterns based on vehicle maneuvers and then were assigned to intersection approaches. Crash frequency of each pattern was modeled at the approach level by mainly using Generalized Estimating Equations (GEE) with the Negative Binomial as the link function to account for the correlation among the crash data. GEE with a binomial logit link function was also applied for patterns with fewer crashes. The Cumulative Residuals test shows that, for correlated left-turn crashes, GEE models usually outperformed basic Negative Binomial models. The estimation results show that there are obvious differences in the factors that cause the occurrence of different left-turn collision patterns. For example, for each pattern, the traffic flows to which the colliding vehicles belong are identified to be significant. The width of the crossing distance (represented by the number of through lanes on the opposing approach of the left-turning traffic) is associated with more left-turn traffic colliding with opposing through traffic (Pattern 5), but with less left-turning traffic colliding with near-side crossing through traffic (Pattern 8). The safety effectiveness of the left-turning signal is not consistent for different crash patterns; "protected" phasing is correlated with fewer Pattern 5 crashes, but with more Pattern 8 crashes. The study indicates that in order to develop efficient countermeasures for left-turn crashes and improve safety at signalized intersections, left-turn crashes should be considered in different patterns.

  17. 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

  18. Methodologies for the modeling and simulation of biochemical networks, illustrated for signal transduction pathways: a primer.

    PubMed

    ElKalaawy, Nesma; Wassal, Amr

    2015-03-01

    Biochemical networks depict the chemical interactions that take place among elements of living cells. They aim to elucidate how cellular behavior and functional properties of the cell emerge from the relationships between its components, i.e. molecules. Biochemical networks are largely characterized by dynamic behavior, and exhibit high degrees of complexity. Hence, the interest in such networks is growing and they have been the target of several recent modeling efforts. Signal transduction pathways (STPs) constitute a class of biochemical networks that receive, process, and respond to stimuli from the environment, as well as stimuli that are internal to the organism. An STP consists of a chain of intracellular signaling processes that ultimately result in generating different cellular responses. This primer presents the methodologies used for the modeling and simulation of biochemical networks, illustrated for STPs. These methodologies range from qualitative to quantitative, and include structural as well as dynamic analysis techniques. We describe the different methodologies, outline their underlying assumptions, and provide an assessment of their advantages and disadvantages. Moreover, publicly and/or commercially available implementations of these methodologies are listed as appropriate. In particular, this primer aims to provide a clear introduction and comprehensive coverage of biochemical modeling and simulation methodologies for the non-expert, with specific focus on relevant literature of STPs.

  19. 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

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

    PubMed

    Cervera, Javier; Alcaraz, Antonio; Mafe, Salvador

    2016-02-04

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

  1. Encoding electric signals by Gymnotus omarorum: heuristic modeling of tuberous electroreceptor organs.

    PubMed

    Cilleruelo, Esteban R; Caputi, Angel Ariel

    2012-01-24

    The role of different substructures of electroreceptor organs in signal encoding was explored using a heuristic computational model. This model consists of four modules representing the pre-receptor structures, the transducer cells, the synapses and the afferent fiber, respectively. Simulations reproduced previously obtained experimental data. We showed that different electroreceptor types described in the literature can be qualitative modeled with the same set of equations by changing only two parameters, one affecting the filtering properties of the pre-receptor, and the other affecting the transducer module. We studied the responses of different electroreceptor types to natural stimuli using simulations derived from an experimentally-obtained database in which the fish were exposed to resistive or capacitive objects. Our results indicate that phase and frequency spectra are differentially encoded by different subpopulations of tuberous electroreceptors. A different type of receptor responses to the same input is a necessary condition for encoding a multidimensional space of stimuli as in the waveform of the EOD. Our simulation analysis suggested that the electroreceptive mosaic may perform a waveform analysis of electrosensory signals. As in color vision or tactile texture perception, a secondary attribute, "electric color" may be encoded as a parallel activity of various electroreceptor types. This article is part of a Special Issue entitled Neural Coding.

  2. Systems modelling methodology for the analysis of apoptosis signal transduction and cell death decisions.

    PubMed

    Rehm, Markus; Prehn, Jochen H M

    2013-06-01

    Systems biology and systems medicine, i.e. the application of systems biology in a clinical context, is becoming of increasing importance in biology, drug discovery and health care. Systems biology incorporates knowledge and methods that are applied in mathematics, physics and engineering, but may not be part of classical training in biology. We here provide an introduction to basic concepts and methods relevant to the construction and application of systems models for apoptosis research. We present the key methods relevant to the representation of biochemical processes in signal transduction models, with a particular reference to apoptotic processes. We demonstrate how such models enable a quantitative and temporal analysis of changes in molecular entities in response to an apoptosis-inducing stimulus, and provide information on cell survival and cell death decisions. We introduce methods for analyzing the spatial propagation of cell death signals, and discuss the concepts of sensitivity analyses that enable a prediction of network responses to disturbances of single or multiple parameters.

  3. 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.

  4. Salidroside Modulates Insulin Signaling in a Rat Model of Nonalcoholic Steatohepatitis

    PubMed Central

    Ying, Hao; Hu, Airong; Li, Dezhou; Hu, Yaoren

    2017-01-01

    A growing body of evidence has shown the beneficial effects of salidroside in cardiovascular and metabolic diseases. This study aimed to evaluate the therapeutic effects of salidroside on nonalcoholic steatohepatitis (NASH) in rats and explore the underlying mechanisms related to insulin signaling. A rat model of NASH was developed by high-fat diet for 14 weeks. From week 9 onward, the treatment group received oral salidroside (4.33 mg/kg) daily for 6 weeks. Salidroside effectively attenuated steatosis and vacuolation of hepatic tissue, with a dramatic decrease in liver triglycerides and free fatty acid levels (P < 0.01). Dysregulation of FINS, FBG, HOMA-IR, ALT, and AST in serum was ameliorated with salidroside treatment (P < 0.01). In the liver, salidroside induced significant increases in key molecules in the insulin signaling pathway, such as phosphorylated insulin receptor substrate 1 (IRS1), phosphoinositide 3-kinase (PI3K), and protein kinase B (PKB), with a significant decrease in SREBP-1c levels (P < 0.01). Therefore, salidroside effectively protected rats from high-fat-diet-induced NASH, which may be partially attributed to its effects on the hepatic insulin signaling pathway. PMID:28255329

  5. A pain-mediated neural signal induces relapse in murine autoimmune encephalomyelitis, a multiple sclerosis model

    PubMed Central

    Arima, Yasunobu; Kamimura, Daisuke; Atsumi, Toru; Harada, Masaya; Kawamoto, Tadafumi; Nishikawa, Naoki; Stofkova, Andrea; Ohki, Takuto; Higuchi, Kotaro; Morimoto, Yuji; Wieghofer, Peter; Okada, Yuka; Mori, Yuki; Sakoda, Saburo; Saika, Shizuya; Yoshioka, Yoshichika; Komuro, Issei; Yamashita, Toshihide; Hirano, Toshio; Prinz, Marco; Murakami, Masaaki

    2015-01-01

    Although pain is a common symptom of various diseases and disorders, its contribution to disease pathogenesis is not well understood. Here we show using murine experimental autoimmune encephalomyelitis (EAE), a model for multiple sclerosis (MS), that pain induces EAE relapse. Mechanistic analysis showed that pain induction activates a sensory-sympathetic signal followed by a chemokine-mediated accumulation of MHC class II+CD11b+ cells that showed antigen-presentation activity at specific ventral vessels in the fifth lumbar cord of EAE-recovered mice. Following this accumulation, various immune cells including pathogenic CD4+ T cells recruited in the spinal cord in a manner dependent on a local chemokine inducer in endothelial cells, resulting in EAE relapse. Our results demonstrate that a pain-mediated neural signal can be transformed into an inflammation reaction at specific vessels to induce disease relapse, thus making this signal a potential therapeutic target. DOI: http://dx.doi.org/10.7554/eLife.08733.001 PMID:26193120

  6. 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.

  7. 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

  8. Palaeoclimate signal recorded by stable isotopes in cave ice: a modeling approach

    NASA Astrophysics Data System (ADS)

    Perşoiu, A.; Bojar, A.-V.

    2012-04-01

    Ice accumulations in caves preserve a large variety of geochemical information as candidate proxies for both past climate and environmental changes, one of the most significant being the stable isotopic composition of the ice. A series of recent studies have targeted oxygen and hydrogen stable isotopes in cave ice as proxies for past air temperatures, but the results are far from being as straightforward as they are in high latitude and altitude glaciers and ice caps. The main problems emerging from these studies are related to the mechanisms of cave ice formation (i.e., freezing of water) and post-formation processes (melting and refreezing), which both alter the original isotopic signal in water. Different methods have been put forward to solve these issues and a fair understanding of the present-day link between stable isotopes in precipitation and cave ice exists now. However, the main issues still lays unsolved: 1) is it possible to extend this link to older ice and thus reconstruct past changes in air temperature?; 2) to what extent are ice dynamics processes modifying the original climatic signal and 3) what is the best method to be used in extracting a climatic signal from stable isotopes in cave ice? To respond to these questions, we have conducted a modeling experiment, in which a theoretical cave ice stable isotope record was constructed using present-day observations on stable isotope behavior in cave ice and ice dynamics, and different methods (presently used for both polar and cave glaciers), were used to reconstruct the original, known, isotopic values. Our results show that it is possible to remove the effects of ice melting and refreezing on stable isotope composition of cave ice, and thus reconstruct the original isotopic signal, and further the climatic one.

  9. Hydroxytyrosol restores proper insulin signaling in an astrocytic model of Alzheimer's disease.

    PubMed

    Crespo, M Carmen; Tomé-Carneiro, Joao; Pintado, Cristina; Dávalos, Alberto; Visioli, Francesco; Burgos-Ramos, Emma

    2017-03-20

    Recent epidemiological evidence demonstrated that diabetes is a risk factor for AD onset and development. Indeed, meta-analyses of longitudinal epidemiologic studies show that diabetes increases AD risk by 50-100%, being insulin resistance (IR) the main binding link between diabetes and AD. Astrocytes are the foremost cerebral macroglial cells and are responsible for converting glucose into lactate and transfer it to neurons that use it as fuel, but Aβ(1-42) impairs insulin signaling and glycogen storage. Recent prospective studies showed that the Mediterranean diet is associated with lower incidence of AD. We hypothesized that hydroxytyrosol (HT, the preeminent polyphenol of olives and olive oil) could exert beneficial effects on IR associated with AD and investigated it mechanisms of action in an astrocytic model of AD. The astrocytic cell line C6 was exposed to Aβ(25-35) and co-incubated with HT for different periods. After treatment with Aβ(25-35), astrocytes' viability was significantly decreased as compared with controls; however, both pre- and post-treatment with HT prevented this effect. Mechanistically, we found that the preventive role of HT on Aβ(25-35)- induced cytotoxicity in astrocytes is moderated by an increased HT-induced activation of Akt, which is mediated by the insulin signaling pathway. In addition, we report that HT prevented the pronounced activation of mTOR, thereby restoring proper insulin signaling. In conclusion, we demonstrate that HT protects Aβ(25-35)-treated astrocytes by improving insulin sensitivity and restoring proper insulin-signaling. These data provide some mechanistic insight on the observed inverse association between olive oil consumption and prevalence of cognitive impairment. © 2017 BioFactors, 2017.

  10. Modeling and model-aware signal processing methods for enhancement of optical systems

    NASA Astrophysics Data System (ADS)

    Aksoylar, Aydan

    Theoretical and numerical modeling of optical systems are increasingly being utilized in a wide range of areas in physics and engineering for characterizing and improving existing systems or developing new methods. This dissertation focuses on determining and improving the performance of imaging and non-imaging optical systems through modeling and developing model-aware enhancement methods. We evaluate the performance, demonstrate enhancements in terms of resolution and light collection efficiency, and improve the capabilities of the systems through changes to the system design and through post-processing techniques. We consider application areas in integrated circuit (IC) imaging for fault analysis and malicious circuitry detection, and free-form lens design for creating prescribed illumination patterns. The first part of this dissertation focuses on sub-surface imaging of ICs for fault analysis using a solid immersion lens (SIL) microscope. We first derive the Green's function of the microscope and use it to determine its resolution limits for bulk silicon and silicon-on-insulator (SOI) chips. We then propose an optimization framework for designing super-resolving apodization masks that utilizes the developed model and demonstrate the trade-offs in designing such masks. Finally, we derive the full electromagnetic model of the SIL microscope that models the image of an arbitrary sub-surface structure. With the rapidly shrinking dimensions of ICs, we are increasingly limited in resolving the features and identifying potential modifications despite the resolution improvements provided by the state-of-the-art microscopy techniques and enhancement methods described here. In the second part of this dissertation, we shift our focus away from improving the resolution and consider an optical framework that does not require high resolution imaging for detecting malicious circuitry. We develop a classification-based high-throughput gate identification method that utilizes

  11. 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

  12. 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

  13. Visual setup of logical models of signaling and regulatory networks with ProMoT

    PubMed Central

    Saez-Rodriguez, Julio; Mirschel, Sebastian; Hemenway, Rebecca; Klamt, Steffen; Gilles, Ernst Dieter; Ginkel, Martin

    2006-01-01

    Background The analysis of biochemical networks using a logical (Boolean) description is an important approach in Systems Biology. Recently, new methods have been proposed to analyze large signaling and regulatory networks using this formalism. Even though there is a large number of tools to set up models describing biological networks using a biochemical (kinetic) formalism, however, they do not support logical models. Results Herein we present a flexible framework for setting up large logical models in a visual manner with the software tool ProMoT. An easily extendible library, ProMoT's inherent modularity and object-oriented concept as well as adaptive visualization techniques provide a versatile environment. Both the graphical and the textual description of the logical model can be exported to different formats. Conclusion New features of ProMoT facilitate an efficient set-up of large Boolean models of biochemical interaction networks. The modeling environment is flexible; it can easily be adapted to specific requirements, and new extensions can be introduced. ProMoT is freely available from . PMID:17109765

  14. 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

  15. A General Framework for Modeling Sub- and Ultraharmonics of Ultrasound Contrast Agent Signals with MISO Volterra Series

    PubMed Central

    Charara, Jamal; Girault, Jean-Marc

    2013-01-01

    Sub- and ultraharmonics generation by ultrasound contrast agents makes possible sub- and ultraharmonics imaging to enhance the contrast of ultrasound images and overcome the limitations of harmonic imaging. In order to separate different frequency components of ultrasound contrast agents signals, nonlinear models like single-input single-output (SISO) Volterra model are used. One important limitation of this model is its incapacity to model sub- and ultraharmonic components. Many attempts are made to model sub- and ultraharmonics using Volterra model. It led to the design of mutiple-input singe-output (MISO) Volterra model instead of SISO Volterra model. The key idea of MISO modeling was to decompose the input signal of the nonlinear system into periodic subsignals at the subharmonic frequency. In this paper, sub- and ultraharmonics modeling with MISO Volterra model is presented in a general framework that details and explains the required conditions to optimally model sub- and ultraharmonics. A new decomposition of the input signal in periodic orthogonal basis functions is presented. Results of application of different MISO Volterra methods to model simulated ultrasound contrast agents signals show its efficiency in sub- and ultraharmonics imaging. PMID:23554840

  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. Increased ghrelin signaling prolongs survival in mouse models of human aging through activation of sirtuin1

    PubMed Central

    Fujitsuka, N; Asakawa, A; Morinaga, A; Amitani, M S; Amitani, H; Katsuura, G; Sawada, Y; Sudo, Y; Uezono, Y; Mochiki, E; Sakata, I; Sakai, T; Hanazaki, K; Yada, T; Yakabi, K; Sakuma, E; Ueki, T; Niijima, A; Nakagawa, K; Okubo, N; Takeda, H; Asaka, M; Inui, A

    2016-01-01

    Caloric restriction (CR) is known to retard aging and delay functional decline as well as the onset of diseases in most organisms. Ghrelin is secreted from the stomach in response to CR and regulates energy metabolism. We hypothesized that in CR ghrelin has a role in protecting aging-related diseases. We examined the physiological mechanisms underlying the ghrelin system during the aging process in three mouse strains with different genetic and biochemical backgrounds as animal models of accelerated or normal human aging. The elevated plasma ghrelin concentration was observed in both klotho-deficient and senescence-accelerated mouse prone/8 (SAMP8) mice. Ghrelin treatment failed to stimulate appetite and prolong survival in klotho-deficient mice, suggesting the existence of ghrelin resistance in the process of aging. However, ghrelin antagonist hastened death and ghrelin signaling potentiators rikkunshito and atractylodin ameliorated several age-related diseases with decreased microglial activation in the brain and prolonged survival in klotho-deficient, SAMP8 and aged ICR mice. In vitro experiments, the elevated sirtuin1 (SIRT1) activity and protein expression through the cAMP–CREB pathway was observed after ghrelin and ghrelin potentiator treatment in ghrelin receptor 1a-expressing cells and human umbilical vein endothelial cells. Furthermore, rikkunshito increased hypothalamic SIRT1 activity and SIRT1 protein expression of the heart in the all three mouse models of aging. Pericarditis, myocardial calcification and atrophy of myocardial and muscle fiber were improved by treatment with rikkunshito. Ghrelin signaling may represent one of the mechanisms activated by CR, and potentiating ghrelin signaling may be useful to extend health and lifespan. PMID:26830139

  18. Computational modelling of multi-cell migration in a multi-signalling substrate.

    PubMed

    Mousavi, Seyed Jamaleddin; Doblaré, Manuel; Doweidar, Mohamed Hamdy

    2014-04-01

    Cell migration is a vital process in many biological phenomena ranging from wound healing to tissue regeneration. Over the past few years, it has been proven that in addition to cell-cell and cell-substrate mechanical interactions (mechanotaxis), cells can be driven by thermal, chemical and/or electrical stimuli. A numerical model was recently presented by the authors to analyse single cell migration in a multi-signalling substrate. That work is here extended to include multi-cell migration due to cell-cell interaction in a multi-signalling substrate under different conditions. This model is based on balancing the forces that act on the cell population in the presence of different guiding cues. Several numerical experiments are presented to illustrate the effect of different stimuli on the trajectory and final location of the cell population within a 3D heterogeneous multi-signalling substrate. Our findings indicate that although multi-cell migration is relatively similar to single cell migration in some aspects, the associated behaviour is very different. For instance, cell-cell interaction may delay single cell migration towards effective cues while increasing the magnitude of the average net cell traction force as well as the local velocity. Besides, the random movement of a cell within a cell population is slightly greater than that of single cell migration. Moreover, higher electrical field strength causes the cell slug to flatten near the cathode. On the other hand, as with single cell migration, the existence of electrotaxis dominates mechanotaxis, moving the cells to the cathode or anode pole located at the free surface. The numerical results here obtained are qualitatively consistent with related experimental works.

  19. Computational modelling of multi-cell migration in a multi-signalling substrate

    NASA Astrophysics Data System (ADS)

    Jamaleddin Mousavi, Seyed; Doblaré, Manuel; Hamdy Doweidar, Mohamed

    2014-04-01

    Cell migration is a vital process in many biological phenomena ranging from wound healing to tissue regeneration. Over the past few years, it has been proven that in addition to cell-cell and cell-substrate mechanical interactions (mechanotaxis), cells can be driven by thermal, chemical and/or electrical stimuli. A numerical model was recently presented by the authors to analyse single cell migration in a multi-signalling substrate. That work is here extended to include multi-cell migration due to cell-cell interaction in a multi-signalling substrate under different conditions. This model is based on balancing the forces that act on the cell population in the presence of different guiding cues. Several numerical experiments are presented to illustrate the effect of different stimuli on the trajectory and final location of the cell population within a 3D heterogeneous multi-signalling substrate. Our findings indicate that although multi-cell migration is relatively similar to single cell migration in some aspects, the associated behaviour is very different. For instance, cell-cell interaction may delay single cell migration towards effective cues while increasing the magnitude of the average net cell traction force as well as the local velocity. Besides, the random movement of a cell within a cell population is slightly greater than that of single cell migration. Moreover, higher electrical field strength causes the cell slug to flatten near the cathode. On the other hand, as with single cell migration, the existence of electrotaxis dominates mechanotaxis, moving the cells to the cathode or anode pole located at the free surface. The numerical results here obtained are qualitatively consistent with related experimental works.

  20. Seismovolcanic signals at Deception Island volcano, Antarctica: Wave field analysis and source modeling

    NASA Astrophysics Data System (ADS)

    IbáñEz, Jesús M.; Pezzo, Edoardo Del; Almendros, Javier; La Rocca, Mario; Alguacil, Gerardo; Ortiz, Ramón; GarcíA, Alicia

    2000-06-01

    The seismovolcanic signals associated with the volcanic activity of Deception Island (Antarctica), recorded during three Antarctic summers (1994-1995, 1995-1996 and 1996-1997), are analyzed using a dense small-aperture (500 m) seismic array. The visual and spectral classification of the seismic events shows the existence of long-period and hybrid isolated seismic events, and of low-frequency, quasi-monochromatic and spasmodic continuous tremors. All spectra have the highest amplitudes in the frequency band between 1 and 4 Hz, while hybrids and spasmodic tremors have also significant amplitudes in the high-frequency band (4-10 Hz). The array analysis indicates that almost all the well-correlated low-frequency signals share similar array parameters (slowness and back azimuth) and have the same source area, close to the array site. The polarization analysis shows that phases at high-frequency are mostly composed of P waves, and those phases dominated by low frequencies can be interpreted as surface waves. No clear shear waves are evidenced. From the energy evaluation, we have found that the reduced displacement values for surface and body waves are confined in a narrow interval. Volcano-tectonic seismicity is located close to the array, at a depth shallower than 1 km. The wave-field properties of the seismovolcanic signals allow us to assume a unique source model, a shallow resonating fluid-filled crack system at a depth of some hundreds of meters. All of the seismic activity is interpreted as the response of a reasonably stable stationary geothermal process. The differences observed in the back azimuth between low and high frequencies are a near-field effect. A few episodes of the degassification process in an open conduit were observed and modeled with a simple organ pipe.

  1. Coordinated movement, neuromuscular synaptogenesis and trans-synaptic signaling defects in Drosophila galactosemia models.

    PubMed

    Jumbo-Lucioni, Patricia P; Parkinson, William M; Kopke, Danielle L; Broadie, Kendal

    2016-09-01

    The multiple galactosemia disease states manifest long-term neurological symptoms. Galactosemia I results from loss of galactose-1-phosphate uridyltransferase (GALT), which converts galactose-1-phosphate + UDP-glucose to glucose-1-phosphate + UDP-galactose. Galactosemia II results from loss of galactokinase (GALK), phosphorylating galactose to galactose-1-phosphate. Galactosemia III results from the loss of UDP-galactose 4'-epimerase (GALE), which interconverts UDP-galactose and UDP-glucose, as well as UDP-N-acetylgalactosamine and UDP-N-acetylglucosamine. UDP-glucose pyrophosphorylase (UGP) alternatively makes UDP-galactose from uridine triphosphate and galactose-1-phosphate. All four UDP-sugars are essential donors for glycoprotein biosynthesis with critical roles at the developing neuromuscular synapse. Drosophila galactosemia I (dGALT) and II (dGALK) disease models genetically interact; manifesting deficits in coordinated movement, neuromuscular junction (NMJ) development, synaptic glycosylation, and Wnt trans-synaptic signalling. Similarly, dGALE and dUGP mutants display striking locomotor and NMJ formation defects, including expanded synaptic arbours, glycosylation losses, and differential changes in Wnt trans-synaptic signalling. In combination with dGALT loss, both dGALE and dUGP mutants compromise the synaptomatrix glycan environment that regulates Wnt trans-synaptic signalling that drives 1) presynaptic Futsch/MAP1b microtubule dynamics and 2) postsynaptic Frizzled nuclear import (FNI). Taken together, these findings indicate UDP-sugar balance is a key modifier of neurological outcomes in all three interacting galactosemia disease models, suggest that Futsch homolog MAP1B and the Wnt Frizzled receptor may be disease-relevant targets in epimerase and transferase galactosemias, and identify UGP as promising new potential therapeutic target for galactosemia neuropathology.

  2. 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.

  3. Prostaglandin signaling suppresses beneficial microglial function in Alzheimer’s disease models

    PubMed Central

    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.

    2014-01-01

    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

  4. A central role for TOR signalling in a yeast model for juvenile CLN3 disease

    PubMed Central

    Bond, Michael E.; Brown, Rachel; Rallis, Charalampos; Bähler, Jürg; Mole, Sara E.

    2015-01-01

    Yeasts provide an excellent genetically tractable eukaryotic system for investigating the function of genes in their biological context, and are especially relevant for those conserved genes that cause disease. We study the role of btn1, the orthologue of a human gene that underlies an early onset neurodegenerative disease (juvenile CLN3 disease, neuronal ceroid lipofuscinosis (NCLs) or Batten disease) in the fission yeast Schizosaccharomyces pombe. A global screen for genetic interactions with btn1 highlighted a conserved key signalling hub in which multiple components functionally relate to this conserved disease gene. This signalling hub includes two major mitogen-activated protein kinase (MAPK) cascades, and centers on the Tor kinase complexes TORC1 and TORC2. We confirmed that yeast cells modelling CLN3 disease exhibit features consistent with dysfunction in the TORC pathways, and showed that modulating TORC function leads to a comprehensive rescue of defects in this yeast disease model. The same pathways may be novel targets in the development of therapies for the NCLs and related diseases. PMID:28357272

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

    PubMed

    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.

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

    SciTech Connect

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

    2007-05-01

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

  7. Sex difference in body weight gain and leptin signaling in hypocretin/orexin deficient mouse models.

    PubMed

    Fujiki, Nobuhiro; Yoshida, Yasushi; Zhang, Shengwen; Sakurai, Takeshi; Yanagisawa, Masashi; Nishino, Seiji

    2006-09-01

    Recent studies in human and animal models of narcolepsy have suggested that obesity in narcolepsy may be due to deficiency of hypocretin signaling, and is also under the influence of environmental factors and the genetic background. In the current study, using two hypocretin/orexin deficient narcoleptic mouse models (i.e. preproorexin knockout (KO) and orexin/ataxin-3 transgenic (TG) mice) with cross-sectional assessments, we have further analyzed factors affecting obesity. We found that both KO and TG narcoleptic mice with mixed genetic backgrounds (N4-5, 93.75-96.88% genetic composition of C57BL/6) tended to be heavier than wild type (WT) mice of 100-200 days old. The body weight of heterozygous mice was intermediate between those of KO and WT mice. Obesity was more prominent in females in both KO and TG narcoleptic mice and was associated with higher serum leptin levels, suggesting a partial leptin resistance. Obesity is less prominent in the congenic TG narcoleptic mice, but is still evident in females. Our results confirmed that hypocretin/orexin ligand deficiency is one of the critical factors for the obese tendency in narcolepsy. However, multiple factors are also likely to affect this phenotype, and a sex difference specific alteration of leptin-hypocretin signaling may be involved.

  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. 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).

  10. On Accuracy Order of Fourier Coefficients Computation for Periodic Signal Processing Models

    NASA Astrophysics Data System (ADS)

    Korytov, I. V.; Golosov, S. E.

    2016-08-01

    The article is devoted to construction piecewise constant functions for modelling periodic signal. The aim of the paper is to suggest a way to avoid discontinuity at points where waveform values are obtained. One solution is to introduce shifted step function whose middle points within its partial intervals coincide with points of observation. This means that large oscillations of Fourier partial sums move to new jump discontinuities where waveform values are not obtained. Furthermore, any step function chosen to model periodic continuous waveform determines a way to calculate Fourier coefficients. In this case, the technique is certainly a weighted rectangular quadrature rule. Here, the weight is either unit or trigonometric. Another effect of the solution consists in following. The shifted function leads to application midpoint quadrature rules for computing Fourier coefficients. As a result the formula for zero coefficient transforms into trapezoid rule. In the same time, the formulas for other coefficients remain of rectangular type.

  11. Channel noise enhances signal detectability in a model of acoustic neuron through the stochastic resonance paradigm.

    PubMed

    Liberti, M; Paffi, A; Maggio, F; De Angelis, A; Apollonio, F; d'Inzeo, G

    2009-01-01

    A number of experimental investigations have evidenced the extraordinary sensitivity of neuronal cells to weak input stimulations, including electromagnetic (EM) fields. Moreover, it has been shown that biological noise, due to random channels gating, acts as a tuning factor in neuronal processing, according to the stochastic resonant (SR) paradigm. In this work the attention is focused on noise arising from the stochastic gating of ionic channels in a model of Ranvier node of acoustic fibers. The small number of channels gives rise to a high noise level, which is able to cause a spike train generation even in the absence of stimulations. A SR behavior has been observed in the model for the detection of sinusoidal signals at frequencies typical of the speech.

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

    PubMed

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

    2014-09-03

    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.

  13. On the Use of Covariates in a Latent Class Signal Detection Model, with Applications to Constructed Response Scoring

    ERIC Educational Resources Information Center

    Wang, Zijian Gerald

    2012-01-01

    A latent class signal detection (SDT) model was recently introduced as an alternative to traditional item response theory (IRT) methods in the analysis of constructed response data. This class of models can be represented as restricted latent class models and differ from the IRT approach in the way the latent construct is conceptualized. One…

  14. Data-driven reverse engineering of signaling pathways using ensembles of dynamic models.

    PubMed

    Henriques, David; Villaverde, Alejandro F; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R

    2017-02-01

    Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM's ensemble prediction is not only consistently better than predictions

  15. Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

    PubMed Central

    Henriques, David; Villaverde, Alejandro F.; Banga, Julio R.

    2017-01-01

    Despite significant efforts and remarkable progress, the inference of signaling networks from experimental data remains very challenging. The problem is particularly difficult when the objective is to obtain a dynamic model capable of predicting the effect of novel perturbations not considered during model training. The problem is ill-posed due to the nonlinear nature of these systems, the fact that only a fraction of the involved proteins and their post-translational modifications can be measured, and limitations on the technologies used for growing cells in vitro, perturbing them, and measuring their variations. As a consequence, there is a pervasive lack of identifiability. To overcome these issues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to experimental data, and combines their individual simulations into an ensemble prediction. It also includes a model reduction step to prune spurious interactions and mitigate overfitting. SELDOM is a data-driven method, in the sense that it does not require any prior knowledge of the system: the interaction networks that act as scaffolds for the dynamic models are inferred from data using mutual information. We have tested SELDOM on a number of experimental and in silico signal transduction case-studies, including the recent HPN-DREAM breast cancer challenge. We found that its performance is highly competitive compared to state-of-the-art methods for the purpose of recovering network topology. More importantly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differential equation) models, which can be used for mechanistic interpretations and reliable dynamic predictions in new experimental conditions (i.e. not used in the training). For this task, SELDOM’s ensemble prediction is not only consistently better than predictions

  16. Model-based control of the temporal patterns of intracellular signaling in silico

    PubMed Central

    Murakami, Yohei; Koyama, Masanori; Oba, Shigeyuki; Kuroda, Shinya; Ishii, Shin

    2017-01-01

    The functions of intracellular signal transduction systems are determined by the temporal behavior of intracellular molecules and their interactions. Of the many dynamical properties of the system, the relationship between the dynamics of upstream molecules and downstream molecules is particularly important. A useful tool in understanding this relationship is a methodology to control the dynamics of intracellular molecules with an extracellular stimulus. However, this is a difficult task because the relationship between the levels of upstream molecules and those of downstream molecules is often not only stochastic, but also time-inhomogeneous, nonlinear, and not one-to-one. In this paper, we present an easy-to-implement model-based control method that makes the target downstream molecule to trace a desired time course by changing the concentration of a controllable upstream molecule. Our method uses predictions from Monte Carlo simulations of the model to decide the strength of the stimulus, while using a particle-based approach to make inferences regarding unobservable states. We applied our method to in silico control problems of insulin-dependent AKT pathway model and EGF-dependent Akt pathway model with system noise. We show that our method can robustly control the dynamics of the intracellular molecules against unknown system noise of various strengths, even in the absence of complete knowledge of the true model of the target system. PMID:28275530

  17. Deconvolution of non-stationary physical signals: a smooth variance model for insulin secretion rate

    NASA Astrophysics Data System (ADS)

    Pillonetto, Gianluigi; Bell, Bradley M.

    2004-04-01

    Deconvolution is the process of estimating a system's input using measurements of a causally related output where the relationship between the input and output is known and linear. Regularization parameters are used to balance smoothness of the estimated input with accuracy of the measurement values. In this paper we present a maximum marginal likelihood method for estimating unknown regularization (and other) parameters used during deconvolution of dynamical systems. Our computational approach uses techniques that were developed for Kalman filters and smoothers. As an example application we consider estimating insulin secretion rate (ISR) following an intravenous glucose stimulus. This procedure is referred to in the medical literature as an intravenous glucose tolerance test (IVGTT). This estimation problem is difficult because ISR is a strongly non-stationary signal; it presents a fast peak in the first minutes of the experiment, followed by a smoother release. We use three regularization parameters to define a smooth model for ISR variance. This model takes into account the rapid variation of ISR during the beginning of an IVGTT and its slower variation as time progresses. Simulations are used to assess marginal likelihood estimation of these regularization parameters as well as of other parameters in the system. Simulations are also used to compare our model for ISR variance with other stochastic ISR models. In addition, we apply maximum marginal likelihood and our ISR variance model to real data that have previous ISR estimation results reported in the literature.

  18. Loss of Fractalkine Signaling Exacerbates Axon Transport Dysfunction in a Chronic Model of Glaucoma

    PubMed Central

    Breen, Kevin T.; Anderson, Sarah R.; Steele, Michael R.; Calkins, David J.; Bosco, Alejandra; Vetter, Monica L.

    2016-01-01

    Neurodegeneration in glaucoma results in decline and loss of retinal ganglion cells (RGCs), and is associated with activation of myeloid cells such as microglia and macrophages. The chemokine fractalkine (FKN or Cx3cl1) mediates communication from neurons to myeloid cells. Signaling through its receptor Cx3cr1 has been implicated in multiple neurodegenerative diseases, but the effects on neuronal pathology are variable. Since it is unknown how FKN-mediated crosstalk influences RGC degeneration in glaucoma, we assessed this in a chronic mouse model, DBA/2J. We analyzed a DBA/2J substrain deficient in Cx3cr1, and compared compartmentalized RGC degeneration and myeloid cell responses to those in standard DBA/2J mice. We found that loss of FKN signaling exacerbates axon transport dysfunction, an early event in neurodegeneration, with a significant increase in RGCs with somal accumulation of the axonal protein phosphorylated neurofilament, and reduced retinal expression of genes involved in axon transport, Kif1b, and Atp8a2. There was no change in the loss of Brn3-positive RGCs, and no difference in the extent of damage to the proximal optic nerve, suggesting that the loss of fractalkine signaling primarily affects axon transport. Since Cx3cr1 is specifically expressed in myeloid cells, we assessed changes in retinal microglial number and activation, changes in gene expression, and the extent of macrophage infiltration. We found that loss of fractalkine signaling led to innate immune changes within the retina, including increased infiltration of peripheral macrophages and upregulated nitric oxide synthase-2 (Nos-2) expression in myeloid cells, which contributes to the production of NO and can promote axon transport deficits. In contrast, resident retinal microglia appeared unchanged either in number, morphology, or expression of the myeloid activation marker ionized calcium binding adaptor molecule 1 (Iba1). There was also no significant increase in the proinflammatory

  19. A receptor-based model for dopamine-induced fMRI signal

    PubMed Central

    Mandeville, Joseph. B.; Sander, Christin Y. M.; Jenkins, Bruce G.; Hooker, Jacob M.; Catana, Ciprian; Vanduffel, Wim; Alpert, Nathaniel M.; Rosen, Bruce R.; Normandin, Marc D.

    2013-01-01

    This report describes a multi-receptor physiological model of the fMRI temporal response and signal magnitude evoked by drugs that elevate synaptic dopamine in basal ganglia. The model is formulated as a summation of dopamine’s effects at D1-like and D2-like receptor families, which produce functional excitation and inhibition, respectively, as measured by molecular indicators like adenylate cyclase or neuroimaging techniques like fMRI. Functional effects within the model are described in terms of relative changes in receptor occupancies scaled by receptor densities and neuro-vascular coupling constants. Using literature parameters, the model reconciles many discrepant observations and interpretations of pre-clinical data. Additionally, we present data showing that amphetamine stimulation produces fMRI inhibition at low doses and a biphasic response at higher doses in the basal ganglia of non-human primates (NHP), in agreement with model predictions based upon the respective levels of evoked dopamine. Because information about dopamine release is required to inform the fMRI model, we simultaneously acquired PET 11C-raclopride data in several studies to evaluate the relationship between raclopride displacement and assumptions about dopamine release. At high levels of dopamine release, results suggest that refinements of the model will be required to consistently describe the PET and fMRI data. Overall, the remarkable success of the model in describing a wide range of preclinical fMRI data indicate that this approach will be useful for guiding the design and analysis of basic science and clinical investigations and for interpreting the functional consequences of dopaminergic stimulation in normal subjects and in populations with dopaminergic neuroadaptations. PMID:23466936

  20. A receptor-based model for dopamine-induced fMRI signal.

    PubMed

    Mandeville, Joseph B; Sander, Christin Y M; Jenkins, Bruce G; Hooker, Jacob M; Catana, Ciprian; Vanduffel, Wim; Alpert, Nathaniel M; Rosen, Bruce R; Normandin, Marc D

    2013-07-15

    This report describes a multi-receptor physiological model of the fMRI temporal response and signal magnitude evoked by drugs that elevate synaptic dopamine in basal ganglia. The model is formulated as a summation of dopamine's effects at D1-like and D2-like receptor families, which produce functional excitation and inhibition, respectively, as measured by molecular indicators like adenylate cyclase or neuroimaging techniques like fMRI. Functional effects within the model are described in terms of relative changes in receptor occupancies scaled by receptor densities and neuro-vascular coupling constants. Using literature parameters, the model reconciles many discrepant observations and interpretations of pre-clinical data. Additionally, we present data showing that amphetamine stimulation produces fMRI inhibition at low doses and a biphasic response at higher doses in the basal ganglia of non-human primates (NHP), in agreement with model predictions based upon the respective levels of evoked dopamine. Because information about dopamine release is required to inform the fMRI model, we simultaneously acquired PET (11)C-raclopride data in several studies to evaluate the relationship between raclopride displacement and assumptions about dopamine release. At high levels of dopamine release, results suggest that refinements of the model will be required to consistently describe the PET and fMRI data. Overall, the remarkable success of the model in describing a wide range of preclinical fMRI data indicate that this approach will be useful for guiding the design and analysis of basic science and clinical investigations and for interpreting the functional consequences of dopaminergic stimulation in normal subjects and in populations with dopaminergic neuroadaptations.

  1. Integrated signaling pathway and gene expression regulatory model to dissect dynamics of Escherichia coli challenged mammary epithelial cells.

    PubMed

    den Breems, Nicoline Y; Nguyen, Lan K; Kulasiri, Don

    2014-12-01

    Cells transform external stimuli, through the activation of signaling pathways, which in turn activate gene regulatory networks, in gene expression. As more omics data are generated from experiments, eliciting the integrated relationship between the external stimuli, the signaling process in the cell and the subsequent gene expression is a major challenge in systems biology. The complex system of non-linear dynamic protein interactions in signaling pathways and gene networks regulates gene expression. The complexity and non-linear aspects have resulted in the study of the signaling pathway or the gene network regulation in isolation. However, this limits the analysis of the interaction between the two components and the identification of the source of the mechanism differentiating the gene expression profiles. Here, we present a study of a model of the combined signaling pathway and gene network to highlight the importance of integrated modeling. Based on the experimental findings we developed a compartmental model and conducted several simulation experiments. The model simulates the mRNA expression of three different cytokines (RANTES, IL8 and TNFα) regulated by the transcription factor NFκB in mammary epithelial cells challenged with E. coli. The analysis of the gene network regulation identifies a lack of robustness and therefore sensitivity for the transcription factor regulation. However, analysis of the integrated signaling and gene network regulation model reveals distinctly different underlying mechanisms in the signaling pathway responsible for the variation between the three cytokine's mRNA expression levels. Our key findings reveal the importance of integrating the signaling pathway and gene expression dynamics in modeling. Modeling infers valid research questions which need to be verified experimentally and can assist in the design of future biological experiments.

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

    PubMed

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

    2015-10-30

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

  3. 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

  4. Cryptosporidium parvum-induced ileo-caecal adenocarcinoma and Wnt signaling in a mouse model.

    PubMed

    Benamrouz, Sadia; Conseil, Valerie; Chabé, Magali; Praet, Marleen; Audebert, Christophe; Blervaque, Renaud; Guyot, Karine; Gazzola, Sophie; Mouray, Anthony; Chassat, Thierry; Delaire, Baptiste; Goetinck, Nathalie; Gantois, Nausicaa; Osman, Marwan; Slomianny, Christian; Dehennaut, Vanessa; Lefebvre, Tony; Viscogliosi, Eric; Cuvelier, Claude; Dei-Cas, Eduardo; Creusy, Colette; Certad, Gabriela

    2014-06-01

    Cryptosporidium species are apicomplexan protozoans that are found worldwide. These parasites constitute a large risk to human and animal health. They cause self-limited diarrhea in immunocompetent hosts and a life-threatening disease in immunocompromised hosts. Interestingly, Cryptosporidium parvum has been related to digestive carcinogenesis in humans. Consistent with a potential tumorigenic role of this parasite, in an original reproducible animal model of chronic cryptosporidiosis based on dexamethasone-treated or untreated adult SCID mice, we formerly reported that C. parvum (strains of animal and human origin) is able to induce digestive adenocarcinoma even in infections induced with very low inoculum. The aim of this study was to further characterize this animal model and to explore metabolic pathways potentially involved in the development of C. parvum-induced ileo-caecal oncogenesis. We searched for alterations in genes or proteins commonly involved in cell cycle, differentiation or cell migration, such as β-catenin, Apc, E-cadherin, Kras and p53. After infection of animals with C. parvum we demonstrated immunohistochemical abnormal localization of Wnt signaling pathway components and p53. Mutations in the selected loci of studied genes were not found after high-throughput sequencing. Furthermore, alterations in the ultrastructure of adherens junctions of the ileo-caecal neoplastic epithelia of C. parvum-infected mice were recorded using transmission electron microscopy. In conclusion, we found for the first time that the Wnt signaling pathway, and particularly the cytoskeleton network, seems to be pivotal for the development of the C. parvum-induced neoplastic process and cell migration of transformed cells. Furthermore, this model is a valuable tool in understanding the host-pathogen interactions associated with the intricate infection process of this parasite, which is able to modulate host cytoskeleton activities and several host-cell biological

  5. Empirical Analysis and Modeling of Stop-Line Crossing Time and Speed at Signalized Intersections.

    PubMed

    Tang, Keshuang; Wang, Fen; Yao, Jiarong; Sun, Jian

    2016-12-23

    In China, a flashing green (FG) indication of 3 s followed by a yellow (Y) indication of 3 s is commonly applied to end the green phase at signalized intersections. Stop-line crossing behavior of drivers during such a phase transition period significantly influences safety performance of signalized intersections. The objective of this study is thus to empirically analyze and model drivers' stop-line crossing time and speed in response to the specific phase transition period of FG and Y. High-resolution trajectories for 1465 vehicles were collected at three rural high-speed intersections with a speed limit of 80 km/h and two urban intersections with a speed limit of 50 km/h in Shanghai. With the vehicle trajectory data, statistical analyses were performed to look into the general characteristics of stop-line crossing time and speed at the two types of intersections. A multinomial logit model and a multiple linear regression model were then developed to predict the stop-line crossing patterns and speeds respectively. It was found that the percentage of stop-line crossings during the Y interval is remarkably higher and the stop-line crossing time is approximately 0.7 s longer at the urban intersections, as compared with the rural intersections. In addition, approaching speed and distance to the stop-line at the onset of FG as well as area type significantly affect the percentages of stop-line crossings during the FG and Y intervals. Vehicle type and stop-line crossing pattern were found to significantly influence the stop-line crossing speed, in addition to the above factors. The red-light-running seems to occur more frequently at the large intersections with a long cycle length.

  6. Empirical Analysis and Modeling of Stop-Line Crossing Time and Speed at Signalized Intersections

    PubMed Central

    Tang, Keshuang; Wang, Fen; Yao, Jiarong; Sun, Jian

    2016-01-01

    In China, a flashing green (FG) indication of 3 s followed by a yellow (Y) indication of 3 s is commonly applied to end the green phase at signalized intersections. Stop-line crossing behavior of drivers during such a phase transition period significantly influences safety performance of signalized intersections. The objective of this study is thus to empirically analyze and model drivers’ stop-line crossing time and speed in response to the specific phase transition period of FG and Y. High-resolution trajectories for 1465 vehicles were collected at three rural high-speed intersections with a speed limit of 80 km/h and two urban intersections with a speed limit of 50 km/h in Shanghai. With the vehicle trajectory data, statistical analyses were performed to look into the general characteristics of stop-line crossing time and speed at the two types of intersections. A multinomial logit model and a multiple linear regression model were then developed to predict the stop-line crossing patterns and speeds respectively. It was found that the percentage of stop-line crossings during the Y interval is remarkably higher and the stop-line crossing time is approximately 0.7 s longer at the urban intersections, as compared with the rural intersections. In addition, approaching speed and distance to the stop-line at the onset of FG as well as area type significantly affect the percentages of stop-line crossings during the FG and Y intervals. Vehicle type and stop-line crossing pattern were found to significantly influence the stop-line crossing speed, in addition to the above factors. The red-light-running seems to occur more frequently at the large intersections with a long cycle length. PMID:28025558

  7. 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.

  8. Dysfunctional oleoylethanolamide signaling in a mouse model of Prader-Willi syndrome.

    PubMed

    Igarashi, Miki; Narayanaswami, Vidya; Kimonis, Virginia; Galassetti, Pietro M; Oveisi, Fariba; Jung, Kwang-Mook; Piomelli, Daniele

    2017-03-01

    Prader-Willi syndrome (PWS), the leading genetic cause of obesity, is characterized by a striking hyperphagic behavior that can lead to obesity, type-2 diabetes, cardiovascular disease and death. The molecular mechanism underlying impaired satiety in PWS is unknown. Oleoylethanolamide (OEA) is a lipid mediator involved in the control of feeding, body weight and energy metabolism. OEA produced by small-intestinal enterocytes during dietary fat digestion activates type-α peroxisome proliferator-activated receptors (PPAR-α) to trigger an afferent signal that causes satiety. Emerging evidence from genetic and human laboratory studies suggests that deficits in OEA-mediated signaling might be implicated in human obesity. In the present study, we investigated whether OEA contributes to feeding dysregulation in Magel2(m+/p-) (Magel2 KO) mice, an animal model of PWS. Fasted/refed male Magel2 KO mice eat more than do their wild-type littermates and become overweight with age. Meal pattern analyses show that hyperphagia in Magel2 KO is due to increased meal size and meal duration rather than to lengthening of the intermeal interval, which is suggestive of a defect in mechanisms underlying satiation. Food-dependent OEA accumulation in jejunum and fasting OEA levels in plasma are significantly greater in Magel2 KO mice than in wild-type controls. Together, these findings indicate that deletion of the Magel2 gene is accompanied by marked changes in OEA signaling. Importantly, intraperitoneal administration of OEA (10mg/kg) significantly reduces food intake in fasted/refed Magel2 KO mice, pointing to a possible use of this natural compound to control hunger in PWS.

  9. 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

  10. A Comparison of Estimates of Atmospheric Effects on Signal Propagation Using ITU Models: Initial Study Results

    NASA Astrophysics Data System (ADS)

    Morabito, D. D.

    2014-11-01

    This article provides details on a comparison performed on calculated atmospheric effects on signal propagation using different methods for the Deep Space Network (DSN) and two Near Earth Network (NEN) sites commonly used in telecommunications link budgets. Atmospheric attenuation and scintillation fading are two of the many contributors that need to be taken into account in such link budgets between transmitter and receiver. Although atmospheric noise temperature increase is another contributor (at the receiver), it is well related to atmospheric attenuation through appropriate model equations. Telecommunication engineers working NEN link budgets make use of data and models obtained from the International Telecommunication Union (ITU) in order to estimate atmospheric effects. Such effects include atmospheric attenuation (gaseous, rain, and cloud), atmospheric noise temperature contribution, and scintillation. Because most NEN links usually operate at very high margins, uncertainties in the ITU models were not much of a concern in the past as they tended to be conservative, in comparison to links of the DSN that operate at low margins and thus require more accurate statistics on atmospheric effects. Such statistics for the DSN links make use of brightness temperature measurements from multiyear water vapor radiometer (WVR) data from instruments operating at the DSN sites. Atmospheric attenuation statistics derived from WVR data are well documented and are published by the DSN. Thus, the DSN sites make a good testbed in which to cross-compare atmospheric loss statistics with those derived from ITU data and models.

  11. Modeling the effects of distortion, contrast, and signal-to-noise ratio on stereophotogrammetric range mapping

    NASA Astrophysics Data System (ADS)

    Sellar, R. Glenn; Deen, Robert G.; Huffman, William C.; Willson, Reginald G.

    2016-09-01

    Stereophotogrammetry typically employs a pair of cameras, or a single moving camera, to acquire pairs of images from different camera positions, in order to create a three dimensional `range map' of the area being observed. Applications of this technique for building three-dimensional shape models include aerial surveying, remote sensing, machine vision, and robotics. Factors that would be expected to affect the quality of the range maps include the projection function (distortion) of the lenses and the contrast (modulation) and signal-to-noise ratio (SNR) of the acquired image pairs. Basic models of the precision with which the range can be measured assume a pinhole-camera model of the geometry, i.e. that the lenses provide perspective projection with zero distortion. Very-wide-angle or `fisheye' lenses, however (for e.g. those used by robotic vehicles) typically exhibit projection functions that differ significantly from this assumption. To predict the stereophotogrammetric range precision for such applications, we extend the model to the case of an equidistant lens projection function suitable for a very-wide-angle lens. To predict the effects of contrast and SNR on range precision, we perform numerical simulations using stereo image pairs acquired by a stereo camera pair on NASA's Mars rover Curiosity. Contrast is degraded and noise is added to these data in a controlled fashion and the effects on the quality of the resulting range maps are assessed.

  12. Involvement of the Janus Kinase/Signal Transducer and Activator of Transcription Signaling Pathway in Multiple Sclerosis and the Animal Model of Experimental Autoimmune Encephalomyelitis

    PubMed Central

    Liu, Yudong; McFarland, Braden C.; Qin, Hongwei

    2014-01-01

    Multiple sclerosis (MS) and its animal model of experimental autoimmune encephalomyelitis (EAE) are characterized by focal inflammatory infiltrates into the central nervous system, demyelinating lesions, axonal damage, and abundant production of cytokines that activate immune cells and damage neurons and oligodendrocytes, including interleukin-12 (IL-12), IL-6, IL-17, IL-21, IL-23, granulocyte macrophage-colony stimulating factor, and interferon-gamma. The Janus Kinase/Signal Transducer and Activator of Transcription (JAK/STAT) signaling pathway mediates the biological activities of these cytokines and is essential for the development and regulation of immune responses. Dysregulation of the JAK/STAT pathway contributes to numerous autoimmune diseases, including MS/EAE. The JAK/STAT pathway is aberrantly activated in MS/EAE because of excessive production of cytokines, loss of expression of negative regulators such as suppressors of cytokine signaling proteins, and significant enrichment of genes encoding components of the JAK/STAT pathway, including STAT3. Specific JAK/STAT inhibitors have been used in numerous preclinical models of MS and demonstrate beneficial effects on the clinical course of disease and attenuation of innate and adaptive immune responses. In addition, other drugs such as statins, glatiramer acetate, laquinimod, and fumarates have beneficial effects that involve inhibition of the JAK/STAT pathway. We conclude by discussing the feasibility of the JAK/STAT pathway as a target for neuroinflammatory diseases. PMID:25084174

  13. Fetal signaling through placental structure and endocrine function: illustrations and implications from a nonhuman primate model.

    PubMed

    Rutherford, Julienne N

    2009-01-01

    The placenta is a transmitter of fetal need and fetal quality, interfacing directly with maternal physiology and ecology. Plasticity of placental structure and function across the developmental timeframe of gestation may serve as an important tool by which a fetus calibrates its growth to shifting maternal ecology and resource availability, and thereby signals its quality and adaptability to a changing environment. Signals of this quality may be conveyed by the size of the placental interface, an important marker of fetal access to maternal resources, or by production of placental insulin-like growth factor-II, a driver of fetoplacental growth. Litter size variation in the common marmoset monkey offers the opportunity to explore intrauterine resource allocation and placental plasticity in an important nonhuman primate model. Triplet marmosets are born at lower birth weights and have poorer postnatal outcomes and survivorship than do twins; triplet placentas differ in placental efficiency, microscopic morphology, and endocrine function. Through placental plasticity, triplet fetuses are able to adjust functional access to maternal resources in a way that allows pregnancy to proceed. However, the costs of such mechanisms may relate to reduced fetal growth and altered postnatal outcomes, with the potential to lead to adverse adult health consequences, suggesting an important link between the placenta itself and the developmental origins of health and disease.

  14. Modelling TFE renal cell carcinoma in mice reveals a critical role of WNT signaling

    PubMed Central

    Calcagnì, Alessia; kors, Lotte; Verschuren, Eric; De Cegli, Rossella; Zampelli, Nicolina; Nusco, Edoardo; Confalonieri, Stefano; Bertalot, Giovanni; Pece, Salvatore; Settembre, Carmine; Malouf, Gabriel G; Leemans, Jaklien C; de Heer, Emile; Salvatore, Marco; Peters, Dorien JM; Di Fiore, Pier Paolo; Ballabio, Andrea

    2016-01-01

    TFE-fusion renal cell carcinomas (TFE-fusion RCCs) are caused by chromosomal translocations that lead to overexpression of the TFEB and TFE3 genes (Kauffman et al., 2014). The mechanisms leading to kidney tumor development remain uncharacterized and effective therapies are yet to be identified. Hence, the need to model these diseases in an experimental animal system (Kauffman et al., 2014). Here, we show that kidney-specific TFEB overexpression in transgenic mice, resulted in renal clear cells, multi-layered basement membranes, severe cystic pathology, and ultimately papillary carcinomas with hepatic metastases. These features closely recapitulate those observed in both TFEB- and TFE3-mediated human kidney tumors. Analysis of kidney samples revealed transcriptional induction and enhanced signaling of the WNT β-catenin pathway. WNT signaling inhibitors normalized the proliferation rate of primary kidney cells and significantly rescued the disease phenotype in vivo. These data shed new light on the mechanisms underlying TFE-fusion RCCs and suggest a possible therapeutic strategy based on the inhibition of the WNT pathway. DOI: http://dx.doi.org/10.7554/eLife.17047.001 PMID:27668431

  15. Emergence of complex dynamics in a simple model of signaling networks

    PubMed Central

    Amaral, Luís A. N.; Díaz-Guilera, Albert; Moreira, Andre A.; Goldberger, Ary L.; Lipsitz, Lewis A.

    2004-01-01

    Various physical, social, and biological systems generate complex fluctuations with correlations across multiple time scales. In physiologic systems, these long-range correlations are altered with disease and aging. Such correlated fluctuations in living systems have been attributed to the interaction of multiple control systems; however, the mechanisms underlying this behavior remain unknown. Here, we show that a number of distinct classes of dynamical behaviors, including correlated fluctuations characterized by 1/f scaling of their power spectra, can emerge in networks of simple signaling units. We found that, under general conditions, complex dynamics can be generated by systems fulfilling the following two requirements, (i) a “small-world” topology and (ii) the presence of noise. Our findings support two notable conclusions. First, complex physiologic-like signals can be modeled with a minimal set of components; and second, systems fulfilling conditions i and ii are robust to some degree of degradation (i.e., they will still be able to generate 1/f dynamics). PMID:15505227

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

    PubMed

    Vanni, Simo; Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

    2015-08-01

    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.

  17. 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

  18. A spectral model for signal elements isolated from zebrafish photopic electroretinogram

    PubMed Central

    Nelson, Ralph; Singla, Nirmish

    2009-01-01

    The zebrafish photopic ERG sums isolatable elements. In each element red, blue, green and UV (r, g, b, u) cone signals combine in a way that reflects retinal organization. ERG responses to monochromatic stimuli of different wavelengths and irradiances were recorded on a white, rod suppressing background using superfused eyecups. Onset elements were isolated with glutamatergic blockers and response subtractions. CNQX blocked ionotropic (AMPA/kainate) glutamate receptors; L-AP4 or CPPG blocked metabotropic (mGluR6) glutamate receptors; TBOA blocked glutamate transporters; and L-Aspartate inactivated all glutamatergic mechanisms. Seven elements emerged: photopic PIII, the L-Aspartate-isolated cone response; b1, a CNQX-sensitive early b-wave element of inner retinal origin; PII, a photopic, CNQX-insensitive, composite b-wave element from ON bipolar cells; PIIm, an L-AP4/CPPG-sensitive, CNQX-insensitive metabotropic sub-element of PII; PIInm, an L-AP4/CPPG/CNQX-insensitive, non-metabotropic sub-element of PII; a1nm, a TBOA-sensitive, CNQX/L-AP4/CPPG-insensitive, non-metabotropic, post-photoreceptor a-wave element; and a2, a CNQX-sensitive a-wave element linked to OFF bipolar cells. The first five elements were fit with a spectral model that demonstrates independence of cone color pathways. From this Vmax and half-saturation values (k) for the contributing r- g- b- and u-cone signals were calculated. Two signal patterns emerged. For PIII or PIInm the Vmax order was Vr > Vg ≫ Vb ≈ Vu. For b1, PII, and PIIm the Vmax order was Vr ≈ Vb > Vg > Vu. In either pattern u-cone amplitude (Vu) was smallest, but u-cone sensitivity (ku362) was greatest, some 10-30 times greater than r-cone (kr570). The spectra of b1/PII/PIIm elements peaked near b-cone and u-cone absorbance maxima regardless of criteria, but the spectra of PIII/PIInm elements shifted from b- towards r-cone absorbance maxima as criterion levels increased. The greatest gains in Vmax relative to PIII occurred for

  19. Investigation of model based beamforming and Bayesian inversion signal processing methods for seismic localization of underground sources.

    PubMed

    Oh, Geok Lian; Brunskog, Jonas

    2014-08-01

    Techniques have been studied for the localization of an underground source with seismic interrogation signals. Much of the work has involved defining either a P-wave acoustic model or a dispersive surface wave model to the received signal and applying the time-delay processing technique and frequency-wavenumber processing to determine the location of the underground tunnel. Considering the case of determining the location of an underground tunnel, this paper proposed two physical models, the acoustic approximation ray tracing model and the finite difference time domain three-dimensional (3D) elastic wave model to represent the received seismic signal. Two localization algorithms, beamforming and Bayesian inversion, are developed for each physical model. The beam-forming algorithms implemented are the modified time-and-delay beamformer and the F-K beamformer. Inversion is posed as an optimization problem to estimate the unknown position variable using the described physical forward models. The proposed four methodologies are demonstrated and compared using seismic signals recorded by geophones set up on ground surface generated by a surface seismic excitation. The examples show that for field data, inversion for localization is most advantageous when the forward model completely describe all the elastic wave components as is the case of the FDTD 3D elastic model.

  20. Testing signal-detection models of yes/no and two-alternative forced-choice recognition memory.

    PubMed

    Jang, Yoonhee; Wixted, John T; Huber, David E

    2009-05-01

    The current study compared 3 models of recognition memory in their ability to generalize across yes/no and 2-alternative forced-choice (2AFC) testing. The unequal-variance signal-detection model assumes a continuous memory strength process. The dual-process signal-detection model adds a thresholdlike recollection process to a continuous familiarity process. The mixture signal-detection model assumes a continuous memory strength process, but the old item distribution consists of a mixture of 2 distributions with different means. Prior efforts comparing the ability of the models to characterize data from both test formats did not consider the role of parameter reliability, which can be critical when comparing models that differ in flexibility. Parametric bootstrap simulations revealed that parameter regressions based on separate fits of each test type only served to identify the least flexible model. However, simultaneous fits of receiver-operating characteristic data from both test types with goodness-of-fit adjusted with Akaike's information criterion (AIC) successfully recovered the true model that generated the data. With AIC and simultaneous fits to real data, the unequal-variance signal-detection model was found to provide the best account across yes/no and 2AFC testing.

  1. Delayed signatures of underground nuclear explosions

    DOE PAGES

    Carrigan, Charles R.; Sun, Yunwei; Hunter, Steven L.; ...

    2016-03-16

    Radionuclide signals from underground nuclear explosions (UNEs) are strongly influenced by the surrounding hydrogeologic regime. One effect of containment is delay of detonation-produced radioxenon reaching the surface as well as lengthening of its period of detectability compared to uncontained explosions. Using a field-scale tracer experiment, we evaluate important transport properties of a former UNE site. Here, we observe the character of signals at the surface due to the migration of gases from the post-detonation chimney under realistic transport conditions. Background radon signals are found to be highly responsive to cavity pressurization suggesting that large local radon anomalies may be anmore » indicator of a clandestine UNE. Computer simulations, using transport properties obtained from the experiment, track radioxenon isotopes in the chimney and their migration to the surface. They show that the chimney surrounded by a fractured containment regime behaves as a leaky chemical reactor regarding its effect on isotopic evolution introducing a dependence on nuclear yield not previously considered. This evolutionary model for radioxenon isotopes is validated by atmospheric observations of radioxenon from a 2013 UNE in the Democratic People’s Republic of Korea (DPRK). In conclusion, our model produces results similar to isotopic observations with nuclear yields being comparable to seismic estimates.« less

  2. Delayed signatures of underground nuclear explosions

    SciTech Connect

    Carrigan, Charles R.; Sun, Yunwei; Hunter, Steven L.; Ruddle, David G.; Wagoner, Jeffrey L.; Myers, Katherine B. L.; Emer, Dudley F.; Drellack, Sigmund L.; Chipman, Veraun D.

    2016-03-16

    Radionuclide signals from underground nuclear explosions (UNEs) are strongly influenced by the surrounding hydrogeologic regime. One effect of containment is delay of detonation-produced radioxenon reaching the surface as well as lengthening of its period of detectability compared to uncontained explosions. Using a field-scale tracer experiment, we evaluate important transport properties of a former UNE site. Here, we observe the character of signals at the surface due to the migration of gases from the post-detonation chimney under realistic transport conditions. Background radon signals are found to be highly responsive to cavity pressurization suggesting that large local radon anomalies may be an indicator of a clandestine UNE. Computer simulations, using transport properties obtained from the experiment, track radioxenon isotopes in the chimney and their migration to the surface. They show that the chimney surrounded by a fractured containment regime behaves as a leaky chemical reactor regarding its effect on isotopic evolution introducing a dependence on nuclear yield not previously considered. This evolutionary model for radioxenon isotopes is validated by atmospheric observations of radioxenon from a 2013 UNE in the Democratic People’s Republic of Korea (DPRK). In conclusion, our model produces results similar to isotopic observations with nuclear yields being comparable to seismic estimates.

  3. Delayed signatures of underground nuclear explosions

    PubMed Central

    Carrigan, Charles R.; Sun, Yunwei; Hunter, Steven L.; Ruddle, David G.; Wagoner, Jeffrey L.; Myers, Katherine B. L.; Emer, Dudley F.; Drellack, Sigmund L.; Chipman, Veraun D.

    2016-01-01

    Radionuclide signals from underground nuclear explosions (UNEs) are strongly influenced by the surrounding hydrogeologic regime. One effect of containment is delay of detonation-produced radioxenon reaching the surface as well as lengthening of its period of detectability compared to uncontained explosions. Using a field-scale tracer experiment, we evaluate important transport properties of a former UNE site. We observe the character of signals at the surface due to the migration of gases from the post-detonation chimney under realistic transport conditions. Background radon signals are found to be highly responsive to cavity pressurization suggesting that large local radon anomalies may be an indicator of a clandestine UNE. Computer simulations, using transport properties obtained from the experiment, track radioxenon isotopes in the chimney and their migration to the surface. They show that the chimney surrounded by a fractured containment regime behaves as a leaky chemical reactor regarding its effect on isotopic evolution introducing a dependence on nuclear yield not previously considered. This evolutionary model for radioxenon isotopes is validated by atmospheric observations of radioxenon from a 2013 UNE in the Democratic People’s Republic of Korea (DPRK). Our model produces results similar to isotopic observations with nuclear yields being comparable to seismic estimates. PMID:26979288

  4. On the influence of time-series length in EMD to extract frequency content: simulations and models in biomedical signals.

    PubMed

    Fonseca-Pinto, R; Ducla-Soares, J L; Araújo, F; Aguiar, P; Andrade, A

    2009-07-01

    In this paper, fractional Gaussian noise (fGn) was used to simulate a homogeneously spreading broadband signal without any dominant frequency band, and to perform a simulation study about the influence of time-series length in the number of intrinsic mode functions (IMFs) obtained after empirical mode decomposition (EMD). In this context three models are presented. The first two models depend on the Hurst exponent H, and the last one is designed for small data lengths, in which the number of IMFs after EMD is obtained based on the regularity of the signal, and depends on an index measure of regularity. These models contribute to a better understanding of the EMD decomposition through the evaluation of its performance in fGn signals. Since an analytical formulation to evaluate the EMD performance is not available, using well-known signals allows for a better insight into the process. The last model presented is meant for application to real data. Its purpose is to predict, in function of the regularity signal, the time-series length that should be used when one wants to divide the spectrum into a pre-determined number of modes, corresponding to different frequency bands, using EMD. This is the case, e.g., in heart rate and blood pressure signals, used to assess sympathovagal balance in the central nervous system.

  5. FMCW CSAR Doppler shifting correction and the layover phenomenon analysising at a new received signal model

    NASA Astrophysics Data System (ADS)

    Song, Depeng; Qu, Yi; Xie, Yuehui

    2016-10-01

    Because of go-stop mode not applying to FMCW CSAR (frequency modulated continuous wave circular synthetic aperture radar), received signal include Doppler shifting result from the radar fly in one period, which have a bad effect on the quality of imaging in wide-field FMCW CSAR. However the compensation functions of liner SAR are not suitable for CSAR. To solve the problem, the paper rebuild a received mode and elicit the Doppler shifting. At the same time, based on the model, the paper analysis the layover phenomenon while obtaining two-dimensional (2D) representations of 3D large scenes due to the wide-field FMCW CSAR and simulate the phenomenon. By the simulation, the effect of the layover can be expressed clearly.

  6. Boosted top quark signals for heavy vector boson excitations in a universal extra dimension model

    SciTech Connect

    Bhattacherjee, Biplob; Raychaudhuri, Sreerup; Sridhar, K.; Guchait, Monoranjan

    2010-09-01

    In view of the fact that the n=1 Kaluza-Klein (KK) modes in a model with a universal extra dimension could mimic supersymmetry signatures at the LHC, it is necessary to look for the n=2 KK modes, which have no analogues in supersymmetry. We discuss the possibility of searching for heavy n=2 vector boson resonances--especially the g{sub 2}--through their decays to a highly boosted top quark-antiquark pair using recently developed top-jet tagging techniques in the hadronic channel. It is shown that tt signals from the n=2 gluon resonance are as efficient a discovery mode at the LHC as dilepton channels from the {gamma}{sub 2} and Z{sub 2} resonances.

  7. 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

  8. Atmospheric transport modelling of time resolved 133Xe emissions from the isotope production facility ANSTO, Australia.

    PubMed

    Schöppner, M; Plastino, W; Hermanspahn, N; Hoffmann, E; Kalinowski, M; Orr, B; Tinker, R

    2013-12-01

    The verification of the Comprehensive Nuclear-Test Ban Treaty (CTBT) relies amongst other things on the continuous and worldwide monitoring of radioxenon. The characterization of the existing and legitimate background, which is produced mainly by nuclear power plants and isotope production facilities, is of high interest to improve the capabilities of the monitoring network. However, the emissions from legitimate sources can usually only be estimated. For this paper historic source terms of (133)Xe emissions from the isotope production facility at ANSTO, Sydney, Australia, have been made available in a daily resolution. Based on these high resolution data, different source term sets with weekly, monthly and yearly time resolution have been compiled. These different sets are then applied together with atmospheric transport modelling (ATM) to predict the concentration time series at two radioxenon monitoring stations. The results are compared with each other in order to examine the improvement of the prediction capability depending on the used time resolution of the most dominant source term in the region.

  9. 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.

  10. A consistent model for leptogenesis, dark matter and the IceCube signal

    NASA Astrophysics Data System (ADS)

    Fiorentin, M. Re; Niro, V.; Fornengo, N.

    2016-11-01

    We discuss a left-right symmetric extension of the Standard Model in which the three additional right-handed neutrinos play a central role in explaining the baryon asymmetry of the Universe, the dark matter abundance and the ultra energetic signal detected by the IceCube experiment. The energy spectrum and neutrino flux measured by IceCube are ascribed to the decays of the lightest right-handed neutrino N 1, thus fixing its mass and lifetime, while the production of N 1 in the primordial thermal bath occurs via a freeze-in mechanism driven by the additional SU(2) R interactions. The constraints imposed by IceCube and the dark matter abundance allow nonetheless the heavier right-handed neutrinos to realize a standard type-I seesaw leptogenesis, with the B - L asymmetry dominantly produced by the next-to-lightest neutrino N 2. Further consequences and predictions of the model are that: the N 1 production implies a specific power-law relation between the reheating temperature of the Universe and the vacuum expectation value of the SU(2) R triplet; leptogenesis imposes a lower bound on the reheating temperature of the Universe at 7 × 109 GeV. Additionally, the model requires a vanishing absolute neutrino mass scale m 1 ≃ 0.

  11. 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

  12. Computational modeling of chemotactic signaling and aggregation of microglia around implantation site during deep brain stimulation

    NASA Astrophysics Data System (ADS)

    Silchenko, A. N.; Tass, P. A.

    2013-10-01

    It is well established that prolonged electrical stimulation of brain tissue causes massive release of ATP in the extracellular space. The released ATP and the products of its hydrolysis, such as ADP and adenosine, become the main elements mediating chemotactic sensitivity and motility of microglial cells via subsequent activation of P2Y2,12 as well as A3A and A2A adenosine receptors. The size of the sheath around the electrode formed by the microglial cells is an important criterion for the optimization of the parameters of electrical current delivered to brain tissue. Here, we study a purinergic signaling pathway underlying the chemotactic motion of microglia towards the implanted electrode during deep brain stimulation. We present a computational model describing formation of a stable aggregate around the implantation site due to the joint chemo-attractive action of ATP and ADP together with a mixed influence of extracellular adenosine. The model was built in accordance with the classical Keller-Segel approach and includes an equation for the cells' density as well as equations describing the hydrolysis of extracellular ATP via successive reaction steps ATP →ADP →AMP →adenosine. The results of our modeling allowed us to reveal the dependence of the width of the encapsulating layer around the electrode on the amount of ATP released due to permanent electrical stimulation. The dependences of the aggregates' size on the parameter governing the nonlinearity of interaction between extracellular adenosine and adenosine receptors are also analyzed.

  13. Simulation and analysis of GPR signal based on stochastic media model with an ellipsoidal autocorrelation function

    NASA Astrophysics Data System (ADS)

    Jiang, Zimeng; Zeng, Zhaofa; Li, Jing; Liu, Fengshan; Li, Wenben

    2013-12-01

    Target detection using ground penetrating radar (GPR) is based on the contrast between the electrical parameters of the target and the background medium, such as dielectric permittivity, conductivity and permeability. The application mainly concentrates on the detection of the medium interface and the target shape. In any theoretical study, a simulation model is built with a homogeneous medium. However, real detection encounters heterogeneous media which might produce scattering and diffraction at electrical interfaces and distort the radar pulse shape and affect the detection resolution. In this paper, we build multi-scale random media model with an ellipsoidal autocorrelation function and use FDTD method to simulate the GPR signal response. We then estimate and analyze the arrival time, layer thickness, permittivity and the physics relation in different scale random models according to the S transform method and the transmission wave method. The results demonstrate that we can use GPR to obtain geophysical information of multi-scale heterogeneous media, and provide a foundation for real media detection and complex media inversion.

  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. Model order estimation for blind source separation of multichannel magnetoencephalogram and electroencephalogram signals.

    PubMed

    Hesse, Christian W

    2008-01-01

    Most blind source separation (BSS) approaches - especially independent component analysis (ICA) - assume a noiseless mixture of the same number of sources as sensors. It is doubtful, however, whether this assumption actually holds for multichannel magnetoencephalogram (MEG) and electroencephalogram (EEG) measurements comprising a large number of channels. Corroborating and extending previous results, this work further examines the utility of second-order statistical methods based on probabilistic principal component analysis (PPCA) and factor analysis (FA) models for estimating the number of underlying sources in multichannel MEG and EEG. Compared with conventional PCA-based eigenvalue thresholding, both PPCA and FA approaches yield stable model order estimates which are almost independent of total signal power. The FA model provides a more optimal description of both MEG and EEG data than PPCA, in terms of balancing goodness-of-fit and parsimony. These findings add to the growing evidence that anisotropic 'sensor noise' may be a statistically robust characteristic of both the EEG and MEG, which most BSS algorithms and applications do not address.

  16. Real-time calibration of platoon dispersion model to optimize the coordinated traffic signal timing in ATMS networks

    SciTech Connect

    Yu, L.

    1999-06-01

    Vehicles form platoons at the exit point of a given traffic signal, which will disperse while they progress along the link towards the next downstream traffic signal. The platoons may disperse either more quickly or slowly depending on the actual road geometric and traffic conditions between the two adjacent intersections of interest. The adequate modeling and description of the platoon dispersion behavior ultimately affect the quality of the coordinated traffic signal timings. At present, the most widely used modeling method of platoon dispersion is the TRANSYT`s macroscopic platoon dispersion model in which the determination of its major parameters is based on the empirical values. This report presents a methodology for calibrating the platoon dispersion parameters in the TRANSYT`s platoon dispersion model, which is based on a statistical analysis of link travel time data rather than more traditional goodness-of-fit tests between the observed and the projected vehicles` progression patterns.

  17. Modeling the sub-cellular signaling pathways involved in reinforcement learning at the striatum.

    PubMed

    Wanjerkhede, Shesharao M; Bapi, Raju S

    2008-01-01

    A general discussion of various levels of models in computational neuroscience is presented. A detailed case study of modeling at the sub-cellular level is undertaken. The process of learning actions by reward or punishment is called 'Instrumental Conditioning' or 'Reinforcement Learning' (RL). Temporal difference learning (TDL) is a mathematical framework for RL. Houk et al. (1995) proposed a cellular signaling model for interaction of dopamine (DA) and glutamate activities at the striatum that forms the basis for TDL. In the model, glutamatergic input generates a membrane depolarization through N-methyl-d-aspartate (NMDA), alpha-amino-5-hydroxy-3-methyl-4-isoxazole propionic acid (AMPA), metabotropic glutamate receptors (mGluR), and opens calcium two plus ion (Ca(2+)) channels resulting in the influx of Ca(2+) into the dendritic spine. This raises the postsynaptic calcium concentration in the dendritic spine leading to the autophosphorylation of calcium/calmodulin-dependent protein kinase II (CaMKII). The timely arrival of the DA input at the neck of the spine head generates a cascade of reactions which then leads to the prolongation of long-term potentiation (LTP) generated by the autophosphorylation of CaMKII. Since no simulations were done so far to support this proposal, we undertook the task of computational verification of the model. During the simulations it was found that there was enhancement and prolongation of autophosphorylation of CaMKII. This result verifies Houk's proposal for LTP in the striatum. Our simulation results are generally in line with the known biological experimental data and also suggest predictions for future experimental verification.

  18. 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.

  19. Evaluation of JPEG 2000 encoder options: human and model observer detection of variable signals in X-ray coronary angiograms.

    PubMed

    Zhang, Yani; Pham, Binh; Eckstein, Miguel P

    2004-05-01

    Previous studies have evaluated the effect of the new still image compression standard JPEG 2000 using nontask based image quality metrics, i.e., peak-signal-to-noise-ratio (PSNR) for nonmedical images. In this paper, the effect of JPEG 2000 encoder options was investigated using the performance of human and model observers (nonprewhitening matched filter with an eye filter, square-window Hotelling, Laguerre-Gauss Hotelling and channelized Hotelling model observer) for clinically relevant visual tasks. Two tasks were investigated: the signal known exactly but variable task (SKEV) and the signal known statistically task (SKS). Test images consisted of real X-ray coronary angiograms with simulated filling defects (signals) inserted in one of the four simulated arteries. The signals varied in size and shape. Experimental results indicated that the dependence of task performance on the JPEG 2000 encoder options was similar for all model and human observers. Model observer performance in the more tractable and computationally economic SKEV task can be used to reliably estimate performance in the complex but clinically more realistic SKS task. JPEG 2000 encoder settings different from the default ones resulted in greatly improved model and human observer performance in the studied clinically relevant visual tasks using real angiography backgrounds.

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

    PubMed

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

    2016-01-01

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

  1. 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

  2. The Process-Interaction-Model: a common representation of rule-based and logical models allows studying signal transduction on different levels of detail

    PubMed Central

    2012-01-01

    Background Signaling systems typically involve large, structured molecules each consisting of a large number of subunits called molecule domains. In modeling such systems these domains can be considered as the main players. In order to handle the resulting combinatorial complexity, rule-based modeling has been established as the tool of choice. In contrast to the detailed quantitative rule-based modeling, qualitative modeling approaches like logical modeling rely solely on the network structure and are particularly useful for analyzing structural and functional properties of signaling systems. Results We introduce the Process-Interaction-Model (PIM) concept. It defines a common representation (or basis) of rule-based models and site-specific logical models, and, furthermore, includes methods to derive models of both types from a given PIM. A PIM is based on directed graphs with nodes representing processes like post-translational modifications or binding processes and edges representing the interactions among processes. The applicability of the concept has been demonstrated by applying it to a model describing EGF insulin crosstalk. A prototypic implementation of the PIM concept has been integrated in the modeling software ProMoT. Conclusions The PIM concept provides a common basis for two modeling formalisms tailored to the study of signaling systems: a quantitative (rule-based) and a qualitative (logical) modeling formalism. Every PIM is a compact specification of a rule-based model and facilitates the systematic set-up of a rule-based model, while at the same time facilitating the automatic generation of a site-specific logical model. Consequently, modifications can be made on the underlying basis and then be propagated into the different model specifications – ensuring consistency of all models, regardless of the modeling formalism. This facilitates the analysis of a system on different levels of detail as it guarantees the application of established

  3. A statistical model for brain networks inferred from large-scale electrophysiological signals.

    PubMed

    Obando, Catalina; De Vico Fallani, Fabrizio

    2017-03-01

    Network science has been extensively developed to characterize the structural properties of complex systems, including brain networks inferred from neuroimaging data. As a result of the inference process, networks estimated from experimentally obtained biological data represent one instance of a larger number of realizations with similar intrinsic topology. A modelling approach is therefore needed to support statistical inference on the bottom-up local connectivity mechanisms influencing the formation of the estimated brain networks. Here, we adopted a statistical model based on exponential random graph models (ERGMs) to reproduce brain networks, or connectomes, estimated by spectral coherence between high-density electroencephalographic (EEG) signals. ERGMs are made up by different local graph metrics, whereas the parameters weight the respective contribution in explaining the observed network. We validated this approach in a dataset of N = 108 healthy subjects during eyes-open (EO) and eyes-closed (EC) resting-state conditions. Results showed that the tendency to form triangles and stars, reflecting clustering and node centrality, better explained the global properties of the EEG connectomes than other combinations of graph metrics. In particular, the synthetic networks generated by this model configuration replicated the characteristic differences found in real brain networks, with EO eliciting significantly higher segregation in the alpha frequency band (8-13 Hz) than EC. Furthermore, the fitted ERGM parameter values provided complementary information showing that clustering connections are significantly more represented from EC to EO in the alpha range, but also in the beta band (14-29 Hz), which is known to play a crucial role in cortical processing of visual input and externally oriented attention. Taken together, these findings support the current view of the functional segregation and integration of the brain in terms of modules and hubs, and provide a

  4. Insulin signaling in type 2 diabetes: experimental and modeling analyses reveal mechanisms of insulin resistance in human adipocytes.

    PubMed

    Brännmark, Cecilia; Nyman, Elin; Fagerholm, Siri; Bergenholm, Linnéa; Ekstrand, Eva-Maria; Cedersund, Gunnar; Strålfors, Peter

    2013-04-05

    Type 2 diabetes originates in an expanding adipose tissue that for unknown reasons becomes insulin resistant. Insulin resistance reflects impairments in insulin signaling, but mechanisms involved are unclear because current research is fragmented. We report a systems level mechanistic understanding of insulin resistance, using systems wide and internally consistent data from human adipocytes. Based on quantitative steady-state and dynamic time course data on signaling intermediaries, normally and in diabetes, we developed a dynamic mathematical model of insulin signaling. The model structure and parameters are identical in the normal and diabetic states of the model, except for three parameters that change in diabetes: (i) reduced concentration of insulin receptor, (ii) reduced concentration of insulin-regulated glucose transporter GLUT4, and (iii) changed feedback from mammalian target of rapamycin in complex with raptor (mTORC1). Modeling reveals that at the core of insulin resistance in human adipocytes is attenuation of a positive feedback from mTORC1 to the insulin receptor substrate-1, which explains reduced sensitivity and signal strength throughout the signaling network. Model simulations with inhibition of mTORC1 are comparable with experimental data on inhibition of mTORC1 using rapamycin in human adipocytes. We demonstrate the potential of the model for identification of drug targets, e.g. increasing the feedback restores insulin signaling, both at the cellular level and, using a multilevel model, at the whole body level. Our findings suggest that insulin resistance in an expanded adipose tissue results from cell growth restriction to prevent cell necrosis.

  5. 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

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

    PubMed Central

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

    2016-01-01

    Diabetic retinopathy (DR) affects approximately one-third of diabetic patients and, if left untreated, progresses to proliferative DR (PDR) with associated vitreous hemorrhage, retinal detachment, iris neovascularization, glaucoma and irreversible blindness. In vitreous samples of human patients with PDR, we found elevated levels of hypoxia inducible factor 1 alpha (HIF1α). HIFs are transcription factors that promote hypoxia adaptation and have important functional roles in a wide range of ischemic and inflammatory diseases. To recreate the human PDR phenotype for a preclinical animal model, we generated a mouse with neuroretinal-specific loss of the von Hippel Lindau tumor suppressor protein, a protein that targets HIF1α for ubiquitination. We found that the neuroretinal cells in these mice overexpressed HIF1α and developed severe, irreversible