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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. Inverse modeling of April 2013 radioxenon detections

    NASA Astrophysics Data System (ADS)

    Hofman, Radek; Seibert, Petra; Philipp, Anne

    2014-05-01

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

  3. 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

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

    PubMed

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

    2008-11-01

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

  5. 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.

  6. 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.

  7. 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. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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

  15. Redesigned β γ radioxenon detector

    NASA Astrophysics Data System (ADS)

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

    2007-08-01

    The Automated Radio-xenon Sampler/Analyzer (ARSA), designed by Pacific Northwest National Laboratory (PNNL) collects and detects several radioxenon isotopes, and is used to monitor underground nuclear explosions. The ARSA is very sensitive to 133Xe, 131mXe, 133mXe, and 135Xe (<1 mBq/SCM) [M. Auera et al., Wernspergera, Appl. Radiat. 6 (2004) 60] through use of its compact high efficiency β-γ coincidence detector. For this reason, it is an excellent treaty monitoring system and it can be used as an environmental sampling device as well. Field testing of the ARSA has shown it to be both robust and reliable, but the nuclear detector requires a detailed photomultiplier tube (PMT) gain matching regime difficult to implement in a field environment. Complexity is a problem from a maintenance and quality assurance/quality control (QA/QC) standpoint, and efforts to reduce these issues have led to development of a simplified β-γ coincident detector. The new design reduces the number of PMT's and the complexity of the calibration needed in comparison to the old design. New scintillation materials (NaI(Tl), CsI(Na), and CsI(Tl)) were investigated and a comparison of three different gamma sensitive well detectors has been completed. A new plastic-scintillator gas cell was constructed and a new method of forming the scintillator gas cell was developed. The simplified detector system compares favorably with the original ARSA design in spectral resolution and efficiency and is significantly easier to set up and calibrate. The new materials and configuration allow the resulting β-γ coincidence detector to maintain the overall performance of the ARSA type β-γ detector while simplifying the design.

  16. 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.

  17. Radioxenon background at high northern latitudes

    NASA Astrophysics Data System (ADS)

    Saey, Paul R. J.; Wotawa, Gerhard; de Geer, Lars-Erik; Axelsson, Anders; Bean, Marc; D'Amours, Real; Elmgren, Klas; Peterson, Jenny; Ringbom, Anders; Stocki, Trevor J.; Ungar, R. K.

    2006-09-01

    As part of the International Noble Gas Experiment (INGE) two stations were deployed in remote regions at high northern latitudes: Longyearbyen, Spitsbergen, Norway (78.2°N), and Yellowknife, Canada (62.5°N). With one exception, both stations are 2000 km or more from any single known stationary nuclear facility. Nevertheless, the short-lived anthropogenic radionuclide ? = 5.24 days) has been detected on a regular basis at both stations, and also ? = 11.84 days) was found at the Yellowknife station. Measuring these very low concentrations (˜0.1 mBq/m3) has been possible because of the introduction of new and sensitive equipment developed specifically for the verification of the Comprehensive Nuclear-Test Ban Treaty. By means of atmospheric transport modeling, it was determined that the measurements at both sites are broadly consistent with reported releases from reactors in North America and Europe and that the Spitsbergen station is much more susceptible to this influence than the Yellowknife station. Especially at Spitsbergen, the simplified assumption of a continuous bulk release across Europe could well explain the month-to-month variation of the time series. A future radioxenon event classification scheme for treaty verification purposes thus needs to consider the actual meteorological situation and large-scale transport processes.

  18. 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

  19. Radioxenon Production from an Underground Nuclear Detonation

    NASA Astrophysics Data System (ADS)

    Sun, Y.

    2016-12-01

    The Comprehensive Nuclear Test Ban Treaty of 1996 has sparked the attention of many nations around the world for detecting Underground Nuclear Explosions (UNEs). The radioisotopes, specifically isotopes of xenon, Xe-131m, Xe-133m, Xe-133, and Xe-135, are being studied using their half-lives and decay networks for distinguishing civilian nuclear applications from UNEs. This study aims to simulate radioxenon concentrations and their uncertainties using analytical solutions of radioactive decay networks.

  20. Environmental Radioxenon Levels in Europe: a Comprehensive Overview

    NASA Astrophysics Data System (ADS)

    Saey, Paul R. J.; Schlosser, Clemens; Achim, Pascal; Auer, Matthias; Axelsson, Anders; Becker, Andreas; Blanchard, Xavier; Brachet, Guy; Cella, Luis; de Geer, Lars-Erik; Kalinowski, Martin B.; Le Petit, Gilbert; Peterson, Jenny; Popov, Vladimir; Popov, Yury; Ringbom, Anders; Sartorius, Hartmut; Taffary, Thomas; Zähringer, Matthias

    2010-05-01

    Activity concentration data from ambient radioxenon measurements in ground level air, which were carried out in Europe in the framework of the International Noble Gas Experiment (INGE) in support of the development and build-up of a radioxenon monitoring network for the Comprehensive Nuclear-Test-Ban Treaty verification regime are presented and discussed. Six measurement stations provided data from 5 years of measurements performed between 2003 and 2008: Longyearbyen (Spitsbergen, Norway), Stockholm (Sweden), Dubna (Russian Federation), Schauinsland Mountain (Germany), Bruyères-le-Châtel and Marseille (both France). The noble gas systems used within the INGE are designed to continuously measure low concentrations of the four radioxenon isotopes which are most relevant for detection of nuclear explosions: 131mXe, 133mXe, 133Xe and 135Xe with a time resolution less than or equal to 24 h and a minimum detectable concentration of 133Xe less than 1 mBq/m3. This European cluster of six stations is particularly interesting because it is highly influenced by a high density of nuclear power reactors and some radiopharmaceutical production facilities. The activity concentrations at the European INGE stations are studied to characterise the influence of civilian releases, to be able to distinguish them from possible nuclear explosions. It was found that the mean activity concentration of the most frequently detected isotope, 133Xe, was 5-20 mBq/m3 within Central Europe where most nuclear installations are situated (Bruyères-le-Châtel and Schauinsland), 1.4-2.4 mBq/m3 just outside that region (Stockholm, Dubna and Marseille) and 0.2 mBq/m3 in the remote polar station of Spitsbergen. No seasonal trends could be observed from the data. Two interesting events have been examined and their source regions have been identified using atmospheric backtracking methods that deploy Lagrangian particle dispersion modelling and inversion techniques. The results are consistent with known

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. 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.

  8. 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.

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

    SciTech Connect

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

    2009-12-03

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

  10. 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

  11. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

  13. 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.

  14. 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.

  15. 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).

  16. 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

  17. 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

  18. 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.

  19. A fluid-based measurement system for airborne radioxenon surveillance

    SciTech Connect

    Rooney, B.; Gross, K.C.; Nietert, R.; Valentine, J.; Russ, W.

    1997-10-01

    A new and innovative technique for concentrating heavy noble gases from the atmosphere and subsequently measuring the radioactive xenon isotopes has recently been developed at Argonne National Laboratory. The concentration technique is based on the discovery of a phenomenon where certain organic fluids absorb heavy noble gases with very high efficiency at room temperature and release the noble gases when slightly warmed (about 60{degrees}C). Research has been conducted to study the application of this technology to the design of an ultra sensitive radioxenon measurement system. Such a system could be used to monitor or sample the atmosphere for noble gas fission products ({sup 133}Xe, {sup 133m}Xe, and {sup 135}Xe) generated by nuclear testing. A system that utilizes this fluid-based technology provides a simpler, more portable, less-expensive means of concentrating xenon than current cryogenic techniques and avoids some of the complications associated with charcoal-based systems. Preliminary experiments to demonstrate the feasibility of utilizing this fluid-based technology in the design of an atmospheric radioxenon measurement have been very promising and research is continuing toward applying this technology to monitoring activities which support the Comprehensive Test Ban Treaty (CTBT).

  20. Improved performance comparisons of radioxenon systems for low level releases in nuclear explosion monitoring.

    PubMed

    Haas, Derek A; Eslinger, Paul W; Bowyer, Theodore W; Cameron, Ian M; Hayes, James C; Lowrey, Justin D; Miley, Harry S

    2017-08-14

    The Comprehensive Nuclear-Test-Ban Treaty bans all nuclear tests and mandates development of verification measures to detect treaty violations. One verification measure is detection of radioactive xenon isotopes produced in the fission of actinides. The International Monitoring System (IMS) currently deploys automated radioxenon systems that can detect four radioxenon isotopes. Radioxenon systems with lower detection limits are currently in development. Historically, the sensitivity of radioxenon systems was measured by the minimum detectable concentration for each isotope. In this paper we analyze the response of radioxenon systems using rigorous metrics in conjunction with hypothetical representative releases indicative of an underground nuclear explosion instead of using only minimum detectable concentrations. Our analyses incorporate the impact of potential spectral interferences on detection limits and the importance of measuring isotopic ratios of the relevant radioxenon isotopes in order to improve discrimination from background sources particularly for low-level releases. To provide a sufficient data set for analysis, hypothetical representative releases are simulated every day from the same location for an entire year. The performance of three types of samplers are evaluated assuming they are located at 15 IMS radionuclide stations in the region of the release point. The performance of two IMS-deployed samplers and a next-generation system is compared with proposed metrics for detection and discrimination using representative releases from the nuclear test site used by the Democratic People's Republic of Korea. Copyright © 2017. Published by Elsevier Ltd.

  1. Multipath signal model development

    NASA Technical Reports Server (NTRS)

    Ghais, A. F.; Wachsman, R. H.

    1970-01-01

    The development and use of mathematical models of signals received through the multipath environmental of a TDRS-to-user spacecraft link and vice versa are discussed. The TDRS (tracking and data relay satellite) will be in synchronous orbit. The user spacecraft will be in a low altitude orbit between 200 and 4000 km.

  2. Surface electromyogram signal modelling.

    PubMed

    McGill, K C

    2004-07-01

    The paper reviews the fundamental components of stochastic and motor-unit-based models of the surface electromyogram (SEMG). Stochastic models used in ergonomics and kinesiology consider the SEMG to be a stochastic process whose amplitude is related to the level of muscle activation and whose power spectral density reflects muscle conduction velocity. Motor-unit-based models for describing the spatio-temporal distribution of individual motor-unit action potentials throughout the limb are quite robust, making it possible to extract precise information about motor-unit architecture from SEMG signals recorded by multi-electrode arrays. Motor-unit-based models have not yet been proven as successful, however, for extracting information about recruitment and firing rates throughout the full range of contraction. The relationship between SEMG and force during natural dynamic movements is much too complex to model in terms of single motor units.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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].

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. A Multi-Layer Phoswich Radioxenon Detection System

    SciTech Connect

    David M. Hamby

    2007-07-01

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

  15. Bistability in biochemical signaling models.

    PubMed

    Sobie, Eric A

    2011-09-20

    This Teaching Resource provides lecture notes, slides, and a student assignment for a two-part lecture on the principles underlying bistability in biochemical signaling networks, which are illustrated with examples from the literature. The lectures cover analog, or graded, versus digital, all-or-none, responses in cells, with examples from different types of biological processes requiring each. Rate-balance plots are introduced as a method for determining whether generic one-variable systems exhibit one or several stable steady states. Bifurcation diagrams are presented as a more general method for detecting the presence of bistability in biochemical signaling networks. The examples include an artificial toggle switch, the lac operon in bacteria, and the mitogen-activated protein kinase cascade in both Xenopus oocytes and mammalian cells. The second part of the lecture links the concepts of bistability more closely to the mathematical tools provided by dynamical systems analysis. The examples from the first part of the lecture are analyzed with phase-plane techniques and bifurcation analysis, using the scientific programming language MATLAB. Using these programs as a template, the assignment requires the students to implement a model from the literature and analyze the stability of this model's steady states.

  16. 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

  17. 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.

  18. Optical signal splitting and chirping device modeling

    NASA Astrophysics Data System (ADS)

    Vinogradova, Irina L.; Andrianova, Anna V.; Meshkov, Ivan K.; Sultanov, Albert Kh.; Abdrakhmanova, Guzel I.; Grakhova, Elizaveta P.; Ishmyarov, Arsen A.; Yantilina, Liliya Z.; Kutlieva, Gulnaz R.

    2017-04-01

    This article examines the devices for optical signal splitting and chirping device modeling. Models with splitting and switching functions are taken into consideration. The described device for optical signal splitting and chirping represents interferential splitter with profiled mixer which provides allocation of correspondent spectral component from ultra wide band frequency diapason, and signal phase shift for aerial array (AA) directive diagram control. This paper proposes modeling for two types of devices for optical signal splitting and chirping: the interference-type optical signal splitting and chirping device and the long-distance-type optical signal splitting and chirping device.

  19. 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.

  20. 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.

  1. 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…

  2. 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…

  3. 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. Copyright © 2016, American Association for the Advancement of Science.

  4. 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.

  5. 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.

  6. 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. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

  7. 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.

  8. 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.

  9. 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. Copyright © 2012 Elsevier Ltd. All rights reserved.

  10. 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

  11. 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.

  12. (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).

  13. Isotopic Characterization of Radioiodine and Radioxenon in Releases from Underground Nuclear Explosions with Various Degrees of Fractionation

    NASA Astrophysics Data System (ADS)

    Kalinowski, Martin B.; Liao, Yen-Yo

    2014-03-01

    Both radioxenon and radioiodine are possible indicators for a nuclear explosion. Therefore, they will be, together with other relevant radionuclides, globally monitored by the International Monitoring System in order to verify compliance with the Comprehensive Nuclear-Test-Ban Treaty once the treaty has entered into force. This paper studies the temporal development of radioxenon and radioiodine activities with two different assumptions on fractionation during the release from an underground test. In the first case, only the noble gases are released, in the second case, radioiodine is released as well while the precursors remain underground. For the second case, the simulated curves of activity ratios are compared to prompt and delayed atmospheric radioactivity releases from underground nuclear tests at Nevada as a function of the time of atmospheric air sampling for concentration measurements of 135I, 133I and 131I. In addition, the effect of both fractionation cases on the isotopic activity ratios is shown in the four-isotope-plot (with 135Xe, 133mXe, 133Xe and 131mXe) that can be utilized for distinguishing nuclear explosion sources from civilian releases.

  14. Modeling the intracellular organization of calcium signaling.

    PubMed

    Dupont, Geneviève

    2014-01-01

    Calcium (Ca²⁺) is a key signaling ion that plays a fundamental role in many cellular processes in most types of tissues and organisms. The versatility of this signaling pathway is remarkable. Depending on the cell type and the stimulus, intracellular Ca²⁺ increases can last over different periods, as short spikes or more sustained signals. From a spatial point of view, they can be localized or invade the whole cell. Such a richness of behaviors is possible thanks to numerous exchange processes with the external medium or internal Ca²⁺ pools, mainly the endoplasmic or sarcoplasmic reticulum and mitochondria. These fluxes are also highly regulated. In order to get an accurate description of the spatiotemporal organization of Ca²⁺ signaling, it is useful to resort to modeling. Thus, each flux can be described by an appropriate kinetic expression. Ca²⁺ dynamics in a given cell type can then be simulated by a modular approach, consisting of the assembly of computational descriptions of the appropriate fluxes and regulations. Modeling can also be used to get insight into the mechanisms of decoding of the Ca²⁺ signals responsible for cellular responses. Cells can use frequency or amplitude coding, as well as take profit of Ca²⁺ oscillations to increase their sensitivity to small average Ca²⁺ increases. © 2014 Wiley Periodicals, Inc.

  15. 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.

  16. 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.

  17. Spatial Modeling of Cell Signaling Networks

    PubMed Central

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

    2012-01-01

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

  18. Logic integer programming models for signaling networks.

    PubMed

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

    2009-05-01

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

  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. 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

  1. 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.

  2. Modelling protein functional domains in signal transduction using Maude

    NASA Technical Reports Server (NTRS)

    Sriram, M. G.

    2003-01-01

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

  3. 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.

  4. 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

  5. 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

  6. 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.

  7. A dynamical model for generating synthetic Phonocardiogram signals

    PubMed Central

    Almasi, Ali; Shamsollahi, Mohammad-Bagher; Senhadji, Lotfi

    2011-01-01

    In this paper we introduce a dynamical model for Phonocardiogram (PCG) signal which is capable of generating realistic synthetic PCG signals. This model is based on PCG morphology and consists of three ordinary differential equations and can represent various morphologies of normal PCG signals. Beat-to-beat variation in PCG morphology is significant so model parameters vary from beat to beat. This model is inspired of Electrocardiogram (ECG) dynamical model proposed by McSharry et al. and can be employed to assess biomedical signal processing techniques. PMID:22255630

  8. Mathematical model of TGF-βsignalling: feedback coupling is consistent with signal switching.

    PubMed

    Khatibi, Shabnam; Zhu, Hong-Jian; Wagner, John; Tan, Chin Wee; Manton, Jonathan H; Burgess, Antony W

    2017-04-13

    Transforming growth factor β (TGF-β) signalling regulates the development of embryos and tissue homeostasis in adults. In conjunction with other oncogenic changes, long-term perturbation of TGF-β signalling is associated with cancer metastasis. Although TGF-β signalling can be complex, many of the signalling components are well defined, so it is possible to develop mathematical models of TGF-β signalling using reduction and scaling methods. The parameterization of our TGF-β signalling model is consistent with experimental data. We developed our mathematical model for the TGF-β signalling pathway, i.e. the RF- model of TGF-β signalling, using the "rapid equilibrium assumption" to reduce the network of TGF-β signalling reactions based on the time scales of the individual reactions. By adding time-delayed positive feedback to the inherent time-delayed negative feedback for TGF-β signalling. We were able to simulate the sigmoidal, switch-like behaviour observed for the concentration dependence of long-term (> 3 hours) TGF-β stimulation. Computer simulations revealed the vital role of the coupling of the positive and negative feedback loops on the regulation of the TGF-β signalling system. The incorporation of time-delays for the negative feedback loop improved the accuracy, stability and robustness of the model. This model reproduces both the short-term and long-term switching responses for the intracellular signalling pathways at different TGF-β concentrations. We have tested the model against experimental data from MEF (mouse embryonic fibroblasts) WT, SV40-immortalized MEFs and Gp130 (F/F) MEFs. The predictions from the RF- model are consistent with the experimental data. Signalling feedback loops are required to model TGF-β signal transduction and its effects on normal and cancer cells. We focus on the effects of time-delayed feedback loops and their coupling to ligand stimulation in this system. The model was simplified and reduced to its key

  9. Signal Processing in the Linear Statistical Model

    DTIC Science & Technology

    1994-11-04

    Covariance Bounds," Proc 07th Asilo - mar Conf on Signals, Systems, and Computers, Pacific Grove, CA (November 1993). [MuS9l] C. T. Mullis and L. L. Scharf...Transforms," Proc Asilo - mar Con. on Signals, Systems, and Computers, Asilomar, CA (November 1991). [SpS94] M. Spurbeck and L. L. Scharf, "Least Squares...McWhorter and L. L. Scharf, "Multiwindow Estimators of Correlation," Proc 28th Annual Asilo - mar Conf on Signals, Systems, and Computers, Asilomar, CA

  10. Bigger, better, faster: principles and models of AKAP signaling

    PubMed Central

    Greenwald, Eric C.; Saucerman, Jeffrey J.

    2011-01-01

    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 feedforward and feedback loops that may create complex network responses including adaptation, oscillation, and ultrasensitivity. Computational models have begun to provide insight into how AKAPs regulate signaling dynamics and cardiovascular pathophysiology. Models of MAPK and EGFR 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. PMID:21562426

  11. Improvements in Calibration and Analysis of the CTBT-relevant Radioxenon Isotopes with High Resolution SiPIN-based Electron Detectors

    NASA Astrophysics Data System (ADS)

    Khrustalev, K.

    2016-12-01

    Current process for the calibration of the beta-gamma detectors used for radioxenon isotope measurements for CTBT purposes is laborious and time consuming. It uses a combination of point sources and gaseous sources resulting in differences between energy and resolution calibrations. The emergence of high resolution SiPIN based electron detectors allows improvements in the calibration and analysis process to be made. Thanks to high electron resolution of SiPIN detectors ( 8-9 keV@129 keV) compared to plastic scintillators ( 35 keV@129keV) there are a lot more CE peaks (from radioxenon and radon progenies) can be resolved and used for energy and resolution calibration in the energy range of the CTBT-relevant radioxenon isotopes. The long term stability of the SiPIN energy calibration allows one to significantly reduce the time of the QC measurements needed for checking the stability of the E/R calibration. The currently used second order polynomials for the E/R calibration fitting are unphysical and shall be replaced by a linear energy calibration for NaI and SiPIN, owing to high linearity and dynamic range of the modern digital DAQ systems, and resolution calibration functions shall be modified to reflect the underlying physical processes. Alternatively, one can completely abandon the use of fitting functions and use only point-values of E/R (similar to the efficiency calibration currently used) at the energies relevant for the isotopes of interest (ROI - Regions Of Interest ). Current analysis considers the detector as a set of single channel analysers, with an established set of coefficients relating the positions of ROIs with the positions of the QC peaks. The analysis of the spectra can be made more robust using peak and background fitting in the ROIs with a single free parameter (peak area) of the potential peaks from the known isotopes and a fixed E/R calibration values set.

  12. 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.

  13. 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".

  14. 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…

  15. 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…

  16. Observation, analysis, and modeling of deep radio occultation signals: Effects of tropospheric ducts and interfering signals

    NASA Astrophysics Data System (ADS)

    Sokolovskiy, S.; Schreiner, W.; Zeng, Z.; Hunt, D.; Lin, Y.-C.; Kuo, Y.-H.

    2014-10-01

    GPS radio occultation (RO) signals are sometimes observed very deep in the Earth's shadow. To investigate these phenomena, one of the FORMOSAT-3/COSMIC RO receivers was set to track RO signals deep below the limb, down to a height of straight line -350 km on 5-6 October 2010. Analysis of the spectrograms revealed the existence of two types of signals below -200 km, RO signals induced by tropospheric propagation and interfering signals not transmitted by the occulted GPS. The RO signals induced by tropospheric propagation arrive from impact heights corresponding to inversion layers. Wave optics modeling of RO signals showed that deep signals exist when the refractivity gradient exceeds critical (super-refraction). The existence of such signals is a diffractional phenomenon, which offers a new quality control parameter to identify occultations that may be affected by super-refraction. This is important for RO data assimilation in weather models in the moist lower troposphere because assimilation of RO data affected by super-refraction is an ill-conditioned problem. Detection of the tropospheric ducts also may be useful for evaluation of radio wave propagation conditions. For infinitely horizontally extended ducts, the deep signals are extended in duration, have amplitudes of about 0.1%, and exist for only elevated ducts. For ducts of limited horizontal extension, the deep signals are shorter in duration, have amplitude of about 1%, and may exist for both elevated and surface ducts. The interfering signals were found in about half of occultations. Based on frequency modeling, in most cases, the interfering signal was identified with non-occulted GPS. The disturbance of retrieved bending angle induced by an interfering signal from a non-occulted GPS in a region of strong defocusing and significant spectral spread of RO signal was modeled and determined to be quite large, up to 10% of bending angle. However, the probability of occurrence of such interference (not

  17. 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.

  18. Hedgehog signaling pathway: a novel model and molecular mechanisms of signal transduction.

    PubMed

    Gorojankina, Tatiana

    2016-04-01

    The Hedgehog (Hh) signaling pathway has numerous roles in the control of cell proliferation, tissue patterning and stem cell maintenance. In spite of intensive study, the mechanisms of Hh signal transduction are not completely understood. Here I review published data and present a novel model of vertebrate Hh signaling suggesting that Smoothened (Smo) functions as a G-protein-coupled receptor in cilia. This is the first model to propose molecular mechanisms for the major steps of Hh signaling, including inhibition of Smo by Patched, Smo activation, and signal transduction from active Smo to Gli transcription factors. It also suggests a novel role for the negative pathway regulators Sufu and PKA in these processes.

  19. Power-law models of signal transduction pathways.

    PubMed

    Vera, Julio; Balsa-Canto, Eva; Wellstead, Peter; Banga, Julio R; Wolkenhauer, Olaf

    2007-07-01

    The mathematical modelling of signal transduction pathways has become a valuable aid to understanding the complex interactions involved in intracellular signalling mechanisms. An important aspect of the mathematical modelling process is the selection of the model type and structure. Until recently, the convention has been to use a standard kinetic model, often with the Michaelis-Menten steady state assumption. However this model form, although valuable, is only one of a number of choices, and the aim of this article is to consider the mathematical structure and essential features of an alternative model form--the power-law model. Specifically, we analyse how power-law models can be applied to increase our understanding of signal transduction pathways when there may be limited prior information. We distinguish between two kinds of power law models: a) Detailed power-law models, as a tool for investigating pathways when the structure of protein-protein interactions is completely known, and; b) Simplified power-law models, for the analysis of systems with incomplete structural information or insufficient quantitative data for generating detailed models. If sufficient data of high quality are available, the advantage of detailed power-law models is that they are more realistic representations of non-homogenous or crowded cellular environments. The advantages of the simplified power-law model formulation are illustrated using some case studies in cell signalling. In particular, the investigation on the effects of signal inhibition and feedback loops and the validation of structural hypotheses are discussed.

  20. LHC diphoton Higgs signal predicted by little Higgs models

    SciTech Connect

    Wang Lei; Yang Jinmin

    2011-10-01

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

  1. 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.

  2. Mechanical Signaling for Bone Modeling and Remodeling

    PubMed Central

    Robling, Alexander G.; Turner, Charles H.

    2012-01-01

    Proper development of the skeleton in utero and during growth requires mechanical stimulation. Loading results in adaptive changes in bone that strengthen bone structure. Bone’s adaptive response is regulated by the ability of resident bone cells to perceive and translate mechanical energy into a cascade of structural and biochemical changes within the cells — a process known as mechanotransduction. Mechanotransduction pathways are among the most anabolic in bone, and consequently, there is great interest in elucidating how mechanical loading produces its observed effects, including increased bone formation, reduced bone loss, changes in bone cell differentiation and lifespan, among others. A molecular understanding of these processes is developing, and with it comes a profound new insight into the biology of bone. In this article, we review the nature of the physical stimulus to which bone cells mount an adaptive response, including the identity of the sensor cells, their attributes and physical environment, and putative mechanoreceptors they express. Particular attention is allotted to the focal adhesion and Wnt signaling, in light of their emerging role in bone mechanotransduction. The cellular mechanisms for increased bone loss during disuse, and reduced bone loss during loading are considered. Finally, we summarize the published data on bone cell accommodation, whereby bone cells stop responding to mechanical signaling events. Collectively, these data highlight the complex yet finely orchestrated process of mechanically regulated bone homeostasis. PMID:19817708

  3. 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.

  4. 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.

  5. Quantitative modelling in cognitive ergonomics: predicting signals passed at danger.

    PubMed

    Moray, Neville; Groeger, John; Stanton, Neville

    2017-02-01

    This paper shows how to combine field observations, experimental data and mathematical modelling to produce quantitative explanations and predictions of complex events in human-machine interaction. As an example, we consider a major railway accident. In 1999, a commuter train passed a red signal near Ladbroke Grove, UK, into the path of an express. We use the Public Inquiry Report, 'black box' data, and accident and engineering reports to construct a case history of the accident. We show how to combine field data with mathematical modelling to estimate the probability that the driver observed and identified the state of the signals, and checked their status. Our methodology can explain the SPAD ('Signal Passed At Danger'), generate recommendations about signal design and placement and provide quantitative guidance for the design of safer railway systems' speed limits and the location of signals. Practitioner Summary: Detailed ergonomic analysis of railway signals and rail infrastructure reveals problems of signal identification at this location. A record of driver eye movements measures attention, from which a quantitative model for out signal placement and permitted speeds can be derived. The paper is an example of how to combine field data, basic research and mathematical modelling to solve ergonomic design problems.

  6. 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.

  7. 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.

  8. Angiogenic Signaling in Living Breast Tumor Models

    DTIC Science & Technology

    2010-06-01

    harmonic generation imaging of the diseased state osteogenesis imperfecta : experiment and simulation,” Biophys. J. 94(11), 4504–4514 (2008). 3. O...biopsies, mouse models of breast cancer, and dermis from mouse models of Osteogenesis Imperfecta (OIM) [1–5,7]. The F/B ratio revealed the length scale of...interest in discriminating skin with Osteogenesis Imperfecta [2] from normal dermis [2] and SHG F/B ratio measurements have been used to help determine

  9. Multiscale adaptive basis function modeling of spatiotemporal vectorcardiogram signals.

    PubMed

    Gang Liu; Hui Yang

    2013-03-01

    Mathematical modeling of cardiac electrical signals facilitates the simulation of realistic cardiac electrical behaviors, the evaluation of algorithms, and the characterization of underlying space-time patterns. However, there are practical issues pertinent to model efficacy, robustness, and generality. This paper presents a multiscale adaptive basis function modeling approach to characterize not only temporal but also spatial behaviors of vectorcardiogram (VCG) signals. Model parameters are adaptively estimated by the "best matching" projections of VCG characteristic waves onto a dictionary of nonlinear basis functions. The model performance is experimentally evaluated with respect to the number of basis functions, different types of basis function (i.e., Gaussian, Mexican hat, customized wavelet, and Hermitian wavelets), and various cardiac conditions, including 80 healthy controls and different myocardial infarctions (i.e., 89 inferior, 77 anterior-septal, 56 inferior-lateral, 47 anterior, and 43 anterior-lateral). Multiway analysis of variance shows that the basis function and the model complexity have significant effects on model performances while cardiac conditions are not significant. The customized wavelet is found to be an optimal basis function for the modeling of spacetime VCG signals. The comparison of QT intervals shows small relative errors (<;5%) between model representations and realworld VCG signals when the model complexity is greater than 10. The proposed model shows great potentials to model space-time cardiac pathological behaviors and can lead to potential benefits in feature extraction, data compression, algorithm evaluation, and disease prognostics.

  10. Model-based Bayesian signal extraction algorithm for peripheral nerves

    NASA Astrophysics Data System (ADS)

    Eggers, Thomas E.; Dweiri, Yazan M.; McCallum, Grant A.; Durand, Dominique M.

    2017-10-01

    Objective. Multi-channel cuff electrodes have recently been investigated for extracting fascicular-level motor commands from mixed neural recordings. Such signals could provide volitional, intuitive control over a robotic prosthesis for amputee patients. Recent work has demonstrated success in extracting these signals in acute and chronic preparations using spatial filtering techniques. These extracted signals, however, had low signal-to-noise ratios and thus limited their utility to binary classification. In this work a new algorithm is proposed which combines previous source localization approaches to create a model based method which operates in real time. Approach. To validate this algorithm, a saline benchtop setup was created to allow the precise placement of artificial sources within a cuff and interference sources outside the cuff. The artificial source was taken from five seconds of chronic neural activity to replicate realistic recordings. The proposed algorithm, hybrid Bayesian signal extraction (HBSE), is then compared to previous algorithms, beamforming and a Bayesian spatial filtering method, on this test data. An example chronic neural recording is also analyzed with all three algorithms. Main results. The proposed algorithm improved the signal to noise and signal to interference ratio of extracted test signals two to three fold, as well as increased the correlation coefficient between the original and recovered signals by 10-20%. These improvements translated to the chronic recording example and increased the calculated bit rate between the recovered signals and the recorded motor activity. Significance. HBSE significantly outperforms previous algorithms in extracting realistic neural signals, even in the presence of external noise sources. These results demonstrate the feasibility of extracting dynamic motor signals from a multi-fascicled intact nerve trunk, which in turn could extract motor command signals from an amputee for the end goal of

  11. Modeling Protein Expression and Protein Signaling Pathways

    PubMed Central

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

    2015-01-01

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

  12. 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).

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

    NASA Astrophysics Data System (ADS)

    Lowrey, J. D.; Biegalski, S. R.; Osborne, A. G.; Deinert, M. R.

    2013-01-01

    The ratios of noble gas radioisotopes can provide critical information with which to verify that a belowground nuclear test has taken place. The relative abundance of anthropogenic isotopes is typically assumed to rely solely on their fission yield and decay rate. The xenon signature of a nuclear test is then bounded by the signal from directly produced fission xenon, and by the signal that would come from the addition of xenon from iodine precursors. Here we show that this signal range is too narrowly defined. Transport simulations were done to span the range of geological conditions within the Nevada Test Site. The simulations assume a 1 kt test and the barometric history following the nuclear test at Pahute Mesa in March 1992. Predicted xenon ratios fall outside of the typically assumed range 20% of the time and situations can arise where the ground level signal comes entirely from the decay of iodine precursors.

  14. Collective signaling behavior in a networked-oscillator model

    NASA Astrophysics Data System (ADS)

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

    2007-09-01

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

  15. Angiogenic Signaling in Living Breast Tumor Models

    DTIC Science & Technology

    2008-06-01

    A.S. Kamoun-Goldrat and M.F. Le Merrer, "Animal models of osteogenesis imperfecta and related syndromes," J. Bone Miner. Metab. 25, 211-8 (2007...in the tumor reactive stroma. Therefore these optical properties may be useful in studying genetic disorders of collagen, such as in Osteogenesis ... Imperfecta [26]. Acknowledgments This work is supported by Department of Defense grant W81XWH-05-1-0396. We thank Drs. Ania Majewska and Dr. Julie

  16. Modeling Horizontal GPS Seasonal Signals Caused by Ocean Loading

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  17. A split signal polynomial as a model of an impulse noise filter for speech signal recovery

    NASA Astrophysics Data System (ADS)

    Solovyeva, E. B.

    2017-01-01

    The synthesis of the non-linear non-recursive digital filter of impulse noise on the basis of the splitting method in time domain is described. The filter recovers speech signals, distorted by impulse noise. The filter model is constructed as the splitting polynomial of an odd degree. The splitter is the time delay line, comprising the equal number of previous and subsequent samples with respect to the current time moment. The polynomial parameters result from solving an approximation problem in the mean-square norm. It is shown that the filter with the splitting model provides more precise speech signal recovery than the median and Volterra filters.

  18. 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.

  19. 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.

  20. 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.

  1. 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...

  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. 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.

  8. 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.

  9. 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.

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

    PubMed Central

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

    2013-01-01

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

  11. 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.

  12. 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

  13. Modeling Infrared Signal Reflections to Characterize Indoor Multipath Propagation

    PubMed Central

    De-La-Llana-Calvo, Álvaro; Lázaro-Galilea, José Luis; Gardel-Vicente, Alfredo; Rodríguez-Navarro, David; Bravo-Muñoz, Ignacio; Tsirigotis, Georgios; Iglesias-Miguel, Juan

    2017-01-01

    In this paper, we propose a model to characterize Infrared (IR) signal reflections on any kind of surface material, together with a simplified procedure to compute the model parameters. The model works within the framework of Local Positioning Systems (LPS) based on IR signals (IR-LPS) to evaluate the behavior of transmitted signal Multipaths (MP), which are the main cause of error in IR-LPS, and makes several contributions to mitigation methods. Current methods are based on physics, optics, geometry and empirical methods, but these do not meet our requirements because of the need to apply several different restrictions and employ complex tools. We propose a simplified model based on only two reflection components, together with a method for determining the model parameters based on 12 empirical measurements that are easily performed in the real environment where the IR-LPS is being applied. Our experimental results show that the model provides a comprehensive solution to the real behavior of IR MP, yielding small errors when comparing real and modeled data (the mean error ranges from 1% to 4% depending on the environment surface materials). Other state-of-the-art methods yielded mean errors ranging from 15% to 40% in test measurements. PMID:28406436

  14. 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.

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

    PubMed

    Ifrim, Sandra

    2015-12-01

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

  16. 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

  17. Preliminary Experiments with a Triple-Layer Phoswich Detector for Radioxenon Detection

    DTIC Science & Technology

    2008-09-01

    current available manufacturing capabilities, a prototypic planar triple-layer phoswich detector was designed, modeled , and constructed (Farsoni and...written in Python programming language and was developed with the wxPython GUI toolkit. Through the software interface, the user can specify data...Our radiation transport modeling (Farsoni and Hamby, 2006) showed that the 30 keV X-ray is significantly attenuated by the quartz. Thus, to

  18. 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.

  19. 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

  20. 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

  1. Fractional cable model for signal conduction in spiny neuronal dendrites

    NASA Astrophysics Data System (ADS)

    Vitali, Silvia; Mainardi, Francesco

    2017-06-01

    The cable model is widely used in several fields of science to describe the propagation of signals. A relevant medical and biological example is the anomalous subdiffusion in spiny neuronal dendrites observed in several studies of the last decade. Anomalous subdiffusion can be modelled in several ways introducing some fractional component into the classical cable model. The Chauchy problem associated to these kind of models has been investigated by many authors, but up to our knowledge an explicit solution for the signalling problem has not yet been published. Here we propose how this solution can be derived applying the generalized convolution theorem (known as Efros theorem) for Laplace transforms. The fractional cable model considered in this paper is defined by replacing the first order time derivative with a fractional derivative of order α ∈ (0, 1) of Caputo type. The signalling problem is solved for any input function applied to the accessible end of a semi-infinite cable, which satisfies the requirements of the Efros theorem. The solutions corresponding to the simple cases of impulsive and step inputs are explicitly calculated in integral form containing Wright functions. Thanks to the variability of the parameter α, the corresponding solutions are expected to adapt to the qualitative behaviour of the membrane potential observed in experiments better than in the standard case α = 1.

  2. 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.

  3. 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

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

    PubMed

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

    2013-12-01

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

  5. Nonlinear dynamics of the voice: Signal analysis and biomechanical modeling

    NASA Astrophysics Data System (ADS)

    Herzel, Hanspeter; Berry, David; Titze, Ingo; Steinecke, Ina

    1995-03-01

    Irregularities in voiced speech are often observed as a consequence of vocal fold lesions, paralyses, and other pathological conditions. Many of these instabilities are related to the intrinsic nonlinearities in the vibrations of the vocal folds. In this paper, bifurcations in voice signals are analyzed using narrow-band spectrograms. We study sustained phonation of patients with laryngeal paralysis and data from an excised larynx experiment. These spectrograms are compared with computer simulations of an asymmetric 2-mass model of the vocal folds.

  6. 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

  7. A broadband ocean sediment acoustics model for signal processing applications

    NASA Astrophysics Data System (ADS)

    Chotiros, Nicholas P.; Isakson, Marcia J.

    2002-11-01

    It has been shown that fluid and viscoelastic solid approximations cannot accommodate the observed sound speed dispersion and enhanced reflection loss over sandy shallow water sediments. A plausible poroelastic model has been developed for the high frequency band (>50 kHz) using measurements from several sources. This model, with constant coefficients, is unable to track the observed sound speed dispersion at lower frequencies. It is hypothesized that one parameter, the frame bulk modulus, varies with frequency in a relaxation process associated with squirt flow at the grain-grain contact. This hypothesis has the potential to be a critical component in broadband acoustic models of granular ocean sediments. It will link measurements at high frequencies to propagation modeling at low frequencies, provide accurate, physics based, models of propagation loss, and a means to invert for bottom properties over a broad range of frequencies. [Work supported by ONR, Undersea Signal Processing.

  8. Modeling SMAP Spacecraft Attitude Control Estimation Error Using Signal Generation Model

    NASA Technical Reports Server (NTRS)

    Rizvi, Farheen

    2016-01-01

    Two ground simulation software are used to model the SMAP spacecraft dynamics. The CAST software uses a higher fidelity model than the ADAMS software. The ADAMS software models the spacecraft plant, controller and actuator models, and assumes a perfect sensor and estimator model. In this simulation study, the spacecraft dynamics results from the ADAMS software are used as CAST software is unavailable. The main source of spacecraft dynamics error in the higher fidelity CAST software is due to the estimation error. A signal generation model is developed to capture the effect of this estimation error in the overall spacecraft dynamics. Then, this signal generation model is included in the ADAMS software spacecraft dynamics estimate such that the results are similar to CAST. This signal generation model has similar characteristics mean, variance and power spectral density as the true CAST estimation error. In this way, ADAMS software can still be used while capturing the higher fidelity spacecraft dynamics modeling from CAST software.

  9. Models of Acetylcholine and Dopamine Signals Differentially Improve Neural Representations.

    PubMed

    Holca-Lamarre, Raphaël; Lücke, Jörg; Obermayer, Klaus

    2017-01-01

    Biological and artificial neural networks (ANNs) represent input signals as patterns of neural activity. In biology, neuromodulators can trigger important reorganizations of these neural representations. For instance, pairing a stimulus with the release of either acetylcholine (ACh) or dopamine (DA) evokes long lasting increases in the responses of neurons to the paired stimulus. The functional roles of ACh and DA in rearranging representations remain largely unknown. Here, we address this question using a Hebbian-learning neural network model. Our aim is both to gain a functional understanding of ACh and DA transmission in shaping biological representations and to explore neuromodulator-inspired learning rules for ANNs. We model the effects of ACh and DA on synaptic plasticity and confirm that stimuli coinciding with greater neuromodulator activation are over represented in the network. We then simulate the physiological release schedules of ACh and DA. We measure the impact of neuromodulator release on the network's representation and on its performance on a classification task. We find that ACh and DA trigger distinct changes in neural representations that both improve performance. The putative ACh signal redistributes neural preferences so that more neurons encode stimulus classes that are challenging for the network. The putative DA signal adapts synaptic weights so that they better match the classes of the task at hand. Our model thus offers a functional explanation for the effects of ACh and DA on cortical representations. Additionally, our learning algorithm yields performances comparable to those of state-of-the-art optimisation methods in multi-layer perceptrons while requiring weaker supervision signals and interacting with synaptically-local weight updates.

  10. Models of Acetylcholine and Dopamine Signals Differentially Improve Neural Representations

    PubMed Central

    Holca-Lamarre, Raphaël; Lücke, Jörg; Obermayer, Klaus

    2017-01-01

    Biological and artificial neural networks (ANNs) represent input signals as patterns of neural activity. In biology, neuromodulators can trigger important reorganizations of these neural representations. For instance, pairing a stimulus with the release of either acetylcholine (ACh) or dopamine (DA) evokes long lasting increases in the responses of neurons to the paired stimulus. The functional roles of ACh and DA in rearranging representations remain largely unknown. Here, we address this question using a Hebbian-learning neural network model. Our aim is both to gain a functional understanding of ACh and DA transmission in shaping biological representations and to explore neuromodulator-inspired learning rules for ANNs. We model the effects of ACh and DA on synaptic plasticity and confirm that stimuli coinciding with greater neuromodulator activation are over represented in the network. We then simulate the physiological release schedules of ACh and DA. We measure the impact of neuromodulator release on the network's representation and on its performance on a classification task. We find that ACh and DA trigger distinct changes in neural representations that both improve performance. The putative ACh signal redistributes neural preferences so that more neurons encode stimulus classes that are challenging for the network. The putative DA signal adapts synaptic weights so that they better match the classes of the task at hand. Our model thus offers a functional explanation for the effects of ACh and DA on cortical representations. Additionally, our learning algorithm yields performances comparable to those of state-of-the-art optimisation methods in multi-layer perceptrons while requiring weaker supervision signals and interacting with synaptically-local weight updates. PMID:28690509

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. Modeling skull's acoustic attenuation and dispersion on photoacoustic signal

    NASA Astrophysics Data System (ADS)

    Mohammadi, L.; Behnam, H.; Nasiriavanaki, M. R.

    2017-03-01

    Despite the great promising results of a recent new transcranial photoacoustic brain imaging technology, it has been shown that the presence of the skull severely affects the performance of this imaging modality. In this paper, we investigate the effect of skull on generated photoacoustic signals with a mathematical model. The developed model takes into account the frequency dependence attenuation and acoustic dispersion effects occur with the wave reflection and refraction at the skull surface. Numerical simulations based on the developed model are performed for calculating the propagation of photoacoustic waves through the skull. From the simulation results, it was found that the skull-induced distortion becomes very important and the reconstructed image would be strongly distorted without correcting these effects. In this regard, it is anticipated that an accurate quantification and modeling of the skull transmission effects would ultimately allow for skull aberration correction in transcranial photoacoustic brain imaging.

  16. 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

  17. 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

  18. An extended car-following model at signalized intersections

    NASA Astrophysics Data System (ADS)

    Yu, Shaowei; Shi, Zhongke

    2014-08-01

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

  19. 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

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. Design of experiments to investigate dynamic cell signaling models.

    PubMed

    Bandara, Samuel; Meyer, Tobias

    2012-01-01

    This chapter describes approaches to make use of dynamic models of cell signaling systems in order to optimize experiments in cell biology. We are particularly focusing on the question of how small molecule inhibitors or activators can best be used to get the most information out of a limited number of experiments when only a handful of molecular species can be measured. One goal addressed by this chapter is to find time course experiments to discriminate between rivaling molecular mechanisms. The other goal is to find experiments that are useful for inferring rate constants, binding affinities, concentrations, and other model parameters from time course data. Both are treated as optimal control problems in which rapid pharmacological perturbation schemes are identified in silico in order to close an experimental cycle from modeling back to the laboratory bench.

  5. Methods for Modeling Brassinosteroid-Mediated Signaling in Plant Development.

    PubMed

    Frigola, David; Caño-Delgado, Ana I; Ibañes, Marta

    2017-01-01

    Mathematical modeling of biological processes is a useful tool to draw conclusions that are contained in the data, but not directly reachable, as well as to make predictions and select the most efficient follow-up experiments. Here we outline a method to model systems of a few proteins that interact transcriptionally and/or posttranscriptionally, by representing the system as Ordinary Differential Equations and to study the model dynamics and stationary states. We exemplify this method by focusing on the regulation by the brassinosteroid (BR) signaling component BRASSINOSTEROID INSENSITIVE1 ETHYL METHYL SULFONATE SUPPRESSOR1 (BES1) of BRAVO, a quiescence-regulating transcription factor expressed in the quiescent cells of Arabidopsis thaliana roots. The method to extract the stationary states and the dynamics is provided as a Mathematica code and requires basic knowledge of the Mathematica software to be executed.

  6. 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.

  7. 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.

  8. Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.

    PubMed

    DeCarlo, Lawrence T

    2003-02-01

    The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.

  9. Modeling Signaling Networks to Advance New Cancer Therapies.

    PubMed

    Saez-Rodriguez, Julio; MacNamara, Aidan; Cook, Simon

    2015-01-01

    Cell signaling pathways control cells' responses to their environment through an intricate network of proteins and small molecules partitioned by intracellular structures, such as the cytoskeleton and nucleus. Our understanding of these pathways has been revised recently with the advent of more advanced experimental techniques; no longer are signaling pathways viewed as linear cascades of information flowing from membrane-bound receptors to the nucleus. Instead, such pathways must be understood in the context of networks, and studying such networks requires an integration of computational and experimental approaches. This understanding is becoming more important in designing novel therapies for diseases such as cancer. Using the MAPK (mitogen-activated protein kinase) and PI3K (class I phosphoinositide-3' kinase) pathways as case studies of cellular signaling, we give an overview of these pathways and their functions. We then describe, using a number of case studies, how computational modeling has aided in understanding these pathways' deregulation in cancer, and how such understanding can be used to optimally tailor current therapies or help design new therapies against cancer.

  10. Modelling contemporary GIA signals in northern Europe and Scandinavia

    NASA Astrophysics Data System (ADS)

    Simon, Karen; Riva, Riccardo

    2017-04-01

    GPS-measured rates of vertical crustal motion and GRACE-derived gravity change rates are incorporated into a semi-empirical model to constrain better the present-day glacial isostatic adjustment (GIA) signal associated with the former Fennoscandian Ice Sheet. The study area extends from northern Europe just south of the LGM ice margin to the load-central regions of Scandinavia. The observational data are combined with a suite of forward GIA model predictions which allow for variation in both ice sheet history and Earth model characteristics, with the best-fit posterior model simultaneously minimizing the misfit between both the observational and model constraints. When only the GPS data are incorporated into the prior model a good fit is obtained (χ2 < 1), with the most prominent post-fit residuals predicted to the north and east of the Gulf of Bothnia. The result is similar when only the GRACE data are used as constraint, and the best overall fit is obtained when both datasets are inverted. Both the GPS and GRACE datasets are corrected a priori for the effect of hydrological loading using the PCR-GLOBWB hydrology model, a correction which can, at least at the local scale, significantly impact the fit of model predictions to the observational data. Within formerly glaciated regions, the methodology provides a realistic prediction of the uncertainty associated with the glacial isostatic adjustment process; for example, for rates of vertical land motion, predicted uncertainties range from 0.2-1 mm/yr, with the largest rates present in the northern Gulf of Bothnia. The GIA predictions can be used in sea-level studies to better constrain the magnitude and uncertainty of the GIA contribution to the regional sea-level budget. Also assessed is the sensitivity of the model predictions to variations in ice sheet and Earth model combinations, and the ability of the method to resolve preferred values for these parameters.

  11. 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.

  12. 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.

  13. Numerical Modeling of Doppler Radar Signals of Strombolian Eruptions

    NASA Astrophysics Data System (ADS)

    Gouhier, M.; Donnadieu, F.

    2006-12-01

    VOLDORAD is a ground-based UHF Doppler radar developed specifically for the remote sounding of volcanic eruptions. Its 23.5 cm wavelength allows us to monitor and quantify eruption intensity in real time from several km, with negligible attenuation by meteorological effects or volcanic ash. In particular, the signal can penetrate inside volcanic jets or plumes to measure the reflectivity and velocities of ejecta in several sampling volumes. The precise knowledge of these parameters is crucial to monitoring the evolution of an eruption and to provide more stringent constraints on assumptions included in models of volcanic processes. To improve our interpretation of radar signals, we have developed a numerical model simulating radar echoes from Strombolian jets. Ballistic projectiles of various sizes are accelerated upwards, over a range of angles, by gas with a given imposed initial velocity , and the equations of motion are solved with a fourth-order Runge-Kutta algorithm. The power backscattered to the radar is simulated by Rayleigh scattering from spheres. Taking into account the sounding geometry used for measurements on Etna in July 2001, our model is able to reproduce many characteristic trends of the time series and Doppler spectra measured during repeated Strombolian outbursts. Models show that measured radar velocities depend mostly on jet geometry, particle size, and initial gas velocity. For wide emission angles, measured radial velocities can be considered as the real ejecta velocities, whereas in the case of narrow vertical or asymmetrical jets, real velocity might be underestimated. However, video analyses confirm that for the majority of explosions, although most particles concentrate in the inner part of the jets, many blocks are also emitted at wide angles. For instance, maximum radial velocities recorded during the July 4 episode of Etna reached 70 m/s. The model radar signal obtained is strongly dependent on the degree of coupling between

  14. 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.

  15. 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.

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

    PubMed Central

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

    2016-01-01

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

  17. Vibration signal models for fault diagnosis of planet bearings

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    PubMed

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

    2012-01-01

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

  6. Modeling and processing of laser Doppler reactive hyperaemia signals

    NASA Astrophysics Data System (ADS)

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

    2003-07-01

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

  7. 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.

  8. Modeling the photoacoustic signal during the porous silicon formation

    NASA Astrophysics Data System (ADS)

    Ramirez-Gutierrez, C. F.; Castaño-Yepes, J. D.; Rodriguez-García, M. E.

    2017-01-01

    Within this work, the kinetics of the growing stage of porous silicon (PS) during the etching process was studied using the photoacoustic technique. A p-type Si with low resistivity was used as a substrate. An extension of the Rosencwaig and Gersho model is proposed in order to analyze the temporary changes that take place in the amplitude of the photoacoustic signal during the PS growth. The solution of the heat equation takes into account the modulated laser beam, the changes in the reflectance of the PS-backing heterostructure, the electrochemical reaction, and the Joule effect as thermal sources. The model includes the time-dependence of the sample thickness during the electrochemical etching of PS. The changes in the reflectance are identified as the laser reflections in the internal layers of the system. The reflectance is modeled by an additional sinusoidal-monochromatic light source and its modulated frequency is related to the velocity of the PS growth. The chemical reaction and the DC components of the heat sources are taken as an average value from the experimental data. The theoretical results are in agreement with the experimental data and hence provided a method to determine variables of the PS growth, such as the etching velocity and the thickness of the porous layer during the growing process.

  9. 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.

  10. Exotic electroweak signals in the twin Higgs model

    NASA Astrophysics Data System (ADS)

    Cheng, Hsin-Chia; Salvioni, Ennio; Tsai, Yuhsin

    2017-06-01

    The twin Higgs model is the preeminent example of a theory of neutral naturalness, where the new particles that alleviate the little hierarchy problem are Standard Model (SM) singlets. The most promising collider search strategy, based on rare Higgs decays, is nevertheless not effective in significant regions of the parameter space of the low-energy theory. This underlines the importance of phenomenological studies on ultraviolet completions of the twin Higgs model, which must lie at a scale lower than 5-10 TeV. We pursue this course in the context of nonsupersymmetric completions, focusing on exotic fermions that carry SM electroweak and twin color charges, as well as on exotic vectors that transform as the bifundamental of the electroweak or color groups. Both Z2 -preserving and Z2 -breaking mass spectra are considered for the exotic fermions. In the former case they must be heavier than ˜1 TeV , but can still be sizably produced in the decays of the color bifundamental vector. In the Z2-breaking scenario, the exotic fermions can have masses in the few hundred GeV range without significantly increasing the fine-tuning. Once pair-produced through the electroweak interactions, they naturally form bound states held together by the twin color force, which subsequently annihilate back to SM particles. The associated resonance signals are discussed in detail. We also outline the phenomenology of the electroweak bifundamental vectors, some of which mix with the SM W and Z and can therefore be singly produced in hadron collisions.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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

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

    PubMed Central

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

    2012-01-01

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

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

    PubMed

    Engelberg, David; Perlman, Riki; Levitzki, Alexander

    2014-12-01

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

  19. An Interdisciplinary Approach for Designing Kinetic Models of the Ras/MAPK Signaling Pathway.

    PubMed

    Reis, Marcelo S; Noël, Vincent; Dias, Matheus H; Albuquerque, Layra L; Guimarães, Amanda S; Wu, Lulu; Barrera, Junior; Armelin, Hugo A

    2017-01-01

    We present in this article a methodology for designing kinetic models of molecular signaling networks, which was exemplarily applied for modeling one of the Ras/MAPK signaling pathways in the mouse Y1 adrenocortical cell line. The methodology is interdisciplinary, that is, it was developed in a way that both dry and wet lab teams worked together along the whole modeling process.

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  5. Generalized logical model based on network topology to capture the dynamical trends of cellular signaling pathways.

    PubMed

    Zhang, Fan; Chen, Haoting; Zhao, Li Na; Liu, Hui; Przytycka, Teresa M; Zheng, Jie

    2016-01-11

    Cellular responses to extracellular perturbations require signaling pathways to capture and transmit the signals. However, the underlying molecular mechanisms of signal transduction are not yet fully understood, thus detailed and comprehensive models may not be available for all the signaling pathways. In particular, insufficient knowledge of parameters, which is a long-standing hindrance for quantitative kinetic modeling necessitates the use of parameter-free methods for modeling and simulation to capture dynamic properties of signaling pathways. We present a computational model that is able to simulate the graded responses to degradations, the sigmoidal biological relationships between signaling molecules and the effects of scheduled perturbations to the cells. The simulation results are validated using experimental data of protein phosphorylation, demonstrating that the proposed model is capable of capturing the main trend of protein activities during the process of signal transduction. Compared with existing simulators, our model has better performance on predicting the state transitions of signaling networks. The proposed simulation tool provides a valuable resource for modeling cellular signaling pathways using a knowledge-based method.

  6. 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.

  7. A Minimal Model of Signaling Network Elucidates Cell-to-Cell Stochastic Variability in Apoptosis

    PubMed Central

    Raychaudhuri, Subhadip

    2010-01-01

    Background Signaling networks are designed to sense an environmental stimulus and adapt to it. We propose and study a minimal model of signaling network that can sense and respond to external stimuli of varying strength in an adaptive manner. The structure of this minimal network is derived based on some simple assumptions on its differential response to external stimuli. Methodology We employ stochastic differential equations and probability distributions obtained from stochastic simulations to characterize differential signaling response in our minimal network model. Gillespie's stochastic simulation algorithm (SSA) is used in this study. Conclusions/Significance We show that the proposed minimal signaling network displays two distinct types of response as the strength of the stimulus is decreased. The signaling network has a deterministic part that undergoes rapid activation by a strong stimulus in which case cell-to-cell fluctuations can be ignored. As the strength of the stimulus decreases, the stochastic part of the network begins dominating the signaling response where slow activation is observed with characteristic large cell-to-cell stochastic variability. Interestingly, this proposed stochastic signaling network can capture some of the essential signaling behaviors of a complex apoptotic cell death signaling network that has been studied through experiments and large-scale computer simulations. Thus we claim that the proposed signaling network is an appropriate minimal model of apoptosis signaling. Elucidating the fundamental design principles of complex cellular signaling pathways such as apoptosis signaling remains a challenging task. We demonstrate how our proposed minimal model can help elucidate the effect of a specific apoptotic inhibitor Bcl-2 on apoptotic signaling in a cell-type independent manner. We also discuss the implications of our study in elucidating the adaptive strategy of cell death signaling pathways. PMID:20711445

  8. A minimal model of signaling network elucidates cell-to-cell stochastic variability in apoptosis.

    PubMed

    Raychaudhuri, Subhadip

    2010-08-11

    Signaling networks are designed to sense an environmental stimulus and adapt to it. We propose and study a minimal model of signaling network that can sense and respond to external stimuli of varying strength in an adaptive manner. The structure of this minimal network is derived based on some simple assumptions on its differential response to external stimuli. We employ stochastic differential equations and probability distributions obtained from stochastic simulations to characterize differential signaling response in our minimal network model. Gillespie's stochastic simulation algorithm (SSA) is used in this study. We show that the proposed minimal signaling network displays two distinct types of response as the strength of the stimulus is decreased. The signaling network has a deterministic part that undergoes rapid activation by a strong stimulus in which case cell-to-cell fluctuations can be ignored. As the strength of the stimulus decreases, the stochastic part of the network begins dominating the signaling response where slow activation is observed with characteristic large cell-to-cell stochastic variability. Interestingly, this proposed stochastic signaling network can capture some of the essential signaling behaviors of a complex apoptotic cell death signaling network that has been studied through experiments and large-scale computer simulations. Thus we claim that the proposed signaling network is an appropriate minimal model of apoptosis signaling. Elucidating the fundamental design principles of complex cellular signaling pathways such as apoptosis signaling remains a challenging task. We demonstrate how our proposed minimal model can help elucidate the effect of a specific apoptotic inhibitor Bcl-2 on apoptotic signaling in a cell-type independent manner. We also discuss the implications of our study in elucidating the adaptive strategy of cell death signaling pathways.

  9. 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

  10. 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.

  11. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  13. 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.

  14. Modeling inter-signal arrival times for accurate detection of CAN bus signal injection attacks

    SciTech Connect

    Moore, Michael Roy; Bridges, Robert A; Combs, Frank L; Starr, Michael S; Prowell, Stacy J

    2017-01-01

    Modern vehicles rely on hundreds of on-board electronic control units (ECUs) communicating over in-vehicle networks. As external interfaces to the car control networks (such as the on-board diagnostic (OBD) port, auxiliary media ports, etc.) become common, and vehicle-to-vehicle / vehicle-to-infrastructure technology is in the near future, the attack surface for vehicles grows, exposing control networks to potentially life-critical attacks. This paper addresses the need for securing the CAN bus by detecting anomalous traffic patterns via unusual refresh rates of certain commands. While previous works have identified signal frequency as an important feature for CAN bus intrusion detection, this paper provides the first such algorithm with experiments on five attack scenarios. Our data-driven anomaly detection algorithm requires only five seconds of training time (on normal data) and achieves true positive / false discovery rates of 0.9998/0.00298, respectively (micro-averaged across the five experimental tests).

  15. Detecting Primary Signal Using Time and Space Model (PREPRINT)

    DTIC Science & Technology

    2010-06-01

    Conference of Telecommunications, Networking, and Broad Casting (PG Net 2007), June 2007. 4. J. Unnikrishnan and V. Veeravalli, “Cooperative...Cognitive Radio”, 41st Annual Conference on Information Sciences and Systems (CISS apos 07), 14-16 March 2007 Page(s):369 – 369, 2007. 14. M . Gudmundson...Signals, Systems and Computers, Nov. 2004. 19. M . Vu, N. Devroye, and V. Tarokh, “The Primary Exclusive Region in Cognitive Networks“, invited paper

  16. Specification, annotation, visualization and simulation of a large rule-based model for ERBB receptor signaling

    PubMed Central

    2012-01-01

    Background Mathematical/computational models are needed to understand cell signaling networks, which are complex. Signaling proteins contain multiple functional components and multiple sites of post-translational modification. The multiplicity of components and sites of modification ensures that interactions among signaling proteins have the potential to generate myriad protein complexes and post-translational modification states. As a result, the number of chemical species that can be populated in a cell signaling network, and hence the number of equations in an ordinary differential equation model required to capture the dynamics of these species, is prohibitively large. To overcome this problem, the rule-based modeling approach has been developed for representing interactions within signaling networks efficiently and compactly through coarse-graining of the chemical kinetics of molecular interactions. Results Here, we provide a demonstration that the rule-based modeling approach can be used to specify and simulate a large model for ERBB receptor signaling that accounts for site-specific details of protein-protein interactions. The model is considered large because it corresponds to a reaction network containing more reactions than can be practically enumerated. The model encompasses activation of ERK and Akt, and it can be simulated using a network-free simulator, such as NFsim, to generate time courses of phosphorylation for 55 individual serine, threonine, and tyrosine residues. The model is annotated and visualized in the form of an extended contact map. Conclusions With the development of software that implements novel computational methods for calculating the dynamics of large-scale rule-based representations of cellular signaling networks, it is now possible to build and analyze models that include a significant fraction of the protein interactions that comprise a signaling network, with incorporation of the site-specific details of the interactions

  17. 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.

  18. Short-term information processing, long-term responses: Insights by mathematical modeling of signal transduction

    PubMed Central

    Schneider, Annette; Klingmüller, Ursula; Schilling, Marcel

    2012-01-01

    How do cells interpret information from their environment and translate it into specific cell fate decisions? We propose that cell fate is already encoded in early signaling events and thus can be predicted from defined signal properties. Specifically, we hypothesize that the time integral of activated key signaling molecules can be correlated to cellular behavior such as proliferation or differentiation. The identification of these decisive key signal mediators and their connection to cell fate is facilitated by mathematical modeling. A possible mechanistic linkage between signaling dynamics and cellular function is the directed control of gene regulatory networks by defined signals. Targeted experiments in combination with mathematical modeling can increase our understanding of how cells process information and realize distinct cell fates. PMID:22528856

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

    PubMed

    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.

  20. 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

  1. 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.

  2. 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

  3. Transforming Boolean models to continuous models: methodology and application to T-cell receptor signaling

    PubMed Central

    Wittmann, Dominik M; Krumsiek, Jan; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Klamt, Steffen; Theis, Fabian J

    2009-01-01

    Background The understanding of regulatory and signaling networks has long been a core objective in Systems Biology. Knowledge about these networks is mainly of qualitative nature, which allows the construction of Boolean models, where the state of a component is either 'off' or 'on'. While often able to capture the essential behavior of a network, these models can never reproduce detailed time courses of concentration levels. Nowadays however, experiments yield more and more quantitative data. An obvious question therefore is how qualitative models can be used to explain and predict the outcome of these experiments. Results In this contribution we present a canonical way of transforming Boolean into continuous models, where the use of multivariate polynomial interpolation allows transformation of logic operations into a system of ordinary differential equations (ODE). The method is standardized and can readily be applied to large networks. Other, more limited approaches to this task are briefly reviewed and compared. Moreover, we discuss and generalize existing theoretical results on the relation between Boolean and continuous models. As a test case a logical model is transformed into an extensive continuous ODE model describing the activation of T-cells. We discuss how parameters for this model can be determined such that quantitative experimental results are explained and predicted, including time-courses for multiple ligand concentrations and binding affinities of different ligands. This shows that from the continuous model we may obtain biological insights not evident from the discrete one. Conclusion The presented approach will facilitate the interaction between modeling and experiments. Moreover, it provides a straightforward way to apply quantitative analysis methods to qualitatively described systems. PMID:19785753

  4. Mouth-clicks used by blind expert human echolocators - signal description and model based signal synthesis.

    PubMed

    Thaler, Lore; Reich, Galen M; Zhang, Xinyu; Wang, Dinghe; Smith, Graeme E; Tao, Zeng; Abdullah, Raja Syamsul Azmir Bin Raja; Cherniakov, Mikhail; Baker, Christopher J; Kish, Daniel; Antoniou, Michail

    2017-08-01

    Echolocation is the ability to use sound-echoes to infer spatial information about the environment. Some blind people have developed extraordinary proficiency in echolocation using mouth-clicks. The first step of human biosonar is the transmission (mouth click) and subsequent reception of the resultant sound through the ear. Existing head-related transfer function (HRTF) data bases provide descriptions of reception of the resultant sound. For the current report, we collected a large database of click emissions with three blind people expertly trained in echolocation, which allowed us to perform unprecedented analyses. Specifically, the current report provides the first ever description of the spatial distribution (i.e. beam pattern) of human expert echolocation transmissions, as well as spectro-temporal descriptions at a level of detail not available before. Our data show that transmission levels are fairly constant within a 60° cone emanating from the mouth, but levels drop gradually at further angles, more than for speech. In terms of spectro-temporal features, our data show that emissions are consistently very brief (~3ms duration) with peak frequencies 2-4kHz, but with energy also at 10kHz. This differs from previous reports of durations 3-15ms and peak frequencies 2-8kHz, which were based on less detailed measurements. Based on our measurements we propose to model transmissions as sum of monotones modulated by a decaying exponential, with angular attenuation by a modified cardioid. We provide model parameters for each echolocator. These results are a step towards developing computational models of human biosonar. For example, in bats, spatial and spectro-temporal features of emissions have been used to derive and test model based hypotheses about behaviour. The data we present here suggest similar research opportunities within the context of human echolocation. Relatedly, the data are a basis to develop synthetic models of human echolocation that could be

  5. 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.

  6. Addressing multi-use issues in sustainable forest management with signal-transfer modeling

    Treesearch

    Robert J. Luxmoore; William W. Hargrove; M. Lynn Tharp; W. Mac Post; Michael W. Berry; Karen S. Minser; Wendell P. Cropper; Dale W. Johnson; Boris Zeide; Ralph L. Amateis; Harold E. Burkhart; V. Clark Baldwin; Kelly D. Peterson

    2002-01-01

    Management decisions concerning impacts of projected changes in environmental and social conditions on multi-use forest products and services, such as productivity, water supply or carbon sequestration, may be facilitated with signal-transfer modeling. This simulation method utilizes a hierarchy of simulators in which the integrated responses (signals) from smaller-...

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

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

    PubMed Central

    Verbruggen, Frederick; Logan, Gordon D.

    2009-01-01

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

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

    PubMed Central

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

    2003-01-01

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

  14. Robust detection of heartbeats using association models from blood pressure and EEG signals.

    PubMed

    Jeon, Taegyun; Yu, Jongmin; Pedrycz, Witold; Jeon, Moongu; Lee, Boreom; Lee, Byeongcheol

    2016-01-15

    The heartbeat is fundamental cardiac activity which is straightforwardly detected with a variety of measurement techniques for analyzing physiological signals. Unfortunately, unexpected noise or contaminated signals can distort or cut out electrocardiogram (ECG) signals in practice, misleading the heartbeat detectors to report a false heart rate or suspend itself for a considerable length of time in the worst case. To deal with the problem of unreliable heartbeat detection, PhysioNet/CinC suggests a challenge in 2014 for developing robust heart beat detectors using multimodal signals. This article proposes a multimodal data association method that supplements ECG as a primary input signal with blood pressure (BP) and electroencephalogram (EEG) as complementary input signals when input signals are unreliable. If the current signal quality index (SQI) qualifies ECG as a reliable input signal, our method applies QRS detection to ECG and reports heartbeats. Otherwise, the current SQI selects the best supplementary input signal between BP and EEG after evaluating the current SQI of BP. When BP is chosen as a supplementary input signal, our association model between ECG and BP enables us to compute their regular intervals, detect characteristics BP signals, and estimate the locations of the heartbeat. When both ECG and BP are not qualified, our fusion method resorts to the association model between ECG and EEG that allows us to apply an adaptive filter to ECG and EEG, extract the QRS candidates, and report heartbeats. The proposed method achieved an overall score of 86.26 % for the test data when the input signals are unreliable. Our method outperformed the traditional method, which achieved 79.28 % using QRS detector and BP detector from PhysioNet. Our multimodal signal processing method outperforms the conventional unimodal method of taking ECG signals alone for both training and test data sets. To detect the heartbeat robustly, we have proposed a novel multimodal data

  15. 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.

  16. 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.

  17. 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.

  18. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

  20. 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

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. Melanoma mouse model implicates metabotropic glutamate signaling in melanocytic neoplasia.

    PubMed

    Pollock, Pamela M; Cohen-Solal, Karine; Sood, Raman; Namkoong, Jin; Martino, Jeffrey J; Koganti, Aruna; Zhu, Hua; Robbins, Christiane; Makalowska, Izabela; Shin, Seung-Shick; Marin, Yari; Roberts, Kathleen G; Yudt, Laura M; Chen, Amy; Cheng, Jun; Incao, Arturo; Pinkett, Heather W; Graham, Christopher L; Dunn, Karen; Crespo-Carbone, Steven M; Mackason, Kerine R; Ryan, Kevin B; Sinsimer, Daniel; Goydos, James; Reuhl, Kenneth R; Eckhaus, Michael; Meltzer, Paul S; Pavan, William J; Trent, Jeffrey M; Chen, Suzie

    2003-05-01

    To gain insight into melanoma pathogenesis, we characterized an insertional mouse mutant, TG3, that is predisposed to develop multiple melanomas. Physical mapping identified multiple tandem insertions of the transgene into intron 3 of Grm1 (encoding metabotropic glutamate receptor 1) with concomitant deletion of 70 kb of intronic sequence. To assess whether this insertional mutagenesis event results in alteration of transcriptional regulation, we analyzed Grm1 and two flanking genes for aberrant expression in melanomas from TG3 mice. We observed aberrant expression of only Grm1. Although we did not detect its expression in normal mouse melanocytes, Grm1 was ectopically expressed in the melanomas from TG3 mice. To confirm the involvement of Grm1 in melanocytic neoplasia, we created an additional transgenic line with Grm1 expression driven by the dopachrome tautomerase promoter. Similar to the original TG3, the Tg(Grm1)EPv line was susceptible to melanoma. In contrast to human melanoma, these transgenic mice had a generalized hyperproliferation of melanocytes with limited transformation to fully malignant metastasis. We detected expression of GRM1 in a number of human melanoma biopsies and cell lines but not in benign nevi and melanocytes. This study provides compelling evidence for the importance of metabotropic glutamate signaling in melanocytic neoplasia.

  9. 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).

  10. 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.

  11. 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.

  12. Logic-Based Models for the Analysis of Cell Signaling Networks†

    PubMed Central

    2010-01-01

    Computational models are increasingly used to analyze the operation of complex biochemical networks, including those involved in cell signaling networks. Here we review recent advances in applying logic-based modeling to mammalian cell biology. Logic-based models represent biomolecular networks in a simple and intuitive manner without describing the detailed biochemistry of each interaction. A brief description of several logic-based modeling methods is followed by six case studies that demonstrate biological questions recently addressed using logic-based models and point to potential advances in model formalisms and training procedures that promise to enhance the utility of logic-based methods for studying the relationship between environmental inputs and phenotypic or signaling state outputs of complex signaling networks. PMID:20225868

  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. 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.

  15. 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.

  16. 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…

  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. 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

  19. 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.

  20. A mathematical model coupling polarity signaling to cell adhesion explains diverse cell migration patterns.

    PubMed

    Holmes, William R; Park, JinSeok; Levchenko, Andre; Edelstein-Keshet, Leah

    2017-05-01

    Protrusion and retraction of lamellipodia are common features of eukaryotic cell motility. As a cell migrates through its extracellular matrix (ECM), lamellipod growth increases cell-ECM contact area and enhances engagement of integrin receptors, locally amplifying ECM input to internal signaling cascades. In contrast, contraction of lamellipodia results in reduced integrin engagement that dampens the level of ECM-induced signaling. These changes in cell shape are both influenced by, and feed back onto ECM signaling. Motivated by experimental observations on melanoma cells lines (1205Lu and SBcl2) migrating on fibronectin (FN) coated topographic substrates (anisotropic post-density arrays), we probe this interplay between intracellular and ECM signaling. Experimentally, cells exhibited one of three lamellipodial dynamics: persistently polarized, random, or oscillatory, with competing lamellipodia oscillating out of phase (Park et al., 2017). Pharmacological treatments, changes in FN density, and substrate topography all affected the fraction of cells exhibiting these behaviours. We use these observations as constraints to test a sequence of hypotheses for how intracellular (GTPase) and ECM signaling jointly regulate lamellipodial dynamics. The models encoding these hypotheses are predicated on mutually antagonistic Rac-Rho signaling, Rac-mediated protrusion (via activation of Arp2/3 actin nucleation) and Rho-mediated contraction (via ROCK phosphorylation of myosin light chain), which are coupled to ECM signaling that is modulated by protrusion/contraction. By testing each model against experimental observations, we identify how the signaling layers interact to generate the diverse range of cell behaviors, and how various molecular perturbations and changes in ECM signaling modulate the fraction of cells exhibiting each. We identify several factors that play distinct but critical roles in generating the observed dynamic: (1) competition between lamellipodia for

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

    PubMed

    Bykov, V; Gol'dshtein, V

    2016-05-01

    In recent few decades numerical treatment has become a standard tool in the system analysis and investigation of complex chemical reactions networks of reacting flows. The information about certain networks of biochemical reactions constantly increases. This leads to detailed descriptions of biochemical processes as a system of differential equations of high complexity and dimension. Nowadays methods, which are able automatically reduce the system dimension and complexity, are highly desirable. Recently several methods were developed for model reduction in combustion and chemical kinetics aiming at automatic numerical treatment and constructing the reduced system. The reduced system represents reliable description reproducing the detailed system behavior accurately enough. In this work the method of qualitative ODEs system analysis and the global quasi-linearization method (GQL) for kinetic mechanism reduction of combustion models are applied to the biochemical reaction network of the apoptosis. It is shown that the original model of the apoptosis can be essentially simplified firstly by using linear system integrals (9 dimensions) of the ODEs system, secondly the results of GQL analysis reveals the possibility of a further reduction (4 dimensions). It means that the final system dimension reaches 15 compare to the original 28 without any noticeable accuracy losses. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. 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.

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

    PubMed Central

    2013-01-01

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

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. Loran-C Signal Analysis Propagation Model Evaluation.

    DTIC Science & Technology

    1979-07-01

    Recipient’s Caoesi No. Propagation Model Evaluation de i e t tcnuth accout forbth teKenndeth mpchwartn mh eveoPed b 9. P a, ou- n ts f,0e ==tori...is currently used for Loran-C chart preparation. 3. Wait’s Multisegment Spherical Earth (MULSEG) - an extension of the classical theory to account for...pre- dictions are described. Limitations of the current theory with recom- mendations for further research are also discussed. An example of predicted

  9. 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.

  10. 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.

  11. 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.

  12. 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

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

    PubMed

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

    2015-11-07

    Signaling proteins are an important topic in drug development due to the increased importance of finding fast, accurate and cheap methods to evaluate new molecular targets involved in specific diseases. The complexity of the protein structure hinders the direct association of the signaling activity with the molecular structure. Therefore, the proposed solution involves the use of protein star graphs for the peptide sequence information encoding into specific topological indices calculated with S2SNet tool. The Quantitative Structure-Activity Relationship classification model obtained with Machine Learning techniques is able to predict new signaling peptides. The best classification model is the first signaling prediction model, which is based on eleven descriptors and it was obtained using the Support Vector Machines-Recursive Feature Elimination (SVM-RFE) technique with the Laplacian kernel (RFE-LAP) and an AUROC of 0.961. Testing a set of 3114 proteins of unknown function from the PDB database assessed the prediction performance of the model. Important signaling pathways are presented for three UniprotIDs (34 PDBs) with a signaling prediction greater than 98.0%. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. 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.

  15. 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.

  16. Sunyaev-Zel'dovich Effect Signals in Cluster Models

    NASA Astrophysics Data System (ADS)

    Reid, Beth A.; Spergel, D. N.

    2006-12-01

    The upcoming generation of Sunyaev-Zel’dovich effect (SZE) surveys will shed fresh light onto the study of clusters. What will this new observational window reveal about cluster properties? What can we learn from combining X-ray, SZE, and optical observations? How do variations in the gas entropy profile, dark matter concentration, accretion pressure, and intracluster medium (ICM) mass fraction affect SZE observables? We investigate the signature of these important cluster parameters with an analytic model of the ICM. Given the current uncertainties in ICM physics, our approach is to span the range of plausible models motivated by observations and a small set of assumptions. We find a tight relation between the central Compton parameter and the X-ray luminosity outside the cluster core, suggesting that these observables carry the same information about the ICM. The total SZE luminosity is proportional to the thermal energy of the gas, and is a surprisingly robust indicator of cluster mass: LSZ α fICM M5/3. We show that a combination of LSZ and the half-luminosity radius rSZ provides a measure of the potential energy of the cluster gas, and thus we can deduce the total energy content of the ICM. We caution that any systematic variation of the ICM mass fraction will distort the expected LSZ M calibration to be used to study the evolution of cluster number density, and propose a technique using kSZ to constrain fICM(M,z). B. A. R. acknowledges support from the National Science Foundation (NSF) Graduate Research Fellowship. D. N. S. acknowledges support from NASA Astrophysics Theory Program NNG04GK55G and NSF PIRE grant OISE-0530095.

  17. Sunyaev-Zel'dovich Effect Signals in Cluster Models

    NASA Astrophysics Data System (ADS)

    Reid, Beth A.; Spergel, David N.

    2006-11-01

    The upcoming generation of Sunyaev-Zel'dovich effect (SZE) surveys will shed fresh light onto the study of clusters. What will this new observational window reveal about cluster properties? What can we learn from combining X-ray, SZE, and optical observations? How do variations in the gas entropy profile, dark matter concentration, accretion pressure, and intracluster medium (ICM) mass fraction affect SZE observables? We investigate the signature of these important cluster parameters with an analytic model of the ICM. Given the current uncertainties in ICM physics, our approach is to span the range of plausible models motivated by observations and a small set of assumptions. We find a tight relation between the central Compton parameter and the X-ray luminosity outside the cluster core, suggesting that these observables carry the same information about the ICM. The total SZE luminosity is proportional to the thermal energy of the gas and is a surprisingly robust indicator of cluster mass: LSZ~fICMM5/3. We show that a combination of LSZ and the half-luminosity radius rSZ provides a measure of the potential energy of the cluster gas, and thus we can deduce the total energy content of the ICM. We caution that any systematic variation of the ICM mass fraction will distort the expected LSZ-M calibration to be used to study the evolution of cluster number density, and propose a technique using the kinetic Sunyaev-Zel'dovich (kSZ) effect to constrain fICM(M,z).

  18. 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.

  19. 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.

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

    PubMed

    Kirana, Firman Ahmad; Alatas, Husin; 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.

  1. 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.

  2. 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

  3. 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

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

    PubMed

    Yi, Yongwoo; Merfeld, Daniel M

    2016-04-01

    Perceptual thresholds are commonly assayed in the laboratory and clinic. When precision and accuracy are required, thresholds are quantified by fitting a psychometric function to forced-choice data. The primary shortcoming of this approach is that it typically requires 100 trials or more to yield accurate (i.e., small bias) and precise (i.e., small variance) psychometric parameter estimates. We show that confidence probability judgments combined with a model of confidence can yield psychometric parameter estimates that are markedly more precise and/or markedly more efficient than conventional methods. Specifically, both human data and simulations show that including confidence probability judgments for just 20 trials can yield psychometric parameter estimates that match the precision of those obtained from 100 trials using conventional analyses. Such an efficiency advantage would be especially beneficial for tasks (e.g., taste, smell, and vestibular assays) that require more than a few seconds for each trial, but this potential benefit could accrue for many other tasks. Copyright © 2016 the American Physiological Society.

  5. 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.

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

    USDA-ARS?s Scientific Manuscript database

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

  7. 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.

  8. 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.

  9. 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.

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

    SciTech Connect

    Pettigrew, Michel F.; Resat, Haluk

    2005-09-15

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

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

    PubMed

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

    2015-01-01

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

  12. 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

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. 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

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

    PubMed

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

    2010-07-01

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

  19. The performance of different synthesis signals in acoustic models of cochlear implants.

    PubMed

    Strydom, Trudie; Hanekom, Johan J

    2011-02-01

    Synthesis (carrier) signals in acoustic models embody assumptions about perception of auditory electric stimulation. This study compared speech intelligibility of consonants and vowels processed through a set of nine acoustic models that used Spectral Peak (SPEAK) and Advanced Combination Encoder (ACE)-like speech processing, using synthesis signals which were representative of signals used previously in acoustic models as well as two new ones. Performance of the synthesis signals was determined in terms of correspondence with cochlear implant (CI) listener results for 12 attributes of phoneme perception (consonant and vowel recognition; F1, F2, and duration information transmission for vowels; voicing, manner, place of articulation, affrication, burst, nasality, and amplitude envelope information transmission for consonants) using four measures of performance. Modulated synthesis signals produced the best correspondence with CI consonant intelligibility, while sinusoids, narrow noise bands, and varying noise bands produced the best correspondence with CI vowel intelligibility. The signals that performed best overall (in terms of correspondence with both vowel and consonant attributes) were modulated and unmodulated noise bands of varying bandwidth that corresponded to a linearly varying excitation width of 0.4 mm at the apical to 8 mm at the basal channels.

  20. A computer simulation model for Doppler ultrasound signals from pulsatile blood flow in stenosed vessels.

    PubMed

    Gao, Lian; Zhang, Yufeng; Zhang, Kexin; Cai, Guanghui; Zhang, Junhua; Shi, Xinling

    2012-09-01

    A computer simulation model based on an analytic flow velocity distribution is proposed to generate Doppler ultrasound signals from pulsatile blood flow in the vessels with various stenosis degrees. The model takes into account the velocity field from pulsatile blood flow in the stenosed vessels, sample volume shape and acoustic factors that affect the Doppler signals. By analytically solving the Navier-Stokes equations, the velocity distributions of pulsatile blood flow in the vessels with various stenosis degrees are firstly calculated according to the velocity at the axis of the circular tube. Secondly, power spectral density (PSD) of the Doppler signals is estimated by summing the contribution of all scatterers passing through the sample volume grouped into elemental volumes. Finally, Doppler signals are generated using cosine-superposed components that are modulated by the PSD functions that vary over the cardiac cycle. The results show that the model generates Doppler blood flow signals with characteristics similar to those found in practice. It could be concluded that the proposed approach offers the advantages of computational simplicity and practicality for simulating Doppler ultrasound signals from pulsatile blood flow in stenosed vessels. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. 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.

  2. 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.

  3. 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.

  4. A Simulation Study of the Radiation-Induced Bystander Effect: Modeling with Stochastically Defined Signal Reemission

    PubMed Central

    Sasaki, Kohei; Wakui, Kosuke; Tsutsumi, Kaori; Itoh, Akio; Date, Hiroyuki

    2012-01-01

    The radiation-induced bystander effect (RIBE) has been experimentally observed for different types of radiation, cell types, and cell culture conditions. However, the behavior of signal transmission between unirradiated and irradiated cells is not well known. In this study, we have developed a new model for RIBE based on the diffusion of soluble factors in cell cultures using a Monte Carlo technique. The model involves the signal emission probability from bystander cells following Poisson statistics. Simulations with this model show that the spatial configuration of the bystander cells agrees well with that of corresponding experiments, where the optimal emission probability is estimated through a large number of simulation runs. It was suggested that the most likely probability falls within 0.63–0.92 for mean number of the emission signals ranging from 1.0 to 2.5. PMID:23197991

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

    PubMed Central

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

    2014-01-01

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

  6. 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

  7. 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.

  8. 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.

  9. Adaptive denoising for simplified signal-dependent random noise model in optoelectronic detector

    NASA Astrophysics Data System (ADS)

    Zhang, Yu; Wang, Weiping; Wang, Guangyi; Xu, Jiangtao

    2017-05-01

    Existing denoising algorithms based on a simplified signal-dependent noise model are valid under the assumption of the predefined parameters. Consequently, these methods fail if the predefined conditions are not satisfied. An adaptive method for eliminating random noise from the simplified signal-dependent noise model is presented in this paper. A linear mapping function between multiplicative noise and noiseless image data is established using the Maclaurin formula. Through demonstrations of the cross-correlation between random variables and independent random variable functions, the mapping function between the variances of multiplicative noise and noiseless image data is acquired. Accordingly, the adaptive denoising model of simplified signal-dependent noise in the wavelet domain is built. The experimental results confirm that the proposed method outperforms conventional ones.

  10. The eye of Drosophila as a model system for studying intracellular signaling in ontogenesis and pathogenesis.

    PubMed

    Katanaev, V L; Kryuchkov, M V

    2011-12-01

    Many human diseases are caused by malfunction of basic types of cellular activity such as proliferation, differentiation, apoptosis, cell polarization, and migration. In turn, these processes are associated with different routes of intracellular signal transduction. A number of model systems have been designed to study normal and abnormal cellular and molecular processes associated with pathogenesis. The developing eye of the fruit fly Drosophila melanogaster is one of these systems. The sequential development of compound eyes of this insect makes it possible to model human neurodegenerative diseases and mechanisms of carcinogenesis. In this paper we overview the program of the eye development in Drosophila, with emphasis on intracellular signaling pathways that regulate this complex process. We discuss in detail the roles of the Notch, Hedgehog, TGFβ, Wnt, and receptor tyrosine kinase signaling pathways in Drosophila eye development and human pathology. We also briefly describe the modern methods of experimentation with this model organism to analyze the function of human pathogenic proteins.

  11. 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.

  12. Successive spike times predicted by a stochastic neuronal model with a variable input signal.

    PubMed

    D'Onofrio, Giuseppe; Pirozzi, Enrica

    2016-06-01

    Two different stochastic processes are used to model the evolution of the membrane voltage of a neuron exposed to a time-varying input signal. The first process is an inhomogeneous Ornstein-Uhlenbeck process and its first passage time through a constant threshold is used to model the first spike time after the signal onset. The second process is a Gauss-Markov process identified by a particular mean function dependent on the first passage time of the first process. It is shown that the second process is also of a diffusion type. The probability density function of the maximum between the first passage time of the first and the second process is considered to approximate the distribution of the second spike time. Results obtained by simulations are compared with those following the numerical and asymptotic approximations. A general equation to model successive spike times is given. Finally, examples with specific input signals are provided.

  13. 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.

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

    PubMed Central

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

    2014-01-01

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

  15. 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.

  16. 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

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

    PubMed

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

    2016-05-01

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

  18. 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.

  19. 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

  20. When should signals of submission be given?-A game theory model.

    PubMed

    Matsumura, Shuichi; Hayden, Thomas J

    2006-06-07

    During contests, losing animals often show signals communicating submission. From an evolutionary viewpoint, however, it is not so obvious why the losing individual gives such a signal instead of running away and why the winning individual accepts the signal instead of inflicting more severe damage. We investigated factors influencing the evolution of signals of submission using a numerical ESS model. The present analysis reveals that there is much space for the evolution of signals of submission, even when the winner of an escalated contest gets some extra benefit. In most cases, signals of submission are given by animals which are slightly or moderately weaker than the opponent. Signals of submission are expected to occur frequently (1) when the value of contested resource does not differ greatly from the cost of injury, (2) when the extra benefit of winning an escalated contest is small, (3) when the opportunity for safe retreat by the losing animal is small, and (4) when the estimation of the difference in the resource holding potential (RHP) between the combatants is accurate but not perfect.

  1. Modeling signaling pathways leading to wrinkle formation: identification of the skin aging target.

    PubMed

    Chauhan, Pallavi; Shakya, Madhvi

    2009-01-01

    In the present scenario, wrinkle formation, prominent sign of skin ageing, is one of the most demanding areas of research. This burgeoning research demand to reduce, delay and restore the effects of skin ageing has led to the study of various signaling pathways leading to wrinkle formation. Wrinkles appear on skin due to influence of intrinsic and extrinsic factors on mitogenic reactions and signal transduction pathways. The aim of the present study is to analyze each protein involved in the signaling pathway leading to dilapidation of collagen and an attempt has been made to compare different signal transduction pathways to identify a common target for skin ageing. In the present work, bioinformatics tools have been used to extract information from already existing experimental data. The statistical techniques are used for further analysis and make useful predictions for skin ageing. Stressors like UV irradiation, osmotic stress and heat shock have been reported to activate epidermal growth factor receptor, interleukin 1 receptor, tumor necrosis factor receptor, platelet-derived growth factor receptor and platelet activation factor receptor signaling pathways, which lead to the production of matrix metalloproteinases, collagen degradation and, consequently, wrinkle formation. When all the five signaling pathways were modeled, the c-jun part of the AP-1 transcription factor was found to be a common intermediate protein involved in all the signaling cascades. Moreover, it shows differential expression in the skin on response to stressors. We proposed c-jun to be the most potent target for drug designing against wrinkle formation.

  2. Mathematical modeling of the insulin signal transduction pathway for prediction of insulin sensitivity from expression data.

    PubMed

    Ho, Clark K; Rahib, Lola; Liao, James C; Sriram, Ganesh; Dipple, Katrina M

    2015-01-01

    Mathematical models of biological pathways facilitate a systems biology approach to medicine. However, these models need to be updated to reflect the latest available knowledge of the underlying pathways. We developed a mathematical model of the insulin signal transduction pathway by expanding the last major previously reported model and incorporating pathway components elucidated since the original model was reported. Furthermore, we show that inputting gene expression data of key components of the insulin signal transduction pathway leads to sensible predictions of glucose clearance rates in agreement with reported clinical measurements. In one set of simulations, our model predicted that glycerol kinase knockout mice have reduced GLUT4 translocation, and consequently, reduced glucose uptake. Additionally, a comparison of our extended model with the original model showed that the added pathway components improve simulations of glucose clearance rates. We anticipate this expanded model to be a useful tool for predicting insulin sensitivity in mammalian tissues with altered expression protein phosphorylation or mRNA levels of insulin signal transduction pathway components. Copyright © 2014 Elsevier Inc. All rights reserved.

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

    PubMed

    Walter, André; Elgar, Mark A

    2012-08-01

    Contemporary animal signals may derive from an elaboration of existing forms or novel non-signalling traits. Unravelling the evolution of the latter is challenging because experiments investigating the maintenance of the signal may provide little insight into its early evolution. The web decorations, or stabilimenta of some orb web spiders represent an intriguing model system to investigate novel animal signals. For over 100 years, biologists have struggled to explain why spiders decorate their webs with additional threads of silk, producing a conspicuous signal on a construction whose function is to entangle unsuspecting prey. The numerous explanations for the maintenance of this behaviour starkly contrast with the absence of a plausible explanation for its evolutionary origin. Our review highlights the difficulties in resolving both the evolution and maintenance of animal signalling, and inferring the causative arrow-even from experimental studies. Drawing on recent research that focuses on physiological processes, we provide a model of the evolutionary progression of web-decorating behaviour. © 2012 The Authors. Biological Reviews © 2011 Cambridge Philosophical Society.

  6. 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.

  7. 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.

  8. 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.

  9. 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

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

    PubMed Central

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

    2014-01-01

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

  11. 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

  12. 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.

  13. 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.

  14. Fast and Stable Signal Deconvolution via Compressible State-Space Models.

    PubMed

    Kazemipour, Abbas; Liu, Ji; Solarana, Krystyna; Nagode, Daniel; Kanold, Patrick; Wu, Min; Babadi, Behtash

    2017-04-13

    Common biological measurements are in the form of noisy convolutions of signals of interest with possibly unknown and transient blurring kernels. Examples include EEG and calcium imaging data. Thus, signal deconvolution of these measurements is crucial in understanding the underlying biological processes. The objective of this paper is to develop fast and stable solutions for signal deconvolution from noisy, blurred and undersampled data, where the signals are in the form of discrete events distributed in time and space. We introduce compressible state-space models as a framework to model and estimate such discrete events. These state-space models admit abrupt changes in the states and have a convergent transition matrix, and are coupled with compressive linear measurements. We consider a dynamic compressive sensing optimization problem and develop a fast solution, using two nested Expectation Maximization algorithms, to jointly estimate the states as well as their transition matrices. Under suitable sparsity assumptions on the dynamics, we prove optimal stability guarantees for the recovery of the states and present a method for the identification of the underlying discrete events with precise confidence bounds. We present simulation studies as well as application to calcium deconvolution and sleep spindle detection, which verify our theoretical results and show significant improvement over existing techniques. Our results show that by explicitly modeling the dynamics of the underlying signals, it is possible to construct signal deconvolution solutions that are scalable, statistically robust, and achieve high temporal resolution. Our proposed methodology provides a framework for modeling and deconvolution of noisy, blurred, and undersampled measurements in a fast and stable fashion, with potential application to a wide range of biological data.

  15. 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

  16. 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

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

    PubMed

    Sriraam, N; Eswaran, C

    2008-09-01

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

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. Spectrum analysis of radar life signal in the three kinds of theoretical models

    NASA Astrophysics Data System (ADS)

    Yang, X. F.; Ma, J. F.; Wang, D.

    2017-02-01

    In the single frequency continuous wave radar life detection system, based on the Doppler effect, the theory model of radar life signal is expressed by the real function, and there is a phenomenon that can't be confirmed by the experiment. When the phase generated by the distance between the measured object and the radar measuring head is л of integer times, the main frequency spectrum of life signal (respiration and heartbeat) is not existed in radar life signal. If this phase is л/2 of odd times, the main frequency spectrum of breath and heartbeat frequency is the strongest. In this paper, we use the Doppler effect as the basic theory, using three different mathematical expressions——real function, complex exponential function and Bessel's function expansion form. They are used to establish the theoretical model of radar life signal. Simulation analysis revealed that the Bessel expansion form theoretical model solve the problem of real function form. Compared with the theoretical model of the complex exponential function, the derived spectral line is greatly reduced in the theoretical model of Bessel expansion form, which is more consistent with the actual situation.

  3. 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

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

    PubMed

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

    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.

  5. 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

  6. 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

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

    PubMed

    Xu, Tiantian; 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.

  8. 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

  9. 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.

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

    PubMed

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

    2015-06-15

    Protein kinase B (Akt) kinases are critical signal transducers mediating insulin action. Genetic studies revealed that Akt1 and Akt2 signalling differentially contribute to sustain lipid and glucose homoeostasis; however Akt isoform-specific effectors remain elusive due to the lack of a suitable model system to mechanistically interrogate Akt isoform-specific signalling. To overcome those technical limitations we developed a novel model system that provides acute and specific control of signalling by Akt isoforms. We generated mutants of Akt1 and Akt2 resistant to the allosteric Akt inhibitor MK-2206. We then developed adipocyte cell lines, in which endogenous Akt1 or Akt2 has been replaced by their corresponding drug-resistant Akt mutant. Treatment of those cells with MK-2206 allowed for acute and specific control of either Akt1 or Akt2 function. Our data showed that Akt1(W80A) and Akt2(W80A) mutants are resistant to MK-2206, dynamically regulated by insulin and able to signal to Akt downstream effectors. Analyses of insulin action in this cellular system showed that Akt1 and Akt2 are both able to mediate insulin regulation of the transcription factor forkhead box O1 (FoxO1) and the glucose transporter 4 (GLUT4), revealing a redundant role for these Akt kinases in the control of glucose transport into fat cells. In contrast, Akt1 signalling is uniquely required for adipogenesis, by controlling the mitotic clonal expansion (MCE) of pre-adipocytes that precedes white adipose cell differentiation. Our data provide new insights into the role of Akt kinases in glucose transport and adipogenesis and support our model system as a valuable tool for the biochemical characterization of signalling by specific Akt isoforms. © 2015 Authors.

  11. 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

  12. 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.

  13. New insights into mammalian signaling pathways using microfluidic pulsatile inputs and mathematical modeling.

    PubMed

    Sumit, M; Takayama, S; Linderman, J J

    2017-01-23

    Temporally modulated input mimics physiology. This chemical communication strategy filters the biochemical noise through entrainment and phase-locking. Under laboratory conditions, it also expands the observability space for downstream responses. A combined approach involving microfluidic pulsatile stimulation and mathematical modeling has led to deciphering of hidden/unknown temporal motifs in several mammalian signaling pathways and has provided mechanistic insights, including how these motifs combine to form distinct band-pass filters and govern fate regulation under dynamic microenvironment. This approach can be utilized to understand signaling circuit architectures and to gain mechanistic insights for several other signaling systems. Potential applications include synthetic biology and biotechnology, in developing pharmaceutical interventions, and in developing lab-on-chip models.

  14. 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.

  15. 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.

  16. 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.

  17. 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

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

    PubMed

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

    2016-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Ho, Christian

    2005-01-01

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

  20. 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

  1. Modeling of signal propagation and sensor performance for infrasound and blast noise

    NASA Astrophysics Data System (ADS)

    Glaser, Danney R.; Wilson, D. Keith; Waldrop, Lauren E.; Hart, Carl R.; White, Michael J.; Nykaza, Edward T.; Swearingen, Michelle E.

    2017-05-01

    This paper describes a comprehensive modeling approach for infrasonic (sub-audible acoustic) signals, which starts with an accurate representation of the source spectrum and directivity, propagates the signals through the environment, and senses and processes the signals at the receiver. The calculations are implemented within EASEE (Environmental Awareness for Sensor and Emitter Employment), which is a general software framework for modeling the impacts of terrain and weather on target signatures and the performance of a diverse range of battlefield sensing systems, including acoustic, seismic, RF, visible, and infrared. At each stage in the modeling process, the signals are described by realistic statistical distributions. Sensor performance is quantified using statistical metrics such as probability of detection and target location error. To extend EASEE for infrasonic calculations, new feature sets were created including standard octaves and one-third octaves. A library of gunfire and blast noise spectra and directivity functions was added from ERDC's BNOISE (Blast Noise) and SARNAM (Small Arms Range Noise Assessment Model) software. Infrasonic propagation modeling is supported by extension of several existing propagation algorithms, including a basic ground impedance model, and the Green's function parabolic equation (GFPE), which provides accurate numerical solutions for wave propagation in a refractive atmosphere. The BNOISE propagation algorithm, which is based on tables generated by a fast-field program (FFP), was also added. Finally, an extensive library of transfer functions for microphones operating in the infrasonic range were added, which interface to EASEE's sensor performance algorithms. Example calculations illustrate terrain and atmospheric impacts on infrasonic signal propagation and the directivity characteristics of blast noise.

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

    ERIC Educational Resources Information Center

    Hollich, George; Prince, Christopher G.

    2009-01-01

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

  3. 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

  4. 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.

  5. A New Signal Model for Axion Cavity Searches from N-body Simulations

    NASA Astrophysics Data System (ADS)

    Lentz, Erik W.; Quinn, Thomas R.; Rosenberg, Leslie J.; Tremmel, Michael J.

    2017-08-01

    Signal estimates for direct axion dark matter (DM) searches have used the isothermal sphere halo model for the last several decades. While insightful, the isothermal model does not capture effects from a halo’s infall history nor the influence of baryonic matter, which has been shown to significantly influence a halo’s inner structure. The high resolution of cavity axion detectors can make use of modern cosmological structure-formation simulations, which begin from realistic initial conditions, incorporate a wide range of baryonic physics, and are capable of resolving detailed structure. This work uses a state-of-the-art cosmological N-body+Smoothed-Particle Hydrodynamics simulation to develop an improved signal model for axion cavity searches. Signal shapes from a class of galaxies encompassing the Milky Way are found to depart significantly from the isothermal sphere. A new signal model for axion detectors is proposed and projected sensitivity bounds on the Axion DM eXperiment (ADMX) data are presented.

  6. 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.

  7. 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

  8. Laguerre-model blind system identification: cardiovascular dynamics estimated from multiple peripheral circulatory signals.

    PubMed

    McCombie, Devin B; Reisner, Andrew T; Asada, Haruhiko Harry

    2005-11-01

    This paper presents a method for comparing multiple circulatory waveforms measured at different locations to improve cardiovascular parameter estimation from these signals. The method identifies the distinct vascular dynamics that shape each waveform signal, and estimates the common cardiac flow input shared by them. This signal-processing algorithm uses the Laguerre function series expansion for modeling the hemodynamics of each arterial branch, and identifies unknown parameters in these models from peripheral waveforms using multichannel blind system identification. An effective technique for determining the Laguerre base pole is developed, so that the Laguerre expansion captures and quickly converges to the intrinsic arterial dynamics observed in the two circulatory signals. Furthermore, a novel deconvolution method is developed in order to stably invert the identified dynamic models for estimating the cardiac output (CO) waveform from peripheral pressure waveforms. The method is applied to experimental swine data. A mean error of less than 5% with the measured peripheral pressure waveforms has been achieved using the models and excellent agreement between the estimated CO waveforms and the gold standard measurements have been obtained.

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

    EPA Science Inventory

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

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

    PubMed Central

    Blackwell, KT

    2013-01-01

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

  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. 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.

  13. 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. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2015-08-01

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

  15. 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.

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

    PubMed Central

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

    2016-01-01

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

  17. 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

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

    PubMed

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

    2015-01-01

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

  19. 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

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2005-04-01

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

  2. 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.

  3. 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

  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. Do early MRI signals predict lesion size in a neonatal stroke rat model?

    PubMed

    Fau, S; Po, C; Goyenvalle, C; Meric, P; Charriaut-Marlangue, C

    2013-07-01

    In this study, we compared lesion size by using VADC and VT2 at 0, 2, 5, 24, and 48 hours and histologic lesions at 48 hours in a P7 rat stroke model. The best correlation between VHISTO and VADC was at H0, and between VHISTO and VT2, at H2-H5. Early MR imaging signals allowed excluding "no-lesion" and "no-reflow" animals to help standardize this neonatal stroke model and predict lesion size.

  6. 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…

  7. Aberrant neuronal activity-induced signaling and gene expression in a mouse model of RASopathy

    PubMed Central

    Nakhaei-Rad, Saeideh; Montenegro-Venegas, Carolina; Pina-Fernández, Eneko; Marini, Claudia; Santos, Monica; Ahmadian, Mohammad R.; Stork, Oliver; Zenker, Martin

    2017-01-01

    Noonan syndrome (NS) is characterized by reduced growth, craniofacial abnormalities, congenital heart defects, and variable cognitive deficits. NS belongs to the RASopathies, genetic conditions linked to mutations in components and regulators of the Ras signaling pathway. Approximately 50% of NS cases are caused by mutations in PTPN11. However, the molecular mechanisms underlying cognitive impairments in NS patients are still poorly understood. Here, we report the generation and characterization of a new conditional mouse strain that expresses the overactive Ptpn11D61Y allele only in the forebrain. Unlike mice with a global expression of this mutation, this strain is viable and without severe systemic phenotype, but shows lower exploratory activity and reduced memory specificity, which is in line with a causal role of disturbed neuronal Ptpn11 signaling in the development of NS-linked cognitive deficits. To explore the underlying mechanisms we investigated the neuronal activity-regulated Ras signaling in brains and neuronal cultures derived from this model. We observed an altered surface expression and trafficking of synaptic glutamate receptors, which are crucial for hippocampal neuronal plasticity. Furthermore, we show that the neuronal activity-induced ERK signaling, as well as the consecutive regulation of gene expression are strongly perturbed. Microarray-based hippocampal gene expression profiling revealed profound differences in the basal state and upon stimulation of neuronal activity. The neuronal activity-dependent gene regulation was strongly attenuated in Ptpn11D61Y neurons. In silico analysis of functional networks revealed changes in the cellular signaling beyond the dysregulation of Ras/MAPK signaling that is nearly exclusively discussed in the context of NS at present. Importantly, changes in PI3K/AKT/mTOR and JAK/STAT signaling were experimentally confirmed. In summary, this study uncovers aberrant neuronal activity-induced signaling and regulation

  8. Population PK/PD analysis of metformin using the signal transduction model.

    PubMed

    Chae, Jung-woo; Baek, In-hwan; Lee, Byung-yo; Cho, Seong-kwon; Kwon, Kwang-il

    2012-11-01

    Metformin, a biguanide glucose lowering agent, is commonly used to manage type 2 diabetes. The molecular mechanisms of metformin have not been fully identified, but turnover of biomarkers such as glucose and signalling pathways or translocation of glucose transporters are closely related to the glucose-lowering effects of metformin. The PK/PD of metformin have been investigated in healthy humans and patients with type 2 diabetes mellitus and modelling has been performed using an indirect response model. The purpose of this investigation was to develop a population PK/PD model for metformin using a signal transduction model in healthy humans and predict the PK/PD profile in patients with type 2 diabetes. The aim was to compare a previous model (a biophase model) with the signal transduction model, and use a more appropriate model to follow the actions of metformin. Additionally, our developed model was appropriate to predict the time course of plasma metformin and fasting plasma glucose (FPG) concentrations in patients with type 2 diabetes. To our knowledge, this is the first published population PK/PD analysis using the signal transduction model for metformin. AIMS To develop a population pharmacokinetic (PK) and pharmacodynamic (PD) model for metformin (500 mg) using the signal transduction model in healthy humans and to predict the PK/PD profile in patients with type 2 diabetes. Following the oral administration of 500 mg metformin to healthy humans, plasma concentrations of metformin were measured using LC-MS/MS. A sequential modelling approach using NONMEM VI was used to facilitate data analysis. Monte Carlo simulation was performed to predict the antihyperglycaemic effect in patients with type 2 diabetes. Forty-two healthy humans were included in the study. Population mean estimates (relative standard error, RSE) of apparent clearance, apparent volume of distribution and the absorption rate constant were 52.6 l h(-1) (4.18%), 113 l (56.6%) and 0.41

  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. Modelling reveals novel roles of two parallel signalling pathways and homeostatic feedbacks in yeast

    PubMed Central

    Schaber, Jörg; Baltanas, Rodrigo; Bush, Alan; Klipp, Edda; Colman-Lerner, Alejandro

    2012-01-01

    The high osmolarity glycerol (HOG) pathway in yeast serves as a prototype signalling system for eukaryotes. We used an unprecedented amount of data to parameterise 192 models capturing different hypotheses about molecular mechanisms underlying osmo-adaptation and selected a best approximating model. This model implied novel mechanisms regulating osmo-adaptation in yeast. The model suggested that (i) the main mechanism for osmo-adaptation is a fast and transient non-transcriptional Hog1-mediated activation of glycerol production, (ii) the transcriptional response serves to maintain an increased steady-state glycerol production with low steady-state Hog1 activity, and (iii) fast negative feedbacks of activated Hog1 on upstream signalling branches serves to stabilise adaptation response. The best approximating model also indicated that homoeostatic adaptive systems with two parallel redundant signalling branches show a more robust and faster response than single-branch systems. We corroborated this notion to a large extent by dedicated measurements of volume recovery in single cells. Our study also demonstrates that systematically testing a model ensemble against data has the potential to achieve a better and unbiased understanding of molecular mechanisms. PMID:23149687

  11. Modelling reveals novel roles of two parallel signalling pathways and homeostatic feedbacks in yeast.

    PubMed

    Schaber, Jörg; Baltanas, Rodrigo; Bush, Alan; Klipp, Edda; Colman-Lerner, Alejandro

    2012-01-01

    The high osmolarity glycerol (HOG) pathway in yeast serves as a prototype signalling system for eukaryotes. We used an unprecedented amount of data to parameterise 192 models capturing different hypotheses about molecular mechanisms underlying osmo-adaptation and selected a best approximating model. This model implied novel mechanisms regulating osmo-adaptation in yeast. The model suggested that (i) the main mechanism for osmo-adaptation is a fast and transient non-transcriptional Hog1-mediated activation of glycerol production, (ii) the transcriptional response serves to maintain an increased steady-state glycerol production with low steady-state Hog1 activity, and (iii) fast negative feedbacks of activated Hog1 on upstream signalling branches serves to stabilise adaptation response. The best approximating model also indicated that homoeostatic adaptive systems with two parallel redundant signalling branches show a more robust and faster response than single-branch systems. We corroborated this notion to a large extent by dedicated measurements of volume recovery in single cells. Our study also demonstrates that systematically testing a model ensemble against data has the potential to achieve a better and unbiased understanding of molecular mechanisms.

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

    PubMed Central

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

    2013-01-01

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

  13. 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

  14. Suppressing thyroid hormone signaling preserves cone photoreceptors in mouse models of retinal degeneration.

    PubMed

    Ma, Hongwei; Thapa, Arjun; Morris, Lynsie; Redmond, T Michael; Baehr, Wolfgang; Ding, Xi-Qin

    2014-03-04

    Cone phototransduction and survival of cones in the human macula is essential for color vision and for visual acuity. Progressive cone degeneration in age-related macular degeneration, Stargardt disease, and recessive cone dystrophies is a major cause of blindness. Thyroid hormone (TH) signaling, which regulates cell proliferation, differentiation, and apoptosis, plays a central role in cone opsin expression and patterning in the retina. Here, we investigated whether TH signaling affects cone viability in inherited retinal degeneration mouse models. Retinol isomerase RPE65-deficient mice [a model of Leber congenital amaurosis (LCA) with rapid cone loss] and cone photoreceptor function loss type 1 mice (severe recessive achromatopsia) were used to determine whether suppressing TH signaling with antithyroid treatment reduces cone death. Further, cone cyclic nucleotide-gated channel B subunit-deficient mice (moderate achromatopsia) and guanylate cyclase 2e-deficient mice (LCA with slower cone loss) were used to determine whether triiodothyronine (T3) treatment (stimulating TH signaling) causes deterioration of cones. We found that cone density in retinol isomerase RPE65-deficient and cone photoreceptor function loss type 1 mice increased about sixfold following antithyroid treatment. Cone density in cone cyclic nucleotide-gated channel B subunit-deficient and guanylate cyclase 2e-deficient mice decreased about 40% following T3 treatment. The effect of TH signaling on cone viability appears to be independent of its regulation on cone opsin expression. This work demonstrates that suppressing TH signaling in retina dystrophy mouse models is protective of cones, providing insights into cone preservation and therapeutic interventions.

  15. Suppressing thyroid hormone signaling preserves cone photoreceptors in mouse models of retinal degeneration

    PubMed Central

    Ma, Hongwei; Thapa, Arjun; Morris, Lynsie; Redmond, T. Michael; Baehr, Wolfgang; Ding, Xi-Qin

    2014-01-01

    Cone phototransduction and survival of cones in the human macula is essential for color vision and for visual acuity. Progressive cone degeneration in age-related macular degeneration, Stargardt disease, and recessive cone dystrophies is a major cause of blindness. Thyroid hormone (TH) signaling, which regulates cell proliferation, differentiation, and apoptosis, plays a central role in cone opsin expression and patterning in the retina. Here, we investigated whether TH signaling affects cone viability in inherited retinal degeneration mouse models. Retinol isomerase RPE65-deficient mice [a model of Leber congenital amaurosis (LCA) with rapid cone loss] and cone photoreceptor function loss type 1 mice (severe recessive achromatopsia) were used to determine whether suppressing TH signaling with antithyroid treatment reduces cone death. Further, cone cyclic nucleotide-gated channel B subunit-deficient mice (moderate achromatopsia) and guanylate cyclase 2e-deficient mice (LCA with slower cone loss) were used to determine whether triiodothyronine (T3) treatment (stimulating TH signaling) causes deterioration of cones. We found that cone density in retinol isomerase RPE65-deficient and cone photoreceptor function loss type 1 mice increased about sixfold following antithyroid treatment. Cone density in cone cyclic nucleotide-gated channel B subunit-deficient and guanylate cyclase 2e-deficient mice decreased about 40% following T3 treatment. The effect of TH signaling on cone viability appears to be independent of its regulation on cone opsin expression. This work demonstrates that suppressing TH signaling in retina dystrophy mouse models is protective of cones, providing insights into cone preservation and therapeutic interventions. PMID:24550448

  16. 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

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

    PubMed

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

    2013-01-01

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

  18. Computational Modeling of Spatiotemporal Ca(2+) Signal Propagation Along Hepatocyte Cords.

    PubMed

    Verma, Aalap; Makadia, Hirenkumar; Hoek, Jan B; Ogunnaike, Babatunde A; Vadigepalli, Rajanikanth

    2016-10-01

    The purpose of this study is to model the dynamics of lobular Ca(2+) wave propagation induced by an extracellular stimulus, and to analyze the effect of spatially systematic variations in cell-intrinsic signaling parameters on sinusoidal Ca(2+) response. We developed a computational model of lobular scale Ca(2+) signaling that accounts for receptor- mediated initiation of cell-intrinsic Ca(2+) signal in hepatocytes and its propagation to neighboring hepatocytes through gap junction-mediated molecular exchange. Analysis of the simulations showed that a pericentral-to-periportal spatial gradient in hormone sensitivity and/or rates of IP3 synthesis underlies the Ca(2+) wave propagation. We simulated specific cases corresponding to localized disruptions in the graded pattern of these parameters along a hepatic sinusoid. Simulations incorporating locally altered parameters exhibited Ca(2+) waves that do not propagate throughout the hepatic plate. Increased gap junction coupling restored normal Ca(2+) wave propagation when hepatocytes with low Ca(2+) signaling ability were localized in the midlobular or the pericentral region. Multiple spatial patterns in intracellular signaling parameters can lead to Ca(2+) wave propagation that is consistent with the experimentally observed spatial patterns of Ca(2+) dynamics. Based on simulations and analysis, we predict that increased gap junction-mediated intercellular coupling can induce robust Ca(2+) signals in otherwise poorly responsive hepatocytes, at least partly restoring the sinusoidally oriented Ca (2+) waves. Our bottom-up model of agonist-evoked spatial Ca(2+) patterns can be integrated with detailed descriptions of liver histology to study Ca(2+) regulation at the tissue level.

  19. 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

  20. Multiscale Model of Dynamic Neuromodulation Integrating Neuropeptide-Induced Signaling Pathway Activity with Membrane Electrophysiology

    PubMed Central

    Makadia, Hirenkumar K.; Anderson, Warren D.; Fey, Dirk; Sauter, Thomas; Schwaber, James S.; Vadigepalli, Rajanikanth

    2015-01-01

    We developed a multiscale model to bridge neuropeptide receptor-activated signaling pathway activity with membrane electrophysiology. Typically, the neuromodulation of biochemical signaling and biophysics have been investigated separately in modeling studies. We studied the effects of Angiotensin II (AngII) on neuronal excitability changes mediated by signaling dynamics and downstream phosphorylation of ion channels. Experiments have shown that AngII binding to the AngII receptor type-1 elicits baseline-dependent regulation of cytosolic Ca2+ signaling. Our model simulations revealed a baseline Ca2+-dependent response to AngII receptor type-1 activation by AngII. Consistent with experimental observations, AngII evoked a rise in Ca2+ when starting at a low baseline Ca2+ level, and a decrease in Ca2+ when starting at a higher baseline. Our analysis predicted that the kinetics of Ca2+ transport into the endoplasmic reticulum play a critical role in shaping the Ca2+ response. The Ca2+ baseline also influenced the AngII-induced excitability changes such that lower Ca2+ levels were associated with a larger firing rate increase. We examined the relative contributions of signaling kinases protein kinase C and Ca2+/Calmodulin-dependent protein kinase II to AngII-mediated excitability changes by simulating activity blockade individually and in combination. We found that protein kinase C selectively controlled firing rate adaptation whereas Ca2+/Calmodulin-dependent protein kinase II induced a delayed effect on the firing rate increase. We tested whether signaling kinetics were necessary for the dynamic effects of AngII on excitability by simulating three scenarios of AngII-mediated KDR channel phosphorylation: (1), an increased steady state; (2), a step-change increase; and (3), dynamic modulation. Our results revealed that the kinetics emerging from neuromodulatory activation of the signaling network were required to account for the dynamical changes in excitability. In

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

    SciTech Connect

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

    1993-03-01

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

  2. Signal-3L 2.0: A Hierarchical Mixture Model for Enhancing Protein Signal Peptide Prediction by Incorporating Residue-Domain Cross-Level Features.

    PubMed

    Zhang, Yi-Ze; Shen, Hong-Bin

    2017-04-24

    Signal peptides play key roles in targeting and translocation of integral membrane proteins and secretory proteins. However, signal peptides present several challenges for automatic prediction methods. One challenge is that it is difficult to discriminate signal peptides from transmembrane helices, as both the H-region of the peptides and the transmembrane helices are hydrophobic. Another is that it is difficult to identify the cleavage site between signal peptides and mature proteins, as cleavage motifs or patterns are still unclear for most proteins. To solve these problems and further enhance automatic signal peptide recognition, we report a new Signal-3L 2.0 predictor. Our new model is constructed with a hierarchical protocol, where it first determines the existence of a signal peptide. For this, we propose a new residue-domain cross-level feature-driven approach, and we demonstrate that protein functional domain information is particularly useful for discriminating between the transmembrane helices and signal peptides as they perform different functions. Next, in order to accurately identify the unique signal peptide cleavage sites along the sequence, we designed a top-down approach where a subset of potential cleavage sites are screened using statistical learning rules, and then a final unique site is selected according to its evolution conservation score. Because this mixed approach utilizes both statistical learning and evolution analysis, it shows a strong capacity for recognizing cleavage sites. Signal-3L 2.0 has been benchmarked on multiple data sets, and the experimental results have demonstrated its accuracy. The online server is available at www.csbio.sjtu.edu.cn/bioinf/Signal-3L/ .

  3. 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.

  4. 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

  5. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Examination of ERα signaling pathways in bone of mutant mouse models reveals the importance of ERE-dependent signaling.

    PubMed

    Chokalingam, Kumar; Roforth, Matthew M; Nicks, Kristy M; McGregor, Ulrike; Fraser, Daniel; Khosla, Sundeep; Monroe, David G

    2012-11-01

    The mechanisms of estrogen receptor (ER)-α activity can be categorized into those involving direct (classical) or indirect (nonclassical) DNA binding. Although various mouse models have demonstrated the importance of ERα in bone, the specific gene expression patterns affected by these modes of ERα action are unknown. In this report, the gene expression patterns of ERα-deficient (ERKO) mice and nonclassical ER knock-in (NERKI) mice, which can function only by nonclassical means, were analyzed. Three-month-old mice were ovariectomized and implanted with estrogen pellets for 1 month to normalize estrogen levels. Microarray analysis of flushed cortical bone revealed 28% (210 of 763) of the genes differentially expressed in ERKO mice were altered in NERKI mice, suggesting estrogen response element-dependent regulation of these genes in bone. Pathway analysis revealed alterations in genes involved in focal adhesion and extracellular matrix interactions. However, the majority of genes regulated in ERKO mice (72%) were unique (i.e. not altered in NERKI mice), suggesting these are regulated by nonclassical mechanisms. To further explore the pathways affected in ERKO mice, we performed focused quantitative PCR arrays for genes involved in various aspects of bone physiology. Genes involved in bone formation, senescence, apoptosis, and autophagy were significantly regulated. Overall, the majority of the genes regulated by ERα in bone are via nonclassical pathways. However, because NERKI mice display an osteoporotic phenotype, it can be deduced that the minority of the estrogen response element-dependent genes/pathways play critical roles in the regulation of bone physiology. These data demonstrate the importance of classical ERα signaling in regulating bone metabolism.

  2. SMAD signaling drives heart and muscle dysfunction in a Drosophila model of muscular dystrophy

    PubMed Central

    Goldstein, Jeffery A.; Kelly, Sean M.; LoPresti, Peter P.; Heydemann, Ahlke; Earley, Judy U.; Ferguson, Edwin L.; Wolf, Matthew J.; McNally, Elizabeth M.

    2011-01-01

    Loss-of-function mutations in the genes encoding dystrophin and the associated membrane proteins, the sarcoglycans, produce muscular dystrophy and cardiomyopathy. The dystrophin complex provides stability to the plasma membrane of striated muscle during muscle contraction. Increased SMAD signaling due to activation of the transforming growth factor-β (TGFβ) pathway has been described in muscular dystrophy; however, it is not known whether this canonical TGFβ signaling is pathogenic in the muscle itself. Drosophila deleted for the γ/δ-sarcoglycan gene (Sgcd) develop progressive muscle and heart dysfunction and serve as a model for the human disorder. We used dad-lacZ flies to demonstrate the signature of TGFβ activation in response to exercise-induced injury in Sgcd null flies, finding that those muscle nuclei immediately adjacent to muscle injury demonstrate high-level TGFβ signaling. To determine the pathogenic nature of this signaling, we found that partial reduction of the co-SMAD Medea, homologous to SMAD4, or the r-SMAD, Smox, corrected both heart and muscle dysfunction in Sgcd mutants. Reduction in the r-SMAD, MAD, restored muscle function but interestingly not heart function in Sgcd mutants, consistent with a role for activin but not bone morphogenic protein signaling in cardiac dysfunction. Mammalian sarcoglycan null muscle was also found to exhibit exercise-induced SMAD signaling. These data demonstrate that hyperactivation of SMAD signaling occurs in response to repetitive injury in muscle and heart. Reduction of this pathway is sufficient to restore cardiac and muscle function and is therefore a target for therapeutic reduction. PMID:21138941

  3. 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.

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

    NASA Astrophysics Data System (ADS)

    Khrennikov, Andrei; Nilsson, Börje; Nordebo, Sven

    2012-05-01

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

  5. 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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed

    Gray, Catheryn W; Coster, Adelle C F

    2015-12-01

    Insulin is a potent peptide hormone that regulates glucose levels in the blood. Insulin-sensitive cells respond to insulin stimulation with the translocation of glucose transporter 4 (GLUT4) to the plasma membrane (PM), enabling the clearance of glucose from the blood. Defects in this process can give rise to insulin resistance and ultimately diabetes. One widely cited model of insulin signalling leading to glucose transport is that of Sedaghat et al. (2002) Am. J. Physiol. Endocrinol. Metab. 283, E1084-E1101. Consisting of 20 deterministic ordinary differential equations (ODEs), it is the most comprehensive model of insulin signalling to date. However, the model possesses some major limitations, including the non-conservation of key components. In the current work, we detail mathematical and sensitivity analyses of the Sedaghat model. Based on the results of these analyses, we propose a reduced state space model of the insulin receptor subsystem. This reduced model maintains the input-output relation of the original model but is computationally more efficient, analytically tractable and resolves some of the limitations of the Sedaghat model. © The Authors 2015. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

  9. Signal integrity analysis on materials and via structures modeling and characterization

    NASA Astrophysics Data System (ADS)

    Li, Qian

    The development of modern digital communication systems has been entered a new era with faster signal transmission and processing capability, called high-speed circuit systems. As their clock frequencies have increased and rise times of signals have decreased, the signal integrity of interconnects in the packaging and printed circuit boards plays a more and more important role. In high-speed circuit systems, the well-designed logic functions most likely will not work well if their interconnects are not taken into account. This dissertation addresses to profoundly understand the signal integrity knowledge, be proficient in calculation, simulation and measurements, and be capable of solving related signal integrity problems. The research mainly emphasizes on three aspects. First of all, the impact of on-wafer calibration methods on the measured results of coplanar waveguide circuits is comprehensively investigated, with their measurement repeatability and accuracy. Furthermore, a method is presented to characterize the physically-consistent broadband material properties for both rigid and flexible dielectric materials. Last but not least, a hybrid method for efficient modeling of three dimensional via structures is developed, in order to simplify the traditional 3D full-length via simulations and dramatically reduce the via build and simulation time and complexity.

  10. 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.

  11. Modeled microgravity disrupts collagen I/integrin signaling during osteoblastic differentiation of human mesenchymal stem cells.

    PubMed

    Meyers, Valerie E; Zayzafoon, Maid; Gonda, Steve R; Gathings, William E; McDonald, Jay M

    2004-11-01

    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 7 days culture in modeled microgravity (MMG). One potential mechanism for reduced osteoblastic differentiation is disruption of type I collagen (Col I)-integrin interactions and reduced integrin signaling. Integrins are heterodimeric transmembrane receptors that bind extracellular matrix (ECM) proteins and produce signals essential for proper cellular function, survival, and differentiation. Therefore, we investigated the effects of MMG on integrin expression and function in hMSC. We demonstrate that 7 days of culture in MMG leads to reduced expression of the ECM protein, Col I. Conversely, MMG consistently increases Col I-specific alpha2 and beta1 integrin protein expression. Despite this increase in integrin subunit expression, autophosphorylation of adhesion-dependent kinases, focal adhesion kinase (FAK) and proline-rich tyrosine kinase 2 (PYK2), is significantly reduced. Activation of Akt protein kinase (Akt) is unaffected by the reduction in FAK activation. However, reduced downstream signaling via the Ras-mitogen activated protein kinase (MAPK) pathway is evidenced by a reduction in Ras and extracellular signal-related protein kinase (ERK) activation. Taken together, our findings indicate that MMG decreases integrin/MAPK signaling, which likely contributes to the observed reduction in osteoblastogenesis.

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

    PubMed

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

    2013-09-15

    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. 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. caspo is freely available for download (license GPLv3) and as a web service at http://caspo.genouest.org/. Supplementary materials are available at Bioinformatics online. santiago.videla@irisa.fr.

  16. Comparison of measured and simulated IR signals from a scaled model ship

    NASA Astrophysics Data System (ADS)

    Kim, Dong-Geon; Han, Kuk-Il; Choi, Jun-Hyuk; Kim, Tae-Kuk

    2013-09-01

    The goal of the present study is to develop a S/W that predicts infrared signals from objects synthetically by considering the internal and external factors, such as surface properties, internal heat sources, solar irradiations, atmospheric temperature, etc. As a part of developing a S/W, this paper contains some results of the measured and simulated IR signals for comparison and validation. The scaled model ship used in this study is made of 3mm-thick steel and 1.5m long. It has virtual internal heat sources that are made of a brass block with a heater. The experiments are performed under an indoor environment to exclude the external effects such as solar irradiance, wind effect, etc. The radiance from the ship is mainly due to the surface temperature because the effects of solar and wind are excluded. Also the IR signals are collected by the IR cameras which are operated at MWIR(3.7~5.1μm ) and LWIR(7.5~9.1 μm), respectively. At the same time, the atmospheric temperature and the relative humidity are measured to use for input conditions for calculation. The surface temperature and the IR signals within the two wavelengths are calculated by using the S/W developed in this study considering the 3D ship model, the internal heater temperature, and the atmospheric conditions. The temperature and IR signals from the scaled model ship obtained from measurements and from the S/W developed in this study are compared each other by showing fairly good agreements with each other.

  17. 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

  18. 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

  19. 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

  20. 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

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

    SciTech Connect

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

    1990-03-01

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

  2. Quantification of absolute fat mass using an adipose tissue reference signal model.

    PubMed

    Hu, Houchun H; Nayak, Krishna S

    2008-12-01

    To develop a method for quantifying absolute fat mass, and to demonstrate its feasibility in phantoms and in ex vivo swine specimens at 3 Tesla. Chemical-shift-based fat-water decomposition was used to first reconstruct fat-only images. Our proposed model used a reference signal from fat in pure adipose tissue to calibrate and normalize the fat signal intensities from the fat-only images. Fat mass was subsequently computed on a voxel-by-voxel basis and summed across each sample. Feasibility of the model was tested in six ex vivo swine samples containing varying mixtures of fat (adipose) and lean tissues. The samples were imaged using 1.5-mm isotropic voxels and a single-channel birdcage head coil at 3 Tesla. Lipid assay was independently performed to determine fat mass, and served as the comparison standard. Absolute fat mass values (in grams) derived by our proposed model were in excellent agreement with lipid assay results, with a 5% to 7% difference (r > 0.99; P < 0.001). Preliminary results in ex vivo swine samples demonstrated the feasibility of computing absolute fat mass as a quantitative endpoint using chemical-shift fat-water MRI with a signal model based on reference fat from pure adipose tissue. (c) 2008 Wiley-Liss, Inc.

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

    PubMed

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

    2011-05-01

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

  4. 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. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

  5. 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.

  6. 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.

  7. Population PK/PD analysis of metformin using the signal transduction model

    PubMed Central

    Chae, Jung-woo; Baek, In-hwan; Lee, Byung-yo; Cho, Seong-kwon; Kwon, Kwang-il

    2012-01-01

    AIMS To develop a population pharmacokinetic (PK) and pharmacodynamic (PD) model for metformin (500 mg) using the signal transduction model in healthy humans and to predict the PK/PD profile in patients with type 2 diabetes. METHODS Following the oral administration of 500 mg metformin to healthy humans, plasma concentrations of metformin were measured using LC-MS/MS. A sequential modelling approach using NONMEM VI was used to facilitate data analysis. Monte Carlo simulation was performed to predict the antihyperglycaemic effect in patients with type 2 diabetes. RESULTS Forty-two healthy humans were included in the study. Population mean estimates (relative standard error, RSE) of apparent clearance, apparent volume of distribution and the absorption rate constant were 52.6 l h−1 (4.18%), 113 l (56.6%) and 0.41 h−1, respectively. Covariate analyses revealed that creatinine clearance (CLCR) significantly influenced metformin: CL/F= 52.6 × (CLcr/106.5)0.782. The signal transduction model was applied to describe the antihyperglycaemic effect of metformin. The population means for efficacy, potency, transit time and the Hill coefficient were estimated to be 19.8 (3.17%), 3.68 µg ml−1 (3.89%), 0.5 h (2.89%) and 0.547 (9.05%), respectively. The developed model was used to predict the antihyperglycaemic effect in patients with type 2 diabetes. The predicted plasma glucose concentration value was similar to previous values. CONCLUSIONS The population signal transduction model was developed and evaluated for metformin use in healthy volunteers. Model evaluation by non-parametric bootstrap analysis suggested that the proposed model was robust and parameter values were estimated with good precision. PMID:22380769

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

    NASA Astrophysics Data System (ADS)

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

    2013-11-01

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

  9. 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

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

    PubMed

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

    2015-11-01

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

  11. A speed guidance model accounting for the driver's bounded rationality at a signalized intersection

    NASA Astrophysics Data System (ADS)

    Tang, Tie-Qiao; Zhang, Jian; Liu, Kai

    2017-05-01

    In this paper, we propose a speed guidance model to explore the influences of the drivers' bounded rationality on the vehicle's fuel consumption and emissions during the whole process of the vehicle passing through the signalized intersection. In the proposed speed guidance model, we apply three parameters (i.e., the response time, acceptance threshold value and execution level) to quantify the driver's bounded rationality. In the numerical tests, we use the signalized intersection (consisting of the Xinan Road and the Wuyi Road in Dalian, China) as the simulation scenario, the Vissim to describe the vehicle's movement and the MOVES (motor vehicle emission simulator) to explore the vehicle's fuel consumption and emissions. The numerical results show that the driver's bounded rationality has prominent effects on the vehicle's fuel consumption and emissions, but the impacts are directly dependent on each parameter of the driver's bounded rationality.

  12. 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.

  13. 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

  14. 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

  15. Aging-like skin changes in metabolic syndrome model mice are mediated by mineralocorticoid receptor signaling.

    PubMed

    Nagase, Takashi; Akase, Tomoko; Sanada, Hiromi; Minematsu, Takeo; Ibuki, Ai; Huang, Lijuan; Asada, Mayumi; Yoshimura, Kotaro; Nagase, Miki; Shimada, Tsutomu; Aburada, Masaki; Nakagami, Gojiro; Sugama, Junko

    2013-02-01

    Aging is accelerated, at least in part, by pathological condition such as metabolic syndrome (MetS), and various molecular pathways such as oxidative stress are common mediators of aging and MetS. We previously developed the aging-like skin model by single ultraviolet (UV) irradiation on the MetS model mice. Recent studies revealed that mineralocorticoid receptor (MR) signaling plays a pivotal role for various tissue inflammation and damages in MetS. Although previous studies reported that MR is expressed in the skin and that overexpression of MR in the skin resulted in the skin atrophy, the physiological or pathological functions of MR in the skin are not fully elucidated. Here, we show the involvement of MR signaling in the aging-like skin changes in our own model. Elevations of oxidative stress and inflammation markers were observed in the MetS mice, and the UV-evoked aging-like skin damages were attenuated by topical antioxidant. MR expression was higher in the MetS mouse skin, and notably, expression of its effecter gene Sgk1 was significantly upregulated in the aging-like skin in the UV-irradiated MetS mice. Furthermore, topical application of MR antagonist spironolactone suppressed Sgk1 expression, oxidative stress, inflammation, and the aging-like changes in the skin. The 2-week UV onto the non-MetS mice, the more usual photoaging model, resulted in the skin damages mostly equivalent to the MetS mice with single UV, but they were not associated with upregulation of MR signaling. Our studies suggested an unexpected role of MR signaling in the skin aging in MetS status.

  16. 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

  17. An artificial neural network model of energy expenditure using nonintegrated acceleration signals.

    PubMed

    Rothney, Megan P; Neumann, Megan; Béziat, Ashley; Chen, Kong Y

    2007-10-01

    Accelerometers are a promising tool for characterizing physical activity patterns in free living. The major limitation in their widespread use to date has been a lack of precision in estimating energy expenditure (EE), which may be attributed to the oversimplified time-integrated acceleration signals and subsequent use of linear regression models for EE estimation. In this study, we collected biaxial raw (32 Hz) acceleration signals at the hip to develop a relationship between acceleration and minute-to-minute EE in 102 healthy adults using EE data collected for nearly 24 h in a room calorimeter as the reference standard. From each 1 min of acceleration data, we extracted 10 signal characteristics (features) that we felt had the potential to characterize EE intensity. Using these data, we developed a feed-forward/back-propagation artificial neural network (ANN) model with one hidden layer (12 x 20 x 1 nodes). Results of the ANN were compared with estimations using the ActiGraph monitor, a uniaxial accelerometer, and the IDEEA monitor, an array of five accelerometers. After training and validation (leave-one-subject out) were completed, the ANN showed significantly reduced mean absolute errors (0.29 +/- 0.10 kcal/min), mean squared errors (0.23 +/- 0.14 kcal(2)/min(2)), and difference in total EE (21 +/- 115 kcal/day), compared with both the IDEEA (P < 0.01) and a regression model for the ActiGraph accelerometer (P < 0.001). Thus ANN combined with raw acceleration signals is a promising approach to link body accelerations to EE. Further validation is needed to understand the performance of the model for different physical activity types under free-living conditions.

  18. 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.

  19. 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.

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

    DTIC Science & Technology

    1984-04-30

    use EMG electrodes with the signal processing circuitry resident in a common package. The electrodes were supplied by Motion Control Incorporated of...Instrumentation 2-1 2.2.1 Development System Selection 2-1 2.2.2 Analog-to-Digital Board Selection and Hardware Interface 2-4 2.2.3 Electrode Selection and...34 the models and possibly "filtering out" pattern variations due to variables * in electrode locations and individual biases. (5) To develop

  1. 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.

  2. 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

  3. 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.

  4. Transmembrane helix dynamics of bacterial chemoreceptors supports a piston model of signalling.

    PubMed

    Hall, Benjamin A; Armitage, Judith P; Sansom, Mark S P

    2011-10-01

    Transmembrane α-helices play a key role in many receptors, transmitting a signal from one side to the other of the lipid bilayer membrane. Bacterial chemoreceptors are one of the best studied such systems, with a wealth of biophysical and mutational data indicating a key role for the TM2 helix in signalling. In particular, aromatic (Trp and Tyr) and basic (Arg) residues help to lock α-helices into a membrane. Mutants in TM2 of E. coli Tar and related chemoreceptors involving these residues implicate changes in helix location and/or orientation in signalling. We have investigated the detailed structural basis of this via high throughput coarse-grained molecular dynamics (CG-MD) of Tar TM2 and its mutants in lipid bilayers. We focus on the position (shift) and orientation (tilt, rotation) of TM2 relative to the bilayer and how these are perturbed in mutants relative to the wildtype. The simulations reveal a clear correlation between small (ca. 1.5 Å) shift in position of TM2 along the bilayer normal and downstream changes in signalling activity. Weaker correlations are seen with helix tilt, and little/none between signalling and helix twist. This analysis of relatively subtle changes was only possible because the high throughput simulation method allowed us to run large (n = 100) ensembles for substantial numbers of different helix sequences, amounting to ca. 2000 simulations in total. Overall, this analysis supports a swinging-piston model of transmembrane signalling by Tar and related chemoreceptors.

  5. 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.

  6. A Heckman selection model for the safety analysis of signalized intersections

    PubMed Central

    Wong, S. C.; Zhu, Feng; Pei, Xin; Huang, Helai; Liu, Youjun

    2017-01-01

    Purpose The objective of this paper is to provide a new method for estimating crash rate and severity simultaneously. Methods This study explores a Heckman selection model of the crash rate and severity simultaneously at different levels and a two-step procedure is used to investigate the crash rate and severity levels. The first step uses a probit regression model to determine the sample selection process, and the second step develops a multiple regression model to simultaneously evaluate the crash rate and severity for slight injury/kill or serious injury (KSI), respectively. The model uses 555 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during two years. Results The results of the proposed two-step Heckman selection model illustrate the necessity of different crash rates for different crash severity levels. Conclusions A comparison with the existing approaches suggests that the Heckman selection model offers an efficient and convenient alternative method for evaluating the safety performance at signalized intersections. PMID:28732050

  7. 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).

  8. 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.

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

    NASA Astrophysics Data System (ADS)

    Racic, V.; Pavic, A.

    2010-01-01

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

  10. 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.

  11. 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.

  12. 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.