WorldWideScience

Sample records for modeling radioxenon signals

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

    International Nuclear Information System (INIS)

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

    2010-01-01

    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.

  2. Categorization of Radioxenon

    Energy Technology Data Exchange (ETDEWEB)

    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.

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

    International Nuclear Information System (INIS)

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

    2005-01-01

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

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

    Science.gov (United States)

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

    2005-01-01

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

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

    International Nuclear Information System (INIS)

    Deshmukh, Nikhil; Prinke, Amanda; Miller, Brian; McIntyre, Justin

    2017-01-01

    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 newer algorithms can be better than the ones currently used.

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

    International Nuclear Information System (INIS)

    Deshmukh, Nikhil; Prinke, Amanda; Miller, Brian; McIntyre, Justin

    2017-01-01

    The aim of this paper 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. Our results show that existing algorithms can be improved and some newer algorithms can be better than the ones currently used. (author)

  7. Regional transport of radioxenon released from the Chalk River Laboratories medical isotope facility

    International Nuclear Information System (INIS)

    Christine Johnson; Steven Biegalski

    2015-01-01

    An examination of proposed sampling sites near Chalk River Laboratories in Ontario, Canada is performed by considering the regional transport of radioxenon using atmospheric dispersion modeling. The local geography is considered, as are the local meteorological conditions during the summer months. In particular the impacts of predicted conditions on the imprinting of atmospheric radioxenon into the subsurface are considered and weighed against site proximity, geography, and geology. (author)

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

    International Nuclear Information System (INIS)

    Foxe, Michael P.; McIntyre, Justin I.

    2015-01-01

    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 cm 3 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: 131m Xe - 0.12 mBq/m 3 (0.12 mBq/m 3 ); 133 Xe - 0.18 mBq/m 3 (0.21 mBq/m 3 ); 133m Xe - 0.07 mBq/m 3 (0.15 mBq/m 3 ); 135 Xe - 0.45 mBq/m 3 (0.67 mBq/m 3 ). 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 131m Xe and 133m Xe, but similar for 133 Xe and 135 Xe. 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 reduced by a factor of 10 in the Si PIN detector compared to the current plastic scintillator cells. There is potential for further reduction with the

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

    Energy Technology Data Exchange (ETDEWEB)

    Stocki, Trevor J., E-mail: trevor_stocki@hc-sc.gc.c [Radiation Protection Bureau, 775 Brookfield Road, A.L. 6302D1, Ottawa, ON, K1A 1C1 (Canada); Li, Guichong; Japkowicz, Nathalie [School of Information Technology and Engineering, University of Ottawa, 800 King Edward Avenue, Ottawa, ON, K1N 6N5 (Canada); Ungar, R. Kurt [Radiation Protection Bureau, 775 Brookfield Road, A.L. 6302D1, Ottawa, ON, K1A 1C1 (Canada)

    2010-01-15

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

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  11. Production of beta-gamma coincidence spectra of individual radioxenon isotopes for improved analysis of nuclear explosion monitoring data

    Science.gov (United States)

    Haas, Derek Anderson

    Radioactive xenon gas is a fission product released in the detonation of nuclear devices that can be detected in atmospheric samples far from the detonation site. In order to improve the capabilities of radioxenon detection systems, this work produces beta-gamma coincidence spectra of individual isotopes of radioxenon. Previous methods of radioxenon production consisted of the removal of mixed isotope samples of radioxenon gas released from fission of contained fissile materials such as 235U. In order to produce individual samples of the gas, isotopically enriched stable xenon gas is irradiated with neutrons. The detection of the individual isotopes is also modeled using Monte Carlo simulations to produce spectra. The experiment shows that samples of 131mXe, 133 Xe, and 135Xe with a purity greater than 99% can be produced, and that a sample of 133mXe can be produced with a relatively low amount of 133Xe background. These spectra are compared to models and used as essential library data for the Spectral Deconvolution Analysis Tool (SDAT) to analyze atmospheric samples of radioxenon for evidence of nuclear events.

  12. Measurements of ambient radioxenon levels using the automated radioxenon sampler/analyzer (ARSA)

    International Nuclear Information System (INIS)

    McIntyre, J.I.; Abel, K.H.; Bowyer, T.W.; Hayes, J.C.; Heimbigner, T.R.; Panisko, M.E.; Reeder, P.L.; Thompson, R.C.

    2001-01-01

    The Pacific Northwest National Laboratory has developed an Automated Radioxenon Sampler/Analyzer (ARSA) in support of the Comprehensive Nuclear-Test-Ban-Treaty (CTBT) to measure four radioxenon isotopes: 131m Xe, 133m Xe, 133g Xe, and 135g Xe. This system uses a beta-gamma coincidence counting detector to produce two-dimensional plots of gamma-energy versus beta-energy. Betas and conversion electrons (CE) are detected in a cylindrical plastic scintillation cell and gamma and X-rays are detected in a surrounding NaI(Tl) scintillation detector. The ARSA has been field tested at several locations to measure the radioxenon concentrations. Most recently it has been deployed at the Institut fuer Atmosphaerische Radioaktivitaet in Freiburg, Germany. During the first 4 months of 2000 the measured 133 Xe concentrations have varied between 0.0 ± 0.1 and 110 ± 10 mBq/m 3 air. The longer lived 131m Xe (T 1/2 = 11.9 d) and short lived 135 Xe (T 1/2 = 9.1 h) have also been detected in small quantities, while 133m Xe concentrations have been consistent with zero. Minimum detectable concentration (MDC) calculations for 133g Xe fell well below the 1 mBq per standard-cubic-meter of air requirement adopted by the CTBT Preparatory Commission. A description of the radioxenon detector, the concentration and MDC calculations and preliminary results of the field test in Germany are presented. (author)

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

    Science.gov (United States)

    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

  14. Automatic radioxenon analyzer for CTBT monitoring

    International Nuclear Information System (INIS)

    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 ampersand D program, PNNL has developed and demonstrated a fully automatic analyzer for collecting and measuring the four Xe radionuclides, 131m Xe(11.9 d), 133m Xe(2.19 d), 133 Xe (5.24 d), and 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 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 μBq/m 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

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

    Science.gov (United States)

    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.

  16. Buildup of radioxenon isotopes in MOX-assemblies

    Energy Technology Data Exchange (ETDEWEB)

    Gniffke, Thomas; Kirchner, Gerald [Carl Friedrich von Weizsaecker-Centre for Science and Peace Research, Hamburg (Germany)

    2015-07-01

    Radioxenon is the main tracer for detection of nuclear tests conducted underground under the verification regime of the Comprehensive Nuclear Test Ban Treaty (CTBT). Since radioxenon is emitted by civilian sources too, like commercial nuclear reactors, source discrimination is still an important issue. Inventory calculations are necessary to predict which xenon isotopic ratios are built up in a reactor and how they differ from those generated by a nuclear explosion. The screening line actually used by the CTBT Organization for source discrimination is based on calculations for uranium fuel of various enrichments used in pressurized water reactors (PWRs). The usage of different fuel, especially mixed U/Pu oxide (MOX) assemblies with reprocessed plutonium, may alter the radioxenon signature of civilian reactors. In this talk, calculations of the radioxenon buildup in a MOX-assembly used in a commercial PWR are presented. Implications for the CTBT verification regimes are discussed and open questions are addressed.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-09-24

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

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

    Science.gov (United States)

    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

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

    International Nuclear Information System (INIS)

    Ringbom, A.; Elmgren, K.; Lindh, K.; Peterson, J.; Bowyer, T.W.; Hayes, J.C.; McIntyre, J.I.; Panisko, M.; Williams, R.

    2009-01-01

    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. (author)

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

    International Nuclear Information System (INIS)

    David M. Hamby

    2007-01-01

    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

  1. Preparation of radioxenon and radioargon mixed sources for IFE14

    International Nuclear Information System (INIS)

    Biegalski, S.R.; Tipping, T.N.; Klingberg, F.J.

    2016-01-01

    The Integrated Field Exercise (IFE14) was conducted from November 3, 2014 through December 9, 2014 in Jordan. This was an exercise to test the capabilities for On-Site Inspection (OSI) as part of the Comprehensive Nuclear-Test-Ban Treaty. One important OSI technology is the measurement of noble gasses that are produced within a nuclear explosion. To support IFE14, radioxenon samples and radioargon samples were created at The University of Texas at Austin TRIGA reactor facility. The goal was to produce a mixed sample containing 131m Xe, 133 Xe, and 37 Ar in activity ratios consistent with the nuclear explosion scenario defined for the exercise. (author)

  2. Multiscale Signal Analysis and Modeling

    CERN Document Server

    Zayed, Ahmed

    2013-01-01

    Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory. This book also: Discusses recently developed signal modeling techniques, such as the multiscale method for complex time series modeling, multiscale positive density estimations, Bayesian Shrinkage Strategies, and algorithms for data adaptive statistics Introduces new sampling algorithms for multidimensional signal processing Provides comprehensive coverage of wavelets with presentations on waveform design and modeling, wavelet analysis of ECG signals and wavelet filters Reviews features extraction and classification algorithms for multiscale signal and image proce...

  3. Modeling binaural signal detection

    NARCIS (Netherlands)

    Breebaart, D.J.

    2001-01-01

    With the advent of multimedia technology and powerful signal processing systems, audio processing and reproduction has gained renewed interest. Examples of products that have been developed are audio coding algorithms to efficiently store and transmit music and speech, or audio reproduction systems

  4. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.; Byrne, H.M.; King, J.R.; Bennett, M.J.

    2013-01-01

    methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more

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

    International Nuclear Information System (INIS)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  7. Models of calcium signalling

    CERN Document Server

    Dupont, Geneviève; Kirk, Vivien; Sneyd, James

    2016-01-01

    This book discusses the ways in which mathematical, computational, and modelling methods can be used to help understand the dynamics of intracellular calcium. The concentration of free intracellular calcium is vital for controlling a wide range of cellular processes, and is thus of great physiological importance. However, because of the complex ways in which the calcium concentration varies, it is also of great mathematical interest.This book presents the general modelling theory as well as a large number of specific case examples, to show how mathematical modelling can interact with experimental approaches, in an interdisciplinary and multifaceted approach to the study of an important physiological control mechanism. Geneviève Dupont is FNRS Research Director at the Unit of Theoretical Chronobiology of the Université Libre de Bruxelles;Martin Falcke is head of the Mathematical Cell Physiology group at the Max Delbrück Center for Molecular Medicine, Berlin;Vivien Kirk is an Associate Professor in the Depar...

  8. Detection of nuclear testing from surface concentration measurements: Analysis of radioxenon from the February 2013 underground test in North Korea

    Science.gov (United States)

    Kurzeja, R. J.; Buckley, R. L.; Werth, D. W.; Chiswell, S. R.

    2018-03-01

    A method is outlined and tested to detect low level nuclear or chemical sources from time series of concentration measurements. The method uses a mesoscale atmospheric model to simulate the concentration signature from a known or suspected source at a receptor which is then regressed successively against segments of the measurement series to create time series of metrics that measure the goodness of fit between the signatures and the measurement segments. The method was applied to radioxenon data from the Comprehensive Test Ban Treaty (CTBT) collection site in Ussuriysk, Russia (RN58) after the Democratic People's Republic of Korea (North Korea) underground nuclear test on February 12, 2013 near Punggye. The metrics were found to be a good screening tool to locate data segments with a strong likelihood of origin from Punggye, especially when multiplied together to a determine the joint probability. Metrics from RN58 were also used to find the probability that activity measured in February and April of 2013 originated from the Feb 12 test. A detailed analysis of an RN58 data segment from April 3/4, 2013 was also carried out for a grid of source locations around Punggye and identified Punggye as the most likely point of origin. Thus, the results support the strong possibility that radioxenon was emitted from the test site at various times in April and was detected intermittently at RN58, depending on the wind direction. The method does not locate unsuspected sources, but instead, evaluates the probability of a source at a specified location. However, it can be extended to include a set of suspected sources. Extension of the method to higher resolution data sets, arbitrary sampling, and time-varying sources is discussed along with a path to evaluate uncertainty in the calculated probabilities.

  9. A review of the developments of radioxenon detectors for nuclear explosion monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Sivels, Ciara B.; McIntyre, Justin I.; Bowyer, Theodore W.; Kalinowski, Martin B.; Pozzi, Sara A.

    2017-09-27

    Developments in radioxenon monitoring since the implementation of the International Monitoring System are reviewed with emphasis on the most current technologies to improve detector sensitivity and resolution. The nuclear detectors reviewed include combinations of plastic and NaI(Tl) detectors, high purity germanium detectors, silicon detectors, and phoswich detectors. The minimum detectable activity and calibration methods for the various detectors are also discussed.

  10. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.

    2013-01-01

    During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.

  11. Diabetes: Models, Signals and control

    Science.gov (United States)

    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. Comparison of phoswich and ARSA-type detectors for radioxenon measurements

    International Nuclear Information System (INIS)

    Ward, R.M.; Biegalski, S.R.F.; Hennig, W.

    2009-01-01

    The monitoring of atmospheric radioxenon to ensure compliance with the Comprehensive Nuclear Test Ban Treaty (CTBT) 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 β-γ coincidence, thus greatly reducing the bulk and electronics of the detector in comparison to the ARSA-type detector. In this experiment, 135 Xe 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 β-γ 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 β-γ coincidence of radioxenon was evaluated. (author)

  13. Atomic layer deposition α-Al2O3 diffusion barriers to eliminate the memory effect in beta-gamma radioxenon detectors

    International Nuclear Information System (INIS)

    Warburton, W.K.; Wolfgang Hennig; Bertrand, J.A.; George, S.M.; Steven Biegalski

    2013-01-01

    Well designed scintillator detectors, including such examples as ARSA, SAUNA, and XIA's 'PhosWatch', can readily achieve the state of the art radioxenon detection limits required for nuclear explosion monitoring. They are also reliable, robust detectors that do not require cryogenic cooling for operation. All three employ the principle of beta-gamma coincidence detection to reduce background counting rates, using a BC-404 plastic scintillator to detect the betas and a CsI or NaI scintillator to detect the gamma-rays. As a consequence of this commonality of design, all three also display a 'memory effect' arising from the diffusion of Xe into BC-404. Thus, when one sample is pumped out of the detector, a fraction remains behind, embedded in the BC-404, where it artificially raises the signal counting rate for the next sample. While this is not a fatal flaw in scintillator detectors, developing a method to eliminate the memory effect would significantly enhance their utility. This paper reports efforts to develop thin, amorphous Al 2 O 3 films, deposited by atomic layer deposition (ALD) to act as diffusion barriers on the BC-404 surfaces exposed to radioxenon. Using radon as a convenient substitute for Xe, film thicknesses between 2 and 10 nm were originally investigated and found to show a memory effect to varying degrees. A second set of 20 and 30 nm films was then produced, which appeared to completely eliminate the radon memory effect, but, when consequentially tested with radioxenon, were found to exhibit xenon memory effects that were approximately half of the effect found on uncoated BC-404. We draw two conclusions from this result. The first is that it will be necessary to develop an improved method for depositing thicker ALD Al 2 O 3 films at lower temperatures while still retaining high film quality. The second is that, since xenon is required to test for the xenon memory effect, we need a test method that does not require xenon radio-isotopes in order to

  14. A Multi-Layer Phoswich Radioxenon Detection System

    International Nuclear Information System (INIS)

    David M. Hamby

    2007-01-01

    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. Analysis method for beta-gamma coincidence spectra from radio-xenon isotopes

    International Nuclear Information System (INIS)

    Yang Wenjing; Yin Jingpeng; Huang Xiongliang; Cheng Zhiwei; Shen Maoquan; Zhang Yang

    2012-01-01

    Radio-xenon isotopes monitoring is one important method for the verification of CTBT, what includes the measurement methods of HPGe γ spectrometer and β-γ coincidence. The article describes the analytic flowchart and method of three-dimensional beta-gamma coincidence spectra from β-γ systems, and analyses in detail the principles and methods of the regions of interest of coincidence spectra and subtracting the interference, finally gives the formula of radioactivity of Xenon isotopes and minimum detectable concentrations. Studying on the principles of three-dimensional beta-gamma coincidence spectra, which can supply the foundation for designing the software of β-γ coincidence systems. (authors)

  16. Modeling High-Dimensional Multichannel Brain Signals

    KAUST Repository

    Hu, Lechuan; Fortin, Norbert J.; Ombao, Hernando

    2017-01-01

    aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel

  17. Investigations of surface coatings to reduce memory effect in plastic scintillator detectors used for radioxenon detection

    International Nuclear Information System (INIS)

    Blaeckberg, L.; Fay, A.; Jogi, I.; Biegalski, S.; Boman, M.; Elmgren, K.; Fritioff, T.; Johansson, A.; Martensson, L.; Nielsen, F.; Ringbom, A.; Rooth, M.; Sjoestrand, H.; Klintenberg, M.

    2011-01-01

    In this work Al 2 O 3 and SiO 2 coatings are tested as Xe diffusion barriers on plastic scintillator substrates. The motivation is improved beta-gamma coincidence detection systems, used to measure atmospheric radioxenon within the verification regime of the Comprehensive Nuclear-Test-Ban Treaty. One major drawback with the current setup of these systems is that the radioxenon tends to diffuse into the plastic scintillator material responsible for the beta detection, resulting in an unwanted memory effect. Here, coatings with thicknesses between 20 and 900 nm have been deposited onto plastic scintillators, and investigated using two different experimental techniques. The results show that all tested coatings reduce the Xe diffusion into the plastic. The reduction is observed to increase with coating thickness for both coating materials. The 425 nm Al 2 O 3 coating is the most successful one, presenting a diffusion reduction of a factor 100, compared to uncoated plastic. In terms of memory effect reduction this coating is thus a viable solution to the problem in question.

  18. Investigations of surface coatings to reduce memory effect in plastic scintillator detectors used for radioxenon detection

    Science.gov (United States)

    Bläckberg, L.; Fay, A.; Jõgi, I.; Biegalski, S.; Boman, M.; Elmgren, K.; Fritioff, T.; Johansson, A.; Mårtensson, L.; Nielsen, F.; Ringbom, A.; Rooth, M.; Sjöstrand, H.; Klintenberg, M.

    2011-11-01

    In this work Al2O3 and SiO2 coatings are tested as Xe diffusion barriers on plastic scintillator substrates. The motivation is improved beta-gamma coincidence detection systems, used to measure atmospheric radioxenon within the verification regime of the Comprehensive Nuclear-Test-Ban Treaty. One major drawback with the current setup of these systems is that the radioxenon tends to diffuse into the plastic scintillator material responsible for the beta detection, resulting in an unwanted memory effect. Here, coatings with thicknesses between 20 and 900 nm have been deposited onto plastic scintillators, and investigated using two different experimental techniques. The results show that all tested coatings reduce the Xe diffusion into the plastic. The reduction is observed to increase with coating thickness for both coating materials. The 425 nm Al2O3 coating is the most successful one, presenting a diffusion reduction of a factor 100, compared to uncoated plastic. In terms of memory effect reduction this coating is thus a viable solution to the problem in question.

  19. Discrete dynamic modeling of cellular signaling networks.

    Science.gov (United States)

    Albert, Réka; Wang, Rui-Sheng

    2009-01-01

    Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

  20. Regression models of reactor diagnostic signals

    International Nuclear Information System (INIS)

    Vavrin, J.

    1989-01-01

    The application is described of an autoregression model as the simplest regression model of diagnostic signals in experimental analysis of diagnostic systems, in in-service monitoring of normal and anomalous conditions and their diagnostics. The method of diagnostics is described using a regression type diagnostic data base and regression spectral diagnostics. The diagnostics is described of neutron noise signals from anomalous modes in the experimental fuel assembly of a reactor. (author)

  1. MASCOTTE: analytical model of eddy current signals

    International Nuclear Information System (INIS)

    Delsarte, G.; Levy, R.

    1992-01-01

    Tube examination is a major application of the eddy current technique in the nuclear and petrochemical industries. Such examination configurations being specially adapted to analytical modes, a physical model is developed on portable computers. It includes simple approximations made possible by the effective conditions of the examinations. The eddy current signal is described by an analytical formulation that takes into account the tube dimensions, the sensor conception, the physical characteristics of the defect and the examination parameters. Moreover, the model makes it possible to associate real signals and simulated signals

  2. Effects of surface coatings on the light collection in plastic scintillators used for radioxenon detection

    International Nuclear Information System (INIS)

    Bläckberg, L; Klintenberg, M; Sjöstrand, H; Ringbom, A

    2012-01-01

    Atomic layer deposition coatings are under investigation to reduce the diffusion of radioxenon into plastic scintillators. This paper investigates the impact of such surface coating on the light collection efficiency in a cylindrical geometry. A high and uniform light collection efficiency is important to preserve detector resolution. Monte Carlo simulations and measurements have been carried out to study the influence of coating thickness, refractive index and surface quality. It was found that it is important to achieve a smooth coating and good optical match between the refractive indices of the coating and the plastic scintillator. Taking into account these considerations, the detector under study could be coated without a significant degradation of its resolution.

  3. Memory effect, resolution, and efficiency measurements of an Al2O3 coated plastic scintillator used for radioxenon detection

    International Nuclear Information System (INIS)

    Bläckberg, L.; Fritioff, T.; Mårtensson, L.; Nielsen, F.; Ringbom, A.; Sjöstrand, H.; Klintenberg, M.

    2013-01-01

    A cylindrical plastic scintillator cell, used for radioxenon monitoring within the verification regime of the Comprehensive Nuclear-Test-Ban Treaty, has been coated with 425 nm Al 2 O 3 using low temperature Atomic Layer Deposition, and its performance has been evaluated. The motivation is to reduce the memory effect caused by radioxenon diffusing into the plastic scintillator material during measurements, resulting in an elevated detection limit. Measurements with the coated detector show both energy resolution and efficiency comparable to uncoated detectors, and a memory effect reduction of a factor of 1000. Provided that the quality of the detector is maintained for a longer period of time, Al 2 O 3 coatings are believed to be a viable solution to the memory effect problem in question

  4. Memory effect, resolution, and efficiency measurements of an Al2O3 coated plastic scintillator used for radioxenon detection

    Science.gov (United States)

    Bläckberg, L.; Fritioff, T.; Mårtensson, L.; Nielsen, F.; Ringbom, A.; Sjöstrand, H.; Klintenberg, M.

    2013-06-01

    A cylindrical plastic scintillator cell, used for radioxenon monitoring within the verification regime of the Comprehensive Nuclear-Test-Ban Treaty, has been coated with 425 nm Al2O3 using low temperature Atomic Layer Deposition, and its performance has been evaluated. The motivation is to reduce the memory effect caused by radioxenon diffusing into the plastic scintillator material during measurements, resulting in an elevated detection limit. Measurements with the coated detector show both energy resolution and efficiency comparable to uncoated detectors, and a memory effect reduction of a factor of 1000. Provided that the quality of the detector is maintained for a longer period of time, Al2O3 coatings are believed to be a viable solution to the memory effect problem in question.

  5. Learning sparse generative models of audiovisual signals

    OpenAIRE

    Monaci, Gianluca; Sommer, Friedrich T.; Vandergheynst, Pierre

    2008-01-01

    This paper presents a novel framework to learn sparse represen- tations for audiovisual signals. An audiovisual signal is modeled as a sparse sum of audiovisual kernels. The kernels are bimodal functions made of synchronous audio and video components that can be positioned independently and arbitrarily in space and time. We design an algorithm capable of learning sets of such audiovi- sual, synchronous, shift-invariant functions by alternatingly solving a coding and a learning pr...

  6. Patterns of flavor signals in supersymmetric models

    Energy Technology Data Exchange (ETDEWEB)

    Goto, T. [KEK National High Energy Physics, Tsukuba (Japan)]|[Kyoto Univ. (Japan). YITP; Okada, Y. [KEK National High Energy Physics, Tsukuba (Japan)]|[Graduate Univ. for Advanced Studies, Tsukuba (Japan). Dept. of Particle and Nucelar Physics; Shindou, T. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)]|[International School for Advanced Studies, Trieste (Italy); Tanaka, M. [Osaka Univ., Toyonaka (Japan). Dept. of Physics

    2007-11-15

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

  7. Patterns of flavor signals in supersymmetric models

    International Nuclear Information System (INIS)

    Goto, T.; Tanaka, M.

    2007-11-01

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

  8. Mathematical Models Light Up Plant Signaling

    NARCIS (Netherlands)

    Chew, Y.H.; Smith, R.W.; Jones, H.J.; Seaton, D.D.; Grima, R.; Halliday, K.J.

    2014-01-01

    Plants respond to changes in the environment by triggering a suite of regulatory networks that control and synchronize molecular signaling in different tissues, organs, and the whole plant. Molecular studies through genetic and environmental perturbations, particularly in the model plant Arabidopsis

  9. Modeling high dimensional multichannel brain signals

    KAUST Repository

    Hu, Lechuan

    2017-03-27

    In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.

  10. Modeling High-Dimensional Multichannel Brain Signals

    KAUST Repository

    Hu, Lechuan

    2017-12-12

    Our goal is to model and measure functional and effective (directional) connectivity in multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The difficulties from analyzing these data mainly come from two aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with potentially high lag order so that complex lead-lag temporal dynamics between the channels can be captured. Estimates of the VAR model will be obtained by our proposed hybrid LASSLE (LASSO + LSE) method which combines regularization (to control for sparsity) and least squares estimation (to improve bias and mean-squared error). Then we employ some measures of connectivity but put an emphasis on partial directed coherence (PDC) which can capture the directional connectivity between channels. PDC is a frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative to all possible receivers in the network. The proposed modeling approach provided key insights into potential functional relationships among simultaneously recorded sites during performance of a complex memory task. Specifically, this novel method was successful in quantifying patterns of effective connectivity across electrode locations, and in capturing how these patterns varied across trial epochs and trial types.

  11. Modeling high dimensional multichannel brain signals

    KAUST Repository

    Hu, Lechuan; Fortin, Norbert; Ombao, Hernando

    2017-01-01

    In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.

  12. Model for neural signaling leap statistics

    International Nuclear Information System (INIS)

    Chevrollier, Martine; Oria, Marcos

    2011-01-01

    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 0 C, awaken regime) and Levy statistics (T = 35.5 0 C, sleeping period), characterized by rare events of long range connections.

  13. Model for neural signaling leap statistics

    Science.gov (United States)

    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.

  14. Model for neural signaling leap statistics

    Energy Technology Data Exchange (ETDEWEB)

    Chevrollier, Martine; Oria, Marcos, E-mail: oria@otica.ufpb.br [Laboratorio de Fisica Atomica e Lasers Departamento de Fisica, Universidade Federal da ParaIba Caixa Postal 5086 58051-900 Joao Pessoa, Paraiba (Brazil)

    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{sup 0}C, awaken regime) and Levy statistics (T = 35.5{sup 0}C, sleeping period), characterized by rare events of long range connections.

  15. Logic integer programming models for signaling networks.

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2014-05-01

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

  17. A parametric framework for modelling of bioelectrical signals

    CERN Document Server

    Mughal, Yar Muhammad

    2016-01-01

    This book examines non-invasive, electrical-based methods for disease diagnosis and assessment of heart function. In particular, a formalized signal model is proposed since this offers several advantages over methods that rely on measured data alone. By using a formalized representation, the parameters of the signal model can be easily manipulated and/or modified, thus providing mechanisms that allow researchers to reproduce and control such signals. In addition, having such a formalized signal model makes it possible to develop computer tools that can be used for manipulating and understanding how signal changes result from various heart conditions, as well as for generating input signals for experimenting with and evaluating the performance of e.g. signal extraction methods. The work focuses on bioelectrical information, particularly electrical bio-impedance (EBI). Once the EBI has been measured, the corresponding signals have to be modelled for analysis. This requires a structured approach in order to move...

  18. Signal Processing Model for Radiation Transport

    Energy Technology Data Exchange (ETDEWEB)

    Chambers, D H

    2008-07-28

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

  19. Statistical Challenges in Modeling Big Brain Signals

    KAUST Repository

    Yu, Zhaoxia

    2017-11-01

    Brain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible solutions, and highlight future research directions.

  20. Statistical Challenges in Modeling Big Brain Signals

    KAUST Repository

    Yu, Zhaoxia; Pluta, Dustin; Shen, Tong; Chen, Chuansheng; Xue, Gui; Ombao, Hernando

    2017-01-01

    Brain signal data are inherently big: massive in amount, complex in structure, and high in dimensions. These characteristics impose great challenges for statistical inference and learning. Here we review several key challenges, discuss possible

  1. Memory effect, resolution, and efficiency measurements of an Al{sub 2}O{sub 3} coated plastic scintillator used for radioxenon detection

    Energy Technology Data Exchange (ETDEWEB)

    Bläckberg, L., E-mail: lisa.blackberg@physics.uu.se [Department of Physics and Astronomy, Uppsala University, Box 516, SE-75120 Uppsala (Sweden); Fritioff, T.; Mårtensson, L.; Nielsen, F.; Ringbom, A. [Division of Defence and Security Systems, Swedish Defence Research Agency (FOI), SE-17290 Stockholm (Sweden); Sjöstrand, H.; Klintenberg, M. [Department of Physics and Astronomy, Uppsala University, Box 516, SE-75120 Uppsala (Sweden)

    2013-06-21

    A cylindrical plastic scintillator cell, used for radioxenon monitoring within the verification regime of the Comprehensive Nuclear-Test-Ban Treaty, has been coated with 425 nm Al{sub 2}O{sub 3} using low temperature Atomic Layer Deposition, and its performance has been evaluated. The motivation is to reduce the memory effect caused by radioxenon diffusing into the plastic scintillator material during measurements, resulting in an elevated detection limit. Measurements with the coated detector show both energy resolution and efficiency comparable to uncoated detectors, and a memory effect reduction of a factor of 1000. Provided that the quality of the detector is maintained for a longer period of time, Al{sub 2}O{sub 3} coatings are believed to be a viable solution to the memory effect problem in question.

  2. Mathematical modelling of SERK mediated BR signalling

    NARCIS (Netherlands)

    Esse, van G.W.

    2013-01-01

    Being sessile by nature plants are continuously challenged by biotic and abiotic stress factors. At the cellular level, different stimuli are perceived and translated to the desired response. In order to achieve this, signal transduction cascades have to be interlinked. Complex networks

  3. Efficient ECG Signal Compression Using Adaptive Heart Model

    National Research Council Canada - National Science Library

    Szilagyi, S

    2001-01-01

    This paper presents an adaptive, heart-model-based electrocardiography (ECG) compression method. After conventional pre-filtering the waves from the signal are localized and the model's parameters are determined...

  4. Improving traffic signal management and operations : a basic service model.

    Science.gov (United States)

    2009-12-01

    This report provides a guide for achieving a basic service model for traffic signal management and : operations. The basic service model is based on simply stated and defensible operational objectives : that consider the staffing level, expertise and...

  5. Signals and Systems in Biomedical Engineering Signal Processing and Physiological Systems Modeling

    CERN Document Server

    Devasahayam, Suresh R

    2013-01-01

    The use of digital signal processing is ubiquitous in the field of physiology and biomedical engineering. The application of such mathematical and computational tools requires a formal or explicit understanding of physiology. Formal models and analytical techniques are interlinked in physiology as in any other field. This book takes a unitary approach to physiological systems, beginning with signal measurement and acquisition, followed by signal processing, linear systems modelling, and computer simulations. The signal processing techniques range across filtering, spectral analysis and wavelet analysis. Emphasis is placed on fundamental understanding of the concepts as well as solving numerical problems. Graphs and analogies are used extensively to supplement the mathematics. Detailed models of nerve and muscle at the cellular and systemic levels provide examples for the mathematical methods and computer simulations. Several of the models are sufficiently sophisticated to be of value in understanding real wor...

  6. MPD model for radar echo signal of hypersonic targets

    Directory of Open Access Journals (Sweden)

    Xu Xuefei

    2014-08-01

    Full Text Available The stop-and-go (SAG model is typically used for echo signal received by the radar using linear frequency modulation pulse compression. In this study, the authors demonstrate that this model is not applicable to hypersonic targets. Instead of SAG model, they present a more realistic echo signal model (moving-in-pulse duration (MPD for hypersonic targets. Following that, they evaluate the performances of pulse compression under the SAG and MPD models by theoretical analysis and simulations. They found that the pulse compression gain has an increase of 3 dB by using the MPD model compared with the SAG model in typical cases.

  7. Large-signal modeling method for power FETs and diodes

    Energy Technology Data Exchange (ETDEWEB)

    Sun Lu; Wang Jiali; Wang Shan; Li Xuezheng; Shi Hui; Wang Na; Guo Shengping, E-mail: sunlu_1019@126.co [School of Electromechanical Engineering, Xidian University, Xi' an 710071 (China)

    2009-06-01

    Under a large signal drive level, a frequency domain black box model of the nonlinear scattering function is introduced into power FETs and diodes. A time domain measurement system and a calibration method based on a digital oscilloscope are designed to extract the nonlinear scattering function of semiconductor devices. The extracted models can reflect the real electrical performance of semiconductor devices and propose a new large-signal model to the design of microwave semiconductor circuits.

  8. Large-signal modeling method for power FETs and diodes

    International Nuclear Information System (INIS)

    Sun Lu; Wang Jiali; Wang Shan; Li Xuezheng; Shi Hui; Wang Na; Guo Shengping

    2009-01-01

    Under a large signal drive level, a frequency domain black box model of the nonlinear scattering function is introduced into power FETs and diodes. A time domain measurement system and a calibration method based on a digital oscilloscope are designed to extract the nonlinear scattering function of semiconductor devices. The extracted models can reflect the real electrical performance of semiconductor devices and propose a new large-signal model to the design of microwave semiconductor circuits.

  9. Modeling laser velocimeter signals as triply stochastic Poisson processes

    Science.gov (United States)

    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.

  10. Coherence method of identifying signal noise model

    International Nuclear Information System (INIS)

    Vavrin, J.

    1981-01-01

    The noise analysis method is discussed in identifying perturbance models and their parameters by a stochastic analysis of the noise model of variables measured on a reactor. The analysis of correlations is made in the frequency region using coherence analysis methods. In identifying an actual specific perturbance, its model should be determined and recognized in a compound model of the perturbance system using the results of observation. The determination of the optimum estimate of the perturbance system model is based on estimates of related spectral densities which are determined from the spectral density matrix of the measured variables. Partial and multiple coherence, partial transfers, the power spectral densities of the input and output variables of the noise model are determined from the related spectral densities. The possibilities of applying the coherence identification methods were tested on a simple case of a simulated stochastic system. Good agreement was found of the initial analytic frequency filters and the transfers identified. (B.S.)

  11. Modeling of Nonlinear Beat Signals of TAE's

    Science.gov (United States)

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

    2012-03-01

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

  12. Modelling of Signal - Level Crossing System

    Directory of Open Access Journals (Sweden)

    Daniel Novak

    2006-01-01

    Full Text Available The author presents an object-oriented model of a railway level-crossing system created for the purpose of functional requirements specification. Unified Modelling Language (UML, version 1.4, which enables specification, visualisation, construction and documentation of software system artefacts, was used. The main attention was paid to analysis and design phases. The former phase resulted in creation of use case diagrams and sequential diagrams, the latter in creation of class/object diagrams and statechart diagrams.

  13. HP Memristor mathematical model for periodic signals and DC

    KAUST Repository

    Radwan, Ahmed G.; Salama, Khaled N.; Zidan, Mohammed A.

    2012-01-01

    the formulas for any general square wave. The limiting conditions for saturation are also provided in case of either DC or periodic signals. The derived equations are compared to the SPICE model of the Memristor showing a perfect match.

  14. Comparison of Linear Prediction Models for Audio Signals

    Directory of Open Access Journals (Sweden)

    2009-03-01

    Full Text Available While linear prediction (LP has become immensely popular in speech modeling, it does not seem to provide a good approach for modeling audio signals. This is somewhat surprising, since a tonal signal consisting of a number of sinusoids can be perfectly predicted based on an (all-pole LP model with a model order that is twice the number of sinusoids. We provide an explanation why this result cannot simply be extrapolated to LP of audio signals. If noise is taken into account in the tonal signal model, a low-order all-pole model appears to be only appropriate when the tonal components are uniformly distributed in the Nyquist interval. Based on this observation, different alternatives to the conventional LP model can be suggested. Either the model should be changed to a pole-zero, a high-order all-pole, or a pitch prediction model, or the conventional LP model should be preceded by an appropriate frequency transform, such as a frequency warping or downsampling. By comparing these alternative LP models to the conventional LP model in terms of frequency estimation accuracy, residual spectral flatness, and perceptual frequency resolution, we obtain several new and promising approaches to LP-based audio modeling.

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

    Science.gov (United States)

    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

  16. A simple statistical signal loss model for deep underground garage

    DEFF Research Database (Denmark)

    Nguyen, Huan Cong; Gimenez, Lucas Chavarria; Kovacs, Istvan

    2016-01-01

    In this paper we address the channel modeling aspects for a deep-indoor scenario with extreme coverage conditions in terms of signal losses, namely underground garage areas. We provide an in-depth analysis in terms of path loss (gain) and large scale signal shadowing, and a propose simple...... propagation model which can be used to predict cellular signal levels in similar deep-indoor scenarios. The proposed frequency-independent floor attenuation factor (FAF) is shown to be in range of 5.2 dB per meter deep....

  17. Wires in the soup: quantitative models of cell signaling

    Science.gov (United States)

    Cheong, Raymond; Levchenko, Andre

    2014-01-01

    Living cells are capable of extracting information from their environments and mounting appropriate responses to a variety of associated challenges. The underlying signal transduction networks enabling this can be quite complex, necessitating for their unraveling by sophisticated computational modeling coupled with precise experimentation. Although we are still at the beginning of this process, some recent examples of integrative analysis of cell signaling are very encouraging. This review highlights the case of the NF-κB pathway in order to illustrate how a quantitative model of a signaling pathway can be gradually constructed through continuous experimental validation, and what lessons one might learn from such exercises. PMID:18291655

  18. THE SIGNAL APPROACH TO MODELLING THE BALANCE OF PAYMENT CRISIS

    Directory of Open Access Journals (Sweden)

    O. Chernyak

    2016-12-01

    Full Text Available The paper considers and presents synthesis of theoretical models of balance of payment crisis and investigates the most effective ways to model the crisis in Ukraine. For mathematical formalization of balance of payment crisis, comparative analysis of the effectiveness of different calculation methods of Exchange Market Pressure Index was performed. A set of indicators that signal the growing likelihood of balance of payments crisis was defined using signal approach. With the help of minimization function thresholds indicators were selected, the crossing of which signalize increase in the probability of balance of payment crisis.

  19. Small signal modeling of wind farms

    DEFF Research Database (Denmark)

    Ebrahimzadeh, Esmaeil; Blaabjerg, Frede; Wang, Xiongfei

    2017-01-01

    -Input Multi-Output (MIMO) dynamic system, where the current control loops with Phase-Locked Loops (PLLs) are linearized around an operating point. Each sub-module of the wind farm is modeled as a 2×2 admittance matrix in dq-domain and all are combined together by using a dq nodal admittance matrix....... The frequency and damping of the oscillatory modes are calculated by finding the poles of the introduced MIMO matrix. Time-domain simulation results obtained from a 400-MW wind farm are used to verify the effectiveness of the presented model....

  20. An accurate and simple large signal model of HEMT

    DEFF Research Database (Denmark)

    Liu, Qing

    1989-01-01

    A large-signal model of discrete HEMTs (high-electron-mobility transistors) has been developed. It is simple and suitable for SPICE simulation of hybrid digital ICs. The model parameters are extracted by using computer programs and data provided by the manufacturer. Based on this model, a hybrid...

  1. Semiconductor Modeling For Simulating Signal, Power, and Electromagneticintegrity

    CERN Document Server

    Leventhal, Roy

    2006-01-01

    Assists engineers in designing high-speed circuits. The emphasis is on semiconductor modeling, with PCB transmission line effects, equipment enclosure effects, and other modeling issues discussed as needed. This text addresses practical considerations, including process variation, model accuracy, validation and verification, and signal integrity.

  2. Vibration Signal Forecasting on Rotating Machinery by means of Signal Decomposition and Neurofuzzy Modeling

    Directory of Open Access Journals (Sweden)

    Daniel Zurita-Millán

    2016-01-01

    Full Text Available Vibration monitoring plays a key role in the industrial machinery reliability since it allows enhancing the performance of the machinery under supervision through the detection of failure modes. Thus, vibration monitoring schemes that give information regarding future condition, that is, prognosis approaches, are of growing interest for the scientific and industrial communities. This work proposes a vibration signal prognosis methodology, applied to a rotating electromechanical system and its associated kinematic chain. The method combines the adaptability of neurofuzzy modeling with a signal decomposition strategy to model the patterns of the vibrations signal under different fault scenarios. The model tuning is performed by means of Genetic Algorithms along with a correlation based interval selection procedure. The performance and effectiveness of the proposed method are validated experimentally with an electromechanical test bench containing a kinematic chain. The results of the study indicate the suitability of the method for vibration forecasting in complex electromechanical systems and their associated kinematic chains.

  3. A computational model of human auditory signal processing and perception

    DEFF Research Database (Denmark)

    Jepsen, Morten Løve; Ewert, Stephan D.; Dau, Torsten

    2008-01-01

    A model of computational auditory signal-processing and perception that accounts for various aspects of simultaneous and nonsimultaneous masking in human listeners is presented. The model is based on the modulation filterbank model described by Dau et al. [J. Acoust. Soc. Am. 102, 2892 (1997...... discrimination with pure tones and broadband noise, tone-in-noise detection, spectral masking with narrow-band signals and maskers, forward masking with tone signals and tone or noise maskers, and amplitude-modulation detection with narrow- and wideband noise carriers. The model can account for most of the key...... properties of the data and is more powerful than the original model. The model might be useful as a front end in technical applications....

  4. Discrete dynamic modeling of T cell survival signaling networks

    Science.gov (United States)

    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).

  5. Collective signaling behavior in a networked-oscillator model

    Science.gov (United States)

    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.

  6. Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation

    Science.gov (United States)

    Gan, Xiao; Albert, RéKa

    Analyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. We identified the long-term behaviors of a multi-level, 70-node discrete dynamic model of the stomatal opening process in plants. We reduce the model's huge state space by reducing unregulated nodes and simple mediator nodes, and by simplifying the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.

  7. Network modeling reveals prevalent negative regulatory relationships between signaling sectors in Arabidopsis immune signaling.

    Directory of Open Access Journals (Sweden)

    Masanao Sato

    Full Text Available Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. We studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2. This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles for 571 immune response genes of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with Pto DC3000 AvrRpt2. The mRNA profiles were analyzed as detailed descriptions of changes in the network state resulting from the genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting static network model accurately predicted 23 of 25 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i the components of the network are highly interconnected; and (ii negative regulatory relationships are common between signaling sectors. Complex regulatory relationships, including a novel negative regulatory relationship between the early microbe-associated molecular pattern-triggered signaling sectors and the salicylic acid sector, were further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a "sector

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

    International Nuclear Information System (INIS)

    Kadtke, J.; Kremliovsky, M.

    1996-01-01

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

  9. Small-signal model for the series resonant converter

    Science.gov (United States)

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

    1985-01-01

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

  10. Mixed-signal instrumentation for large-signal device characterization and modelling

    NARCIS (Netherlands)

    Marchetti, M.

    2013-01-01

    This thesis concentrates on the development of advanced large-signal measurement and characterization tools to support technology development, model extraction and validation, and power amplifier (PA) designs that address the newly introduced third and fourth generation (3G and 4G) wideband

  11. Electromagnetic modeling method for eddy current signal analysis

    International Nuclear Information System (INIS)

    Lee, D. H.; Jung, H. K.; Cheong, Y. M.; Lee, Y. S.; Huh, H.; Yang, D. J.

    2004-10-01

    An electromagnetic modeling method for eddy current signal analysis is necessary before an experiment is performed. Electromagnetic modeling methods consists of the analytical method and the numerical method. Also, the numerical methods can be divided by Finite Element Method(FEM), Boundary Element Method(BEM) and Volume Integral Method(VIM). Each modeling method has some merits and demerits. Therefore, the suitable modeling method can be chosen by considering the characteristics of each modeling. This report explains the principle and application of each modeling method and shows the comparison modeling programs

  12. Reduced modeling of signal transduction – a modular approach

    Directory of Open Access Journals (Sweden)

    Ederer Michael

    2007-09-01

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

  13. HP Memristor mathematical model for periodic signals and DC

    KAUST Repository

    Radwan, Ahmed G.

    2012-07-28

    In this paper mathematical models of the HP Memristor for DC and periodic signal inputs are provided. The need for a rigid model for the Memristor using conventional current and voltage quantities is essential for the development of many promising Memristors\\' applications. Unlike the previous works, which focuses on the sinusoidal input waveform, we derived rules for any periodic signals in general in terms of voltage and current. Square and triangle waveforms are studied explicitly, extending the formulas for any general square wave. The limiting conditions for saturation are also provided in case of either DC or periodic signals. The derived equations are compared to the SPICE model of the Memristor showing a perfect match.

  14. Signal and noise modeling in confocal laser scanning fluorescence microscopy.

    Science.gov (United States)

    Herberich, Gerlind; Windoffer, Reinhard; Leube, Rudolf E; Aach, Til

    2012-01-01

    Fluorescence confocal laser scanning microscopy (CLSM) has revolutionized imaging of subcellular structures in biomedical research by enabling the acquisition of 3D time-series of fluorescently-tagged proteins in living cells, hence forming the basis for an automated quantification of their morphological and dynamic characteristics. Due to the inherently weak fluorescence, CLSM images exhibit a low SNR. We present a novel model for the transfer of signal and noise in CLSM that is both theoretically sound as well as corroborated by a rigorous analysis of the pixel intensity statistics via measurement of the 3D noise power spectra, signal-dependence and distribution. Our model provides a better fit to the data than previously proposed models. Further, it forms the basis for (i) the simulation of the CLSM imaging process indispensable for the quantitative evaluation of CLSM image analysis algorithms, (ii) the application of Poisson denoising algorithms and (iii) the reconstruction of the fluorescence signal.

  15. Corrected Four-Sphere Head Model for EEG Signals.

    Science.gov (United States)

    Næss, Solveig; Chintaluri, Chaitanya; Ness, Torbjørn V; Dale, Anders M; Einevoll, Gaute T; Wójcik, Daniel K

    2017-01-01

    The EEG signal is generated by electrical brain cell activity, often described in terms of current dipoles. By applying EEG forward models we can compute the contribution from such dipoles to the electrical potential recorded by EEG electrodes. Forward models are key both for generating understanding and intuition about the neural origin of EEG signals as well as inverse modeling, i.e., the estimation of the underlying dipole sources from recorded EEG signals. Different models of varying complexity and biological detail are used in the field. One such analytical model is the four-sphere model which assumes a four-layered spherical head where the layers represent brain tissue, cerebrospinal fluid (CSF), skull, and scalp, respectively. While conceptually clear, the mathematical expression for the electric potentials in the four-sphere model is cumbersome, and we observed that the formulas presented in the literature contain errors. Here, we derive and present the correct analytical formulas with a detailed derivation. A useful application of the analytical four-sphere model is that it can serve as ground truth to test the accuracy of numerical schemes such as the Finite Element Method (FEM). We performed FEM simulations of the four-sphere head model and showed that they were consistent with the corrected analytical formulas. For future reference we provide scripts for computing EEG potentials with the four-sphere model, both by means of the correct analytical formulas and numerical FEM simulations.

  16. Corrected Four-Sphere Head Model for EEG Signals

    Directory of Open Access Journals (Sweden)

    Solveig Næss

    2017-10-01

    Full Text Available The EEG signal is generated by electrical brain cell activity, often described in terms of current dipoles. By applying EEG forward models we can compute the contribution from such dipoles to the electrical potential recorded by EEG electrodes. Forward models are key both for generating understanding and intuition about the neural origin of EEG signals as well as inverse modeling, i.e., the estimation of the underlying dipole sources from recorded EEG signals. Different models of varying complexity and biological detail are used in the field. One such analytical model is the four-sphere model which assumes a four-layered spherical head where the layers represent brain tissue, cerebrospinal fluid (CSF, skull, and scalp, respectively. While conceptually clear, the mathematical expression for the electric potentials in the four-sphere model is cumbersome, and we observed that the formulas presented in the literature contain errors. Here, we derive and present the correct analytical formulas with a detailed derivation. A useful application of the analytical four-sphere model is that it can serve as ground truth to test the accuracy of numerical schemes such as the Finite Element Method (FEM. We performed FEM simulations of the four-sphere head model and showed that they were consistent with the corrected analytical formulas. For future reference we provide scripts for computing EEG potentials with the four-sphere model, both by means of the correct analytical formulas and numerical FEM simulations.

  17. Road Impedance Model Study under the Control of Intersection Signal

    Directory of Open Access Journals (Sweden)

    Yunlin Luo

    2015-01-01

    Full Text Available Road traffic impedance model is a difficult and critical point in urban traffic assignment and route guidance. The paper takes a signalized intersection as the research object. On the basis of traditional traffic wave theory including the implementation of traffic wave model and the analysis of vehicles’ gathering and dissipating, the road traffic impedance model is researched by determining the basic travel time and waiting delay time. Numerical example results have proved that the proposed model in this paper has received better calculation performance compared to existing model, especially in flat hours. The values of mean absolute percentage error (MAPE and mean absolute deviation (MAD are separately reduced by 3.78% and 2.62 s. It shows that the proposed model has feasibility and availability in road traffic impedance under intersection signal.

  18. Stochastic Modelling as a Tool for Seismic Signals Segmentation

    Directory of Open Access Journals (Sweden)

    Daniel Kucharczyk

    2016-01-01

    Full Text Available In order to model nonstationary real-world processes one can find appropriate theoretical model with properties following the analyzed data. However in this case many trajectories of the analyzed process are required. Alternatively, one can extract parts of the signal that have homogenous structure via segmentation. The proper segmentation can lead to extraction of important features of analyzed phenomena that cannot be described without the segmentation. There is no one universal method that can be applied for all of the phenomena; thus novel methods should be invented for specific cases. They might address specific character of the signal in different domains (time, frequency, time-frequency, etc.. In this paper we propose two novel segmentation methods that take under consideration the stochastic properties of the analyzed signals in time domain. Our research is motivated by the analysis of vibration signals acquired in an underground mine. In such signals we observe seismic events which appear after the mining activity, like blasting, provoked relaxation of rock, and some unexpected events, like natural rock burst. The proposed segmentation procedures allow for extraction of such parts of the analyzed signals which are related to mentioned events.

  19. Gap Acceptance Behavior Model for Non-signalized

    OpenAIRE

    Fajaruddin Bin Mustakim

    2015-01-01

    The paper proposes field studies that were performed to determine the critical gap on the multiple rural roadways Malaysia, at non-signalized T-intersection by using The Raff and Logic Method. Critical gap between passenger car and motorcycle have been determined.   There are quite number of studied doing gap acceptance behavior model for passenger car however still few research on gap acceptance behavior model for motorcycle. Thus in this paper, logistic regression models were developed to p...

  20. Synchronous Modeling of Modular Avionics Architectures using the SIGNAL Language

    OpenAIRE

    Gamatié , Abdoulaye; Gautier , Thierry

    2002-01-01

    This document presents a study on the modeling of architecture components for avionics applications. We consider the avionics standard ARINC 653 specifications as basis, as well as the synchronous language SIGNAL to describe the modeling. A library of APEX object models (partition, process, communication and synchronization services, etc.) has been implemented. This should allow to describe distributed real-time applications using POLYCHRONY, so as to access formal tools and techniques for ar...

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

    Science.gov (United States)

    Casadei, D.

    2012-01-01

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

  2. State–time spectrum of signal transduction logic models

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  3. An improved large signal model of InP HEMTs

    Science.gov (United States)

    Li, Tianhao; Li, Wenjun; Liu, Jun

    2018-05-01

    An improved large signal model for InP HEMTs is proposed in this paper. The channel current and charge model equations are constructed based on the Angelov model equations. Both the equations for channel current and gate charge models were all continuous and high order drivable, and the proposed gate charge model satisfied the charge conservation. For the strong leakage induced barrier reduction effect of InP HEMTs, the Angelov current model equations are improved. The channel current model could fit DC performance of devices. A 2 × 25 μm × 70 nm InP HEMT device is used to demonstrate the extraction and validation of the model, in which the model has predicted the DC I–V, C–V and bias related S parameters accurately. Project supported by the National Natural Science Foundation of China (No. 61331006).

  4. Analysis and logical modeling of biological signaling transduction networks

    Science.gov (United States)

    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.

  5. Regulation of Wnt signaling by nociceptive input in animal models

    Directory of Open Access Journals (Sweden)

    Shi Yuqiang

    2012-06-01

    Full Text Available Abstract Background Central sensitization-associated synaptic plasticity in the spinal cord dorsal horn (SCDH critically contributes to the development of chronic pain, but understanding of the underlying molecular pathways is still incomplete. Emerging evidence suggests that Wnt signaling plays a crucial role in regulation of synaptic plasticity. Little is known about the potential function of the Wnt signaling cascades in chronic pain development. Results Fluorescent immunostaining results indicate that β-catenin, an essential protein in the canonical Wnt signaling pathway, is expressed in the superficial layers of the mouse SCDH with enrichment at synapses in lamina II. In addition, Wnt3a, a prototypic Wnt ligand that activates the canonical pathway, is also enriched in the superficial layers. Immunoblotting analysis indicates that both Wnt3a a β-catenin are up-regulated in the SCDH of various mouse pain models created by hind-paw injection of capsaicin, intrathecal (i.t. injection of HIV-gp120 protein or spinal nerve ligation (SNL. Furthermore, Wnt5a, a prototypic Wnt ligand for non-canonical pathways, and its receptor Ror2 are also up-regulated in the SCDH of these models. Conclusion Our results suggest that Wnt signaling pathways are regulated by nociceptive input. The activation of Wnt signaling may regulate the expression of spinal central sensitization during the development of acute and chronic pain.

  6. Modelling and Analysis of Biochemical Signalling Pathway Cross-talk

    Directory of Open Access Journals (Sweden)

    Robin Donaldson

    2010-02-01

    Full Text Available Signalling pathways are abstractions that help life scientists structure the coordination of cellular activity. Cross-talk between pathways accounts for many of the complex behaviours exhibited by signalling pathways and is often critical in producing the correct signal-response relationship. Formal models of signalling pathways and cross-talk in particular can aid understanding and drive experimentation. We define an approach to modelling based on the concept that a pathway is the (synchronising parallel composition of instances of generic modules (with internal and external labels. Pathways are then composed by (synchronising parallel composition and renaming; different types of cross-talk result from different combinations of synchronisation and renaming. We define a number of generic modules in PRISM and five types of cross-talk: signal flow, substrate availability, receptor function, gene expression and intracellular communication. We show that Continuous Stochastic Logic properties can both detect and distinguish the types of cross-talk. The approach is illustrated with small examples and an analysis of the cross-talk between the TGF-b/BMP, WNT and MAPK pathways.

  7. Signalling network construction for modelling plant defence response.

    Directory of Open Access Journals (Sweden)

    Dragana Miljkovic

    Full Text Available 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

  8. Modeling, estimation and optimal filtration in signal processing

    CERN Document Server

    Najim, Mohamed

    2010-01-01

    The purpose of this book is to provide graduate students and practitioners with traditional methods and more recent results for model-based approaches in signal processing.Firstly, discrete-time linear models such as AR, MA and ARMA models, their properties and their limitations are introduced. In addition, sinusoidal models are addressed.Secondly, estimation approaches based on least squares methods and instrumental variable techniques are presented.Finally, the book deals with optimal filters, i.e. Wiener and Kalman filtering, and adaptive filters such as the RLS, the LMS and the

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

    Science.gov (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A.; Farber, R.

    1987-06-01

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

  11. Acoustic/seismic signal propagation and sensor performance modeling

    Science.gov (United States)

    Wilson, D. Keith; Marlin, David H.; Mackay, Sean

    2007-04-01

    Performance, optimal employment, and interpretation of data from acoustic and seismic sensors depend strongly and in complex ways on the environment in which they operate. Software tools for guiding non-expert users of acoustic and seismic sensors are therefore much needed. However, such tools require that many individual components be constructed and correctly connected together. These components include the source signature and directionality, representation of the atmospheric and terrain environment, calculation of the signal propagation, characterization of the sensor response, and mimicking of the data processing at the sensor. Selection of an appropriate signal propagation model is particularly important, as there are significant trade-offs between output fidelity and computation speed. Attenuation of signal energy, random fading, and (for array systems) variations in wavefront angle-of-arrival should all be considered. Characterization of the complex operational environment is often the weak link in sensor modeling: important issues for acoustic and seismic modeling activities include the temporal/spatial resolution of the atmospheric data, knowledge of the surface and subsurface terrain properties, and representation of ambient background noise and vibrations. Design of software tools that address these challenges is illustrated with two examples: a detailed target-to-sensor calculation application called the Sensor Performance Evaluator for Battlefield Environments (SPEBE) and a GIS-embedded approach called Battlefield Terrain Reasoning and Awareness (BTRA).

  12. MOTORCYCLE CRASH PREDICTION MODEL FOR NON-SIGNALIZED INTERSECTIONS

    Directory of Open Access Journals (Sweden)

    S. HARNEN

    2003-01-01

    Full Text Available This paper attempts to develop a prediction model for motorcycle crashes at non-signalized intersections on urban roads in Malaysia. The Generalized Linear Modeling approach was used to develop the model. The final model revealed that an increase in motorcycle and non-motorcycle flows entering an intersection is associated with an increase in motorcycle crashes. Non-motorcycle flow on major road had the greatest effect on the probability of motorcycle crashes. Approach speed, lane width, number of lanes, shoulder width and land use were also found to be significant in explaining motorcycle crashes. The model should assist traffic engineers to decide the need for appropriate intersection treatment that specifically designed for non-exclusive motorcycle lane facilities.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  15. A Segmented Signal Progression Model for the Modern Streetcar System

    Directory of Open Access Journals (Sweden)

    Baojie Wang

    2015-01-01

    Full Text Available This paper is on the purpose of developing a segmented signal progression model for modern streetcar system. The new method is presented with the following features: (1 the control concept is based on the assumption of only one streetcar line operating along an arterial under a constant headway and no bandwidth demand for streetcar system signal progression; (2 the control unit is defined as a coordinated intersection group associated with several streetcar stations, and the control joints must be streetcar stations; (3 the objective function is built to ensure the two-way streetcar arrival times distributing within the available time of streetcar phase; (4 the available time of streetcar phase is determined by timing schemes, intersection structures, track locations, streetcar speeds, and vehicular accelerations; (5 the streetcar running speed is constant separately whether it is in upstream or downstream route; (6 the streetcar dwell time is preset according to historical data distribution or charging demand. The proposed method is experimentally examined in Hexi New City Streetcar Project in Nanjing, China. In the experimental results, the streetcar system operation and the progression impacts are shown to affect transit and vehicular traffic. The proposed model presents promising outcomes through the design of streetcar system segmented signal progression, in terms of ensuring high streetcar system efficiency and minimizing negative impacts on transit and vehicular traffic.

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

    Science.gov (United States)

    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.

  17. Mathematical modeling of gonadotropin-releasing hormone signaling.

    Science.gov (United States)

    Pratap, Amitesh; Garner, Kathryn L; Voliotis, Margaritis; Tsaneva-Atanasova, Krasimira; McArdle, Craig A

    2017-07-05

    Gonadotropin-releasing hormone (GnRH) acts via G-protein coupled receptors on pituitary gonadotropes to control reproduction. These are G q -coupled receptors that mediate acute effects of GnRH on the exocytotic secretion of luteinizing hormone (LH) and follicle-stimulating hormone (FSH), as well as the chronic regulation of their synthesis. GnRH is secreted in short pulses and GnRH effects on its target cells are dependent upon the dynamics of these pulses. Here we overview GnRH receptors and their signaling network, placing emphasis on pulsatile signaling, and how mechanistic mathematical models and an information theoretic approach have helped further this field. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  18. Purkinje Cell Signaling Deficits in Animal Models of Ataxia

    Directory of Open Access Journals (Sweden)

    Eriola Hoxha

    2018-04-01

    Full Text Available Purkinje cell (PC dysfunction or degeneration is the most frequent finding in animal models with ataxic symptoms. Mutations affecting intrinsic membrane properties can lead to ataxia by altering the firing rate of PCs or their firing pattern. However, the relationship between specific firing alterations and motor symptoms is not yet clear, and in some cases PC dysfunction precedes the onset of ataxic signs. Moreover, a great variety of ionic and synaptic mechanisms can affect PC signaling, resulting in different features of motor dysfunction. Mutations affecting Na+ channels (NaV1.1, NaV1.6, NaVβ4, Fgf14 or Rer1 reduce the firing rate of PCs, mainly via an impairment of the Na+ resurgent current. Mutations that reduce Kv3 currents limit the firing rate frequency range. Mutations of Kv1 channels act mainly on inhibitory interneurons, generating excessive GABAergic signaling onto PCs, resulting in episodic ataxia. Kv4.3 mutations are responsible for a complex syndrome with several neurologic dysfunctions including ataxia. Mutations of either Cav or BK channels have similar consequences, consisting in a disruption of the firing pattern of PCs, with loss of precision, leading to ataxia. Another category of pathogenic mechanisms of ataxia regards alterations of synaptic signals arriving at the PC. At the parallel fiber (PF-PC synapse, mutations of glutamate delta-2 (GluD2 or its ligand Crbl1 are responsible for the loss of synaptic contacts, abolishment of long-term depression (LTD and motor deficits. At the same synapse, a correct function of metabotropic glutamate receptor 1 (mGlu1 receptors is necessary to avoid ataxia. Failure of climbing fiber (CF maturation and establishment of PC mono-innervation occurs in a great number of mutant mice, including mGlu1 and its transduction pathway, GluD2, semaphorins and their receptors. All these models have in common the alteration of PC output signals, due to a variety of mechanisms affecting incoming

  19. Skull's acoustic attenuation and dispersion modeling on photoacoustic signal

    Science.gov (United States)

    Mohammadi, Leila; Behnam, Hamid; Tavakkoli, Jahan; Nasiriavanaki, Mohammadreza

    2018-02-01

    Despite the promising results of the recent novel transcranial photoacoustic (PA) brain imaging technology, it has been demonstrated that the presence of the skull severely affects the performance of this imaging modality. We theoretically investigate the effects of acoustic heterogeneity induced by skull on the PA signals generated from single particles, with firstly developing a mathematical model for this phenomenon and then explore experimental validation of the results. The model takes into account the frequency dependent attenuation and dispersion effects occur with wave reflection, refraction and mode conversion at the skull surfaces. Numerical simulations based on the developed model are performed for calculating the propagation of photoacoustic waves through the skull. The results show a strong agreement between simulation and ex-vivo study. The findings are as follow: The thickness of the skull is the most PA signal deteriorating factor that affects both its amplitude (attenuation) and phase (distortion). Also we demonstrated that, when the depth of target region is low and it is comparable to the skull thickness, however, the skull-induced distortion becomes increasingly severe and the reconstructed image would be strongly distorted without correcting these effects. It is anticipated that an accurate quantification and modeling of the skull transmission effects would ultimately allow for aberration correction in transcranial PA brain imaging.

  20. Performance analysis of NOAA tropospheric signal delay model

    International Nuclear Information System (INIS)

    Ibrahim, Hassan E; El-Rabbany, Ahmed

    2011-01-01

    Tropospheric delay is one of the dominant global positioning system (GPS) errors, which degrades the positioning accuracy. Recent development in tropospheric modeling relies on implementation of more accurate numerical weather prediction (NWP) models. In North America one of the NWP-based tropospheric correction models is the NOAA Tropospheric Signal Delay Model (NOAATrop), which was developed by the US National Oceanic and Atmospheric Administration (NOAA). Because of its potential to improve the GPS positioning accuracy, the NOAATrop model became the focus of many researchers. In this paper, we analyzed the performance of the NOAATrop model and examined its effect on ionosphere-free-based precise point positioning (PPP) solution. We generated 3 year long tropospheric zenith total delay (ZTD) data series for the NOAATrop model, Hopfield model, and the International GNSS Services (IGS) final tropospheric correction product, respectively. These data sets were generated at ten IGS reference stations spanning Canada and the United States. We analyzed the NOAATrop ZTD data series and compared them with those of the Hopfield model. The IGS final tropospheric product was used as a reference. The analysis shows that the performance of the NOAATrop model is a function of both season (time of the year) and geographical location. However, its performance was superior to the Hopfield model in all cases. We further investigated the effect of implementing the NOAATrop model on the ionosphere-free-based PPP solution convergence and accuracy. It is shown that the use of the NOAATrop model improved the PPP solution convergence by 1%, 10% and 15% for the latitude, longitude and height components, respectively

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

    Science.gov (United States)

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

    2004-03-01

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

  2. Statistical mechanics of learning orthogonal signals for general covariance models

    International Nuclear Information System (INIS)

    Hoyle, David C

    2010-01-01

    Statistical mechanics techniques have proved to be useful tools in quantifying the accuracy with which signal vectors are extracted from experimental data. However, analysis has previously been limited to specific model forms for the population covariance C, which may be inappropriate for real world data sets. In this paper we obtain new statistical mechanical results for a general population covariance matrix C. For data sets consisting of p sample points in R N we use the replica method to study the accuracy of orthogonal signal vectors estimated from the sample data. In the asymptotic limit of N,p→∞ at fixed α = p/N, we derive analytical results for the signal direction learning curves. In the asymptotic limit the learning curves follow a single universal form, each displaying a retarded learning transition. An explicit formula for the location of the retarded learning transition is obtained and we find marked variation in the location of the retarded learning transition dependent on the distribution of population covariance eigenvalues. The results of the replica analysis are confirmed against simulation

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Gregor Moenke

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

  6. Linear collider signal of anomaly mediated supersymmetry breaking model

    International Nuclear Information System (INIS)

    Ghosh Dilip Kumar; Kundu, Anirban; Roy, Probir; Roy, Sourov

    2001-01-01

    Though the minimal model of anomaly mediated supersymmetry breaking has been significantly constrained by recent experimental and theoretical work, there are still allowed regions of the parameter space for moderate to large values of tan β. We show that these regions will be comprehensively probed in a √s = 1 TeV e + e - linear collider. Diagnostic signals to this end are studied by zeroing in on a unique and distinct feature of a large class of models in this genre: a neutral winolike Lightest Supersymmetric Particle closely degenerate in mass with a winolike chargino. The pair production processes e + e - → e tilde L ± e tilde L ± , e tilde R ± e tilde R ± , e tilde L ± e tilde R ± , ν tilde anti ν tilde, χ tilde 1 0 χ tilde 2 0 , χ tilde 2 0 χ tilde 2 0 are all considered at √s = 1 TeV corresponding to the proposed TESLA linear collider in two natural categories of mass ordering in the sparticle spectra. The signals analysed comprise multiple combinations of fast charged leptons (any of which can act as the trigger) plus displaced vertices X D (any of which can be identified by a heavy ionizing track terminating in the detector) and/or associated soft pions with characteristic momentum distributions. (author)

  7. Mathematical model with autoregressive process for electrocardiogram signals

    Science.gov (United States)

    Evaristo, Ronaldo M.; Batista, Antonio M.; Viana, Ricardo L.; Iarosz, Kelly C.; Szezech, José D., Jr.; Godoy, Moacir F. de

    2018-04-01

    The cardiovascular system is composed of the heart, blood and blood vessels. Regarding the heart, cardiac conditions are determined by the electrocardiogram, that is a noninvasive medical procedure. In this work, we propose autoregressive process in a mathematical model based on coupled differential equations in order to obtain the tachograms and the electrocardiogram signals of young adults with normal heartbeats. Our results are compared with experimental tachogram by means of Poincaré plot and dentrended fluctuation analysis. We verify that the results from the model with autoregressive process show good agreement with experimental measures from tachogram generated by electrical activity of the heartbeat. With the tachogram we build the electrocardiogram by means of coupled differential equations.

  8. Large-Signal DG-MOSFET Modelling for RFID Rectification

    Directory of Open Access Journals (Sweden)

    R. Rodríguez

    2016-01-01

    Full Text Available This paper analyses the undoped DG-MOSFETs capability for the operation of rectifiers for RFIDs and Wireless Power Transmission (WPT at microwave frequencies. For this purpose, a large-signal compact model has been developed and implemented in Verilog-A. The model has been numerically validated with a device simulator (Sentaurus. It is found that the number of stages to achieve the optimal rectifier performance is inferior to that required with conventional MOSFETs. In addition, the DC output voltage could be incremented with the use of appropriate mid-gap metals for the gate, as TiN. Minor impact of short channel effects (SCEs on rectification is also pointed out.

  9. Quantitative Models of Imperfect Deception in Network Security using Signaling Games with Evidence

    OpenAIRE

    Pawlick, Jeffrey; Zhu, Quanyan

    2017-01-01

    Deception plays a critical role in many interactions in communication and network security. Game-theoretic models called "cheap talk signaling games" capture the dynamic and information asymmetric nature of deceptive interactions. But signaling games inherently model undetectable deception. In this paper, we investigate a model of signaling games in which the receiver can detect deception with some probability. This model nests traditional signaling games and complete information Stackelberg ...

  10. Modelling noninvasively measured cerebral signals during a hypoxemia challenge: steps towards individualised modelling.

    Directory of Open Access Journals (Sweden)

    Beth Jelfs

    Full Text Available Noninvasive approaches to measuring cerebral circulation and metabolism are crucial to furthering our understanding of brain function. These approaches also have considerable potential for clinical use "at the bedside". However, a highly nontrivial task and precondition if such methods are to be used routinely is the robust physiological interpretation of the data. In this paper, we explore the ability of a previously developed model of brain circulation and metabolism to explain and predict quantitatively the responses of physiological signals. The five signals all noninvasively-measured during hypoxemia in healthy volunteers include four signals measured using near-infrared spectroscopy along with middle cerebral artery blood flow measured using transcranial Doppler flowmetry. We show that optimising the model using partial data from an individual can increase its predictive power thus aiding the interpretation of NIRS signals in individuals. At the same time such optimisation can also help refine model parametrisation and provide confidence intervals on model parameters. Discrepancies between model and data which persist despite model optimisation are used to flag up important questions concerning the underlying physiology, and the reliability and physiological meaning of the signals.

  11. Channel modeling, signal processing and coding for perpendicular magnetic recording

    Science.gov (United States)

    Wu, Zheng

    With the increasing areal density in magnetic recording systems, perpendicular recording has replaced longitudinal recording to overcome the superparamagnetic limit. Studies on perpendicular recording channels including aspects of channel modeling, signal processing and coding techniques are presented in this dissertation. To optimize a high density perpendicular magnetic recording system, one needs to know the tradeoffs between various components of the system including the read/write transducers, the magnetic medium, and the read channel. We extend the work by Chaichanavong on the parameter optimization for systems via design curves. Different signal processing and coding techniques are studied. Information-theoretic tools are utilized to determine the acceptable region for the channel parameters when optimal detection and linear coding techniques are used. Our results show that a considerable gain can be achieved by the optimal detection and coding techniques. The read-write process in perpendicular magnetic recording channels includes a number of nonlinear effects. Nonlinear transition shift (NLTS) is one of them. The signal distortion induced by NLTS can be reduced by write precompensation during data recording. We numerically evaluate the effect of NLTS on the read-back signal and examine the effectiveness of several write precompensation schemes in combating NLTS in a channel characterized by both transition jitter noise and additive white Gaussian electronics noise. We also present an analytical method to estimate the bit-error-rate and use it to help determine the optimal write precompensation values in multi-level precompensation schemes. We propose a mean-adjusted pattern-dependent noise predictive (PDNP) detection algorithm for use on the channel with NLTS. We show that this detector can offer significant improvements in bit-error-rate (BER) compared to conventional Viterbi and PDNP detectors. Moreover, the system performance can be further improved by

  12. Mathematical modeling and signal processing in speech and hearing sciences

    CERN Document Server

    Xin, Jack

    2014-01-01

    The aim of the book is to give an accessible introduction of mathematical models and signal processing methods in speech and hearing sciences for senior undergraduate and beginning graduate students with basic knowledge of linear algebra, differential equations, numerical analysis, and probability. Speech and hearing sciences are fundamental to numerous technological advances of the digital world in the past decade, from music compression in MP3 to digital hearing aids, from network based voice enabled services to speech interaction with mobile phones. Mathematics and computation are intimately related to these leaps and bounds. On the other hand, speech and hearing are strongly interdisciplinary areas where dissimilar scientific and engineering publications and approaches often coexist and make it difficult for newcomers to enter.

  13. Modeling and processing of laser Doppler reactive hyperaemia signals

    Science.gov (United States)

    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.

  14. Modeling the photoacoustic signal during the porous silicon formation

    Science.gov (United States)

    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.

  15. A signaling model of foreign direct investment attraction

    Directory of Open Access Journals (Sweden)

    Marcelo de C. Griebeler

    2017-09-01

    Full Text Available Foreign direct investors face uncertainty about government's type of the host country. In a two period game, we allow the host country's government to mitigate such uncertainty by sending a signal through fiscal policy. Our main finding states that a populist government may mimic a conservative one in order to attract foreign direct investment (FDI, and this choice depends mainly on its impatience degree and the originally planned FDI stock. We highlight the role of the government's reputation in attracting foreign capital and thus provide some policy implications. Moreover, our model explains why some governments considered to be populist adopt conservative policies in the beginning of its terms of office. Resumo: Investidores estrangeiros diretos são incertos sobre o tipo do governo do país onde desejam investir. Em um jogo de dois períodos, permitimos que o governo de tal país mitigue essa incerteza ao enviar um sinal através da política fiscal. Nosso principal resultado estabelece que um governo populista pode imitar um conservador a fim de atrair investimento estrangeiro direto (IED, e essa escolha depende principalmente do grau de impaciência e do estoque de IED originalmente planejado. Destacamos o papel da reputação do governo em atrair capital externo e assim fornecemos algumas recomendações de política. Além disso, nosso modelo explica porque alguns governos considerados populistas adotam políticas conservadores no início do seus mandatos. JEL classification: F41, F34, C72, Keywords: Signaling, Foreign direct investment, Game theory, Palavras-chave: Sinalização, Investimento estrangeiro direto, Teoria dos jogos

  16. Measures of metacognition on signal-detection theoretic models.

    Science.gov (United States)

    Barrett, Adam B; Dienes, Zoltan; Seth, Anil K

    2013-12-01

    Analyzing metacognition, specifically knowledge of accuracy of internal perceptual, memorial, or other knowledge states, is vital for many strands of psychology, including determining the accuracy of feelings of knowing and discriminating conscious from unconscious cognition. Quantifying metacognitive sensitivity is however more challenging than quantifying basic stimulus sensitivity. Under popular signal-detection theory (SDT) models for stimulus classification tasks, approaches based on Type II receiver-operating characteristic (ROC) curves or Type II d-prime risk confounding metacognition with response biases in either the Type I (classification) or Type II (metacognitive) tasks. A new approach introduces meta-d': The Type I d-prime that would have led to the observed Type II data had the subject used all the Type I information. Here, we (a) further establish the inconsistency of the Type II d-prime and ROC approaches with new explicit analyses of the standard SDT model and (b) analyze, for the first time, the behavior of meta-d' under nontrivial scenarios, such as when metacognitive judgments utilize enhanced or degraded versions of the Type I evidence. Analytically, meta-d' values typically reflect the underlying model well and are stable under changes in decision criteria; however, in relatively extreme cases, meta-d' can become unstable. We explore bias and variance of in-sample measurements of meta-d' and supply MATLAB code for estimation in general cases. Our results support meta-d' as a useful measure of metacognition and provide rigorous methodology for its application. Our recommendations are useful for any researchers interested in assessing metacognitive accuracy. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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

    International Nuclear Information System (INIS)

    Haghpanahi, Masoumeh; Borkholder, David A

    2014-01-01

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

  18. Lung cancer, intracellular signaling pathways, and preclinical models

    International Nuclear Information System (INIS)

    Mordant, P.

    2012-01-01

    Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide. Activation of phosphatidylinositol-3-kinase (PI3K)-AKT and Kirsten rat sarcoma viral oncogene homologue (KRAS) can induce cellular immortalization, proliferation, and resistance to anticancer therapeutics such as epidermal growth factor receptor inhibitors or chemotherapy. This study assessed the consequences of inhibiting these two pathways in tumor cells with activation of KRAS, PI3K-AKT, or both. We investigated whether the combination of a novel RAF/vascular endothelial growth factor receptor inhibitor, RAF265, with a mammalian target of rapamycin (mTOR) inhibitor, RAD001 (everolimus), could lead to enhanced anti-tumoral effects in vitro and in vivo. To address this question, we used cell lines with different status regarding KRAS, PIK3CA, and BRAF mutations, using immunoblotting to evaluate the inhibitors, and MTT and clonogenic assays for effects on cell viability and proliferation. Subcutaneous xenografts were used to assess the activity of the combination in vivo. RAD001 inhibited mTOR downstream signaling in all cell lines, whereas RAF265 inhibited RAF downstream signaling only in BRAF mutant cells. In vitro, addition of RAF265 to RAD001 led to decreased AKT, S6, and Eukaryotic translation initiation factor 4E binding protein 1 phosphorylation in HCT116 cells. In vitro and in vivo, RAD001 addition enhanced the anti-tumoral effect of RAF265 in HCT116 and H460 cells (both KRAS mut, PIK3CA mut); in contrast, the combination of RAF265 and RAD001 yielded no additional activity in A549 and MDAMB231 cells. The combination of RAF and mTOR inhibitors is effective for enhancing anti-tumoral effects in cells with deregulation of both RAS-RAF and PI3K, possibly through the cross-inhibition of 4E binding protein 1 and S6 protein. We then focus on animal models. Preclinical models of NSCLC require better clinical relevance to study disease mechanisms and innovative

  19. A Multi-Model Stereo Similarity Function Based on Monogenic Signal Analysis in Poisson Scale Space

    Directory of Open Access Journals (Sweden)

    Jinjun Li

    2011-01-01

    Full Text Available A stereo similarity function based on local multi-model monogenic image feature descriptors (LMFD is proposed to match interest points and estimate disparity map for stereo images. Local multi-model monogenic image features include local orientation and instantaneous phase of the gray monogenic signal, local color phase of the color monogenic signal, and local mean colors in the multiscale color monogenic signal framework. The gray monogenic signal, which is the extension of analytic signal to gray level image using Dirac operator and Laplace equation, consists of local amplitude, local orientation, and instantaneous phase of 2D image signal. The color monogenic signal is the extension of monogenic signal to color image based on Clifford algebras. The local color phase can be estimated by computing geometric product between the color monogenic signal and a unit reference vector in RGB color space. Experiment results on the synthetic and natural stereo images show the performance of the proposed approach.

  20. EEG Signal Classification With Super-Dirichlet Mixture Model

    DEFF Research Database (Denmark)

    Ma, Zhanyu; Tan, Zheng-Hua; Prasad, Swati

    2012-01-01

    Classification of the Electroencephalogram (EEG) signal is a challengeable task in the brain-computer interface systems. The marginalized discrete wavelet transform (mDWT) coefficients extracted from the EEG signals have been frequently used in researches since they reveal features related...

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

    Science.gov (United States)

    Hausken, Kjell; Hirshleifer, Jack

    2004-06-21

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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

  4. Advanced radar detection schemes under mismatched signal models

    CERN Document Server

    Bandiera, Francesco

    2009-01-01

    Adaptive detection of signals embedded in correlated Gaussian noise has been an active field of research in the last decades. This topic is important in many areas of signal processing such as, just to give some examples, radar, sonar, communications, and hyperspectral imaging. Most of the existing adaptive algorithms have been designed following the lead of the derivation of Kelly's detector which assumes perfect knowledge of the target steering vector. However, in realistic scenarios, mismatches are likely to occur due to both environmental and instrumental factors. When a mismatched signal

  5. Enhancement of speech signals - with a focus on voiced speech models

    DEFF Research Database (Denmark)

    Nørholm, Sidsel Marie

    This thesis deals with speech enhancement, i.e., noise reduction in speech signals. This has applications in, e.g., hearing aids and teleconference systems. We consider a signal-driven approach to speech enhancement where a model of the speech is assumed and filters are generated based...... on this model. The basic model used in this thesis is the harmonic model which is a commonly used model for describing the voiced part of the speech signal. We show that it can be beneficial to extend the model to take inharmonicities or the non-stationarity of speech into account. Extending the model...

  6. Stochastic model for detection of signals in noise

    OpenAIRE

    Klein, Stanley A.; Levi, Dennis M.

    2009-01-01

    Fifty years ago Birdsall, Tanner, and colleagues made rapid progress in developing signal detection theory into a powerful psychophysical tool. One of their major insights was the utility of adding external noise to the signals of interest. These methods have been enhanced in recent years by the addition of multipass and classification-image methods for opening up the black box. There remain a number of as yet unresolved issues. In particular, Birdsall developed a theorem that large amounts o...

  7. Study on non-linear bistable dynamics model based EEG signal discrimination analysis method.

    Science.gov (United States)

    Ying, Xiaoguo; Lin, Han; Hui, Guohua

    2015-01-01

    Electroencephalogram (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations generating from ionic current flows within the neurons of the brain. EEG signal is looked as one of the most important factors that will be focused in the next 20 years. In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed. EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index. Experimental results showed that the proposed method could properly extract the features of different EEG signals.

  8. Evaluation of the autoregression time-series model for analysis of a noisy signal

    International Nuclear Information System (INIS)

    Allen, J.W.

    1977-01-01

    The autoregression (AR) time-series model of a continuous noisy signal was statistically evaluated to determine quantitatively the uncertainties of the model order, the model parameters, and the model's power spectral density (PSD). The result of such a statistical evaluation enables an experimenter to decide whether an AR model can adequately represent a continuous noisy signal and be consistent with the signal's frequency spectrum, and whether it can be used for on-line monitoring. Although evaluations of other types of signals have been reported in the literature, no direct reference has been found to AR model's uncertainties for continuous noisy signals; yet the evaluation is necessary to decide the usefulness of AR models of typical reactor signals (e.g., neutron detector output or thermocouple output) and the potential of AR models for on-line monitoring applications. AR and other time-series models for noisy data representation are being investigated by others since such models require fewer parameters than the traditional PSD model. For this study, the AR model was selected for its simplicity and conduciveness to uncertainty analysis, and controlled laboratory bench signals were used for continuous noisy data. (author)

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Hau-Tieng Wu

    Full Text Available 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.

  11. Modeling evolution of crosstalk in noisy signal transduction networks

    Science.gov (United States)

    Tareen, Ammar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

    2018-02-01

    Signal transduction networks can form highly interconnected systems within cells due to crosstalk between constituent pathways. To better understand the evolutionary design principles underlying such networks, we study the evolution of crosstalk for two parallel signaling pathways that arise via gene duplication. We use a sequence-based evolutionary algorithm and evolve the network based on two physically motivated fitness functions related to information transmission. We find that one fitness function leads to a high degree of crosstalk while the other leads to pathway specificity. Our results offer insights on the relationship between network architecture and information transmission for noisy biomolecular networks.

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

    Science.gov (United States)

    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. A knowledge representation meta-model for rule-based modelling of signalling networks

    Directory of Open Access Journals (Sweden)

    Adrien Basso-Blandin

    2016-03-01

    Full Text Available The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes—at least apparently—inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers—each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.

  14. Modelling and simulation of signal transductions in an apoptosis ...

    Indian Academy of Sciences (India)

    Prakash

    Structural Analysis of Metabolic Networks: Elementary Flux. Mode, Analogy to Petri Nets, and Application to Mycoplasma pneumoniae; German Conference on Bioinformatics 2000 pp 115–120. Takai-Igarashi T and Mizoguchi R 2004 Cell signalling networks ontology; In Silico Biol. 4 81–87. Thompson C 1995 Apoptosis in ...

  15. Modeling the diffusion magnetic resonance imaging signal inside neurons

    International Nuclear Information System (INIS)

    Nguyen, D V; Li, J R; Grebenkov, D S; Le Bihan, D

    2014-01-01

    The Bloch-Torrey partial differential equation (PDE) describes the complex transverse water proton magnetization due to diffusion-encoding magnetic field gradient pulses. The integral of the solution of this PDE yields the diffusion magnetic resonance imaging (dMRI) signal. In a complex medium such as cerebral tissue, it is difficult to explicitly link the dMRI signal to biological parameters such as the cellular geometry or the cellular volume fraction. Studying the dMRI signal arising from a single neuron can provide insight into how the geometrical structure of neurons influences the measured signal. We formulate the Bloch-Torrey PDE inside a single neuron, under no water exchange condition with the extracellular space, and show how to reduce the 3D simulation in the full neuron to a 3D simulation around the soma and 1D simulations in the neurites. We show that this latter approach is computationally much faster than full 3D simulation and still gives accurate results over a wide range of diffusion times

  16. Phonetic perspectives on modelling information in the speech signal

    Indian Academy of Sciences (India)

    Centre for Music and Science, Faculty of Music, University of Cambridge,. Cambridge .... However, to develop systems that can han- .... 1.2a Phonemes are not clearly identifiable in movement or in the acoustic speech signal: As ..... while the speaker role-played the part of a mother at a child's athletics meeting where the.

  17. Model-based design of self-Adapting networked signal processing systems

    NARCIS (Netherlands)

    Oliveira Filho, J.A. de; Papp, Z.; Djapic, R.; Oostveen, J.C.

    2013-01-01

    The paper describes a model based approach for architecture design of runtime reconfigurable, large-scale, networked signal processing applications. A graph based modeling formalism is introduced to describe all relevant aspects of the design (functional, concurrency, hardware, communication,

  18. Microscopic Control Delay Modeling at Signalized Arterials Using Bluetooth Technology

    OpenAIRE

    Rajasekhar, Lakshmi

    2011-01-01

    Real-time control delay estimation is an important performance measure for any intersection to improve the signal timing plans dynamically in real-time and hence improve the overall system performance. Control delay estimates helps to determine the level-of-service (LOS) characteristics of various approaches at an intersection and takes into account deceleration delay, stopped delay and acceleration delay. All kinds of traffic delay calculation especially control delay calculation has always ...

  19. A speed guidance strategy for multiple signalized intersections based on car-following model

    Science.gov (United States)

    Tang, Tie-Qiao; Yi, Zhi-Yan; Zhang, Jian; Wang, Tao; Leng, Jun-Qiang

    2018-04-01

    Signalized intersection has great roles in urban traffic system. The signal infrastructure and the driving behavior near the intersection are paramount factors that have significant impacts on traffic flow and energy consumption. In this paper, a speed guidance strategy is introduced into a car-following model to study the driving behavior and the fuel consumption in a single-lane road with multiple signalized intersections. The numerical results indicate that the proposed model can reduce the fuel consumption and the average stop times. The findings provide insightful guidance for the eco-driving strategies near the signalized intersections.

  20. Modeling and Simulation of Bus Dispatching Policy for Timed Transfers on Signalized Networks

    Science.gov (United States)

    Cho, Hsun-Jung; Lin, Guey-Shii

    2007-12-01

    The major work of this study is to formulate the system cost functions and to integrate the bus dispatching policy with signal control. The integrated model mainly includes the flow dispersion model for links, signal control model for nodes, and dispatching control model for transfer terminals. All such models are inter-related for transfer operations in one-center transit network. The integrated model that combines dispatching policies with flexible signal control modes can be applied to assess the effectiveness of transfer operations. It is found that, if bus arrival information is reliable, an early dispatching decision made at the mean bus arrival times is preferable. The costs for coordinated operations with slack times are relatively low at the optimal common headway when applying adaptive route control. Based on such findings, a threshold function of bus headway for justifying an adaptive signal route control under various time values of auto drivers is developed.

  1. The ontogeny of insulin signaling in the preterm baboon model.

    Science.gov (United States)

    Blanco, Cynthia L; Liang, Hanyu; Joya-Galeana, Joaquin; DeFronzo, Ralph A; McCurnin, Donald; Musi, Nicolas

    2010-05-01

    Hyperglycemia, a prevalent condition in premature infants, is thought to be a consequence of incomplete suppression of endogenous glucose production and reduced insulin-stimulated glucose disposal in peripheral tissues. However, the molecular basis for these conditions remains unclear. To test the hypothesis that the insulin transduction pathway is underdeveloped with prematurity, fetal baboons were delivered, anesthetized, and euthanized at 125 d gestational age (GA), 140 d GA, or near term at 175 d GA. Vastus lateralis muscle and liver tissues were obtained, and protein content of insulin signaling molecules [insulin receptor (IR)-beta, IR substate-1, p85 subunit of phosphatidylinositol 3-kinase, Akt, and AS160] and glucose transporters (GLUT)-1 and GLUT4 was measured by Western blotting. Muscle from 125 d GA baboons had markedly reduced GLUT1 protein content (16% of 140 d GA and 9% of 175 d GA fetuses). GLUT4 and AS160 also were severely reduced in 125 d GA fetal muscle (43% of 175 d GA and 35% of 175 d GA, respectively). In contrast, the protein content of IR-beta, IR substate-1, and Akt was elevated by 1.7-, 5.2-, and 1.9-fold, respectively, in muscle from 125 d GA baboons when compared with 175 d GA fetuses. No differences were found in the content of insulin signaling proteins in liver. In conclusion, significant gestational differences exist in the protein content of several insulin signaling proteins in the muscle of fetal baboons. Reduced muscle content of key glucose transport-regulating proteins (GLUT1, GLUT4, AS160) could play a role in the pathogenesis of neonatal hyperglycemia and reduced insulin-stimulated glucose disposal.

  2. Wideband Small-Signal Input dq Admittance Modeling of Six-Pulse Diode Rectifiers

    DEFF Research Database (Denmark)

    Yue, Xiaolong; Wang, Xiongfei; Blaabjerg, Frede

    2018-01-01

    This paper studies the wideband small-signal input dq admittance of six-pulse diode rectifiers. Considering the frequency coupling introduced by ripple frequency harmonics of d-and q-channel switching function, the proposed model successfully predicts the small-signal input dq admittance of six......-pulse diode rectifiers in high frequency regions that existing models fail to explain. Simulation and experimental results verify the accuracy of the proposed model....

  3. Modeling off-frequency binaural masking for short- and long-duration signals.

    Science.gov (United States)

    Nitschmann, Marc; Yasin, Ifat; Henning, G Bruce; Verhey, Jesko L

    2017-08-01

    Experimental binaural masking-pattern data are presented together with model simulations for 12- and 600-ms signals. The masker was a diotic 11-Hz wide noise centered on 500 Hz. The tonal signal was presented either diotically or dichotically (180° interaural phase difference) with frequencies ranging from 400 to 600 Hz. The results and the modeling agree with previous data and hypotheses; simulations with a binaural model sensitive to monaural modulation cues show that the effect of duration on off-frequency binaural masking-level differences is mainly a result of modulation cues which are only available in the monaural detection of long signals.

  4. A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

    Science.gov (United States)

    Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

    2017-11-01

    Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this

  5. A Signal Detection Model of Compound Decision Tasks

    Science.gov (United States)

    2006-12-01

    strict isolation (for many examples of such models see Egan, 1975; Macmillan & Creelman , 1991). The result has been twofold: A rich corpus of decision...Macmillan & Creelman , 1991). It is important to point out that SDT models are primarily decision models. They specify the rules and procedures for how...Broadbent, 1958; Macmillan & Creelman , 1991; Nolte & Jaarsma, 1967; Swensson & Judy, 1981; Tanner & Norman, 1954). To better understand how these two

  6. Small- and large-signal modeling of InP HBTs in transferred-substrate technology

    DEFF Research Database (Denmark)

    Johansen, Tom Keinicke; Rudolph, Matthias; Jensen, Thomas

    2014-01-01

    In this paper, the small- and large-signal modeling of InP heterojunction bipolar transistors (HBTs) in transferred substrate (TS) technology is investigated. The small-signal equivalent circuit parameters for TS-HBTs in two-terminal and three-terminal configurations are determined by employing...

  7. Model of multicomponent micro-Doppler signal in environment MatLab

    Directory of Open Access Journals (Sweden)

    Kucheryavenko Alexander

    2017-01-01

    Full Text Available The article illustrates the problem of measuring the speed glider component targets in the presence of a turboprop effect of the reflected signal in a pulse-Doppler radar, proposed a model turboprop signal component and an algorithm for its suppression

  8. Unified and Modular Modeling and Functional Verification Framework of Real-Time Image Signal Processors

    Directory of Open Access Journals (Sweden)

    Abhishek Jain

    2016-01-01

    Full Text Available In VLSI industry, image signal processing algorithms are developed and evaluated using software models before implementation of RTL and firmware. After the finalization of the algorithm, software models are used as a golden reference model for the image signal processor (ISP RTL and firmware development. In this paper, we are describing the unified and modular modeling framework of image signal processing algorithms used for different applications such as ISP algorithms development, reference for hardware (HW implementation, reference for firmware (FW implementation, and bit-true certification. The universal verification methodology- (UVM- based functional verification framework of image signal processors using software reference models is described. Further, IP-XACT based tools for automatic generation of functional verification environment files and model map files are described. The proposed framework is developed both with host interface and with core using virtual register interface (VRI approach. This modeling and functional verification framework is used in real-time image signal processing applications including cellphone, smart cameras, and image compression. The main motivation behind this work is to propose the best efficient, reusable, and automated framework for modeling and verification of image signal processor (ISP designs. The proposed framework shows better results and significant improvement is observed in product verification time, verification cost, and quality of the designs.

  9. Modelling discontinuous well log signal to identify lithological ...

    Indian Academy of Sciences (India)

    1Indian School of Mines (ISM), Dhanbad 826 004, India. ... new wavelet transform-based algorithm to model the abrupt discontinuous changes from well log data by taking care of ...... the 11th ACM International Conference on Multimedia,.

  10. Large-Signal Code TESLA: Improvements in the Implementation and in the Model

    National Research Council Canada - National Science Library

    Chernyavskiy, Igor A; Vlasov, Alexander N; Anderson, Jr., Thomas M; Cooke, Simon J; Levush, Baruch; Nguyen, Khanh T

    2006-01-01

    We describe the latest improvements made in the large-signal code TESLA, which include transformation of the code to a Fortran-90/95 version with dynamical memory allocation and extension of the model...

  11. Inequality signals in dorsolateral prefrontal cortex inform social preference models.

    Science.gov (United States)

    Holper, Lisa; Burke, Christopher J; Fausch, Christoph; Seifritz, Erich; Tobler, Philippe N

    2018-05-01

    Humans typically display inequality aversion in social situations, which manifests itself as a preference for fairer distributions of resources. However, people differ in the degree to which they dislike being worse off [disadvantageous inequality (DI) aversion] or better off [advantageous inequality (AI) aversion] than others. Competing models explain such behavior by focusing on aversion to payoff differences, maximization of total payoff or reciprocity. Using functional near-infrared spectroscopy, we asked which of these theories could better explain dorsolateral prefrontal cortex (dlPFC) activity while participants accepted or punished fair vs unfair monetary transfers in an anonymous norm compliance task. We found that while all participants exhibited DI aversion, there were substantial differences in preferences for AI, which were strongly predicted by dlPFC activation. Model comparisons revealed that both punishment behavior and prefrontal activity were best explained by a model that allowed for AI seeking rather than imposing aversion. Moreover, enhancing this model by taking into account behavioral response times, as a proxy for choice difficulty, further improved model fits. Our data provide evidence that the dlPFC encodes subjective values of payoff inequality and that this representation is richer than envisaged by standard models of social preferences.

  12. Validation of Nonlinear Bipolar Transistor Model by Small-Signal Measurements

    DEFF Research Database (Denmark)

    Vidkjær, Jens; Porra, V.; Zhu, J.

    1992-01-01

    A new method for the validity analysis of nonlinear transistor models is presented based on DC-and small-signal S-parameter measurements and realistic consideration of the measurement and de-embedding errors and singularities of the small-signal equivalent circuit. As an example, some analysis...... results for an extended Gummel Poon model are presented in the case of a UHF bipolar power transistor....

  13. Constraint-based modeling and kinetic analysis of the Smad dependent TGF-beta signaling pathway.

    Directory of Open Access Journals (Sweden)

    Zhike Zi

    Full Text Available BACKGROUND: Investigation of dynamics and regulation of the TGF-beta signaling pathway is central to the understanding of complex cellular processes such as growth, apoptosis, and differentiation. In this study, we aim at using systems biology approach to provide dynamic analysis on this pathway. METHODOLOGY/PRINCIPAL FINDINGS: We proposed a constraint-based modeling method to build a comprehensive mathematical model for the Smad dependent TGF-beta signaling pathway by fitting the experimental data and incorporating the qualitative constraints from the experimental analysis. The performance of the model generated by constraint-based modeling method is significantly improved compared to the model obtained by only fitting the quantitative data. The model agrees well with the experimental analysis of TGF-beta pathway, such as the time course of nuclear phosphorylated Smad, the subcellular location of Smad and signal response of Smad phosphorylation to different doses of TGF-beta. CONCLUSIONS/SIGNIFICANCE: The simulation results indicate that the signal response to TGF-beta is regulated by the balance between clathrin dependent endocytosis and non-clathrin mediated endocytosis. This model is useful to be built upon as new precise experimental data are emerging. The constraint-based modeling method can also be applied to quantitative modeling of other signaling pathways.

  14. Electrocardiogram (ECG Signal Modeling and Noise Reduction Using Hopfield Neural Networks

    Directory of Open Access Journals (Sweden)

    F. Bagheri

    2013-02-01

    Full Text Available The Electrocardiogram (ECG signal is one of the diagnosing approaches to detect heart disease. In this study the Hopfield Neural Network (HNN is applied and proposed for ECG signal modeling and noise reduction. The Hopfield Neural Network (HNN is a recurrent neural network that stores the information in a dynamic stable pattern. This algorithm retrieves a pattern stored in memory in response to the presentation of an incomplete or noisy version of that pattern. Computer simulation results show that this method can successfully model the ECG signal and remove high-frequency noise.

  15. Using a 1-D model to reproduce diurnal SST signals

    DEFF Research Database (Denmark)

    Karagali, Ioanna; Høyer, Jacob L.

    2014-01-01

    The diurnal variability of SST has been extensively studied as it poses challenges for validating and calibrating satellite sensors, merging SST time series, oceanic and atmospheric modelling. As heat is significantly trapped close to the surface, the diurnal signal’s maximum amplitude is best...... captured by radiometers. The availability of infra-red retrievals from a geostationary orbit allows the hourly monitoring of the diurnal SST evolution. When infra-red SSTs are validated with in situ measurements a general mismatch is found, associated with the different reference depth of each type...... of measurement. A generally preferred approach to bridge the gap between in situ and remotely obtained measurements is through modelling of the upper ocean temperature. This ESA supported study focuses on the implementation of the 1 dimensional General Ocean Turbulence Model (GOTM), in order to resolve...

  16. Modelling Field Bus Communications in Mixed-Signal Embedded Systems

    Directory of Open Access Journals (Sweden)

    Alassir Mohamad

    2008-01-01

    Full Text Available Abstract We present a modelling platform using the SystemC-AMS language to simulate field bus communications for embedded systems. Our platform includes the model of an I/O controller IP (in this specific case an C controller that interfaces a master microprocessor with its peripherals on the field bus. Our platform shows the execution of the embedded software and its analog response on the lines of the bus. Moreover, it also takes into account the influence of the circuits's I/O by including their IBIS models in the SystemC-AMS description, as well as the bus lines imperfections. Finally, we present simulation results to validate our platform and measure the overhead introduced by SystemC-AMS over a pure digital SystemC simulation.

  17. Modelling Field Bus Communications in Mixed-Signal Embedded Systems

    Directory of Open Access Journals (Sweden)

    Patrick Garda

    2008-08-01

    Full Text Available We present a modelling platform using the SystemC-AMS language to simulate field bus communications for embedded systems. Our platform includes the model of an I/O controller IP (in this specific case an I2C controller that interfaces a master microprocessor with its peripherals on the field bus. Our platform shows the execution of the embedded software and its analog response on the lines of the bus. Moreover, it also takes into account the influence of the circuits's I/O by including their IBIS models in the SystemC-AMS description, as well as the bus lines imperfections. Finally, we present simulation results to validate our platform and measure the overhead introduced by SystemC-AMS over a pure digital SystemC simulation.

  18. Modeling Signal-Noise Processes Supports Student Construction of a Hierarchical Image of Sample

    Science.gov (United States)

    Lehrer, Richard

    2017-01-01

    Grade 6 (modal age 11) students invented and revised models of the variability generated as each measured the perimeter of a table in their classroom. To construct models, students represented variability as a linear composite of true measure (signal) and multiple sources of random error. Students revised models by developing sampling…

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

    NARCIS (Netherlands)

    Selten, M.M.; Meyer, F.; Ba, W.; Valles, A.; Maas, D.A.; Negwer, M.J.; Eijsink, V.D.; Vugt, R.W.M. van; Hulten, J.A; Bakel, N.H.M. van; Roosen, J.; Linden, R.J. van der; Schubert, D.; Verheij, M.M.M.; Nadif Kasri, N.; Martens, G.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

  20. Direct and indirect signals of natural composite Higgs models

    Science.gov (United States)

    Niehoff, Christoph; Stangl, Peter; Straub, David M.

    2016-01-01

    We present a comprehensive numerical analysis of a four-dimensional model with the Higgs as a composite pseudo-Nambu-Goldstone boson that features a calculable Higgs potential and protective custodial and flavour symmetries to reduce electroweak fine-tuning. We employ a novel numerical technique that allows us for the first time to study constraints from radiative electroweak symmetry breaking, Higgs physics, electroweak precision tests, flavour physics, and direct LHC bounds on fermion and vector boson resonances in a single framework. We consider four different flavour symmetries in the composite sector, one of which we show to not be viable anymore in view of strong precision constraints. In the other cases, all constraints can be passed with a sub-percent electroweak fine-tuning. The models can explain the excesses recently observed in WW, WZ, Wh and ℓ + ℓ - resonance searches by ATLAS and CMS and the anomalies in angular observables and branching ratios of rare semi-leptonic B decays observed by LHCb. Solving the B physics anomalies predicts the presence of a dijet or toverline{t} resonance around 1 TeV just below the sensitivity of LHC run 1. We discuss the prospects to probe the models at run 2 of the LHC. As a side product, we identify several gaps in the searches for vector-like quarks at hadron colliders, that could be closed by reanalyzing existing LHC data.

  1. A morphing technique for signal modelling in a multidimensional space of coupling parameters

    CERN Document Server

    The ATLAS collaboration

    2015-01-01

    This note describes a morphing method that produces signal models for fits to data in which both the affected event yields and kinematic distributions are simultaneously taken into account. The signal model is morphed in a continuous manner through the available multi-dimensional parameter space. Searches for deviations from Standard Model predictions for Higgs boson properties have so far used information either from event yields or kinematic distributions. The combined approach described here is expected to substantially enhance the sensitivity to beyond the Standard Model contributions.

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

    Science.gov (United States)

    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

  3. A Dynamic Traffic Signal Timing Model and its Algorithm for Junction of Urban Road

    DEFF Research Database (Denmark)

    Cai, Yanguang; Cai, Hao

    2012-01-01

    As an important part of Intelligent Transportation System, the scientific traffic signal timing of junction can improve the efficiency of urban transport. This paper presents a novel dynamic traffic signal timing model. According to the characteristics of the model, hybrid chaotic quantum...... evolutionary algorithm is employed to solve it. The proposed model has simple structure, and only requires traffic inflow speed and outflow speed are bounded functions with at most finite number of discontinuity points. The condition is very loose and better meets the requirements of the practical real......-time and dynamic signal control of junction. To obtain the optimal solution of the model by hybrid chaotic quantum evolutionary algorithm, the model is converted to an easily solvable form. To simplify calculation, we give the expression of the partial derivative and change rate of the objective function...

  4. Hierarchical Colored Petri Nets for Modeling and Analysis of Transit Signal Priority Control Systems

    Directory of Open Access Journals (Sweden)

    Yisheng An

    2018-01-01

    Full Text Available In this paper, we consider the problem of developing a model for traffic signal control with transit priority using Hierarchical Colored Petri nets (HCPN. Petri nets (PN are useful for state analysis of discrete event systems due to their powerful modeling capability and mathematical formalism. This paper focuses on their use to formalize the transit signal priority (TSP control model. In a four-phase traffic signal control model, the transit detection and two kinds of transit priority strategies are integrated to obtain the HCPN-based TSP control models. One of the advantages to use these models is the clear presentation of traffic light behaviors in terms of conditions and events that cause the detection of a priority request by a transit vehicle. Another advantage of the resulting models is that the correctness and reliability of the proposed strategies are easily analyzed. After their full reachable states are generated, the boundness, liveness, and fairness of the proposed models are verified. Experimental results show that the proposed control model provides transit vehicles with better effectiveness at intersections. This work helps advance the state of the art in the design of signal control models related to the intersection of roadways.

  5. Gap junction modulation by extracellular signaling molecules: the thymus model

    Directory of Open Access Journals (Sweden)

    Alves L.A.

    2000-01-01

    Full Text Available Gap junctions are intercellular channels which connect adjacent cells and allow direct exchange of molecules of low molecular weight between them. Such a communication has been described as fundamental in many systems due to its importance in coordination, proliferation and differentiation. Recently, it has been shown that gap junctional intercellular communication (GJIC can be modulated by several extracellular soluble factors such as classical hormones, neurotransmitters, interleukins, growth factors and some paracrine substances. Herein, we discuss some aspects of the general modulation of GJIC by extracellular messenger molecules and more particularly the regulation of such communication in the thymus gland. Additionally, we discuss recent data concerning the study of different neuropeptides and hormones in the modulation of GJIC in thymic epithelial cells. We also suggest that the thymus may be viewed as a model to study the modulation of gap junction communication by different extracellular messengers involved in non-classical circuits, since this organ is under bidirectional neuroimmunoendocrine control.

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

    Science.gov (United States)

    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.

  7. An Analysis/Synthesis System of Audio Signal with Utilization of an SN Model

    Directory of Open Access Journals (Sweden)

    G. Rozinaj

    2004-12-01

    Full Text Available An SN (sinusoids plus noise model is a spectral model, in which theperiodic components of the sound are represented by sinusoids withtime-varying frequencies, amplitudes and phases. The remainingnon-periodic components are represented by a filtered noise. Thesinusoidal model utilizes physical properties of musical instrumentsand the noise model utilizes the human inability to perceive the exactspectral shape or the phase of stochastic signals. SN modeling can beapplied in a compression, transformation, separation of sounds, etc.The designed system is based on methods used in the SN modeling. Wehave proposed a model that achieves good results in audio perception.Although many systems do not save phases of the sinusoids, they areimportant for better modelling of transients, for the computation ofresidual and last but not least for stereo signals, too. One of thefundamental properties of the proposed system is the ability of thesignal reconstruction not only from the amplitude but from the phasepoint of view, as well.

  8. On stochastic modeling of the modernized global positioning system (GPS) L2C signal

    International Nuclear Information System (INIS)

    Elsobeiey, Mohamed; El-Rabbany, Ahmed

    2010-01-01

    In order to take full advantage of the modernized GPS L2C signal, it is essential that its stochastic characteristics and code bias be rigorously determined. In this paper, long sessions of GPS measurements are used to study the stochastic characteristics of the modernized GPS L2C signal. As a byproduct, the stochastic characteristics of the legacy GPS signals, namely C/A and P2 codes, are also determined, which are used to verify the developed stochastic model of the modernized signal. The differential code biases between P2 and C2, DCB P2-C2 , are also estimated using the Bernese GPS software. It is shown that the developed models improved the precise point positioning (PPP) solution and convergence time

  9. Sequential decoding of intramuscular EMG signals via estimation of a Markov model.

    Science.gov (United States)

    Monsifrot, Jonathan; Le Carpentier, Eric; Aoustin, Yannick; Farina, Dario

    2014-09-01

    This paper addresses the sequential decoding of intramuscular single-channel electromyographic (EMG) signals to extract the activity of individual motor neurons. A hidden Markov model is derived from the physiological generation of the EMG signal. The EMG signal is described as a sum of several action potentials (wavelet) trains, embedded in noise. For each train, the time interval between wavelets is modeled by a process that parameters are linked to the muscular activity. The parameters of this process are estimated sequentially by a Bayes filter, along with the firing instants. The method was tested on some simulated signals and an experimental one, from which the rates of detection and classification of action potentials were above 95% with respect to the reference decomposition. The method works sequentially in time, and is the first to address the problem of intramuscular EMG decomposition online. It has potential applications for man-machine interfacing based on motor neuron activities.

  10. Assessment of the Dominant Path Model and Field Measurements for NLOS DTV Signal Propagation

    Science.gov (United States)

    Adonias, Geoflly L.; Carvalho, Joabson N.

    2018-03-01

    In Brazil, one of the most important telecommunications systems is broadcast television. Such relevance demands an extensive analysis to be performed chasing technical excellence in order to offer a better digital transmission to the user. Therefore, it is mandatory to evaluate the quality and strength of the Digital TV signal, through studies of coverage predictions models, allowing stations to be projected in a way that their respective signals are harmoniously distributed. The purpose of this study is to appraise measurements of digital television signal obtained in the field and to compare them with numerical results from the simulation of the Dominant Path Model. The outcomes indicate possible blocking zones and a low accumulated probability index above the reception threshold, as well as characterise the gain level of the receiving antenna, which would prevent signal blocking.

  11. Analysis and modelization of short-duration windows of seismic signals

    International Nuclear Information System (INIS)

    Berriani, B.; Lacoume, J.L.; Martin, N.; Cliet, C.; Dubesset, M.

    1987-01-01

    The spectral analysis of a seismic arrival is of a great interest, but unfortunately the common Fourier analysis is unserviceable on short-time windows. So, in order to obtain the spectral characteristics of the dominant components of a seismic signal on a short-time interval, the authors study parametric methods. At first, the autoregressive methods are able to localize a small number of non-stationary pure frequencies. But the amplitude determination is impossible with these methods. So, they develop a combination of AR and Capon's methods. In the Capon's method, the amplitude is conserved for a given frequency, at the very time when the contribution of the other frequencies is minimized. Finally, to characterize completely the different pure-frequency dominant components of the signal and to be able to reconstruct the signal and to be able to reconstruct the signal with these elements, the authors need also the phase and the attenuation; for that, they use the Prony's method where the signal is represented by a sum of damped sinusoids. This last method is used to modelize an offset VSP. It is shown that, using four frequencies and their attributes (amplitude, phase, attenuation), it is possible to modelize quasi-exactly the section. When reconstructing the signal, if one (or more) frequency is eliminated, an efficient filtering can be applied. The AR methods, and Prony's in particular, are efficient tools for signal component decomposition and information compression

  12. Discovery of intramolecular signal transduction network based on a new protein dynamics model of energy dissipation.

    Directory of Open Access Journals (Sweden)

    Cheng-Wei Ma

    Full Text Available A novel approach to reveal intramolecular signal transduction network is proposed in this work. To this end, a new algorithm of network construction is developed, which is based on a new protein dynamics model of energy dissipation. A key feature of this approach is that direction information is specified after inferring protein residue-residue interaction network involved in the process of signal transduction. This enables fundamental analysis of the regulation hierarchy and identification of regulation hubs of the signaling network. A well-studied allosteric enzyme, E. coli aspartokinase III, is used as a model system to demonstrate the new method. Comparison with experimental results shows that the new approach is able to predict all the sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. In addition, the signal transduction network shows a clear preference for specific structural regions, secondary structural types and residue conservation. Occurrence of super-hubs in the network indicates that allosteric regulation tends to gather residues with high connection ability to collectively facilitate the signaling process. Furthermore, a new parameter of propagation coefficient is defined to determine the propagation capability of residues within a signal transduction network. In conclusion, the new approach is useful for fundamental understanding of the process of intramolecular signal transduction and thus has significant impact on rational design of novel allosteric proteins.

  13. Recognition of NEMP and LEMP signals based on auto-regression model and artificial neutral network

    International Nuclear Information System (INIS)

    Li Peng; Song Lijun; Han Chao; Zheng Yi; Cao Baofeng; Li Xiaoqiang; Zhang Xueqin; Liang Rui

    2010-01-01

    Auto-regression (AR) model, one power spectrum estimation method of stationary random signals, and artificial neutral network were adopted to recognize nuclear and lightning electromagnetic pulses. Self-correlation function and Burg algorithms were used to acquire the AR model coefficients as eigenvalues, and BP artificial neural network was introduced as the classifier with different numbers of hidden layers and hidden layer nodes. The results show that AR model is effective in those signals, feature extraction, and the Burg algorithm is more effective than the self-correlation function algorithm. (authors)

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

    Directory of Open Access Journals (Sweden)

    Gabriele Scheler

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

  15. Raising Awareness and Signaling Quality to Uninformed Consumers: A Price-Advertising Model

    OpenAIRE

    Hao Zhao

    2000-01-01

    The objective of this paper is to investigate the firm's optimal advertising and pricing strategies when introducing a new product. We extend the existing signaling literature on advertising spending and price by constructing a model in which advertising is used both to raise awareness about the product and to signal its quality. By comparing the complete information game and the incomplete information game, we find that the high-quality firm will reduce advertising spending and increase pric...

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

    OpenAIRE

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

    2014-01-01

    Photoreceptors degenerate in a wide array of hereditary retinal diseases and age-related macular degeneration. There is currently no treatment available for retinal degenerations. While outnumbered roughly 20:1 by rods in the human retina, it is the cones that mediate color vision and visual acuity, and their survival is critical for vision. In this communication, we investigate whether thyroid hormone (TH) signaling affects cone viability in retinal degeneration mouse models. TH signaling is...

  17. How to detect a cuckoo egg : A signal-detection theory model for recognition and learning

    NARCIS (Netherlands)

    Rodriguez-Girones, MA; Lotem, A

    This article presents a model of egg rejection in cases of brood parasitism. The model is developed in three stages in the framework of signal-detection theory. We first assume that the behavior of host females is adapted to the relevant parameters concerning the appearance of the eggs they lay. In

  18. Human circadian phase estimation from signals collected in ambulatory conditions using an autoregressive model

    NARCIS (Netherlands)

    Gil, Enrique A; Aubert, Xavier L; Møst, Els I S; Beersma, Domien G M

    Phase estimation of the human circadian rhythm is a topic that has been explored using various modeling approaches. The current models range from physiological to mathematical, all attempting to estimate the circadian phase from different physiological or behavioral signals. Here, we have focused on

  19. Dynamical patterns of calcium signaling in a functional model of neuron-astrocyte networks

    DEFF Research Database (Denmark)

    Postnov, D.E.; Koreshkov, R.N.; Brazhe, N.A.

    2009-01-01

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

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

    Science.gov (United States)

    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...

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Alexander Mitsos

    Full Text Available 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.

  4. Applying computer modeling to eddy current signal analysis for steam generator and heat exchanger tube inspections

    International Nuclear Information System (INIS)

    Sullivan, S.P.; Cecco, V.S.; Carter, J.R.; Spanner, M.; McElvanney, M.; Krause, T.W.; Tkaczyk, R.

    2000-01-01

    Licensing requirements for eddy current inspections for nuclear steam generators and heat exchangers are becoming increasingly stringent. The traditional industry-standard method of comparing inspection signals with flaw signals from simple in-line calibration standards is proving to be inadequate. A more complete understanding of eddy current and magnetic field interactions with flaws and other anomalies is required for the industry to generate consistently reliable inspections. Computer modeling is a valuable tool in improving the reliability of eddy current signal analysis. Results from computer modeling are helping inspectors to properly discriminate between real flaw signals and false calls, and improving reliability in flaw sizing. This presentation will discuss complementary eddy current computer modeling techniques such as the Finite Element Method (FEM), Volume Integral Method (VIM), Layer Approximation and other analytic methods. Each of these methods have advantages and limitations. An extension of the Layer Approximation to model eddy current probe responses to ferromagnetic materials will also be presented. Finally examples will be discussed demonstrating how some significant eddy current signal analysis problems have been resolved using appropriate electromagnetic computer modeling tools

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

    Directory of Open Access Journals (Sweden)

    Klinke David J

    2009-11-01

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

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

    Science.gov (United States)

    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.

  7. Multiobjective Traffic Signal Control Model for Intersection Based on Dynamic Turning Movements Estimation

    Directory of Open Access Journals (Sweden)

    Pengpeng Jiao

    2014-01-01

    Full Text Available The real-time traffic signal control for intersection requires dynamic turning movements as the basic input data. It is impossible to detect dynamic turning movements directly through current traffic surveillance systems, but dynamic origin-destination (O-D estimation can obtain it. However, the combined models of dynamic O-D estimation and real-time traffic signal control are rare in the literature. A framework for the multiobjective traffic signal control model for intersection based on dynamic O-D estimation (MSC-DODE is presented. A state-space model using Kalman filtering is first formulated to estimate the dynamic turning movements; then a revised sequential Kalman filtering algorithm is designed to solve the model, and the root mean square error and mean percentage error are used to evaluate the accuracy of estimated dynamic turning proportions. Furthermore, a multiobjective traffic signal control model is put forward to achieve real-time signal control parameters and evaluation indices. Finally, based on practical survey data, the evaluation indices from MSC-DODE are compared with those from Webster method. The actual and estimated turning movements are further input into MSC-DODE, respectively, and results are also compared. Case studies show that results of MSC-DODE are better than those of Webster method and are very close to unavailable actual values.

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

    Science.gov (United States)

    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.

  9. Development of a Modified Kernel Regression Model for a Robust Signal Reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Ahmed, Ibrahim; Heo, Gyunyoung [Kyung Hee University, Yongin (Korea, Republic of)

    2016-10-15

    The demand for robust and resilient performance has led to the use of online-monitoring techniques to monitor the process parameters and signal validation. On-line monitoring and signal validation techniques are the two important terminologies in process and equipment monitoring. These techniques are automated methods of monitoring instrument performance while the plant is operating. To implementing these techniques, several empirical models are used. One of these models is nonparametric regression model, otherwise known as kernel regression (KR). Unlike parametric models, KR is an algorithmic estimation procedure which assumes no significant parameters, and it needs no training process after its development when new observations are prepared; which is good for a system characteristic of changing due to ageing phenomenon. Although KR is used and performed excellently when applied to steady state or normal operating data, it has limitation in time-varying data that has several repetition of the same signal, especially if those signals are used to infer the other signals. The convectional KR has limitation in correctly estimating the dependent variable when time-varying data with repeated values are used to estimate the dependent variable especially in signal validation and monitoring. Therefore, we presented here in this work a modified KR that can resolve this issue which can also be feasible in time domain. Data are first transformed prior to the Euclidian distance evaluation considering their slopes/changes with respect to time. The performance of the developed model is evaluated and compared with that of conventional KR using both the lab experimental data and the real time data from CNS provided by KAERI. The result shows that the proposed developed model, having demonstrated high performance accuracy than that of conventional KR, is capable of resolving the identified limitation with convectional KR. We also discovered that there is still need to further

  10. Blind Separation of Acoustic Signals Combining SIMO-Model-Based Independent Component Analysis and Binary Masking

    Directory of Open Access Journals (Sweden)

    Hiekata Takashi

    2006-01-01

    Full Text Available A new two-stage blind source separation (BSS method for convolutive mixtures of speech is proposed, in which a single-input multiple-output (SIMO-model-based independent component analysis (ICA and a new SIMO-model-based binary masking are combined. SIMO-model-based ICA enables us to separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources in their original form at the microphones. Thus, the separated signals of SIMO-model-based ICA can maintain the spatial qualities of each sound source. Owing to this attractive property, our novel SIMO-model-based binary masking can be applied to efficiently remove the residual interference components after SIMO-model-based ICA. The experimental results reveal that the separation performance can be considerably improved by the proposed method compared with that achieved by conventional BSS methods. In addition, the real-time implementation of the proposed BSS is illustrated.

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

    Science.gov (United States)

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

    2015-05-01

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

  12. Modeling the frequency of opposing left-turn conflicts at signalized intersections using generalized linear regression models.

    Science.gov (United States)

    Zhang, Xin; Liu, Pan; Chen, Yuguang; Bai, Lu; Wang, Wei

    2014-01-01

    The primary objective of this study was to identify whether the frequency of traffic conflicts at signalized intersections can be modeled. The opposing left-turn conflicts were selected for the development of conflict predictive models. Using data collected at 30 approaches at 20 signalized intersections, the underlying distributions of the conflicts under different traffic conditions were examined. Different conflict-predictive models were developed to relate the frequency of opposing left-turn conflicts to various explanatory variables. The models considered include a linear regression model, a negative binomial model, and separate models developed for four traffic scenarios. The prediction performance of different models was compared. The frequency of traffic conflicts follows a negative binominal distribution. The linear regression model is not appropriate for the conflict frequency data. In addition, drivers behaved differently under different traffic conditions. Accordingly, the effects of conflicting traffic volumes on conflict frequency vary across different traffic conditions. The occurrences of traffic conflicts at signalized intersections can be modeled using generalized linear regression models. The use of conflict predictive models has potential to expand the uses of surrogate safety measures in safety estimation and evaluation.

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

    Directory of Open Access Journals (Sweden)

    Kohei Sasaki

    2012-01-01

    Full Text Available 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.

  14. Applied to neuro-fuzzy models for signal validation in Angra 1 nuclear power plant

    International Nuclear Information System (INIS)

    Oliveira, Mauro Vitor de

    1999-06-01

    This work develops two models of signal validation in which the analytical redundancy of the monitored signals from an industrial plant is made by neural networks. In one model the analytical redundancy is made by only one neural network while in the other it is done by several neural networks, each one working in a specific part of the entire operation region of the plant. Four cluster techniques were tested to separate the entire region of operation in several specific regions. An additional information of systems' reliability is supplied by a fuzzy inference system. The models were implemented in C language and tested with signals acquired from Angra I nuclear power plant, from its start to 100% of power. (author)

  15. Models of signal validation using artificial intelligence techniques applied to a nuclear reactor

    International Nuclear Information System (INIS)

    Oliveira, Mauro V.; Schirru, Roberto

    2000-01-01

    This work presents two models of signal validation in which the analytical redundancy of the monitored signals from a nuclear plant is made by neural networks. In one model the analytical redundancy is made by only one neural network while in the other it is done by several neural networks, each one working in a specific part of the entire operation region of the plant. Four cluster techniques were tested to separate the entire operation region in several specific regions. An additional information of systems' reliability is supplied by a fuzzy inference system. The models were implemented in C language and tested with signals acquired from Angra I nuclear power plant, from its start to 100% of power. (author)

  16. Mathematical modeling of sustainable synaptogenesis by repetitive stimuli suggests signaling mechanisms in vivo.

    Directory of Open Access Journals (Sweden)

    Hiromu Takizawa

    Full Text Available The mechanisms of long-term synaptic maintenance are a key component to understanding the mechanism of long-term memory. From biological experiments, a hypothesis arose that repetitive stimuli with appropriate intervals are essential to maintain new synapses for periods of longer than a few days. We successfully reproduce the time-course of relative numbers of synapses with our mathematical model in the same conditions as biological experiments, which used Adenosine-3', 5'-cyclic monophosphorothioate, Sp-isomer (Sp-cAMPS as external stimuli. We also reproduce synaptic maintenance responsiveness to intervals of Sp-cAMPS treatment accompanied by PKA activation. The model suggests a possible mechanism of sustainable synaptogenesis which consists of two steps. First, the signal transduction from an external stimulus triggers the synthesis of a new signaling protein. Second, the new signaling protein is required for the next signal transduction with the same stimuli. As a result, the network component is modified from the first network, and a different signal is transferred which triggers the synthesis of another new signaling molecule. We refer to this hypothetical mechanism as network succession. We build our model on the basis of two hypotheses: (1 a multi-step network succession induces downregulation of SSH and COFILIN gene expression, which triggers the production of stable F-actin; (2 the formation of a complex of stable F-actin with Drebrin at PSD is the critical mechanism to achieve long-term synaptic maintenance. Our simulation shows that a three-step network succession is sufficient to reproduce sustainable synapses for a period longer than 14 days. When we change the network structure to a single step network, the model fails to follow the exact condition of repetitive signals to reproduce a sufficient number of synapses. Another advantage of the three-step network succession is that this system indicates a greater tolerance of parameter

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

    Science.gov (United States)

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

    2015-01-01

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

  18. Numerical modelling of the pump-to-signal relative intensity noise ...

    Indian Academy of Sciences (India)

    An accurate numerical model to investigate the pump-to-signal relative intensity noise (RIN) transfer in two-pump fibre optical parametric amplifiers (2-P FOPAs) for low modulation frequencies is presented. Compared to other models in the field, this model takes into account the fibre loss, pump depletion as well as the gain ...

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

    Directory of Open Access Journals (Sweden)

    Takashi eTateno

    2013-11-01

    Full Text Available 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.

  20. Underwater Cylindrical Object Detection Using the Spectral Features of Active Sonar Signals with Logistic Regression Models

    Directory of Open Access Journals (Sweden)

    Yoojeong Seo

    2018-01-01

    Full Text Available The issue of detecting objects bottoming on the sea floor is significant in various fields including civilian and military areas. The objective of this study is to investigate the logistic regression model to discriminate the target from the clutter and to verify the possibility of applying the model trained by the simulated data generated by the mathematical model to the real experimental data because it is not easy to obtain sufficient data in the underwater field. In the first stage of this study, when the clutter signal energy is so strong that the detection of a target is difficult, the logistic regression model is employed to distinguish the strong clutter signal and the target signal. Previous studies have found that if the clutter energy is larger, false detection occurs even for the various existing detection schemes. For this reason, the discrete Fourier transform (DFT magnitude spectrum of acoustic signals received by active sonar is applied to train the model to distinguish whether the received signal contains a target signal or not. The goodness of fit of the model is verified in terms of receiver operation characteristic (ROC, area under ROC curve (AUC, and classification table. The detection performance of the proposed model is evaluated in terms of detection rate according to target to clutter ratio (TCR. Furthermore, the real experimental data are employed to test the proposed approach. When using the experimental data to test the model, the logistic regression model is trained by the simulated data that are generated based on the mathematical model for the backscattering of the cylindrical object. The mathematical model is developed according to the size of the cylinder used in the experiment. Since the information on the experimental environment including the sound speed, the sediment type and such is not available, once simulated data are generated under various conditions, valid simulated data are selected using 70% of the

  1. Modeling oscillatory control in NF-¿B, p53 and Wnt signaling

    DEFF Research Database (Denmark)

    Mengel, Benedicte; Hunziker, Alexander; Pedersen, Lykke

    2010-01-01

    Oscillations are commonly observed in cellular behavior and span a wide range of timescales, from seconds in calcium signaling to 24 hours in circadian rhythms. In between lie oscillations with time periods of 1-5 hours seen in NF-¿B, p53 and Wnt signaling, which play key roles in the immune system......, cell growth/death and embryo development, respectively. In the first part of this article, we provide a brief overview of simple deterministic models of oscillations. In particular, we explain the mechanism of saturated degradation that has been used to model oscillations in the NF-¿B, p53 and Wnt...

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Lorenza A D'Alessandro

    2015-04-01

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

  4. Wavelet modeling of signals for non-destructive testing of concretes

    International Nuclear Information System (INIS)

    Shao, Zhixue; Shi, Lihua; Cai, Jian

    2011-01-01

    In a non-destructive test of concrete structures, ultrasonic pulses are commonly used to detect damage or embedded objects from their reflections. A wavelet modeling method is proposed here to identify the main reflections and to remove the interferences in the detected ultrasonic waves. This method assumes that if the structure is stimulated by a wavelet function with good time–frequency localization ability, the detected signal is a combination of time-delayed and amplitude-attenuated wavelets. Therefore, modeling of the detected signal by wavelets can give a straightforward and simple model of the original signal. The central time and amplitude of each wavelet represent the position and amplitude of the reflections in the detected structure. A signal processing method is also proposed to estimate the structure response to wavelet excitation from its response to a high-voltage pulse with a sharp leading edge. A signal generation card with a compact peripheral component interconnect extension for instrumentation interface is designed to produce this high-voltage pulse. The proposed method is applied to synthesized aperture focusing technology of concrete specimens and the image results are provided

  5. Making Faces - State-Space Models Applied to Multi-Modal Signal Processing

    DEFF Research Database (Denmark)

    Lehn-Schiøler, Tue

    2005-01-01

    The two main focus areas of this thesis are State-Space Models and multi modal signal processing. The general State-Space Model is investigated and an addition to the class of sequential sampling methods is proposed. This new algorithm is denoted as the Parzen Particle Filter. Furthermore...... optimizer can be applied to speed up convergence. The linear version of the State-Space Model, the Kalman Filter, is applied to multi modal signal processing. It is demonstrated how a State-Space Model can be used to map from speech to lip movements. Besides the State-Space Model and the multi modal...... application an information theoretic vector quantizer is also proposed. Based on interactions between particles, it is shown how a quantizing scheme based on an analytic cost function can be derived....

  6. PATHLOGIC-S: a scalable Boolean framework for modelling cellular signalling.

    Directory of Open Access Journals (Sweden)

    Liam G Fearnley

    Full Text Available 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.

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

    Directory of Open Access Journals (Sweden)

    Jameson Miller

    2010-05-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

  9. Detection of GNSS Signals Propagation in Urban Canyos Using 3D City Models

    Directory of Open Access Journals (Sweden)

    Petra Pisova

    2015-01-01

    Full Text Available This paper presents one of the solutions to the problem of multipath propagation and effects on Global Navigation Satellite Systems (GNSS signals in urban canyons. GNSS signals may reach a receiver not only through Line-of-Sight (LOS paths, but they are often blocked, reflected or diffracted from tall buildings, leading to unmodelled GNSS errors in position estimation. Therefore in order to detect and mitigate the impact of multipath, a new ray-tracing model for simulation of GNSS signals reception in urban canyons is proposed - based on digital 3D maps information, known positions of GNSS satellites and an assumed position of a receiver. The model is established and validated using experimental, as well as real data. It is specially designed for complex environments and situations where positioning with highest accuracy is required - a typical example is navigation for blind people.

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

    Directory of Open Access Journals (Sweden)

    Wei He

    Full Text Available 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.

  11. Long term atmospheric radioxenon measurements and iodine-131 detections over Europe in 2011 and 2012; Langzeitmessungen von Radioxenon in der Atmosphaere und Jod-131 Nachweis in Europa in 2011 und 2012

    Energy Technology Data Exchange (ETDEWEB)

    Schlosser, C.; Bieringer, J.; Krais, R.; Konrad, M.; Kumberg, T.; Schmid, S. [Bundesamt fuer Strahlenschutz, Freiburg (Germany); Ross, J.O. [Bundesanstalt fuer Geowissenschaften und Rohstoffe, Hannover (Germany)

    2014-01-20

    The German Federal Office for Radiation Protection (Bundesamt fuer Strahlenschutz, BfS) continuously monitors the activity concentration of {sup 133}Xe in ground level air in Germany since 1976. Since 2004, Xenon is measured at Schauinsland in samples with 24 hours sampling time with the automated system SPALAX as part of the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Furthermore the BfS operates two high air volume samplers, one in Freiburg and one at the monitoring station Schauinsland. The surveillance of radioactive traces in the atmosphere is part of the German monitoring program of the Integrated Measurement and Information System (IMIS). The available data set allow the study of trends over long time periods and therefore the influence of different sources. Possible sources and their contribution could be investigated by the methods of Atmospheric Transport Modelling (ATM). Beside radioactive xenon isotopes also the medical isotope {sup 131}I is released in traces into the atmosphere and the detection at single trace analysis stations is not exceptional. However, in autumn 2011 and spring 2012 traces of this radioisotope were detected over longer periods over Europe. These events clearly showed the importance of a fast, transboundary and comprehensive data exchange between institutions to identify and localize the source.

  12. Quantification, modelling and design for signal history dependent effects in mixed-signal SOI/SOS circuits

    International Nuclear Information System (INIS)

    Edwards, C.F.; Redman-White, W.; Bracey, M.; Tenbroek, B.M.; Lee, M.S.; Uren, M.J.; Brunson, K.M.

    1999-01-01

    This paper deals with how the radiation hardness of mixed signal SOI/SOS CMOS circuits is taken into account at both architectural terms as well as the the transistor level cell designs. The primary issue is to deal with divergent transistor threshold shifts, and to understand the effects of large amplitude non stationary signals on analogue cell behaviour. (authors)

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

    Science.gov (United States)

    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. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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

    Energy Technology Data Exchange (ETDEWEB)

    Candy, J. V. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Lentz, Erik W.; Rosenberg, Leslie J. [Physics Department, University of Washington, Seattle, WA 98195-1580 (United States); Quinn, Thomas R.; Tremmel, Michael J., E-mail: lentze@phys.washington.edu, E-mail: ljrosenberg@phys.washington.edu, E-mail: trq@astro.washington.edu, E-mail: mjt29@astro.washington.edu [Astronomy Department, University of Washington, Seattle, WA 98195-1580 (United States)

    2017-08-20

    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.

  16. A model for generating Surface EMG signal of m. Tibialis Anterior.

    Science.gov (United States)

    Siddiqi, Ariba; Kumar, Dinesh; Arjunan, Sridhar P

    2014-01-01

    A model that simulates surface electromyogram (sEMG) signal of m. Tibialis Anterior has been developed and tested. This has a firing rate equation that is based on experimental findings. It also has a recruitment threshold that is based on observed statistical distribution. Importantly, it has considered both, slow and fast type which has been distinguished based on their conduction velocity. This model has assumed that the deeper unipennate half of the muscle does not contribute significantly to the potential induced on the surface of the muscle and has approximated the muscle to have parallel structure. The model was validated by comparing the simulated and the experimental sEMG signal recordings. Experiments were conducted on eight subjects who performed isometric dorsiflexion at 10, 20, 30, 50, 75, and 100% maximal voluntary contraction. Normalized root mean square and median frequency of the experimental and simulated EMG signal were computed and the slopes of the linearity with the force were statistically analyzed. The gradients were found to be similar (p>0.05) for both experimental and simulated sEMG signal, validating the proposed model.

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

    Directory of Open Access Journals (Sweden)

    Franziska Altmüller

    2017-03-01

    Full Text Available 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

  18. Progesterone receptors (PR) mediate STAT actions: PR and prolactin receptor signaling crosstalk in breast cancer models.

    Science.gov (United States)

    Leehy, Katherine A; Truong, Thu H; Mauro, Laura J; Lange, Carol A

    2018-02-01

    Estrogen is the major mitogenic stimulus of mammary gland development during puberty wherein ER signaling acts to induce abundant PR expression. PR signaling, in contrast, is the primary driver of mammary epithelial cell proliferation in adulthood. The high circulating levels of progesterone during pregnancy signal through PR, inducing expression of the prolactin receptor (PRLR). Cooperation between PR and prolactin (PRL) signaling, via regulation of downstream components in the PRL signaling pathway including JAKs and STATs, facilitates the alveolar morphogenesis observed during pregnancy. Indeed, these pathways are fully integrated via activation of shared signaling pathways (i.e. JAKs, MAPKs) as well as by the convergence of PRs and STATs at target genes relevant to both mammary gland biology and breast cancer progression (i.e. proliferation, stem cell outgrowth, tissue cell type heterogeneity). Thus, rather than a single mediator such as ER, transcription factor cascades (ER>PR>STATs) are responsible for rapid proliferative and developmental programming in the normal mammary gland. It is not surprising that these same mediators typify uncontrolled proliferation in a majority of breast cancers, where ER and PR are most often co-expressed and may cooperate to drive malignant tumor progression. This review will primarily focus on the integration of PR and PRL signaling in breast cancer models and the importance of this cross-talk in cancer progression in the context of mammographic density. Components of these PR/PRL signaling pathways could offer alternative drug targets and logical complements to anti-ER or anti-estrogen-based endocrine therapies. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    Matsubara, Takamitsu; Morimoto, Jun

    2013-08-01

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

  20. HSP v2: Haptic Signal Processing with Extensions for Physical Modeling

    DEFF Research Database (Denmark)

    Overholt, Daniel; Kontogeorgakopoulos, Alexandros; Berdahl, Edgar

    2010-01-01

    The Haptic Signal Processing (HSP) platform aims to enable musicians to easily design and perform with digital haptic musical instruments [1]. In this paper, we present some new objects introduced in version v2 for modeling of musical dynamical systems such as resonators and vibrating strings. To....... To our knowledge, this is the first time that these diverse physical modeling elements have all been made available for a modular, real-time haptics platform....

  1. MATHEMATICAL MODELING OF THE UNPUT DEVICES IN AUTOMATIC LOCOMOTIVE SIGNALING SYSTEM

    Directory of Open Access Journals (Sweden)

    O. O. Gololobova

    2014-03-01

    Full Text Available Purpose. To examine the operation of the automatic locomotive signaling system (ALS, to find out the influence of external factors on the devices operation and the quality of the code information derived from track circuit information, as well as to enable modeling of failure occurrences that may appear during operation. Methodology. To achieve this purpose, the main obstacles in ALS operation and the reasons for their occurrence were considered and the system structure principle was researched. The mathematical model for input equipment of the continuous automatic locomotive signaling system (ALS with the number coding was developed. It was designed taking into account all the types of code signals “R”, “Y”, “RY” and equivalent scheme of replacing the filter with a frequency of 50 Hz. Findings. The operation of ALSN with a signal current frequency of 50 Hz was examined. The adequate mathematical model of input equipment of ALS with a frequency of 50 Hz was developed. Originality. The computer model of input equipment of ALS system in the environment of MATLAB+Simulink was developed. The results of the computer modeling on the outlet of the filter during delivering every type of code combination were given in the article. Practical value. With the use of developed mathematical model of ALS system operation we have an opportunity to study, research and determine behavior of the circuit during the normal operation mode and failure occurrences. Also there is a possibility to develop and apply different scheme decisions in modeling environment MATLAB+Simulink for reducing the influence of obstacles on the functional capability of ALS and to model the occurrence of possible difficulties.

  2. A signal detection-item response theory model for evaluating neuropsychological measures.

    Science.gov (United States)

    Thomas, Michael L; Brown, Gregory G; Gur, Ruben C; Moore, Tyler M; Patt, Virginie M; Risbrough, Victoria B; Baker, Dewleen G

    2018-02-05

    Models from signal detection theory are commonly used to score neuropsychological test data, especially tests of recognition memory. Here we show that certain item response theory models can be formulated as signal detection theory models, thus linking two complementary but distinct methodologies. We then use the approach to evaluate the validity (construct representation) of commonly used research measures, demonstrate the impact of conditional error on neuropsychological outcomes, and evaluate measurement bias. Signal detection-item response theory (SD-IRT) models were fitted to recognition memory data for words, faces, and objects. The sample consisted of U.S. Infantry Marines and Navy Corpsmen participating in the Marine Resiliency Study. Data comprised item responses to the Penn Face Memory Test (PFMT; N = 1,338), Penn Word Memory Test (PWMT; N = 1,331), and Visual Object Learning Test (VOLT; N = 1,249), and self-report of past head injury with loss of consciousness. SD-IRT models adequately fitted recognition memory item data across all modalities. Error varied systematically with ability estimates, and distributions of residuals from the regression of memory discrimination onto self-report of past head injury were positively skewed towards regions of larger measurement error. Analyses of differential item functioning revealed little evidence of systematic bias by level of education. SD-IRT models benefit from the measurement rigor of item response theory-which permits the modeling of item difficulty and examinee ability-and from signal detection theory-which provides an interpretive framework encompassing the experimentally validated constructs of memory discrimination and response bias. We used this approach to validate the construct representation of commonly used research measures and to demonstrate how nonoptimized item parameters can lead to erroneous conclusions when interpreting neuropsychological test data. Future work might include the

  3. Model developments for quantitative estimates of the benefits of the signals on nuclear power plant availability and economics

    International Nuclear Information System (INIS)

    Seong, Poong Hyun

    1993-01-01

    A novel framework for quantitative estimates of the benefits of signals on nuclear power plant availability and economics has been developed in this work. The models developed in this work quantify how the perfect signals affect the human operator's success in restoring the power plant to the desired state when it enters undesirable transients. Also, the models quantify the economic benefits of these perfect signals. The models have been applied to the condensate feedwater system of the nuclear power plant for demonstration. (Author)

  4. IFN signaling: how a non-canonical model led to the development of IFN mimetics

    Directory of Open Access Journals (Sweden)

    Howard M Johnson

    2013-07-01

    Full Text Available The classical model of cytokine signaling dominates our view of specific gene activation by cytokines such as the interferons (IFNs. The importance of the model extends beyond cytokines and applies to hormones such as growth hormone (GH and insulin, and growth factors such as epidermal growth factor (EGF and fibroblast growth factor (FGF. According to this model, ligand activates the cell via interaction with the extracellular domain of the receptor. This results in activation of receptor or receptor-associated tyrosine kinases, primarily of the Janus kinase (JAK family, phosphorylation and dimerization of the STAT transcription factors, which dissociate from the receptor cytoplasmic domain and translocate to the nucleus. This view ascribes no further role to the ligand, JAK kinase, or receptor in either specific gene activation or the associated epigenetic events. The presence of dimeric STATs in the nucleus essentially explains it all. Our studies have resulted in the development of a non-canonical, more complex model of IFNγ signaling that is akin to that of steroid hormone/steroid receptor signaling. We have shown that ligand, receptor, activated JAKs and STATs are associated with specific gene activation, where the receptor subunit IFNGR1 functions as a co-transcription factor and the JAKs are involved in associated epigenetic events. We found that the type I IFN system functions similarly. The fact that GH receptor, insulin receptor, EGF receptor, and FGF receptor undergo nuclear translocation upon ligand binding suggests that they may also function similarly. The steroid hormone/steroid receptor nature of type I and II IFN signaling provides insight into the specificity of signaling by members of cytokine families. The non-canonical model could also provide better understanding to more complex cytokine families such as those of IL-2 and IL-12, whose members often use the same JAKs and STATs, but also have different functions and

  5. The reduced kinome of Ostreococcus tauri: core eukaryotic signalling components in a tractable model species.

    Science.gov (United States)

    Hindle, Matthew M; Martin, Sarah F; Noordally, Zeenat B; van Ooijen, Gerben; Barrios-Llerena, Martin E; Simpson, T Ian; Le Bihan, Thierry; Millar, Andrew J

    2014-08-02

    The current knowledge of eukaryote signalling originates from phenotypically diverse organisms. There is a pressing need to identify conserved signalling components among eukaryotes, which will lead to the transfer of knowledge across kingdoms. Two useful properties of a eukaryote model for signalling are (1) reduced signalling complexity, and (2) conservation of signalling components. The alga Ostreococcus tauri is described as the smallest free-living eukaryote. With less than 8,000 genes, it represents a highly constrained genomic palette. Our survey revealed 133 protein kinases and 34 protein phosphatases (1.7% and 0.4% of the proteome). We conducted phosphoproteomic experiments and constructed domain structures and phylogenies for the catalytic protein-kinases. For each of the major kinases families we review the completeness and divergence of O. tauri representatives in comparison to the well-studied kinomes of the laboratory models Arabidopsis thaliana and Saccharomyces cerevisiae, and of Homo sapiens. Many kinase clades in O. tauri were reduced to a single member, in preference to the loss of family diversity, whereas TKL and ABC1 clades were expanded. We also identified kinases that have been lost in A. thaliana but retained in O. tauri. For three, contrasting eukaryotic pathways - TOR, MAPK, and the circadian clock - we established the subset of conserved components and demonstrate conserved sites of substrate phosphorylation and kinase motifs. We conclude that O. tauri satisfies our two central requirements. Several of its kinases are more closely related to H. sapiens orthologs than S. cerevisiae is to H. sapiens. The greatly reduced kinome of O. tauri is therefore a suitable model for signalling in free-living eukaryotes.

  6. Large Signal Model of a Four-quadrant AC to DC Converter for Accelerator Magnets

    CERN Document Server

    De la Calle, R; Rinaldi, L; Völker, F V

    2001-01-01

    This paper presents the large signal model of a four-quadrant AC to DC converter, which is expected to be used in the area of particle accelerators. The system’s first stage is composed of a three-phase boost PWM (Pulse Width Modulated) rectifier with DSP (Digital Signal Processing) based power factor correction (PFC) and output voltage regulation. The second stage is a full-bridge PWM inverter that allows fast four-quadrant operation. The structure is fully reversible, and an additional resistance (brake chopper) is not needed to dissipate the energy when the beam deflection magnet acts as generator.

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

    Science.gov (United States)

    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.

  8. A novel wavelet sequence based on deep bidirectional LSTM network model for ECG signal classification.

    Science.gov (United States)

    Yildirim, Özal

    2018-05-01

    Long-short term memory networks (LSTMs), which have recently emerged in sequential data analysis, are the most widely used type of recurrent neural networks (RNNs) architecture. Progress on the topic of deep learning includes successful adaptations of deep versions of these architectures. In this study, a new model for deep bidirectional LSTM network-based wavelet sequences called DBLSTM-WS was proposed for classifying electrocardiogram (ECG) signals. For this purpose, a new wavelet-based layer is implemented to generate ECG signal sequences. The ECG signals were decomposed into frequency sub-bands at different scales in this layer. These sub-bands are used as sequences for the input of LSTM networks. New network models that include unidirectional (ULSTM) and bidirectional (BLSTM) structures are designed for performance comparisons. Experimental studies have been performed for five different types of heartbeats obtained from the MIT-BIH arrhythmia database. These five types are Normal Sinus Rhythm (NSR), Ventricular Premature Contraction (VPC), Paced Beat (PB), Left Bundle Branch Block (LBBB), and Right Bundle Branch Block (RBBB). The results show that the DBLSTM-WS model gives a high recognition performance of 99.39%. It has been observed that the wavelet-based layer proposed in the study significantly improves the recognition performance of conventional networks. This proposed network structure is an important approach that can be applied to similar signal processing problems. Copyright © 2018 Elsevier Ltd. All rights reserved.

  9. Fractional Gaussian noise-enhanced information capacity of a nonlinear neuron model with binary signal input

    Science.gov (United States)

    Gao, Feng-Yin; Kang, Yan-Mei; Chen, Xi; Chen, Guanrong

    2018-05-01

    This paper reveals the effect of fractional Gaussian noise with Hurst exponent H ∈(1 /2 ,1 ) on the information capacity of a general nonlinear neuron model with binary signal input. The fGn and its corresponding fractional Brownian motion exhibit long-range, strong-dependent increments. It extends standard Brownian motion to many types of fractional processes found in nature, such as the synaptic noise. In the paper, for the subthreshold binary signal, sufficient conditions are given based on the "forbidden interval" theorem to guarantee the occurrence of stochastic resonance, while for the suprathreshold binary signal, the simulated results show that additive fGn with Hurst exponent H ∈(1 /2 ,1 ) could increase the mutual information or bits count. The investigation indicated that the synaptic noise with the characters of long-range dependence and self-similarity might be the driving factor for the efficient encoding and decoding of the nervous system.

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

    International Nuclear Information System (INIS)

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

    2010-01-01

    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.

  11. A Review on Human Body Communication: Signal Propagation Model, Communication Performance, and Experimental Issues

    Directory of Open Access Journals (Sweden)

    Jian Feng Zhao

    2017-01-01

    Full Text Available Human body communication (HBC, which uses the human body tissue as the transmission medium to transmit health informatics, serves as a promising physical layer solution for the body area network (BAN. The human centric nature of HBC offers an innovative method to transfer the healthcare data, whose transmission requires low interference and reliable data link. Therefore, the deployment of HBC system obtaining good communication performance is required. In this regard, a tutorial review on the important issues related to HBC data transmission such as signal propagation model, channel characteristics, communication performance, and experimental considerations is conducted. In this work, the development of HBC and its first attempts are firstly reviewed. Then a survey on the signal propagation models is introduced. Based on these models, the channel characteristics are summarized; the communication performance and selection of transmission parameters are also investigated. Moreover, the experimental issues, such as electrodes and grounding strategies, are also discussed. Finally, the recommended future studies are provided.

  12. Small-Signal Modeling and Analysis of Grid-Connected Inverter with Power Differential Droop Control

    Directory of Open Access Journals (Sweden)

    Xin Chen

    2016-01-01

    Full Text Available The conventional voltage and frequency droop control strategy in grid-connected inverter suffers a major setback in the presence of disturbance by producing oscillations. Adding a power differential term in droop controller is an effective way to address such drawback. In this paper, grid-connected inverter’s small-signal models of the conventional droop control and the power differential droop control are established. The eigenvalues of the models are then determined by system matrix. The eigenvalues analysis is presented which helps in identifying the relationship between the system stability and controller parameters. It is concluded that the damping ratio of dominant low-frequency eigenvalues increased and the oscillation caused by the disturbance is suppressed when a power differential term is added to the droop control method. The MATLAB/Simulink models of grid-connected inverter with both control strategies are also established to validate the results of small-signal analysis.

  13. Composite mathematical modeling of calcium signaling behind neuronal cell death in Alzheimer's disease.

    Science.gov (United States)

    Ranjan, Bobby; Chong, Ket Hing; Zheng, Jie

    2018-04-11

    Alzheimer's disease (AD) is a progressive neurological disorder, recognized as the most common cause of dementia affecting people aged 65 and above. AD is characterized by an increase in amyloid metabolism, and by the misfolding and deposition of β-amyloid oligomers in and around neurons in the brain. These processes remodel the calcium signaling mechanism in neurons, leading to cell death via apoptosis. Despite accumulating knowledge about the biological processes underlying AD, mathematical models to date are restricted to depicting only a small portion of the pathology. Here, we integrated multiple mathematical models to analyze and understand the relationship among amyloid depositions, calcium signaling and mitochondrial permeability transition pore (PTP) related cell apoptosis in AD. The model was used to simulate calcium dynamics in the absence and presence of AD. In the absence of AD, i.e. without β-amyloid deposition, mitochondrial and cytosolic calcium level remains in the low resting concentration. However, our in silico simulation of the presence of AD with the β-amyloid deposition, shows an increase in the entry of calcium ions into the cell and dysregulation of Ca 2+ channel receptors on the Endoplasmic Reticulum. This composite model enabled us to make simulation that is not possible to measure experimentally. Our mathematical model depicting the mechanisms affecting calcium signaling in neurons can help understand AD at the systems level and has potential for diagnostic and therapeutic applications.

  14. Modeling pedestrian crossing speed profiles considering speed change behavior for the safety assessment of signalized intersections.

    Science.gov (United States)

    Iryo-Asano, Miho; Alhajyaseen, Wael K M

    2017-11-01

    Pedestrian safety is one of the most challenging issues in road networks. Understanding how pedestrians maneuver across an intersection is the key to applying countermeasures against traffic crashes. It is known that the behaviors of pedestrians at signalized crosswalks are significantly different from those in ordinary walking spaces, and they are highly influenced by signal indication, potential conflicts with vehicles, and intersection geometries. One of the most important characteristics of pedestrian behavior at crosswalks is the possible sudden speed change while crossing. Such sudden behavioral change may not be expected by conflicting vehicles, which may lead to hazardous situations. This study aims to quantitatively model the sudden speed changes of pedestrians as they cross signalized crosswalks under uncongested conditions. Pedestrian speed profiles are collected from empirical data and speed change events are extracted assuming that the speed profiles are stepwise functions. The occurrence of speed change events is described by a discrete choice model as a function of the necessary walking speed to complete crossing before the red interval ends, current speed, and the presence of turning vehicles in the conflict area. The amount of speed change before and after the event is modeled using regression analysis. A Monte Carlo simulation is applied for the entire speed profile of the pedestrians. The results show that the model can represent the pedestrian travel time distribution more accurately than the constant speed model. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    Mainprize, James G.; Yaffe, Martin J.

    2010-01-01

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

  17. Methodology Development for SiC Sensor Signal Modelling in the Nuclear Reactor Radiation Environments

    International Nuclear Information System (INIS)

    Cetnar, J.; Krolikowski, I.P.

    2013-06-01

    This paper deals with SiC detector simulation methodology for signal formation by neutrons and induced secondary radiation as well as its inverse interpretation. The primary goal is to achieve the SiC capability of simultaneous spectroscopic measurements of neutrons and gamma-rays for which an appropriate methodology of the detector signal modelling and its interpretation must be adopted. The process of detector simulation is divided into two basically separate but actually interconnected sections. The first one is the forward simulation of detector signal formation in the field of the primary neutron and secondary radiations, whereas the second one is the inverse problem of finding a representation of the primary radiation, based on the measured detector signals. The applied methodology under development is based on the Monte Carlo description of radiation transport and analysis of the reactor physics. The methodology of SiC detector signal interpretation will be based on the existing experience in neutron metrology developed in the past for various neutron and gamma-ray detection systems. Since the novel sensors based on SiC are characterised by a new structure, yet to be finally designed, the methodology for particle spectroscopic fluence measurement must be developed while giving a productive feed back to the designing process of SiC sensor, in order to arrive at the best possible design. (authors)

  18. Predictive model identifies key network regulators of cardiomyocyte mechano-signaling.

    Directory of Open Access Journals (Sweden)

    Philip M Tan

    2017-11-01

    Full Text Available Mechanical strain is a potent stimulus for growth and remodeling in cells. Although many pathways have been implicated in stretch-induced remodeling, the control structures by which signals from distinct mechano-sensors are integrated to modulate hypertrophy and gene expression in cardiomyocytes remain unclear. Here, we constructed and validated a predictive computational model of the cardiac mechano-signaling network in order to elucidate the mechanisms underlying signal integration. The model identifies calcium, actin, Ras, Raf1, PI3K, and JAK as key regulators of cardiac mechano-signaling and characterizes crosstalk logic imparting differential control of transcription by AT1R, integrins, and calcium channels. We find that while these regulators maintain mostly independent control over distinct groups of transcription factors, synergy between multiple pathways is necessary to activate all the transcription factors necessary for gene transcription and hypertrophy. We also identify a PKG-dependent mechanism by which valsartan/sacubitril, a combination drug recently approved for treating heart failure, inhibits stretch-induced hypertrophy, and predict further efficacious pairs of drug targets in the network through a network-wide combinatorial search.

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

    Science.gov (United States)

    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.

  20. Icotinib inhibits EGFR signaling and alleviates psoriasis-like symptoms in animal models.

    Science.gov (United States)

    Tan, Fenlai; Yang, Guiqun; Wang, Yanping; Chen, Haibo; Yu, Bo; Li, He; Guo, Jing; Huang, Xiaoling; Deng, Yifang; Yu, Pengxia; Ding, Lieming

    2018-02-01

    To investigate the effects of icotinib hydrochloride and a derivative cream on epidermal growth factor receptor (EGFR) signaling and within animal psoriasis models, respectively. The effect of icotinib on EGFR signaling was examined in HaCaT cells, while its effect on angiogenesis was tested in chick embryo chorioallantoic membranes (CAM). The effectiveness of icotinib in treating psoriasis was tested in three psoriasis models, including diethylstilbestrol-treated mouse vaginal epithelial cells, mouse tail granular cell layer formation, and propranolol-induced psoriasis-like features in guinea pig ear skin. Icotinib treatment blocked EGFR signaling and reduced HaCaT cell viability as well as suppressed CAM angiogenesis. Topical application of icotinib ameliorated psoriasis-like histological characteristics in mouse and guinea pig psoriasis models. Icotinib also significantly inhibited mouse vaginal epithelium mitosis, promoted mouse tail squamous epidermal granular layer formation, and reduced the thickness of the horny layer in propranolol treated auricular dorsal surface of guinea pig. We conclude that icotinib can effectively inhibit psoriasis in animal models. Future clinical studies should be conducted to explore the therapeutic effects of icotinb in humans. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  1. An adult passive transfer mouse model to study desmoglein 3 signaling in pemphigus vulgaris.

    Science.gov (United States)

    Schulze, Katja; Galichet, Arnaud; Sayar, Beyza S; Scothern, Anthea; Howald, Denise; Zymann, Hillard; Siffert, Myriam; Zenhäusern, Denise; Bolli, Reinhard; Koch, Peter J; Garrod, David; Suter, Maja M; Müller, Eliane J

    2012-02-01

    Evidence has accumulated that changes in intracellular signaling downstream of desmoglein 3 (Dsg3) may have a significant role in epithelial blistering in the autoimmune disease pemphigus vulgaris (PV). Currently, most studies on PV involve passive transfer of pathogenic antibodies into neonatal mice that have not finalized epidermal morphogenesis, and do not permit analysis of mature hair follicles (HFs) and stem cell niches. To investigate Dsg3 antibody-induced signaling in the adult epidermis at defined stages of the HF cycle, we developed a model with passive transfer of AK23 (a mouse monoclonal pathogenic anti-Dsg3 antibody) into adult 8-week-old C57Bl/6J mice. Validated using histopathological and molecular methods, we found that this model faithfully recapitulates major features described in PV patients and PV models. Two hours after AK23 transfer, we observed widening of intercellular spaces between desmosomes and EGFR activation, followed by increased Myc expression and epidermal hyperproliferation, desmosomal Dsg3 depletion, and predominant blistering in HFs and oral mucosa. These data confirm that the adult passive transfer mouse model is ideally suited for detailed studies of Dsg3 antibody-mediated signaling in adult skin, providing the basis for investigations on novel keratinocyte-specific therapeutic strategies.

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

    Science.gov (United States)

    Jiang, Jiefeng; Schmajuk, Nestor; Egner, Tobias

    2012-08-01

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

  3. Large signal S-parameters: modeling and radiation effects in microwave power transistors

    International Nuclear Information System (INIS)

    Graham, E.D. Jr.; Chaffin, R.J.; Gwyn, C.W.

    1973-01-01

    Microwave power transistors are usually characterized by measuring the source and load impedances, efficiency, and power output at a specified frequency and bias condition in a tuned circuit. These measurements provide limited data for circuit design and yield essentially no information concerning broadbanding possibilities. Recently, a method using large signal S-parameters has been developed which provides a rapid and repeatable means for measuring microwave power transistor parameters. These large signal S-parameters have been successfully used to design rf power amplifiers. Attempts at modeling rf power transistors have in the past been restricted to a modified Ebers-Moll procedure with numerous adjustable model parameters. The modified Ebers-Moll model is further complicated by inclusion of package parasitics. In the present paper an exact one-dimensional device analysis code has been used to model the performance of the transistor chip. This code has been integrated into the SCEPTRE circuit analysis code such that chip, package and circuit performance can be coupled together in the analysis. Using []his computational tool, rf transistor performance has been examined with particular attention given to the theoretical validity of large-signal S-parameters and the effects of nuclear radiation on device parameters. (auth)

  4. An Adaptive Model for Calculating the Correlation Degree of Multiple Adjacent Signalized Intersections

    Directory of Open Access Journals (Sweden)

    Linhong Wang

    2013-01-01

    Full Text Available As an important component of the urban adaptive traffic control system, subarea partition algorithm divides the road network into some small subareas and then determines the optimal signal control mode for each signalized intersection. Correlation model is the core of subarea partition algorithm because it can quantify the correlation degree of adjacent signalized intersections and decides whether these intersections can be grouped into one subarea. In most cases, there are more than two intersections in one subarea. However, current researches only focus on the correlation model for two adjacent intersections. The objective of this study is to develop a model which can calculate the correlation degree of multiple intersections adaptively. The cycle lengths, link lengths, number of intersections, and path flow between upstream and downstream coordinated phases were selected as the contributing factors of the correlation model. Their jointly impacts on the performance of the coordinated control mode relative to the isolated control mode were further studied using numerical experiments. The paper then proposed a correlation index (CI as an alternative to relative performance. The relationship between CI and the four contributing factors was established in order to predict the correlation, which determined whether adjacent intersections could be partitioned into one subarea. A value of 0 was set as the threshold of CI. If CI was larger than 0, multiple intersections could be partitioned into one subarea; otherwise, they should be separated. Finally, case studies were conducted in a real-life signalized network to evaluate the performance of the model. The results show that the CI simulates the relative performance well and could be a reliable index for subarea partition.

  5. A speech production model including the nasal Cavity: A novel approach to articulatory analysis of speech signals

    DEFF Research Database (Denmark)

    Olesen, Morten

    In order to obtain articulatory analysis of speech production the model is improved. the standard model, as used in LPC analysis, to a large extent only models the acoustic properties of speech signal as opposed to articulatory modelling of the speech production. In spite of this the LPC model...... is by far the most widely used model in speech technology....

  6. An original piecewise model for computing energy expenditure from accelerometer and heart rate signals.

    Science.gov (United States)

    Romero-Ugalde, Hector M; Garnotel, M; Doron, M; Jallon, P; Charpentier, G; Franc, S; Huneker, E; Simon, C; Bonnet, S

    2017-07-28

    Activity energy expenditure (EE) plays an important role in healthcare, therefore, accurate EE measures are required. Currently available reference EE acquisition methods, such as doubly labeled water and indirect calorimetry, are complex, expensive, uncomfortable, and/or difficult to apply on real time. To overcome these drawbacks, the goal of this paper is to propose a model for computing EE in real time (minute-by-minute) from heart rate and accelerometer signals. The proposed model, which consists of an original branched model, uses heart rate signals for computing EE on moderate to vigorous physical activities and a linear combination of heart rate and counts per minute for computing EE on light to moderate physical activities. Model parameters were estimated from a given data set composed of 53 subjects performing 25 different physical activities (light-, moderate- and vigorous-intensity), and validated using leave-one-subject-out. A different database (semi-controlled in-city circuit), was used in order to validate the versatility of the proposed model. Comparisons are done versus linear and nonlinear models, which are also used for computing EE from accelerometer and/or HR signals. The proposed piecewise model leads to more accurate EE estimations ([Formula: see text], [Formula: see text] and [Formula: see text] J kg -1 min -1 and [Formula: see text], [Formula: see text], and [Formula: see text] J kg -1 min -1 on each validation database). This original approach, which is more conformable and less expensive than the reference methods, allows accurate EE estimations, in real time (minute-by-minute), during a large variety of physical activities. Therefore, this model may be used on applications such as computing the time that a given subject spent on light-intensity physical activities and on moderate to vigorous physical activities (binary classification accuracy of 0.8155).

  7. Model Based Beamforming and Bayesian Inversion Signal Processing Methods for Seismic Localization of Underground Source

    DEFF Research Database (Denmark)

    Oh, Geok Lian

    properties such as the elastic wave speeds and soil densities. One processing method is casting the estimation problem into an inverse problem to solve for the unknown material parameters. The forward model for the seismic signals used in the literatures include ray tracing methods that consider only...... density values of the discretized ground medium, which leads to time-consuming computations and instability behaviour of the inversion process. In addition, the geophysics inverse problem is generally ill-posed due to non-exact forward model that introduces errors. The Bayesian inversion method through...... the first arrivals of the reflected compressional P-waves from the subsurface structures, or 3D elastic wave models that model all the seismic wave components. The ray tracing forward model formulation is linear, whereas the full 3D elastic wave model leads to a nonlinear inversion problem. In this Ph...

  8. A Linearized Large Signal Model of an LCL-Type Resonant Converter

    Directory of Open Access Journals (Sweden)

    Hong-Yu Li

    2015-03-01

    Full Text Available In this work, an LCL-type resonant dc/dc converter with a capacitive output filter is modeled in two stages. In the first high-frequency ac stage, all ac signals are decomposed into two orthogonal vectors in a synchronous rotating d–q frame using multi-frequency modeling. In the dc stage, all dc quantities are represented by their average values with average state-space modeling. A nonlinear two-stage model is then created by means of a non-linear link. By aligning the transformer voltage on the d-axis, the nonlinear link can be eliminated, and the whole converter can be modeled by a single set of linear state-space equations. Furthermore, a feedback control scheme can be formed according to the steady-state solutions. Simulation and experimental results have proven that the resulted model is good for fast simulation and state variable estimation.

  9. Mathematical models for the diffusion magnetic resonance signal abnormality in patients with prion diseases

    Directory of Open Access Journals (Sweden)

    Matteo Figini

    2015-01-01

    Full Text Available In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR diffusion-weighted images (DWIs is a marker of sporadic Creutzfeldt–Jakob Disease (sCJD. MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightings were acquired in 15 patients with suspected diagnosis of prion disease and in 4 healthy age-matched subjects. Clinical diagnosis of sCJD was made in nine patients, genetic CJD in one, rapidly progressive encephalopathy in three, and Gerstmann–Sträussler–Scheinker syndrome in two. Data were analysed with two bi-compartment models that represent different hypotheses about the histopathological alterations responsible for the DWI signal hyperintensity. A ROI-based analysis was performed in 13 grey matter areas located in affected and apparently unaffected regions from patients and healthy subjects. We provide for the first time non-invasive estimate of the restricted compartment radius, designed to reflect vacuole size, which is a key discriminator of sCJD subtypes. The estimated vacuole size in DWI hyperintense cortex was in the range between 3 and 10 µm that is compatible with neuropathology measurements. In DWI hyperintense grey matter of sCJD patients the two bi-compartment models outperform the classic mono-exponential ADC model. Both new models show that T2 relaxation times significantly increase, fast and slow diffusivities reduce, and the fraction of the compartment with slow/restricted diffusion increases compared to unaffected grey matter of

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

    Directory of Open Access Journals (Sweden)

    Matthew Caldwell

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

  11. The signal-to-noise analysis of the Little-Hopfield model revisited

    International Nuclear Information System (INIS)

    Bolle, D; Blanco, J Busquets; Verbeiren, T

    2004-01-01

    Using the generating functional analysis an exact recursion relation is derived for the time evolution of the effective local field of the fully connected Little-Hopfield model. It is shown that, by leaving out the feedback correlations arising from earlier times in this effective dynamics, one precisely finds the recursion relations usually employed in the signal-to-noise approach. The consequences of this approximation as well as the physics behind it are discussed. In particular, it is pointed out why it is hard to notice the effects, especially for model parameters corresponding to retrieval. Numerical simulations confirm these findings. The signal-to-noise analysis is then extended to include all correlations, making it a full theory for dynamics at the level of the generating functional analysis. The results are applied to the frequently employed extremely diluted (a)symmetric architectures and to sequence processing networks

  12. Rapid anatomical brain imaging using spiral acquisition and an expanded signal model.

    Science.gov (United States)

    Kasper, Lars; Engel, Maria; Barmet, Christoph; Haeberlin, Maximilian; Wilm, Bertram J; Dietrich, Benjamin E; Schmid, Thomas; Gross, Simon; Brunner, David O; Stephan, Klaas E; Pruessmann, Klaas P

    2018-03-01

    We report the deployment of spiral acquisition for high-resolution structural imaging at 7T. Long spiral readouts are rendered manageable by an expanded signal model including static off-resonance and B 0 dynamics along with k-space trajectories and coil sensitivity maps. Image reconstruction is accomplished by inversion of the signal model using an extension of the iterative non-Cartesian SENSE algorithm. Spiral readouts up to 25 ms are shown to permit whole-brain 2D imaging at 0.5 mm in-plane resolution in less than a minute. A range of options is explored, including proton-density and T 2 * contrast, acceleration by parallel imaging, different readout orientations, and the extraction of phase images. Results are shown to exhibit competitive image quality along with high geometric consistency. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

    Haase, Steven J; Fisk, Gary D

    2011-08-01

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

  14. Dynamic Modeling of Indole Glucosinolate Hydrolysis and Its Impact on Auxin Signaling

    Directory of Open Access Journals (Sweden)

    Daniel Vik

    2018-04-01

    Full Text Available Plants release chemicals to deter attackers. Arabidopsis thaliana relies on multiple defense compounds, including indol-3-ylmethyl glucosinolate (I3G, which upon hydrolysis initiated by myrosinase enzymes releases a multitude of bioactive compounds, among others, indole-3-acetonitrile and indole-3-acetoisothiocyanate. The highly unstable isothiocyanate rapidly reacts with other molecules. One of the products, indole-3-carbinol, was reported to inhibit auxin signaling through binding to the TIR1 auxin receptor. On the contrary, the nitrile product of I3G hydrolysis can be converted by nitrilase enzymes to form the primary auxin molecule, indole-3-acetic acid, which activates TIR1. This suggests that auxin signaling is subject to both antagonistic and protagonistic effects of I3G hydrolysis upon attack. We hypothesize that I3G hydrolysis and auxin signaling form an incoherent feedforward loop and we build a mathematical model to examine the regulatory network dynamics. We use molecular docking to investigate the possible antagonistic properties of different I3G hydrolysis products by competitive binding to the TIR1 receptor. Our simulations reveal an uncoupling of auxin concentration and signaling, and we determine that enzyme activity and antagonist binding affinity are key parameters for this uncoupling. The molecular docking predicts that several I3G hydrolysis products strongly antagonize auxin signaling. By comparing a tissue disrupting attack – e.g., by chewing insects or necrotrophic pathogens that causes rapid release of I3G hydrolysis products – to sustained cell-autonomous I3G hydrolysis, e.g., upon infection by biotrophic pathogens, we find that each scenario gives rise to distinct auxin signaling dynamics. This suggests that plants have different defense versus growth strategies depending on the nature of the attack.

  15. Modeling borehole microseismic and strain signals measured by a distributed fiber optic sensor

    Science.gov (United States)

    Mellors, R. J.; Sherman, C. S.; Ryerson, F. J.; Morris, J.; Allen, G. S.; Messerly, M. J.; Carr, T.; Kavousi, P.

    2017-12-01

    The advent of distributed fiber optic sensors installed in boreholes provides a new and data-rich perspective on the subsurface environment. This includes the long-term capability for vertical seismic profiles, monitoring of active borehole processes such as well stimulation, and measuring of microseismic signals. The distributed fiber sensor, which measures strain (or strain-rate), is an active sensor with highest sensitivity parallel to the fiber and subject to varying types of noise, both external and internal. We take a systems approach and include the response of the electronics, fiber/cable, and subsurface to improve interpretation of the signals. This aids in understanding noise sources, assessing error bounds on amplitudes, and developing appropriate algorithms for improving the image. Ultimately, a robust understanding will allow identification of areas for future improvement and possible optimization in fiber and cable design. The subsurface signals are simulated in two ways: 1) a massively parallel multi-physics code that is capable of modeling hydraulic stimulation of heterogeneous reservoir with a pre-existing discrete fracture network, and 2) a parallelized 3D finite difference code for high-frequency seismic signals. Geometry and parameters for the simulations are derived from fiber deployments, including the Marcellus Shale Energy and Environment Laboratory (MSEEL) project in West Virginia. The combination mimics both the low-frequency strain signals generated during the fracture process and high-frequency signals from microseismic and perforation shots. Results are compared with available fiber data and demonstrate that quantitative interpretation of the fiber data provides valuable constraints on the fracture geometry and microseismic activity. These constraints appear difficult, if not impossible, to obtain otherwise.

  16. Towards a time-domain modeling framework for small-signal analysis of unbalanced microgrids

    OpenAIRE

    Ojo, Y; Schiffer, JF

    2017-01-01

    Small-signal analysis is one of the most frequently used techniques to assess the operating conditions of power systems. Typically, this analysis is conducted by employing a phasor-based model of the power network derived under the assumption of balanced operating conditions. However, distribution networks and, amongst these, microgrids are often unbalanced. Hence, their analysis requires the development of tools and methods valid under such conditions. Motivated by this, we propose a modelin...

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

    Science.gov (United States)

    Magliocca, N. R.

    2015-12-01

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

  18. Transcription factor RBP-J-mediated signalling regulates basophil immunoregulatory function in mouse asthma model.

    Science.gov (United States)

    Qu, Shuo-Yao; He, Ya-Long; Zhang, Jian; Wu, Chang-Gui

    2017-09-01

    Basophils (BA) play an important role in the promotion of aberrant T helper type 2 (Th2) immune responses in asthma. It is not only the effective cell, but also modulates the initiation of Th2 immune responses. We earlier demonstrated that Notch signalling regulates the biological function of BAin vitro. However, whether this pathway plays the same role in vivo is not clear. The purpose of the present study was to investigate the effect of Notch signalling on BA function in the regulation of allergic airway inflammation in a murine model of asthma. Bone marrow BA were prepared by bone marrow cell culture in the presence of recombinant interleukin-3 (rIL-3; 300 pg/ml) for 7 days, followed by isolation of the CD49b + microbeads. The recombination signal binding protein J (RBP-J -/- ) BA were co-cultured with T cells, and the supernatant and the T-cell subtypes were examined. The results indicated disruption of the capacity of BA for antigen presentation alongside an up-regulation of the immunoregulatory function. This was possibly due to the low expression of OX40L in the RBP-J -/- BA. Basophils were adoptively transferred to ovalbumin-sensitized recipient mice, to establish an asthma model. Lung pathology, cytokine profiles of brobchoalveolar fluid, airway hyperactivity and the absolute number of Th1/Th2 cells in lungs were determined. Overall, our results indicate that the RBP-J-mediated Notch signalling is critical for BA-dependent immunoregulation. Deficiency of RBP-J influences the immunoregulatory functions of BA, which include activation of T cells and their differentiation into T helper cell subtypes. The Notch signalling pathway is a potential therapeutic target for BA-based immunotherapy against asthma. © 2017 John Wiley & Sons Ltd.

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

    Science.gov (United States)

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

    2016-01-01

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

  20. Modeling Left-Turn Driving Behavior at Signalized Intersections with Mixed Traffic Conditions

    Directory of Open Access Journals (Sweden)

    Hong Li

    2016-01-01

    Full Text Available In many developing countries, mixed traffic is the most common type of urban transportation; traffic of this type faces many major problems in traffic engineering, such as conflicts, inefficiency, and security issues. This paper focuses on the traffic engineering concerns on the driving behavior of left-turning vehicles caused by different degrees of pedestrian violations. The traffic characteristics of left-turning vehicles and pedestrians in the affected region at a signalized intersection were analyzed and a cellular-automata-based “following-conflict” driving behavior model that mainly addresses four basic behavior modes was proposed to study the conflict and behavior mechanisms of left-turning vehicles by mathematic methodologies. Four basic driving behavior modes were reproduced in computer simulations, and a logit model of the behavior mode choice was also developed to analyze the relative share of each behavior mode. Finally, the microscopic characteristics of driving behaviors and the macroscopic parameters of traffic flow in the affected region were all determined. These data are important reference for geometry and capacity design for signalized intersections. The simulation results show that the proposed models are valid and can be used to represent the behavior of left-turning vehicles in the case of conflicts with illegally crossing pedestrians. These results will have potential applications on improving traffic safety and traffic capacity at signalized intersections with mixed traffic conditions.

  1. Real-time traffic signal optimization model based on average delay time per person

    Directory of Open Access Journals (Sweden)

    Pengpeng Jiao

    2015-10-01

    Full Text Available Real-time traffic signal control is very important for relieving urban traffic congestion. Many existing traffic control models were formulated using optimization approach, with the objective functions of minimizing vehicle delay time. To improve people’s trip efficiency, this article aims to minimize delay time per person. Based on the time-varying traffic flow data at intersections, the article first fits curves of accumulative arrival and departure vehicles, as well as the corresponding functions. Moreover, this article transfers vehicle delay time to personal delay time using average passenger load of cars and buses, employs such time as the objective function, and proposes a signal timing optimization model for intersections to achieve real-time signal parameters, including cycle length and green time. This research further implements a case study based on practical data collected at an intersection in Beijing, China. The average delay time per person and queue length are employed as evaluation indices to show the performances of the model. The results show that the proposed methodology is capable of improving traffic efficiency and is very effective for real-world applications.

  2. On Signal Modeling of Moon-Based Synthetic Aperture Radar (SAR Imaging of Earth

    Directory of Open Access Journals (Sweden)

    Zhen Xu

    2018-03-01

    Full Text Available The Moon-based Synthetic Aperture Radar (Moon-Based SAR, using the Moon as a platform, has a great potential to offer global-scale coverage of the earth’s surface with a high revisit cycle and is able to meet the scientific requirements for climate change study. However, operating in the lunar orbit, Moon-Based SAR imaging is confined within a complex geometry of the Moon-Based SAR, Moon, and Earth, where both rotation and revolution have effects. The extremely long exposure time of Moon-Based SAR presents a curved moving trajectory and the protracted time-delay in propagation makes the “stop-and-go” assumption no longer valid. Consequently, the conventional SAR imaging technique is no longer valid for Moon-Based SAR. This paper develops a Moon-Based SAR theory in which a signal model is derived. The Doppler parameters in the context of lunar revolution with the removal of ‘stop-and-go’ assumption are first estimated, and then characteristics of Moon-Based SAR imaging’s azimuthal resolution are analyzed. In addition, a signal model of Moon-Based SAR and its two-dimensional (2-D spectrum are further derived. Numerical simulation using point targets validates the signal model and enables Doppler parameter estimation for image focusing.

  3. Investigating Irregularly Patterned Deep Brain Stimulation Signal Design Using Biophysical Models

    Directory of Open Access Journals (Sweden)

    Samantha Rose Summerson

    2015-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Xuecai Xu

    Full Text Available The objective of this paper is to provide a new method for estimating crash rate and severity simultaneously.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.The results of the proposed two-step Heckman selection model illustrate the necessity of different crash rates for different crash severity levels.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.

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

    DEFF Research Database (Denmark)

    Oh, Geok Lian; Brunskog, Jonas

    2014-01-01

    Techniques have been studied for the localization of an underground source with seismic interrogation signals. Much of the work has involved defining either a P-wave acoustic model or a dispersive surface wave model to the received signal and applying the time-delay processing technique and frequ...... that for field data, inversion for localization is most advantageous when the forward model completely describe all the elastic wave components as is the case of the FDTD 3D elastic model....

  6. Multiobjective optimization model of intersection signal timing considering emissions based on field data: A case study of Beijing.

    Science.gov (United States)

    Kou, Weibin; Chen, Xumei; Yu, Lei; Gong, Huibo

    2018-04-18

    Most existing signal timing models are aimed to minimize the total delay and stops at intersections, without considering environmental factors. This paper analyzes the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. First, considering the different operating modes of cruising, acceleration, deceleration, and idling, field data of emissions and Global Positioning System (GPS) are collected to estimate emission rates for heavy-duty and light-duty vehicles. Second, multiobjective signal timing optimization model is established based on a genetic algorithm to minimize delay, stops, and emissions. Finally, a case study is conducted in Beijing. Nine scenarios are designed considering different weights of emission and traffic efficiency. The results compared with those using Highway Capacity Manual (HCM) 2010 show that signal timing optimized by the model proposed in this paper can decrease vehicles delay and emissions more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development. Vehicle emissions are heavily at signal intersections in urban area. The multiobjective signal timing optimization model is proposed considering the trade-off between vehicle emissions and traffic efficiencies on the basis of field data. The results indicate that signal timing optimized by the model proposed in this paper can decrease vehicle emissions and delays more significantly. The optimization model can be applied in different cities, which provides supports for eco-signal design and development.

  7. A compartmentalized mathematical model of the β1-adrenergic signaling system in mouse ventricular myocytes.

    Directory of Open Access Journals (Sweden)

    Vladimir E Bondarenko

    Full Text Available The β1-adrenergic signaling system plays an important role in the functioning of cardiac cells. Experimental data shows that the activation of this system produces inotropy, lusitropy, and chronotropy in the heart, such as increased magnitude and relaxation rates of [Ca(2+]i transients and contraction force, and increased heart rhythm. However, excessive stimulation of β1-adrenergic receptors leads to heart dysfunction and heart failure. In this paper, a comprehensive, experimentally based mathematical model of the β1-adrenergic signaling system for mouse ventricular myocytes is developed, which includes major subcellular functional compartments (caveolae, extracaveolae, and cytosol. The model describes biochemical reactions that occur during stimulation of β1-adrenoceptors, changes in ionic currents, and modifications of Ca(2+ handling system. Simulations describe the dynamics of major signaling molecules, such as cyclic AMP and protein kinase A, in different subcellular compartments; the effects of inhibition of phosphodiesterases on cAMP production; kinetics and magnitudes of phosphorylation of ion channels, transporters, and Ca(2+ handling proteins; modifications of action potential shape and duration; magnitudes and relaxation rates of [Ca(2+]i transients; changes in intracellular and transmembrane Ca(2+ fluxes; and [Na(+]i fluxes and dynamics. The model elucidates complex interactions of ionic currents upon activation of β1-adrenoceptors at different stimulation frequencies, which ultimately lead to a relatively modest increase in action potential duration and significant increase in [Ca(2+]i transients. In particular, the model includes two subpopulations of the L-type Ca(2+ channels, in caveolae and extracaveolae compartments, and their effects on the action potential and [Ca(2+]i transients are investigated. The presented model can be used by researchers for the interpretation of experimental data and for the developments of

  8. Renormalizability and model-independent description of Z' signals at low energies

    International Nuclear Information System (INIS)

    Gulov, A.V.; Skalozub, V.V.

    2000-01-01

    The model-independent search for signals of heavy Z' gauge bosons in low-energy four-fermion processes is analyzed. It is shown that the renormalizability of the underlying theory containing Z', formulated as a scattering in the field of heavy virtual states, can be implemented in specific relations between different processes. Considering the two-Higgs-doublet model as the low-energy basis theory, the two types of Z' interactions with light particles are found to be compatible with the renormalizability. They are called the Abelian and the ''chiral'' couplings. Observables giving the possibility to uniquely detect Z' in both cases are introduced. (orig.)

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

    DEFF Research Database (Denmark)

    Finlay, Chris; Lesur, V.; Thébault, E.

    2017-01-01

    systems in the ionosphere and magnetosphere. In order to fully exploit magnetic data to probe the physical properties and dynamics of the Earth’s interior, field models with suitable treatments of external sources, and their associated induced signals, are essential. Here we review the methods presently......-by-track analysis to characterize magnetospheric field fluctuations, differences in internal field models that result from alternative treatments of the quiet-time ionospheric field, and challenges associated with rapidly changing, but spatially correlated, magnetic signatures of polar cap current systems. Possible...

  10. Modeling speech intelligibility based on the signal-to-noise envelope power ratio

    DEFF Research Database (Denmark)

    Jørgensen, Søren

    of modulation frequency selectivity in the auditory processing of sound with a decision metric for intelligibility that is based on the signal-to-noise envelope power ratio (SNRenv). The proposed speech-based envelope power spectrum model (sEPSM) is demonstrated to account for the effects of stationary...... through three commercially available mobile phones. The model successfully accounts for the performance across the phones in conditions with a stationary speech-shaped background noise, whereas deviations were observed in conditions with “Traffic” and “Pub” noise. Overall, the results of this thesis...

  11. Modeling of the shape of infrared stimulated luminescence signals in feldspars

    DEFF Research Database (Denmark)

    Pagonis, Vasilis; Jain, Mayank; Murray, Andrew S.

    2012-01-01

    This paper presents a new empirical model describing infrared (IR) stimulation phenomena in feldspars. In the model electrons from the ground state of an electron trap are raised by infrared optical stimulation to the excited state, and subsequently recombine with a nearest-neighbor hole via...... corresponds to a fast rate of recombination processes taking place along the infrared stimulated luminescence (IRSL) curves. The subsequent decay of the simulated IRSL signal is characterized by a much slower recombination rate, which can be described by a power-law type of equation.Several simulations...

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

    OpenAIRE

    Sinha, Shriprakash

    2016-01-01

    Simulation study in systems biology involving computational experiments dealing with Wnt signaling pathways abound in literature but often lack a pedagogical perspective that might ease the understanding of beginner students and researchers in transition, who intend to work on the modeling of the pathway. This paucity might happen due to restrictive business policies which enforce an unwanted embargo on the sharing of important scientific knowledge. A tutorial introduction to computational mo...

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

    Science.gov (United States)

    Sinha, Shriprakash

    2016-12-01

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

  14. A viscoelastic model of the correlation between respiratory lung tumour motion and an external abdominal signal

    International Nuclear Information System (INIS)

    Cavan, A.E.; Wilson, P.L.; Meyer, J.; Berbeco, R.I.

    2010-01-01

    Full text: Accuracy of radiotherapy treatment of lung cancer is limited by respiratory induced tumour motion. Compensation for this motion is required to increase treatment efficacy. The lung tumour motion is related to motion of an external abdominal marker, but a reliable model of this correlation is essential. Three viscoelastic systems were developed, in order to determine the best model and analyse its effectiveness on clinical data. Three 1D viscoelastic systems (a spring and dash pot in parallel, series and a combination) were developed and compared using a simulated breathing pattern. The most effective model was applied to 60 clinical data sets (consisting of co-ordinates of tumour and abdominal motion) from multiple treatment fractions of ten patients. The model was optimised for each data set, and efficacy determined by calculating the root mean square (RMS) error between the mo elled position and the actual tumour motion. Upon application to clinical data the parallel configuration achieved an average RMS error of 0.95 mm (superior-inferior direction). The model had patient specific parameters, and displayed good consistency over extended treatment periods. The model ha dled amplitude, frequency and baseline variations of the input signal, and phase shifts between tumour and abdominal motions. This study has shown that a viscoelastic model can be used to cor relate internal lung tumour motion with an external abdominal signal. The ability to handle breathing pattern in'egularities is comparable or better than previous models. Extending the model to a full 3D, pr dictive system could allow clinical implementation for radiotherapy.

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

    Science.gov (United States)

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

    2017-02-01

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

  16. Exploiting magnetic resonance angiography imaging improves model estimation of BOLD signal.

    Directory of Open Access Journals (Sweden)

    Zhenghui Hu

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

  17. Modelling the thermal bleaching of OSL signal in the case of a competition between recombination centres

    International Nuclear Information System (INIS)

    Chruscinska, A.

    2009-01-01

    The thermal bleaching of the optically stimulated luminescence (OSL) has been investigated by computer simulations for a model including three traps and two luminescence centres. The deepest trap is active only during the OSL process. Two other traps are active only during the thermal bleaching. The thermal bleaching effects on the OSL intensity as well as on the OSL curve shape are presented for the wide range of trap and luminescence centre parameters and for the different settings of optical detection window. The conventional OSL curve analysis consisting in decomposition of the OSL curve into first order components is applied to the simulation results and the optical cross section spectra obtained as a result of this analysis are compared with the model assumptions. The simulations show that OSL signal can decrease to undetectable level even when the traps related to this signal are not emptied during thermal bleaching. The residual level of the OSL signal after bleaching process, however, depends strongly on centre parameters and concentrations. The modifications of optical detection spectral window lead to significant changes of bleaching effects. The thermal bleaching influences also the optical cross section spectra obtained as a result of the OSL curve decomposition.

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

    Science.gov (United States)

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

    2015-03-01

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

  19. Intestinal tumorigenesis is not affected by progesterone signaling in rodent models.

    Directory of Open Access Journals (Sweden)

    Jarom Heijmans

    Full Text Available Clinical data suggest that progestins have chemopreventive properties in the development of colorectal cancer. We set out to examine a potential protective effect of progestins and progesterone signaling on colon cancer development. In normal and neoplastic intestinal tissue, we found that the progesterone receptor (PR is not expressed. Expression was confined to sporadic mesenchymal cells. To analyze the influence of systemic progesterone receptor signaling, we crossed mice that lacked the progesterone receptor (PRKO to the Apc(Min/+ mouse, a model for spontaneous intestinal polyposis. PRKO-Apc(Min/+ mice exhibited no change in polyp number, size or localization compared to Apc(Min/+. To examine effects of progestins on the intestinal epithelium that are independent of the PR, we treated mice with MPA. We found no effects of either progesterone or MPA on gross intestinal morphology or epithelial proliferation. Also, in rats treated with MPA, injection with the carcinogen azoxymethane did not result in a difference in the number or size of aberrant crypt foci, a surrogate end-point for adenoma development. We conclude that expression of the progesterone receptor is limited to cells in the intestinal mesenchyme. We did not observe any effect of progesterone receptor signaling or of progestin treatment in rodent models of intestinal tumorigenesis.

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

    Science.gov (United States)

    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 types under free-living conditions.

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

    Science.gov (United States)

    Guo, Shaodong

    2014-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Mockler, Todd C. [Donald Danforth Plant Science Center, Saint Louis, MO (United States)

    2016-11-07

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

  3. Observations and modeling of the elastogravity signals preceding direct seismic waves

    Science.gov (United States)

    Vallée, Martin; Ampuero, Jean Paul; Juhel, Kévin; Bernard, Pascal; Montagner, Jean-Paul; Barsuglia, Matteo

    2017-12-01

    After an earthquake, the earliest deformation signals are not expected to be carried by the fastest (P) elastic waves but by the speed-of-light changes of the gravitational field. However, these perturbations are weak and, so far, their detection has not been accurate enough to fully understand their origins and to use them for a highly valuable rapid estimate of the earthquake magnitude. We show that gravity perturbations are particularly well observed with broadband seismometers at distances between 1000 and 2000 kilometers from the source of the 2011, moment magnitude 9.1, Tohoku earthquake. We can accurately model them by a new formalism, taking into account both the gravity changes and the gravity-induced motion. These prompt elastogravity signals open the window for minute time-scale magnitude determination for great earthquakes.

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

    Directory of Open Access Journals (Sweden)

    Francesca eCamera

    2015-04-01

    Full Text Available Several experimental results published in the literature showed that weak pulsed magnetic fields affected the response of the central nervous system. However, the specific biological mechanisms that regulate the observed behaviors are still unclear and further scientific investigation is required. In this work we performed simulations on a neuronal network model exposed to a specific pulsed magnetic field signal that seems to be very effective in modulating the brain activity: the Complex Neuroelectromagnetic Pulse (CNP. Results show that CNP can silence the neurons of a feed-forward network for signal intensities that depend on the strength of the bias current, the endogenous noise level and the specific waveforms of the pulses.

  5. Proteomes of the barley aleurone layer: A model system for plant signalling and protein secretion

    DEFF Research Database (Denmark)

    Finnie, Christine; Andersen, Birgit; Shahpiri, Azar

    2011-01-01

    molecules in an isolated system. These properties have led to its use as a model system for the study of plant signalling and germination. More recently, proteome analysis of the aleurone layer has provided new insight into this unique tissue including identification of plasma membrane proteins and targeted...... analysis of germination-related changes and the thioredoxin system. Here, analysis of intracellular and secreted proteomes reveals features of the aleurone layer system that makes it promising for investigations of plant protein secretion mechanisms....... to gibberellic acid produced by the embryo, the aleurone layer synthesises hydrolases that are secreted to the endosperm for the degradation of storage products. The barley aleurone layer can be separated from the other seed tissues and maintained in culture, allowing the study of the effect of added signalling...

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

    Science.gov (United States)

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

    2009-03-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

    Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and posttranslational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). © 2013 Wiley Periodicals, Inc.

  9. Investigation of signal models and methods for evaluating structures of processing telecommunication information exchange systems under acoustic noise conditions

    Science.gov (United States)

    Kropotov, Y. A.; Belov, A. A.; Proskuryakov, A. Y.; Kolpakov, A. A.

    2018-05-01

    The paper considers models and methods for estimating signals during the transmission of information messages in telecommunication systems of audio exchange. One-dimensional probability distribution functions that can be used to isolate useful signals, and acoustic noise interference are presented. An approach to the estimation of the correlation and spectral functions of the parameters of acoustic signals is proposed, based on the parametric representation of acoustic signals and the components of the noise components. The paper suggests an approach to improving the efficiency of interference cancellation and highlighting the necessary information when processing signals from telecommunications systems. In this case, the suppression of acoustic noise is based on the methods of adaptive filtering and adaptive compensation. The work also describes the models of echo signals and the structure of subscriber devices in operational command telecommunications systems.

  10. Noise Reduction of MEMS Gyroscope Based on Direct Modeling for an Angular Rate Signal

    Directory of Open Access Journals (Sweden)

    Liang Xue

    2015-02-01

    Full Text Available In this paper, a novel approach for processing the outputs signal of the microelectromechanical systems (MEMS gyroscopes was presented to reduce the bias drift and noise. The principle for the noise reduction was presented, and an optimal Kalman filter (KF was designed by a steady-state filter gain obtained from the analysis of KF observability. In particular, the true angular rate signal was directly modeled to obtain an optimal estimate and make a self-compensation for the gyroscope without needing other sensor’s information, whether in static or dynamic condition. A linear fit equation that describes the relationship between the KF bandwidth and modeling parameter of true angular rate was derived from the analysis of KF frequency response. The test results indicated that the MEMS gyroscope having an ARW noise of 4.87°/h0.5 and a bias instability of 44.41°/h were reduced to 0.4°/h0.5 and 4.13°/h by the KF under a given bandwidth (10 Hz, respectively. The 1σ estimated error was reduced from 1.9°/s to 0.14°/s and 1.7°/s to 0.5°/s in the constant rate test and swing rate test, respectively. It also showed that the filtered angular rate signal could well reflect the dynamic characteristic of the input rate signal in dynamic conditions. The presented algorithm is proved to be effective at improving the measurement precision of the MEMS gyroscope.

  11. Responding to vaccine safety signals during pandemic influenza: a modeling study.

    Directory of Open Access Journals (Sweden)

    Judith C Maro

    Full Text Available Managing emerging vaccine safety signals during an influenza pandemic is challenging. Federal regulators must balance vaccine risks against benefits while maintaining public confidence in the public health system.We developed a multi-criteria decision analysis model to explore regulatory decision-making in the context of emerging vaccine safety signals during a pandemic. We simulated vaccine safety surveillance system capabilities and used an age-structured compartmental model to develop potential pandemic scenarios. We used an expert-derived multi-attribute utility function to evaluate potential regulatory responses by combining four outcome measures into a single measure of interest: 1 expected vaccination benefit from averted influenza; 2 expected vaccination risk from vaccine-associated febrile seizures; 3 expected vaccination risk from vaccine-associated Guillain-Barre Syndrome; and 4 expected change in vaccine-seeking behavior in future influenza seasons.Over multiple scenarios, risk communication, with or without suspension of vaccination of high-risk persons, were the consistently preferred regulatory responses over no action or general suspension when safety signals were detected during a pandemic influenza. On average, the expert panel valued near-term vaccine-related outcomes relative to long-term projected outcomes by 3:1. However, when decision-makers had minimal ability to influence near-term outcomes, the response was selected primarily by projected impacts on future vaccine-seeking behavior.The selected regulatory response depends on how quickly a vaccine safety signal is identified relative to the peak of the pandemic and the initiation of vaccination. Our analysis suggested two areas for future investment: efforts to improve the size and timeliness of the surveillance system and behavioral research to understand changes in vaccine-seeking behavior.

  12. An Optimization Model of Multi-Intersection Signal Control for Trunk Road under Collaborative Information

    Directory of Open Access Journals (Sweden)

    Xun Li

    2017-01-01

    Full Text Available We proposed a signal control optimization model for urban main trunk line intersections. Four-phase intersection was analyzed and modeled based on the Cell Transmission Model (CTM. CTM and signal control model in our study had both been improved for multi-intersections by three-phase theory and information-exchanging. To achieve a real-time application, an improved genetic algorithm (GA was proposed finally, the DISCO traffic simulation software was used for numerical simulation experiment, and comparisons with the standard GA and CTM were reported in this paper. Experimental results indicate that our searching time is less than that of SGA by 38%, and our method needs only 1/3 iteration time of SGA. According to our DISCO traffic simulation processing, compared with SGA, if the input traffic flow is changed from free phase to synchronized phase, for example, less than 900 vel/h, the delay time can reduce to 87.99% by our method, and the minimum delay time is 77.76% of existing method. Furthermore, if input traffic volume is increased to 1200 vel/h or more at the synchronized phase, the summary and minimum values of average delay time are reduced to 81.16% and 75.83%, respectively, and the average delay time is reduced to 17.72 seconds.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

    The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result, the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated, and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures. (paper)

  14. Effect of LIPUS on inflammatory factors, cell apoptosis and integrin signaling pathway in osteoarthritis animal models

    Directory of Open Access Journals (Sweden)

    Li-Cai Zhang

    2017-05-01

    Full Text Available Objective: To study the effect of low-intensity pulsed ultrasound (LIPUS on inflammatory factors, cell apoptosis and integrin signaling pathway in osteoarthritis animal models. Methods: Male New Zealand white rabbits were selected as the experimental animals and randomly divided into sham group, osteoarthritis model group (OA group and LIPUS intervention group (LIPUS group, animal models with osteoarthritis in hind limb knee joint were established and then given LIPUS intervention. 6 weeks after the intervention, the articular cartilage was separated to detect the expression of inflammatory factors, cell apoptosis molecules and integrin signaling pathway molecules. Results: OPN, NO, IL-1β, TNF-α, Fas, FasL, LC3-II, Beclin-1, Integrinβ1, FAK, ERK1/2, JNK, p38MAPK, MMP-1 and MMP-3 protein expression in articular cartilage of OA group were significantly higher than those of Sham group while Col-I and Col-II protein expression were significantly lower than those of Sham group; OPN, NO, IL-1β, TNF-α, Fas, FasL, LC3-II, Beclin-1, Integrinβ1, FAK, ERK1/2, JNK, p38MAPK, MMP-1 and MMP-3 protein expression in articular cartilage of LIPUS group were significantly lower than those of OA group while Col-I and Col-II protein expression were significantly higher than those of OA group. Conclusion: LIPUS has inhibiting effect on the inflammation, apoptosis and integrin signaling pathway in articular cartilage of osteoarthritis animal models, and it can promote the repair of articular cartilage.

  15. Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks

    Directory of Open Access Journals (Sweden)

    Kirouac Daniel C

    2012-05-01

    Full Text Available Abstract Background Understanding the information-processing capabilities of signal transduction networks, how those networks are disrupted in disease, and rationally designing therapies to manipulate diseased states require systematic and accurate reconstruction of network topology. Data on networks central to human physiology, such as the inflammatory signalling networks analyzed here, are found in a multiplicity of on-line resources of pathway and interactome databases (Cancer CellMap, GeneGo, KEGG, NCI-Pathway Interactome Database (NCI-PID, PANTHER, Reactome, I2D, and STRING. We sought to determine whether these databases contain overlapping information and whether they can be used to construct high reliability prior knowledge networks for subsequent modeling of experimental data. Results We have assembled an ensemble network from multiple on-line sources representing a significant portion of all machine-readable and reconcilable human knowledge on proteins and protein interactions involved in inflammation. This ensemble network has many features expected of complex signalling networks assembled from high-throughput data: a power law distribution of both node degree and edge annotations, and topological features of a “bow tie” architecture in which diverse pathways converge on a highly conserved set of enzymatic cascades focused around PI3K/AKT, MAPK/ERK, JAK/STAT, NFκB, and apoptotic signaling. Individual pathways exhibit “fuzzy” modularity that is statistically significant but still involving a majority of “cross-talk” interactions. However, we find that the most widely used pathway databases are highly inconsistent with respect to the actual constituents and interactions in this network. Using a set of growth factor signalling networks as examples (epidermal growth factor, transforming growth factor-beta, tumor necrosis factor, and wingless, we find a multiplicity of network topologies in which receptors couple to downstream

  16. Proposition of delay model for signalized intersections with queueing theory analytical models usage

    Directory of Open Access Journals (Sweden)

    Grzegorz SIERPIŃSKI

    2007-01-01

    Full Text Available Time delay on intersections is a very important transport problem. Thearticle includes a proposition of time delay model. Variance of service times is considered by used average waiting time in queue for queuing system with compressed queuing processes usage as a part of proposed time delays model.

  17. Predicting seizure by modeling synaptic plasticity based on EEG signals - a case study of inherited epilepsy

    Science.gov (United States)

    Zhang, Honghui; Su, Jianzhong; Wang, Qingyun; Liu, Yueming; Good, Levi; Pascual, Juan M.

    2018-03-01

    This paper explores the internal dynamical mechanisms of epileptic seizures through quantitative modeling based on full brain electroencephalogram (EEG) signals. Our goal is to provide seizure prediction and facilitate treatment for epileptic patients. Motivated by an earlier mathematical model with incorporated synaptic plasticity, we studied the nonlinear dynamics of inherited seizures through a differential equation model. First, driven by a set of clinical inherited electroencephalogram data recorded from a patient with diagnosed Glucose Transporter Deficiency, we developed a dynamic seizure model on a system of ordinary differential equations. The model was reduced in complexity after considering and removing redundancy of each EEG channel. Then we verified that the proposed model produces qualitatively relevant behavior which matches the basic experimental observations of inherited seizure, including synchronization index and frequency. Meanwhile, the rationality of the connectivity structure hypothesis in the modeling process was verified. Further, through varying the threshold condition and excitation strength of synaptic plasticity, we elucidated the effect of synaptic plasticity to our seizure model. Results suggest that synaptic plasticity has great effect on the duration of seizure activities, which support the plausibility of therapeutic interventions for seizure control.

  18. Human-like motion planning model for driving in signalized intersections

    Directory of Open Access Journals (Sweden)

    Yanlei Gu

    2017-10-01

    Full Text Available Highly automated and fully autonomous vehicles are much more likely to be accepted if they react in the same way as human drivers do, especially in a hybrid traffic situation, which allows autonomous vehicles and human-driven vehicles to share the same road. This paper proposes a human-like motion planning model to represent how human drivers assess environments and operate vehicles in signalized intersections. The developed model consists of a pedestrian intention detection model, gap detection model, and vehicle control model. These three submodels are individually responsible for situation assessment, decision making, and action, and also depend on each other in the process of motion planning. In addition, these submodels are constructed and learned on the basis of human drivers' data collected from real traffic environments. To verify the effectiveness of the proposed motion planning model, we compared the proposed model with actual human driver and pedestrian data. The experimental results showed that our proposed model and actual human driver behaviors are highly similar with respect to gap acceptance in intersections.

  19. Development of a RF large signal MOSFET model, based on an equivalent circuit, and comparison with the BSIM3v3 compact model.

    NARCIS (Netherlands)

    Vandamme, E.P.; Schreurs, D.; Dinther, van C.H.J.; Badenes, G.; Deferm, L.

    2002-01-01

    The improved RF performance of silicon-based technologies over the years and their potential use in telecommunication applications has increased the research in RF modelling of MOS transistors. Especially for analog circuits, accurate RF small signal and large signal transistor models are required.

  20. Modeling the signaling endosome hypothesis: Why a drive to the nucleus is better than a (random walk

    Directory of Open Access Journals (Sweden)

    Howe Charles L

    2005-10-01

    Full Text Available Abstract Background Information transfer from the plasma membrane to the nucleus is a universal cell biological property. Such information is generally encoded in the form of post-translationally modified protein messengers. Textbook signaling models typically depend upon the diffusion of molecular signals from the site of initiation at the plasma membrane to the site of effector function within the nucleus. However, such models fail to consider several critical constraints placed upon diffusion by the cellular milieu, including the likelihood of signal termination by dephosphorylation. In contrast, signaling associated with retrogradely transported membrane-bounded organelles such as endosomes provides a dephosphorylation-resistant mechanism for the vectorial transmission of molecular signals. We explore the relative efficiencies of signal diffusion versus retrograde transport of signaling endosomes. Results Using large-scale Monte Carlo simulations of diffusing STAT-3 molecules coupled with probabilistic modeling of dephosphorylation kinetics we found that predicted theoretical measures of STAT-3 diffusion likely overestimate the effective range of this signal. Compared to the inherently nucleus-directed movement of retrogradely transported signaling endosomes, diffusion of STAT-3 becomes less efficient at information transfer in spatial domains greater than 200 nanometers from the plasma membrane. Conclusion Our model suggests that cells might utilize two distinct information transmission paradigms: 1 fast local signaling via diffusion over spatial domains on the order of less than 200 nanometers; 2 long-distance signaling via information packets associated with the cytoskeletal transport apparatus. Our model supports previous observations suggesting that the signaling endosome hypothesis is a subset of a more general hypothesis that the most efficient mechanism for intracellular signaling-at-a-distance involves the association of signaling

  1. Optimal experimental design in an epidermal growth factor receptor signalling and down-regulation model.

    Science.gov (United States)

    Casey, F P; Baird, D; Feng, Q; Gutenkunst, R N; Waterfall, J J; Myers, C R; Brown, K S; Cerione, R A; Sethna, J P

    2007-05-01

    We apply the methods of optimal experimental design to a differential equation model for epidermal growth factor receptor signalling, trafficking and down-regulation. The model incorporates the role of a recently discovered protein complex made up of the E3 ubiquitin ligase, Cbl, the guanine exchange factor (GEF), Cool-1 (beta -Pix) and the Rho family G protein Cdc42. The complex has been suggested to be important in disrupting receptor down-regulation. We demonstrate that the model interactions can accurately reproduce the experimental observations, that they can be used to make predictions with accompanying uncertainties, and that we can apply ideas of optimal experimental design to suggest new experiments that reduce the uncertainty on unmeasurable components of the system.

  2. Modeling the intra- and extracellular cytokine signaling pathway under heat stroke in the liver.

    Directory of Open Access Journals (Sweden)

    Maria Rodriguez-Fernandez

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

  3. Histopathologic correlation of magnetic resonance imaging signal patterns in a spinal cord injury model.

    Science.gov (United States)

    Weirich, S D; Cotler, H B; Narayana, P A; Hazle, J D; Jackson, E F; Coupe, K J; McDonald, C L; Langford, L A; Harris, J H

    1990-07-01

    Magnetic resonance imaging (MRI) provides a noninvasive method of monitoring the pathologic response to spinal cord injury. Specific MR signal intensity patterns appear to correlate with degrees of improvement in the neurologic status in spinal cord injury patients. Histologic correlation of two types of MR signal intensity patterns are confirmed in the current study using a rat animal model. Adult male Sprague-Dawley rats underwent spinal cord trauma at the midthoracic level using a weight-dropping technique. After laminectomy, 5- and 10-gm brass weights were dropped from designated heights onto a 0.1-gm impounder placed on the exposed dura. Animals allowed to regain consciousness demonstrated variable recovery of hind limb paraplegia. Magnetic resonance images were obtained from 2 hours to 1 week after injury using a 2-tesla MRI/spectrometer. Sacrifice under anesthesia was performed by perfusive fixation; spinal columns were excised en bloc, embedded, sectioned, and observed with the compound light microscope. Magnetic resonance axial images obtained during the time sequence after injury demonstrate a distinct correlation between MR signal intensity patterns and the histologic appearance of the spinal cord. Magnetic resonance imaging delineates the pathologic processes resulting from acute spinal cord injury and can be used to differentiate the type of injury and prognosis.

  4. Collective Cellular Decision-Making Gives Developmental Plasticity: A Model of Signaling in Branching Roots

    Science.gov (United States)

    McCleery, W. Tyler; Mohd-Radzman, Nadiatul A.; Grieneisen, Veronica A.

    Cells within tissues can be regarded as autonomous entities that respond to their local environment and signaling from neighbors. Cell coordination is particularly important in plants, where root architecture must strategically invest resources for growth to optimize nutrient acquisition. Thus, root cells are constantly adapting to environmental cues and neighbor communication in a non-linear manner. To explain such plasticity, we view the root as a swarm of coupled multi-cellular structures, ''metamers'', rather than as a continuum of identical cells. These metamers are individually programmed to achieve a local objective - developing a lateral root primordia, which aids in local foraging of nutrients. Collectively, such individual attempts may be halted, structuring root architecture as an emergent behavior. Each metamer's decision to branch is coordinated locally and globally through hormone signaling, including processes of controlled diffusion, active polar transport, and dynamic feedback. We present a physical model of the signaling mechanism that coordinates branching decisions in response to the environment. This work was funded by the European Commission 7th Framework Program, Project No. 601062, SWARM-ORGAN.

  5. Robustness of digitally modulated signal features against variation in HF noise model

    Directory of Open Access Journals (Sweden)

    Shoaib Mobien

    2011-01-01

    Full Text Available Abstract High frequency (HF band has both military and civilian uses. It can be used either as a primary or backup communication link. Automatic modulation classification (AMC is of an utmost importance in this band for the purpose of communications monitoring; e.g., signal intelligence and spectrum management. A widely used method for AMC is based on pattern recognition (PR. Such a method has two main steps: feature extraction and classification. The first step is generally performed in the presence of channel noise. Recent studies show that HF noise could be modeled by Gaussian or bi-kappa distributions, depending on day-time. Therefore, it is anticipated that change in noise model will have impact on features extraction stage. In this article, we investigate the robustness of well known digitally modulated signal features against variation in HF noise. Specifically, we consider temporal time domain (TTD features, higher order cumulants (HOC, and wavelet based features. In addition, we propose new features extracted from the constellation diagram and evaluate their robustness against the change in noise model. This study is targeting 2PSK, 4PSK, 8PSK, 16QAM, 32QAM, and 64QAM modulations, as they are commonly used in HF communications.

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

    Directory of Open Access Journals (Sweden)

    Zhengguo Shang

    2009-05-01

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

  7. Traffic Congestion Evaluation and Signal Control Optimization Based on Wireless Sensor Networks: Model and Algorithms

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2012-01-01

    Full Text Available This paper presents the model and algorithms for traffic flow data monitoring and optimal traffic light control based on wireless sensor networks. Given the scenario that sensor nodes are sparsely deployed along the segments between signalized intersections, an analytical model is built using continuum traffic equation and develops the method to estimate traffic parameter with the scattered sensor data. Based on the traffic data and principle of traffic congestion formation, we introduce the congestion factor which can be used to evaluate the real-time traffic congestion status along the segment and to predict the subcritical state of traffic jams. The result is expected to support the timing phase optimization of traffic light control for the purpose of avoiding traffic congestion before its formation. We simulate the traffic monitoring based on the Mobile Century dataset and analyze the performance of traffic light control on VISSIM platform when congestion factor is introduced into the signal timing optimization model. The simulation result shows that this method can improve the spatial-temporal resolution of traffic data monitoring and evaluate traffic congestion status with high precision. It is helpful to remarkably alleviate urban traffic congestion and decrease the average traffic delays and maximum queue length.

  8. Multi-factor models and signal processing techniques application to quantitative finance

    CERN Document Server

    Darolles, Serges; Jay, Emmanuelle

    2013-01-01

    With recent outbreaks of multiple large-scale financial crises, amplified by interconnected risk sources, a new paradigm of fund management has emerged. This new paradigm leverages "embedded" quantitative processes and methods to provide more transparent, adaptive, reliable and easily implemented "risk assessment-based" practices.This book surveys the most widely used factor models employed within the field of financial asset pricing. Through the concrete application of evaluating risks in the hedge fund industry, the authors demonstrate that signal processing techniques are an intere

  9. Dihydrotestosterone deteriorates cardiac insulin signaling and glucose transport in the rat model of polycystic ovary syndrome.

    Science.gov (United States)

    Tepavčević, Snežana; Vojnović Milutinović, Danijela; Macut, Djuro; Žakula, Zorica; Nikolić, Marina; Božić-Antić, Ivana; Romić, Snježana; Bjekić-Macut, Jelica; Matić, Gordana; Korićanac, Goran

    2014-05-01

    It is supposed that women with polycystic ovary syndrome (PCOS) are prone to develop cardiovascular disease as a consequence of multiple risk factors that are mostly related to the state of insulin resistance and consequent hyperinsulinemia. In the present study, we evaluated insulin signaling and glucose transporters (GLUT) in cardiac cells of dihydrotestosterone (DHT) treated female rats as an animal model of PCOS. Expression of proteins involved in cardiac insulin signaling pathways and glucose transporters, as well as their phosphorylation or intracellular localization were studied by Western blot analysis in DHT-treated and control rats. Treatment with DHT resulted in increased body mass, absolute mass of the heart, elevated plasma insulin concentration, dyslipidemia and insulin resistance. At the molecular level, DHT treatment did not change protein expression of cardiac insulin receptor and insulin receptor substrate 1, while phosphorylation of the substrate at serine 307 was increased. Unexpectedly, although expression of downstream Akt kinase and its phosphorylation at threonine 308 were not altered, phosphorylation of Akt at serine 473 was increased in the heart of DHT-treated rats. In contrast, expression and phosphorylation of extracellular signal regulated kinases 1/2 were decreased. Plasma membrane contents of GLUT1 and GLUT4 were decreased, as well as the expression of GLUT4 in cardiac cells at the end of androgen treatment. The obtained results provide evidence for alterations in expression and especially in functional characteristics of insulin signaling molecules and glucose transporters in the heart of DHT-treated rats with PCOS, indicating impaired cardiac insulin action. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. Relieving the Impact of Transit Signal Priority on Passenger Cars through a Bilevel Model

    Directory of Open Access Journals (Sweden)

    Ding Wang

    2017-01-01

    Full Text Available Transit signal priority (TSP is an effective control strategy to improve transit operations on the urban network. However, the TSP may sacrifice the right-of-way of vehicles from side streets which have only few transit vehicles; therefore, how to minimize the negative impact of TSP strategy on the side streets is an important issue to be addressed. Concerning the typical mixed-traffic flow pattern and heavy transit volume in China, a bilevel model is proposed in this paper: the upper-level model focused on minimizing the vehicle delay in the nonpriority direction while ensuring acceptable delay variation in transit priority direction, and the lower-level model aimed at minimizing the average passenger delay in the entire intersection. The parameters which will affect the efficiency of the bilevel model have been analyzed based on a hypothetical intersection. Finally, a real-world intersection has been studied, and the average vehicle delay in the nonpriority direction decreased 11.28 s and 22.54 s (under different delay variation constraint compared to the models that only minimize average passenger delay, while the vehicle delay in the priority direction increased only 1.37 s and 2.87 s; the results proved the practical applicability and efficiency of the proposed bilevel model.

  11. Using Regularization to Infer Cell Line Specificity in Logical Network Models of Signaling Pathways

    Directory of Open Access Journals (Sweden)

    Sébastien De Landtsheer

    2018-05-01

    Full Text Available Understanding the functional properties of cells of different origins is a long-standing challenge of personalized medicine. Especially in cancer, the high heterogeneity observed in patients slows down the development of effective cures. The molecular differences between cell types or between healthy and diseased cellular states are usually determined by the wiring of regulatory networks. Understanding these molecular and cellular differences at the systems level would improve patient stratification and facilitate the design of rational intervention strategies. Models of cellular regulatory networks frequently make weak assumptions about the distribution of model parameters across cell types or patients. These assumptions are usually expressed in the form of regularization of the objective function of the optimization problem. We propose a new method of regularization for network models of signaling pathways based on the local density of the inferred parameter values within the parameter space. Our method reduces the complexity of models by creating groups of cell line-specific parameters which can then be optimized together. We demonstrate the use of our method by recovering the correct topology and inferring accurate values of the parameters of a small synthetic model. To show the value of our method in a realistic setting, we re-analyze a recently published phosphoproteomic dataset from a panel of 14 colon cancer cell lines. We conclude that our method efficiently reduces model complexity and helps recovering context-specific regulatory information.

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  13. Ocean angular momentum signals in a climate model and implications for Earth rotation

    Science.gov (United States)

    Ponte, R. M.; Rajamony, J.; Gregory, J. M.

    2002-03-01

    Estimates of ocean angular momentum (OAM) provide an integrated measure of variability in ocean circulation and mass fields and can be directly related to observed changes in Earth rotation. We use output from a climate model to calculate 240 years of 3-monthly OAM values (two equatorial terms L1 and L2, related to polar motion or wobble, and axial term L3, related to length of day variations) representing the period 1860-2100. Control and forced runs permit the study of the effects of natural and anthropogenically forced climate variability on OAM. All OAM components exhibit a clear annual cycle, with large decadal modulations in amplitude, and also longer period fluctuations, all associated with natural climate variability in the model. Anthropogenically induced signals, inferred from the differences between forced and control runs, include an upward trend in L3, related to inhomogeneous ocean warming and increases in the transport of the Antarctic Circumpolar Current, and a significantly weaker seasonal cycle in L2 in the second half of the record, related primarily to changes in seasonal bottom pressure variability in the Southern Ocean and North Pacific. Variability in mass fields is in general more important to OAM signals than changes in circulation at the seasonal and longer periods analyzed. Relation of OAM signals to changes in surface atmospheric forcing are discussed. The important role of the oceans as an excitation source for the annual, Chandler and Markowitz wobbles, is confirmed. Natural climate variability in OAM and related excitation is likely to measurably affect the Earth rotation, but anthropogenically induced effects are comparatively weak.

  14. Radial plasma drifts deduced from VLF whistler mode signals - A modelling study

    Science.gov (United States)

    Poulter, E. M.; Andrews, M. K.; Bailey, G. J.; Moffett, R. J.

    1984-05-01

    VLF whistler mode signals have previously been used to infer radial plasma drifts in the equatorial plane of the plasmasphere and the field-aligned ionosphere-protonosphere coupling fluxes. Physical models of the plasmasphere consisting of O(+) adn H(+) ions along dipole magnetic field lines, and including radial E x B drifts, are applied to a mid-latitude flux tube appropriate to whistler mode signals received at Wellington, New Zealand, from the fixed frequency VLF transmitter NLK (18.6 kHz) in Seattle, U.S.A. These models are first shown to provide a good representation of the recorded Doppler shift and group delay data. They are then used to simulate the process of deducing the drifts and fluxes from the recorded data. Provided the initial whistler mode duct latitude and the ionospheric contributions are known, the drifts at the equatorial plane can be estimated to about + or - 20 m/s (approximately 10-15 percent), and the two hemisphere ionosphere-protonosphere coupling fluxes to about + or - 10 to the 12th/sq m-sec (approximately 40 percent).

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

    International Nuclear Information System (INIS)

    Wahl, Elizabeth C.; Aronson, James; Liu, Lichu; Liu, Zhendong; Perrien, Daniel S.; Skinner, Robert A.; Badger, Thomas M.; Ronis, Martin J.J.; Lumpkin, Charles K.

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Michael E. Bond

    2015-11-01

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

  17. Spaced training rescues memory and ERK1/2 signaling in fragile X syndrome model mice.

    Science.gov (United States)

    Seese, Ronald R; Wang, Kathleen; Yao, Yue Qin; Lynch, Gary; Gall, Christine M

    2014-11-25

    Recent studies have shown that short, spaced trains of afferent stimulation produce much greater long-term potentiation (LTP) than that obtained with a single, prolonged stimulation episode. The present studies demonstrate that spaced training regimens, based on these LTP timing rules, facilitate learning in wild-type (WT) mice and can offset learning and synaptic signaling impairments in the fragile X mental retardation 1 (Fmr1) knockout (KO) model of fragile X syndrome. We determined that 5 min of continuous training supports object location memory (OLM) in WT but not Fmr1 KO mice. However, the same amount of training distributed across three short trials, spaced by one hour, produced robust long-term memory in the KOs. At least three training trials were needed to realize the benefit of spacing, and intertrial intervals shorter or longer than 60 min were ineffective. Multiple short training trials also rescued novel object recognition in Fmr1 KOs. The spacing effect was surprisingly potent: just 1 min of OLM training, distributed across three trials, supported robust memory in both genotypes. Spacing also rescued training-induced activation of synaptic ERK1/2 in dorsal hippocampus of Fmr1 KO mice. These results show that a spaced training regimen designed to maximize synaptic potentiation facilitates recognition memory in WT mice and can offset synaptic signaling and memory impairments in a model of congenital intellectual disability.

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

    Science.gov (United States)

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

    2009-01-01

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

  19. A unitary signal-detection model of implicit and explicit memory.

    Science.gov (United States)

    Berry, Christopher J; Shanks, David R; Henson, Richard N A

    2008-10-01

    Do dissociations imply independent systems? In the memory field, the view that there are independent implicit and explicit memory systems has been predominantly supported by dissociation evidence. Here, we argue that many of these dissociations do not necessarily imply distinct memory systems. We review recent work with a single-system computational model that extends signal-detection theory (SDT) to implicit memory. SDT has had a major influence on research in a variety of domains. The current work shows that it can be broadened even further in its range of application. Indeed, the single-system model that we present does surprisingly well in accounting for some key dissociations that have been taken as evidence for independent implicit and explicit memory systems.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-12-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  2. Design of complete software GPS signal simulator with low complexity and precise multipath channel model

    Directory of Open Access Journals (Sweden)

    G. Arul Elango

    2016-09-01

    Full Text Available The need for GPS data simulators have become important due to the tremendous growth in the design of versatile GPS receivers. Commercial hardware and software based GPS simulators are expensive and time consuming. In this work, a low cost simple novel GPS L1 signal simulator is designed for testing and evaluating the performance of software GPS receiver in a laboratory environment. A typical real time paradigm, similar to actual satellite derived GPS signal is created on a computer generated scenario. In this paper, a GPS software simulator is proposed that may offer a lot of analysis and testing flexibility to the researchers and developers as it is totally software based primarily running on a laptop/personal computer without the requirement of any hardware. The proposed GPS simulator allows provision for re-configurability and test repeatability and is developed in VC++ platform to minimize the simulation time. It also incorporates Rayleigh multipath channel fading model under non-line of sight (NLOS conditions. In this work, to efficiently design the simulator, several Rayleigh fading models viz. Inverse Discrete Fourier Transform (IDFT, Filtering White Gaussian Noise (FWFN and modified Sum of Sinusoidal (SOS simulators are tested and compared in terms of accuracy of its first and second order statistical metrics, execution time and the later one is found to be as the best appropriate Rayleigh multipath model suitable for incorporating with GPS simulator. The fading model written in ‘MATLAB’ engine has been linked with software GPS simulator module enable to test GPS receiver’s functionality in different fading environments.

  3. Research on a Small Signal Stability Region Boundary Model of the Interconnected Power System with Large-Scale Wind Power

    Directory of Open Access Journals (Sweden)

    Wenying Liu

    2015-03-01

    Full Text Available For the interconnected power system with large-scale wind power, the problem of the small signal stability has become the bottleneck of restricting the sending-out of wind power as well as the security and stability of the whole power system. Around this issue, this paper establishes a small signal stability region boundary model of the interconnected power system with large-scale wind power based on catastrophe theory, providing a new method for analyzing the small signal stability. Firstly, we analyzed the typical characteristics and the mathematic model of the interconnected power system with wind power and pointed out that conventional methods can’t directly identify the topological properties of small signal stability region boundaries. For this problem, adopting catastrophe theory, we established a small signal stability region boundary model of the interconnected power system with large-scale wind power in two-dimensional power injection space and extended it to multiple dimensions to obtain the boundary model in multidimensional power injection space. Thirdly, we analyzed qualitatively the topological property’s changes of the small signal stability region boundary caused by large-scale wind power integration. Finally, we built simulation models by DIgSILENT/PowerFactory software and the final simulation results verified the correctness and effectiveness of the proposed model.

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

    Directory of Open Access Journals (Sweden)

    David Henriques

    2017-02-01

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

  5. A PSP-based small-signal MOSFET model for both quasi-static and nonquasi-static operations

    NARCIS (Netherlands)

    Aarts, A.C.T.; Smit, G.D.J.; Scholten, A.J.; Klaassen, D.B.M.

    2008-01-01

    In this paper, a small-signal MOSFET model is described, which takes the local effects of both velocity saturation and transverse mobility reduction into account. The model is based on the PSP model and is valid for both quasi-static and nonquasi-static (NQS) operations. Recently, it has been found

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2013-01-01

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

  8. Inhibition of Hedgehog signaling antagonizes serous ovarian cancer growth in a primary xenograft model.

    Directory of Open Access Journals (Sweden)

    Christopher K McCann

    Full Text Available Recent evidence links aberrant activation of Hedgehog (Hh signaling with the pathogenesis of several cancers including medulloblastoma, basal cell, small cell lung, pancreatic, prostate and ovarian. This investigation was designed to determine if inhibition of this pathway could inhibit serous ovarian cancer growth.We utilized an in vivo pre-clinical model of serous ovarian cancer to characterize the anti-tumor activity of Hh pathway inhibitors cyclopamine and a clinically applicable derivative, IPI-926. Primary human serous ovarian tumor tissue was used to generate tumor xenografts in mice that were subsequently treated with cyclopamine or IPI-926.Both compounds demonstrated significant anti-tumor activity as single agents. When IPI-926 was used in combination with paclitaxel and carboplatinum (T/C, no synergistic effect was observed, though sustained treatment with IPI-926 after cessation of T/C continued to suppress tumor growth. Hh pathway activity was analyzed by RT-PCR to assess changes in Gli1 transcript levels. A single dose of IPI-926 inhibited mouse stromal Gli1 transcript levels at 24 hours with unchanged human intra-tumor Gli1 levels. Chronic IPI-926 therapy for 21 days, however, inhibited Hh signaling in both mouse stromal and human tumor cells. Expression data from the micro-dissected stroma in human serous ovarian tumors confirmed the presence of Gli1 transcript and a significant association between elevated Gli1 transcript levels and worsened survival.IPI-926 treatment inhibits serous tumor growth suggesting the Hh signaling pathway contributes to the pathogenesis of ovarian cancer and may hold promise as a novel therapeutic target, especially in the maintenance setting.

  9. Transmission experiment by the simulated LMFBR model and propagation analysis of acoustic signals

    International Nuclear Information System (INIS)

    Kobayashi, Kenji; Yasuda, Tsutomu; Araki, Hitoshi.

    1981-01-01

    Acoustic transducers to detect a boiling of sodium may be installed in the upper structure and at the upper position of reactor vessel wall under constricted conditions. A set of the experiments of transmission of acoustic vibration to various points of the vessel was performed utilizing the half scale-hydraulic flow test facility simulating reactor vessel over the frequency range 20 kHz -- 100 kHz. Acoustic signals from an installed sound source in the core were measured at each point by both hydrophones in the vessel and vibration pickups on the vessel wall. In these experiments transmission of signals to each point of detectors were clearly observed to background noise level. These data have been summarized in terms of the transmission loss and furthermore are compared with background noise level of flow to estimate the feasibility of detection of sodium boiling sound. The ratio of signal to noise was obtained to be about 13 dB by hydrophone in the upper structure, 8 dB by accelerometer and 16 dB by AE-sensor at the upper position on the vessel in experiments used the simulation model. Sound waves emanated due to sodium boiling also propagate along the wall of the vessel may be predicted theoretically. The result of analysis suggests a capability of detection at the upper position of the reactor vessel wall. Leaky Lamb waves of the first symmetric (L 1 ) and of the antisymmetric (F 1 ) mode and shear horizontal wave (SH) have been derived in light of the attenuation due to coupling to liquid sodium as the traveling modes over the frequency range 10 kHz -- 100 kHz up to 50 mm in thickness of the vessel wall. Leaky Lamb wave (L 1 ) and (SH) mode have been proposed theoretically on the some assumption to be most available to detect the boiling sound of sodium propagating along the vessel wall. (author)

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

    Directory of Open Access Journals (Sweden)

    Sadia Benamrouz

    2014-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Keshuang Tang

    2016-12-01

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

  12. A model for tetrapyrrole synthesis as the primary mechanism for plastid-to-nucleus signaling during chloroplast biogenesis

    Directory of Open Access Journals (Sweden)

    Matthew J. Terry

    2013-02-01

    Full Text Available Chloroplast biogenesis involves the co-ordinated expression of the chloroplast and nuclear genomes, requiring information to be sent from the developing chloroplasts to the nucleus. This is achieved through retrograde signaling pathways and can be demonstrated experimentally using the photobleaching herbicide, Norflurazon, which results in chloroplast damage and the reduced expression of many photosynthesis-related, nuclear genes in seedlings. Genetic analysis of this pathway points to a major role for tetrapyrrole synthesis in retrograde signaling, as well as a strong interaction with light-signaling pathways. Currently, the best model to explain the genetic data is that a specific heme pool generated by flux through ferrochelatase-1 functions as a positive signal to promote the expression of genes required for chloroplast development. We propose that this heme-related signal is the primary positive signal during chloroplast biogenesis, and that treatments and mutations affecting chloroplast transcription, RNA editing, translation, or protein import all impact on the synthesis and/or processing of this signal. A positive signal is consistent with the need to provide information on chloroplast status at all times. We further propose that GUN1 normally serves to restrict the production of the heme signal. In addition to a positive signal re-enforcing chloroplast development under normal conditions, aberrant chloroplast development may produce a negative signal due to accumulation of unbound chlorophyll biosynthesis intermediates, such as Mg-porphyrins. Under these conditions a rapid shut-down of tetrapyrrole synthesis is required. We propose that accumulation of these intermediates results in a rapid light-dependent inhibition of nuclear gene expression that is most likely mediated via singlet oxygen generated by photo-excitation of Mg-porphyrins. Thus, the tetrapyrrole pathway may provide both positive and inhibitory signals to control

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

    Directory of Open Access Journals (Sweden)

    Manuel Perez Malumbres

    2013-02-01

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

  14. Analytical models of probability distribution and excess noise factor of solid state photomultiplier signals with crosstalk

    International Nuclear Information System (INIS)

    Vinogradov, S.

    2012-01-01

    Silicon Photomultipliers (SiPM), also called Solid State Photomultipliers (SSPM), are based on Geiger mode avalanche breakdown that is limited by a strong negative feedback. An SSPM can detect and resolve single photons due to the high gain and ultra-low excess noise of avalanche multiplication in this mode. Crosstalk and afterpulsing processes associated with the high gain introduce specific excess noise and deteriorate the photon number resolution of the SSPM. The probabilistic features of these processes are widely studied because of its significance for the SSPM design, characterization, optimization and application, but the process modeling is mostly based on Monte Carlo simulations and numerical methods. In this study, crosstalk is considered to be a branching Poisson process, and analytical models of probability distribution and excess noise factor (ENF) of SSPM signals based on the Borel distribution as an advance on the geometric distribution models are presented and discussed. The models are found to be in a good agreement with the experimental probability distributions for dark counts and a few photon spectrums in a wide range of fired pixels number as well as with observed super-linear behavior of crosstalk ENF.

  15. 3D Organotypic Culture Model to Study Components of ERK Signaling.

    Science.gov (United States)

    Chioni, Athina-Myrto; Bajwa, Rabia Tayba; Grose, Richard

    2017-01-01

    Organotypic models are 3D in vitro representations of an in vivo environment. Their complexity can range from an epidermal replica to the establishment of a cancer microenvironment. These models have been used for many years, in an attempt to mimic the structure and function of cells and tissues found inside the body. Methods for developing 3D organotypic models differ according to the tissue of interest and the experimental design. For example, cultures may be grown submerged in culture medium and or at an air-liquid interface. Our group is focusing on an air-liquid interface 3D organotypic model. These cultures are grown on a nylon membrane-covered metal grid with the cells embedded in a Collagen-Matrigel gel. This allows cells to grow in an air-liquid interface to enable diffusion and nourishment from the medium below. Subsequently, the organotypic cultures can be used for immunohistochemical staining of various components of ERK signaling, which is a key player in mediating communication between cells and their microenvironment.

  16. Signals of dark matter in a supersymmetric two dark matter model

    International Nuclear Information System (INIS)

    Fukuoka, Hiroki; Suematsu, Daijiro; Toma, Takashi

    2011-01-01

    Supersymmetric radiative neutrino mass models have often two dark matter candidates. One is the usual lightest neutralino with odd R parity and the other is a new neutral particle whose stability is guaranteed by a discrete symmetry that forbids tree-level neutrino Yukawa couplings. If their relic abundance is comparable, dark matter phenomenology can be largely different from the minimal supersymmetric standard model (MSSM). We study this in a supersymmetric radiative neutrino mass model with the conserved R parity and a Z 2 symmetry weakly broken by the anomaly effect. The second dark matter with odd parity of this new Z 2 is metastable and decays to the neutralino dark matter. Charged particles and photons associated to this decay can cause the deviation from the expected background of the cosmic rays. Direct search of the neutralino dark matter is also expected to show different features from the MSSM since the relic abundance is not composed of the neutralino dark matter only. We discuss the nature of dark matter in this model by analyzing these signals quantitatively

  17. The TOR Signaling Network in the Model Unicellular Green Alga Chlamydomonas reinhardtii

    Directory of Open Access Journals (Sweden)

    María Esther Pérez-Pérez

    2017-07-01

    Full Text Available Cell growth is tightly coupled to nutrient availability. The target of rapamycin (TOR kinase transmits nutritional and environmental cues to the cellular growth machinery. TOR functions in two distinct multiprotein complexes, termed TOR complex 1 (TORC1 and TOR complex 2 (TORC2. While the structure and functions of TORC1 are highly conserved in all eukaryotes, including algae and plants, TORC2 core proteins seem to be missing in photosynthetic organisms. TORC1 controls cell growth by promoting anabolic processes, including protein synthesis and ribosome biogenesis, and inhibiting catabolic processes such as autophagy. Recent studies identified rapamycin-sensitive TORC1 signaling regulating cell growth, autophagy, lipid metabolism, and central metabolic pathways in the model unicellular green alga Chlamydomonas reinhardtii. The central role that microalgae play in global biomass production, together with the high biotechnological potential of these organisms in biofuel production, has drawn attention to the study of proteins that regulate cell growth such as the TOR kinase. In this review we discuss the recent progress on TOR signaling in algae.

  18. On temporal connectivity of PFC via Gauss-Markov modeling of fNIRS signals.

    Science.gov (United States)

    Aydöre, Sergül; Mihçak, M Kivanç; Ciftçi, Koray; Akin, Ata

    2010-03-01

    Functional near-infrared spectroscopy (fNIRS) is an optical imaging method, which monitors the brain activation by measuring the successive changes in the concentration of oxy- and deoxyhemoglobin in real time. In this study, we present a method to investigate the functional connectivity of prefrontal cortex (PFC) Sby applying a Gauss-Markov model to fNIRS signals. The hemodynamic changes on PFC during the performance of cognitive paradigm are measured by fNIRS for 17 healthy adults. The color-word matching Stroop task is performed to activate 16 different regions of PFC. There are three different types of stimuli in this task, which can be listed as incongruent stimulus (IS), congruent stimulus (CS), and neutral stimulus (NS), respectively. We introduce a new measure, called "information transfer metric" (ITM) for each time sample. The behavior of ITMs during IS are significantly different from the ITMs during CS and NS, which is consistent with the outcome of the previous research, which concentrated on fNIRS signal analysis via color-word matching Stroop task. Our analysis shows that the functional connectivity of PFC is highly relevant with the cognitive load, i.e., functional connectivity increases with the increasing cognitive load.

  19. The TOR Signaling Network in the Model Unicellular Green Alga Chlamydomonas reinhardtii.

    Science.gov (United States)

    Pérez-Pérez, María Esther; Couso, Inmaculada; Crespo, José L

    2017-07-12

    Cell growth is tightly coupled to nutrient availability. The target of rapamycin (TOR) kinase transmits nutritional and environmental cues to the cellular growth machinery. TOR functions in two distinct multiprotein complexes, termed TOR complex 1 (TORC1) and TOR complex 2 (TORC2). While the structure and functions of TORC1 are highly conserved in all eukaryotes, including algae and plants, TORC2 core proteins seem to be missing in photosynthetic organisms. TORC1 controls cell growth by promoting anabolic processes, including protein synthesis and ribosome biogenesis, and inhibiting catabolic processes such as autophagy. Recent studies identified rapamycin-sensitive TORC1 signaling regulating cell growth, autophagy, lipid metabolism, and central metabolic pathways in the model unicellular green alga Chlamydomonas reinhardtii . The central role that microalgae play in global biomass production, together with the high biotechnological potential of these organisms in biofuel production, has drawn attention to the study of proteins that regulate cell growth such as the TOR kinase. In this review we discuss the recent progress on TOR signaling in algae.

  20. A model for the biosynthesis and transport of plasma membrane-associated signaling receptors to the cell surface

    Directory of Open Access Journals (Sweden)

    Sorina Claudia Popescu

    2012-04-01

    Full Text Available Intracellular protein transport is emerging as critical in determining the outcome of receptor-activated signal transduction pathways. In plants, relatively little is known about the nature of the molecular components and mechanisms involved in coordinating receptor synthesis and transport to the cell surface. Recent advances in this field indicate that signaling pathways and intracellular transport machinery converge and coordinate to render receptors competent for signaling at their plasma membrane activity sites. The biogenesis and transport to the cell surface of signaling receptors appears to require both general trafficking and receptor-specific factors. Several molecular determinants, residing or associated with compartments of the secretory pathway and known to influence aspects in receptor biogenesis, are discussed and integrated into a predictive cooperative model for the functional expression of signaling receptors at the plasma membrane.

  1. Receiving more than data - a signal model, theory and implementation of a cognitive IEEE 802.15.4 receiver

    Directory of Open Access Journals (Sweden)

    Tim Esemann

    2016-09-01

    Full Text Available Standard medium access schemes sense the channel immediately prior transmission, but are blind during the transmission. Therefore, standard transceivers have limited cognitive capabilities which are important for operation in heterogeneous radio environments. Specifically, mobile interferers move gradually into the reception range before actually causing collisions. These gradual interferences cannot yet be detected, and upcoming collisions cannot be predicted. We present a theoretical analysis of the received and demodulated signal. This analysis and the derived signal model verifies that the received signal contains more than transmitted data exclusively. Enhanced signal processing extracts signal components of an interference at the receiver and enables advanced interference detection to provide information about approaching mobile interferers. Our theoretical analysis is evaluated by simulations and experiments with an IEEE 802.15.4 transmitter and an extended cognitive receiver.

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

    Science.gov (United States)

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

    2015-08-01

    Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. Copyright © 2015 the American Physiological Society.

  3. Modeling the response of small myelinated axons in a compound nerve to kilohertz frequency signals.

    Science.gov (United States)

    Pelot, N A; Behrend, C E; Grill, W M

    2017-08-01

    There is growing interest in electrical neuromodulation of peripheral nerves, particularly autonomic nerves, to treat various diseases. Electrical signals in the kilohertz frequency (KHF) range can produce different responses, including conduction block. For example, EnteroMedics' vBloc ® therapy for obesity delivers 5 kHz stimulation to block the abdominal vagus nerves, but the mechanisms of action are unclear. We developed a two-part computational model, coupling a 3D finite element model of a cuff electrode around the human abdominal vagus nerve with biophysically-realistic electrical circuit equivalent (cable) model axons (1, 2, and 5.7 µm in diameter). We developed an automated algorithm to classify conduction responses as subthreshold (transmission), KHF-evoked activity (excitation), or block. We quantified neural responses across kilohertz frequencies (5-20 kHz), amplitudes (1-8 mA), and electrode designs. We found heterogeneous conduction responses across the modeled nerve trunk, both for a given parameter set and across parameter sets, although most suprathreshold responses were excitation, rather than block. The firing patterns were irregular near transmission and block boundaries, but otherwise regular, and mean firing rates varied with electrode-fibre distance. Further, we identified excitation responses at amplitudes above block threshold, termed 're-excitation', arising from action potentials initiated at virtual cathodes. Excitation and block thresholds decreased with smaller electrode-fibre distances, larger fibre diameters, and lower kilohertz frequencies. A point source model predicted a larger fraction of blocked fibres and greater change of threshold with distance as compared to the realistic cuff and nerve model. Our findings of widespread asynchronous KHF-evoked activity suggest that conduction block in the abdominal vagus nerves is unlikely with current clinical parameters. Our results indicate that compound neural or downstream muscle

  4. Modeling the response of small myelinated axons in a compound nerve to kilohertz frequency signals

    Science.gov (United States)

    Pelot, N. A.; Behrend, C. E.; Grill, W. M.

    2017-08-01

    Objective. There is growing interest in electrical neuromodulation of peripheral nerves, particularly autonomic nerves, to treat various diseases. Electrical signals in the kilohertz frequency (KHF) range can produce different responses, including conduction block. For example, EnteroMedics’ vBloc® therapy for obesity delivers 5 kHz stimulation to block the abdominal vagus nerves, but the mechanisms of action are unclear. Approach. We developed a two-part computational model, coupling a 3D finite element model of a cuff electrode around the human abdominal vagus nerve with biophysically-realistic electrical circuit equivalent (cable) model axons (1, 2, and 5.7 µm in diameter). We developed an automated algorithm to classify conduction responses as subthreshold (transmission), KHF-evoked activity (excitation), or block. We quantified neural responses across kilohertz frequencies (5-20 kHz), amplitudes (1-8 mA), and electrode designs. Main results. We found heterogeneous conduction responses across the modeled nerve trunk, both for a given parameter set and across parameter sets, although most suprathreshold responses were excitation, rather than block. The firing patterns were irregular near transmission and block boundaries, but otherwise regular, and mean firing rates varied with electrode-fibre distance. Further, we identified excitation responses at amplitudes above block threshold, termed ‘re-excitation’, arising from action potentials initiated at virtual cathodes. Excitation and block thresholds decreased with smaller electrode-fibre distances, larger fibre diameters, and lower kilohertz frequencies. A point source model predicted a larger fraction of blocked fibres and greater change of threshold with distance as compared to the realistic cuff and nerve model. Significance. Our findings of widespread asynchronous KHF-evoked activity suggest that conduction block in the abdominal vagus nerves is unlikely with current clinical parameters. Our

  5. MOTION ARTIFACT REDUCTION IN FUNCTIONAL NEAR INFRARED SPECTROSCOPY SIGNALS BY AUTOREGRESSIVE MOVING AVERAGE MODELING BASED KALMAN FILTERING

    Directory of Open Access Journals (Sweden)

    MEHDI AMIAN

    2013-10-01

    Full Text Available Functional near infrared spectroscopy (fNIRS is a technique that is used for noninvasive measurement of the oxyhemoglobin (HbO2 and deoxyhemoglobin (HHb concentrations in the brain tissue. Since the ratio of the concentration of these two agents is correlated with the neuronal activity, fNIRS can be used for the monitoring and quantifying the cortical activity. The portability of fNIRS makes it a good candidate for studies involving subject's movement. The fNIRS measurements, however, are sensitive to artifacts generated by subject's head motion. This makes fNIRS signals less effective in such applications. In this paper, the autoregressive moving average (ARMA modeling of the fNIRS signal is proposed for state-space representation of the signal which is then fed to the Kalman filter for estimating the motionless signal from motion corrupted signal. Results are compared to the autoregressive model (AR based approach, which has been done previously, and show that the ARMA models outperform AR models. We attribute it to the richer structure, containing more terms indeed, of ARMA than AR. We show that the signal to noise ratio (SNR is about 2 dB higher for ARMA based method.

  6. Electromigration inside logic cells modeling, analyzing and mitigating signal electromigration in nanoCMOS

    CERN Document Server

    Posser, Gracieli; Reis, Ricardo

    2017-01-01

    This book describes new and effective methodologies for modeling, analyzing and mitigating cell-internal signal electromigration in nanoCMOS, with significant circuit lifetime improvements and no impact on performance, area and power. The authors are the first to analyze and propose a solution for the electromigration effects inside logic cells of a circuit. They show in this book that an interconnect inside a cell can fail reducing considerably the circuit lifetime and they demonstrate a methodology to optimize the lifetime of circuits, by placing the output, Vdd and Vss pin of the cells in the less critical regions, where the electromigration effects are reduced. Readers will be enabled to apply this methodology only for the critical cells in the circuit, avoiding impact in the circuit delay, area and performance, thus increasing the lifetime of the circuit without loss in other characteristics. .

  7. Found in Translation: Applying Lessons from Model Systems to Strigolactone Signaling in Parasitic Plants.

    Science.gov (United States)

    Lumba, Shelley; Subha, Asrinus; McCourt, Peter

    2017-07-01

    Strigolactones (SLs) are small molecules that act as endogenous hormones to regulate plant development as well as exogenous cues that help parasitic plants to infect their hosts. Given that parasitic plants are experimentally challenging systems, researchers are using two approaches to understand how they respond to host-derived SLs. The first involves extrapolating information on SLs from model genetic systems to dissect their roles in parasitic plants. The second uses chemicals to probe SL signaling directly in the parasite Striga hermonthica. These approaches indicate that parasitic plants have co-opted a family of α/β hydrolases to perceive SLs. The importance of this genetic and chemical information cannot be overstated since parasitic plant infestations are major obstacles to food security in the developing world. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Signals for the QCD phase transition and critical point in a Langevin dynamical model

    International Nuclear Information System (INIS)

    Herold, Christoph; Bleicher, Marcus; Yan, Yu-Peng

    2013-01-01

    The search for the critical point is one of the central issues that will be investigated in the upcoming FAIR project. For a profound theoretical understanding of the expected signals we go beyond thermodynamic studies and present a fully dynamical model for the chiral and deconfinement phase transition in heavy ion collisions. The corresponding order parameters are propagated by Langevin equations of motions on a thermal background provided by a fluid dynamically expanding plasma of quarks. By that we are able to describe nonequilibrium effects occurring during the rapid expansion of a hot fireball. For an evolution through the phase transition the formation of a supercooled phase and its subsequent decay crucially influence the trajectories in the phase diagram and lead to a significant reheating of the quark medium at highest baryon densities. Furthermore, we find inhomogeneous structures with high density domains along the first order transition line within single events.

  9. [Digital signal processing of a novel neuron discharge model stimulation strategy for cochlear implants].

    Science.gov (United States)

    Yang, Yiwei; Xu, Yuejin; Miu, Jichang; Zhou, Linghong; Xiao, Zhongju

    2012-10-01

    To apply the classic leakage integrate-and-fire models, based on the mechanism of the generation of physiological auditory stimulation, in the information processing coding of cochlear implants to improve the auditory result. The results of algorithm simulation in digital signal processor (DSP) were imported into Matlab for a comparative analysis. Compared with CIS coding, the algorithm of membrane potential integrate-and-fire (MPIF) allowed more natural pulse discharge in a pseudo-random manner to better fit the physiological structures. The MPIF algorithm can effectively solve the problem of the dynamic structure of the delivered auditory information sequence issued in the auditory center and allowed integration of the stimulating pulses and time coding to ensure the coherence and relevance of the stimulating pulse time.

  10. Establishment of a Ewing's sarcoma mouse model: JAK/STAT signalling in Ewing's sarcoma

    International Nuclear Information System (INIS)

    Sax, B.

    2011-01-01

    The Ewing's sarcoma family of tumours (ESFT) comprises paediatric cancers of bone and soft tissue which presumably originate from mesenchymal progenitor cells(MPC). One hallmark of ESFT is the presence of a chromosomal translocation. In 90% of the cases chromosome 11 fuses with chromosome 22. This translocation generates the EWS/FLI-1 fusion which acts as an aberrant transcription factor deregulating many genes involved in tumour development. Surgery and/or radiotherapy combined with chemotherapy are the usual forms of treatment for ESFT. But since there is only little progress in the field of chemotherapy the need for an animal model for pre-clinical drug testing is evident. Thus, the main focus of this thesis was to establish a mouse model that develops sarcomas resembling the phenotype of ESFT. We used a conditional EWS/FLI-1 mouse model, which upon Cre activity (controlled by a tissue specific promotor) expressed EWS/FLI-1 in the targeted cells. Since ESFT arises in bone and surrounding soft tissue we decided to direct expression of EWS/FLI-1 to the mesenchymal lineage by using different Cre lines. Only when using the Prx1Cre, double transgenic mice tolerated EWS/FLI-1 expression. We observed developmental abnormalities with severe skeletal deformations. Bone formation was impaired due to the absence of mature chondrocytes and osteoblasts and hence a lack of calcified bone. The lack of mature bone cells in EWS/FLI-1 expressing Prx1Cre mice supports in vitro data showing that EWS/FLI-1 impedes differentiation of murine mesenchymal progenitor cells. Currently, the project is extended to analysis of an inducible Prx1Cre system which circumvents the early lethality of Prx1Cre EF mice. This should provide the basis for tumour formation in these mice and hence the development of an appropriate mouse model for pre-clinical research. In the second project of my PhD thesis, the role of the Janus Kinase/Signal Transducer and Activator of Transcription (JAK

  11. Two time-delay dynamic model on the transmission of malicious signals in wireless sensor network

    International Nuclear Information System (INIS)

    Keshri, Neha; Mishra, Bimal Kumar

    2014-01-01

    Highlights: • Role of time delay to reduce the adversary effect in WSN is explored. • Model with two time delays is proposed to analyse spread of malicious signal in WSN. • Dynamical behaviour of worm-free equilibrium and endemic equilibrium is shown. • Threshold condition for switch of stability are obtained analytically. • Relation between stability and the two time delays is also explored. - Abstract: Deployed in a hostile environment, motes of a Wireless sensor network (WSN) could be easily compromised by the attackers because of several constraints such as limited processing capabilities, memory space, and limited battery life time etc. While transmitting the data to their neighbour motes within the network, motes are easily compromised due to resource constraints. Here time delay can play an efficient role to reduce the adversary effect on motes. In this paper, we propose an epidemic model SEIR (Susceptible–Exposed–Infectious–Recovered) with two time delays to describe the transmission dynamics of malicious signals in wireless sensor network. The first delay accounts for an exposed (latent) period while the second delay is for the temporary immunity period due to multiple worm outbreaks. The dynamical behaviour of worm-free equilibrium and endemic equilibrium is shown from the point of stability which switches under some threshold condition specified by the basic reproduction number. Our results show that the global properties of equilibria also depends on the threshold condition and that latent and temporary immunity period in a mote does not affect the stability, but they play a positive role to control malicious attack. Moreover, numerical simulations are given to support the theoretical analysis

  12. Four wind speed multi-step forecasting models using extreme learning machines and signal decomposing algorithms

    International Nuclear Information System (INIS)

    Liu, Hui; Tian, Hong-qi; Li, Yan-fei

    2015-01-01

    Highlights: • A hybrid architecture is proposed for the wind speed forecasting. • Four algorithms are used for the wind speed multi-scale decomposition. • The extreme learning machines are employed for the wind speed forecasting. • All the proposed hybrid models can generate the accurate results. - Abstract: Realization of accurate wind speed forecasting is important to guarantee the safety of wind power utilization. In this paper, a new hybrid forecasting architecture is proposed to realize the wind speed accurate forecasting. In this architecture, four different hybrid models are presented by combining four signal decomposing algorithms (e.g., Wavelet Decomposition/Wavelet Packet Decomposition/Empirical Mode Decomposition/Fast Ensemble Empirical Mode Decomposition) and Extreme Learning Machines. The originality of the study is to investigate the promoted percentages of the Extreme Learning Machines by those mainstream signal decomposing algorithms in the multiple step wind speed forecasting. The results of two forecasting experiments indicate that: (1) the method of Extreme Learning Machines is suitable for the wind speed forecasting; (2) by utilizing the decomposing algorithms, all the proposed hybrid algorithms have better performance than the single Extreme Learning Machines; (3) in the comparisons of the decomposing algorithms in the proposed hybrid architecture, the Fast Ensemble Empirical Mode Decomposition has the best performance in the three-step forecasting results while the Wavelet Packet Decomposition has the best performance in the one and two step forecasting results. At the same time, the Wavelet Packet Decomposition and the Fast Ensemble Empirical Mode Decomposition are better than the Wavelet Decomposition and the Empirical Mode Decomposition in all the step predictions, respectively; and (4) the proposed algorithms are effective in the wind speed accurate predictions

  13. Modeling traffic accidents at signalized intersections in the city of Norfolk, VA.

    Science.gov (United States)

    2010-12-31

    This study was an attempt to apply a proactive approach using traffic pattern and signalized intersection characteristics to predict accident rates at signalized intersections in a citys arterial network. An earlier analysis of accident data at se...

  14. Basic Investigations of Dynamic Travel Time Estimation Model for Traffic Signals Control Using Information from Optical Beacons

    Science.gov (United States)

    Okutani, Iwao; Mitsui, Tatsuro; Nakada, Yusuke

    In this paper put forward are neuron-type models, i.e., neural network model, wavelet neuron model and three layered wavelet neuron model(WV3), for estimating traveling time between signalized intersections in order to facilitate adaptive setting of traffic signal parameters such as green time and offset. Model validation tests using simulated data reveal that compared to other models, WV3 model works very fast in learning process and can produce more accurate estimates of travel time. Also, it is exhibited that up-link information obtainable from optical beacons, i.e., travel time observed during the former cycle time in this case, makes a crucial input variable to the models in that there isn't any substantial difference between the change of estimated and simulated travel time with the change of green time or offset when up-link information is employed as input while there appears big discrepancy between them when not employed.

  15. Aortopathy in a Mouse Model of Marfan Syndrome Is Not Mediated by Altered Transforming Growth Factor β Signaling.

    Science.gov (United States)

    Wei, Hao; Hu, Jie Hong; Angelov, Stoyan N; Fox, Kate; Yan, James; Enstrom, Rachel; Smith, Alexandra; Dichek, David A

    2017-01-24

    Marfan syndrome (MFS) is caused by mutations in the gene encoding fibrillin-1 (FBN1); however, the mechanisms through which fibrillin-1 deficiency causes MFS-associated aortopathy are uncertain. Recently, attention was focused on the hypothesis that MFS-associated aortopathy is caused by increased transforming growth factor-β (TGF-β) signaling in aortic medial smooth muscle cells (SMC). However, there are many reasons to doubt that TGF-β signaling drives MFS-associated aortopathy. We used a mouse model to test whether SMC TGF-β signaling is perturbed by a fibrillin-1 variant that causes MFS and whether blockade of SMC TGF-β signaling prevents MFS-associated aortopathy. MFS mice (Fbn1 C1039G/+ genotype) were genetically modified to allow postnatal SMC-specific deletion of the type II TGF-β receptor (TBRII; essential for physiologic TGF-β signaling). In young MFS mice with and without superimposed deletion of SMC-TBRII, we measured aortic dimensions, histopathology, activation of aortic SMC TGF-β signaling pathways, and changes in aortic SMC gene expression. Young Fbn1 C1039G/+ mice had ascending aortic dilation and significant disruption of aortic medial architecture. Both aortic dilation and disrupted medial architecture were exacerbated by superimposed deletion of TBRII. TGF-β signaling was unaltered in aortic SMC of young MFS mice; however, SMC-specific deletion of TBRII in Fbn1 C1039G/+ mice significantly decreased activation of SMC TGF-β signaling pathways. In young Fbn1 C1039G/+ mice, aortopathy develops in the absence of detectable alterations in SMC TGF-β signaling. Loss of physiologic SMC TGF-β signaling exacerbates MFS-associated aortopathy. Our data support a protective role for SMC TGF-β signaling during early development of MFS-associated aortopathy. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

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

    Energy Technology Data Exchange (ETDEWEB)

    Fiorentin, M. Re [School of Physics and Astronomy, University of Southampton,SO17 1BJ Southampton (United Kingdom); Niro, V. [Departamento de Física Teórica, Universidad Autónoma de Madrid,Cantoblanco, E-28049 Madrid (Spain); Instituto de Física Teórica UAM/CSIC,Calle Nicolás Cabrera 13-15, Cantoblanco, E-28049 Madrid (Spain); Fornengo, N. [Dipartimento di Fisica, Università di Torino,via P. Giuria, 1, 10125 Torino (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Torino,via P. Giuria, 1, 10125 Torino (Italy)

    2016-11-04

    We discuss a left-right symmetric extension of the Standard Model in which the three additional right-handed neutrinos play a central role in explaining the baryon asymmetry of the Universe, the dark matter abundance and the ultra energetic signal detected by the IceCube experiment. The energy spectrum and neutrino flux measured by IceCube are ascribed to the decays of the lightest right-handed neutrino N{sub 1}, thus fixing its mass and lifetime, while the production of N{sub 1} in the primordial thermal bath occurs via a freeze-in mechanism driven by the additional SU(2){sub R} interactions. The constraints imposed by IceCube and the dark matter abundance allow nonetheless the heavier right-handed neutrinos to realize a standard type-I seesaw leptogenesis, with the B−L asymmetry dominantly produced by the next-to-lightest neutrino N{sub 2}. Further consequences and predictions of the model are that: the N{sub 1} production implies a specific power-law relation between the reheating temperature of the Universe and the vacuum expectation value of the SU(2){sub R} triplet; leptogenesis imposes a lower bound on the reheating temperature of the Universe at 7×10{sup 9} GeV. Additionally, the model requires a vanishing absolute neutrino mass scale m{sub 1}≃0.

  17. Safety impacts of red light cameras at signalized intersections based on cellular automata models.

    Science.gov (United States)

    Chai, C; Wong, Y D; Lum, K M

    2015-01-01

    This study applies a simulation technique to evaluate the hypothesis that red light cameras (RLCs) exert important effects on accident risks. Conflict occurrences are generated by simulation and compared at intersections with and without RLCs to assess the impact of RLCs on several conflict types under various traffic conditions. Conflict occurrences are generated through simulating vehicular interactions based on an improved cellular automata (CA) model. The CA model is calibrated and validated against field observations at approaches with and without RLCs. Simulation experiments are conducted for RLC and non-RLC intersections with different geometric layouts and traffic demands to generate conflict occurrences that are analyzed to evaluate the hypothesis that RLCs exert important effects on road safety. The comparison of simulated conflict occurrences show favorable safety impacts of RLCs on crossing conflicts and unfavorable impacts for rear-end conflicts during red/amber phases. Corroborative results are found from broad analysis of accident occurrence. RLCs are found to have a mixed effect on accident risk at signalized intersections: crossing collisions are reduced, whereas rear-end collisions may increase. The specially developed CA model is found to be a feasible safety assessment tool.

  18. Large signal-to-noise ratio quantification in MLE for ARARMAX models

    Science.gov (United States)

    Zou, Yiqun; Tang, Xiafei

    2014-06-01

    It has been shown that closed-loop linear system identification by indirect method can be generally transferred to open-loop ARARMAX (AutoRegressive AutoRegressive Moving Average with eXogenous input) estimation. For such models, the gradient-related optimisation with large enough signal-to-noise ratio (SNR) can avoid the potential local convergence in maximum likelihood estimation. To ease the application of this condition, the threshold SNR needs to be quantified. In this paper, we build the amplitude coefficient which is an equivalence to the SNR and prove the finiteness of the threshold amplitude coefficient within the stability region. The quantification of threshold is achieved by the minimisation of an elaborately designed multi-variable cost function which unifies all the restrictions on the amplitude coefficient. The corresponding algorithm based on two sets of physically realisable system input-output data details the minimisation and also points out how to use the gradient-related method to estimate ARARMAX parameters when local minimum is present as the SNR is small. Then, the algorithm is tested on a theoretical AutoRegressive Moving Average with eXogenous input model for the derivation of the threshold and a gas turbine engine real system for model identification, respectively. Finally, the graphical validation of threshold on a two-dimensional plot is discussed.

  19. A mathematical model for source separation of MMG signals recorded with a coupled microphone-accelerometer sensor pair.

    Science.gov (United States)

    Silva, Jorge; Chau, Tom

    2005-09-01

    Recent advances in sensor technology for muscle activity monitoring have resulted in the development of a coupled microphone-accelerometer sensor pair for physiological acousti signal recording. This sensor can be used to eliminate interfering sources in practical settings where the contamination of an acoustic signal by ambient noise confounds detection but cannot be easily removed [e.g., mechanomyography (MMG), swallowing sounds, respiration, and heart sounds]. This paper presents a mathematical model for the coupled microphone-accelerometer vibration sensor pair, specifically applied to muscle activity monitoring (i.e., MMG) and noise discrimination in externally powered prostheses for below-elbow amputees. While the model provides a simple and reliable source separation technique for MMG signals, it can also be easily adapted to other aplications where the recording of low-frequency (< 1 kHz) physiological vibration signals is required.

  20. Impact of the Test Device on the Behavior of the Acoustic Emission Signals: Contribution of the Numerical Modeling to Signal Processing

    Science.gov (United States)

    Issiaka Traore, Oumar; Cristini, Paul; Favretto-Cristini, Nathalie; Pantera, Laurent; Viguier-Pla, Sylvie

    2018-01-01

    In a context of nuclear safety experiment monitoring with the non destructive testing method of acoustic emission, we study the impact of the test device on the interpretation of the recorded physical signals by using spectral finite element modeling. The numerical results are validated by comparison with real acoustic emission data obtained from previous experiments. The results show that several parameters can have significant impacts on acoustic wave propagation and then on the interpretation of the physical signals. The potential position of the source mechanism, the positions of the receivers and the nature of the coolant fluid have to be taken into account in the definition a pre-processing strategy of the real acoustic emission signals. In order to show the relevance of such an approach, we use the results to propose an optimization of the positions of the acoustic emission sensors in order to reduce the estimation bias of the time-delay and then improve the localization of the source mechanisms.

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

    Science.gov (United States)

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

    2016-01-01

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

  2. Increased chemokine signaling in a model of HIV1-associated peripheral neuropathy

    Directory of Open Access Journals (Sweden)

    Buchanan David J

    2009-08-01

    Full Text Available Abstract Painful distal sensory polyneuropathy (DSP is the most common neurological complication of HIV1 infection. Although infection with the virus itself is associated with an incidence of DSP, patients are more likely to become symptomatic following initiation of nucleoside reverse transcriptase inhibitor (NRTI treatment. The chemokines monocyte chemoattractant protein-1 (MCP1/CCL2 and stromal derived factor-1 (SDF1/CXCL12 and their respective receptors, CCR2 and CXCR4, have been implicated in HIV1 related neuropathic pain mechanisms including NRTI treatment in rodents. Utilizing a rodent model that incorporates the viral coat protein, gp120, and the NRTI, 2'3'-dideoxycytidine (ddC, we examined the degree to which chemokine receptor signaling via CCR2 and CXCR4 potentially influences the resultant chronic hypernociceptive behavior. We observed that following unilateral gp120 sciatic nerve administration, rats developed profound tactile hypernociception in the hindpaw ipsilateral to gp120 treatment. Behavioral changes were also present in the hindpaw contralateral to the injury, albeit delayed and less robust. Using immunohistochemical studies, we demonstrated that MCP1 and CCR2 were upregulated by primary sensory neurons in lumbar ganglia by post-operative day (POD 14. The functional nature of these observations was confirmed using calcium imaging in acutely dissociated lumbar dorsal root ganglion (DRG derived from gp120 injured rats at POD 14. Tactile hypernociception in gp120 treated animals was reversed following treatment with a CCR2 receptor antagonist at POD 14. Some groups of animals were subjected to gp120 sciatic nerve injury in combination with an injection of ddC at POD 14. This injury paradigm produced pronounced bilateral tactile hypernociception from POD 14–48. More importantly, functional MCP1/CCR2 and SDF1/CXCR4 signaling was present in sensory neurons. In contrast to gp120 treatment alone, the hypernociceptive behavior

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

    Directory of Open Access Journals (Sweden)

    Kaustubh Supekar

    2012-02-01

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

  4. NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction

    Directory of Open Access Journals (Sweden)

    Provart Nicholas

    2009-06-01

    Full Text Available Abstract Background Nuclear localization signals (NLSs are stretches of residues within a protein that are important for the regulated nuclear import of the protein. Of the many import pathways that exist in yeast, the best characterized is termed the 'classical' NLS pathway. The classical NLS contains specific patterns of basic residues and computational methods have been designed to predict the location of these motifs on proteins. The consensus sequences, or patterns, for the other import pathways are less well-understood. Results In this paper, we present an analysis of characterized NLSs in yeast, and find, despite the large number of nuclear import pathways, that NLSs seem to show similar patterns of amino acid residues. We test current prediction methods and observe a low true positive rate. We therefore suggest an approach using hidden Markov models (HMMs to predict novel NLSs in proteins. We show that our method is able to consistently find 37% of the NLSs with a low false positive rate and that our method retains its true positive rate outside of the yeast data set used for the training parameters. Conclusion Our implementation of this model, NLStradamus, is made available at: http://www.moseslab.csb.utoronto.ca/NLStradamus/

  5. A PREDICTIVE STUDY: CARBON MONOXIDE EMISSION MODELING AT A SIGNALIZED INTERSECTION

    Directory of Open Access Journals (Sweden)

    FREDDY WEE LIANG KHO

    2014-02-01

    Full Text Available CAL3QHC dispersion model was used to predict the present and future carbonmonoxide (CO levels at a busy signalized intersection. This study attempted to identify CO “hot-spots” at nearby areas of the intersection during typical A.M. and P.M. peak hours. The CO concentration “hot-spots” had been identified at 101 Commercial Park and the simulated maximum 1-hour Time-Weighted Average (1-h TWA ground level CO concentrations of 18.3 ppm and 18.6 ppm had been observed during A.M. and P.M. peaks, respectively in year 2006. This study shows that there would be no significant increment in CO level for year 2014 although a substantial increase in the number of vehicles is assumed to affect CO levels. It was also found that CO levels would be well below the Malaysian Ambient Air Quality Guideline of 30 ppm (1-h TWA. Comparisons between the measured and simulated CO levels using quantitative data analysis technique and statistical methods indicated that CAL3QHC dispersion model correlated well with measured data.

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

    Directory of Open Access Journals (Sweden)

    Sergio Iván Ravelo Arias

    2013-12-01

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

  7. Searching for dark matter signals in the left-right symmetric gauge model with CP symmetry

    International Nuclear Information System (INIS)

    Guo Wanlei; Wu Yueliang; Zhou Yufeng

    2010-01-01

    We investigate the singlet scalar dark matter (DM) candidate in a left-right symmetric gauge model with two Higgs bidoublets in which the stabilization of the DM particle is induced by the discrete symmetries P and CP. According to the observed DM abundance, we predict the DM direct and indirect detection cross sections for the DM mass range from 10 to 500 GeV. We show that the DM indirect detection cross section is not sensitive to the light Higgs mixing and Yukawa couplings except for the resonance regions. The predicted spin-independent DM-nucleon elastic scattering cross section is found to be significantly dependent on the above two factors. Our results show that the future DM direct search experiments can cover the most parts of the allowed parameter space. The PAMELA antiproton data can only exclude two very narrow regions in the two Higgs bidoublets model. It is very difficult to detect the DM direct or indirect signals in the resonance regions due to the Breit-Wigner resonance effect.

  8. Recognition of emotions using multimodal physiological signals and an ensemble deep learning model.

    Science.gov (United States)

    Yin, Zhong; Zhao, Mengyuan; Wang, Yongxiong; Yang, Jingdong; Zhang, Jianhua

    2017-03-01

    Using deep-learning methodologies to analyze multimodal physiological signals becomes increasingly attractive for recognizing human emotions. However, the conventional deep emotion classifiers may suffer from the drawback of the lack of the expertise for determining model structure and the oversimplification of combining multimodal feature abstractions. In this study, a multiple-fusion-layer based ensemble classifier of stacked autoencoder (MESAE) is proposed for recognizing emotions, in which the deep structure is identified based on a physiological-data-driven approach. Each SAE consists of three hidden layers to filter the unwanted noise in the physiological features and derives the stable feature representations. An additional deep model is used to achieve the SAE ensembles. The physiological features are split into several subsets according to different feature extraction approaches with each subset separately encoded by a SAE. The derived SAE abstractions are combined according to the physiological modality to create six sets of encodings, which are then fed to a three-layer, adjacent-graph-based network for feature fusion. The fused features are used to recognize binary arousal or valence states. DEAP multimodal database was employed to validate the performance of the MESAE. By comparing with the best existing emotion classifier, the mean of classification rate and F-score improves by 5.26%. The superiority of the MESAE against the state-of-the-art shallow and deep emotion classifiers has been demonstrated under different sizes of the available physiological instances. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  9. Traffic flow model at fixed control signals with discrete service time distribution

    Directory of Open Access Journals (Sweden)

    Lucky I. Igbinosun

    2016-04-01

    Full Text Available Most of the models of road traffic flow at fixed-cycle controlled intersection assume stationary distributions and provide steady state results. The assumption that a constant number of vehicles can leave the system during the green phase is unrealistic in real life situations. A discrete time queuing model was developed to describe the operation of traffic flow at a road intersection with fixed-cycle signalized control and to account for the randomness in the number of vehicles that can leave the system. The results show the expected queue size in the system when the traffic is light and for a busy period, respectively. For the light period, when the traffic intensity is less than one, it takes a shorter green cycle time for vehicles to clear up than during high traffic intensity (the road junction is saturated. Increasing the number of cars that can leave the junction at the turn of the green phase reduces the number of cycle times before the queue is cleared.

  10. Insulin signaling misregulation underlies circadian and cognitive deficits in a Drosophila fragile X model.

    Science.gov (United States)

    Monyak, R E; Emerson, D; Schoenfeld, B P; Zheng, X; Chambers, D B; Rosenfelt, C; Langer, S; Hinchey, P; Choi, C H; McDonald, T V; Bolduc, F V; Sehgal, A; McBride, S M J; Jongens, T A

    2017-08-01

    Fragile X syndrome (FXS) is an undertreated neurodevelopmental disorder characterized by low intelligence quotent and a wide range of other symptoms including disordered sleep and autism. Although FXS is the most prevalent inherited cause of intellectual disability, its mechanistic underpinnings are not well understood. Using Drosophila as a model of FXS, we showed that select expression of dfmr1 in the insulin-producing cells (IPCs) of the brain was sufficient to restore normal circadian behavior and to rescue the memory deficits in the fragile X mutant fly. Examination of the insulin signaling (IS) pathway revealed elevated levels of Drosophila insulin-like peptide 2 (Dilp2) in the IPCs and elevated IS in the dfmr1 mutant brain. Consistent with a causal role for elevated IS in dfmr1 mutant phenotypes, the expression of dfmr1 specifically in the IPCs reduced IS, and genetic reduction of the insulin pathway also led to amelioration of circadian and memory defects. Furthermore, we showed that treatment with the FDA-approved drug metformin also rescued memory. Finally, we showed that reduction of IS is required at different time points to rescue circadian behavior and memory. Our results indicate that insulin misregulation underlies the circadian and cognitive phenotypes displayed by the Drosophila fragile X model, and thus reveal a metabolic pathway that can be targeted by new and already approved drugs to treat fragile X patients.

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

    Science.gov (United States)

    Cowie, Sarah; Davison, Michael; Elliffe, Douglas

    2014-11-01

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

  12. Non-destructive testing of high heat flux components of fusion devices by infrared thermography: modeling and signal processing

    International Nuclear Information System (INIS)

    Cismondi, Fabio

    2007-01-01

    In Plasma Facing Components (PFCs) the joint of the CFC armour material onto the metallic CuCrZr heat sink needs to be significant defects free. Detection of material flaws is a major issue of the PFCs acceptance protocol. A Non-Destructive Technique (NDT) based upon active infrared thermography allows testing PFCs on SATIR tests bed in Cadarache. Up to now defect detection was based on the comparison of the surface temperature evolution of the inspected component with that of a supposed 'defect-free' one (used as a reference element). This work deals with improvement of thermal signal processing coming from SATIR. In particular the contributions of the thermal modelling and statistical signal processing converge in this work. As for thermal modelling, the identification of a sensitive parameter to defect presence allows improving the quantitative estimation of defect Otherwise Finite Element (FE) modeling of SATIR allows calculating the so called deterministic numerical tile. Statistical approach via the Monte Carlo technique extends the numerical tile concept to the numerical population concept. As for signal processing, traditional statistical treatments allow a better localization of the bond defect processing thermo-signal by itself, without utilising a reference signal. Moreover the problem of detection and classification of random signals can be solved by maximizing the signal-to-noise ratio. Two filters maximizing the signal-to-noise ratio are optimized: the stochastic matched filter aims at detects detection and the constrained stochastic matched filter aims at defects classification. Performances are quantified and methods are compared via the ROC curves. (author)

  13. Signaling aggression.

    Science.gov (United States)

    van Staaden, Moira J; Searcy, William A; Hanlon, Roger T

    2011-01-01

    From psychological and sociological standpoints, aggression is regarded as intentional behavior aimed at inflicting pain and manifested by hostility and attacking behaviors. In contrast, biologists define aggression as behavior associated with attack or escalation toward attack, omitting any stipulation about intentions and goals. Certain animal signals are strongly associated with escalation toward attack and have the same function as physical attack in intimidating opponents and winning contests, and ethologists therefore consider them an integral part of aggressive behavior. Aggressive signals have been molded by evolution to make them ever more effective in mediating interactions between the contestants. Early theoretical analyses of aggressive signaling suggested that signals could never be honest about fighting ability or aggressive intentions because weak individuals would exaggerate such signals whenever they were effective in influencing the behavior of opponents. More recent game theory models, however, demonstrate that given the right costs and constraints, aggressive signals are both reliable about strength and intentions and effective in influencing contest outcomes. Here, we review the role of signaling in lieu of physical violence, considering threat displays from an ethological perspective as an adaptive outcome of evolutionary selection pressures. Fighting prowess is conveyed by performance signals whose production is constrained by physical ability and thus limited to just some individuals, whereas aggressive intent is encoded in strategic signals that all signalers are able to produce. We illustrate recent advances in the study of aggressive signaling with case studies of charismatic taxa that employ a range of sensory modalities, viz. visual and chemical signaling in cephalopod behavior, and indicators of aggressive intent in the territorial calls of songbirds. Copyright © 2011 Elsevier Inc. All rights reserved.

  14. Large-signal modeling of multi-finger InP DHBT devices at millimeter-wave frequencies

    DEFF Research Database (Denmark)

    Johansen, Tom Keinicke; Midili, Virginio; Squartecchia, Michele

    2017-01-01

    A large-signal modeling approach has been developed for multi-finger devices fabricated in an Indium Phosphide (InP) Double Heterojunction Bipolar Transistor (DHBT) process. The approach utilizes unit-finger device models embedded in a multi-port parasitic network. The unit-finger model is based...... on an improved UCSD HBT model formulation avoiding an erroneous RciCbci transit-time contribution from the intrinsic collector region as found in other III-V based HBT models. The mutual heating between fingers is modeled by a thermal coupling network with parameters extracted from electro-thermal simulations...

  15. Expanding signaling-molecule wavefront model of cell polarization in the Drosophila wing primordium.

    Science.gov (United States)

    Wortman, Juliana C; Nahmad, Marcos; Zhang, Peng Cheng; Lander, Arthur D; Yu, Clare C

    2017-07-01

    In developing tissues, cell polarization and proliferation are regulated by morphogens and signaling pathways. Cells throughout the Drosophila wing primordium typically show subcellular localization of the unconventional myosin Dachs on the distal side of cells (nearest the center of the disc). Dachs localization depends on the spatial distribution of bonds between the protocadherins Fat (Ft) and Dachsous (Ds), which form heterodimers between adjacent cells; and the Golgi kinase Four-jointed (Fj), which affects the binding affinities of Ft and Ds. The Fj concentration forms a linear gradient while the Ds concentration is roughly uniform throughout most of the wing pouch with a steep transition region that propagates from the center to the edge of the pouch during the third larval instar. Although the Fj gradient is an important cue for polarization, it is unclear how the polarization is affected by cell division and the expanding Ds transition region, both of which can alter the distribution of Ft-Ds heterodimers around the cell periphery. We have developed a computational model to address these questions. In our model, the binding affinity of Ft and Ds depends on phosphorylation by Fj. We assume that the asymmetry of the Ft-Ds bond distribution around the cell periphery defines the polarization, with greater asymmetry promoting cell proliferation. Our model predicts that this asymmetry is greatest in the radially-expanding transition region that leaves polarized cells in its wake. These cells naturally retain their bond distribution asymmetry after division by rapidly replenishing Ft-Ds bonds at new cell-cell interfaces. Thus we predict that the distal localization of Dachs in cells throughout the pouch requires the movement of the Ds transition region and the simple presence, rather than any specific spatial pattern, of Fj.

  16. Intra-amniotic pharmacological blockade of inflammatory signalling pathways in an ovine chorioamnionitis model.

    Science.gov (United States)

    Ireland, D J; Kemp, M W; Miura, Y; Saito, M; Newnham, J P; Keelan, J A

    2015-05-01

    Intrauterine inflammation (IUI) associated with infection is the major cause of preterm birth (PTB) at PTBs. Pharmacological strategies to prevent PTB and improve fetal outcomes will likely require both antimicrobial and anti-inflammatory therapies. Here we investigated the effects of two cytokine-suppressive anti-inflammatory drugs (CSAIDs), compounds that specifically target inflammatory signalling pathways, in an ovine model of lipopolysaccharide (LPS)-induced chorioamnionitis. Chronically catheterized ewes at 116 days gestation (n = 7/group) received an intra-amniotic (IA) bolus of LPS (10 mg) plus vehicle or CSAIDS: TPCA-1 (1.2 mg/kg fetal weight) or 5z-7-oxozeaenol (OxZnl; 0.4 mg/kg fetal weight); controls received vehicle (dimethylsulphoxide). Amniotic fluid (AF), fetal and maternal blood samples were taken 0, 2, 6, 12, 24 and 48 h later; tissues were taken at autopsy (48 h). Administration of TPCA-1 or OxZnl abrogated the stimulatory effects of LPS (P < 0.01 versus vehicle control) on production of PGE2 in AF, with lesser (non-significant) effects on IL-6 production. Fetal membrane polymorphonuclear cell infiltration score was significantly higher in LPS versus vehicle control animals (P < 0.01), and this difference was absent with TPCA-1 and OxZnl treatment. LPS-induced systemic fetal inflammation was highly variable, with no significant effects of CSAIDs observed. Lung inflammation was evident with LPS exposure, but unaffected by CSAID treatment. We have shown in a large animal model that IA administration of a single dose of CSAIDs can suppress LPS-induced IA inflammatory responses, while fetal effects were minimal. Further development and investigation of these compounds in infectious models is warranted. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  17. Induced mitochondrial membrane potential for modeling solitonic conduction of electrotonic signals.

    Directory of Open Access Journals (Sweden)

    R R Poznanski

    Full Text Available A cable model that includes polarization-induced capacitive current is derived for modeling the solitonic conduction of electrotonic potentials in neuronal branchlets with microstructure containing endoplasmic membranes. A solution of the nonlinear cable equation modified for fissured intracellular medium with a source term representing charge 'soakage' is used to show how intracellular capacitive effects of bound electrical charges within mitochondrial membranes can influence electrotonic signals expressed as solitary waves. The elastic collision resulting from a head-on collision of two solitary waves results in localized and non-dispersing electrical solitons created by the nonlinearity of the source term. It has been shown that solitons in neurons with mitochondrial membrane and quasi-electrostatic interactions of charges held by the microstructure (i.e., charge 'soakage' have a slower velocity of propagation compared with solitons in neurons with microstructure, but without endoplasmic membranes. When the equilibrium potential is a small deviation from rest, the nonohmic conductance acts as a leaky channel and the solitons are small compared when the equilibrium potential is large and the outer mitochondrial membrane acts as an amplifier, boosting the amplitude of the endogenously generated solitons. These findings demonstrate a functional role of quasi-electrostatic interactions of bound electrical charges held by microstructure for sustaining solitons with robust self-regulation in their amplitude through changes in the mitochondrial membrane equilibrium potential. The implication of our results indicate that a phenomenological description of ionic current can be successfully modeled with displacement current in Maxwell's equations as a conduction process involving quasi-electrostatic interactions without the inclusion of diffusive current. This is the first study in which solitonic conduction of electrotonic potentials are generated by

  18. A model system for targeted drug release triggered by biomolecular signals logically processed through enzyme logic networks.

    Science.gov (United States)

    Mailloux, Shay; Halámek, Jan; Katz, Evgeny

    2014-03-07

    A new Sense-and-Act system was realized by the integration of a biocomputing system, performing analytical processes, with a signal-responsive electrode. A drug-mimicking release process was triggered by biomolecular signals processed by different logic networks, including three concatenated AND logic gates or a 3-input OR logic gate. Biocatalytically produced NADH, controlled by various combinations of input signals, was used to activate the electrochemical system. A biocatalytic electrode associated with signal-processing "biocomputing" systems was electrically connected to another electrode coated with a polymer film, which was dissolved upon the formation of negative potential releasing entrapped drug-mimicking species, an enzyme-antibody conjugate, operating as a model for targeted immune-delivery and consequent "prodrug" activation. The system offers great versatility for future applications in controlled drug release and personalized medicine.

  19. Spatial modeling of the membrane-cytosolic interface in protein kinase signal transduction.

    Directory of Open Access Journals (Sweden)

    Wolfgang Giese

    2018-04-01

    Full Text Available The spatial architecture of signaling pathways and the interaction with cell size and morphology are complex, but little understood. With the advances of single cell imaging and single cell biology, it becomes crucial to understand intracellular processes in time and space. Activation of cell surface receptors often triggers a signaling cascade including the activation of membrane-attached and cytosolic signaling components, which eventually transmit the signal to the cell nucleus. Signaling proteins can form steep gradients in the cytosol, which cause strong cell size dependence. We show that the kinetics at the membrane-cytosolic interface and the ratio of cell membrane area to the enclosed cytosolic volume change the behavior of signaling cascades significantly. We suggest an estimate of average concentration for arbitrary cell shapes depending on the cell volume and cell surface area. The normalized variance, known from image analysis, is suggested as an alternative measure to quantify the deviation from the average concentration. A mathematical analysis of signal transduction in time and space is presented, providing analytical solutions for different spatial arrangements of linear signaling cascades. Quantification of signaling time scales reveals that signal propagation is faster at the membrane than at the nucleus, while this time difference decreases with the number of signaling components in the cytosol. Our investigations are complemented by numerical simulations of non-linear cascades with feedback and asymmetric cell shapes. We conclude that intracellular signal propagation is highly dependent on cell geometry and, thereby, conveys information on cell size and shape to the nucleus.

  20. A threshold model for receptor tyrosine kinase signaling specificity and cell fate determination [version 1; referees: 4 approved

    Directory of Open Access Journals (Sweden)

    Allen Zinkle

    2018-06-01

    Full Text Available Upon ligand engagement, the single-pass transmembrane receptor tyrosine kinases (RTKs dimerize to transmit qualitatively and quantitatively different intracellular signals that alter the transcriptional landscape and thereby determine the cellular response. The molecular mechanisms underlying these fundamental events are not well understood. Considering recent insights into the structural biology of fibroblast growth factor signaling, we propose a threshold model for RTK signaling specificity in which quantitative differences in the strength/longevity of ligand-induced receptor dimers on the cell surface lead to quantitative differences in the phosphorylation of activation loop (A-loop tyrosines as well as qualitative differences in the phosphorylation of tyrosines mediating substrate recruitment. In this model, quantitative differences on A-loop tyrosine phosphorylation result in gradations in kinase activation, leading to the generation of intracellular signals of varying amplitude/duration. In contrast, qualitative differences in the pattern of tyrosine phosphorylation on the receptor result in the recruitment/activation of distinct substrates/intracellular pathways. Commensurate with both the dynamics of the intracellular signal and the types of intracellular pathways activated, unique transcriptional signatures are established. Our model provides a framework for engineering clinically useful ligands that can tune receptor dimerization stability so as to bias the cellular transcriptome to achieve a desired cellular output.

  1. Systems Medicine in Oncology: Signaling Network Modeling and New-Generation Decision-Support Systems.

    Science.gov (United States)

    Parodi, Silvio; Riccardi, Giuseppe; Castagnino, Nicoletta; Tortolina, Lorenzo; Maffei, Massimo; Zoppoli, Gabriele; Nencioni, Alessio; Ballestrero, Alberto; Patrone, Franco

    2016-01-01

    Two different perspectives are the main focus of this book chapter: (1) A perspective that looks to the future, with the goal of devising rational associations of targeted inhibitors against distinct altered signaling-network pathways. This goal implies a sufficiently in-depth molecular diagnosis of the personal cancer of a given patient. A sufficiently robust and extended dynamic modeling will suggest rational combinations of the abovementioned oncoprotein inhibitors. The work toward new selective drugs, in the field of medicinal chemistry, is very intensive. Rational associations of selective drug inhibitors will become progressively a more realistic goal within the next 3-5 years. Toward the possibility of an implementation in standard oncologic structures of technologically sufficiently advanced countries, new (legal) rules probably will have to be established through a consensus process, at the level of both diagnostic and therapeutic behaviors.(2) The cancer patient of today is not the patient of 5-10 years from now. How to support the choice of the most convenient (and already clinically allowed) treatment for an individual cancer patient, as of today? We will consider the present level of artificial intelligence (AI) sophistication and the continuous feeding, updating, and integration of cancer-related new data, in AI systems. We will also report briefly about one of the most important projects in this field: IBM Watson US Cancer Centers. Allowing for a temporal shift, in the long term the two perspectives should move in the same direction, with a necessary time lag between them.

  2. Impact of evolving greenhouse gas forcing on the warming signal in regional climate model experiments.

    Science.gov (United States)

    Jerez, S; López-Romero, J M; Turco, M; Jiménez-Guerrero, P; Vautard, R; Montávez, J P

    2018-04-03

    Variations in the atmospheric concentrations of greenhouse gases (GHG) may not be included as external forcing when running regional climate models (RCMs); at least, this is a non-regulated, non-documented practice. Here we investigate the so far unexplored impact of considering the rising evolution of the CO 2 , CH 4 , and N 2 O atmospheric concentrations on near-surface air temperature (TAS) trends, for both the recent past and the near future, as simulated by a state-of-the-art RCM over Europe. The results show that the TAS trends are significantly affected by 1-2 K century -1 , which under 1.5 °C global warming translates into a non-negligible impact of up to 1 K in the regional projections of TAS, similarly affecting projections for maximum and minimum temperatures. In some cases, these differences involve a doubling signal, laying further claim to careful reconsideration of the RCM setups with regard to the inclusion of GHG concentrations as an evolving external forcing which, for the sake of research reproducibility and reliability, should be clearly documented in the literature.

  3. EASEE: an open architecture approach for modeling battlespace signal and sensor phenomenology

    Science.gov (United States)

    Waldrop, Lauren E.; Wilson, D. Keith; Ekegren, Michael T.; Borden, Christian T.

    2017-04-01

    Open architecture in the context of defense applications encourages collaboration across government agencies and academia. This paper describes a success story in the implementation of an open architecture framework that fosters transparency and modularity in the context of Environmental Awareness for Sensor and Emitter Employment (EASEE), a complex physics-based software package for modeling the effects of terrain and atmospheric conditions on signal propagation and sensor performance. Among the highlighted features in this paper are: (1) a code refactorization to separate sensitive parts of EASEE, thus allowing collaborators the opportunity to view and interact with non-sensitive parts of the EASEE framework with the end goal of supporting collaborative innovation, (2) a data exchange and validation effort to enable the dynamic addition of signatures within EASEE thus supporting a modular notion that components can be easily added or removed to the software without requiring recompilation by developers, and (3) a flexible and extensible XML interface, which aids in decoupling graphical user interfaces from EASEE's calculation engine, and thus encourages adaptability to many different defense applications. In addition to the outlined points above, this paper also addresses EASEE's ability to interface with both proprietary systems such as ArcGIS. A specific use case regarding the implementation of an ArcGIS toolbar that leverages EASEE's XML interface and enables users to set up an EASEE-compliant configuration for probability of detection or optimal sensor placement calculations in various modalities is discussed as well.

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

    Science.gov (United States)

    Koch, Karoline; Havermann, Susannah; Büchter, Christian

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Karoline Koch

    2014-01-01

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

  6. An analytical model for the SO2- centre, ESR signal at g=2.0057 in carbonates

    International Nuclear Information System (INIS)

    Martinez, M.; Woda, C.; Walther, R.; Mangini, A.

    2001-01-01

    Detailed experiments were conducted to test the behaviour of the ESR signal at the g-value of 2.0057 in corals after irradiation and heating. On the basis of the results an analytical model for this signal was developed. We assume the existence of a precursor to the SO 2 - radical. On irradiation traps are produced, some in the precursor state and some in the radical state. Heating then causes transfer of electrons into the precursor state, from the precursor state into the radical state and out of the radical state into a base state. On the base of this model, we suggest that the signal at g=2.0057 can be applied for dating. Our first dating attempts on corals delivered promising results for the suggested procedure

  7. Modelling cardiac signal as a confound in EEG-fMRI and its application in focal epilepsy studies

    DEFF Research Database (Denmark)

    Liston, A. D.; Ellegaard Lund, Torben; Salek-Haddadi, A

    2006-01-01

    effects to be modelled, as effects of no interest. Our model is based on an over-complete basis set covering a linear relationship between cardiac-related MR signal and the phase of the cardiac cycle or time after pulse (TAP). This method showed that, on average, 24.6 +/- 10.9% of grey matter voxels......Cardiac noise has been shown to reduce the sensitivity of functional Magnetic Resonance Imaging (fMRI) to an experimental effect due to its confounding presence in the blood oxygenation level-dependent (BOLD) signal. Its effect is most severe in particular regions of the brain and a method is yet...... to take it into account in routine fMRI analysis. This paper reports the development of a general and robust technique to improve the reliability of EEG-fMRI studies to BOLD signal correlated with interictal epileptiform discharges (IEDs). In these studies, ECG is routinely recorded, enabling cardiac...

  8. S113R mutation in SLC33A1 leads to neurodegeneration and augmented BMP signaling in a mouse model

    Directory of Open Access Journals (Sweden)

    Pingting Liu

    2017-01-01

    Full Text Available The S113R mutation (c.339T>G (MIM #603690.0001 in SLC33A1 (MIM #603690, an ER membrane acetyl-CoA transporter, has been previously identified in individuals with hereditary spastic paraplegia type 42 (SPG42; MIM #612539. SLC33A1 has also been shown to inhibit the bone morphogenetic protein (BMP signaling pathway in zebrafish. To better understand the function of SLC33A1, we generated and characterized Slc33a1S113R knock-in mice. Homozygous Slc33a1S113R mutant mice were embryonic lethal, whereas heterozygous Slc33a1 mutant mice (Slc33a1wt/mut exhibited behavioral abnormalities and central neurodegeneration, which is consistent with hereditary spastic paraplegia (HSP phenotypes. Importantly, we found an upregulation of BMP signaling in the nervous system and mouse embryonic fibroblasts of Slc33a1wt/mut mice. Using a sciatic nerve crush injury model in vivo and dorsal root ganglion (DRG culture in vitro we showed that injury-induced axonal regeneration in Slc33a1wt/mut mice was accelerated and mediated by upregulated BMP signaling. Exogenous addition of BMP signaling antagonist, noggin, could efficiently alleviate the accelerated injury-induced axonal regrowth. These results indicate that SLC33A1 can negatively regulate BMP signaling in mice, further supporting the notion that upregulation of BMP signaling is a common mechanism of a subset of hereditary spastic paraplegias.

  9. Gas ultrasonic flow rate measurement through genetic-ant colony optimization based on the ultrasonic pulse received signal model

    Science.gov (United States)

    Hou, Huirang; Zheng, Dandan; Nie, Laixiao

    2015-04-01

    For gas ultrasonic flowmeters, the signals received by ultrasonic sensors are susceptible to noise interference. If signals are mingled with noise, a large error in flow measurement can be caused by triggering mistakenly using the traditional double-threshold method. To solve this problem, genetic-ant colony optimization (GACO) based on the ultrasonic pulse received signal model is proposed. Furthermore, in consideration of the real-time performance of the flow measurement system, the improvement of processing only the first three cycles of the received signals rather than the whole signal is proposed. Simulation results show that the GACO algorithm has the best estimation accuracy and ant-noise ability compared with the genetic algorithm, ant colony optimization, double-threshold and enveloped zero-crossing. Local convergence doesn’t appear with the GACO algorithm until -10 dB. For the GACO algorithm, the converging accuracy and converging speed and the amount of computation are further improved when using the first three cycles (called GACO-3cycles). Experimental results involving actual received signals show that the accuracy of single-gas ultrasonic flow rate measurement can reach 0.5% with GACO-3 cycles, which is better than with the double-threshold method.

  10. Gas ultrasonic flow rate measurement through genetic-ant colony optimization based on the ultrasonic pulse received signal model

    International Nuclear Information System (INIS)

    Hou, Huirang; Zheng, Dandan; Nie, Laixiao

    2015-01-01

    For gas ultrasonic flowmeters, the signals received by ultrasonic sensors are susceptible to noise interference. If signals are mingled with noise, a large error in flow measurement can be caused by triggering mistakenly using the traditional double-threshold method. To solve this problem, genetic-ant colony optimization (GACO) based on the ultrasonic pulse received signal model is proposed. Furthermore, in consideration of the real-time performance of the flow measurement system, the improvement of processing only the first three cycles of the received signals rather than the whole signal is proposed. Simulation results show that the GACO algorithm has the best estimation accuracy and ant-noise ability compared with the genetic algorithm, ant colony optimization, double-threshold and enveloped zero-crossing. Local convergence doesn’t appear with the GACO algorithm until –10 dB. For the GACO algorithm, the converging accuracy and converging speed and the amount of computation are further improved when using the first three cycles (called GACO-3cycles). Experimental results involving actual received signals show that the accuracy of single-gas ultrasonic flow rate measurement can reach 0.5% with GACO-3 cycles, which is better than with the double-threshold method. (paper)

  11. Mathematical model reveals role of nucleotide signaling in airway surface liquid homeostasis and its dysregulation in cystic fibrosis.

    Science.gov (United States)

    Sandefur, Conner I; Boucher, Richard C; Elston, Timothy C

    2017-08-29

    Mucociliary clearance is composed of three components (i.e., mucin secretion, airway surface hydration, and ciliary-activity) which function coordinately to clear inhaled microbes and other foreign particles from airway surfaces. Airway surface hydration is maintained by water fluxes driven predominantly by active chloride and sodium ion transport. The ion channels that mediate electrogenic ion transport are regulated by extracellular purinergic signals that signal through G protein-coupled receptors. These purinoreceptors and the signaling pathways they activate have been identified as possible therapeutic targets for treating lung disease. A systems-level description of airway surface liquid (ASL) homeostasis could accelerate development of such therapies. Accordingly, we developed a mathematical model to describe the dynamic coupling of ion and water transport to extracellular purinergic signaling. We trained our model from steady-state and time-dependent experimental measurements made using normal and cystic fibrosis (CF) cultured human airway epithelium. To reproduce CF conditions, reduced chloride secretion, increased potassium secretion, and increased sodium absorption were required. The model accurately predicted ASL height under basal normal and CF conditions and the collapse of surface hydration due to the accelerated nucleotide metabolism associated with CF exacerbations. Finally, the model predicted a therapeutic strategy to deliver nucleotide receptor agonists to effectively rehydrate the ASL of CF airways.

  12. Estimation of urinary flow velocity in models of obstructed and unobstructed urethras by decorrelation of ultrasound radiofrequency signals

    NARCIS (Netherlands)

    Arif, M.; Idzenga, T.; Mastrigt, R. van; Korte, C.L. de

    2014-01-01

    The feasibility of estimating urinary flow velocity from the decorrelation of radiofrequency (RF) signals was investigated in soft tissue-mimicking models of obstructed and unobstructed urethras. The decorrelation was studied in the near field, focal zone and far field of the ultrasound beam.

  13. Modeling and Assessment of Precise Time Transfer by Using BeiDou Navigation Satellite System Triple-Frequency Signals

    Science.gov (United States)

    Zhang, Pengfei; Zhang, Rui; Liu, Jinhai; Lu, Xiaochun

    2018-01-01

    This study proposes two models for precise time transfer using the BeiDou Navigation Satellite System triple-frequency signals: ionosphere-free (IF) combined precise point positioning (PPP) model with two dual-frequency combinations (IF-PPP1) and ionosphere-free combined PPP model with a single triple-frequency combination (IF-PPP2). A dataset with a short baseline (with a common external time frequency) and a long baseline are used for performance assessments. The results show that IF-PPP1 and IF-PPP2 models can both be used for precise time transfer using BeiDou Navigation Satellite System (BDS) triple-frequency signals, and the accuracy and stability of time transfer is the same in both cases, except for a constant system bias caused by the hardware delay of different frequencies, which can be removed by the parameter estimation and prediction with long time datasets or by a priori calibration. PMID:29596330

  14. Low signal-to-noise FDEM in-phase data: Practical potential for magnetic susceptibility modelling

    Science.gov (United States)

    Delefortrie, Samuël; Hanssens, Daan; De Smedt, Philippe

    2018-05-01

    In this paper, we consider the use of land-based frequency-domain electromagnetics (FDEM) for magnetic susceptibility modelling. FDEM data comprises both out-of-phase and in-phase components, which can be related to the electrical conductivity and magnetic susceptibility of the subsurface. Though applying the FDEM method to obtain information on the subsurface conductivity is well established in various domains (e.g. through the low induction number approximation of subsurface apparent conductivity), the potential for susceptibility mapping is often overlooked. Especially given a subsurface with a low magnetite and maghemite content (e.g. most sedimentary environments), it is generally assumed that susceptibility is negligible. Nonetheless, the heterogeneity of the near surface and the impact of anthropogenic disturbances on the soil can cause sufficient variation in susceptibility for it to be detectable in a repeatable way. Unfortunately, it can be challenging to study the potential for susceptibility mapping due to systematic errors, an often poor low signal-to-noise ratio, and the intricacy of correlating in-phase responses with subsurface susceptibility and conductivity. Alongside use of an accurate forward model - accounting for out-of-phase/in-phase coupling - any attempt at relating the in-phase response with subsurface susceptibility requires overcoming instrument-specific limitations that burden the real-world application of FDEM susceptibility mapping. Firstly, the often erratic and drift-sensitive nature of in-phase responses calls for relative data levelling. In addition, a correction for absolute levelling offsets may be equally necessary: ancillary (subsurface) susceptibility data can be used to assess the importance of absolute in-phase calibration though hereby accurate in-situ data is required. To allow assessing the (importance of) in-phase calibration alongside the potential of FDEM data for susceptibility modelling, we consider an experimental

  15. On the relationship between input parameters in two-mass vocal-fold model with acoustical coupling an signal parameters of the glottal flow

    NARCIS (Netherlands)

    van Hirtum, Annemie; Lopez, Ines; Hirschberg, Abraham; Pelorson, Xavier

    2003-01-01

    In this paper the sensitivity of the two-mass model with acoustical coupling to the model input-parameters is assessed. The model-output or the glottal volume air flow is characterised by signal-parameters in the time-domain. The influence of changing input-parameters on the signal-parameters is

  16. On the relationship between input parameters in the two-mass vocal-fold model with acoustical coupling and signal parameters of the glottal flow

    NARCIS (Netherlands)

    Hirtum, van A.; Lopez Arteaga, I.; Hirschberg, A.; Pelorson, X.

    2003-01-01

    In this paper the sensitivity of the two-mass model with acoustical coupling to the model input-parameters is assessed. The model-output or the glottal volume air flow is characterised by signal-parameters in the time-domain. The influence of changing input-parameters on the signal-parameters is

  17. Novel calibration model maintenance strategy for solving the signal instability in quantitative liquid chromatography-mass spectrometry.

    Science.gov (United States)

    Du, Hai-Li; Chen, Zeng-Ping; Song, Mi; Chen, Yao; Yu, Ru-Qin

    2014-04-18

    In this contribution, a multiplicative effects model with a parameter accounting for the variations in overall sensitivity over time was proposed to reduce the effects of signal instability on quantitative results of LC-MS/MS. This method allows the use of calibration models constructed from large standard sets without having to repeat their measurement even though variations occur in sensitivity and baseline signal intensity. The performance of the proposed method was tested on two proof-of-concept model systems: the determination of the target peptide in two sets of peptide digests mixtures and the quantification of melamine and metronidazole in two sets of milk powder samples. Experimental results confirmed that multiplicative effects model could provide quite satisfactory concentration predictions for both systems with average relative predictive error values far lower than the corresponding values of various models investigated in this paper. Considering its capability in solving the problem of signal instability across samples and over time in LC-MS/MS assays and its implementation simplicity, it is expected that the multiplicative effects model can be developed and extended in many application areas such as the quantification of specific protein in cells and human plasma and other complex systems. Copyright © 2014 Elsevier B.V. All rights reserved.

  18. Effects of vitamin D analog on bladder function and sensory signaling in animal models of cystitis.

    Science.gov (United States)

    Shapiro, Bennett; Redman, T Lawton; Zvara, Peter

    2013-02-01

    To measure the effects of nonhypercalcemic vitamin D receptor agonist elocalcitol on bladder function in rats with cyclophosphamide-induced cystitis and on bladder function and sensory nerve activity in a mouse with acetic acid-evoked bladder irritation. Female Wistar rats and male Balb/C mice were gavaged once daily with elocalcitol diluted in miglyol 812 (treatment group) or miglyol alone (control group). On experimental day 12, polyethylene tubing was implanted into the urinary bladder in all the animals. In the mice, a bipolar electrode was positioned under a single postganglionic bladder nerve. At 48 hours after surgery, bladder function was measured in awake, freely moving rats during bladder filling with 0.9% NaCl and both bladder function and sensory nerve activity was measured in awake, restrained mice during continuous intravesical infusion of 0.9% NaCl followed by 0.25% acetic acid. In rats, the treatment group showed a significant increase in bladder capacity and decrease in number of nonvoiding bladder contractions. In mice, the filling pressure during saline infusion was similar in both groups; however, during acetic acid infusion, the average filling pressure was significantly increased (47%) in the control group but not in the elocalcitol treatment group. The firing rate at filling pressure for the treatment group was 3.6-fold and 2.7-fold lower than that in the control group during the saline and acetic acid infusion, respectively. Oral treatment with elocalcitol suppressed signs of detrusor overactivity in both animal models and exerted strong suppressive effect on urinary bladder sensory signaling during filling in mice. Copyright © 2013 Elsevier Inc. All rights reserved.

  19. Signals in the ionosphere generated by tsunami earthquakes: observations and modeling suppor

    Science.gov (United States)

    Rolland, L.; Sladen, A.; Mikesell, D.; Larmat, C. S.; Rakoto, V.; Remillieux, M.; Lee, R.; Khelfi, K.; Lognonne, P. H.; Astafyeva, E.

    2017-12-01

    Forecasting systems failed to predict the magnitude of the 2011 great tsunami in Japan due to the difficulty and cost of instrumenting the ocean with high-quality and dense networks. Melgar et al. (2013) show that using all of the conventional data (inland seismic, geodetic, and tsunami gauges) with the best inversion method still fails to predict the correct height of the tsunami before it breaks onto a coast near the epicenter (Even though typical tsunami waves are only a few centimeters high, they are powerful enough to create atmospheric vibrations extending all the way to the ionosphere, 300 kilometers up in the atmosphere. Therefore, we are proposing to incorporate the ionospheric signals into tsunami early-warning systems. We anticipate that the method could be decisive for mitigating "tsunami earthquakes" which trigger tsunamis larger than expected from their short-period magnitude. These events are challenging to characterize as they rupture the near-trench subduction interface, in a distant region less constrained by onshore data. As a couple of devastating tsunami earthquakes happens per decade, they represent a real threat for onshore populations and a challenge for tsunami early-warning systems. We will present the TEC observations of the recent Java 2006 and Mentawaii 2010 tsunami earthquakes and base our analysis on acoustic ray tracing, normal modes summation and the simulation code SPECFEM, which solves the wave equation in coupled acoustic (ocean, atmosphere) and elastic (solid earth) domains. Rupture histories are entered as finite source models, which will allow us to evaluate the effect of a relatively slow rupture on the surrounding ocean and atmosphere.

  20. Assessment of the Impact of Various Ionospheric Models on High-Frequency Signal Raytracing

    National Research Council Canada - National Science Library

    Werner, Joshua T

    2007-01-01

    .... Ionospheric refraction can strongly affect the propagation of HF signals. Consequently, Department of Defense missions such as over-the-horizon RADAR, HF communications, and geo-location all depend on an accurate specification of the ionosphere...

  1. Research on the Wire Network Signal Prediction Based on the Improved NNARX Model

    Science.gov (United States)

    Zhang, Zipeng; Fan, Tao; Wang, Shuqing

    It is difficult to obtain accurately the wire net signal of power system's high voltage power transmission lines in the process of monitoring and repairing. In order to solve this problem, the signal measured in remote substation or laboratory is employed to make multipoint prediction to gain the needed data. But, the obtained power grid frequency signal is delay. In order to solve the problem, an improved NNARX network which can predict frequency signal based on multi-point data collected by remote substation PMU is describes in this paper. As the error curved surface of the NNARX network is more complicated, this paper uses L-M algorithm to train the network. The result of the simulation shows that the NNARX network has preferable predication performance which provides accurate real time data for field testing and maintenance.

  2. Modelling of polysomnographic respiratory measurements for artefact detection and signal restoration

    International Nuclear Information System (INIS)

    Rathnayake, S I; Abeyratne, U R; Hukins, C; Duce, B

    2008-01-01

    Polysomnography (PSG), which incorporates measures of sleep with measures of EEG arousal, air flow, respiratory movement and oxygenation, is universally regarded as the reference standard in diagnosing sleep-related respiratory diseases such as obstructive sleep apnoea syndrome. Over 15 channels of physiological signals are measured from a subject undergoing a typical overnight PSG session. The signals often suffer from data losses, interferences and artefacts. In a typical sleep scoring session, artefact-corrupted signal segments are visually detected and removed from further consideration. This is a highly time-consuming process, and subjective judgement is required for the job. During typical sleep scoring sessions, the target is the detection of segments of diagnostic interest, and signal restoration is not utilized for distorted segments. In this paper, we propose a novel framework for artefact detection and signal restoration based on the redundancy among respiratory flow signals. We focus on the air flow (thermistor sensors) and nasal pressure signals which are clinically significant in detecting respiratory disturbances. The method treats the respiratory system and other organs that provide respiratory-related inputs/outputs to it (e.g., cardiovascular, brain) as a possibly nonlinear coupled-dynamical system, and uses the celebrated Takens embedding theorem as the theoretical basis for signal prediction. Nonlinear prediction across time (self-prediction) and signals (cross-prediction) provides us with a mechanism to detect artefacts as unexplained deviations. In addition to detection, the proposed method carries the potential to correct certain classes of artefacts and restore the signal. In this study, we categorize commonly occurring artefacts and distortions in air flow and nasal pressure measurements into several groups and explore the efficacy of the proposed technique in detecting/recovering them. The results we obtained from a database of clinical

  3. Optimizing a Synthetic Signaling System, Using Mathematical Modeling to Direct Experimental Work

    Science.gov (United States)

    2014-09-05

    arsenic , toluene, lead, DDT, mercury, etc.). The synthetic signaling system then be used to trigger a phytoremediation process upon detection of these...transferred to soil and allowed to set seed. The T1 generation will yield plants heterozygous and homozygous for the synthetic signaling system, allowing...compounds, either by breaking them down or transporting them to the aerial tissue where they can be harvested and removed from the soil

  4. Biased Type 1 Cannabinoid Receptor Signaling Influences Neuronal Viability in a Cell Culture Model of Huntington Disease.

    Science.gov (United States)

    Laprairie, Robert B; Bagher, Amina M; Kelly, Melanie E M; Denovan-Wright, Eileen M

    2016-03-01

    Huntington disease (HD) is an inherited, autosomal dominant, neurodegenerative disorder with limited treatment options. Prior to motor symptom onset or neuronal cell loss in HD, levels of the type 1 cannabinoid receptor (CB1) decrease in the basal ganglia. Decreasing CB1 levels are strongly correlated with chorea and cognitive deficit. CB1 agonists are functionally selective (biased) for divergent signaling pathways. In this study, six cannabinoids were tested for signaling bias in in vitro models of medium spiny projection neurons expressing wild-type (STHdh(Q7/Q7)) or mutant huntingtin protein (STHdh(Q111/Q111)). Signaling bias was assessed using the Black and Leff operational model. Relative activity [ΔlogR (τ/KA)] and system bias (ΔΔlogR) were calculated relative to the reference compound WIN55,212-2 for Gαi/o, Gαs, Gαq, Gβγ, and β-arrestin1 signaling following treatment with 2-arachidonoylglycerol (2-AG), anandamide (AEA), CP55,940, Δ(9)-tetrahydrocannabinol (THC), cannabidiol (CBD), and THC+CBD (1:1), and compared between wild-type and HD cells. The Emax of Gαi/o-dependent extracellular signal-regulated kinase (ERK) signaling was 50% lower in HD cells compared with wild-type cells. 2-AG and AEA displayed Gαi/o/Gβγ bias and normalized CB1 protein levels and improved cell viability, whereas CP55,940 and THC displayed β-arrestin1 bias and reduced CB1 protein levels and cell viability in HD cells. CBD was not a CB1 agonist but inhibited THC-dependent signaling (THC+CBD). Therefore, enhancing Gαi/o-biased endocannabinoid signaling may be therapeutically beneficial in HD. In contrast, cannabinoids that are β-arrestin-biased--such as THC found at high levels in modern varieties of marijuana--may be detrimental to CB1 signaling, particularly in HD where CB1 levels are already reduced. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

  5. An extended car-following model at un-signalized intersections under V2V communication environment

    Science.gov (United States)

    Wang, Tao; Li, Peng

    2018-01-01

    An extended car-following model is proposed in this paper to analyze the impacts of V2V (vehicle to vehicle) communication on the micro driving behavior at the un-signalized intersection. A four-leg un-signalized intersection with twelve streams (left-turn, through movement, and right turn from each leg) is used. The effect of the guidance strategy on the reduction of the rate of stops and total delay is explored by comparing the proposed model and the traditional FVD car-following model. The numerical results illustrate that potential conflicts between vehicles can be predicted and some stops can be avoided by decelerating in advance. The driving comfort and traffic efficiency can be improved accordingly. More benefits could be obtained under the long communication range, low to medium traffic density, and simple traffic pattern conditions. PMID:29425243

  6. FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter.

    Science.gov (United States)

    Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao

    2016-07-12

    In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved.

  7. Preliminary Modeling of Permanent Magnet Probe Flowmeter for Voltage Signal Estimation

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, Uiju; Kim, Sung Joong [Hanyang Univ., Seoul (Korea, Republic of); Jeong, Ji Young; Kim, Tae Joon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-10-15

    An experimental study on performance analysis of the flowmeter has been performed. The study shows that sodium flow rate is linearly proportional to the induced voltage signal from the flowmeter under the turbulent flow condition. The experimental results support its availability in the PDRC system. But, the flowmeter should be able to measure sodium flow at low Reynolds number as well. That is because the PDRC system uses sodium natural convection for its operation. Thus, calibration of the flowmeter should be done at very low sodium flow rates. However, Von Weissenfluh et al. showed that the relationship between flow rate and measured voltage signal from the flowmeter may become non-linear at very low flow rates. The nonlinearity restricts the utilization of level sensor which provide reference flow rate in the calibration experiment. The primary objective of this study is to predict the sodium flow rate range where the induced voltage signals are linearly proportional to flow rates by estimating the induced voltage signals against sodium flow rates for a wide range of flows numerically. A commercial code FLUENT is adopted for the analysis of flow field. And MAXWELL which is an electromagnetic analysis software using a finite volume method has been used to analyze the magnetic field generated by permanent magnet of the flowmeter. The induced voltage signals have been estimated by coupling the sodium flow field and the magnetic field using FLUENT MHD module. It is expected that the PMPF voltage signals are linearly proportional to flow rates range of 0.0059 to 1.96 lps. This suggests that simple calibration technique using the linearity between flow rate and the voltage signal can be adopted in calibration of the PMPF.

  8. Synthetic modeling chemistry of iron-sulfur clusters in nitric oxide signaling.

    Science.gov (United States)

    Fitzpatrick, Jessica; Kim, Eunsuk

    2015-08-18

    Nitric oxide (NO) is an important signaling molecule that is involved in many physiological and pathological functions. Iron-sulfur proteins are one of the main reaction targets for NO, and the [Fe-S] clusters within these proteins are converted to various iron nitrosyl species upon reaction with NO, of which dinitrosyl iron complexes (DNICs) are the most prevalent. Much progress has been made in identifying the origin of cellular DNIC generation. However, it is not well-understood which other products besides DNICs may form during [Fe-S] cluster degradation nor what effects DNICs and other degradation products can have once they are generated in cells. Even more elusive is an understanding of the manner by which cells cope with unwanted [Fe-S] modifications by NO. This Account describes our synthetic modeling efforts to identify cluster degradation products derived from the [2Fe-2S]/NO reaction in order to establish their chemical reactivity and repair chemistry. Our intent is to use the chemical knowledge that we generate to provide insight into the unknown biological consequences of cluster modification. Our recent advances in three different areas are described. First, new reaction conditions that lead to the formation of previously unrecognized products during the reaction of [Fe-S] clusters with NO are identified. Hydrogen sulfide (H2S), a gaseous signaling molecule, can be generated from the reaction between [2Fe-2S] clusters and NO in the presence of acid or formal H• (e(-)/H(+)) donors. In the presence of acid, a mononitrosyl iron complex (MNIC) can be produced as the major iron-containing product. Second, cysteine analogues can efficiently convert MNICs back to [2Fe-2S] clusters without the need for any other reagents. This reaction is possible for cysteine analogues because of their ability to labilize NO from MNICs and their capacity to undergo C-S bond cleavage, providing the necessary sulfide for [2Fe-2S] cluster formation. Lastly, unique dioxygen

  9. Sample Entropy Analysis of EEG Signals via Artificial Neural Networks to Model Patients’ Consciousness Level Based on Anesthesiologists Experience

    Directory of Open Access Journals (Sweden)

    George J. A. Jiang

    2015-01-01

    Full Text Available Electroencephalogram (EEG signals, as it can express the human brain’s activities and reflect awareness, have been widely used in many research and medical equipment to build a noninvasive monitoring index to the depth of anesthesia (DOA. Bispectral (BIS index monitor is one of the famous and important indicators for anesthesiologists primarily using EEG signals when assessing the DOA. In this study, an attempt is made to build a new indicator using EEG signals to provide a more valuable reference to the DOA for clinical researchers. The EEG signals are collected from patients under anesthetic surgery which are filtered using multivariate empirical mode decomposition (MEMD method and analyzed using sample entropy (SampEn analysis. The calculated signals from SampEn are utilized to train an artificial neural network (ANN model through using expert assessment of consciousness level (EACL which is assessed by experienced anesthesiologists as the target to train, validate, and test the ANN. The results that are achieved using the proposed system are compared to BIS index. The proposed system results show that it is not only having similar characteristic to BIS index but also more close to experienced anesthesiologists which illustrates the consciousness level and reflects the DOA successfully.

  10. Measurement of oxygen extraction fraction (OEF): An optimized BOLD signal model for use with hypercapnic and hyperoxic calibration.

    Science.gov (United States)

    Merola, Alberto; Murphy, Kevin; Stone, Alan J; Germuska, Michael A; Griffeth, Valerie E M; Blockley, Nicholas P; Buxton, Richard B; Wise, Richard G

    2016-04-01

    Several techniques have been proposed to estimate relative changes in cerebral metabolic rate of oxygen consumption (CMRO2) by exploiting combined BOLD fMRI and cerebral blood flow data in conjunction with hypercapnic or hyperoxic respiratory challenges. More recently, methods based on respiratory challenges that include both hypercapnia and hyperoxia have been developed to assess absolute CMRO2, an important parameter for understanding brain energetics. In this paper, we empirically optimize a previously presented "original calibration model" relating BOLD and blood flow signals specifically for the estimation of oxygen extraction fraction (OEF) and absolute CMRO2. To do so, we have created a set of synthetic BOLD signals using a detailed BOLD signal model to reproduce experiments incorporating hypercapnic and hyperoxic respiratory challenges at 3T. A wide range of physiological conditions was simulated by varying input parameter values (baseline cerebral blood volume (CBV0), baseline cerebral blood flow (CBF0), baseline oxygen extraction fraction (OEF0) and hematocrit (Hct)). From the optimization of the calibration model for estimation of OEF and practical considerations of hypercapnic and hyperoxic respiratory challenges, a new "simplified calibration model" is established which reduces the complexity of the original calibration model by substituting the standard parameters α and β with a single parameter θ. The optimal value of θ is determined (θ=0.06) across a range of experimental respiratory challenges. The simplified calibration model gives estimates of OEF0 and absolute CMRO2 closer to the true values used to simulate the experimental data compared to those estimated using the original model incorporating literature values of α and β. Finally, an error propagation analysis demonstrates the susceptibility of the original and simplified calibration models to measurement errors and potential violations in the underlying assumptions of isometabolism

  11. Conflict anticipation in alcohol dependence - A model-based fMRI study of stop signal task.

    Science.gov (United States)

    Hu, Sien; Ide, Jaime S; Zhang, Sheng; Sinha, Rajita; Li, Chiang-Shan R

    2015-01-01

    Our previous work characterized altered cerebral activations during cognitive control in individuals with alcohol dependence (AD). A hallmark of cognitive control is the ability to anticipate changes and adjust behavior accordingly. Here, we employed a Bayesian model to describe trial-by-trial anticipation of the stop signal and modeled fMRI signals of conflict anticipation in a stop signal task. Our goal is to characterize the neural correlates of conflict anticipation and its relationship to response inhibition and alcohol consumption in AD. Twenty-four AD and 70 age and gender matched healthy control individuals (HC) participated in the study. fMRI data were pre-processed and modeled with SPM8. We modeled fMRI signals at trial onset with individual events parametrically modulated by estimated probability of the stop signal, p(Stop), and compared regional responses to conflict anticipation between AD and HC. To address the link to response inhibition, we regressed whole-brain responses to conflict anticipation against the stop signal reaction time (SSRT). Compared to HC (54/70), fewer AD (11/24) showed a significant sequential effect - a correlation between p(Stop) and RT during go trials - and the magnitude of sequential effect is diminished, suggesting a deficit in proactive control. Parametric analyses showed decreased learning rate and over-estimated prior mean of the stop signal in AD. In fMRI, both HC and AD responded to p(Stop) in bilateral inferior parietal cortex and anterior pre-supplementary motor area, although the magnitude of response increased in AD. In contrast, HC but not AD showed deactivation of the perigenual anterior cingulate cortex (pgACC). Furthermore, deactivation of the pgACC to increasing p(Stop) is positively correlated with the SSRT in HC but not AD. Recent alcohol consumption is correlated with increased activation of the thalamus and cerebellum in AD during conflict anticipation. The current results highlight altered proactive

  12. Delayed signatures of underground nuclear explosions

    Science.gov (United States)

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

    2016-03-01

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

  13. [Modeling the occurrence of shellfish poisoning outbreaks caused by Gymnodinium catenatum (Dinophyceae) through electromagnetic signal triggering].

    Science.gov (United States)

    Vale, Pulo

    2014-01-01

    Accumulation of paralytic shellfish poisoning toxins (PSTs) in bivalves attributed to Gymnodinium catenatum blooms at the NW Portuguese coast was previously associated with periods of low solar activity (measured by the radio flux [R]), or low geomagnetic A(a) index. It was also observed that reduction of R preceded the occurrence of toxin accumulation, while A(a) index increase could be related to its absence during periods of low activity. For modeling toxin accumulation, the monthly decrease in R was studied along the decade 2003-2012. A match that helped explaining the highly toxic years of 2007 and 2008 was obtained by plotting the formula: ΔR = (R(n-1) - R(n))/(R(n) - 65)2, where 65 represented the lowest radio activity known to date. The complex denominator was required to take into account the sunspot cycle. A 1-2 month lag was observed between maximal relative decline and maximal PSTs accumulation. PSTs in bivalves from the Portuguese south coast were related with natural electromagnetic cycles for the first time, and were not statistically associated with low R. A statistically significant association with low A(a) index also was not achieved, due to the low number of occurrences, although the 25-75 percentile was restricted to low Aa indexes in a similar way to that found for the NW coast. PSTs accumulation outside solar minima could be triggered by a steep decline in the A(a) index (ΔA), but no lag was observed in this case. While ΔR amplitude helped explaining the highly toxic years of 2007 and 2008 at the NW coast, the amplitude of ΔA was not related to the severity of the accumulation. Other kind of local electromagnetic signaling was investigated resorting to the occurrence of seismologic phenomena, because these events can trigger electric activities. No statistical association was found between seism number or magnitude and PSTs at the south coast, located near the boundary between the African and Eurasian plates, and marked by moderate

  14. Prediction of Above-elbow Motions in Amputees, based on Electromyographic(EMG Signals, Using Nonlinear Autoregressive Exogenous (NARX Model

    Directory of Open Access Journals (Sweden)

    Ali Akbar Akbari

    2014-08-01

    Full Text Available Introduction In order to improve the quality of life of amputees, biomechatronic researchers and biomedical engineers have been trying to use a combination of various techniques to provide suitable rehabilitation systems. Diverse biomedical signals, acquired from a specialized organ or cell system, e.g., the nervous system, are the driving force for the whole system. Electromyography(EMG, as an experimental technique,is concerned with the development, recording, and analysis of myoelectric signals. EMG-based research is making progress in the development of simple, robust, user-friendly, and efficient interface devices for the amputees. Materials and Methods Prediction of muscular activity and motion patterns is a common, practical problem in prosthetic organs. Recurrent neural network (RNN models are not only applicable for the prediction of time series, but are also commonly used for the control of dynamical systems. The prediction can be assimilated to identification of a dynamic process. An architectural approach of RNN with embedded memory is Nonlinear Autoregressive Exogenous (NARX model, which seems to be suitable for dynamic system applications. Results Performance of NARX model is verified for several chaotic time series, which are applied as input for the neural network. The results showed that NARX has the potential to capture the model of nonlinear dynamic systems. The R-value and MSE are  and  , respectively. Conclusion  EMG signals of deltoid and pectoralis major muscles are the inputs of the NARX  network. It is possible to obtain EMG signals of muscles in other arm motions to predict the lost functions of the absent arm in above-elbow amputees, using NARX model.

  15. Bistatic SAR/ISAR/FSR geometry, signal models and imaging algorithms

    CERN Document Server

    Lazarov, Andon Dimitrov

    2013-01-01

    Bistatic radar consists of a radar system which comprises a transmitter and receiver which are separated by a distance comparable to the expected target distance. This book provides a general theoretical description of such bistatic technology in the context of synthetic aperture, inverse synthetic aperture and forward scattering radars from the point of view of analytical geometrical and signal formation as well as processing theory. Signal formation and image reconstruction algorithms are developed with the application of high informative linear frequency and phase code modulating techniques

  16. An equilibrium-point model of electromyographic patterns during single-joint movements based on experimentally reconstructed control signals.

    Science.gov (United States)

    Latash, M L; Goodman, S R

    1994-01-01

    The purpose of this work has been to develop a model of electromyographic (EMG) patterns during single-joint movements based on a version of the equilibrium-point hypothesis, a method for experimental reconstruction of the joint compliant characteristics, the dual-strategy hypothesis, and a kinematic model of movement trajectory. EMG patterns are considered emergent properties of hypothetical control patterns that are equally affected by the control signals and peripheral feedback reflecting actual movement trajectory. A computer model generated the EMG patterns based on simulated movement kinematics and hypothetical control signals derived from the reconstructed joint compliant characteristics. The model predictions have been compared to published recordings of movement kinematics and EMG patterns in a variety of movement conditions, including movements over different distances, at different speeds, against different-known inertial loads, and in conditions of possible unexpected decrease in the inertial load. Changes in task parameters within the model led to simulated EMG patterns qualitatively similar to the experimentally recorded EMG patterns. The model's predictive power compares it favourably to the existing models of the EMG patterns. Copyright © 1994. Published by Elsevier Ltd.

  17. Improvements to the extraction of an AlGaN/GaN HEMT small-signal model

    International Nuclear Information System (INIS)

    Pu Yan; Pang Lei; Wang Liang; Chen Xiaojuan; Li Chengzhan; Liu Xinyu

    2009-01-01

    The accurate extraction of AlGaN/GaN HEMT small-signal models, which is an important step in large-signal modeling, can exactly reflect the microwave performance of the physical structure of the device. A new method of extracting the parasitic elements is presented, and an open dummy structure is introduced to obtain the parasitic capacitances. With a Schottky resistor in the gate, a new method is developed to extract R g . In order to characterize the changes of the depletion region under various drain voltages, the drain delay factor is involved in the output conductance of the device. Compared to the traditional method, the fitting of S 11 and S 22 is improved, and f T and f max can be better predicted. The validity of the proposed method is verified with excellent correlation between the measured and simulated S-parameters in the range of 0.1 to 26.1 GHz. (semiconductor devices)

  18. Computational Analysis and Simulation of Empathic Behaviors: a Survey of Empathy Modeling with Behavioral Signal Processing Framework.

    Science.gov (United States)

    Xiao, Bo; Imel, Zac E; Georgiou, Panayiotis; Atkins, David C; Narayanan, Shrikanth S

    2016-05-01

    Empathy is an important psychological process that facilitates human communication and interaction. Enhancement of empathy has profound significance in a range of applications. In this paper, we review emerging directions of research on computational analysis of empathy expression and perception as well as empathic interactions, including their simulation. We summarize the work on empathic expression analysis by the targeted signal modalities (e.g., text, audio, and facial expressions). We categorize empathy simulation studies into theory-based emotion space modeling or application-driven user and context modeling. We summarize challenges in computational study of empathy including conceptual framing and understanding of empathy, data availability, appropriate use and validation of machine learning techniques, and behavior signal processing. Finally, we propose a unified view of empathy computation and offer a series of open problems for future research.

  19. A simple testable model of baryon number violation: Baryogenesis, dark matter, neutron-antineutron oscillation and collider signals

    Science.gov (United States)

    Allahverdi, Rouzbeh; Dev, P. S. Bhupal; Dutta, Bhaskar

    2018-04-01

    We study a simple TeV-scale model of baryon number violation which explains the observed proximity of the dark matter and baryon abundances. The model has constraints arising from both low and high-energy processes, and in particular, predicts a sizable rate for the neutron-antineutron (n - n bar) oscillation at low energy and the monojet signal at the LHC. We find an interesting complementarity among the constraints arising from the observed baryon asymmetry, ratio of dark matter and baryon abundances, n - n bar oscillation lifetime and the LHC monojet signal. There are regions in the parameter space where the n - n bar oscillation lifetime is found to be more constraining than the LHC constraints, which illustrates the importance of the next-generation n - n bar oscillation experiments.

  20. Modeling of the Signal Formation in SiC Sensors for Measurements of the Radiation Spectrum in Nuclear Energy

    International Nuclear Information System (INIS)

    Krolikowski, Igor P.

    2013-06-01

    The modeling methodology of the signal formation in SiC sensors is presented. The modeling uses two approaches: the first one is the integrated approach whereas the second is the analytical approach. The sensor response is obtained from both approaches: this is the usual solution of the forward problem. Moreover, the response function of the sensor is evaluated by means of the analytical approach and it can be used to solve the inverse problem: recovering the primary radiation spectrum using the response of the sensor. Additionally, the response function returns information about the signal formation in the sensor such as the shape of the response formed by particles with a specific energy. Results obtained by simulations are then compared with experimental data. (authors)

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

    DEFF Research Database (Denmark)

    Nørum, Ulrik; Brinkløv, Signe; Surlykke, Annemarie

    2012-01-01

    Echolocating bats emit ultrasonic calls and listen for the returning echoes to orient and localize prey in darkness. The emitted source level, SL (estimated signal intensity 10 cm from the mouth), is adjusted dynamically from call to call in response to sensory feedback as bats approach objects. ...

  2. Adaptive interpolation of discrete-time signals that can be modeled as autoregressive processes

    NARCIS (Netherlands)

    Janssen, A.J.E.M.; Veldhuis, R.N.J.; Vries, L.B.

    1986-01-01

    The authors present an adaptive algorithm for the restoration of lost sample values in discrete-time signals that can locally be described by means of autoregressive processes. The only restrictions are that the positions of the unknown samples should be known and that they should be embedded in a

  3. Adaptive interpolation of discrete-time signals that can be modeled as autoregressive processes

    NARCIS (Netherlands)

    Janssen, A.J.E.M.; Veldhuis, Raymond N.J.; Vries, Lodewijk B.

    1986-01-01

    This paper presents an adaptive algorithm for the restoration of lost sample values in discrete-time signals that can locally be described by means of autoregressive processes. The only restrictions are that the positions of the unknown samples should be known and that they should be embedded in a

  4. Maximum likelihood estimation of signal detection model parameters for the assessment of two-stage diagnostic strategies.

    Science.gov (United States)

    Lirio, R B; Dondériz, I C; Pérez Abalo, M C

    1992-08-01

    The methodology of Receiver Operating Characteristic curves based on the signal detection model is extended to evaluate the accuracy of two-stage diagnostic strategies. A computer program is developed for the maximum likelihood estimation of parameters that characterize the sensitivity and specificity of two-stage classifiers according to this extended methodology. Its use is briefly illustrated with data collected in a two-stage screening for auditory defects.

  5. Buck-Boost DC-DC Converter Control by Using the Extracted Model from Signal Flow Graph Method

    OpenAIRE

    Mohammadian, Leila; Babaei, Ebrahim; Bannae Sharifian, Mohammad Bagher

    2015-01-01

    In this paper, the signal flow graph technique and Mason gain formula are applied for extracting the model and transfer functions from control to output and from input to output of a buck-boost converter. In order to investigate a controller necessity for the converter of assumed parameters, the frequency and time domain analysis are done and the open loop system characteristics are verified and the needed closed loop controlled system specifications are determined. Finally designing a contro...

  6. Detailed qualitative dynamic knowledge representation using a BioNetGen model of TLR-4 signaling and preconditioning.

    Science.gov (United States)

    An, Gary C; Faeder, James R

    2009-01-01

    Intracellular signaling/synthetic pathways are being increasingly extensively characterized. However, while these pathways can be displayed in static diagrams, in reality they exist with a degree of dynamic complexity that is responsible for heterogeneous cellular behavior. Multiple parallel pathways exist and interact concurrently, limiting the ability to integrate the various identified mechanisms into a cohesive whole. Computational methods have been suggested as a means of concatenating this knowledge to aid in the understanding of overall system dynamics. Since the eventual goal of biomedical research is the identification and development of therapeutic modalities, computational representation must have sufficient detail to facilitate this 'engineering' process. Adding to the challenge, this type of representation must occur in a perpetual state of incomplete knowledge. We present a modeling approach to address this challenge that is both detailed and qualitative. This approach is termed 'dynamic knowledge representation,' and is intended to be an integrated component of the iterative cycle of scientific discovery. BioNetGen (BNG), a software platform for modeling intracellular signaling pathways, was used to model the toll-like receptor 4 (TLR-4) signal transduction cascade. The informational basis of the model was a series of reference papers on modulation of (TLR-4) signaling, and some specific primary research papers to aid in the characterization of specific mechanistic steps in the pathway. This model was detailed with respect to the components of the pathway represented, but qualitative with respect to the specific reaction coefficients utilized to execute the reactions. Responsiveness to simulated lipopolysaccharide (LPS) administration was measured by tumor necrosis factor (TNF) production. Simulation runs included evaluation of initial dose-dependent response to LPS administration at 10, 100, 1000 and 10,000, and a subsequent examination of

  7. Precursory tremor of the Askja Caldera landslide, July 2014 - seismic signal analysis and numerical modelling

    Science.gov (United States)

    Lipovsky, B. P.; Schöpa, A.; Chao, W. A.; Hovius, N.; White, R. S.; Green, R. G.

    2017-12-01

    Seismic records can contain valuable information about triggers and precursors of slope failures that might become useful for early-warning purposes. We investigated the seismic data of 52 stations from the University of Cambridge, UK, with respect to the tremor signals preceding a 20-80x106 m3 landslide at the Askja caldera in the Icelandic highlands on 21 July 2014. The landslide created a tsunami in the caldera lake, which inundated the shore up to 60 m high reaching famous tourist spots. This shows the high hazard potential of the site that motivated this study. About 30 min before the landslide, the seismic ground velocities >1 Hz of stations up to 30 km away from the landslide source area started to increase and the tremor signal reached up to three times the background noise level about 7 min before the landslide. In the spectral domain, the tremor is visible as a continuous, harmonic signal with a fundamental frequency of 2.5 Hz and overtones at 5 and 7.5 Hz. About 10 min before the landslide, the activated frequency bands changed their spectral content and up and down gliding is observed contemporaneously. The tremor signal ceases about 5 min before the high-energy failure of the landslide. We interpret the harmonic tremor before the landslide as stick-slip motion on fault patches at the boundaries of the landslide mass. Individual stick-slip events cannot be distinguished in the seismic data and thus have already merged into continuous tremor as they occur very close in time. As up and down gliding of the frequency bands occurs at the same time we favour an explanation where several fault patches are active simultaneously. One patch might accelerate and create up gliding signals and another patch might decelerate and create down gliding. We matched synthetic seismograms produced by numerical simulations of stick-slip movement and the seismic observations. The results show that a patch with a radius of 45 m and a realistic landslide thickness of 30 m can

  8. Research on Healthy Anomaly Detection Model Based on Deep Learning from Multiple Time-Series Physiological Signals

    Directory of Open Access Journals (Sweden)

    Kai Wang

    2016-01-01

    Full Text Available Health is vital to every human being. To further improve its already respectable medical technology, the medical community is transitioning towards a proactive approach which anticipates and mitigates risks before getting ill. This approach requires measuring the physiological signals of human and analyzes these data at regular intervals. In this paper, we present a novel approach to apply deep learning in physiological signals analysis that allows doctor to identify latent risks. However, extracting high level information from physiological time-series data is a hard problem faced by the machine learning communities. Therefore, in this approach, we apply model based on convolutional neural network that can automatically learn features from raw physiological signals in an unsupervised manner and then based on the learned features use multivariate Gauss distribution anomaly detection method to detect anomaly data. Our experiment is shown to have a significant performance in physiological signals anomaly detection. So it is a promising tool for doctor to identify early signs of illness even if the criteria are unknown a priori.

  9. Pharmacologic Activation of Wnt Signaling by Lithium Normalizes Retinal Vasculature in a Murine Model of Familial Exudative Vitreoretinopathy.

    Science.gov (United States)

    Wang, Zhongxiao; Liu, Chi-Hsiu; Sun, Ye; Gong, Yan; Favazza, Tara L; Morss, Peyton C; Saba, Nicholas J; Fredrick, Thomas W; He, Xi; Akula, James D; Chen, Jing

    2016-10-01

    Familial exudative vitreoretinopathy (FEVR) is characterized by delayed retinal vascular development, which promotes hypoxia-induced pathologic vessels. In severe cases FEVR may lead to retinal detachment and visual impairment. Genetic studies linked FEVR with mutations in Wnt signaling ligand or receptors, including low-density lipoprotein receptor-related protein 5 (LRP5) gene. Here, we investigated ocular pathologies in a Lrp5 knockout (Lrp5(-/-)) mouse model of FEVR and explored whether treatment with a pharmacologic Wnt activator lithium could bypass the genetic defects, thereby protecting against eye pathologies. Lrp5(-/-) mice displayed significantly delayed retinal vascular development, absence of deep layer retinal vessels, leading to increased levels of vascular endothelial growth factor and subsequent pathologic glomeruloid vessels, as well as decreased inner retinal visual function. Lithium treatment in Lrp5(-/-) mice significantly restored the delayed development of retinal vasculature and the intralaminar capillary networks, suppressed formation of pathologic glomeruloid structures, and promoted hyaloid vessel regression. Moreover, lithium treatment partially rescued inner-retinal visual function and increased retinal thickness. These protective effects of lithium were largely mediated through restoration of canonical Wnt signaling in Lrp5(-/-) retina. Lithium treatment also substantially increased vascular tubular formation in LRP5-deficient endothelial cells. These findings suggest that pharmacologic activation of Wnt signaling may help treat ocular pathologies in FEVR and potentially other defective Wnt signaling-related diseases. Copyright © 2016 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

  10. Inhibition of WNT signaling in the bone marrow niche prevents the development of MDS in the Apcdel/+ MDS mouse model.

    Science.gov (United States)

    Stoddart, Angela; Wang, Jianghong; Hu, Chunmei; Fernald, Anthony A; Davis, Elizabeth M; Cheng, Jason X; Le Beau, Michelle M

    2017-06-01

    There is accumulating evidence that functional alteration(s) of the bone marrow (BM) microenvironment contribute to the development of some myeloid disorders, such as myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). In addition to a cell-intrinsic role of WNT activation in leukemia stem cells, WNT activation in the BM niche is also thought to contribute to the pathogenesis of MDS and AML. We previously showed that the Apc -haploinsufficient mice ( Apc del/+ ) model MDS induced by an aberrant BM microenvironment. We sought to determine whether Apc, a multifunctional protein and key negative regulator of the canonical β-catenin (Ctnnb1)/WNT-signaling pathway, mediates this disease through modulating WNT signaling, and whether inhibition of WNT signaling prevents the development of MDS in Apc del/+ mice. Here, we demonstrate that loss of 1 copy of Ctnnb1 is sufficient to prevent the development of MDS in Apc del/+ mice and that altered canonical WNT signaling in the microenvironment is responsible for the disease. Furthermore, the US Food and Drug Administration (FDA)-approved drug pyrvinium delays and/or inhibits disease in Apc del /+ mice, even when it is administered after the presentation of anemia. Other groups have observed increased nuclear CTNNB1 in stromal cells from a high frequency of MDS/AML patients, a finding that together with our results highlights a potential new strategy for treating some myeloid disorders. © 2017 by The American Society of Hematology.

  11. Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system

    Directory of Open Access Journals (Sweden)

    Das Sajal K

    2010-12-01

    Full Text Available Abstract Background The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the “in silico” stochastic event based modeling approach to find the molecular dynamics of the system. Results In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Conclusions Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model

  12. Small-Signal Modeling, Analysis and Testing of Parallel Three-Phase-Inverters with A Novel Autonomous Current Sharing Controller

    DEFF Research Database (Denmark)

    Guan, Yajuan; Quintero, Juan Carlos Vasquez; Guerrero, Josep M.

    2015-01-01

    A novel simple and effective autonomous currentsharing controller for parallel three-phase inverters is employed in this paper. The novel controller is able to endow to the system high speed response and precision in contrast to the conventional droop control as it does not require calculating any...... active or reactive power, instead it uses a virtual impedance loop and a SFR phase-locked loop. The small-signal model of the system was developed for the autonomous operation of inverter-based microgrid with the proposed controller. The developed model shows large stability margin and fast transient...

  13. Characterization and modelling of signal dynamics in 3D-DDTC detectors

    International Nuclear Information System (INIS)

    Zoboli, A.; Boscardin, M.; Bosisio, L.; Dalla Betta, G.-F.; Gabos, P.; Piemonte, C.; Ronchin, S.; Zorzi, N.

    2010-01-01

    In the past few years we have developed 3D detector technologies within a collaboration between INFN and FBK-irst aiming at a simplification of the fabrication technology with respect to the original 3D design. These detectors are the object of an increasing interest from the HEP community because of their intrinsic radiation hardness, making them appealing for innermost layers of tracking at the foreseen upgrades of the large hadron collider. In this paper we evaluate the signal shape in response to localized and uniform charge deposition both by solving Ramo's theorem and with the aid of TCAD simulations. Signals observed in 3D diodes, stimulated by lasers at different wavelengths, are compared with simulations results.

  14. Characterization and modelling of signal dynamics in 3D-DDTC detectors

    Energy Technology Data Exchange (ETDEWEB)

    Zoboli, A., E-mail: zoboli@disi.unitn.i [INFN, Sezione di Padova (Gruppo Collegato di Trento), and Dipartimento di Ingegneria e Scienza dell' Informazione, Universita di Trento, Via Sommarive, 14, I-38050 Povo (Trento) (Italy); Boscardin, M. [Fondazione Bruno Kessler, Centro per i Materiali e i Microsistemi, Via Sommarive, 18, I-38050 Povo (Trento) (Italy); Bosisio, L. [INFN, Sezione di Trieste, e Dipartimento di Fisica, Universita di Trieste, I-34127 Trieste (Italy); Dalla Betta, G.-F.; Gabos, P. [INFN, Sezione di Padova (Gruppo Collegato di Trento), and Dipartimento di Ingegneria e Scienza dell' Informazione, Universita di Trento, Via Sommarive, 14, I-38050 Povo (Trento) (Italy); Piemonte, C.; Ronchin, S.; Zorzi, N. [Fondazione Bruno Kessler, Centro per i Materiali e i Microsistemi, Via Sommarive, 18, I-38050 Povo (Trento) (Italy)

    2010-05-21

    In the past few years we have developed 3D detector technologies within a collaboration between INFN and FBK-irst aiming at a simplification of the fabrication technology with respect to the original 3D design. These detectors are the object of an increasing interest from the HEP community because of their intrinsic radiation hardness, making them appealing for innermost layers of tracking at the foreseen upgrades of the large hadron collider. In this paper we evaluate the signal shape in response to localized and uniform charge deposition both by solving Ramo's theorem and with the aid of TCAD simulations. Signals observed in 3D diodes, stimulated by lasers at different wavelengths, are compared with simulations results.

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

    Science.gov (United States)

    2013-09-05

    to be construed as official or as reflecting the views of the Army or the Department of Defense. Citations of commercial organizations and trade names...commercial organizations and trade names in this report do not constitute an official Department of the Army endorsement or approval of the products or...pathway. Nature Medicine 6: 422–428. 93. Murray PJ (2007) The jak-stat signaling pathway: Input and output intergration . Journal of Immunology 178

  16. Modeling DNA?damage-induced pneumopathy in mice: insight from danger signaling cascades

    OpenAIRE

    Wirsd?rfer, Florian; Jendrossek, Verena

    2017-01-01

    Radiation-induced pneumonitis and fibrosis represent severe and dose-limiting side effects in the radiotherapy of thorax-associated neoplasms leading to decreased quality of life or - as a consequence of treatment with suboptimal radiation doses - to fatal outcomes by local recurrence or metastatic disease. It is assumed that the initial radiation-induced damage to the resident cells triggers a multifaceted damage-signalling cascade in irradiated normal tissues including a multifactorial secr...

  17. The Yeast Retrograde Response as a Model of Intracellular Signaling of Mitochondrial Dysfunction

    Directory of Open Access Journals (Sweden)

    S. Michal eJazwinski

    2012-05-01

    Full Text Available Mitochondrial dysfunction activates intracellular signaling pathways that impact yeast longevity, and the best known of these pathways is the retrograde response. More recently, similar responses have been discerned in other systems, from invertebrates to human cells. However, the identity of the signal transducers is either unknown or apparently diverse, contrasting with the well-established signaling module of the yeast retrograde response. On the other hand, it has become equally clear that several other pathways and processes interact with the retrograde response, embedding it in a network responsive to a variety of cellular states. An examination of this network supports the notion that the master regulator NFkB aggregated a variety of mitochondria-related cellular responses at some point in evolution and has become the retrograde transcription factor. This has significant consequences for how we view some of the deficits associated with aging, such as inflammation. The support for NFkB as the retrograde response transcription factor is not only based on functional analyses. It is bolstered by the fact that NFkB can regulate Myc-Max, which is activated in human cells with dysfunctional mitochondria and impacts cellular metabolism. Myc-Max is homologous to the yeast retrograde response transcription factor Rtg1-Rtg3. Further research will be needed to disentangle the pro-aging from the anti-aging effects of NFkB. Interestingly, this is also a challenge for the complete understanding of the yeast retrograde response.

  18. Modeling of coupled differential equations for cellular chemical signaling pathways: Implications for assay protocols utilized in cellular engineering.

    Science.gov (United States)

    O'Clock, George D

    2016-08-01

    Cellular engineering involves modification and control of cell properties, and requires an understanding of fundamentals and mechanisms of action for cellular derived product development. One of the keys to success in cellular engineering involves the quality and validity of results obtained from cell chemical signaling pathway assays. The accuracy of the assay data cannot be verified or assured if the effect of positive feedback, nonlinearities, and interrelationships between cell chemical signaling pathway elements are not understood, modeled, and simulated. Nonlinearities and positive feedback in the cell chemical signaling pathway can produce significant aberrations in assay data collection. Simulating the pathway can reveal potential instability problems that will affect assay results. A simulation, using an electrical analog for the coupled differential equations representing each segment of the pathway, provides an excellent tool for assay validation purposes. With this approach, voltages represent pathway enzyme concentrations and operational amplifier feedback resistance and input resistance values determine pathway gain and rate constants. The understanding provided by pathway modeling and simulation is strategically important in order to establish experimental controls for assay protocol structure, time frames specified between assays, and assay concentration variation limits; to ensure accuracy and reproducibility of results.

  19. Probing the Standard Model with Higgs signal rates from the Tevatron, the LHC and a future ILC

    International Nuclear Information System (INIS)

    Bechtle, P.; Staal, O.

    2014-03-01

    We explore the room for possible deviations from the Standard Model (SM) Higgs boson coupling structure in a systematic study of Higgs coupling scale factor (κ) benchmark scenarios using the latest signal rate measurements from the Tevatron and LHC experiments. We employ a profile likelihood method based on a χ 2 test performed with HiggsSignals, which takes into account detailed information on signal efficiencies and major correlations of theoretical and experimental uncertainties. All considered scenarios allow for additional non-standard Higgs boson decay modes, and various assumptions for constraining the total decay width are discussed. No significant deviations from the SM Higgs boson coupling structure are found in any of the investigated benchmark scenarios. We derive upper limits on an additional (undetectable) Higgs decay mode under the assumption that the Higgs couplings to weak gauge bosons do not exceed the SM prediction. We furthermore discuss the capabilities of future facilities for probing deviations from the SM Higgs couplings, comparing the high luminosity upgrade of the LHC with a future International Linear Collider (ILC), where for the latter various energy and luminosity scenarios are considered. At the ILC model-independent measurements of the coupling structure can be performed, and we provide estimates of the precision that can be achieved.

  20. A one-dimensional model of PCP signaling: polarized cell behavior in the notochord of the ascidian Ciona.

    Science.gov (United States)

    Kourakis, Matthew J; Reeves, Wendy; Newman-Smith, Erin; Maury, Benoit; Abdul-Wajid, Sarah; Smith, William C

    2014-11-01

    Despite its importance in development and physiology the planar cell polarity (PCP) pathway remains one of the most enigmatic signaling mechanisms. The notochord of the ascidian Ciona provides a unique model for investigating the PCP pathway. Interestingly, the notochord appears to be the only embryonic structure in Ciona activating the PCP pathway. Moreover, the Ciona notochord as a single-file array of forty polarized cells is a uniquely tractable system for the study of polarization dynamics and the transmission of the PCP pathway. Here, we test models for propagation of a polarizing signal, interrogating temporal, spatial and signaling requirements. A simple cell-cell relay cascading through the entire length of the notochord is not supported; instead a more complex mechanism is revealed, with interactions influencing polarity between neighboring cells, but not distant ones. Mechanisms coordinating notochord-wide polarity remain elusive, but appear to entrain general (i.e., global) polarity even while local interactions remain important. However, this global polarizer does not appear to act as a localized, spatially-restricted determinant. Coordination of polarity along the long axis of the notochord requires the PCP pathway, a role we demonstrate is temporally distinct from this pathway's earlier role in convergent extension and intercalation. We also reveal polarity in the notochord to be dynamic: a cell's polarity state can be changed and then restored, underscoring the Ciona notochord's amenability for in vivo studies of PCP. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Mono-jet, -photon and -Z signals of a supersymmetric (B−L) model at the Large Hadron Collider

    Energy Technology Data Exchange (ETDEWEB)

    Abdallah, W. [Center for Fundamental Physics, Zewail City of Science and Technology,6 October City, Giza (Egypt); Department of Mathematics, Faculty of Science, Cairo University,Giza (Egypt); Fiaschi, J. [School of Physics and Astronomy, University of Southampton,Highfield, Southampton (United Kingdom); Khalil, S. [Center for Fundamental Physics, Zewail City of Science and Technology,6 October City, Giza (Egypt); Moretti, S. [School of Physics and Astronomy, University of Southampton,Highfield, Southampton (United Kingdom)

    2016-02-23

    Search for invisible final states produced at the Large Hadron Collider (LHC) by new physics scenarios are normally carried out resorting to a variety of probes emerging from the initial state, in the form of single-jet, -photon and -Z boson signatures. These are particularly effective for models of Supersymmetry (SUSY) in presence of R-parity conservation, owing to the presence in their spectra of a stable neutralino as a Dark Matter (DM) candidate. We assume here as theoretical framework the Supersymmetric version of the (B−L) extension of the Standard Model (BLSSM), wherein a mediator for invisible decays can be the Z{sup ′} boson present in this scenario. The peculiarity of the signal is thus that the final state objects carry a very large (transverse) missing energy, since the Z{sup ′} is naturally massive and constrained by direct searches and Electro-Weak Precision Tests (EWPTs) to be at least in the TeV scale region. Under these circumstances the efficiency in accessing the invisible final state and rejecting the Standard Model (SM) background is very high. This somehow compensates the rather meagre production rates. Another special feature of this invisible BLSSM signal is its composition, which is often dominated by sneutrino decays (alongside the more traditional neutrino and neutralino modes). Sensitivity of the CERN machine to these two features can therefore help disentangling the BLSSM from more popular SUSY models. We assess in this analysis the scope of the LHC in establishing the aforementioned invisible signals through a sophisticated signal-to-background simulation carried out in presence of parton shower, hadronisation as well as detector effects. We find that significant sensitivity exists already after 300 fb{sup −1} during Run 2. We find that mono-jet events can be readily accessible at the LHC, so as to enable one to claim a prompt discovery, while mono-photon and -Z signals can be used as diagnostic tools of the underlying scenario.

  2. 3D FDTD modelling of GPR: the effects of antenna polarisation on gpr signals from nonmetal pipes

    International Nuclear Information System (INIS)

    Amiruddin Shaari

    2003-01-01

    A 3D finite-difference time domain (FDTD) modelling of ground penetrating radar (GPR) has been carried out in order to determine the effectiveness of the method when it is used in a ground survey for metal and nonmetal pipes. In particular, the effects of the relative orientation between the antenna polarisation and pipe length and the dielectric contrast between ground soil and pipes on the GPR signal strength are investigated. The results show that the parallel antenna-target is the preferred orientation for metal pipes while the normal or orthogonal arrangement is the preferred one for the nonmetal pipes. The dielectric contrast between medium and target also seems to affect the strength the GPR signals from the nines. (Author)

  3. Comparison of Langevin and Markov channel noise models for neuronal signal generation.

    Science.gov (United States)

    Sengupta, B; Laughlin, S B; Niven, J E

    2010-01-01

    The stochastic opening and closing of voltage-gated ion channels produce noise in neurons. The effect of this noise on the neuronal performance has been modeled using either an approximate or Langevin model based on stochastic differential equations or an exact model based on a Markov process model of channel gating. Yet whether the Langevin model accurately reproduces the channel noise produced by the Markov model remains unclear. Here we present a comparison between Langevin and Markov models of channel noise in neurons using single compartment Hodgkin-Huxley models containing either Na+ and K+, or only K+ voltage-gated ion channels. The performance of the Langevin and Markov models was quantified over a range of stimulus statistics, membrane areas, and channel numbers. We find that in comparison to the Markov model, the Langevin model underestimates the noise contributed by voltage-gated ion channels, overestimating information rates for both spiking and nonspiking membranes. Even with increasing numbers of channels, the difference between the two models persists. This suggests that the Langevin model may not be suitable for accurately simulating channel noise in neurons, even in simulations with large numbers of ion channels.

  4. Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

    OpenAIRE

    Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

    2012-01-01

    Abstract Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. Background There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real...

  5. Modeling and Assessment of Precise Time Transfer by Using BeiDou Navigation Satellite System Triple-Frequency Signals

    Directory of Open Access Journals (Sweden)

    Rui Tu

    2018-03-01

    Full Text Available This study proposes two models for precise time transfer using the BeiDou Navigation Satellite System triple-frequency signals: ionosphere-free (IF combined precise point positioning (PPP model with two dual-frequency combinations (IF-PPP1 and ionosphere-free combined PPP model with a single triple-frequency combination (IF-PPP2. A dataset with a short baseline (with a common external time frequency and a long baseline are used for performance assessments. The results show that IF-PPP1 and IF-PPP2 models can both be used for precise time transfer using BeiDou Navigation Satellite System (BDS triple-frequency signals, and the accuracy and stability of time transfer is the same in both cases, except for a constant system bias caused by the hardware delay of different frequencies, which can be removed by the parameter estimation and prediction with long time datasets or by a priori calibration.

  6. Modeling of non-steroidal anti-inflammatory drug effect within signaling pathways and miRNA-regulation pathways.

    Directory of Open Access Journals (Sweden)

    Jian Li

    Full Text Available To date, it is widely recognized that Non-Steroidal Anti-Inflammatory Drugs (NSAIDs can exert considerable anti-tumor effects regarding many types of cancers. The prolonged use of NSAIDs is highly associated with diverse side effects. Therefore, tailoring down the NSAID application onto individual patients has become a necessary and relevant step towards personalized medicine. This study conducts the systemsbiological approach to construct a molecular model (NSAID model containing a cyclooxygenase (COX-pathway and its related signaling pathways. Four cancer hallmarks are integrated into the model to reflect different developmental aspects of tumorigenesis. In addition, a Flux-Comparative-Analysis (FCA based on Petri net is developed to transfer the dynamic properties (including drug responsiveness of individual cellular system into the model. The gene expression profiles of different tumor-types with available drug-response information are applied to validate the predictive ability of the NSAID model. Moreover, two therapeutic developmental strategies, synthetic lethality and microRNA (miRNA biomarker discovery, are investigated based on the COX-pathway. In conclusion, the result of this study demonstrates that the NSAID model involving gene expression, gene regulation, signal transduction, protein interaction and other cellular processes, is able to predict the individual cellular responses for different therapeutic interventions (such as NS-398 and COX-2 specific siRNA inhibition. This strongly indicates that this type of model is able to reflect the physiological, developmental and pathological processes of an individual. The approach of miRNA biomarker discovery is demonstrated for identifying miRNAs with oncogenic and tumor suppressive functions for individual cell lines of breast-, colon- and lung-tumor. The achieved results are in line with different independent studies that investigated miRNA biomarker related to diagnostics of cancer

  7. A Model for the representation of Speech Signals in Normal and Impaired Ears

    DEFF Research Database (Denmark)

    Christiansen, Thomas Ulrich

    2004-01-01

    hearing was modelled as a combination of outer- and inner hair cell loss. The percentage of dead inner hair cells was calculated based on a new computational method relating auditory nerve fibre thresholds to behavioural thresholds. Finally, a model of the entire auditory nerve fibre population......A model of human auditory periphery, ranging from the outer ear to the auditory nerve, was developed. The model consists of the following components: outer ear transfer function, middle ear transfer function, basilar membrane velocity, inner hair cell receptor potential, inner hair cell probability...... of neurotransmitter release and auditory nerve fibre refractoriness. The model builds on previously published models, however, parameters for basilar membrane velocity and inner hair cell probability of neurotransmitter release were successfully fitted to model data from psychophysical and physiological data...

  8. Ihh and Runx2/Runx3 signaling interact to coordinate early chondrogenesis: a mouse model.

    Directory of Open Access Journals (Sweden)

    Eun-Jung Kim

    Full Text Available Endochondral bone formation begins with the development of a cartilage intermediate that is subsequently replaced by calcified bone. The mechanisms occurring during early chondrogenesis that control both mesenchymal cell differentiation into chondrocytes and cell proliferation are not clearly understood in vertebrates. Indian hedgehog (Ihh, one of the hedgehog signaling molecules, is known to control both the hypertrophy of chondrocytes and bone replacement; these processes are particularly important in postnatal endochondral bone formation rather than in early chondrogenesis. In this study, we utilized the maternal transfer of 5E1 to E12.5 in mouse embryos, a process that leads to an attenuation of Ihh activity. As a result, mouse limb bud chondrogenesis was inhibited, and an exogenous recombinant IHH protein enhanced the proliferation and differentiation of mesenchymal cells. Analysis of the genetic relationships in the limb buds suggested a more extensive role for Ihh and Runx genes in early chondrogenesis. The transfer of 5E1 decreased the expression of Runx2 and Runx3, whereas an exogenous recombinant IHH protein increased Runx2 and Runx3 expression. Moreover, a transcription factor Gli1 in hedgehog pathway enhances the direct induction of both Runx2 and Runx3 transcription. These findings suggested that Ihh signaling plays an important role in chondrocyte proliferation and differentiation via interactions with Runx2 and Runx3.

  9. Ihh and Runx2/Runx3 signaling interact to coordinate early chondrogenesis: a mouse model.

    Science.gov (United States)

    Kim, Eun-Jung; Cho, Sung-Won; Shin, Jeong-Oh; Lee, Min-Jung; Kim, Kye-Seong; Jung, Han-Sung

    2013-01-01

    Endochondral bone formation begins with the development of a cartilage intermediate that is subsequently replaced by calcified bone. The mechanisms occurring during early chondrogenesis that control both mesenchymal cell differentiation into chondrocytes and cell proliferation are not clearly understood in vertebrates. Indian hedgehog (Ihh), one of the hedgehog signaling molecules, is known to control both the hypertrophy of chondrocytes and bone replacement; these processes are particularly important in postnatal endochondral bone formation rather than in early chondrogenesis. In this study, we utilized the maternal transfer of 5E1 to E12.5 in mouse embryos, a process that leads to an attenuation of Ihh activity. As a result, mouse limb bud chondrogenesis was inhibited, and an exogenous recombinant IHH protein enhanced the proliferation and differentiation of mesenchymal cells. Analysis of the genetic relationships in the limb buds suggested a more extensive role for Ihh and Runx genes in early chondrogenesis. The transfer of 5E1 decreased the expression of Runx2 and Runx3, whereas an exogenous recombinant IHH protein increased Runx2 and Runx3 expression. Moreover, a transcription factor Gli1 in hedgehog pathway enhances the direct induction of both Runx2 and Runx3 transcription. These findings suggested that Ihh signaling plays an important role in chondrocyte proliferation and differentiation via interactions with Runx2 and Runx3.

  10. Rivaroxaban attenuates thrombosis by targeting the NF-κB signaling pathway in a rat model of deep venous thrombus.

    Science.gov (United States)

    Ma, Junhao; Li, Xinxi; Wang, Yang; Yang, Zhenwei; Luo, Jun

    2017-12-01

    Anticoagulant therapy is commonly used for the prevention and treatment of patients with deep venous thrombus. Evidence has shown that rivaroxaban is a potential oral anticoagulant drug for the acute treatment of venous thromboembolism. However, the rivaroxaban-mediated molecular mechanism involved in the progression of deep venous thrombosis has not been investigated. In the present study, we investigated the efficacy of rivaroxaban and the underlying signaling pathways in the prevention and treatment of rats with deep venous thrombosis. A rat model with deep vein thrombus formation was established and received treatment with rivaroxaban or PBS as control. The thrombin-activatable fibrinolysis inhibitor (TAFI) and plasminogen activator inhibitor-1 (PAI-1) were analyzed both in vitro and in vivo. The progression of thrombosis and stroke was evaluated after treatment with rivaroxaban or PBS. Nuclear factor-κB (NF-κB) signaling pathway in venous endothelial cells and in the rat model of deep venous thrombus was assessed. The therapeutic effects of rivaroxaban were evaluated as determined by changes in deep venous thrombosis in the rat model. Our results showed that rivaroxaban markedly inhibited TAFI and PAI-1 expression levels, neutrophils, tissue factor, neutrophil extracellular traps (NETs), myeloperoxidase and macrophages in venous endothelial cells and in the rat model of deep venous thrombus. Expression levels of ADP, PAIs, von Willebrand factor (vWF) and thromboxane were downregulated in vein endothelial cells and in serum from the experimental rats. Importantly, the incidences of inferior vena cava filter thrombus were protected by rivaroxaban during heparin-induced thrombolysis deep venous thrombosis in the rat model. We observed that activity of the NF-κB signaling pathway was inhibited by rivaroxaban in vein endothelial cells both in vitro and in vivo. Notably, immunohistology indicated that rivaroxaban attenuated deep venous thrombosis and the

  11. Lepton number violating signals of the top quark partners in the left-right twin Higgs model

    International Nuclear Information System (INIS)

    Goh, Hock-Seng; Krenke, Christopher A.

    2010-01-01

    We study the collider signatures of the left-right twin Higgs model in the case that the right-handed neutrino mass is less than the mass of the right-handed gauge boson. In this scenario, new leptonic decay chains open up, allowing the particles which cancel the one-loop quadratic divergences of the Higgs, the right-handed gauge bosons and top-partners, to be discovered. Half of these events contain same-sign leptons without missing energy, which have no genuine standard model background and for which the backgrounds are purely instrumental. These signals may be used to complement other collider searches and, in certain regions of parameter space, may be the only way to observe the particles responsible for natural electroweak symmetry breaking in the left-right twin Higgs model.

  12. Signal and image processing systems performance evaluation, simulation, and modeling; Proceedings of the Meeting, Orlando, FL, Apr. 4, 5, 1991

    Science.gov (United States)

    Nasr, Hatem N.; Bazakos, Michael E.

    The various aspects of the evaluation and modeling problems in algorithms, sensors, and systems are addressed. Consideration is given to a generic modular imaging IR signal processor, real-time architecture based on the image-processing module family, application of the Proto Ware simulation testbed to the design and evaluation of advanced avionics, development of a fire-and-forget imaging infrared seeker missile simulation, an adaptive morphological filter for image processing, laboratory development of a nonlinear optical tracking filter, a dynamic end-to-end model testbed for IR detection algorithms, wind tunnel model aircraft attitude and motion analysis, an information-theoretic approach to optimal quantization, parametric analysis of target/decoy performance, neural networks for automated target recognition parameters adaptation, performance evaluation of a texture-based segmentation algorithm, evaluation of image tracker algorithms, and multisensor fusion methodologies. (No individual items are abstracted in this volume)

  13. Dopamine-signalled reward predictions generated by competitive excitation and inhibition in a spiking neural network model

    Directory of Open Access Journals (Sweden)

    Paul eChorley

    2011-05-01

    Full Text Available Dopaminergic neurons in the mammalian substantia nigra displaycharacteristic phasic responses to stimuli which reliably predict thereceipt of primary rewards. These responses have been suggested toencode reward prediction-errors similar to those used in reinforcementlearning. Here, we propose a model of dopaminergic activity in whichprediction error signals are generated by the joint action ofshort-latency excitation and long-latency inhibition, in a networkundergoing dopaminergic neuromodulation of both spike-timing dependentsynaptic plasticity and neuronal excitability. In contrast toprevious models, sensitivity to recent events is maintained by theselective modification of specific striatal synapses, efferent tocortical neurons exhibiting stimulus-specific, temporally extendedactivity patterns. Our model shows, in the presence of significantbackground activity, (i a shift in dopaminergic response from rewardto reward predicting stimuli, (ii preservation of a response tounexpected rewards, and (iii a precisely-timed below-baseline dip inactivity observed when expected rewards are omitted.

  14. Current collapse modeling in AlGaN/GaN HEMT using small signal equivalent circuit for high power application

    Science.gov (United States)

    Nirmal, D.; Arivazhagan, L.; Fletcher, A. S. Augustine; Ajayan, J.; Prajoon, P.

    2018-01-01

    In this paper, the drain current collapse in AlGaN/GaN High Electron Mobility Transistor (HEMT) with field plate engineering is investigated. A small signal equivalent circuit of AlGaN/GaN HEMT is developed and a new drain current model is derived. This model is useful to correlate the impact of intrinsic capacitance and conductance on drain current collapse. The proposed device suppressed the current collapse phenomena by 10% compared with the conventional AlGaN/GaN HEMT. Moreover, the DC characteristics of the simulated device shows a drain current of 900 mA/mm, breakdown voltage of 291 V and transconductance of 175 mS/mm. Besides, the intrinsic capacitance and conductance parameters are extracted and its impact on drain current is analysed. Finally, the simulation results obtained were in compliance with the derived mathematical model of AlGaN/GaN HEMT.

  15. Impact of the choice of the precipitation reference data set on climate model selection and the resulting climate change signal

    Science.gov (United States)

    Gampe, D.; Ludwig, R.

    2017-12-01

    Regional Climate Models (RCMs) that downscale General Circulation Models (GCMs) are the primary tool to project future climate and serve as input to many impact models to assess the related changes and impacts under such climate conditions. Such RCMs are made available through the Coordinated Regional climate Downscaling Experiment (CORDEX). The ensemble of models provides a range of possible future climate changes around the ensemble mean climate change signal. The model outputs however are prone to biases compared to regional observations. A bias correction of these deviations is a crucial step in the impact modelling chain to allow the reproduction of historic conditions of i.e. river discharge. However, the detection and quantification of model biases are highly dependent on the selected regional reference data set. Additionally, in practice due to computational constraints it is usually not feasible to consider the entire ensembles of climate simulations with all members as input for impact models which provide information to support decision-making. Although more and more studies focus on model selection based on the preservation of the climate model spread, a selection based on validity, i.e. the representation of the historic conditions is still a widely applied approach. In this study, several available reference data sets for precipitation are selected to detect the model bias for the reference period 1989 - 2008 over the alpine catchment of the Adige River located in Northern Italy. The reference data sets originate from various sources, such as station data or reanalysis. These data sets are remapped to the common RCM grid at 0.11° resolution and several indicators, such as dry and wet spells, extreme precipitation and general climatology, are calculate to evaluate the capability of the RCMs to produce the historical conditions. The resulting RCM spread is compared against the spread of the reference data set to determine the related uncertainties and

  16. A signal processing application for evaluating self-monitoring blood glucose strategies in a software agent model.

    Science.gov (United States)

    Wang, Zhanle; Paranjape, Raman

    2015-07-01

    We propose the signal processing technique of calculating a cross-correlation function and an average deviation between the continuous blood glucose and the interpolation of limited blood glucose samples to evaluate blood glucose monitoring frequency in a self-aware patient software agent model. The diabetic patient software agent model [1] is a 24-h circadian, self-aware, stochastic model of a diabetic patient's blood glucose levels in a software agent environment. The purpose of this work is to apply a signal processing technique to assist patients and physicians in understanding the extent of a patient's illness using a limited number of blood glucose samples. A second purpose of this work is to determine an appropriate blood glucose monitoring frequency in order to have a minimum number of samples taken that still provide a good understanding of the patient's blood glucose levels. For society in general, the monitoring cost of diabetes is an extremely important issue, and these costs can vary tremendously depending on monitoring approaches and monitoring frequencies. Due to the cost and discomfort associated with blood glucose monitoring, today, patients expect monitoring frequencies specific to their health profile. The proposed method quantitatively assesses various monitoring protocols (from 6 times per day to 1 time per week) in nine predefined categories of patient agents in terms of risk factors of health status and age. Simulation results show that sampling 6 times per day is excessive, and not necessary for understanding the dynamics of the continuous signal in the experiments. In addition, patient agents in certain conditions only need to sample their blood glucose 1 time per week to have a good understanding of the characteristics of their blood glucose. Finally, an evaluation scenario is developed to visualize this concept, in which appropriate monitoring frequencies are shown based on the particular conditions of patient agents. This base line can

  17. Integrating a Linear Signal Model with Groundwater and Rainfall time-series on the Characteristic Identification of Groundwater Systems

    Science.gov (United States)

    Chen, Yu-Wen; Wang, Yetmen; Chang, Liang-Cheng

    2017-04-01

    Groundwater resources play a vital role on regional supply. To avoid irreversible environmental impact such as land subsidence, the characteristic identification of groundwater system is crucial before sustainable management of groundwater resource. This study proposes a signal process approach to identify the character of groundwater systems based on long-time hydrologic observations include groundwater level and rainfall. The study process contains two steps. First, a linear signal model (LSM) is constructed and calibrated to simulate the variation of underground hydrology based on the time series of groundwater levels and rainfall. The mass balance equation of the proposed LSM contains three major terms contain net rate of horizontal exchange, rate of rainfall recharge and rate of pumpage and four parameters are required to calibrate. Because reliable records of pumpage is rare, the time-variant groundwater amplitudes of daily frequency (P ) calculated by STFT are assumed as linear indicators of puamage instead of pumpage records. Time series obtained from 39 observation wells and 50 rainfall stations in and around the study area, Pintung Plain, are paired for model construction. Second, the well-calibrated parameters of the linear signal model can be used to interpret the characteristic of groundwater system. For example, the rainfall recharge coefficient (γ) means the transform ratio between rainfall intention and groundwater level raise. The area around the observation well with higher γ means that the saturated zone here is easily affected by rainfall events and the material of unsaturated zone might be gravel or coarse sand with high infiltration ratio. Considering the spatial distribution of γ, the values of γ decrease from the upstream to the downstream of major rivers and also are correlated to the spatial distribution of grain size of surface soil. Via the time-series of groundwater levels and rainfall, the well-calibrated parameters of LSM have

  18. Wavelet-based study of valence-arousal model of emotions on EEG signals with LabVIEW.

    Science.gov (United States)

    Guzel Aydin, Seda; Kaya, Turgay; Guler, Hasan

    2016-06-01

    This paper illustrates the wavelet-based feature extraction for emotion assessment using electroencephalogram (EEG) signal through graphical coding design. Two-dimensional (valence-arousal) emotion model was studied. Different emotions (happy, joy, melancholy, and disgust) were studied for assessment. These emotions were stimulated by video clips. EEG signals obtained from four subjects were decomposed into five frequency bands (gamma, beta, alpha, theta, and delta) using "db5" wavelet function. Relative features were calculated to obtain further information. Impact of the emotions according to valence value was observed to be optimal on power spectral density of gamma band. The main objective of this work is not only to investigate the influence of the emotions on different frequency bands but also to overcome the difficulties in the text-based program. This work offers an alternative approach for emotion evaluation through EEG processing. There are a number of methods for emotion recognition such as wavelet transform-based, Fourier transform-based, and Hilbert-Huang transform-based methods. However, the majority of these methods have been applied with the text-based programming languages. In this study, we proposed and implemented an experimental feature extraction with graphics-based language, which provides great convenience in bioelectrical signal processing.

  19. The Wnt signalling pathway is upregulated in an in vitro model of acquired tamoxifen resistant breast cancer

    International Nuclear Information System (INIS)

    Loh, Yan Ni; Hedditch, Ellen L; Baker, Laura A; Jary, Eve; Ward, Robyn L; Ford, Caroline E

    2013-01-01

    Acquired resistance to Tamoxifen remains a critical problem in breast cancer patient treatment, yet the underlying causes of resistance have not been fully elucidated. Abberations in the Wnt signalling pathway have been linked to many human cancers, including breast cancer, and appear to be associated with more metastatic and aggressive types of cancer. Here, our aim was to investigate if this key pathway was involved in acquired Tamoxifen resistance, and could be targeted therapeutically. An in vitro model of acquired Tamoxifen resistance (named TamR) was generated by growing the estrogen receptor alpha (ER) positive MCF7 breast cancer cell line in increasing concentrations of Tamoxifen (up to 5 uM). Alterations in the Wnt signalling pathway and epithelial to mesenchymal transition (EMT) in response to Tamoxifen and treatment with the Wnt inhibitor, IWP-2 were measured via quantitative RT-PCR (qPCR) and TOP/FOP Wnt reporter assays. Resistance to Tamoxifen, and effects of IWP-2 treatment were determined by MTT proliferation assays. TamR cells exhibited increased Wnt signalling as measured via the TOP/FOP Wnt luciferase reporter assays. Genes associated with both the β-catenin dependent (AXIN2, MYC, CSNK1A1) and independent arms (ROR2, JUN), as well as general Wnt secretion (PORCN) of the Wnt signalling pathway were upregulated in the TamR cells compared to the parental MCF7 cell line. Treatment of the TamR cell line with human recombinant Wnt3a (rWnt3a) further increased the resistance of both MCF7 and TamR cells to the anti-proliferative effects of Tamoxifen treatment. TamR cells demonstrated increased expression of EMT markers (VIM, TWIST1, SNAI2) and decreased CDH1, which may contribute to their resistance to Tamoxifen. Treatment with the Wnt inhibitor, IWP-2 inhibited cell proliferation and markers of EMT. These data support the role of the Wnt signalling pathway in acquired resistance to Tamoxifen. Further research into the mechanism by which activated Wnt

  20. Application of a model-based fault detection system to nuclear plant signals

    International Nuclear Information System (INIS)

    Gross, K.C.; Singer, R.M.; Wegerich, S.W.; Herzog, J.P.; VanAlstine, R.; Bockhorst, F.

    1997-01-01

    To assure the continued safe and reliable operation of a nuclear power station, it is essential that accurate online information on the current state of the entire system be available to the operators. Such information is needed to determine the operability of safety and control systems, the condition of active components, the necessity of preventative maintenance, and the status of sensory systems. To this end, ANL has developed a new Multivariate State Estimation Technique (MSET) which utilizes advanced pattern recognition methods to enhance sensor and component operational validation for commercial nuclear reactors. Operational data from the Crystal River-3 (CR-3) nuclear power plant are used to illustrate the high sensitivity, accuracy, and the rapid response time of MSET for annunciation of a variety of signal disturbances

  1. Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

    Science.gov (United States)

    Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

    2012-08-29

    Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real numbers, mainly based on differential equations and chemical kinetics formalism; (2) and qualitative modeling, representing chemical species concentrations or activities by a finite set of discrete values. Both approaches answer particular (and often different) biological questions. Qualitative modeling approach permits a simple and less detailed description of the biological systems, efficiently describes stable state identification but remains inconvenient in describing the transient kinetics leading to these states. In this context, time is represented by discrete steps. Quantitative modeling, on the other hand, can describe more accurately the dynamical behavior of biological processes as it follows the evolution of concentration or activities of chemical species as a function of time, but requires an important amount of information on the parameters difficult to find in the literature. Here, we propose a modeling framework based on a qualitative approach that is intrinsically continuous in time. The algorithm presented in this article fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to describe the temporal evolution of the biological process we wish to model, we explicitly specify the transition rates for each node. For that purpose, we built a language that can be seen as a generalization of Boolean equations. Mathematically, this approach can be translated in a set of ordinary differential

  2. PI3K-Akt signaling activates mTOR-mediated epileptogenesis in organotypic hippocampal culture model of posttraumatic epilepsy

    OpenAIRE

    Berdichevsky, Yevgeny; Dryer, Alexandra M.; Saponjian, Yero; Mahoney, Mark M.; Pimentel, Corrin A.; Lucini, Corrina A.; Usenovic, Marija; Staley, Kevin J.

    2013-01-01

    mTOR is activated in epilepsy, but the mechanisms of mTOR activation in post-traumatic epileptogenesis are unknown. It is also not clear whether mTOR inhibition has an antiepileptogenic, or merely anti-convulsive effect. The rat hippocampal organotypic culture model of post-traumatic epilepsy was used to study the effects of long term (four weeks) inhibition of signaling pathways that interact with mTOR. Ictal activity was quantified by measurement of lactate production and electrical recordi...

  3. Reduced fractal model for quantitative analysis of averaged micromotions in mesoscale: Characterization of blow-like signals

    International Nuclear Information System (INIS)

    Nigmatullin, Raoul R.; Toboev, Vyacheslav A.; Lino, Paolo; Maione, Guido

    2015-01-01

    Highlights: •A new approach describes fractal-branched systems with long-range fluctuations. •A reduced fractal model is proposed. •The approach is used to characterize blow-like signals. •The approach is tested on data from different fields. -- Abstract: It has been shown that many micromotions in the mesoscale region are averaged in accordance with their self-similar (geometrical/dynamical) structure. This distinctive feature helps to reduce a wide set of different micromotions describing relaxation/exchange processes to an averaged collective motion, expressed mathematically in a rather general form. This reduction opens new perspectives in description of different blow-like signals (BLS) in many complex systems. The main characteristic of these signals is a finite duration also when the generalized reduced function is used for their quantitative fitting. As an example, we describe quantitatively available signals that are generated by bronchial asthmatic people, songs by queen bees, and car engine valves operating in the idling regime. We develop a special treatment procedure based on the eigen-coordinates (ECs) method that allows to justify the generalized reduced fractal model (RFM) for description of BLS that can propagate in different complex systems. The obtained describing function is based on the self-similar properties of the different considered micromotions. This kind of cooperative model is proposed here for the first time. In spite of the fact that the nature of the dynamic processes that take place in fractal structure on a mesoscale level is not well understood, the parameters of the RFM fitting function can be used for construction of calibration curves, affected by various external/random factors. Then, the calculated set of the fitting parameters of these calibration curves can characterize BLS of different complex systems affected by those factors. Though the method to construct and analyze the calibration curves goes beyond the scope

  4. Comment on "A dynamic network model of mTOR signaling reveals TSC-independent mTORC2 regulation": building a model of the mTOR signaling network with a potentially faulty tool.

    Science.gov (United States)

    Manning, Brendan D

    2012-07-10

    In their study published in Science Signaling (Research Article, 27 March 2012, DOI: 10.1126/scisignal.2002469), Dalle Pezze et al. tackle the dynamic and complex wiring of the signaling network involving the protein kinase mTOR, which exists within two distinct protein complexes (mTORC1 and mTORC2) that differ in their regulation and function. The authors use a combination of immunoblotting for specific phosphorylation events and computational modeling. The primary experimental tool employed is to monitor the autophosphorylation of mTOR on Ser(2481) in cell lysates as a surrogate for mTOR activity, which the authors conclude is a specific readout for mTORC2. However, Ser(2481) phosphorylation occurs on both mTORC1 and mTORC2 and will dynamically change as the network through which these two complexes are connected is manipulated. Therefore, models of mTOR network regulation built using this tool are inherently imperfect and open to alternative explanations. Specific issues with the main conclusion made in this study, involving the TSC1-TSC2 (tuberous sclerosis complex 1 and 2) complex and its potential regulation of mTORC2, are discussed here. A broader goal of this Letter is to clarify to other investigators the caveats of using mTOR Ser(2481) phosphorylation in cell lysates as a specific readout for either of the two mTOR complexes.

  5. SUSY signals at DESY HERA in the no-scale flipped SU(5) supergravity model

    Energy Technology Data Exchange (ETDEWEB)

    Lopez, J.L.; Nanopoulos, D.V.; Wang, X.; Zichichi, A. (Center for Theoretical Physics, Department of Physics, Texas A M University, College Station, Texas 77843-4242 (United States) Astroparticle Physics Group, Houston Advanced Research Center (HARC), The Woodlands, Texas 77381 (United States) CERN, Geneva (Switzerland))

    1993-11-01

    Sparticle production and detection at DESY HERA are studied within the recently proposed no-scale flipped SU(5) supergravity model. Among the various reaction channels that could lead to sparticle production at HERA, only the following are within its limit of sensitivity in this model: [ital e][sup [minus

  6. Optic nerve signals in a neuromorphic chip I: Outer and inner retina models.

    Science.gov (United States)

    Zaghloul, Kareem A; Boahen, Kwabena

    2004-04-01

    We present a novel model for the mammalian retina and analyze its behavior. Our outer retina model performs bandpass spatiotemporal filtering. It is comprised of two reciprocally connected resistive grids that model the cone and horizontal cell syncytia. We show analytically that its sensitivity is proportional to the space-constant-ratio of the two grids while its half-max response is set by the local average intensity. Thus, this outer retina model realizes luminance adaptation. Our inner retina model performs high-pass temporal filtering. It features slow negative feedback whose strength is modulated by a locally computed measure of temporal contrast, modeling two kinds of amacrine cells, one narrow-field, the other wide-field. We show analytically that, when the input is spectrally pure, the corner-frequency tracks the input frequency. But when the input is broadband, the corner frequency is proportional to contrast. Thus, this inner retina model realizes temporal frequency adaptation as well as contrast gain control. We present CMOS circuit designs for our retina model in this paper as well. Experimental measurements from the fabricated chip, and validation of our analytical results, are presented in the companion paper [Zaghloul and Boahen (2004)].

  7. ANALYTICAL MODEL OF A DIFFERENTIAL METHOD FOR RECEIVING AND PROCESSING SIGNALS OF THE INFRARED RANGE OF WAVELENGTHS

    Directory of Open Access Journals (Sweden)

    N. S. Akinshin

    2017-01-01

    Full Text Available One of the classic methods to improve the noise immunity of passive detection of infrared wavelength range (IKSO is a differential inclusion of pyrocatechol, placed at some distance. An analytical model of a differential method of receiving infrared radiation from moving objects is introduced. A comparison with experimental results for moving objects of different types is made. Differential inclusion of sensors can be used not only to compensate the external interference, but also to determine the boundaries of a temporary "slot", inside which the movable object is most likely to be detected. The temporal boundaries are used for the decision making about the type and parameters of the movable object in complexional device of object classification.The principle of operation of ikso, which is to record signals with diversity of pyrocatechol into the appropriate memory registers and output detection of the differential signal envelope. Subsequently, from the memory registers portions of a recording signal posted pyrocatechol are selected which are later processed to determine the temporal provisions of minimum minimore and maximum maximore. The direction of movement of the object abeam is determined by the delay or advance of the extrema of the signals of one sensor relative to another within a given temporal "slot".It is shown that aggregation should be the following – the tool with a maximum radius of the zone of sensitivity should be active and the basic, but if there is a more reliable piece of information about the detected object which can implement a more refined classification of the object (for example, a group of people, wheeled vehicles-tracked vehicles, etc.. The conclusion is made about the advantages of differential option to include spaced sensors.The results can be used in the development of infrared wavelengths passive detection in the conceptual design phase.

  8. Experimental Verification of a New Model Describing the Influence of Incomplete Signal Extinction Ratio on the Sensitivity Degradation due to Multiple Interferometric Crosstalk

    DEFF Research Database (Denmark)

    Liu, Fenghai; Rasmussen, Christian Jørgen; Pedersen, Rune Johan Skullerud

    1999-01-01

    Larger optical penalties than predicted by a Gaussian crosstalk model are found both in our experiments and in the literature when investigating signals including multiple interferometric crosstalk contributions. We attribute this to an imperfect signal extinction ratio. In this letter, simple...... analytical relations for crosstalk induced power penalties are derived taking the signal extinction ratio into account and excellent agreement with 10-Gb/s experiments is obtained. Both theory and experiment show the importance of the signal extinction ratio in connection with interferometric crosstalk....

  9. RESULTS OF THE SHORT COMPARATIVE ANALYSIS OF MATHEMATICAL MODELS OF INFLUENCE OF THE IONOSPHERE OF THE EARTH ON ULTRA BROADBAND SIGNALS X-RANGE

    Directory of Open Access Journals (Sweden)

    M. M. Kasperovich

    2015-01-01

    Full Text Available For range portrait formation at usage ultrabroadband linearly frequency-modulated signal in radar it is necessary to consider all distortions of an electromagnetic wave on a radio route. At observation over circumterraneousobjects the signal transits through an ionosphere. The electromagnetic wave in it will be exposed to non-linearity distortions, which transform of signal time structure. It leads to distance error origin. For its compensating it is necessary to use the mathematical model of signal distortions in an ionosphere.

  10. The Catchment Feature Model: A Device for Multimodal Fusion and a Bridge between Signal and Sense

    Science.gov (United States)

    Quek, Francis

    2004-12-01

    The catchment feature model addresses two questions in the field of multimodal interaction: how we bridge video and audio processing with the realities of human multimodal communication, and how information from the different modes may be fused. We argue from a detailed literature review that gestural research has clustered around manipulative and semaphoric use of the hands, motivate the catchment feature model psycholinguistic research, and present the model. In contrast to "whole gesture" recognition, the catchment feature model applies a feature decomposition approach that facilitates cross-modal fusion at the level of discourse planning and conceptualization. We present our experimental framework for catchment feature-based research, cite three concrete examples of catchment features, and propose new directions of multimodal research based on the model.

  11. The Catchment Feature Model: A Device for Multimodal Fusion and a Bridge between Signal and Sense

    Directory of Open Access Journals (Sweden)

    Francis Quek

    2004-09-01

    Full Text Available The catchment feature model addresses two questions in the field of multimodal interaction: how we bridge video and audio processing with the realities of human multimodal communication, and how information from the different modes may be fused. We argue from a detailed literature review that gestural research has clustered around manipulative and semaphoric use of the hands, motivate the catchment feature model psycholinguistic research, and present the model. In contrast to “whole gesture” recognition, the catchment feature model applies a feature decomposition approach that facilitates cross-modal fusion at the level of discourse planning and conceptualization. We present our experimental framework for catchment feature-based research, cite three concrete examples of catchment features, and propose new directions of multimodal research based on the model.

  12. Finding viable models in SUSY parameter spaces with signal specific discovery potential

    Science.gov (United States)

    Burgess, Thomas; Lindroos, Jan Øye; Lipniacka, Anna; Sandaker, Heidi

    2013-08-01

    Recent results from ATLAS giving a Higgs mass of 125.5 GeV, further constrain already highly constrained supersymmetric models such as pMSSM or CMSSM/mSUGRA. As a consequence, finding potentially discoverable and non-excluded regions of model parameter space is becoming increasingly difficult. Several groups have invested large effort in studying the consequences of Higgs mass bounds, upper limits on rare B-meson decays, and limits on relic dark matter density on constrained models, aiming at predicting superpartner masses, and establishing likelihood of SUSY models compared to that of the Standard Model vis-á-vis experimental data. In this paper a framework for efficient search for discoverable, non-excluded regions of different SUSY spaces giving specific experimental signature of interest is presented. The method employs an improved Markov Chain Monte Carlo (MCMC) scheme exploiting an iteratively updated likelihood function to guide search for viable models. Existing experimental and theoretical bounds as well as the LHC discovery potential are taken into account. This includes recent bounds on relic dark matter density, the Higgs sector and rare B-mesons decays. A clustering algorithm is applied to classify selected models according to expected phenomenology enabling automated choice of experimental benchmarks and regions to be used for optimizing searches. The aim is to provide experimentalist with a viable tool helping to target experimental signatures to search for, once a class of models of interest is established. As an example a search for viable CMSSM models with τ-lepton signatures observable with the 2012 LHC data set is presented. In the search 105209 unique models were probed. From these, ten reference benchmark points covering different ranges of phenomenological observables at the LHC were selected.

  13. High Resolution Modeling of the Water Cycle to Refine GRACE Signal Analysis in the Gulf of Alaska Drainage

    Science.gov (United States)

    Beamer, J.; Hill, D. F.; Arendt, A. A.; Luthcke, S. B.; Liston, G. E.

    2015-12-01

    A comprehensive study of the Gulf of Alaska (GOA) drainage basin was carried out to improve understanding of the coastal freshwater discharge (FWD) and surface mass balance (SMB) of glaciers. Coastal FWD and SMB for all glacier surfaces were modeled using a suite of physically based, spatially distributed weather, energy-balance snow/ice melt, soil water balance, and runoff routing models at a high resolution (1 km horizontal grid; daily time step). A 35 year hind cast was performed, providing complete records of precipitation, runoff, sno