Possibility of deriving the Hermean surface composition through low energy neutral atom detection

NASA Astrophysics Data System (ADS)

Milillo, A.; Orsini, S.; Massetti, S.; Mura, A.; de Angelis, E.; Lammer, H.; Wurz, P.; di Lellis, A. M.

2003-04-01

The release processes induced by ion sputtering and/or micrometeoroids impacts induces erosion of the Mercury surface. The sputtered neutrals exhibit spectra peaked at low energies (few eV). Nevertheless, a high-energy neutral signal also emerges, due to these release processes. In principle, the directional neutral signal can be detected, providing information on the local surface composition. In this study, we simulate the neutral signal due to ion sputtering below the cusp regions, assuming a highly anisotropic surface composition. The NPA SERENA / ELENA instrument proposed on board the ESA mission BepiColombo is a nadir-pointing 1-D sensor, able to detect neutral atoms, form tens of eV to about 5 keV with a capability of resolving the major species. The ELENA field-of-view (FOV) is ~ 60 degrees, with the FOV plane perpendicular to the MPO orbital plane. Here, we speculate on the possibility of discriminating composition anisotropies by detecting the high-energy portion of the sputtered signal.

Certification of windshear performance with RTCA class D radomes

NASA Technical Reports Server (NTRS)

Mathews, Bruce D.; Miller, Fran; Rittenhouse, Kirk; Barnett, Lee; Rowe, William

1994-01-01

Superposition testing of detection range performance forms a digital signal for input into a simulation of signal and data processing equipment and algorithms to be employed in a sensor system for advanced warning of hazardous windshear. For suitable pulse-Doppler radar, recording of the digital data at the input to the digital signal processor furnishes a realistic operational scenario and environmentally responsive clutter signal including all sidelobe clutter, ground moving target indications (GMTI), and large signal spurious due to mainbeam clutter and/or RFI respective of the urban airport clutter and aircraft scenarios (approach and landing antenna pointing). For linear radar system processes, a signal at the same point in the process from a hazard phenomena may be calculated from models of the scattering phenomena, for example, as represented in fine 3 dimensional reflectivity and velocity grid structures. Superposition testing furnishes a competing signal environment for detection and warning time performance confirmation of phenomena uncontrollable in a natural environment.

Applications of digital processing for noise removal from plasma diagnostics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kane, R.J.; Candy, J.V.; Casper, T.A.

1985-11-11

The use of digital signal techniques for removal of noise components present in plasma diagnostic signals is discussed, particularly with reference to diamagnetic loop signals. These signals contain noise due to power supply ripple in addition to plasma characteristics. The application of noise canceling techniques, such as adaptive noise canceling and model-based estimation, will be discussed. The use of computer codes such as SIG is described. 19 refs., 5 figs.

Asymmetric Dual-Band Tracking Technique for Optimal Joint Processing of BDS B1I and B1C Signals

PubMed Central

Wang, Chuhan; Cui, Xiaowei; Ma, Tianyi; Lu, Mingquan

2017-01-01

Along with the rapid development of the Global Navigation Satellite System (GNSS), satellite navigation signals have become more diversified, complex, and agile in adapting to increasing market demands. Various techniques have been developed for processing multiple navigation signals to achieve better performance in terms of accuracy, sensitivity, and robustness. This paper focuses on a technique for processing two signals with separate but adjacent center frequencies, such as B1I and B1C signals in the BeiDou global system. The two signals may differ in modulation scheme, power, and initial phase relation and can be processed independently by user receivers; however, the propagation delays of the two signals from a satellite are nearly identical as they are modulated on adjacent frequencies, share the same reference clock, and undergo nearly identical propagation paths to the receiver, resulting in strong coherence between the two signals. Joint processing of these signals can achieve optimal measurement performance due to the increased Gabor bandwidth and power. In this paper, we propose a universal scheme of asymmetric dual-band tracking (ASYM-DBT) to take advantage of the strong coherence, the increased Gabor bandwidth, and power of the two signals in achieving much-reduced thermal noise and more accurate ranging results when compared with the traditional single-band algorithm. PMID:29035350

Asymmetric Dual-Band Tracking Technique for Optimal Joint Processing of BDS B1I and B1C Signals.

PubMed

Wang, Chuhan; Cui, Xiaowei; Ma, Tianyi; Zhao, Sihao; Lu, Mingquan

2017-10-16

Along with the rapid development of the Global Navigation Satellite System (GNSS), satellite navigation signals have become more diversified, complex, and agile in adapting to increasing market demands. Various techniques have been developed for processing multiple navigation signals to achieve better performance in terms of accuracy, sensitivity, and robustness. This paper focuses on a technique for processing two signals with separate but adjacent center frequencies, such as B1I and B1C signals in the BeiDou global system. The two signals may differ in modulation scheme, power, and initial phase relation and can be processed independently by user receivers; however, the propagation delays of the two signals from a satellite are nearly identical as they are modulated on adjacent frequencies, share the same reference clock, and undergo nearly identical propagation paths to the receiver, resulting in strong coherence between the two signals. Joint processing of these signals can achieve optimal measurement performance due to the increased Gabor bandwidth and power. In this paper, we propose a universal scheme of asymmetric dual-band tracking (ASYM-DBT) to take advantage of the strong coherence, the increased Gabor bandwidth, and power of the two signals in achieving much-reduced thermal noise and more accurate ranging results when compared with the traditional single-band algorithm.

Directional dual-tree complex wavelet packet transforms for processing quadrature signals.

PubMed

Serbes, Gorkem; Gulcur, Halil Ozcan; Aydin, Nizamettin

2016-03-01

Quadrature signals containing in-phase and quadrature-phase components are used in many signal processing applications in every field of science and engineering. Specifically, Doppler ultrasound systems used to evaluate cardiovascular disorders noninvasively also result in quadrature format signals. In order to obtain directional blood flow information, the quadrature outputs have to be preprocessed using methods such as asymmetrical and symmetrical phasing filter techniques. These resultant directional signals can be employed in order to detect asymptomatic embolic signals caused by small emboli, which are indicators of a possible future stroke, in the cerebral circulation. Various transform-based methods such as Fourier and wavelet were frequently used in processing embolic signals. However, most of the times, the Fourier and discrete wavelet transforms are not appropriate for the analysis of embolic signals due to their non-stationary time-frequency behavior. Alternatively, discrete wavelet packet transform can perform an adaptive decomposition of the time-frequency axis. In this study, directional discrete wavelet packet transforms, which have the ability to map directional information while processing quadrature signals and have less computational complexity than the existing wavelet packet-based methods, are introduced. The performances of proposed methods are examined in detail by using single-frequency, synthetic narrow-band, and embolic quadrature signals.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Apparatus and method for temperature correction and expanded count rate of inorganic scintillation detectors

DOEpatents

Ianakiev, Kiril D [Los Alamos, NM; Hsue, Sin Tao [Santa Fe, NM; Browne, Michael C [Los Alamos, NM; Audia, Jeffrey M [Abiquiu, NM

2006-07-25

The present invention includes an apparatus and corresponding method for temperature correction and count rate expansion of inorganic scintillation detectors. A temperature sensor is attached to an inorganic scintillation detector. The inorganic scintillation detector, due to interaction with incident radiation, creates light pulse signals. A photoreceiver processes the light pulse signals to current signals. Temperature correction circuitry that uses a fast light component signal, a slow light component signal, and the temperature signal from the temperature sensor to corrected an inorganic scintillation detector signal output and expanded the count rate.

Suppression of Quasiparticle Scattering Signals in Bilayer Graphene Due to Layer Polarization and Destructive Interference

NASA Astrophysics Data System (ADS)

Jolie, Wouter; Lux, Jonathan; Pörtner, Mathias; Dombrowski, Daniela; Herbig, Charlotte; Knispel, Timo; Simon, Sabina; Michely, Thomas; Rosch, Achim; Busse, Carsten

2018-03-01

We study chemically gated bilayer graphene using scanning tunneling microscopy and spectroscopy complemented by tight-binding calculations. Gating is achieved by intercalating Cs between bilayer graphene and Ir(111), thereby shifting the conduction band minima below the chemical potential. Scattering between electronic states (both intraband and interband) is detected via quasiparticle interference. However, not all expected processes are visible in our experiment. We uncover two general effects causing this suppression: first, intercalation leads to an asymmetrical distribution of the states within the two layers, which significantly reduces the scanning tunneling spectroscopy signal of standing waves mainly present in the lower layer; second, forward scattering processes, connecting points on the constant energy contours with parallel velocities, do not produce pronounced standing waves due to destructive interference. We present a theory to describe the interference signal for a general n -band material.

Suppression of Quasiparticle Scattering Signals in Bilayer Graphene Due to Layer Polarization and Destructive Interference.

PubMed

Jolie, Wouter; Lux, Jonathan; Pörtner, Mathias; Dombrowski, Daniela; Herbig, Charlotte; Knispel, Timo; Simon, Sabina; Michely, Thomas; Rosch, Achim; Busse, Carsten

2018-03-09

We study chemically gated bilayer graphene using scanning tunneling microscopy and spectroscopy complemented by tight-binding calculations. Gating is achieved by intercalating Cs between bilayer graphene and Ir(111), thereby shifting the conduction band minima below the chemical potential. Scattering between electronic states (both intraband and interband) is detected via quasiparticle interference. However, not all expected processes are visible in our experiment. We uncover two general effects causing this suppression: first, intercalation leads to an asymmetrical distribution of the states within the two layers, which significantly reduces the scanning tunneling spectroscopy signal of standing waves mainly present in the lower layer; second, forward scattering processes, connecting points on the constant energy contours with parallel velocities, do not produce pronounced standing waves due to destructive interference. We present a theory to describe the interference signal for a general n-band material.

Estimating the delay-Doppler of target echo in a high clutter underwater environment using wideband linear chirp signals: Evaluation of performance with experimental data.

PubMed

Yu, Ge; Yang, T C; Piao, Shengchun

2017-10-01

A chirp signal is a signal with linearly varying instantaneous frequency over the signal bandwidth, also known as a linear frequency modulated (LFM) signal. It is widely used in communication, radar, active sonar, and other applications due to its Doppler tolerance property in signal detection using the matched filter (MF) processing. Modern sonar uses high-gain, wideband signals to improve the signal to reverberation ratio. High gain implies a high product of the signal bandwidth and duration. However, wideband and/or long duration LFM signals are no longer Doppler tolerant. The shortcoming of the standard MF processing is loss of performance, and bias in range estimation. This paper uses the wideband ambiguity function and the fractional Fourier transform method to estimate the target velocity and restore the performance. Target velocity or Doppler provides a clue for differentiating the target from the background reverberation and clutter. The methods are applied to simulated and experimental data.

Robust estimators for speech enhancement in real environments

NASA Astrophysics Data System (ADS)

Sandoval-Ibarra, Yuma; Diaz-Ramirez, Victor H.; Kober, Vitaly

2015-09-01

Common statistical estimators for speech enhancement rely on several assumptions about stationarity of speech signals and noise. These assumptions may not always valid in real-life due to nonstationary characteristics of speech and noise processes. We propose new estimators based on existing estimators by incorporation of computation of rank-order statistics. The proposed estimators are better adapted to non-stationary characteristics of speech signals and noise processes. Through computer simulations we show that the proposed estimators yield a better performance in terms of objective metrics than that of known estimators when speech signals are contaminated with airport, babble, restaurant, and train-station noise.

Implantable electronics: emerging design issues and an ultra light-weight security solution.

PubMed

Narasimhan, Seetharam; Wang, Xinmu; Bhunia, Swarup

2010-01-01

Implantable systems that monitor biological signals require increasingly complex digital signal processing (DSP) electronics for real-time in-situ analysis and compression of the recorded signals. While it is well-known that such signal processing hardware needs to be implemented under tight area and power constraints, new design requirements emerge with their increasing complexity. Use of nanoscale technology shows tremendous benefits in implementing these advanced circuits due to dramatic improvement in integration density and power dissipation per operation. However, it also brings in new challenges such as reliability and large idle power (due to higher leakage current). Besides, programmability of the device as well as security of the recorded information are rapidly becoming major design considerations of such systems. In this paper, we analyze the emerging issues associated with the design of the DSP unit in an implantable system. Next, we propose a novel ultra light-weight solution to address the information security issue. Unlike the conventional information security approaches like data encryption, which come at large area and power overhead and hence are not amenable for resource-constrained implantable systems, we propose a multilevel key-based scrambling algorithm, which exploits the nature of the biological signal to effectively obfuscate it. Analysis of the proposed algorithm in the context of neural signal processing and its hardware implementation shows that we can achieve high level of security with ∼ 13X lower power and ∼ 5X lower area overhead than conventional cryptographic solutions.

A graph signal filtering-based approach for detection of different edge types on airborne lidar data

NASA Astrophysics Data System (ADS)

Bayram, Eda; Vural, Elif; Alatan, Aydin

2017-10-01

Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems has been addressed by many studies in geo-spatial analysis and urban monitoring applications. However, the processing of LiDAR point clouds is challenging due to their irregular structure and 3D geometry. In this study, we propose a novel framework for the detection of the boundaries of an object or scene captured by LiDAR. Our approach is motivated by edge detection techniques in vision research and it is established on graph signal filtering which is an exciting and promising field of signal processing for irregular data types. Due to the convenient applicability of graph signal processing tools on unstructured point clouds, we achieve the detection of the edge points directly on 3D data by using a graph representation that is constructed exclusively to answer the requirements of the application. Moreover, considering the elevation data as the (graph) signal, we leverage aerial characteristic of the airborne LiDAR data. The proposed method can be employed both for discovering the jump edges on a segmentation problem and for exploring the crease edges on a LiDAR object on a reconstruction/modeling problem, by only adjusting the filter characteristics.

Luminescence and conductivity studies on CVD diamond exposed to UV light

NASA Astrophysics Data System (ADS)

Bizzarri, A.; Bogani, F.; Bruzzi, M.; Sciortino, S.

1999-04-01

The photoluminescence (PL), thermoluminescence (TL) and thermally stimulated currents (TSC) of four high-quality CVD diamond films have been investigated in the range of temperatures between 300 and 700 K. The sample excitation has been carried out by means of an UV xenon lamp and UV laser lines. The features of the signals have been found equal to those obtained from particle excitation. The TL analysis shows the existence of several deep traps with activation energies between 0.6 and 1.0 eV. The contribution to the TL signal from different traps has been singled out by means of successive annealing processes. The TL results are in good agreement with those obtained from TSC measurements. The combined use of the two techniques allows a precise determination of the trap parameters. The spectral content of the TL response has also been compared with the PL signal in order to investigate the recombination process. This analysis shows that, in this temperature range, the TL signal is likely due to recombination from bound states rather than due to radiative free to bound transitions, as generally assumed in TL theory. The TSC signal is likely to arise from impurity band rather than from free carriers conduction.

Ultrasonic Signal Processing for Structural Health Monitoring

NASA Astrophysics Data System (ADS)

Michaels, Jennifer E.; Michaels, Thomas E.

2004-02-01

Permanently mounted ultrasonic sensors are a key component of systems under development for structural health monitoring. Signal processing plays a critical role in the viability of such systems due to the difficulty in interpreting signals received from structures of complex geometry. This paper describes a differential feature-based approach to classifying signal changes as either "environmental" or "structural". Data are presented from piezoelectric discs bonded to an aluminum specimen subjected to both environmental changes and introduction of artificial defects. The classifier developed as part of this study was able to correctly identify artificial defects that were not part of the initial training and evaluation data sets. Central to the success of the classifier was the use of the Short Time Cross Correlation to measure coherency between the signal and reference as a function of time.

High stability integrated Tri-axial fluxgate sensor with suspended technology

NASA Astrophysics Data System (ADS)

Wang, Chen; Teng, Yuntian; Wang, Xiaomei; Fan, Xiaoyong; Wu, Qiong

2017-04-01

The relative geomagnetic record of China Geomagnetic Network of China(GNC) has been digitized, network, meanwhile achieving second data acquisition and storage during after 9th five-year and 10th five-year plan upgraded. Currently the relative record in geomagnetic observatories are generally two sets of the same type instrument with parallel observation, which could distinguish the differential between observation instrument failures and environmental interference, and ensure the continuity and integrity of the observation data. Fluxgate magnetometer has become mainstream equipment for relative geomagnetic record because of its low noise, high sensitivity, and fast response. There is a problem about data inconsistency by the same type of instrument in the same station though few years observation data analysis. The researchers have done a lot of experiments and found three main error sources:1. The instrument performances, due to the limitation of manufacturing and assembly process level it is difficult to ensure the orthogonality of the instrument; other performances of scale, zero offset and temperature coefficient; 2. horizontal error, which introduced by the initial installation process due to horizontal adjustment and pillar tilling due to long-term observations; 3.The observation environment, the temperature and humidity, power supply system. The new fluxgate magnetometer uses special nonmagnetic gimbaled (made by beryllium / bronze material) construction for suspension, so the fluxgate sensor is fixed at the suspended platform in order to automatically keep the horizontal level. The advantage of this design is to eliminate horizontal error introduced by the initial installation process due to horizontal adjustment and pillar tilling due to long-term observations. The signal processing circuit board is fixed on the top of the suspended platform with certain distance to ensure the static and dynamic magnetic field produced by circuit board no effect to the sensor, so we could get flexible instrument due to signal attenuation resulting signal transmission cable limited length.

Generation of optical OFDM signals using 21.4 GS/s real time digital signal processing.

PubMed

Benlachtar, Yannis; Watts, Philip M; Bouziane, Rachid; Milder, Peter; Rangaraj, Deepak; Cartolano, Anthony; Koutsoyannis, Robert; Hoe, James C; Püschel, Markus; Glick, Madeleine; Killey, Robert I

2009-09-28

We demonstrate a field programmable gate array (FPGA) based optical orthogonal frequency division multiplexing (OFDM) transmitter implementing real time digital signal processing at a sample rate of 21.4 GS/s. The QPSK-OFDM signal is generated using an 8 bit, 128 point inverse fast Fourier transform (IFFT) core, performing one transform per clock cycle at a clock speed of 167.2 MHz and can be deployed with either a direct-detection or a coherent receiver. The hardware design and the main digital signal processing functions are described, and we show that the main performance limitation is due to the low (4-bit) resolution of the digital-to-analog converter (DAC) and the 8-bit resolution of the IFFT core used. We analyze the back-to-back performance of the transmitter generating an 8.36 Gb/s optical single sideband (SSB) OFDM signal using digital up-conversion, suitable for direct-detection. Additionally, we use the device to transmit 8.36 Gb/s SSB OFDM signals over 200 km of uncompensated standard single mode fiber achieving an overall BER<10(-3).

pySPACE—a signal processing and classification environment in Python

PubMed Central

Krell, Mario M.; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Teiwes, Johannes; Metzen, Jan H.; Kirchner, Elsa A.; Kirchner, Frank

2013-01-01

In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace), signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG). The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms, and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries. PMID:24399965

pySPACE-a signal processing and classification environment in Python.

PubMed

Krell, Mario M; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Teiwes, Johannes; Metzen, Jan H; Kirchner, Elsa A; Kirchner, Frank

2013-01-01

In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace), signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG). The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms, and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries.

40 CFR 86.004-40 - Heavy-duty engine rebuilding practices.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., replacement of multiple parts due to wear, and reassembly, and also may include the removal of the engine from..., emissions-related codes or signals from on-board monitoring systems may not be erased or reset without... signals may not be rendered inoperative during the rebuilding process. (d) When conducting a rebuild...

40 CFR 86.004-40 - Heavy-duty engine rebuilding practices.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., replacement of multiple parts due to wear, and reassembly, and also may include the removal of the engine from..., emissions-related codes or signals from on-board monitoring systems may not be erased or reset without... signals may not be rendered inoperative during the rebuilding process. (d) When conducting a rebuild...

40 CFR 86.004-40 - Heavy-duty engine rebuilding practices.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., replacement of multiple parts due to wear, and reassembly, and also may include the removal of the engine from..., emissions-related codes or signals from on-board monitoring systems may not be erased or reset without... signals may not be rendered inoperative during the rebuilding process. (d) When conducting a rebuild...

40 CFR 86.004-40 - Heavy-duty engine rebuilding practices.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., replacement of multiple parts due to wear, and reassembly, and also may include the removal of the engine from..., emissions-related codes or signals from on-board monitoring systems may not be erased or reset without... signals may not be rendered inoperative during the rebuilding process. (d) When conducting a rebuild...

Robust Connectivity in Sensory and Ad Hoc Network

DTIC Science & Technology

2011-02-01

as the prior probability is π0 = 0.8, the error probability should be capped at 0.2. This seemingly pathological result is due to the fact that the...publications and is the author of the book Multirate and Wavelet Signal Processing (Academic Press, 1998). His research interests include multiscale signal and

Adaptive signal processing and higher order time- frequency analysis for acoustic and vibration signatures in condition monitoring

NASA Astrophysics Data System (ADS)

Lee, Sang-Kwon

This thesis is concerned with the development of a useful engineering technique to detect and analyse faults in rotating machinery. The methods developed are based on the advanced signal processing such as the adaptive signal processing and higher-order time frequency methods. The two-stage Adaptive Line Enhancer (ALE), using adaptive signal processing, has been developed for increasing the Signal to Noise Ratio of impulsive signals. The enhanced signal can then be analysed using time frequency methods to identify fault characteristics. However, if after pre-processing by the two stage ALE, the SNR of the signals is low, the residual noise often hinders clear identification of the fault characteristics in the time-frequency domain. In such cases, higher order time-frequency methods have been proposed and studied. As examples of rotating machinery, the internal combustion engine and an industrial gear box are considered in this thesis. The noise signal from an internal combustion engine and vibration signal measured on a gear box are studied in detail. Typically an impulsive signal manifests itself when the fault occurs in the machinery and is embedded in background noise, such as the fundamental frequency and its harmonic orders of the rotation speed and broadband noise. The two-stage ALE is developed for reducing this background noise. Conditions for the choice of adaptive filter parameters are studied and suitable adaptive algorithms given. The enhanced impulsive signal is analysed in the time- frequency domain using the Wigner higher order moment spectra (WHOMS) and the multi-time WHOMS (which is a dual form of the WHOMS). The WHOMS suffers from unwanted cross-terms, which increase dramatically as the order increases. Novel expressions for the cross-terms in WHOMS have been presented. The number of cross-terms can be reduced by taking the principal slice of the WHOMS. The residual cross-terms are smoothed by using a general class of kernel functions and the γ-method kernel function which is a novel development in this thesis. The WVD and the sliced WHOMS for synthesised signals and measured data from rotating machinery are analysed. The estimated ROC (Receive Operating Characteristic) curves for these methods are computed. These results lead to the conclusion that the detection performance when using the sliced WHOMS, for impulsive signals in embedded in broadband noise, is better than that of the Wigner-Ville distribution. Real data from a faulty car engine and faulty industrial gears are analysed. The car engine radiates an impulsive noise signal due to the loosening of a spark plug. The faulty industrial gear produces an impulsive vibration signal due to a spall on the tooth face in gear. The two- stage ALE and WHOMS are successfully applied to detection and analysis of these impulsive signals.

Radar Doppler Processing with Nonuniform Sampling.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doerry, Armin W.

2017-07-01

Conventional signal processing to estimate radar Doppler frequency often assumes uniform pulse/sample spacing. This is for the convenience of t he processing. More recent performance enhancements in processor capability allow optimally processing nonuniform pulse/sample spacing, thereby overcoming some of the baggage that attends uniform sampling, such as Doppler ambiguity and SNR losses due to sidelobe control measures.

Myoelectric signal processing for control of powered limb prostheses.

PubMed

Parker, P; Englehart, K; Hudgins, B

2006-12-01

Progress in myoelectric control technology has over the years been incremental, due in part to the alternating focus of the R&D between control methodology and device hardware. The technology has over the past 50 years or so moved from single muscle control of a single prosthesis function to muscle group activity control of multifunction prostheses. Central to these changes have been developments in the means of extracting information from the myoelectric signal. This paper gives an overview of the myoelectric signal processing challenge, a brief look at the challenge from an historical perspective, the state-of-the-art in myoelectric signal processing for prosthesis control, and an indication of where this field is heading. The paper demonstrates that considerable progress has been made in providing clients with useful and reliable myoelectric communication channels, and that exciting work and developments are on the horizon.

Signal Restoration of Non-stationary Acoustic Signals in the Time Domain

NASA Technical Reports Server (NTRS)

Babkin, Alexander S.

1988-01-01

Signal restoration is a method of transforming a nonstationary signal acquired by a ground based microphone to an equivalent stationary signal. The benefit of the signal restoration is a simplification of the flight test requirements because it could dispense with the need to acquire acoustic data with another aircraft flying in concert with the rotorcraft. The data quality is also generally improved because the contamination of the signal by the propeller and wind noise is not present. The restoration methodology can also be combined with other data acquisition methods, such as a multiple linear microphone array for further improvement of the test results. The methodology and software are presented for performing the signal restoration in the time domain. The method has no restrictions on flight path geometry or flight regimes. Only requirement is that the aircraft spatial position be known relative to the microphone location and synchronized with the acoustic data. The restoration process assumes that the moving source radiates a stationary signal, which is then transformed into a nonstationary signal by various modulation processes. The restoration contains only the modulation due to the source motion.

Global scale stratospheric processes as measured by the infrasound IMS network

NASA Astrophysics Data System (ADS)

Le Pichon, A.; Ceranna, L.; Kechut, P.

2012-04-01

IMS infrasound array data are routinely processed at the International Data Center (IDC). The wave parameters of the detected signals are estimated with the Progressive Multi-Channel Correlation method (PMCC). This new implementation of the PMCC algorithm allows the full frequency range of interest (0.01-5 Hz) to be processed efficiently in a single computational run. We have processed continuous recordings from 41 certified IMS stations from 2005 to 2010. We show that microbaroms are the dominant source of signals and are near-continuously globally detected. The observed azimuthal seasonal trend correlates well with the variation of the effective sound speed ratio which is a proxy for the combined effects of refraction due to sound speed gradients and advection due to along-path wind on infrasound propagation. A general trend in signal backazimuth is observed between winter and summer, driven by the seasonal reversal of the stratospheric winds. Combined with propagation modeling, we show that such an analysis enables a characterization of the wind and temperature structure above the stratosphere and may provide detailed information on upper atmospheric processes (e.g., large-scale planetary waves, stratospheric warming effects). We correlate perturbations and deviations from the seasonal trend to short time-scale variability of the atmosphere. We discuss the potential benefit of long-term infrasound monitoring to infer stratospheric processes for the first time on a global scale.

Using EEG/MEG Data of Cognitive Processes in Brain-Computer Interfaces

NASA Astrophysics Data System (ADS)

Gutiérrez, David

2008-08-01

Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using electroencephalographic (EEG) and, more recently, magnetoencephalographic (MEG) measurements of the brain function. Most of the current implementations of BCIs rely on EEG/MEG data of motor activities as such neural processes are well characterized, while the use of data related to cognitive activities has been neglected due to its intrinsic complexity. However, cognitive data usually has larger amplitude, lasts longer and, in some cases, cognitive brain signals are easier to control at will than motor signals. This paper briefy reviews the use of EEG/MEG data of cognitive processes in the implementation of BCIs. Specifically, this paper reviews some of the neuromechanisms, signal features, and processing methods involved. This paper also refers to some of the author's work in the area of detection and classifcation of cognitive signals for BCIs using variability enhancement, parametric modeling, and spatial fltering, as well as recent developments in BCI performance evaluation.

Using EEG/MEG Data of Cognitive Processes in Brain-Computer Interfaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gutierrez, David

2008-08-11

Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using electroencephalographic (EEG) and, more recently, magnetoencephalographic (MEG) measurements of the brain function. Most of the current implementations of BCIs rely on EEG/MEG data of motor activities as such neural processes are well characterized, while the use of data related to cognitive activities has been neglected due to its intrinsic complexity. However, cognitive data usually has larger amplitude, lasts longer and, in some cases, cognitive brain signals are easier to control at will than motor signals. This paper briefy reviews the use of EEG/MEGmore » data of cognitive processes in the implementation of BCIs. Specifically, this paper reviews some of the neuromechanisms, signal features, and processing methods involved. This paper also refers to some of the author's work in the area of detection and classifcation of cognitive signals for BCIs using variability enhancement, parametric modeling, and spatial fltering, as well as recent developments in BCI performance evaluation.« less

FIBRE AND INTEGRATED OPTICS. OPTICAL PROCESSING OF INFORMATION: Method for optical data processing based on a two-pulse photon echo

NASA Astrophysics Data System (ADS)

Zakharov, S. M.; Manykin, Eduard A.

1995-02-01

The principles of optical processing based on dynamic spatial—temporal properties of two-pulse photon echo signals are considered. The properties of a resonant medium as an on-line filter of temporal and spatial frequencies are discussed. These properties are due to the sensitivity of such a medium to the Fourier spectrum of the second exiting pulse. Degeneracy of quantum resonant systems, demonstrated by the coherent response dependence on the square of the amplitude of the second pulse, can be used for 'simultaneous' correlation processing of optical 'signals'. Various methods for the processing of the Fourier optical image are discussed.

An intelligent signal processing and pattern recognition technique for defect identification using an active sensor network

NASA Astrophysics Data System (ADS)

Su, Zhongqing; Ye, Lin

2004-08-01

The practical utilization of elastic waves, e.g. Rayleigh-Lamb waves, in high-performance structural health monitoring techniques is somewhat impeded due to the complicated wave dispersion phenomena, the existence of multiple wave modes, the high susceptibility to diverse interferences, the bulky sampled data and the difficulty in signal interpretation. An intelligent signal processing and pattern recognition (ISPPR) approach using the wavelet transform and artificial neural network algorithms was developed; this was actualized in a signal processing package (SPP). The ISPPR technique comprehensively functions as signal filtration, data compression, characteristic extraction, information mapping and pattern recognition, capable of extracting essential yet concise features from acquired raw wave signals and further assisting in structural health evaluation. For validation, the SPP was applied to the prediction of crack growth in an alloy structural beam and construction of a damage parameter database for defect identification in CF/EP composite structures. It was clearly apparent that the elastic wave propagation-based damage assessment could be dramatically streamlined by introduction of the ISPPR technique.

Evaluation of higher order statistics parameters for multi channel sEMG using different force levels.

PubMed

Naik, Ganesh R; Kumar, Dinesh K

2011-01-01

The electromyograpy (EMG) signal provides information about the performance of muscles and nerves. The shape of the muscle signal and motor unit action potential (MUAP) varies due to the movement of the position of the electrode or due to changes in contraction level. This research deals with evaluating the non-Gaussianity in Surface Electromyogram signal (sEMG) using higher order statistics (HOS) parameters. To achieve this, experiments were conducted for four different finger and wrist actions at different levels of Maximum Voluntary Contractions (MVCs). Our experimental analysis shows that at constant force and for non-fatiguing contractions, probability density functions (PDF) of sEMG signals were non-Gaussian. For lesser MVCs (below 30% of MVC) PDF measures tends to be Gaussian process. The above measures were verified by computing the Kurtosis values for different MVCs.

The string soundscape at gravitational wave detectors

NASA Astrophysics Data System (ADS)

Garcia Garcia, Isabel; Krippendorf, Sven; March-Russell, John

2018-04-01

We argue that gravitational wave signals due to collisions of ultra-relativistic bubble walls may be common in string theory. This occurs due to a process of post-inflationary vacuum decay via quantum tunnelling. Though we study a specific string construction involving warped throats, we argue that our conclusions are more general. Many such transitions could have occurred in the post-inflationary Universe, as a large number of throats with exponentially different mass scales can be present in the string landscape, leading to several signals of widely different frequencies - a soundscape connected to the landscape of vacua. Detectors such as aLIGO/VIRGO, LISA, and pulsar timing observations with SKA and EPTA have the sensitivity to detect such signals. A distribution of primordial black holes is also a likely consequence, though reliable estimates of masses and their abundance require dedicated numerical simulations, as do the fine details of the gravitational wave spectrum due to the unusual nature of the transition.

Automatic Speech Recognition from Neural Signals: A Focused Review.

PubMed

Herff, Christian; Schultz, Tanja

2016-01-01

Speech interfaces have become widely accepted and are nowadays integrated in various real-life applications and devices. They have become a part of our daily life. However, speech interfaces presume the ability to produce intelligible speech, which might be impossible due to either loud environments, bothering bystanders or incapabilities to produce speech (i.e., patients suffering from locked-in syndrome). For these reasons it would be highly desirable to not speak but to simply envision oneself to say words or sentences. Interfaces based on imagined speech would enable fast and natural communication without the need for audible speech and would give a voice to otherwise mute people. This focused review analyzes the potential of different brain imaging techniques to recognize speech from neural signals by applying Automatic Speech Recognition technology. We argue that modalities based on metabolic processes, such as functional Near Infrared Spectroscopy and functional Magnetic Resonance Imaging, are less suited for Automatic Speech Recognition from neural signals due to low temporal resolution but are very useful for the investigation of the underlying neural mechanisms involved in speech processes. In contrast, electrophysiologic activity is fast enough to capture speech processes and is therefor better suited for ASR. Our experimental results indicate the potential of these signals for speech recognition from neural data with a focus on invasively measured brain activity (electrocorticography). As a first example of Automatic Speech Recognition techniques used from neural signals, we discuss the Brain-to-text system.

An optimal filter for short photoplethysmogram signals

PubMed Central

Liang, Yongbo; Elgendi, Mohamed; Chen, Zhencheng; Ward, Rabab

2018-01-01

A photoplethysmogram (PPG) contains a wealth of cardiovascular system information, and with the development of wearable technology, it has become the basic technique for evaluating cardiovascular health and detecting diseases. However, due to the varying environments in which wearable devices are used and, consequently, their varying susceptibility to noise interference, effective processing of PPG signals is challenging. Thus, the aim of this study was to determine the optimal filter and filter order to be used for PPG signal processing to make the systolic and diastolic waves more salient in the filtered PPG signal using the skewness quality index. Nine types of filters with 10 different orders were used to filter 219 (2.1s) short PPG signals. The signals were divided into three categories by PPG experts according to their noise levels: excellent, acceptable, or unfit. Results show that the Chebyshev II filter can improve the PPG signal quality more effectively than other types of filters and that the optimal order for the Chebyshev II filter is the 4th order. PMID:29714722

Calcium and ROS: A mutual interplay

PubMed Central

Görlach, Agnes; Bertram, Katharina; Hudecova, Sona; Krizanova, Olga

2015-01-01

Calcium is an important second messenger involved in intra- and extracellular signaling cascades and plays an essential role in cell life and death decisions. The Ca2+ signaling network works in many different ways to regulate cellular processes that function over a wide dynamic range due to the action of buffers, pumps and exchangers on the plasma membrane as well as in internal stores. Calcium signaling pathways interact with other cellular signaling systems such as reactive oxygen species (ROS). Although initially considered to be potentially detrimental byproducts of aerobic metabolism, it is now clear that ROS generated in sub-toxic levels by different intracellular systems act as signaling molecules involved in various cellular processes including growth and cell death. Increasing evidence suggests a mutual interplay between calcium and ROS signaling systems which seems to have important implications for fine tuning cellular signaling networks. However, dysfunction in either of the systems might affect the other system thus potentiating harmful effects which might contribute to the pathogenesis of various disorders. PMID:26296072

Signal Processing in Functional Near-Infrared Spectroscopy (fNIRS): Methodological Differences Lead to Different Statistical Results.

PubMed

Pfeifer, Mischa D; Scholkmann, Felix; Labruyère, Rob

2017-01-01

Even though research in the field of functional near-infrared spectroscopy (fNIRS) has been performed for more than 20 years, consensus on signal processing methods is still lacking. A significant knowledge gap exists between established researchers and those entering the field. One major issue regularly observed in publications from researchers new to the field is the failure to consider possible signal contamination by hemodynamic changes unrelated to neurovascular coupling (i.e., scalp blood flow and systemic blood flow). This might be due to the fact that these researchers use the signal processing methods provided by the manufacturers of their measurement device without an advanced understanding of the performed steps. The aim of the present study was to investigate how different signal processing approaches (including and excluding approaches that partially correct for the possible signal contamination) affect the results of a typical functional neuroimaging study performed with fNIRS. In particular, we evaluated one standard signal processing method provided by a commercial company and compared it to three customized approaches. We thereby investigated the influence of the chosen method on the statistical outcome of a clinical data set (task-evoked motor cortex activity). No short-channels were used in the present study and therefore two types of multi-channel corrections based on multiple long-channels were applied. The choice of the signal processing method had a considerable influence on the outcome of the study. While methods that ignored the contamination of the fNIRS signals by task-evoked physiological noise yielded several significant hemodynamic responses over the whole head, the statistical significance of these findings disappeared when accounting for part of the contamination using a multi-channel regression. We conclude that adopting signal processing methods that correct for physiological confounding effects might yield more realistic results in cases where multi-distance measurements are not possible. Furthermore, we recommend using manufacturers' standard signal processing methods only in case the user has an advanced understanding of every signal processing step performed.

[Cognitive aging mechanism of signaling effects on the memory for procedural sentences].

PubMed

Yamamoto, Hiroki; Shimada, Hideaki

2006-08-01

The aim of this study was to clarify the cognitive aging mechanism of signaling effects on the memory for procedural sentences. Participants were 60 younger adults (college students) and 60 older adults. Both age groups were assigned into two groups; half of each group was presented with procedural sentences with signals that highlighted their top-level structure and the other half with procedural sentences without them. Both groups were requested to perform the sentence arrangement task and the reconstruction task. Each task was composed of procedural sentences with or without signals. Results indicated that signaling supported changes in strategy utilization during the successive organizational processes and that changes in strategy utilization resulting from signaling improved the memory for procedural sentences. Moreover, age-related factors interfered with these signaling effects. This study clarified the cognitive aging mechanism of signaling effects in which signaling supports changes in the strategy utilization during organizational processes at encoding and this mediation promotes memory for procedural sentences, though disuse of the strategy utilization due to aging restrains their memory for procedural sentences.

Analog integrated circuits design for processing physiological signals.

PubMed

Li, Yan; Poon, Carmen C Y; Zhang, Yuan-Ting

2010-01-01

Analog integrated circuits (ICs) designed for processing physiological signals are important building blocks of wearable and implantable medical devices used for health monitoring or restoring lost body functions. Due to the nature of physiological signals and the corresponding application scenarios, the ICs designed for these applications should have low power consumption, low cutoff frequency, and low input-referred noise. In this paper, techniques for designing the analog front-end circuits with these three characteristics will be reviewed, including subthreshold circuits, bulk-driven MOSFETs, floating gate MOSFETs, and log-domain circuits to reduce power consumption; methods for designing fully integrated low cutoff frequency circuits; as well as chopper stabilization (CHS) and other techniques that can be used to achieve a high signal-to-noise performance. Novel applications using these techniques will also be discussed.

Improved signal recovery for flow cytometry based on ‘spatially modulated emission’

NASA Astrophysics Data System (ADS)

Quint, S.; Wittek, J.; Spang, P.; Levanon, N.; Walther, T.; Baßler, M.

2017-09-01

Recently, the technique of ‘spatially modulated emission’ has been introduced (Baßler et al 2008 US Patent 0080181827A1; Kiesel et al 2009 Appl. Phys. Lett. 94 041107; Kiesel et al 2011 Cytometry A 79A 317-24) improving the signal-to-noise ratio (SNR) for detecting bio-particles in the field of flow cytometry. Based on this concept, we developed two advanced signal processing methods which further enhance the SNR and selectivity for cell detection. The improvements are achieved by adapting digital filtering methods from RADAR technology and mainly address inherent offset elimination, increased signal dynamics and moreover reduction of erroneous detections due to processing artifacts. We present a comprehensive theory on SNR gain and provide experimental results of our concepts.

Measurement of fast-changing low velocities by photonic Doppler velocimetry

NASA Astrophysics Data System (ADS)

Song, Hongwei; Wu, Xianqian; Huang, Chenguang; Wei, Yangpeng; Wang, Xi

2012-07-01

Despite the increasing popularity of photonic Doppler velocimetry (PDV) in shock wave experiments, its capability of capturing low particle velocities while changing rapidly is still questionable. The paper discusses the performance of short time Fourier transform (STFT) and continuous wavelet transform (CWT) in processing fringe signals of fast-changing low velocities measured by PDV. Two typical experiments are carried out to evaluate the performance. In the laser shock peening test, the CWT gives a better interpretation to the free surface velocity history, where the elastic precursor, main plastic wave, and elastic release wave can be clearly identified. The velocities of stress waves, Hugoniot elastic limit, and the amplitude of shock pressure induced by laser can be obtained from the measurement. In the Kolsky-bar based tests, both methods show validity of processing the longitudinal velocity signal of incident bar, whereas CWT improperly interprets the radial velocity of the shocked sample at the beginning period, indicating the sensitiveness of the CWT to the background noise. STFT is relatively robust in extracting waveforms of low signal-to-noise ratio. Data processing method greatly affects the temporal resolution and velocity resolution of a given fringe signal, usually CWT demonstrates a better local temporal resolution and velocity resolution, due to its adaptability to the local frequency, also due to the finer time-frequency product according to the uncertainty principle.

Measurement of fast-changing low velocities by photonic Doppler velocimetry.

PubMed

Song, Hongwei; Wu, Xianqian; Huang, Chenguang; Wei, Yangpeng; Wang, Xi

2012-07-01

Despite the increasing popularity of photonic Doppler velocimetry (PDV) in shock wave experiments, its capability of capturing low particle velocities while changing rapidly is still questionable. The paper discusses the performance of short time Fourier transform (STFT) and continuous wavelet transform (CWT) in processing fringe signals of fast-changing low velocities measured by PDV. Two typical experiments are carried out to evaluate the performance. In the laser shock peening test, the CWT gives a better interpretation to the free surface velocity history, where the elastic precursor, main plastic wave, and elastic release wave can be clearly identified. The velocities of stress waves, Hugoniot elastic limit, and the amplitude of shock pressure induced by laser can be obtained from the measurement. In the Kolsky-bar based tests, both methods show validity of processing the longitudinal velocity signal of incident bar, whereas CWT improperly interprets the radial velocity of the shocked sample at the beginning period, indicating the sensitiveness of the CWT to the background noise. STFT is relatively robust in extracting waveforms of low signal-to-noise ratio. Data processing method greatly affects the temporal resolution and velocity resolution of a given fringe signal, usually CWT demonstrates a better local temporal resolution and velocity resolution, due to its adaptability to the local frequency, also due to the finer time-frequency product according to the uncertainty principle.

Measurement of fast-changing low velocities by photonic Doppler velocimetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song Hongwei; Wu Xianqian; Huang Chenguang

2012-07-15

Despite the increasing popularity of photonic Doppler velocimetry (PDV) in shock wave experiments, its capability of capturing low particle velocities while changing rapidly is still questionable. The paper discusses the performance of short time Fourier transform (STFT) and continuous wavelet transform (CWT) in processing fringe signals of fast-changing low velocities measured by PDV. Two typical experiments are carried out to evaluate the performance. In the laser shock peening test, the CWT gives a better interpretation to the free surface velocity history, where the elastic precursor, main plastic wave, and elastic release wave can be clearly identified. The velocities of stressmore » waves, Hugoniot elastic limit, and the amplitude of shock pressure induced by laser can be obtained from the measurement. In the Kolsky-bar based tests, both methods show validity of processing the longitudinal velocity signal of incident bar, whereas CWT improperly interprets the radial velocity of the shocked sample at the beginning period, indicating the sensitiveness of the CWT to the background noise. STFT is relatively robust in extracting waveforms of low signal-to-noise ratio. Data processing method greatly affects the temporal resolution and velocity resolution of a given fringe signal, usually CWT demonstrates a better local temporal resolution and velocity resolution, due to its adaptability to the local frequency, also due to the finer time-frequency product according to the uncertainty principle.« less

Correlation ion mobility spectroscopy

DOEpatents

Pfeifer, Kent B [Los Lunas, NM; Rohde, Steven B [Corrales, NM

2008-08-26

Correlation ion mobility spectrometry (CIMS) uses gating modulation and correlation signal processing to improve IMS instrument performance. Closely spaced ion peaks can be resolved by adding discriminating codes to the gate and matched filtering for the received ion current signal, thereby improving sensitivity and resolution of an ion mobility spectrometer. CIMS can be used to improve the signal-to-noise ratio even for transient chemical samples. CIMS is especially advantageous for small geometry IMS drift tubes that can otherwise have poor resolution due to their small size.

Wavelet transform analysis of transient signals: the seismogram and the electrocardiogram

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anant, K.S.

1997-06-01

In this dissertation I quantitatively demonstrate how the wavelet transform can be an effective mathematical tool for the analysis of transient signals. The two key signal processing applications of the wavelet transform, namely feature identification and representation (i.e., compression), are shown by solving important problems involving the seismogram and the electrocardiogram. The seismic feature identification problem involved locating in time the P and S phase arrivals. Locating these arrivals accurately (particularly the S phase) has been a constant issue in seismic signal processing. In Chapter 3, I show that the wavelet transform can be used to locate both the Pmore » as well as the S phase using only information from single station three-component seismograms. This is accomplished by using the basis function (wave-let) of the wavelet transform as a matching filter and by processing information across scales of the wavelet domain decomposition. The `pick` time results are quite promising as compared to analyst picks. The representation application involved the compression of the electrocardiogram which is a recording of the electrical activity of the heart. Compression of the electrocardiogram is an important problem in biomedical signal processing due to transmission and storage limitations. In Chapter 4, I develop an electrocardiogram compression method that applies vector quantization to the wavelet transform coefficients. The best compression results were obtained by using orthogonal wavelets, due to their ability to represent a signal efficiently. Throughout this thesis the importance of choosing wavelets based on the problem at hand is stressed. In Chapter 5, I introduce a wavelet design method that uses linear prediction in order to design wavelets that are geared to the signal or feature being analyzed. The use of these designed wavelets in a test feature identification application led to positive results. The methods developed in this thesis; the feature identification methods of Chapter 3, the compression methods of Chapter 4, as well as the wavelet design methods of Chapter 5, are general enough to be easily applied to other transient signals.« less

A biological inspired fuzzy adaptive window median filter (FAWMF) for enhancing DNA signal processing.

PubMed

Ahmad, Muneer; Jung, Low Tan; Bhuiyan, Al-Amin

2017-10-01

Digital signal processing techniques commonly employ fixed length window filters to process the signal contents. DNA signals differ in characteristics from common digital signals since they carry nucleotides as contents. The nucleotides own genetic code context and fuzzy behaviors due to their special structure and order in DNA strand. Employing conventional fixed length window filters for DNA signal processing produce spectral leakage and hence results in signal noise. A biological context aware adaptive window filter is required to process the DNA signals. This paper introduces a biological inspired fuzzy adaptive window median filter (FAWMF) which computes the fuzzy membership strength of nucleotides in each slide of window and filters nucleotides based on median filtering with a combination of s-shaped and z-shaped filters. Since coding regions cause 3-base periodicity by an unbalanced nucleotides' distribution producing a relatively high bias for nucleotides' usage, such fundamental characteristic of nucleotides has been exploited in FAWMF to suppress the signal noise. Along with adaptive response of FAWMF, a strong correlation between median nucleotides and the Π shaped filter was observed which produced enhanced discrimination between coding and non-coding regions contrary to fixed length conventional window filters. The proposed FAWMF attains a significant enhancement in coding regions identification i.e. 40% to 125% as compared to other conventional window filters tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms. This study proves that conventional fixed length window filters applied to DNA signals do not achieve significant results since the nucleotides carry genetic code context. The proposed FAWMF algorithm is adaptive and outperforms significantly to process DNA signal contents. The algorithm applied to variety of DNA datasets produced noteworthy discrimination between coding and non-coding regions contrary to fixed window length conventional filters. Copyright © 2017 Elsevier B.V. All rights reserved.

Nonlinear Real-Time Optical Signal Processing.

DTIC Science & Technology

1981-06-30

bandwidth and space-bandwidth products. Real-time homonorphic and loga- rithmic filtering by halftone nonlinear processing has been achieved. A...Page ABSTRACT 1 1. RESEARCH OBJECTIVES AND PROGRESS 3 I-- 1.1 Introduction and Project overview 3 1.2 Halftone Processing 9 1.3 Direct Nonlinear...time homomorphic and logarithmic filtering by halftone nonlinear processing has been achieved. A detailed analysis of degradation due to the finite gamma

Digital signal processing algorithms for automatic voice recognition

NASA Technical Reports Server (NTRS)

Botros, Nazeih M.

1987-01-01

The current digital signal analysis algorithms are investigated that are implemented in automatic voice recognition algorithms. Automatic voice recognition means, the capability of a computer to recognize and interact with verbal commands. The digital signal is focused on, rather than the linguistic, analysis of speech signal. Several digital signal processing algorithms are available for voice recognition. Some of these algorithms are: Linear Predictive Coding (LPC), Short-time Fourier Analysis, and Cepstrum Analysis. Among these algorithms, the LPC is the most widely used. This algorithm has short execution time and do not require large memory storage. However, it has several limitations due to the assumptions used to develop it. The other 2 algorithms are frequency domain algorithms with not many assumptions, but they are not widely implemented or investigated. However, with the recent advances in the digital technology, namely signal processors, these 2 frequency domain algorithms may be investigated in order to implement them in voice recognition. This research is concerned with real time, microprocessor based recognition algorithms.

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

PubMed

Conzelmann, Holger; Gilles, Ernst-Dieter

2008-01-01

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

Review of current GPS methodologies for producing accurate time series and their error sources

NASA Astrophysics Data System (ADS)

He, Xiaoxing; Montillet, Jean-Philippe; Fernandes, Rui; Bos, Machiel; Yu, Kegen; Hua, Xianghong; Jiang, Weiping

2017-05-01

The Global Positioning System (GPS) is an important tool to observe and model geodynamic processes such as plate tectonics and post-glacial rebound. In the last three decades, GPS has seen tremendous advances in the precision of the measurements, which allow researchers to study geophysical signals through a careful analysis of daily time series of GPS receiver coordinates. However, the GPS observations contain errors and the time series can be described as the sum of a real signal and noise. The signal itself can again be divided into station displacements due to geophysical causes and to disturbing factors. Examples of the latter are errors in the realization and stability of the reference frame and corrections due to ionospheric and tropospheric delays and GPS satellite orbit errors. There is an increasing demand on detecting millimeter to sub-millimeter level ground displacement signals in order to further understand regional scale geodetic phenomena hence requiring further improvements in the sensitivity of the GPS solutions. This paper provides a review spanning over 25 years of advances in processing strategies, error mitigation methods and noise modeling for the processing and analysis of GPS daily position time series. The processing of the observations is described step-by-step and mainly with three different strategies in order to explain the weaknesses and strengths of the existing methodologies. In particular, we focus on the choice of the stochastic model in the GPS time series, which directly affects the estimation of the functional model including, for example, tectonic rates, seasonal signals and co-seismic offsets. Moreover, the geodetic community continues to develop computational methods to fully automatize all phases from analysis of GPS time series. This idea is greatly motivated by the large number of GPS receivers installed around the world for diverse applications ranging from surveying small deformations of civil engineering structures (e.g., subsidence of the highway bridge) to the detection of particular geophysical signals.

Chemical process to separate iron oxides particles in pottery sample for EPR dating

NASA Astrophysics Data System (ADS)

Watanabe, S.; Farias, T. M. B.; Gennari, R. F.; Ferraz, G. M.; Kunzli, R.; Chubaci, J. F. D.

2008-12-01

Ancient potteries usually are made of the local clay material, which contains relatively high concentration of iron. The powdered samples are usually quite black, due to magnetite, and, although they can be used for thermoluminescene (TL) dating, it is easiest to obtain better TL reading when clearest natural or pre-treated sample is used. For electron paramagnetic resonance (EPR) measurements, the huge signal due to iron spin-spin interaction, promotes an intense interference overlapping any other signal in this range. Sample dating is obtained by dividing the radiation dose, determined by the concentration of paramagnetic species generated by irradiation, by the natural dose so as a consequence, EPR dating cannot be used, since iron signal do not depend on radiation dose. In some cases, the density separation method using hydrated solution of sodium polytungstate [Na 6(H 2W 12O 40)·H 2O] becomes useful. However, the sodium polytungstate is very expensive in Brazil; hence an alternative method for eliminating this interference is proposed. A chemical process to eliminate about 90% of magnetite was developed. A sample of powdered ancient pottery was treated in a mixture (3:1:1) of HCl, HNO 3 and H 2O 2 for 4 h. After that, it was washed several times in distilled water to remove all acid matrixes. The original black sample becomes somewhat clearer. The resulting material was analyzed by plasma mass spectrometry (ICP-MS), with the result that the iron content is reduced by a factor of about 9. In EPR measurements a non-treated natural ceramic sample shows a broad spin-spin interaction signal, the chemically treated sample presents a narrow signal in g = 2.00 region, possibly due to a radical of (SiO 3) 3-, mixed with signal of remaining iron [M. Ikeya, New Applications of Electron Spin Resonance, World Scientific, Singapore, 1993, p. 285]. This signal increases in intensity under γ-irradiation. However, still due to iron influence, the additive method yielded too old age-value. Since annealing at 300 °C, Toyoda and Ikeya [S. Toyoda, M. Ikeya, Geochem. J. 25 (1991) 427-445] states that E1-signal with maximum intensity is obtained, while annealing at 400 °C E1-signal is completely eliminated, the subtraction of the second one from 300 °C heat-treated sample isolate E1-like signal. Since this is radiation dose-dependent, we show that now EPR dating becomes possible.

A reprogrammable receiver architecture for wireless signal interception

NASA Astrophysics Data System (ADS)

Yao, Timothy S.

2003-09-01

In this paper, a re-programmable receiver architecture, based on software-defined-radio concept, for wireless signal interception is presented. The radio-frequency (RF) signal that the receiver would like to intercept may come from a terrestrial cellular network or communication satellites, which their carrier frequency are in the range from 800 MHz (civilian mobile) to 15 GHz (Ku band). To intercept signals from such a wide range of frequency in these variant communication systems, the traditional way is to deploy multiple receivers to scan and detect the desired signal. This traditional approach is obviously unattractive due to the cost, efficiency, and accuracy. Instead, we propose a universal receiver, which is software-driven and re-configurable, to intercept signals of interest. The software-defined-radio based receiver first intercepts RF energy of wide spectrum (25MHz) through antenna, performs zero-IF down conversion (homodyne architecture) to baseband, and digital channelizes the baseband signal. The channelization module is a bank of high performance digital filters. The bandwidth of the filter bank is programmable according to the wireless communication protocol under watch. In the baseband processing, high-performance digital signal processors carry out the detection process and microprocessors handle the communication protocols. The baseband processing is also re-configurable for different wireless standards and protocol. The advantages of the software-defined-radio architecture over traditional RF receiver make it a favorable technology for the communication signal interception and surveillance.

Comparison of angular dependence of magnetic Barkhausen noise of hysteresis and initial magnetization curve in API5L steel

NASA Astrophysics Data System (ADS)

Chávez-Gonzalez, A. F.; Martínez-Ortiz, P.; Pérez-Benítez, J. A.; Espina-Hernández, J. H.; Caleyo, F.

2018-01-01

This work analyzes the differences between the magnetic Barkhausen noise corresponding to the initial magnetization curve and Barkhausen noise corresponding to one branch of the hysteresis loop in API-5L steel. The outcomes show that the Barkhausen noise signal corresponding to the initial magnetization curve and that corresponding to the hysteresis are significantly different. This difference is due to the presence of different processes of the domain wall dynamics in both phenomena. To study the processes present in magnetization dynamics for an applied field of H > 0, research into the angular dependence of a Barkhausen signal using applied field bands has revealed that a Barkhausen signal corresponding to the initial magnetization curve is more suitable than a Barkhausen signal corresponding to the hysteresis loop.

An Informative Interpretation of Decision Theory: The Information Theoretic Basis for Signal-to-Noise Ratio and Log Likelihood Ratio

DOE PAGES

Polcari, J.

2013-08-16

The signal processing concept of signal-to-noise ratio (SNR), in its role as a performance measure, is recast within the more general context of information theory, leading to a series of useful insights. Establishing generalized SNR (GSNR) as a rigorous information theoretic measure inherent in any set of observations significantly strengthens its quantitative performance pedigree while simultaneously providing a specific definition under general conditions. This directly leads to consideration of the log likelihood ratio (LLR): first, as the simplest possible information-preserving transformation (i.e., signal processing algorithm) and subsequently, as an absolute, comparable measure of information for any specific observation exemplar. Furthermore,more » the information accounting methodology that results permits practical use of both GSNR and LLR as diagnostic scalar performance measurements, directly comparable across alternative system/algorithm designs, applicable at any tap point within any processing string, in a form that is also comparable with the inherent performance bounds due to information conservation.« less

Analysis of embolic signals with directional dual tree rational dilation wavelet transform.

PubMed

Serbes, Gorkem; Aydin, Nizamettin

2016-08-01

The dyadic discrete wavelet transform (dyadic-DWT), which is based on fixed integer sampling factor, has been used before for processing piecewise smooth biomedical signals. However, the dyadic-DWT has poor frequency resolution due to the low-oscillatory nature of its wavelet bases and therefore, it is less effective in processing embolic signals (ESs). To process ESs more effectively, a wavelet transform having better frequency resolution than the dyadic-DWT is needed. Therefore, in this study two ESs, containing micro-emboli and artifact waveforms, are analyzed with the Directional Dual Tree Rational-Dilation Wavelet Transform (DDT-RADWT). The DDT-RADWT, which can be directly applied to quadrature signals, is based on rational dilation factors and has adjustable frequency resolution. The analyses are done for both low and high Q-factors. It is proved that, when high Q-factor filters are employed in the DDT-RADWT, clearer representations of ESs can be attained in decomposed sub-bands and artifacts can be successfully separated.

Radioastronomic signal processing cores for the SKA radio telescope

NASA Astrophysics Data System (ADS)

Comorett, G.; Chiarucc, S.; Belli, C.

Modern radio telescopes require the processing of wideband signals, with sample rates from tens of MHz to tens of GHz, and are composed from hundreds up to a million of individual antennas. Digital signal processing of these signals include digital receivers (the digital equivalent of the heterodyne receiver), beamformers, channelizers, spectrometers. FPGAs present the advantage of providing a relatively low power consumption, relative to GPUs or dedicated computers, a wide signal data path, and high interconnectivity. Efficient algorithms have been developed for these applications. Here we will review some of the signal processing cores developed for the SKA telescope. The LFAA beamformer/channelizer architecture is based on an oversampling channelizer, where the channelizer output sampling rate and channel spacing can be set independently. This is useful where an overlap between adjacent channels is required to provide an uniform spectral coverage. The architecture allows for an efficient and distributed channelization scheme, with a final resolution corresponding to a million of spectral channels, minimum leakage and high out-of-band rejection. An optimized filter design procedure is used to provide an equiripple response with a very large number of spectral channels. A wideband digital receiver has been designed in order to select the processed bandwidth of the SKA Mid receiver. The receiver extracts a 2.5 MHz bandwidth form a 14 GHz input bandwidth. The design allows for non-integer ratios between the input and output sampling rates, with a resource usage comparable to that of a conventional decimating digital receiver. Finally, some considerations on quantization of radioastronomic signals are presented. Due to the stochastic nature of the signal, quantization using few data bits is possible. Good accuracies and dynamic range are possible even with 2-3 bits, but the nonlinearity in the correlation process must be corrected in post-processing. With at least 6 bits it is possible to have a very linear response of the instrument, with nonlinear terms below 80 dB, providing the signal amplitude is kept within bounds.

A Modified Subpulse SAR Processing Procedure Based on the Range-Doppler Algorithm for Synthetic Wideband Waveforms

PubMed Central

Lim, Byoung-Gyun; Woo, Jea-Choon; Lee, Hee-Young; Kim, Young-Soo

2008-01-01

Synthetic wideband waveforms (SWW) combine a stepped frequency CW waveform and a chirp signal waveform to achieve high range resolution without requiring a large bandwidth or the consequent very high sampling rate. If an efficient algorithm like the range-Doppler algorithm (RDA) is used to acquire the SAR images for synthetic wideband signals, errors occur due to approximations, so the images may not show the best possible result. This paper proposes a modified subpulse SAR processing algorithm for synthetic wideband signals which is based on RDA. An experiment with an automobile-based SAR system showed that the proposed algorithm is quite accurate with a considerable improvement in resolution and quality of the obtained SAR image. PMID:27873984

Phytometric intelligence sensors

NASA Technical Reports Server (NTRS)

Seelig, Hans-Dieter (Inventor); Stoner, II, Richard J. (Inventor); Hoehn, Alexander (Inventor); Adams, III, William Walter (Inventor)

2010-01-01

Methods and apparatus for determining when plants require watering, and methods of attending to the watering of plants including signaling the grower that the plants are in need of hydration are provided. The novel methods include real-time measurement of plant metabolics and phytometric physiology changes of intrinsic physical or behavioral traits within the plant such as determining physiological flux measurement of enzyme flux due to environmental changes such as the wind and drought stress, soil and plant mineral deficiencies, or the interaction with a bio-control for organic disease control including, cell movement, signal transduction, internal chemical processes and external environmental processes including when plants require watering, and methods of attending to the watering of plants including signaling the grower that the plants are in need of hydration.

HERMA-Heartbeat Microwave Authentication

NASA Technical Reports Server (NTRS)

Haque, Salman-ul Mohammed (Inventor); Chow, Edward (Inventor); McKee, Michael Ray (Inventor); Tkacenko, Andre (Inventor); Lux, James Paul (Inventor)

2018-01-01

Systems and methods for identifying and/or authenticating individuals utilizing microwave sensing modules are disclosed. A HEaRtbeat Microwave Authentication (HERMA) system can enable the active identification and/or authentication of a user by analyzing reflected RF signals that contain a person's unique characteristics related to their heartbeats. An illumination signal is transmitted towards a person where a reflected signal captures the motion of the skin and tissue (i.e. displacement) due to the person's heartbeats. The HERMA system can utilize existing transmitters in a mobile device (e.g. Wi-Fi, Bluetooth, Cellphone signals) as the illumination source with at least one external receive antenna. The received reflected signals can be pre-processed and analyzed to identify and/or authenticate a user.

Novel approach for low-cost muzzle flash detection system

NASA Astrophysics Data System (ADS)

Voskoboinik, Asher

2008-04-01

A low-cost muzzle flash detection based on CMOS sensor technology is proposed. This low-cost technology makes it possible to detect various transient events with characteristic times between dozens of microseconds up to dozens of milliseconds while sophisticated algorithms successfully separate them from false alarms by utilizing differences in geometrical characteristics and/or temporal signatures. The proposed system consists of off-the-shelf smart CMOS cameras with built-in signal and image processing capabilities for pre-processing together with allocated memory for storing a buffer of images for further post-processing. Such a sensor does not require sending giant amounts of raw data to a real-time processing unit but provides all calculations in-situ where processing results are the output of the sensor. This patented CMOS muzzle flash detection concept exhibits high-performance detection capability with very low false-alarm rates. It was found that most false-alarms due to sun glints are from sources at distances of 500-700 meters from the sensor and can be distinguished by time examination techniques from muzzle flash signals. This will enable to eliminate up to 80% of falsealarms due to sun specular reflections in the battle field. Additional effort to distinguish sun glints from suspected muzzle flash signal is made by optimization of the spectral band in Near-IR region. The proposed system can be used for muzzle detection of small arms, missiles and rockets and other military applications.

Dye bias correction in dual-labeled cDNA microarray gene expression measurements.

PubMed Central

Rosenzweig, Barry A; Pine, P Scott; Domon, Olen E; Morris, Suzanne M; Chen, James J; Sistare, Frank D

2004-01-01

A significant limitation to the analytical accuracy and precision of dual-labeled spotted cDNA microarrays is the signal error due to dye bias. Transcript-dependent dye bias may be due to gene-specific differences of incorporation of two distinctly different chemical dyes and the resultant differential hybridization efficiencies of these two chemically different targets for the same probe. Several approaches were used to assess and minimize the effects of dye bias on fluorescent hybridization signals and maximize the experimental design efficiency of a cell culture experiment. Dye bias was measured at the individual transcript level within each batch of simultaneously processed arrays by replicate dual-labeled split-control sample hybridizations and accounted for a significant component of fluorescent signal differences. This transcript-dependent dye bias alone could introduce unacceptably high numbers of both false-positive and false-negative signals. We found that within a given set of concurrently processed hybridizations, the bias is remarkably consistent and therefore measurable and correctable. The additional microarrays and reagents required for paired technical replicate dye-swap corrections commonly performed to control for dye bias could be costly to end users. Incorporating split-control microarrays within a set of concurrently processed hybridizations to specifically measure dye bias can eliminate the need for technical dye swap replicates and reduce microarray and reagent costs while maintaining experimental accuracy and technical precision. These data support a practical and more efficient experimental design to measure and mathematically correct for dye bias. PMID:15033598

Adaptive frequency-difference matched field processing for high frequency source localization in a noisy shallow ocean.

PubMed

Worthmann, Brian M; Song, H C; Dowling, David R

2017-01-01

Remote source localization in the shallow ocean at frequencies significantly above 1 kHz is virtually impossible for conventional array signal processing techniques due to environmental mismatch. A recently proposed technique called frequency-difference matched field processing (Δf-MFP) [Worthmann, Song, and Dowling (2015). J. Acoust. Soc. Am. 138(6), 3549-3562] overcomes imperfect environmental knowledge by shifting the signal processing to frequencies below the signal's band through the use of a quadratic product of frequency-domain signal amplitudes called the autoproduct. This paper extends these prior Δf-MFP results to various adaptive MFP processors found in the literature, with particular emphasis on minimum variance distortionless response, multiple constraint method, multiple signal classification, and matched mode processing at signal-to-noise ratios (SNRs) from -20 to +20 dB. Using measurements from the 2011 Kauai Acoustic Communications Multiple University Research Initiative experiment, the localization performance of these techniques is analyzed and compared to Bartlett Δf-MFP. The results show that a source broadcasting a frequency sweep from 11.2 to 26.2 kHz through a 106 -m-deep sound channel over a distance of 3 km and recorded on a 16 element sparse vertical array can be localized using Δf-MFP techniques within average range and depth errors of 200 and 10 m, respectively, at SNRs down to 0 dB.

Distributed processing for features improvement in real-time portable medical devices.

PubMed

Mercado, Erwin John Saavedra

2008-01-01

Portable biomedical devices are being developed and incorporated in daily life. Nevertheless, their standalone capacity is diminished due to the lack of processing power required to face such duties as for example, signal artifacts robustness in EKG monitor devices. The following paper presents a multiprocessor architecture made from simple microcontrollers to provide an increase in processing performance, power consumption efficiency and lower cost.

Processing of pulse oximeter signals using adaptive filtering and autocorrelation to isolate perfusion and oxygenation components

NASA Astrophysics Data System (ADS)

Ibey, Bennett; Subramanian, Hariharan; Ericson, Nance; Xu, Weijian; Wilson, Mark; Cote, Gerard L.

2005-03-01

A blood perfusion and oxygenation sensor has been developed for in situ monitoring of transplanted organs. In processing in situ data, motion artifacts due to increased perfusion can create invalid oxygenation saturation values. In order to remove the unwanted artifacts from the pulsatile signal, adaptive filtering was employed using a third wavelength source centered at 810nm as a reference signal. The 810 nm source resides approximately at the isosbestic point in the hemoglobin absorption curve where the absorbance of light is nearly equal for oxygenated and deoxygenated hemoglobin. Using an autocorrelation based algorithm oxygenation saturation values can be obtained without the need for large sampling data sets allowing for near real-time processing. This technique has been shown to be more reliable than traditional techniques and proven to adequately improve the measurement of oxygenation values in varying perfusion states.

Characteristics of High-Resolution Hemoglobin Measurement Microchip Integrated with Signal Processing Circuit

NASA Astrophysics Data System (ADS)

Noda, Toshihiko; Takao, Hidekuni; Ashiki, Mitsuaki; Ebi, Hiroyuki; Sawada, Kazuaki; Ishida, Makoto

2004-04-01

In this study, a microchip for measurement of hemoglobin in human blood has been proposed, fabricated and evaluated. The measurement principle of hemoglobin is based on the “cyanmethemoglobin method” that calculates the cyanmethemoglobin concentration by absorption photometry. A glass/silicon/silicon structure was used for the microchip. The middle silicon layer includes flow channels, and 45° mirrors formed at each end of the flow channels. Photodiodes and metal oxide semiconductor (MOS) integrated circuits were fabricated on the bottom silicon layer. The performance of the microchip for hemoglobin measurement was evaluated using a solution of red food color instead of a real blood sample. The fabricated microchip exhibited a similar performance to a nonminiaturized absorption cell which has the same optical path length. Signal processing output varied with solution concentration from 5.32 V to 5.55 V with very high stability due to differential signal processing.

Grey signal processing and data reconstruction in the non-diffracting beam triangulation measurement system

NASA Astrophysics Data System (ADS)

Meng, Hao; Wang, Zhongyu; Fu, Jihua

2008-12-01

The non-diffracting beam triangulation measurement system possesses the advantages of longer measurement range, higher theoretical measurement accuracy and higher resolution over the traditional laser triangulation measurement system. Unfortunately the measurement accuracy of the system is greatly degraded due to the speckle noise, the CCD photoelectric noise and the background light noise in practical applications. Hence, some effective signal processing methods must be applied to improve the measurement accuracy. In this paper a novel effective method for removing the noises in the non-diffracting beam triangulation measurement system is proposed. In the method the grey system theory is used to process and reconstruct the measurement signal. Through implementing the grey dynamic filtering based on the dynamic GM(1,1), the noises can be effectively removed from the primary measurement data and the measurement accuracy of the system can be improved as a result.

Background Noise Reduction Using Adaptive Noise Cancellation Determined by the Cross-Correlation

NASA Technical Reports Server (NTRS)

Spalt, Taylor B.; Brooks, Thomas F.; Fuller, Christopher R.

2012-01-01

Background noise due to flow in wind tunnels contaminates desired data by decreasing the Signal-to-Noise Ratio. The use of Adaptive Noise Cancellation to remove background noise at measurement microphones is compromised when the reference sensor measures both background and desired noise. The technique proposed modifies the classical processing configuration based on the cross-correlation between the reference and primary microphone. Background noise attenuation is achieved using a cross-correlation sample width that encompasses only the background noise and a matched delay for the adaptive processing. A present limitation of the method is that a minimum time delay between the background noise and desired signal must exist in order for the correlated parts of the desired signal to be separated from the background noise in the crosscorrelation. A simulation yields primary signal recovery which can be predicted from the coherence of the background noise between the channels. Results are compared with two existing methods.

[A modified speech enhancement algorithm for electronic cochlear implant and its digital signal processing realization].

PubMed

Wang, Yulin; Tian, Xuelong

2014-08-01

In order to improve the speech quality and auditory perceptiveness of electronic cochlear implant under strong noise background, a speech enhancement system used for electronic cochlear implant front-end was constructed. Taking digital signal processing (DSP) as the core, the system combines its multi-channel buffered serial port (McBSP) data transmission channel with extended audio interface chip TLV320AIC10, so speech signal acquisition and output with high speed are realized. Meanwhile, due to the traditional speech enhancement method which has the problems as bad adaptability, slow convergence speed and big steady-state error, versiera function and de-correlation principle were used to improve the existing adaptive filtering algorithm, which effectively enhanced the quality of voice communications. Test results verified the stability of the system and the de-noising performance of the algorithm, and it also proved that they could provide clearer speech signals for the deaf or tinnitus patients.

ECG Based Heart Arrhythmia Detection Using Wavelet Coherence and Bat Algorithm

NASA Astrophysics Data System (ADS)

Kora, Padmavathi; Sri Rama Krishna, K.

2016-12-01

Atrial fibrillation (AF) is a type of heart abnormality, during the AF electrical discharges in the atrium are rapid, results in abnormal heart beat. The morphology of ECG changes due to the abnormalities in the heart. This paper consists of three major steps for the detection of heart diseases: signal pre-processing, feature extraction and classification. Feature extraction is the key process in detecting the heart abnormality. Most of the ECG detection systems depend on the time domain features for cardiac signal classification. In this paper we proposed a wavelet coherence (WTC) technique for ECG signal analysis. The WTC calculates the similarity between two waveforms in frequency domain. Parameters extracted from WTC function is used as the features of the ECG signal. These features are optimized using Bat algorithm. The Levenberg Marquardt neural network classifier is used to classify the optimized features. The performance of the classifier can be improved with the optimized features.

Variable threshold method for ECG R-peak detection.

PubMed

Kew, Hsein-Ping; Jeong, Do-Un

2011-10-01

In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.

A dynamic multi-channel speech enhancement system for distributed microphones in a car environment

NASA Astrophysics Data System (ADS)

Matheja, Timo; Buck, Markus; Fingscheidt, Tim

2013-12-01

Supporting multiple active speakers in automotive hands-free or speech dialog applications is an interesting issue not least due to comfort reasons. Therefore, a multi-channel system for enhancement of speech signals captured by distributed distant microphones in a car environment is presented. Each of the potential speakers in the car has a dedicated directional microphone close to his position that captures the corresponding speech signal. The aim of the resulting overall system is twofold: On the one hand, a combination of an arbitrary pre-defined subset of speakers' signals can be performed, e.g., to create an output signal in a hands-free telephone conference call for a far-end communication partner. On the other hand, annoying cross-talk components from interfering sound sources occurring in multiple different mixed output signals are to be eliminated, motivated by the possibility of other hands-free applications being active in parallel. The system includes several signal processing stages. A dedicated signal processing block for interfering speaker cancellation attenuates the cross-talk components of undesired speech. Further signal enhancement comprises the reduction of residual cross-talk and background noise. Subsequently, a dynamic signal combination stage merges the processed single-microphone signals to obtain appropriate mixed signals at the system output that may be passed to applications such as telephony or a speech dialog system. Based on signal power ratios between the particular microphone signals, an appropriate speaker activity detection and therewith a robust control mechanism of the whole system is presented. The proposed system may be dynamically configured and has been evaluated for a car setup with four speakers sitting in the car cabin disturbed in various noise conditions.

[Oligonucleotide derivatives in the nucleic acid hybridization analysis. II. Isothermal signal amplification in process of DNA analysis by minisequencing].

PubMed

Dmitrienko, E V; Khomiakova, E A; Pyshnaia; Bragin, A G; Vedernikov, V E; Pyshnyĭ, D V

2010-01-01

The isothermal amplification of reporter signal via limited probe extension (minisequencing) upon hybridization of nucleic acids has been studied. The intensity of reporter signal has been shown to increase due to enzymatic labeling of multiple probes upon consecutive hybridization with one DNA template both in homophase and heterophase assays using various kinds of detection signal: radioisotope label, fluorescent label, and enzyme-linked assay. The kinetic scheme of the process has been proposed and kinetic parameters for each step have been determined. The signal intensity has been shown to correlate with physicochemical characteristics of both complexes: probe/DNA and product/DNA. The maximum intensity has been observed at minimal difference between the thermodynamic stability of these complexes, provided the reaction temperature has been adjusted near their melting temperature values; rising or lowering the reaction temperature reduces the amount of reporting product. The signal intensity has been shown to decrease significantly upon hybridization with the DNA template containing single-nucleotide mismatches. Limited probe extension assay is useful not only for detection of DNA template but also for its quantitative characterization.

Crossbar Nanocomputer Development

DTIC Science & Technology

2012-04-01

their utilization. Areas such as neuromorphic computing, signal processing, arithmetic processing, and crossbar computing are only some of the...due to its intrinsic, network-on- chip flexibility to re-route around defects. Preliminary efforts in crossbar computing have been demonstrated by...they approach their scaling limits [2]. Other applications that memristive devices are suited for include FPGA [3], encryption [4], and neuromorphic

Redox signaling in skeletal muscle: role of aging and exercise.

PubMed

Ji, Li Li

2015-12-01

Skeletal muscle contraction is associated with the production of ROS due to altered O2 distribution and flux in the cell. Despite a highly efficient antioxidant defense, a small surplus of ROS, such as hydrogen peroxide and nitric oxide, may serve as signaling molecules to stimulate cellular adaptation to reach new homeostasis largely due to the activation of redox-sensitive signaling pathways. Recent research has highlighted the important role of NF-κB, MAPK, and peroxisome proliferator-activated receptor-γ coactivator-1α, along with other newly discovered signaling pathways, in some of the most vital biological functions, such as mitochondrial biogenesis, antioxidant defense, inflammation, protein turnover, apoptosis, and autophagy. There is evidence that the inability of the cell to maintain proper redox signaling underlies some basic mechanisms of biological aging, during which inflammatory and catabolic pathways eventually predominate. Physical exercise has been shown to activate various redox signaling pathways that control the adaptation and remodeling process. Although this stimulatory effect of exercise declines with aging, it is not completed abolished. Thus, aged people can still benefit from regular physical activity in the appropriate forms and at proper intensity to preserve muscle function. Copyright © 2015 The American Physiological Society.

Distribution and Variability of Satellite-Derived Signals of Isolated Convection Initiation Events Over Central Eastern China

NASA Astrophysics Data System (ADS)

Huang, Yipeng; Meng, Zhiyong; Li, Jing; Li, Wanbiao; Bai, Lanqiang; Zhang, Murong; Wang, Xi

2017-11-01

This study combined measurements from the Chinese operational geostationary satellite Fengyun-2E (FY-2E) and ground-based weather radars to conduct a statistical survey of isolated convection initiation (CI) over central eastern China (CEC). The convective environment in CEC is modulated by the complex topography and monsoon climate. From May to August 2010, a total of 1,630 isolated CI signals were derived from FY-2E using a semiautomated method. The formation of these satellite-derived CI signals peaks in the early afternoon and occurs with high frequency in areas with remarkable terrain inhomogeneity (e.g., mountain, water, and mountain-water areas). The high signal frequency areas shift from northwest CEC (dry, high altitude) in early summer to southeast CEC (humid, low altitude) in midsummer along with an increasing monthly mean frequency. The satellite-derived CI signals tend to have longer lead times (the time difference between satellite-derived signal formation and radar-based CI) in the late morning and afternoon than in the early morning and night. During the early morning and night, the distinction between cloud top signatures and background terrestrial radiation becomes less apparent, resulting in delayed identification of the signals and thus short and even negative lead times. A decline in the lead time is observed from May to August, likely due to the increasing cloud growth rate and warm-rain processes. Results show increasing lead times with increasing landscape elevation, likely due to more warm-rain processes over the coastal sea and plain, along with a decreasing cloud growth rate from hill and mountain to the plateau.

Development of signal processing system of avalanche photo diode for space observations by Astro-H

NASA Astrophysics Data System (ADS)

Ohno, M.; Goto, K.; Hanabata, Y.; Takahashi, H.; Fukazawa, Y.; Yoshino, M.; Saito, T.; Nakamori, T.; Kataoka, J.; Sasano, M.; Torii, S.; Uchiyama, H.; Nakazawa, K.; Watanabe, S.; Kokubun, M.; Ohta, M.; Sato, T.; Takahashi, T.; Tajima, H.

2013-01-01

Astro-H is the sixth Japanese X-ray space observatory which will be launched in 2014. Two of onboard instruments of Astro-H, Hard X-ray Imager and Soft Gamma-ray Detector are surrounded by many number of large Bismuth Germanate (Bi4Ge3O12; BGO) scintillators. Optimum readout system of scintillation lights from these BGOs are essential to reduce the background signals and achieve high performance for main detectors because most of gamma-rays from out of field-of-view of main detectors or radio-isotopes produced inside them due to activation can be eliminated by anti-coincidence technique using BGO signals. We apply Avalanche Photo Diode (APD) for light sensor of these BGO detectors since their compactness and high quantum efficiency make it easy to design such large number of BGO detector system. For signal processing from APDs, digital filter and other trigger logics on the Field-Programmable Gate Array (FPGA) is used instead of discrete analog circuits due to limitation of circuit implementation area on spacecraft. For efficient observations, we have to achieve as low threshold of anti-coincidence signal as possible by utilizing the digital filtering. In addition, such anti-coincident signals should be sent to the main detector within 5 μs to make it in time to veto the A-D conversion. Considering this requirement and constraint from logic size of FPGA, we adopt two types of filter, 8 delay taps filter with only 2 bit precision coefficient and 16 delay taps filter with 8 bit precision coefficient. The data after former simple filter provides anti-coincidence signal quickly in orbit, and the latter filter is used for detail analysis after the data is down-linked.

Damage localization by statistical evaluation of signal-processed mode shapes

NASA Astrophysics Data System (ADS)

Ulriksen, M. D.; Damkilde, L.

2015-07-01

Due to their inherent, ability to provide structural information on a local level, mode shapes and t.lieir derivatives are utilized extensively for structural damage identification. Typically, more or less advanced mathematical methods are implemented to identify damage-induced discontinuities in the spatial mode shape signals, hereby potentially facilitating damage detection and/or localization. However, by being based on distinguishing damage-induced discontinuities from other signal irregularities, an intrinsic deficiency in these methods is the high sensitivity towards measurement, noise. The present, article introduces a damage localization method which, compared to the conventional mode shape-based methods, has greatly enhanced robustness towards measurement, noise. The method is based on signal processing of spatial mode shapes by means of continuous wavelet, transformation (CWT) and subsequent, application of a generalized discrete Teager-Kaiser energy operator (GDTKEO) to identify damage-induced mode shape discontinuities. In order to evaluate whether the identified discontinuities are in fact, damage-induced, outlier analysis of principal components of the signal-processed mode shapes is conducted on the basis of T2-statistics. The proposed method is demonstrated in the context, of analytical work with a free-vibrating Euler-Bernoulli beam under noisy conditions.

A method of noise reduction in heterodyne interferometric vibration metrology by combining auto-correlation analysis and spectral filtering

NASA Astrophysics Data System (ADS)

Hao, Hongliang; Xiao, Wen; Chen, Zonghui; Ma, Lan; Pan, Feng

2018-01-01

Heterodyne interferometric vibration metrology is a useful technique for dynamic displacement and velocity measurement as it can provide a synchronous full-field output signal. With the advent of cost effective, high-speed real-time signal processing systems and software, processing of the complex signals encountered in interferometry has become more feasible. However, due to the coherent nature of the laser sources, the sequence of heterodyne interferogram are corrupted by a mixture of coherent speckle and incoherent additive noise, which can severely degrade the accuracy of the demodulated signal and the optical display. In this paper, a new heterodyne interferometric demodulation method by combining auto-correlation analysis and spectral filtering is described leading to an expression for the dynamic displacement and velocity of the object under test that is significantly more accurate in both the amplitude and frequency of the vibrating waveform. We present a mathematical model of the signals obtained from interferograms that contain both vibration information of the measured objects and the noise. A simulation of the signal demodulation process is presented and used to investigate the noise from the system and external factors. The experimental results show excellent agreement with measurements from a commercial Laser Doppler Velocimetry (LDV).

Impulse-induced optimum signal amplification in scale-free networks.

PubMed

Martínez, Pedro J; Chacón, Ricardo

2016-04-01

Optimizing information transmission across a network is an essential task for controlling and manipulating generic information-processing systems. Here, we show how topological amplification effects in scale-free networks of signaling devices are optimally enhanced when the impulse transmitted by periodic external signals (time integral over two consecutive zeros) is maximum. This is demonstrated theoretically by means of a star-like network of overdamped bistable systems subjected to generic zero-mean periodic signals and confirmed numerically by simulations of scale-free networks of such systems. Our results show that the enhancer effect of increasing values of the signal's impulse is due to a correlative increase of the energy transmitted by the periodic signals, while it is found to be resonant-like with respect to the topology-induced amplification mechanism.

[A novel biologic electricity signal measurement based on neuron chip].

PubMed

Lei, Yinsheng; Wang, Mingshi; Sun, Tongjing; Zhu, Qiang; Qin, Ran

2006-06-01

Neuron chip is a multiprocessor with three pipeline CPU; its communication protocol and control processor are integrated in effect to carry out the function of communication, control, attemper, I/O, etc. A novel biologic electronic signal measurement network system is composed of intelligent measurement nodes with neuron chip at the core. In this study, the electronic signals such as ECG, EEG, EMG and BOS can be synthetically measured by those intelligent nodes, and some valuable diagnostic messages are found. Wavelet transform is employed in this system to analyze various biologic electronic signals due to its strong time-frequency ability of decomposing signal local character. Better effect is gained. This paper introduces the hardware structure of network and intelligent measurement node, the measurement theory and the signal figure of data acquisition and processing.

Correction of complex nonlinear signal response from a pixel array detector

PubMed Central

van Driel, Tim Brandt; Herrmann, Sven; Carini, Gabriella; Nielsen, Martin Meedom; Lemke, Henrik Till

2015-01-01

The pulsed free-electron laser light sources represent a new challenge to photon area detectors due to the intrinsic spontaneous X-ray photon generation process that makes single-pulse detection necessary. Intensity fluctuations up to 100% between individual pulses lead to high linearity requirements in order to distinguish small signal changes. In real detectors, signal distortions as a function of the intensity distribution on the entire detector can occur. Here a robust method to correct this nonlinear response in an area detector is presented for the case of exposures to similar signals. The method is tested for the case of diffuse scattering from liquids where relevant sub-1% signal changes appear on the same order as artifacts induced by the detector electronics. PMID:25931072

Correction of complex nonlinear signal response from a pixel array detector.

PubMed

van Driel, Tim Brandt; Herrmann, Sven; Carini, Gabriella; Nielsen, Martin Meedom; Lemke, Henrik Till

2015-05-01

The pulsed free-electron laser light sources represent a new challenge to photon area detectors due to the intrinsic spontaneous X-ray photon generation process that makes single-pulse detection necessary. Intensity fluctuations up to 100% between individual pulses lead to high linearity requirements in order to distinguish small signal changes. In real detectors, signal distortions as a function of the intensity distribution on the entire detector can occur. Here a robust method to correct this nonlinear response in an area detector is presented for the case of exposures to similar signals. The method is tested for the case of diffuse scattering from liquids where relevant sub-1% signal changes appear on the same order as artifacts induced by the detector electronics.

Dual Key Speech Encryption Algorithm Based Underdetermined BSS

PubMed Central

Zhao, Huan; Chen, Zuo; Zhang, Xixiang

2014-01-01

When the number of the mixed signals is less than that of the source signals, the underdetermined blind source separation (BSS) is a significant difficult problem. Due to the fact that the great amount data of speech communications and real-time communication has been required, we utilize the intractability of the underdetermined BSS problem to present a dual key speech encryption method. The original speech is mixed with dual key signals which consist of random key signals (one-time pad) generated by secret seed and chaotic signals generated from chaotic system. In the decryption process, approximate calculation is used to recover the original speech signals. The proposed algorithm for speech signals encryption can resist traditional attacks against the encryption system, and owing to approximate calculation, decryption becomes faster and more accurate. It is demonstrated that the proposed method has high level of security and can recover the original signals quickly and efficiently yet maintaining excellent audio quality. PMID:24955430

A comparison of annual vertical crustal displacements from GPS and Gravity Recovery and Climate Experiment (GRACE) over Europe

NASA Astrophysics Data System (ADS)

van Dam, T.; Wahr, J.; LavalléE, David

2007-03-01

We compare approximately 3 years of GPS height residuals (with respect to the International Terrestrial Reference Frame) with predictions of vertical surface displacements derived from the Gravity Recovery and Climate Experiment (GRACE) gravity fields for stations in Europe. An annual signal fit to the residual monthly heights, corrected for atmospheric pressure and barotropic ocean loading effects, should primarily represent surface displacements due to long-wavelength variations in water storage. A comparison of the annual height signal from GPS and GRACE over Europe indicates that at most sites, the annual signals do not agree in amplitude or phase. We find that unlike the annual signal predicted from GRACE, the annual signal in the GPS heights is not coherent over the region, displaying significant variability from site to site. Confidence in the GRACE data and the unlikely possibility of large-amplitude small-scale features in the load field not captured by the GRACE data leads us to conclude that some of the discrepancy between the GPS and GRACE observations is due to technique errors in the GPS data processing. This is evidenced by the fact that the disagreement between GPS and GRACE is largest at coastal sites, where mismodeling of the semidiurnal ocean tidal loading signal can result in spurious annual signals.

Failures of cognitive control or attention? The case of stop-signal deficits in schizophrenia.

PubMed

Matzke, Dora; Hughes, Matthew; Badcock, Johanna C; Michie, Patricia; Heathcote, Andrew

2017-05-01

We used Bayesian cognitive modelling to identify the underlying causes of apparent inhibitory deficits in the stop-signal paradigm. The analysis was applied to stop-signal data reported by Badcock et al. (Psychological Medicine 32: 87-297, 2002) and Hughes et al. (Biological Psychology 89: 220-231, 2012), where schizophrenia patients and control participants made rapid choice responses, but on some trials were signalled to stop their ongoing response. Previous research has assumed an inhibitory deficit in schizophrenia, because estimates of the mean time taken to react to the stop signal are longer in patients than controls. We showed that these longer estimates are partly due to failing to react to the stop signal ("trigger failures") and partly due to a slower initiation of inhibition, implicating a failure of attention rather than a deficit in the inhibitory process itself. Correlations between the probability of trigger failures and event-related potentials reported by Hughes et al. are interpreted as supporting the attentional account of inhibitory deficits. Our results, and those of Matzke et al. (2016), who report that controls also display a substantial although lower trigger-failure rate, indicate that attentional factors need to be taken into account when interpreting results from the stop-signal paradigm.

Effect of efferent activation on binaural frequency selectivity.

PubMed

Verhey, Jesko L; Kordus, Monika; Drga, Vit; Yasin, Ifat

2017-07-01

Binaural notched-noise experiments indicate a reduced frequency selectivity of the binaural system compared to monaural processing. The present study investigates how auditory efferent activation (via the medial olivocochlear system) affects binaural frequency selectivity in normal-hearing listeners. Thresholds were measured for a 1-kHz signal embedded in a diotic notched-noise masker for various notch widths. The signal was either presented in phase (diotic) or in antiphase (dichotic), gated with the noise. Stimulus duration was 25 ms, in order to avoid efferent activation due to the masker or the signal. A bandpass-filtered noise precursor was presented prior to the masker and signal stimuli to activate the efferent system. The silent interval between the precursor and the masker-signal complex was 50 ms. For comparison, thresholds for detectability of the masked signal were also measured in a baseline condition without the precursor and, in addition, without the masker. On average, the results of the baseline condition indicate an effectively wider binaural filter, as expected. For both signal phases, the addition of the precursor results in effectively wider filters, which is in agreement with the hypothesis that cochlear gain is reduced due to the presence of the precursor. Copyright © 2017 Elsevier B.V. All rights reserved.

Nonlinear Blind Compensation for Array Signal Processing Application

PubMed Central

Ma, Hong; Jin, Jiang; Zhang, Hua

2018-01-01

Recently, nonlinear blind compensation technique has attracted growing attention in array signal processing application. However, due to the nonlinear distortion stemming from array receiver which consists of multi-channel radio frequency (RF) front-ends, it is too difficult to estimate the parameters of array signal accurately. A novel nonlinear blind compensation algorithm aims at the nonlinearity mitigation of array receiver and its spurious-free dynamic range (SFDR) improvement, which will be more precise to estimate the parameters of target signals such as their two-dimensional directions of arrival (2-D DOAs). Herein, the suggested method is designed as follows: the nonlinear model parameters of any channel of RF front-end are extracted to synchronously compensate the nonlinear distortion of the entire receiver. Furthermore, a verification experiment on the array signal from a uniform circular array (UCA) is adopted to testify the validity of our approach. The real-world experimental results show that the SFDR of the receiver is enhanced, leading to a significant improvement of the 2-D DOAs estimation performance for weak target signals. And these results demonstrate that our nonlinear blind compensation algorithm is effective to estimate the parameters of weak array signal in concomitance with strong jammers. PMID:29690571

[INVITED] Evaluation of process observation features for laser metal welding

NASA Astrophysics Data System (ADS)

Tenner, Felix; Klämpfl, Florian; Nagulin, Konstantin Yu.; Schmidt, Michael

2016-06-01

In the present study we show how fast the fluid dynamics change when changing the laser power for different feed rates during laser metal welding. By the use of two high-speed cameras and a data acquisition system we conclude how fast we have to image the process to measure the fluid dynamics with a very high certainty. Our experiments show that not all process features which can be measured during laser welding do represent the process behavior similarly well. Despite the good visibility of the vapor plume the monitoring of its movement is less suitable as an input signal for a closed-loop control. The features measured inside the keyhole show a good correlation with changes of process parameters. Due to its low noise, the area of the keyhole opening is well suited as an input signal for a closed-loop control of the process.

Electroencephalographic compression based on modulated filter banks and wavelet transform.

PubMed

Bazán-Prieto, Carlos; Cárdenas-Barrera, Julián; Blanco-Velasco, Manuel; Cruz-Roldán, Fernando

2011-01-01

Due to the large volume of information generated in an electroencephalographic (EEG) study, compression is needed for storage, processing or transmission for analysis. In this paper we evaluate and compare two lossy compression techniques applied to EEG signals. It compares the performance of compression schemes with decomposition by filter banks or wavelet Packets transformation, seeking the best value for compression, best quality and more efficient real time implementation. Due to specific properties of EEG signals, we propose a quantization stage adapted to the dynamic range of each band, looking for higher quality. The results show that the compressor with filter bank performs better than transform methods. Quantization adapted to the dynamic range significantly enhances the quality.

ON THE RADIO DETECTION OF MULTIPLE-EXOMOON SYSTEMS DUE TO PLASMA TORUS SHARING

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noyola, J. P.; Satyal, S.; Musielak, Z. E., E-mail: jpnoyola@uta.edu, E-mail: ssatyal@uta.edu, E-mail: zmusielak@uta.edu

2016-04-20

The idea of single exomoon detection due to the radio emissions caused by its interaction with the host exoplanet is extended to multiple-exomoon systems. The characteristic radio emissions are made possible in part by plasma from the exomoon’s own ionosphere. In this work, it is demonstrated that neighboring exomoons and the exoplanetary magnetosphere could also provide enough plasma to generate a detectable signal. In particular, the plasma-torus-sharing phenomenon is found to be particularly well suited to facilitate the radio detection of plasma-deficient exomoons. The efficiency of this process is evaluated, and the predicted power and frequency of the resulting radiomore » signals are presented.« less

Computational problems and signal processing in SETI

NASA Technical Reports Server (NTRS)

Deans, Stanley R.; Cullers, D. K.; Stauduhar, Richard

1991-01-01

The Search for Extraterrestrial Intelligence (SETI), currently being planned at NASA, will require that an enormous amount of data (on the order of 10 exp 11 distinct signal paths for a typical observation) be analyzed in real time by special-purpose hardware. Even though the SETI system design is not based on maximum entropy and Bayesian methods (partly due to the real-time processing constraint), it is expected that enough data will be saved to be able to apply these and other methods off line where computational complexity is not an overriding issue. Interesting computational problems that relate directly to the system design for processing such an enormous amount of data have emerged. Some of these problems are discussed, along with the current status on their solution.

Analysis of radiometric signal in sedimentating suspension flow in open channel

NASA Astrophysics Data System (ADS)

Zych, Marcin; Hanus, Robert; Petryka, Leszek; Świsulski, Dariusz; Doktor, Marek; Mastej, Wojciech

2015-05-01

The article discusses issues related to the estimation of the sedimentating solid particles average flow velocity in an open channel using radiometric methods. Due to the composition of the compound, which formed water and diatomite, received data have a very weak signal to noise ratio. In the process analysis the known determining of the solid phase transportation time delay the classical cross-correlation function is the most reliable method. The use of advanced frequency analysis based on mutual spectral density function and wavelet transform of recorded signals allows a reduction of the noise contribution.

DOE Office of Scientific and Technical Information (OSTI.GOV)

van Driel, Tim Brandt; Herrmann, Sven; Carini, Gabriella

The pulsed free-electron laser light sources represent a new challenge to photon area detectors due to the intrinsic spontaneous X-ray photon generation process that makes single-pulse detection necessary. Intensity fluctuations up to 100% between individual pulses lead to high linearity requirements in order to distinguish small signal changes. In real detectors, signal distortions as a function of the intensity distribution on the entire detector can occur. Here a robust method to correct this nonlinear response in an area detector is presented for the case of exposures to similar signals. The method is tested for the case of diffuse scattering frommore » liquids where relevant sub-1% signal changes appear on the same order as artifacts induced by the detector electronics.« less

TMSEEG: A MATLAB-Based Graphical User Interface for Processing Electrophysiological Signals during Transcranial Magnetic Stimulation.

PubMed

Atluri, Sravya; Frehlich, Matthew; Mei, Ye; Garcia Dominguez, Luis; Rogasch, Nigel C; Wong, Willy; Daskalakis, Zafiris J; Farzan, Faranak

2016-01-01

Concurrent recording of electroencephalography (EEG) during transcranial magnetic stimulation (TMS) is an emerging and powerful tool for studying brain health and function. Despite a growing interest in adaptation of TMS-EEG across neuroscience disciplines, its widespread utility is limited by signal processing challenges. These challenges arise due to the nature of TMS and the sensitivity of EEG to artifacts that often mask TMS-evoked potentials (TEP)s. With an increase in the complexity of data processing methods and a growing interest in multi-site data integration, analysis of TMS-EEG data requires the development of a standardized method to recover TEPs from various sources of artifacts. This article introduces TMSEEG, an open-source MATLAB application comprised of multiple algorithms organized to facilitate a step-by-step procedure for TMS-EEG signal processing. Using a modular design and interactive graphical user interface (GUI), this toolbox aims to streamline TMS-EEG signal processing for both novice and experienced users. Specifically, TMSEEG provides: (i) targeted removal of TMS-induced and general EEG artifacts; (ii) a step-by-step modular workflow with flexibility to modify existing algorithms and add customized algorithms; (iii) a comprehensive display and quantification of artifacts; (iv) quality control check points with visual feedback of TEPs throughout the data processing workflow; and (v) capability to label and store a database of artifacts. In addition to these features, the software architecture of TMSEEG ensures minimal user effort in initial setup and configuration of parameters for each processing step. This is partly accomplished through a close integration with EEGLAB, a widely used open-source toolbox for EEG signal processing. In this article, we introduce TMSEEG, validate its features and demonstrate its application in extracting TEPs across several single- and multi-pulse TMS protocols. As the first open-source GUI-based pipeline for TMS-EEG signal processing, this toolbox intends to promote the widespread utility and standardization of an emerging technology in brain research.

TMSEEG: A MATLAB-Based Graphical User Interface for Processing Electrophysiological Signals during Transcranial Magnetic Stimulation

PubMed Central

Atluri, Sravya; Frehlich, Matthew; Mei, Ye; Garcia Dominguez, Luis; Rogasch, Nigel C.; Wong, Willy; Daskalakis, Zafiris J.; Farzan, Faranak

2016-01-01

Concurrent recording of electroencephalography (EEG) during transcranial magnetic stimulation (TMS) is an emerging and powerful tool for studying brain health and function. Despite a growing interest in adaptation of TMS-EEG across neuroscience disciplines, its widespread utility is limited by signal processing challenges. These challenges arise due to the nature of TMS and the sensitivity of EEG to artifacts that often mask TMS-evoked potentials (TEP)s. With an increase in the complexity of data processing methods and a growing interest in multi-site data integration, analysis of TMS-EEG data requires the development of a standardized method to recover TEPs from various sources of artifacts. This article introduces TMSEEG, an open-source MATLAB application comprised of multiple algorithms organized to facilitate a step-by-step procedure for TMS-EEG signal processing. Using a modular design and interactive graphical user interface (GUI), this toolbox aims to streamline TMS-EEG signal processing for both novice and experienced users. Specifically, TMSEEG provides: (i) targeted removal of TMS-induced and general EEG artifacts; (ii) a step-by-step modular workflow with flexibility to modify existing algorithms and add customized algorithms; (iii) a comprehensive display and quantification of artifacts; (iv) quality control check points with visual feedback of TEPs throughout the data processing workflow; and (v) capability to label and store a database of artifacts. In addition to these features, the software architecture of TMSEEG ensures minimal user effort in initial setup and configuration of parameters for each processing step. This is partly accomplished through a close integration with EEGLAB, a widely used open-source toolbox for EEG signal processing. In this article, we introduce TMSEEG, validate its features and demonstrate its application in extracting TEPs across several single- and multi-pulse TMS protocols. As the first open-source GUI-based pipeline for TMS-EEG signal processing, this toolbox intends to promote the widespread utility and standardization of an emerging technology in brain research. PMID:27774054

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

NASA Technical Reports Server (NTRS)

Jong, Jen-Yi

1997-01-01

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

Acoustic signal recovery by thermal demodulation

NASA Astrophysics Data System (ADS)

Boullosa, R. R.; Santillán, Arturo O.

2006-10-01

One operating mode of recently developed thermoacoustic transducers is as an audio speaker that uses an input superimposed on a direct current; as a result, the audio signal occurs at the same frequency as the input signal. To extend the potential applications of these kinds of sources, the authors propose an alternative driving mode in which a simple thermoacoustic device, consisting of a metal film over a substrate and a heat sink, is excited with a high frequency sinusoid that is amplitude modulated by a lower frequency signal. They show that the modulating signal is recovered in the radiated waves due to a mechanism that is inherent to this type of thermoacoustic process. If the frequency of the carrier is higher than 30kHz and any modulating signal (the one of interest) is in the audio frequency range, only this signal will be heard. Thus, the thermoacoustic device operates as an audio-band, self-demodulating speaker.

Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures

NASA Astrophysics Data System (ADS)

Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany

2016-07-01

Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.

An ultra low power ECG signal processor design for cardiovascular disease detection.

PubMed

Jain, Sanjeev Kumar; Bhaumik, Basabi

2015-08-01

This paper presents an ultra low power ASIC design based on a new cardiovascular disease diagnostic algorithm. This new algorithm based on forward search is designed for real time ECG signal processing. The algorithm is evaluated for Physionet PTB database from the point of view of cardiovascular disease diagnosis. The failed detection rate of QRS complex peak detection of our algorithm ranges from 0.07% to 0.26% for multi lead ECG signal. The ASIC is designed using 130-nm CMOS low leakage process technology. The area of ASIC is 1.21 mm(2). This ASIC consumes only 96 nW at an operating frequency of 1 kHz with a supply voltage of 0.9 V. Due to ultra low power consumption, our proposed ASIC design is most suitable for energy efficient wearable ECG monitoring devices.

SLAP, a regulator of immunoreceptor ubiquitination, signaling, and trafficking.

PubMed

Dragone, Leonard L; Shaw, Laura A; Myers, Margaret D; Weiss, Arthur

2009-11-01

Src-like adapter proteins (SLAP and SLAP-2) constitute a family of proteins that are expressed in a variety of cell types but are studied most extensively in lymphocytes. They have been shown to associate with proximal components of the T-cell receptor (TCR) and B-cell receptor (BCR) signaling complexes. An interaction of SLAP with c-Cbl leads to the ubiquitination and degradation of phosphorylated components of the TCR- and BCR-signaling complexes. The absence of this process in immature SLAP-deficient T and B cells leads to increased immunoreceptor levels due to decreased intracellular retention and degradation. We propose a model in which SLAP-dependent regulation of immunoreceptor levels allows for finer control of immunoreceptor signaling. Thus, SLAP functions to dampen immunoreceptor signaling, thereby influencing lymphocyte development and repertoire selection.

Correction of complex nonlinear signal response from a pixel array detector

DOE PAGES

van Driel, Tim Brandt; Herrmann, Sven; Carini, Gabriella; ...

2015-04-22

The pulsed free-electron laser light sources represent a new challenge to photon area detectors due to the intrinsic spontaneous X-ray photon generation process that makes single-pulse detection necessary. Intensity fluctuations up to 100% between individual pulses lead to high linearity requirements in order to distinguish small signal changes. In real detectors, signal distortions as a function of the intensity distribution on the entire detector can occur. Here a robust method to correct this nonlinear response in an area detector is presented for the case of exposures to similar signals. The method is tested for the case of diffuse scattering frommore » liquids where relevant sub-1% signal changes appear on the same order as artifacts induced by the detector electronics.« less

Experimental study of the spatially-modulated light detector

NASA Astrophysics Data System (ADS)

Coppée, Daniël; Pan, Wei; Stiens, Johan; Vounckx, Roger; Kuijk, Maarten

1999-03-01

Usually, integrated detectors in CMOS exhibit long recovery times, limiting the detector bandwidth to only a few MHz. This is due to the long absorption length and the slow diffusion speed of photo-generated carriers. Different approaches have been proposed to solve these problems hereby taxing the compatibility with standard CMOS fabrication processing. We present a novel detector for high-speed light detection in standard CMOS. To solve the problem of slow CMOS-detector recovery, the incident light is spatially modulated and the spatially modulated component of the photo-generated carrier distribution is measured. Though only a single light input signal is required, from the detector on, analog signal processing can be achieved fully differentially. Subsequently, expected good PSRR (Power supply rejection ratio) allows integration with digital circuits. Avoiding hybridization eliminates the conventional problems caused by bonding-pad capacitance, bonding-wire inductance. This reduces the associated signal degradation. In addition, the very low detector capacitance, due to the low effectively used detector area and the low area capacitance of the n-well junction, yields high voltage readout of the detector. This facilitates further amplification and conversion to digital signal levels. The detector will be applicable in arrays due to expected low cross talk. The expected fields of operation involve: serial and parallel optical communication receivers (e.g. for WDM), DVD-reading heads with integrated amplifier, etc. First measurements show 200 Mbit/s operation with a detector-responsivity of 0.05 A/W at λ=860 nm and 0.132 A/W at λ=635 nm. The detector has inherently a low capacitance, in this case only 50 fF (for an effective detector area of 70×70 μm 2).

Linear friction weld process monitoring of fixture cassette deformations using empirical mode decomposition

NASA Astrophysics Data System (ADS)

Bakker, O. J.; Gibson, C.; Wilson, P.; Lohse, N.; Popov, A. A.

2015-10-01

Due to its inherent advantages, linear friction welding is a solid-state joining process of increasing importance to the aerospace, automotive, medical and power generation equipment industries. Tangential oscillations and forge stroke during the burn-off phase of the joining process introduce essential dynamic forces, which can also be detrimental to the welding process. Since burn-off is a critical phase in the manufacturing stage, process monitoring is fundamental for quality and stability control purposes. This study aims to improve workholding stability through the analysis of fixture cassette deformations. Methods and procedures for process monitoring are developed and implemented in a fail-or-pass assessment system for fixture cassette deformations during the burn-off phase. Additionally, the de-noised signals are compared to results from previous production runs. The observed deformations as a consequence of the forces acting on the fixture cassette are measured directly during the welding process. Data on the linear friction-welding machine are acquired and de-noised using empirical mode decomposition, before the burn-off phase is extracted. This approach enables a direct, objective comparison of the signal features with trends from previous successful welds. The capacity of the whole process monitoring system is validated and demonstrated through the analysis of a large number of signals obtained from welding experiments.

Digital nonlinearity compensation in high-capacity optical communication systems considering signal spectral broadening effect.

PubMed

Xu, Tianhua; Karanov, Boris; Shevchenko, Nikita A; Lavery, Domaniç; Liga, Gabriele; Killey, Robert I; Bayvel, Polina

2017-10-11

Nyquist-spaced transmission and digital signal processing have proved effective in maximising the spectral efficiency and reach of optical communication systems. In these systems, Kerr nonlinearity determines the performance limits, and leads to spectral broadening of the signals propagating in the fibre. Although digital nonlinearity compensation was validated to be promising for mitigating Kerr nonlinearities, the impact of spectral broadening on nonlinearity compensation has never been quantified. In this paper, the performance of multi-channel digital back-propagation (MC-DBP) for compensating fibre nonlinearities in Nyquist-spaced optical communication systems is investigated, when the effect of signal spectral broadening is considered. It is found that accounting for the spectral broadening effect is crucial for achieving the best performance of DBP in both single-channel and multi-channel communication systems, independent of modulation formats used. For multi-channel systems, the degradation of DBP performance due to neglecting the spectral broadening effect in the compensation is more significant for outer channels. Our work also quantified the minimum bandwidths of optical receivers and signal processing devices to ensure the optimal compensation of deterministic nonlinear distortions.

Vibration sensing in smart machine rotors using internal MEMS accelerometers

NASA Astrophysics Data System (ADS)

Jiménez, Samuel; Cole, Matthew O. T.; Keogh, Patrick S.

2016-09-01

This paper presents a novel topology for enhanced vibration sensing in which wireless MEMS accelerometers embedded within a hollow rotor measure vibration in a synchronously rotating frame of reference. Theoretical relations between rotor-embedded accelerometer signals and the vibration of the rotor in an inertial reference frame are derived. It is thereby shown that functionality as a virtual stator-mounted displacement transducer can be achieved through appropriate signal processing. Experimental tests on a prototype rotor confirm that both magnitude and phase information of synchronous vibration can be measured directly without additional stator-mounted key-phasor sensors. Displacement amplitudes calculated from accelerometer signals will become erroneous at low rotational speeds due to accelerometer zero-g offsets, hence a corrective procedure is introduced. Impact tests are also undertaken to examine the ability of the internal accelerometers to measure transient vibration. A further capability is demonstrated, whereby the accelerometer signals are used to measure rotational speed of the rotor by analysing the signal component due to gravity. The study highlights the extended functionality afforded by internal accelerometers and demonstrates the feasibility of internal sensor topologies, which can provide improved observability of rotor vibration at externally inaccessible rotor locations.

Cycling excitation process: An ultra efficient and quiet signal amplification mechanism in semiconductor

NASA Astrophysics Data System (ADS)

Liu, Yu-Hsin; Yan, Lujiang; Zhang, Alex Ce; Hall, David; Niaz, Iftikhar Ahmad; Zhou, Yuchun; Sham, L. J.; Lo, Yu-Hwa

2015-08-01

Signal amplification, performed by transistor amplifiers with its merit rated by the efficiency and noise characteristics, is ubiquitous in all electronic systems. Because of transistor thermal noise, an intrinsic signal amplification mechanism, impact ionization was sought after to complement the limits of transistor amplifiers. However, due to the high operation voltage (30-200 V typically), low power efficiency, limited scalability, and, above all, rapidly increasing excess noise with amplification factor, impact ionization has been out of favor for most electronic systems except for a few applications such as avalanche photodetectors and single-photon Geiger detectors. Here, we report an internal signal amplification mechanism based on the principle of the phonon-assisted cycling excitation process (CEP). Si devices using this concept show ultrahigh gain, low operation voltage, CMOS compatibility, and, above all, quantum limit noise performance that is 30 times lower than devices using impact ionization. Established on a unique physical effect of attractive properties, CEP-based devices can potentially revolutionize the fields of semiconductor electronics.

Inertial processing of vestibulo-ocular signals

NASA Technical Reports Server (NTRS)

Hess, B. J.; Angelaki, D. E.

1999-01-01

New evidence for a central resolution of gravito-inertial signals has been recently obtained by analyzing the properties of the vestibulo-ocular reflex (VOR) in response to combined lateral translations and roll tilts of the head. It is found that the VOR generates robust compensatory horizontal eye movements independent of whether or not the interaural translatory acceleration component is canceled out by a gravitational acceleration component due to simultaneous roll-tilt. This response property of the VOR depends on functional semicircular canals, suggesting that the brain uses both otolith and semicircular canal signals to estimate head motion relative to inertial space. Vestibular information about dynamic head attitude relative to gravity is the basis for computing head (and body) angular velocity relative to inertial space. Available evidence suggests that the inertial vestibular system controls both head attitude and velocity with respect to a gravity-centered reference frame. The basic computational principles underlying the inertial processing of otolith and semicircular canal afferent signals are outlined.

Acoustic emission evolution during sliding friction of Hadfield steel single crystal

NASA Astrophysics Data System (ADS)

Lychagin, D. V.; Novitskaya, O. S.; Kolubaev, A. V.; Sizova, O. V.

2017-12-01

Friction is a complex dynamic process. Direct observation of processes occurring in the friction zone is impossible due to a small size of a real contact area and, as a consequence, requires various additional methods applicable to monitor a tribological contact state. One of such methods consists in the analysis of acoustic emission data of a tribological contact. The use of acoustic emission entails the problem of interpreting physical sources of signals. In this paper, we analyze the evolution of acoustic emission signal frames in friction of Hadfield steel single crystals. The chosen crystallographic orientation of single crystals enables to identify four stages related to friction development as well as acoustic emission signals inherent in these stages. Acoustic emission signal parameters are studied in more detail by the short-time Fourier transform used to determine the time variation of the median frequency and its power spectrum. The results obtained will facilitate the development of a more precise method to monitor the tribological contact based on the acoustic emission method.

Residual Optically Stimulated Luminescent (OSL) Signals For Al2O3: C and a Readout System With Reproducible Partial Signal Clearance.

PubMed

Abraham, Sara A; Kearfott, Kimberlee J

2018-06-15

Optically stimulated luminescent dosimeters are devices that, when stimulated with light, emit light in proportion to the integrated ionizing radiation dose. The stimulation of optically stimulated luminescent material results in the loss of a small fraction of signal stored within the dosimetric traps. Previous studies have investigated the signal loss due to readout stimulation and the optical annealing of optically stimulated luminescent dosimeters. This study builds on former research by examining the behavior of optically stimulated luminescent signals after annealing, exploring the functionality of a previously developed signal loss model, and comparing uncertainties for dosimeters reused with or without annealing. For a completely annealed dosimeter, the minimum signal level was 56 ± 8 counts, and readings followed a Gaussian distribution. For dosimeters above this signal level, the fractional signal loss due to the reading process has a linear relationship with the calculated signal. At low signal levels (below 20,000 counts) in this optically stimulated luminescent dosimeter system, calculated signal percent errors increase significantly but otherwise are on average 0.72 ± 0.27%, 0.40 ± 0.19%, 0.33 ± 0.12%, and 0.24 ± 0.07% for 30, 75, 150, and 300 readings, respectively. Theoretical calculations of uncertainties showed that annealing before reusing dosimeters allows for dose errors below 1% with as few as 30 readings. Reusing dosimeters multiple times increases the dose errors especially with low numbers of readouts, so theoretically around 300 readings would be necessary to achieve errors around 1% or below in most scenarios. Note that these dose errors do not include the error associated with the signal-to-dose conversion factor.

Signal processing for order 10 PM accuracy displacement metrology in real-world scientific applications

NASA Astrophysics Data System (ADS)

Halverson, Peter G.; Loya, Frank M.

2017-11-01

Projects such as the Space Interferometry Mission (SIM) [1] and Terrestrial Planet Finder (TPF) [2] rely heavily on sub-nanometer accuracy metrology systems to define their optical paths and geometries. The James Web Space Telescope (JWST) is using this metrology in a cryogenic dilatometer for characterizing material properties (thermal expansion, creep) of optical materials. For all these projects, a key issue has been the reliability and stability of the electronics that convert displacement metrology signals into real-time distance determinations. A particular concern is the behavior of the electronics in situations where laser heterodyne signals are weak or noisy and subject to abrupt Doppler shifts due to vibrations or the slewing of motorized optics. A second concern is the long-term (hours to days) stability of the distance measurements under conditions of drifting laser power and ambient temperature. This paper describes heterodyne displacement metrology gauge signal processing methods that achieve satisfactory robustness against low signal strength and spurious signals, and good long-term stability. We have a proven displacement-measuring approach that is useful not only to space-optical projects at JPL, but also to the wider field of distance measurements.

Improved MIMO radar GMTI via cyclic-shift transmission of orthogonal frequency division signals

NASA Astrophysics Data System (ADS)

Li, Fuyou; He, Feng; Dong, Zhen; Wu, Manqing

2018-05-01

Minimum detectable velocity (MDV) and maximum detectable velocity are both important in ground moving target indication (GMTI) systems. Smaller MDV can be achieved by longer baseline via multiple-input multiple-output (MIMO) radar. Maximum detectable velocity is decided by blind velocities associated with carrier frequencies, and blind velocities can be mitigated by orthogonal frequency division signals. However, the scattering echoes from different carrier frequencies are independent, which is not good for improving MDV performance. An improved cyclic-shift transmission is applied in MIMO GMTI system in this paper. MDV performance is improved due to the longer baseline, and maximum detectable velocity performance is improved due to the mitigation of blind velocities via multiple carrier frequencies. The signal model for this mode is established, the principle of mitigating blind velocities with orthogonal frequency division signals is presented; the performance of different MIMO GMTI waveforms is analysed; and the performance of different array configurations is analysed. Simulation results by space-time-frequency adaptive processing proves that our proposed method is a valid way to improve GMTI performance.

Comparative of signal processing techniques for micro-Doppler signature extraction with automotive radar systems

NASA Astrophysics Data System (ADS)

Rodriguez-Hervas, Berta; Maile, Michael; Flores, Benjamin C.

2014-05-01

In recent years, the automotive industry has experienced an evolution toward more powerful driver assistance systems that provide enhanced vehicle safety. These systems typically operate in the optical and microwave regions of the electromagnetic spectrum and have demonstrated high efficiency in collision and risk avoidance. Microwave radar systems are particularly relevant due to their operational robustness under adverse weather or illumination conditions. Our objective is to study different signal processing techniques suitable for extraction of accurate micro-Doppler signatures of slow moving objects in dense urban environments. Selection of the appropriate signal processing technique is crucial for the extraction of accurate micro-Doppler signatures that will lead to better results in a radar classifier system. For this purpose, we perform simulations of typical radar detection responses in common driving situations and conduct the analysis with several signal processing algorithms, including short time Fourier Transform, continuous wavelet or Kernel based analysis methods. We take into account factors such as the relative movement between the host vehicle and the target, and the non-stationary nature of the target's movement. A comparison of results reveals that short time Fourier Transform would be the best approach for detection and tracking purposes, while the continuous wavelet would be the best suited for classification purposes.

Time-resolved EPR study on the photochemical reactions of benzil

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mukai, Masahiro; Yamnauchi, Seigo; Hirota, Noboru

1992-04-16

TREPR and optical studies on the photochemical reactions of benzil in 2-propanol and benzene-TEA conclude that emissive signals are due to the reaction from T{sub n} produced via the S{sub n} pointing right T{sub n} intersystem crossing process. The free-pair radical-pair mechanism can account for the main features of the slow rise component of the chemically induced dynamic electron polarization signal of the ketyl radical in 2-propanol. 27 refs., 10 figs., 2 tabs.

Crustal deformation in southern California using SAR interferometry

USGS Publications Warehouse

Peltzer, G.; Rosen, P.; Rogez, F.; Hudnut, K.

1997-01-01

By combining pairs of ERS-1/2 SAR images of Southern California spanning long time intervals (1-4 years), we were able to measure the rate of slow deformation processes along faults activated during the Landers 1992 earthquake. Interferograms revealed several centimeters of post-seismic rebound in step-overs of the 1992 break, with a characteristic decay rate of -280 days. We interpreted this process as due to pore fluid flow as pore pressure gradients caused by coseismic stress changes dissipate. The data also revealed evidence of after-slip on different sections of the fault. The southern branches of the 1992 break experienced surface creep producing sharp phase cuts hi the interferometric maps. The same approach was used in the Los Angeles basin, which is currently undergoing NS shortening at a rate of ???8 mm/yr. The tectonic signal in imerferograms of the Los Angeles basin is intermingled with signals due to other sources such as ground subsidence caused by oil and water withdrawal.

Developments of FPGA-based digital back-ends for low frequency antenna arrays at Medicina radio telescopes

NASA Astrophysics Data System (ADS)

Naldi, G.; Bartolini, M.; Mattana, A.; Pupillo, G.; Hickish, J.; Foster, G.; Bianchi, G.; Lingua, A.; Monari, J.; Montebugnoli, S.; Perini, F.; Rusticelli, S.; Schiaffino, M.; Virone, G.; Zarb Adami, K.

In radio astronomy Field Programmable Gate Array (FPGA) technology is largely used for the implementation of digital signal processing techniques applied to antenna arrays. This is mainly due to the good trade-off among computing resources, power consumption and cost offered by FPGA chip compared to other technologies like ASIC, GPU and CPU. In the last years several digital backend systems based on such devices have been developed at the Medicina radio astronomical station (INAF-IRA, Bologna, Italy). Instruments like FX correlator, direct imager, beamformer, multi-beam system have been successfully designed and realized on CASPER (Collaboration for Astronomy Signal Processing and Electronics Research, https://casper.berkeley.edu) processing boards. In this paper we present the gained experience in this kind of applications.

All-optical universal logic gates on nonlinear multimode interference coupler using tunable input intensity

NASA Astrophysics Data System (ADS)

Tajaldini, Mehdi; Jafri, Mohd Zubir Mat

2015-04-01

The theory of Nonlinear Modal Propagation Analysis Method (NMPA) have shown significant features of nonlinear multimode interference (MMI) coupler with compact dimension and when launched near the threshold of nonlinearity. Moreover, NMPA have the potential to allow studying the nonlinear MMI based the modal interference to explorer the phenomenon that what happen due to the natural of multimode region. Proposal of all-optical switch based NMPA has approved its capability to achieving the all-optical gates. All-optical gates have attracted increasing attention due to their practical utility in all-optical signal processing networks and systems. Nonlinear multimode interference devices could apply as universal all-optical gates due to significant features that NMPA introduce them. In this Paper, we present a novel Ultra-compact MMI coupler based on NMPA method in low intensity compared to last reports either as a novel design method and potential application for optical NAND, NOR as universal gates on single structure for Boolean logic signal processing devices and optimize their application via studding the contrast ratio between ON and OFF as a function of output width. We have applied NMPA for several applications so that the miniaturization in low nonlinear intensities is their main purpose.

A cloud masking algorithm for EARLINET lidar systems

NASA Astrophysics Data System (ADS)

Binietoglou, Ioannis; Baars, Holger; D'Amico, Giuseppe; Nicolae, Doina

2015-04-01

Cloud masking is an important first step in any aerosol lidar processing chain as most data processing algorithms can only be applied on cloud free observations. Up to now, the selection of a cloud-free time interval for data processing is typically performed manually, and this is one of the outstanding problems for automatic processing of lidar data in networks such as EARLINET. In this contribution we present initial developments of a cloud masking algorithm that permits the selection of the appropriate time intervals for lidar data processing based on uncalibrated lidar signals. The algorithm is based on a signal normalization procedure using the range of observed values of lidar returns, designed to work with different lidar systems with minimal user input. This normalization procedure can be applied to measurement periods of only few hours, even if no suitable cloud-free interval exists, and thus can be used even when only a short period of lidar measurements is available. Clouds are detected based on a combination of criteria including the magnitude of the normalized lidar signal and time-space edge detection performed using the Sobel operator. In this way the algorithm avoids misclassification of strong aerosol layers as clouds. Cloud detection is performed using the highest available time and vertical resolution of the lidar signals, allowing the effective detection of low-level clouds (e.g. cumulus humilis). Special attention is given to suppress false cloud detection due to signal noise that can affect the algorithm's performance, especially during day-time. In this contribution we present the details of algorithm, the effect of lidar characteristics (space-time resolution, available wavelengths, signal-to-noise ratio) to detection performance, and highlight the current strengths and limitations of the algorithm using lidar scenes from different lidar systems in different locations across Europe.

Novel auto-correction method in a fiber-optic distributed-temperature sensor using reflected anti-Stokes Raman scattering.

PubMed

Hwang, Dusun; Yoon, Dong-Jin; Kwon, Il-Bum; Seo, Dae-Cheol; Chung, Youngjoo

2010-05-10

A novel method for auto-correction of fiber optic distributed temperature sensor using anti-Stokes Raman back-scattering and its reflected signal is presented. This method processes two parts of measured signal. One part is the normal back scattered anti-Stokes signal and the other part is the reflected signal which eliminate not only the effect of local losses due to the micro-bending or damages on fiber but also the differential attenuation. Because the beams of the same wavelength are used to cancel out the local variance in transmission medium there is no differential attenuation inherently. The auto correction concept was verified by the bending experiment on different bending points. (c) 2010 Optical Society of America.

Freeze-drying process monitoring using a cold plasma ionization device.

PubMed

Mayeresse, Y; Veillon, R; Sibille, P H; Nomine, C

2007-01-01

A cold plasma ionization device has been designed to monitor freeze-drying processes in situ by monitoring lyophilization chamber moisture content. This plasma device, which consists of a probe that can be mounted directly on the lyophilization chamber, depends upon the ionization of nitrogen and water molecules using a radiofrequency generator and spectrometric signal collection. The study performed on this probe shows that it is steam sterilizable, simple to integrate, reproducible, and sensitive. The limitations include suitable positioning in the lyophilization chamber, calibration, and signal integration. Sensitivity was evaluated in relation to the quantity of vials and the probe positioning, and correlation with existing methods, such as microbalance, was established. These tests verified signal reproducibility through three freeze-drying cycles. Scaling-up studies demonstrated a similar product signature for the same product using pilot-scale and larger-scale equipment. On an industrial scale, the method efficiently monitored the freeze-drying cycle, but in a larger industrial freeze-dryer the signal was slightly modified. This was mainly due to the positioning of the plasma device, in relation to the vapor flow pathway, which is not necessarily homogeneous within the freeze-drying chamber. The plasma tool is a relevant method for monitoring freeze-drying processes and may in the future allow the verification of current thermodynamic freeze-drying models. This plasma technique may ultimately represent a process analytical technology (PAT) approach for the freeze-drying process.

A Real-Time Capable Software-Defined Receiver Using GPU for Adaptive Anti-Jam GPS Sensors

PubMed Central

Seo, Jiwon; Chen, Yu-Hsuan; De Lorenzo, David S.; Lo, Sherman; Enge, Per; Akos, Dennis; Lee, Jiyun

2011-01-01

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities. PMID:22164116

A review of channel selection algorithms for EEG signal processing

NASA Astrophysics Data System (ADS)

Alotaiby, Turky; El-Samie, Fathi E. Abd; Alshebeili, Saleh A.; Ahmad, Ishtiaq

2015-12-01

Digital processing of electroencephalography (EEG) signals has now been popularly used in a wide variety of applications such as seizure detection/prediction, motor imagery classification, mental task classification, emotion classification, sleep state classification, and drug effects diagnosis. With the large number of EEG channels acquired, it has become apparent that efficient channel selection algorithms are needed with varying importance from one application to another. The main purpose of the channel selection process is threefold: (i) to reduce the computational complexity of any processing task performed on EEG signals by selecting the relevant channels and hence extracting the features of major importance, (ii) to reduce the amount of overfitting that may arise due to the utilization of unnecessary channels, for the purpose of improving the performance, and (iii) to reduce the setup time in some applications. Signal processing tools such as time-domain analysis, power spectral estimation, and wavelet transform have been used for feature extraction and hence for channel selection in most of channel selection algorithms. In addition, different evaluation approaches such as filtering, wrapper, embedded, hybrid, and human-based techniques have been widely used for the evaluation of the selected subset of channels. In this paper, we survey the recent developments in the field of EEG channel selection methods along with their applications and classify these methods according to the evaluation approach.

Crosslinking EEG time-frequency decomposition and fMRI in error monitoring.

PubMed

Hoffmann, Sven; Labrenz, Franziska; Themann, Maria; Wascher, Edmund; Beste, Christian

2014-03-01

Recent studies implicate a common response monitoring system, being active during erroneous and correct responses. Converging evidence from time-frequency decompositions of the response-related ERP revealed that evoked theta activity at fronto-central electrode positions differentiates correct from erroneous responses in simple tasks, but also in more complex tasks. However, up to now it is unclear how different electrophysiological parameters of error processing, especially at the level of neural oscillations are related, or predictive for BOLD signal changes reflecting error processing at a functional-neuroanatomical level. The present study aims to provide crosslinks between time domain information, time-frequency information, MRI BOLD signal and behavioral parameters in a task examining error monitoring due to mistakes in a mental rotation task. The results show that BOLD signal changes reflecting error processing on a functional-neuroanatomical level are best predicted by evoked oscillations in the theta frequency band. Although the fMRI results in this study account for an involvement of the anterior cingulate cortex, middle frontal gyrus, and the Insula in error processing, the correlation of evoked oscillations and BOLD signal was restricted to a coupling of evoked theta and anterior cingulate cortex BOLD activity. The current results indicate that although there is a distributed functional-neuroanatomical network mediating error processing, only distinct parts of this network seem to modulate electrophysiological properties of error monitoring.

A real-time capable software-defined receiver using GPU for adaptive anti-jam GPS sensors.

PubMed

Seo, Jiwon; Chen, Yu-Hsuan; De Lorenzo, David S; Lo, Sherman; Enge, Per; Akos, Dennis; Lee, Jiyun

2011-01-01

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities.

Multivariate Analysis of Ladle Vibration

NASA Astrophysics Data System (ADS)

Yenus, Jaefer; Brooks, Geoffrey; Dunn, Michelle

2016-08-01

The homogeneity of composition and uniformity of temperature of the steel melt before it is transferred to the tundish are crucial in making high-quality steel product. The homogenization process is performed by stirring the melt using inert gas in ladles. Continuous monitoring of this process is important to make sure the action of stirring is constant throughout the ladle. Currently, the stirring process is monitored by process operators who largely rely on visual and acoustic phenomena from the ladle. However, due to lack of measurable signals, the accuracy and suitability of this manual monitoring are problematic. The actual flow of argon gas to the ladle may not be same as the flow gage reading due to leakage along the gas line components. As a result, the actual degree of stirring may not be correctly known. Various researchers have used one-dimensional vibration, and sound and image signals measured from the ladle to predict the degree of stirring inside. They developed online sensors which are indeed to monitor the online stirring phenomena. In this investigation, triaxial vibration signals have been measured from a cold water model which is a model of an industrial ladle. Three flow rate ranges and varying bath heights were used to collect vibration signals. The Fast Fourier Transform was applied to the dataset before it has been analyzed using principal component analysis (PCA) and partial least squares (PLS). PCA was used to unveil the structure in the experimental data. PLS was mainly applied to predict the stirring from the vibration response. It was found that for each flow rate range considered in this study, the informative signals reside in different frequency ranges. The first latent variables in these frequency ranges explain more than 95 pct of the variation in the stirring process for the entire single layer and the double layer data collected from the cold model. PLS analysis in these identified frequency ranges demonstrated that the latent variables of the response and predictor variables are highly correlated. The predicted variable has shown linear relationship with the stirring energy and bath recirculation speed. This outcome can improve the predictability of the mixing status in ladle metallurgy and make the online control of the process easier. Industrial testing of this input will follow.

Frequency Domain Analysis of Sensor Data for Event Classification in Real-Time Robot Assisted Deburring

PubMed Central

Pappachan, Bobby K; Caesarendra, Wahyu; Tjahjowidodo, Tegoeh; Wijaya, Tomi

2017-01-01

Process monitoring using indirect methods relies on the usage of sensors. Using sensors to acquire vital process related information also presents itself with the problem of big data management and analysis. Due to uncertainty in the frequency of events occurring, a higher sampling rate is often used in real-time monitoring applications to increase the chances of capturing and understanding all possible events related to the process. Advanced signal processing methods are used to further decipher meaningful information from the acquired data. In this research work, power spectrum density (PSD) of sensor data acquired at sampling rates between 40–51.2 kHz was calculated and the corelation between PSD and completed number of cycles/passes is presented. Here, the progress in number of cycles/passes is the event this research work intends to classify and the algorithm used to compute PSD is Welch’s estimate method. A comparison between Welch’s estimate method and statistical methods is also discussed. A clear co-relation was observed using Welch’s estimate to classify the number of cycles/passes. The paper also succeeds in classifying vibration signal generated by the spindle from the vibration signal acquired during finishing process. PMID:28556809

Intensity enhancement of vibrational sum frequency generation by gap-mode plasmon resonance

NASA Astrophysics Data System (ADS)

Okuno, Masanari; Tokimoto, Taichi; Eguchi, Miharu; Kano, Hideaki; Ishibashi, Taka-aki

2015-10-01

A metal sphere-plane structure consisting of gold nanoparticles, p-methylbenzenethiol and a gold substrate was measured by vibrational sum frequency generation spectroscopy with four excitation wavelengths, 630, 680, 720, and 780 nm. The enhancement factors of Raman signals were estimated to be 250 and 104 for the 532 and 647 nm excitation. Contrastingly, we found that the enhancements of VSFG signals were much smaller, a factor of 5 at maximum. We speculate that the small enhancement factor of VSFG signals is due to the coherent nature of the VSFG process or the extinction of the infrared laser by the gold nanoparticles.

Calcium: The Missing Link in Auxin Action

PubMed Central

Vanneste, Steffen; Friml, Jiří

2013-01-01

Due to their sessile lifestyles, plants need to deal with the limitations and stresses imposed by the changing environment. Plants cope with these by a remarkable developmental flexibility, which is embedded in their strategy to survive. Plants can adjust their size, shape and number of organs, bend according to gravity and light, and regenerate tissues that were damaged, utilizing a coordinating, intercellular signal, the plant hormone, auxin. Another versatile signal is the cation, Ca2+, which is a crucial second messenger for many rapid cellular processes during responses to a wide range of endogenous and environmental signals, such as hormones, light, drought stress and others. Auxin is a good candidate for one of these Ca2+-activating signals. However, the role of auxin-induced Ca2+ signaling is poorly understood. Here, we will provide an overview of possible developmental and physiological roles, as well as mechanisms underlying the interconnection of Ca2+ and auxin signaling. PMID:27137397

Optimized signal detection and analysis methods for in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Wang, Qiyan; Zhou, Quanyu; Yang, Ping; Wang, Xiaoling; Niu, Zhenyu; Suo, Yuanzhen; He, Hao; Gao, Wenyuan; Tang, Shuo; Wei, Xunbin

2017-02-01

Melanoma is known as a malignant tumor of melanocytes, which usually appear in the blood circulation at the metastasis stage of cancer. Thus the detection of circulating melanoma cells is useful for early diagnosis and therapy of cancer. Here we have developed an in vivo photoacoustic flow cytometry (PAFC) based on the photoacoustic effect to detect melanoma cells. However, the raw signals we obtain from the target cells contain noises such as environmental sonic noises and electronic noises. Therefore we apply correlation comparison and feature separation methods to the detection and verification of the in vivo signals. Due to similar shape and structure of cells, the photoacoustic signals usually have similar vibration mode. By analyzing the correlations and the signal features in time domain and frequency domain, we are able to provide a method for separating photoacoustic signals generated by target cells from background noises. The method introduced here has proved to optimize the signal acquisition and signal processing, which can improve the detection accuracy in PAFC.

Measuring the effect of attention on simple visual search.

PubMed

Palmer, J; Ames, C T; Lindsey, D T

1993-02-01

Set-size in visual search may be due to 1 or more of 3 factors: sensory processes such as lateral masking between stimuli, attentional processes limiting the perception of individual stimuli, or attentional processes affecting the decision rules for combining information from multiple stimuli. These possibilities were evaluated in tasks such as searching for a longer line among shorter lines. To evaluate sensory contributions, display set-size effects were compared with cuing conditions that held sensory phenomena constant. Similar effects for the display and cue manipulations suggested that sensory processes contributed little under the conditions of this experiment. To evaluate the contribution of decision processes, the set-size effects were modeled with signal detection theory. In these models, a decision effect alone was sufficient to predict the set-size effects without any attentional limitation due to perception.

Investigating low flow process controls, through complex modelling, in a UK chalk catchment

NASA Astrophysics Data System (ADS)

Lubega Musuuza, Jude; Wagener, Thorsten; Coxon, Gemma; Freer, Jim; Woods, Ross; Howden, Nicholas

2017-04-01

The typical streamflow response of Chalk catchments is dominated by groundwater contributions due the high degree of groundwater recharge through preferential flow pathways. The groundwater store attenuates the precipitation signal, which causes a delay between the corresponding high and low extremes in the precipitation and the stream flow signals. Streamflow responses can therefore be quite out of phase with the precipitation input to a Chalk catchment. Therefore characterising such catchment systems, including modelling approaches, clearly need to reproduce these percolation and groundwater dominated pathways to capture these dominant flow pathways. The simulation of low flow conditions for chalk catchments in numerical models is especially difficult due to the complex interactions between various processes that may not be adequately represented or resolved in the models. Periods of low stream flows are particularly important due to competing water uses in the summer, including agriculture and water supply. In this study we apply and evaluate the physically-based Pennstate Integrated Hydrologic Model (PIHM) to the River Kennet, a sub-catchment of the Thames Basin, to demonstrate how the simulations of a chalk catchment are improved by a physically-based system representation. We also use an ensemble of simulations to investigate the sensitivity of various hydrologic signatures (relevant to low flows and droughts) to the different parameters in the model, thereby inferring the levels of control exerted by the processes that the parameters represent.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Fiber-connected position localization sensor networks

NASA Astrophysics Data System (ADS)

Pan, Shilong; Zhu, Dan; Fu, Jianbin; Yao, Tingfeng

2014-11-01

Position localization has drawn great attention due to its wide applications in radars, sonars, electronic warfare, wireless communications and so on. Photonic approaches to realize position localization can achieve high-resolution, which also provides the possibility to move the signal processing from each sensor node to the central station, thanks to the low loss, immunity to electromagnetic interference (EMI) and broad bandwidth brought by the photonic technologies. In this paper, we present a review on the recent works of position localization based on photonic technologies. A fiber-connected ultra-wideband (UWB) sensor network using optical time-division multiplexing (OTDM) is proposed to realize high-resolution localization and moving the signal processing to the central station. A 3.9-cm high spatial resolution is achieved. A wavelength-division multiplexed (WDM) fiber-connected sensor network is also demonstrated to realize location which is independent of the received signal format.

Smart Microsystems with Photonic Element and Their Applications to Aerospace Platforms

NASA Technical Reports Server (NTRS)

Adamovsky, G.; Lekki, J.; Sutter, J. K.; Sarkisov, S. S.; Curley, M. J.; Martin, C. E.

2000-01-01

The need to make manufacturing, operation, and support of airborne vehicles safer and more efficient forces engineers and scientists to look for lighter, cheaper, more reliable technologies. Light weight, immunity to EMI, fire safety, high bandwidth, and high signal fidelity have already made photonics in general and fiber optics in particular an extremely attractive medium for communication purposes. With the fiber optics serving as a central nervous system of the vehicle, generation, detection, and processing of the signal occurs at the peripherals that include smart structures and devices. Due to their interdisciplinary nature, photonic technologies cover such diverse areas as optical sensors and actuators, embedded and distributed sensors, sensing schemes and architectures, harnesses and connectors, signal processing and algorithms. The paper includes a brief description of work in the photonic area that is going on at NASA, especially at the Glenn Research Center (GRC).

Central Auditory Processing of Temporal and Spectral-Variance Cues in Cochlear Implant Listeners

PubMed Central

Pham, Carol Q.; Bremen, Peter; Shen, Weidong; Yang, Shi-Ming; Middlebrooks, John C.; Zeng, Fan-Gang; Mc Laughlin, Myles

2015-01-01

Cochlear implant (CI) listeners have difficulty understanding speech in complex listening environments. This deficit is thought to be largely due to peripheral encoding problems arising from current spread, which results in wide peripheral filters. In normal hearing (NH) listeners, central processing contributes to segregation of speech from competing sounds. We tested the hypothesis that basic central processing abilities are retained in post-lingually deaf CI listeners, but processing is hampered by degraded input from the periphery. In eight CI listeners, we measured auditory nerve compound action potentials to characterize peripheral filters. Then, we measured psychophysical detection thresholds in the presence of multi-electrode maskers placed either inside (peripheral masking) or outside (central masking) the peripheral filter. This was intended to distinguish peripheral from central contributions to signal detection. Introduction of temporal asynchrony between the signal and masker improved signal detection in both peripheral and central masking conditions for all CI listeners. Randomly varying components of the masker created spectral-variance cues, which seemed to benefit only two out of eight CI listeners. Contrastingly, the spectral-variance cues improved signal detection in all five NH listeners who listened to our CI simulation. Together these results indicate that widened peripheral filters significantly hamper central processing of spectral-variance cues but not of temporal cues in post-lingually deaf CI listeners. As indicated by two CI listeners in our study, however, post-lingually deaf CI listeners may retain some central processing abilities similar to NH listeners. PMID:26176553

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation.

PubMed

Segreto, Tiziana; Caggiano, Alessandra; Karam, Sara; Teti, Roberto

2017-12-12

Nickel-Titanium (Ni-Ti) alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT). The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs) for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions.

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation

PubMed Central

Segreto, Tiziana; Karam, Sara; Teti, Roberto

2017-01-01

Nickel-Titanium (Ni-Ti) alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT). The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs) for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions. PMID:29231864

S-192 analysis: Conventional and special data processing techniques. [Michigan

NASA Technical Reports Server (NTRS)

Nalepka, R. F. (Principal Investigator); Morganstern, J.; Cicone, R.; Sarno, J.; Lambeck, P.; Malila, W.

1975-01-01

The author has identified the following significant results. Multispectral scanner data gathered over test sites in southeast Michigan were analyzed. This analysis showed the data to be somewhat deficient especially in terms of the limited signal range in most SDOs and also in regard to SDO-SDO misregistration. Further analysis showed that the scan line straightening algorithm increased the misregistration of the data. Data were processed using the conic format. The effects of such misregistration on classification accuracy was analyzed via simulation and found to be significant. Results of employing conventional as well as special, unresolved object, processing techniques were disappointing due, at least in part, to the limited signal range and noise content of the data. Application of a second class of special processing techniques, signature extension techniques, yielded better results. Two of the more basic signature extension techniques seemed to be useful in spite of the difficulties.

Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures.

PubMed

Hegazy, Maha A; Lotfy, Hayam M; Mowaka, Shereen; Mohamed, Ekram Hany

2016-07-05

Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations. Copyright © 2016 Elsevier B.V. All rights reserved.

Toward a model for lexical access based on acoustic landmarks and distinctive features

NASA Astrophysics Data System (ADS)

Stevens, Kenneth N.

2002-04-01

This article describes a model in which the acoustic speech signal is processed to yield a discrete representation of the speech stream in terms of a sequence of segments, each of which is described by a set (or bundle) of binary distinctive features. These distinctive features specify the phonemic contrasts that are used in the language, such that a change in the value of a feature can potentially generate a new word. This model is a part of a more general model that derives a word sequence from this feature representation, the words being represented in a lexicon by sequences of feature bundles. The processing of the signal proceeds in three steps: (1) Detection of peaks, valleys, and discontinuities in particular frequency ranges of the signal leads to identification of acoustic landmarks. The type of landmark provides evidence for a subset of distinctive features called articulator-free features (e.g., [vowel], [consonant], [continuant]). (2) Acoustic parameters are derived from the signal near the landmarks to provide evidence for the actions of particular articulators, and acoustic cues are extracted by sampling selected attributes of these parameters in these regions. The selection of cues that are extracted depends on the type of landmark and on the environment in which it occurs. (3) The cues obtained in step (2) are combined, taking context into account, to provide estimates of ``articulator-bound'' features associated with each landmark (e.g., [lips], [high], [nasal]). These articulator-bound features, combined with the articulator-free features in (1), constitute the sequence of feature bundles that forms the output of the model. Examples of cues that are used, and justification for this selection, are given, as well as examples of the process of inferring the underlying features for a segment when there is variability in the signal due to enhancement gestures (recruited by a speaker to make a contrast more salient) or due to overlap of gestures from neighboring segments.

The role of nutraceuticals in the regulation of Wnt and Hedgehog signaling in cancer

PubMed Central

Li, Yiwei; Wang, Zhiwei; Kong, Dejuan

2010-01-01

Multiple cellular signaling pathways have been involved in the processes of cancer cell invasion and metastasis. Among many signaling pathways, Wnt and Hedgehog (Hh) signaling pathways are critically involved in embryonic development, in the biology of cancer stem cells (CSCs) and in the acquisition of epithelial to mesenchymal transition (EMT), and thus this article will remain focused on Wnt and Hh signaling. Since CSCs and EMT are also known to be responsible for cancer cell invasion and metastasis, the Wnt and Hedgehog signaling pathways are also intimately associated with cancer invasion and metastasis. Emerging evidence suggests the beneficial role of chemopreventive agents commonly known as nutraceutical in cancer. Among many such agents, soy isoflavones, curcumin, green tea polyphenols, 3,3′-diindolylmethane, resveratrol, lycopene, vitamin D, etc. have been found to prevent, reverse, or delay the carcinogenic process. Interestingly, these agents have also shown to prevent or delay the progression of cancer, which could in part be due to their ability to attack CSCs or EMT-type cells by attenuating the Wnt and Hedgehog signaling pathways. In this review, we summarize the current state of our knowledge on the role of Wnt and Hedgehog signaling pathways, and their targeted inactivation by chemopreventive agents (nutraceuticals) for the prevention of tumor progression and/or treatment of human malignancies. PMID:20711635

Moment-Based Physical Models of Broadband Clutter due to Aggregations of Fish

DTIC Science & Technology

2013-09-30

statistical models for signal-processing algorithm development. These in turn will help to develop a capability to statistically forecast the impact of...aggregations of fish based on higher-order statistical measures describable in terms of physical and system parameters. Environmentally , these models...processing. In this experiment, we had good ground truth on (1) and (2), and had control over (3) and (4) except for environmentally -imposed restrictions

High-resolution (>5 800 time-bandwidth product) shear mode TeO2 deflector

NASA Astrophysics Data System (ADS)

Soos, Jolanta I.; Caviris, Nicholas P.; Phuvan, Sonlinh

1992-12-01

Acousto-optic deflectors play an important role in optical signal processing systems due to their real time processing capabilities, as well as their conversion capabilities of a function of time to a function of space and time. In this work Brimrose investigated the design and fabrication of state-of-the-art, very large time-bandwidth acousto-optic devices from TeO2 single crystals.

Global Infrasound Association Based on Probabilistic Clutter Categorization

NASA Astrophysics Data System (ADS)

Arora, Nimar; Mialle, Pierrick

2016-04-01

The IDC advances its methods and continuously improves its automatic system for the infrasound technology. The IDC focuses on enhancing the automatic system for the identification of valid signals and the optimization of the network detection threshold by identifying ways to refine signal characterization methodology and association criteria. An objective of this study is to reduce the number of associated infrasound arrivals that are rejected from the automatic bulletins when generating the reviewed event bulletins. Indeed, a considerable number of signal detections are due to local clutter sources such as microbaroms, waterfalls, dams, gas flares, surf (ocean breaking waves) etc. These sources are either too diffuse or too local to form events. Worse still, the repetitive nature of this clutter leads to a large number of false event hypotheses due to the random matching of clutter at multiple stations. Previous studies, for example [1], have worked on categorization of clutter using long term trends on detection azimuth, frequency, and amplitude at each station. In this work we continue the same line of reasoning to build a probabilistic model of clutter that is used as part of NETVISA [2], a Bayesian approach to network processing. The resulting model is a fusion of seismic, hydroacoustic and infrasound processing built on a unified probabilistic framework. References: [1] Infrasound categorization Towards a statistics based approach. J. Vergoz, P. Gaillard, A. Le Pichon, N. Brachet, and L. Ceranna. ITW 2011 [2] NETVISA: Network Processing Vertically Integrated Seismic Analysis. N. S. Arora, S. Russell, and E. Sudderth. BSSA 2013

Spectral estimation—What is new? What is next?

NASA Astrophysics Data System (ADS)

Tary, Jean Baptiste; Herrera, Roberto Henry; Han, Jiajun; van der Baan, Mirko

2014-12-01

Spectral estimation, and corresponding time-frequency representation for nonstationary signals, is a cornerstone in geophysical signal processing and interpretation. The last 10-15 years have seen the development of many new high-resolution decompositions that are often fundamentally different from Fourier and wavelet transforms. These conventional techniques, like the short-time Fourier transform and the continuous wavelet transform, show some limitations in terms of resolution (localization) due to the trade-off between time and frequency localizations and smearing due to the finite size of the time series of their template. Well-known techniques, like autoregressive methods and basis pursuit, and recently developed techniques, such as empirical mode decomposition and the synchrosqueezing transform, can achieve higher time-frequency localization due to reduced spectral smearing and leakage. We first review the theory of various established and novel techniques, pointing out their assumptions, adaptability, and expected time-frequency localization. We illustrate their performances on a provided collection of benchmark signals, including a laughing voice, a volcano tremor, a microseismic event, and a global earthquake, with the intention to provide a fair comparison of the pros and cons of each method. Finally, their outcomes are discussed and possible avenues for improvements are proposed.

Hydrological processes in glacierized high-altitude basins of the western Himalayas

NASA Astrophysics Data System (ADS)

Jeelani, Ghulam; Shah, Rouf A.; Fryar, Alan E.; Deshpande, Rajendrakumar D.; Mukherjee, Abhijit; Perrin, Jerome

2018-03-01

Western Himalaya is a strategically important region, where the water resources are shared by China, India and Pakistan. The economy of the region is largely dependent on the water resources delivered by snow and glacier melt. The presented study used stable isotopes of water to further understand the basin-scale hydro-meteorological, hydrological and recharge processes in three high-altitude mountainous basins of the western Himalayas. The study provided new insights in understanding the dominant factors affecting the isotopic composition of the precipitation, snowpack, glacier melt, streams and springs. It was observed that elevation-dependent post-depositional processes and snowpack evolution resulted in the higher isotopic altitude gradient in snowpacks. The similar temporal trends of isotopic signals in rivers and karst springs reflect the rapid flow transfer due to karstification of the carbonate aquifers. The attenuation of the extreme isotopic input signal in karst springs appears to be due to the mixing of source waters with the underground karst reservoirs. Basin-wise, the input-output response demonstrates the vital role of winter precipitation in maintaining the perennial flow in streams and karst springs in the region. Isotopic data were also used to estimate the mean recharge altitude of the springs.

A new and reliable method for live imaging and quantification of reactive oxygen species in Botrytis cinerea: technological advancement.

PubMed

Marschall, Robert; Tudzynski, Paul

2014-10-01

Reactive oxygen species (ROS) are produced in conserved cellular processes either as by-products of the cellular respiration in mitochondria, or purposefully for defense mechanisms, signaling cascades or cell homeostasis. ROS have two diametrically opposed attributes due to their highly damaging potential for DNA, lipids and other molecules and due to their indispensability for signaling and developmental processes. In filamentous fungi, the role of ROS in growth and development has been studied in detail, but these analyses were often hampered by the lack of reliable and specific techniques to monitor different activities of ROS in living cells. Here, we present a new method for live cell imaging of ROS in filamentous fungi. We demonstrate that by use of a mixture of two fluorescent dyes it is possible to monitor H2O2 and superoxide specifically and simultaneously in distinct cellular structures during various hyphal differentiation processes. In addition, the method allows for reliable fluorometric quantification of ROS. We demonstrate that this can be used to characterize different mutants with respect to their ROS production/scavenging potential. Copyright © 2014 Elsevier Inc. All rights reserved.

Automatic Modulation Classification Based on Deep Learning for Unmanned Aerial Vehicles.

PubMed

Zhang, Duona; Ding, Wenrui; Zhang, Baochang; Xie, Chunyu; Li, Hongguang; Liu, Chunhui; Han, Jungong

2018-03-20

Deep learning has recently attracted much attention due to its excellent performance in processing audio, image, and video data. However, few studies are devoted to the field of automatic modulation classification (AMC). It is one of the most well-known research topics in communication signal recognition and remains challenging for traditional methods due to complex disturbance from other sources. This paper proposes a heterogeneous deep model fusion (HDMF) method to solve the problem in a unified framework. The contributions include the following: (1) a convolutional neural network (CNN) and long short-term memory (LSTM) are combined by two different ways without prior knowledge involved; (2) a large database, including eleven types of single-carrier modulation signals with various noises as well as a fading channel, is collected with various signal-to-noise ratios (SNRs) based on a real geographical environment; and (3) experimental results demonstrate that HDMF is very capable of coping with the AMC problem, and achieves much better performance when compared with the independent network.

Automatic Modulation Classification Based on Deep Learning for Unmanned Aerial Vehicles

PubMed Central

Ding, Wenrui; Zhang, Baochang; Xie, Chunyu; Li, Hongguang; Liu, Chunhui; Han, Jungong

2018-01-01

Deep learning has recently attracted much attention due to its excellent performance in processing audio, image, and video data. However, few studies are devoted to the field of automatic modulation classification (AMC). It is one of the most well-known research topics in communication signal recognition and remains challenging for traditional methods due to complex disturbance from other sources. This paper proposes a heterogeneous deep model fusion (HDMF) method to solve the problem in a unified framework. The contributions include the following: (1) a convolutional neural network (CNN) and long short-term memory (LSTM) are combined by two different ways without prior knowledge involved; (2) a large database, including eleven types of single-carrier modulation signals with various noises as well as a fading channel, is collected with various signal-to-noise ratios (SNRs) based on a real geographical environment; and (3) experimental results demonstrate that HDMF is very capable of coping with the AMC problem, and achieves much better performance when compared with the independent network. PMID:29558434

Rolling element bearing defect diagnosis under variable speed operation through angle synchronous averaging of wavelet de-noised estimate

NASA Astrophysics Data System (ADS)

Mishra, C.; Samantaray, A. K.; Chakraborty, G.

2016-05-01

Rolling element bearings are widely used in rotating machines and their faults can lead to excessive vibration levels and/or complete seizure of the machine. Under special operating conditions such as non-uniform or low speed shaft rotation, the available fault diagnosis methods cannot be applied for bearing fault diagnosis with full confidence. Fault symptoms in such operating conditions cannot be easily extracted through usual measurement and signal processing techniques. A typical example is a bearing in heavy rolling mill with variable load and disturbance from other sources. In extremely slow speed operation, variation in speed due to speed controller transients or external disturbances (e.g., varying load) can be relatively high. To account for speed variation, instantaneous angular position instead of time is used as the base variable of signals for signal processing purposes. Even with time synchronous averaging (TSA) and well-established methods like envelope order analysis, rolling element faults in rolling element bearings cannot be easily identified during such operating conditions. In this article we propose to use order tracking on the envelope of the wavelet de-noised estimate of the short-duration angle synchronous averaged signal to diagnose faults in rolling element bearing operating under the stated special conditions. The proposed four-stage sequential signal processing method eliminates uncorrelated content, avoids signal smearing and exposes only the fault frequencies and its harmonics in the spectrum. We use experimental data1

Estimation of Fine and Oversize Particle Ratio in a Heterogeneous Compound with Acoustic Emissions.

PubMed

Nsugbe, Ejay; Ruiz-Carcel, Cristobal; Starr, Andrew; Jennions, Ian

2018-03-13

The final phase of powder production typically involves a mixing process where all of the particles are combined and agglomerated with a binder to form a single compound. The traditional means of inspecting the physical properties of the final product involves an inspection of the particle sizes using an offline sieving and weighing process. The main downside of this technique, in addition to being an offline-only measurement procedure, is its inability to characterise large agglomerates of powders due to sieve blockage. This work assesses the feasibility of a real-time monitoring approach using a benchtop test rig and a prototype acoustic-based measurement approach to provide information that can be correlated to product quality and provide the opportunity for future process optimisation. Acoustic emission (AE) was chosen as the sensing method due to its low cost, simple setup process, and ease of implementation. The performance of the proposed method was assessed in a series of experiments where the offline quality check results were compared to the AE-based real-time estimations using data acquired from a benchtop powder free flow rig. A designed time domain based signal processing method was used to extract particle size information from the acquired AE signal and the results show that this technique is capable of estimating the required ratio in the washing powder compound with an average absolute error of 6%.

Left-right symmetry and the charged Higgs bosons at the LHC

NASA Astrophysics Data System (ADS)

Bambhaniya, G.; Chakrabortty, J.; Gluza, J.; Kordiaczynska, M.; Szafron, R.

2014-05-01

The charged Higgs boson sector of the Minimal Manifest Left-Right Symmetric model (MLRSM) is investigated in the context of LHC discovery search for new physics beyond Standard Model. We discuss and summarise the main processes within MLRSM where heavy charged Higgs bosons can be produced at the LHC. We explore the scenarios where the amplified signals due to relatively light charged scalars dominate against heavy neutral Z 2 and charged gauge W 2 as well as heavy neutral Higgs bosons signals which are dumped due to large vacuum expectation value v R of the right-handed scalar triplet. Consistency with FCNC effects implies masses of two neutral Higgs bosons to be at least of 10 TeV order, which in turn implies that in MLRSM only three of four charged Higgs bosons, namely and ,and can be simultaneously light. In particular, production processes with one and two doubly charged Higgs bosons are considered. We further incorporate the decays of those scalars leading to multi lepton signals at the LHC. Branching ratios for heavy neutrino N R , W 2 and Z 2 decay into charged Higgs bosons are calculated. These effects are substantial enough and cannot be neglected. The tri- and four-lepton final states for different benchmark points are analysed. Kinematic cuts are chosen in order to strength the leptonic signals and decrease the Standard Model (SM) background. The results are presented using di-lepton invariant mass and lepton-lepton separation distributions for the same sign (SSDL) and opposite sign (OSDL) di-leptons as well as the charge asymmetry are also discussed. We have found that for considered MLRSM processes tri-lepton and four-lepton signals are most important for their detection when compared to the SM background. Both of the signals can be detected at 14 TeV collisions at the LHC with integrated luminosity at the level of 300 fb-1 with doubly charged Higgs bosons up to approximately 600 GeV. Finally, possible extra contribution of the charged MLRSM scalar particles to the measured Higgs to di-photon ( → γγ) decay is computed and pointed out.

Wavelet Filter Banks for Super-Resolution SAR Imaging

NASA Technical Reports Server (NTRS)

Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

2011-01-01

This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

Structural Health Monitoring and Impact Detection Using Neural Networks for Damage Characterization

NASA Technical Reports Server (NTRS)

Ross, Richard W.

2006-01-01

Detection of damage due to foreign object impact is an important factor in the development of new aerospace vehicles. Acoustic waves generated on impact can be detected using a set of piezoelectric transducers, and the location of impact can be determined by triangulation based on the differences in the arrival time of the waves at each of the sensors. These sensors generate electrical signals in response to mechanical motion resulting from the impact as well as from natural vibrations. Due to electrical noise and mechanical vibration, accurately determining these time differentials can be challenging, and even small measurement inaccuracies can lead to significant errors in the computed damage location. Wavelet transforms are used to analyze the signals at multiple levels of detail, allowing the signals resulting from the impact to be isolated from ambient electromechanical noise. Data extracted from these transformed signals are input to an artificial neural network to aid in identifying the moment of impact from the transformed signals. By distinguishing which of the signal components are resultant from the impact and which are characteristic of noise and normal aerodynamic loads, the time differentials as well as the location of damage can be accurately assessed. The combination of wavelet transformations and neural network processing results in an efficient and accurate approach for passive in-flight detection of foreign object damage.

In situ X-ray diffraction analysis of (CF x) n batteries: signal extraction by multivariate analysis

DOE PAGES

Rodriguez, Mark A.; Keenan, Michael R.; Nagasubramanian, Ganesan

2007-11-10

In this study, (CF x) n cathode reaction during discharge has been investigated using in situ X-ray diffraction (XRD). Mathematical treatment of the in situ XRD data set was performed using multivariate curve resolution with alternating least squares (MCR–ALS), a technique of multivariate analysis. MCR–ALS analysis successfully separated the relatively weak XRD signal intensity due to the chemical reaction from the other inert cell component signals. The resulting dynamic reaction component revealed the loss of (CF x) n cathode signal together with the simultaneous appearance of LiF by-product intensity. Careful examination of the XRD data set revealed an additional dynamicmore » component which may be associated with the formation of an intermediate compound during the discharge process.« less

A high-efficiency real-time digital signal averager for time-of-flight mass spectrometry.

PubMed

Wang, Yinan; Xu, Hui; Li, Qingjiang; Li, Nan; Huang, Zhengxu; Zhou, Zhen; Liu, Husheng; Sun, Zhaolin; Xu, Xin; Yu, Hongqi; Liu, Haijun; Li, David D-U; Wang, Xi; Dong, Xiuzhen; Gao, Wei

2013-05-30

Analog-to-digital converter (ADC)-based acquisition systems are widely applied in time-of-flight mass spectrometers (TOFMS) due to their ability to record the signal intensity of all ions within the same pulse. However, the acquisition system raises the requirement for data throughput, along with increasing the conversion rate and resolution of the ADC. It is therefore of considerable interest to develop a high-performance real-time acquisition system, which can relieve the limitation of data throughput. We present in this work a high-efficiency real-time digital signal averager, consisting of a signal conditioner, a data conversion module and a signal processing module. Two optimization strategies are implemented using field programmable gate arrays (FPGAs) to enhance the efficiency of the real-time processing. A pipeline procedure is used to reduce the time consumption of the accumulation strategy. To realize continuous data transfer, a high-efficiency transmission strategy is developed, based on a ping-pong procedure. The digital signal averager features good responsiveness, analog bandwidth and dynamic performance. The optimal effective number of bits reaches 6.7 bits. For a 32 µs record length, the averager can realize 100% efficiency with an extraction frequency below 31.23 kHz by modifying the number of accumulation steps. In unit time, the averager yields superior signal-to-noise ratio (SNR) compared with data accumulation in a computer. The digital signal averager is combined with a vacuum ultraviolet single-photon ionization time-of-flight mass spectrometer (VUV-SPI-TOFMS). The efficiency of the real-time processing is tested by analyzing the volatile organic compounds (VOCs) from ordinary printed materials. In these experiments, 22 kinds of compounds are detected, and the dynamic range exceeds 3 orders of magnitude. Copyright © 2013 John Wiley & Sons, Ltd.

Galaxy–Galaxy Weak-lensing Measurements from SDSS. I. Image Processing and Lensing Signals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Wentao; Yang, Xiaohu; Zhang, Jun

We present our image processing pipeline that corrects the systematics introduced by the point-spread function (PSF). Using this pipeline, we processed Sloan Digital Sky Survey (SDSS) DR7 imaging data in r band and generated a galaxy catalog containing the shape information. Based on our shape measurements of the galaxy images from SDSS DR7, we extract the galaxy–galaxy (GG) lensing signals around foreground spectroscopic galaxies binned in different luminosities and stellar masses. We estimated the systematics, e.g., selection bias, PSF reconstruction bias, PSF dilution bias, shear responsivity bias, and noise rectification bias, which in total is between −9.1% and 20.8% atmore » 2 σ levels. The overall GG lensing signals we measured are in good agreement with Mandelbaum et al. The reduced χ {sup 2} between the two measurements in different luminosity bins are from 0.43 to 0.83. Larger reduced χ {sup 2} from 0.60 to 1.87 are seen for different stellar mass bins, which is mainly caused by the different stellar mass estimator. The results in this paper with higher signal-to-noise ratio are due to the larger survey area than SDSS DR4, confirming that more luminous/massive galaxies bear stronger GG lensing signals. We divide the foreground galaxies into red/blue and star-forming/quenched subsamples and measure their GG lensing signals. We find that, at a specific stellar mass/luminosity, the red/quenched galaxies have stronger GG lensing signals than their counterparts, especially at large radii. These GG lensing signals can be used to probe the galaxy–halo mass relations and their environmental dependences in the halo occupation or conditional luminosity function framework.« less

Human Prostate Cancer Hallmarks Map

PubMed Central

Datta, Dipamoy; Aftabuddin, Md.; Gupta, Dinesh Kumar; Raha, Sanghamitra; Sen, Prosenjit

2016-01-01

Human prostate cancer is a complex heterogeneous disease that mainly affects elder male population of the western world with a high rate of mortality. Acquisitions of diverse sets of hallmark capabilities along with an aberrant functioning of androgen receptor signaling are the central driving forces behind prostatic tumorigenesis and its transition into metastatic castration resistant disease. These hallmark capabilities arise due to an intense orchestration of several crucial factors, including deregulation of vital cell physiological processes, inactivation of tumor suppressive activity and disruption of prostate gland specific cellular homeostasis. The molecular complexity and redundancy of oncoproteins signaling in prostate cancer demands for concurrent inhibition of multiple hallmark associated pathways. By an extensive manual curation of the published biomedical literature, we have developed Human Prostate Cancer Hallmarks Map (HPCHM), an onco-functional atlas of human prostate cancer associated signaling and events. It explores molecular architecture of prostate cancer signaling at various levels, namely key protein components, molecular connectivity map, oncogenic signaling pathway map, pathway based functional connectivity map etc. Here, we briefly represent the systems level understanding of the molecular mechanisms associated with prostate tumorigenesis by considering each and individual molecular and cell biological events of this disease process. PMID:27476486

Biological Signal Processing with a Genetic Toggle Switch

PubMed Central

Hillenbrand, Patrick; Fritz, Georg; Gerland, Ulrich

2013-01-01

Complex gene regulation requires responses that depend not only on the current levels of input signals but also on signals received in the past. In digital electronics, logic circuits with this property are referred to as sequential logic, in contrast to the simpler combinatorial logic without such internal memory. In molecular biology, memory is implemented in various forms such as biochemical modification of proteins or multistable gene circuits, but the design of the regulatory interface, which processes the input signals and the memory content, is often not well understood. Here, we explore design constraints for such regulatory interfaces using coarse-grained nonlinear models and stochastic simulations of detailed biochemical reaction networks. We test different designs for biological analogs of the most versatile memory element in digital electronics, the JK-latch. Our analysis shows that simple protein-protein interactions and protein-DNA binding are sufficient, in principle, to implement genetic circuits with the capabilities of a JK-latch. However, it also exposes fundamental limitations to its reliability, due to the fact that biological signal processing is asynchronous, in contrast to most digital electronics systems that feature a central clock to orchestrate the timing of all operations. We describe a seemingly natural way to improve the reliability by invoking the master-slave concept from digital electronics design. This concept could be useful to interpret the design of natural regulatory circuits, and for the design of synthetic biological systems. PMID:23874595

Identification and classification of failure modes in laminated composites by using a multivariate statistical analysis of wavelet coefficients

NASA Astrophysics Data System (ADS)

Baccar, D.; Söffker, D.

2017-11-01

Acoustic Emission (AE) is a suitable method to monitor the health of composite structures in real-time. However, AE-based failure mode identification and classification are still complex to apply due to the fact that AE waves are generally released simultaneously from all AE-emitting damage sources. Hence, the use of advanced signal processing techniques in combination with pattern recognition approaches is required. In this paper, AE signals generated from laminated carbon fiber reinforced polymer (CFRP) subjected to indentation test are examined and analyzed. A new pattern recognition approach involving a number of processing steps able to be implemented in real-time is developed. Unlike common classification approaches, here only CWT coefficients are extracted as relevant features. Firstly, Continuous Wavelet Transform (CWT) is applied to the AE signals. Furthermore, dimensionality reduction process using Principal Component Analysis (PCA) is carried out on the coefficient matrices. The PCA-based feature distribution is analyzed using Kernel Density Estimation (KDE) allowing the determination of a specific pattern for each fault-specific AE signal. Moreover, waveform and frequency content of AE signals are in depth examined and compared with fundamental assumptions reported in this field. A correlation between the identified patterns and failure modes is achieved. The introduced method improves the damage classification and can be used as a non-destructive evaluation tool.

Comparison of lifetime-based methods for 2D phosphor thermometry in high-temperature environment

NASA Astrophysics Data System (ADS)

Peng, Di; Liu, Yingzheng; Zhao, Xiaofeng; Kim, Kyung Chun

2016-09-01

This paper discusses the currently available techniques for 2D phosphor thermometry, and compares the performance of two lifetime-based methods: high-speed imaging and the dual-gate. High-speed imaging resolves luminescent decay with a fast frame rate, and has become a popular method for phosphor thermometry in recent years. But it has disadvantages such as high equipment cost and long data processing time, and it would fail at sufficiently high temperature due to a low signal-to-noise ratio and short lifetime. The dual-gate method only requires two images on the decay curve and therefore greatly reduces cost in hardware and processing time. A dual-gate method for phosphor thermometry has been developed and compared with the high-speed imaging method through both calibration and a jet impingement experiment. Measurement uncertainty has been evaluated for a temperature range of 473-833 K. The effects of several key factors on uncertainty have been discussed, including the luminescent signal level, the decay lifetime and temperature sensitivity. The results show that both methods are valid for 2D temperature sensing within the given range. The high-speed imaging method shows less uncertainty at low temperatures where the signal level and the lifetime are both sufficient, but its performance is degraded at higher temperatures due to a rapidly reduced signal and lifetime. For T  >  750 K, the dual-gate method outperforms the high-speed imaging method thanks to its superiority in signal-to-noise ratio and temperature sensitivity. The dual-gate method has great potential for applications in high-temperature environments where the high-speed imaging method is not applicable.

[Study on the arc spectral information for welding quality diagnosis].

PubMed

Li, Zhi-Yong; Gu, Xiao-Yan; Li, Huan; Yang, Li-Jun

2009-03-01

Through collecting the spectral signals of TIG and MIG welding arc with spectrometer, the arc light radiations were analyzed based on the basic theory of plasma physics. The radiation of welding arc distributes over a broad range of frequency, from infrared to ultraviolet. The arc spectrum is composed of line spectra and continuous spectra. Due to the variation of metal density in the welding arc, there is great difference between the welding arc spectra of TIG and MIG in both their intensity and distribution. The MIG welding arc provides more line spectra of metal and the intensity of radiation is greater than TIG. The arc spectrum of TIG welding is stable during the welding process, disturbance factors that cause the spectral variations can be reflected by the spectral line related to the corresponding element entering the welding arc. The arc spectrum of MIG welding will fluctuate severely due to droplet transfer, which produces "noise" in the line spectrum aggregation zone. So for MIG welding, the spectral zone lacking spectral line is suitable for welding quality diagnosis. According to the characteristic of TIG and MIG, special spectral zones were selected for welding quality diagnosis. For TIG welding, the selected zone is in ultraviolet zone (230-300 nm). For MIG welding, the selected zone is in visible zone (570-590 nm). With the basic theory provided for welding quality diagnosis, the integral intensity of spectral signal in the selected zone of welding process with disturbing factor was studied to prove the theory. The results show that the welding quality and disturbance factors can be diagnosed with good signal to noise ratio in the selected spectral zone compared with signal in other spectral zone. The spectral signal can be used for real-time diagnosis of the welding quality.

Few-Flakes Reduced Graphene Oxide Sensors for Organic Vapors with a High Signal-to-Noise Ratio

PubMed Central

Hasan, Nowzesh; Zhang, Wenli

2017-01-01

This paper reports our findings on how to prepare a graphene oxide-based gas sensor for sensing fast pulses of volatile organic compounds with a better signal-to-noise ratio. We use rapid acetone pulses of varying concentrations to test the sensors. First, we compare the effect of graphene oxide deposition method (dielectrophoresis versus solvent evaporation) on the sensor’s response. We find that dielectrophoresis yields films with uniform coverage and better sensor response. Second, we examine the effect of chemical reduction. Contrary to prior reports, we find that graphene oxide reduction leads to a reduction in sensor response and current noise, thus keeping the signal-to-noise ratio the same. We found that if we sonicated the sensor in acetone, we created a sensor with a few flakes of reduced graphene oxide. Such sensors provided a higher signal-to-noise ratio that could be correlated to the vapor concentration of acetone with better repeatability. Modeling shows that the sensor’s response is due to one-site Langmuir adsorption or an overall single exponent process. Further, the desorption of acetone as deduced from the sensor recovery signal follows a single exponent process. Thus, we show a simple way to improve the signal-to-noise ratio in reduced graphene oxide sensors. PMID:29065488

The impact of environmental factors on the performance of millimeter wave seekers in smart munitions

NASA Astrophysics Data System (ADS)

Hager, R.

1987-08-01

An assessment has been made of the degradation in performance of horizontal-glide smart munitions incorporating millimeter wave seekers operating in three types of environments. Atmospheric effects are shown to degrade performance appreciably only in very severe weather conditions. Electromagnetic line-of-sight masking due to foliage (forest canopy and tree-lined roads) will limit submunition usage and may be a potential problem. The most serious problem involves the confident detection of military vehicles in the presence of land clutter. Standard signal processing techniques involving signal amplitude and signal averaging are not likely to be adequate for detection. Observations regarding more sophisticated techniques and the current state of research are included.

Analysis and improved design considerations for airborne pulse Doppler radar signal processing in the detection of hazardous windshear

NASA Technical Reports Server (NTRS)

Lee, Jonggil

1990-01-01

High resolution windspeed profile measurements are needed to provide reliable detection of hazardous low altitude windshear with an airborne pulse Doppler radar. The system phase noise in a Doppler weather radar may degrade the spectrum moment estimation quality and the clutter cancellation capability which are important in windshear detection. Also the bias due to weather return Doppler spectrum skewness may cause large errors in pulse pair spectral parameter estimates. These effects are analyzed for the improvement of an airborne Doppler weather radar signal processing design. A method is presented for the direct measurement of windspeed gradient using low pulse repetition frequency (PRF) radar. This spatial gradient is essential in obtaining the windshear hazard index. As an alternative, the modified Prony method is suggested as a spectrum mode estimator for both the clutter and weather signal. Estimation of Doppler spectrum modes may provide the desired windshear hazard information without the need of any preliminary processing requirement such as clutter filtering. The results obtained by processing a NASA simulation model output support consideration of mode identification as one component of a windshear detection algorithm.

System theory in industrial patient monitoring: an overview.

PubMed

Baura, G D

2004-01-01

Patient monitoring refers to the continuous observation of repeating events of physiologic function to guide therapy or to monitor the effectiveness of interventions, and is used primarily in the intensive care unit and operating room. Commonly processed signals are the electrocardiogram, intraarterial blood pressure, arterial saturation of oxygen, and cardiac output. To this day, the majority of physiologic waveform processing in patient monitors is conducted using heuristic curve fitting. However in the early 1990s, a few enterprising engineers and physicians began using system theory to improve their core processing. Applications included improvement of signal-to-noise ratio, either due to low signal levels or motion artifact, and improvement in feature detection. The goal of this mini-symposium is to review the early work in this emerging field, which has led to technologic breakthroughs. In this overview talk, the process of system theory algorithm research and development is discussed. Research for industrial monitors involves substantial data collection, with some data used for algorithm training and the remainder used for validation. Once the algorithms are validated, they are translated into detailed specifications. Development then translates these specifications into DSP code. The DSP code is verified and validated per the Good Manufacturing Practices mandated by FDA.

A Subsystem Test Bed for Chinese Spectral Radioheliograph

NASA Astrophysics Data System (ADS)

Zhao, An; Yan, Yihua; Wang, Wei

2014-11-01

The Chinese Spectral Radioheliograph is a solar dedicated radio interferometric array that will produce high spatial resolution, high temporal resolution, and high spectral resolution images of the Sun simultaneously in decimetre and centimetre wave range. Digital processing of intermediate frequency signal is an important part in a radio telescope. This paper describes a flexible and high-speed digital down conversion system for the CSRH by applying complex mixing, parallel filtering, and extracting algorithms to process IF signal at the time of being designed and incorporates canonic-signed digit coding and bit-plane method to improve program efficiency. The DDC system is intended to be a subsystem test bed for simulation and testing for CSRH. Software algorithms for simulation and hardware language algorithms based on FPGA are written which use less hardware resources and at the same time achieve high performances such as processing high-speed data flow (1 GHz) with 10 MHz spectral resolution. An experiment with the test bed is illustrated by using geostationary satellite data observed on March 20, 2014. Due to the easy alterability of the algorithms on FPGA, the data can be recomputed with different digital signal processing algorithms for selecting optimum algorithm.

Analysis of transcriptome in hickory (Carya cathayensis), and uncover the dynamics in the hormonal signaling pathway during graft process.

PubMed

Qiu, Lingling; Jiang, Bo; Fang, Jia; Shen, Yike; Fang, Zhongxiang; Rm, Saravana Kumar; Yi, Keke; Shen, Chenjia; Yan, Daoliang; Zheng, Bingsong

2016-11-17

Hickory (Carya cathayensis), a woody plant with high nutritional and economic value, is widely planted in China. Due to its long juvenile phase, grafting is a useful technique for large-scale cultivation of hickory. To reveal the molecular mechanism during the graft process, we sequenced the transcriptomes of graft union in hickory. In our study, six RNA-seq libraries yielded a total of 83,676,860 clean short reads comprising 4.19 Gb of sequence data. A large number of differentially expressed genes (DEGs) at three time points during the graft process were identified. In detail, 777 DEGs in the 7 d vs 0 d (day after grafting) comparison were classified into 11 enriched Gene Ontology (GO) categories, and 262 DEGs in the 14 d vs 0 d comparison were classified into 15 enriched GO categories. Furthermore, an overview of the PPI network was constructed by these DEGs. In addition, 20 genes related to the auxin-and cytokinin-signaling pathways were identified, and some were validated by qRT-PCR analysis. Our comprehensive analysis provides basic information on the candidate genes and hormone signaling pathways involved in the graft process in hickory and other woody plants.

Progresses with Net-VISA on Global Infrasound Association

NASA Astrophysics Data System (ADS)

Mialle, Pierrick; Arora, Nimar

2017-04-01

Global Infrasound Association algorithms are an important area of active development at the International Data Centre (IDC). These algorithms play an important part of the automatic processing system for verification technologies. A key focus at the IDC is to enhance association and signal characterization methods by incorporating the identification of signals of interest and the optimization of the network detection threshold. The overall objective is to reduce the number of associated infrasound arrivals that are rejected from the automatic bulletins when generating the Reviewed Event Bulletins (REB), and hence reduce IDC analyst workload. Despite good accuracy by the IDC categorization, a number of signal detections due to clutter sources such as microbaroms or surf are built into events. In this work we aim to optimize the association criteria based on knowledge acquired by IDC in the last 6 years, and focus on the specificity of seismo-acoustic events. The resulting work has been incorporated into NETVISA [1], a Bayesian approach to network processing. The model that we propose is a fusion of seismic, hydroacoustic and infrasound processing built on a unified probabilistic framework. References: [1] NETVISA: Network Processing Vertically Integrated Seismic Analysis. N. S. Arora, S. Russell, and E. Sudderth. BSSA 2013

Progresses with Net-VISA on Global Infrasound Association

NASA Astrophysics Data System (ADS)

Mialle, P.; Arora, N. S.

2016-12-01

Global Infrasound Association algorithms are an important area of active development at the International Data Centre (IDC). These algorithms play an important part of the automatic processing system for verification technologies. A key focus at the IDC is to enhance association and signal characterization methods by incorporating the identification of signals of interest and the optimization of the network detection threshold. The overall objective is to reduce the number of associated infrasound arrivals that are rejected from the automatic bulletins when generating the Reviewed Event Bulletins (REB), and hence reduce IDC analyst workload. Despite good accuracy by the IDC categorization, a number of signal detections due to clutter sources such as microbaroms or surf are built into events. In this work we aim to optimize the association criteria based on knowledge acquired by IDC in the last 6 years, and focus on the specificity of seismo-acoustic events. The resulting work has been incorporated into NETVISA [1], a Bayesian approach to network processing. The model that we propose is a fusion of seismic, hydroacoustic and infrasound processing built on a unified probabilistic framework. References: [1] NETVISA: Network Processing Vertically Integrated Seismic Analysis. N. S. Arora, S. Russell, and E. Sudderth. BSSA 2013

Theoretical analysis of degradation mechanisms in the formation of morphogen gradients

NASA Astrophysics Data System (ADS)

Bozorgui, Behnaz; Teimouri, Hamid; Kolomeisky, Anatoly B.

2015-07-01

Fundamental biological processes of development of tissues and organs in multicellular organisms are governed by various signaling molecules, which are called morphogens. It is known that spatial and temporal variations in the concentration profiles of signaling molecules, which are frequently referred as morphogen gradients, lead to a cell differentiation via activating specific genes in a concentration-dependent manner. It is widely accepted that the establishment of the morphogen gradients involves multiple biochemical reactions and diffusion processes. One of the critical elements in the formation of morphogen gradients is a degradation of signaling molecules. We develop a new theoretical approach that provides a comprehensive description of the degradation mechanisms. It is based on the idea that the degradation works as an effective potential that drives the signaling molecules away from the source region. Utilizing the method of first-passage processes, the dynamics of the formation of morphogen gradients for various degradation mechanisms is explicitly evaluated. It is found that linear degradation processes lead to a dynamic behavior specified by times to form the morphogen gradients that depend linearly on the distance from the source. This is because the effective potential due to the degradation is quite strong. At the same time, nonlinear degradation mechanisms yield a quadratic scaling in the morphogen gradients formation times since the effective potentials are much weaker. Physical-chemical explanations of these phenomena are presented.

Engineering information on an Analog Signal to Discrete Time Interval Converter (ASDT-IC)

NASA Technical Reports Server (NTRS)

Schwarz, F. C.

1974-01-01

An electronic control system for nondissipative dc power converters is presented which improves (1) the routinely attainable static output voltage accuracy to the order of + or - 1% for ambient temperatures from -55 to 100 C and (2) the dynamic stability by utilizing approximately one tenth of the feedback gain needed otherwise. Performance is due to a functional philosophy of deterministic pulse modulation based on pulse area control and to an autocompensated signal processing principle. The system can be implemented with commercially available unselected components.

A New Indoor Positioning System Architecture Using GPS Signals.

PubMed

Xu, Rui; Chen, Wu; Xu, Ying; Ji, Shengyue

2015-04-29

The pseudolite system is a good alternative for indoor positioning systems due to its large coverage area and accurate positioning solution. However, for common Global Positioning System (GPS) receivers, the pseudolite system requires some modifications of the user terminals. To solve the problem, this paper proposes a new pseudolite-based indoor positioning system architecture. The main idea is to receive real-world GPS signals, repeat each satellite signal and transmit those using indoor transmitting antennas. The transmitted GPS-like signal can be processed (signal acquisition and tracking, navigation data decoding) by the general receiver and thus no hardware-level modification on the receiver is required. In addition, all Tx can be synchronized with each other since one single clock is used in Rx/Tx. The proposed system is simulated using a software GPS receiver. The simulation results show the indoor positioning system is able to provide high accurate horizontal positioning in both static and dynamic situations.

Untangling climate signals from autogenic changes in long-term peatland development

NASA Astrophysics Data System (ADS)

Morris, Paul J.; Baird, Andy J.; Young, Dylan M.; Swindles, Graeme T.

2015-12-01

Peatlands represent important archives of Holocene paleoclimatic information. However, autogenic processes may disconnect peatland hydrological behavior from climate and overwrite climatic signals in peat records. We use a simulation model of peatland development driven by a range of Holocene climate reconstructions to investigate climate signal preservation in peat records. Simulated water-table depths and peat decomposition profiles exhibit homeostatic recovery from prescribed changes in rainfall, whereas changes in temperature cause lasting alterations to peatland structure and function. Autogenic ecohydrological feedbacks provide both high- and low-pass filters for climatic information, particularly rainfall. Large-magnitude climatic changes of an intermediate temporal scale (i.e., multidecadal to centennial) are most readily preserved in our simulated peat records. Simulated decomposition signals are offset from the climatic changes that generate them due to a phenomenon known as secondary decomposition. Our study provides the mechanistic foundations for a framework to separate climatic and autogenic signals in peat records.

Nonintrusive biological signal monitoring in a car to evaluate a driver's stress and health state.

PubMed

Baek, Hyun Jae; Lee, Haet Bit; Kim, Jung Soo; Choi, Jong Min; Kim, Ko Keun; Park, Kwang Suk

2009-03-01

Nonintrusive monitoring of a driver's physiological signals was introduced and evaluated in a car as a test of extending the concept of ubiquitous healthcare to vehicles. Electrocardiogram, photoplethysmogram, galvanic skin response, and respiration were measured in the ubiquitous healthcare car (U-car) using nonintrusively installed sensors on the steering wheel, driver's seat, and seat belt. Measured signals were transmitted to the embedded computer via Bluetooth(R) communication and processed. We collected and analyzed physiological signals during driving in order to estimate a driver's stress state while using this system. In order to compare the effect of stress on physical and mental conditions, two categories of stresses were defined. Experimental results show that a driver's physiological signals were measured with acceptable quality for analysis without interrupting driving, and they were changed meaningfully due to elicited stress. This nonintrusive monitoring can be used to evaluate a driver's state of health and stress.

On-chip temperature-based digital signal processing for customized wireless microcontroller

NASA Astrophysics Data System (ADS)

Farhah Razanah Faezal, Siti; Isa, Mohd Nazrin Md; Harun, Azizi; Nizam Mohyar, Shaiful; Bahari Jambek, Asral

2017-11-01

Increases in die size and power density inside system-on-chip (SoC) design have brought thermal issue inside the system. Uneven heat-up and increasing in temperature offset on-chip has become a major factor that can limits the system performance. This paper presents the design and simulation of a temperature-based digital signal processing for modern system-on-chip design using the Verilog HDL. This design yields continuous monitoring of temperature and reacts to specified conditions. The simulation of the system has been done on Altera Quartus Software v. 14. With system above, microcontroller can achieve nominal power dissipation and operation is within the temperature range due to the incorporate of an interrupt-based system.

Phase editing as a signal pre-processing step for automated bearing fault detection

NASA Astrophysics Data System (ADS)

Barbini, L.; Ompusunggu, A. P.; Hillis, A. J.; du Bois, J. L.; Bartic, A.

2017-07-01

Scheduled maintenance and inspection of bearing elements in industrial machinery contributes significantly to the operating costs. Savings can be made through automatic vibration-based damage detection and prognostics, to permit condition-based maintenance. However automation of the detection process is difficult due to the complexity of vibration signals in realistic operating environments. The sensitivity of existing methods to the choice of parameters imposes a requirement for oversight from a skilled operator. This paper presents a novel approach to the removal of unwanted vibrational components from the signal: phase editing. The approach uses a computationally-efficient full-band demodulation and requires very little oversight. Its effectiveness is tested on experimental data sets from three different test-rigs, and comparisons are made with two state-of-the-art processing techniques: spectral kurtosis and cepstral pre- whitening. The results from the phase editing technique show a 10% improvement in damage detection rates compared to the state-of-the-art while simultaneously improving on the degree of automation. This outcome represents a significant contribution in the pursuit of fully automatic fault detection.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carena, Marcela; Liu, Zhen

Heavy scalar and pseudoscalar resonance searches through themore » $$gg\\rightarrow S\\rightarrow t\\bar t$$ process are challenging due to the peculiar behavior of the large interference effects with the standard model $$t\\bar t$$ background. Such effects generate non-trivial lineshapes from additional relative phases between the signal and background amplitudes. We provide the analytic expressions for the differential cross sections to understand the interference effects in the heavy scalar signal lineshapes. We extend our study to the case of CP-violation and further consider the effect of bottom quarks in the production and decay processes. We also evaluate the contributions from additional particles to the gluon fusion production process, such as stops and vector-like quarks, that could lead to significant changes in the behavior of the signal lineshapes. Taking into account the large interference effects, we perform lineshape searches at the LHC and discuss the importance of the systematic uncertainties and smearing effects. Lastly, we present projected sensitivities for two LHC performance scenarios to probe the $$gg\\rightarrow S \\rightarrow t\\bar t$$ channel in various models.« less

Quantitative Aspects of Single Molecule Microscopy

PubMed Central

Ober, Raimund J.; Tahmasbi, Amir; Ram, Sripad; Lin, Zhiping; Ward, E. Sally

2015-01-01

Single molecule microscopy is a relatively new optical microscopy technique that allows the detection of individual molecules such as proteins in a cellular context. This technique has generated significant interest among biologists, biophysicists and biochemists, as it holds the promise to provide novel insights into subcellular processes and structures that otherwise cannot be gained through traditional experimental approaches. Single molecule experiments place stringent demands on experimental and algorithmic tools due to the low signal levels and the presence of significant extraneous noise sources. Consequently, this has necessitated the use of advanced statistical signal and image processing techniques for the design and analysis of single molecule experiments. In this tutorial paper, we provide an overview of single molecule microscopy from early works to current applications and challenges. Specific emphasis will be on the quantitative aspects of this imaging modality, in particular single molecule localization and resolvability, which will be discussed from an information theoretic perspective. We review the stochastic framework for image formation, different types of estimation techniques and expressions for the Fisher information matrix. We also discuss several open problems in the field that demand highly non-trivial signal processing algorithms. PMID:26167102

Preliminary results of SAR soil moisture experiment, November 1975

NASA Technical Reports Server (NTRS)

Choudhury, B. J.; Chang, A. T. C.; Schmugge, T. J.; Salomonson, V. V.; Wang, J. R.

1979-01-01

The experiment was performed using the Environmental Research Institute of Michigan's (ERIM) dual-frequency and dual-polarization side-looking SAR system on board a C-46 aircraft. For each frequency, horizontally polarized pulses were transmitted and both horizontally and vertically polarized return signals were recorded on the signal film simultaneously. The test sites were located in St. Charles, Missouri; Centralia, Missouri; and Lafayette, Indiana. Each test site was a 4.83 km by 8.05 km (3 mile by 5 mile) rectangular strip of terrain. Concurrent with SAR overflight, ground soil samples of 0-to-2.5 cm and 0-to-15 cm layers were collected for soil moisture estimation. The surface features were also noted. Hard-copy image films and the digital data produced via optical processing of the signal films are analyzed in this report to study the relationship of radar backscatter to the moisture content and the surface roughness. Many difficulties associated with processing and analysis of the SAR imagery are noted. In particular, major uncertainty in the quantitative analysis appeared due to the difficulty of quality reproduction of digital data from the signal films.

Cycling excitation process: An ultra efficient and quiet signal amplification mechanism in semiconductor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yu-Hsin; Yan, Lujiang; Zhang, Alex Ce

2015-08-03

Signal amplification, performed by transistor amplifiers with its merit rated by the efficiency and noise characteristics, is ubiquitous in all electronic systems. Because of transistor thermal noise, an intrinsic signal amplification mechanism, impact ionization was sought after to complement the limits of transistor amplifiers. However, due to the high operation voltage (30-200 V typically), low power efficiency, limited scalability, and, above all, rapidly increasing excess noise with amplification factor, impact ionization has been out of favor for most electronic systems except for a few applications such as avalanche photodetectors and single-photon Geiger detectors. Here, we report an internal signal amplification mechanismmore » based on the principle of the phonon-assisted cycling excitation process (CEP). Si devices using this concept show ultrahigh gain, low operation voltage, CMOS compatibility, and, above all, quantum limit noise performance that is 30 times lower than devices using impact ionization. Established on a unique physical effect of attractive properties, CEP-based devices can potentially revolutionize the fields of semiconductor electronics.« less

Vestibular signals in macaque extrastriate visual cortex are functionally appropriate for heading perception

PubMed Central

Liu, Sheng; Angelaki, Dora E.

2009-01-01

Visual and vestibular signals converge onto the dorsal medial superior temporal area (MSTd) of the macaque extrastriate visual cortex, which is thought to be involved in multisensory heading perception for spatial navigation. Peripheral otolith information, however, is ambiguous and cannot distinguish linear accelerations experienced during self-motion from those due to changes in spatial orientation relative to gravity. Here we show that, unlike peripheral vestibular sensors but similar to lobules 9 and 10 of the cerebellar vermis (nodulus and uvula), MSTd neurons respond selectively to heading and not to changes in orientation relative to gravity. In support of a role in heading perception, MSTd vestibular responses are also dominated by velocity-like temporal dynamics, which might optimize sensory integration with visual motion information. Unlike the cerebellar vermis, however, MSTd neurons also carry a spatial orientation-independent rotation signal from the semicircular canals, which could be useful in compensating for the effects of head rotation on the processing of optic flow. These findings show that vestibular signals in MSTd are appropriately processed to support a functional role in multisensory heading perception. PMID:19605631

Estimating random errors due to shot noise in backscatter lidar observations.

PubMed

Liu, Zhaoyan; Hunt, William; Vaughan, Mark; Hostetler, Chris; McGill, Matthew; Powell, Kathleen; Winker, David; Hu, Yongxiang

2006-06-20

We discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson- distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root mean square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF, uncertainties can be reliably calculated from or for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations lidar and tested using data from the Lidar In-space Technology Experiment.

Estimating Random Errors Due to Shot Noise in Backscatter Lidar Observations

NASA Technical Reports Server (NTRS)

Liu, Zhaoyan; Hunt, William; Vaughan, Mark A.; Hostetler, Chris A.; McGill, Matthew J.; Powell, Kathy; Winker, David M.; Hu, Yongxiang

2006-01-01

In this paper, we discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson-distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root-mean-square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF uncertainties can be reliably calculated from/for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar and tested using data from the Lidar In-space Technology Experiment (LITE). OCIS Codes:

Infrasound as a Depth Discriminant

DTIC Science & Technology

2010-09-01

INFRASOUND AS A DEPTH DISCRIMINANT Stephen J. Arrowsmith1, Hans E. Hartse1, Steven R. Taylor2, Richard J. Stead1, and Rod W. Whitaker1 Los Alamos...LA09-Depth-NDD02 ABSTRACT The identification of a signature relating depth to a remotely recorded infrasound signal requires a dataset of...can generate infrasound via a variety of processes, which have occasionally been confused in past studies due to the complexity of the process; (2

Coastal Application of Altimetric Measurement using Wideband Signals of Opportunity Reflectometry

NASA Astrophysics Data System (ADS)

Shah, R.; Garrison, J. L.; Li, Z.; Ho, S. C.

2017-12-01

The majority of the world's population live in coastal regions, making this region subject to growing stress from resource exploitation, marine operations, and other human activities. The coastal ocean is also a highly dynamic region driven by the interfaces between land, sea, and air. Understanding the evolution over short temporal and small spatial scales of the coastal ocean environment is a complex and long-standing challenge. Over the last decade, it has been well established that submesoscale processes are highly energetic and have a temporal scale of hours at a 10-km of spatial scale. These processes fundamentally impact ocean dynamics, biological processes, trace gas mixing and transport. Satellite altimeters, which have played a significant role in mapping the variability of the Earth's open ocean, have known limitations in coastal areas resulting from land contamination and rapid variations due to tides and atmospheric effects. This study will evaluate the potential application of an emerging remote sensing technology (Signals of Opportunity Reflectometry: SoOp-R) to the problem of resolving submesoscale processes in the coastal regions, with spatial scales on the order of 10 km and temporal scales on the order of 1 day. SoOp-R reutilizes existing powerful communication satellite transmissions as illumination sources in a bistatic radar configuration. A number of direct broadcast satellites (DBS), currently operating in geostationary orbit, occupy very large bandwidth (400-500 MHz) spectral allocations in the Ku- and Ka- bands. Theoretically, sea surface height (SSH) can be estimated by measuring the reflected path delay of these signals with very high precision (on the order of 4-5 cm) due to the large bandwidth and high signal- to-noise ratio. SoOp-R instruments are passive, requiring only low-power receivers which could be launched on constellations of small satellites. The distribution of altimetry measurements, combined with the off-nadir geometry, will enable high temporal coverage. This study will assess the potential of resolving coastal processes using wideband SoOp-R. Theoretical predictions will be compared to results from an ongoing experimental campaign and evaluated against science-driven requirements.

Cullin-4 regulates Wingless and JNK signaling-mediated cell death in the Drosophila eye

PubMed Central

Tare, Meghana; Sarkar, Ankita; Bedi, Shimpi; Kango-Singh, Madhuri; Singh, Amit

2016-01-01

In all multicellular organisms, the fundamental processes of cell proliferation and cell death are crucial for growth regulation during organogenesis. Strict regulation of cell death is important to maintain tissue homeostasis by affecting processes like regulation of cell number, and elimination of unwanted/unfit cells. The developing Drosophila eye is a versatile model to study patterning and growth, where complex signaling pathways regulate growth and cell survival. However, the molecular mechanisms underlying regulation of these processes is not fully understood. In a gain-of-function screen, we found that misexpression of cullin-4 (cul-4), an ubiquitin ligase, can rescue reduced eye mutant phenotypes. Previously, cul-4 has been shown to regulate chromatin remodeling, cell cycle and cell division. Genetic characterization of cul-4 in the developing eye revealed that loss-of-function of cul-4 exhibits a reduced eye phenotype. Analysis of twin-spots showed that in comparison with their wild-type counterparts, the cul-4 loss-of-function clones fail to survive. Here we show that cul-4 clones are eliminated by induction of cell death due to activation of caspases. Aberrant activation of signaling pathways is known to trigger cell death in the developing eye. We found that Wingless (Wg) and c-Jun-amino-terminal-(NH2)-Kinase (JNK) signaling are ectopically induced in cul-4 mutant clones, and these signals co-localize with the dying cells. Modulating levels of Wg and JNK signaling by using agonists and antagonists of these pathways demonstrated that activation of Wg and JNK signaling enhances cul-4 mutant phenotype, whereas downregulation of Wg and JNK signaling rescues the cul-4 mutant phenotypes of reduced eye. Here we present evidences to demonstrate that cul-4 is involved in restricting Wg signaling and downregulation of JNK signaling-mediated cell death during early eye development. Overall, our studies provide insights into a novel role of cul-4 in promoting cell survival in the developing Drosophila eye. PMID:28032862

Separate encoding of model-based and model-free valuations in the human brain.

PubMed

Beierholm, Ulrik R; Anen, Cedric; Quartz, Steven; Bossaerts, Peter

2011-10-01

Behavioral studies have long shown that humans solve problems in two ways, one intuitive and fast (System 1, model-free), and the other reflective and slow (System 2, model-based). The neurobiological basis of dual process problem solving remains unknown due to challenges of separating activation in concurrent systems. We present a novel neuroeconomic task that predicts distinct subjective valuation and updating signals corresponding to these two systems. We found two concurrent value signals in human prefrontal cortex: a System 1 model-free reinforcement signal and a System 2 model-based Bayesian signal. We also found a System 1 updating signal in striatal areas and a System 2 updating signal in lateral prefrontal cortex. Further, signals in prefrontal cortex preceded choices that are optimal according to either updating principle, while signals in anterior cingulate cortex and globus pallidus preceded deviations from optimal choice for reinforcement learning. These deviations tended to occur when uncertainty regarding optimal values was highest, suggesting that disagreement between dual systems is mediated by uncertainty rather than conflict, confirming recent theoretical proposals. Copyright © 2011 Elsevier Inc. All rights reserved.

Grb2 regulates B-cell maturation, B-cell memory responses and inhibits B-cell Ca2+ signalling.

PubMed

Ackermann, Jochen A; Radtke, Daniel; Maurberger, Anna; Winkler, Thomas H; Nitschke, Lars

2011-04-20

Grb2 is a ubiquitously expressed adaptor protein, which activates Ras and MAP kinases in growth factor receptor signalling, while in B-cell receptor (BCR) signalling this role is controversial. In B cell lines it was shown that Grb2 can inhibit BCR-induced Ca(2+) signalling. Nonetheless, the physiological role of Grb2 in primary B cells is still unknown. We generated a B-cell-specific Grb2-deficient mouse line, which had a severe reduction of mature follicular B cells in the periphery due to a differentiation block and decreased B-cell survival. Moreover, we found several changes in important signalling pathways: enhanced BCR-induced Ca(2+) signalling, alterations in mitogen-activated protein kinase activation patterns and strongly impaired Akt activation, the latter pointing towards a defect in PI3K signalling. Interestingly, B-cell-specific Grb2-deficient mice showed impaired IgG and B-cell memory responses, and impaired germinal centre formation. Thus, Grb2-dependent signalling pathways are crucial for lymphocyte differentiation processes, as well as for control of secondary humoral immune responses.

Ultrabroadband phased-array radio frequency (RF) receivers based on optical techniques

NASA Astrophysics Data System (ADS)

Overmiller, Brock M.; Schuetz, Christopher A.; Schneider, Garrett; Murakowski, Janusz; Prather, Dennis W.

2014-03-01

Military operations require the ability to locate and identify electronic emissions in the battlefield environment. However, recent developments in radio detection and ranging (RADAR) and communications technology are making it harder to effectively identify such emissions. Phased array systems aid in discriminating emitters in the scene by virtue of their relatively high-gain beam steering and nulling capabilities. For the purpose of locating emitters, we present an approach realize a broadband receiver based on optical processing techniques applied to the response of detectors in conformal antenna arrays. This approach utilizes photonic techniques that enable us to capture, route, and process the incoming signals. Optical modulators convert the incoming signals up to and exceeding 110 GHz with appreciable conversion efficiency and route these signals via fiber optics to a central processing location. This central processor consists of a closed loop phase control system which compensates for phase fluctuations induced on the fibers due to thermal or acoustic vibrations as well as an optical heterodyne approach for signal conversion down to baseband. Our optical heterodyne approach uses injection-locked paired optical sources to perform heterodyne downconversion/frequency identification of the detected emission. Preliminary geolocation and frequency identification testing of electronic emissions has been performed demonstrating the capabilities of our RF receiver.

Emotional decision-making in autism spectrum disorder: the roles of interoception and alexithymia.

PubMed

Shah, Punit; Catmur, Caroline; Bird, Geoffrey

2016-01-01

The way choices are framed influences decision-making. These "framing effects" emerge through the integration of emotional responses into decision-making under uncertainty. It was previously reported that susceptibility to the framing effect was reduced in individuals with autism spectrum disorder (ASD) due to a reduced tendency to incorporate emotional information into the decision-making process. However, recent research indicates that, where observed, emotional processing impairments in ASD may be due to co-occurring alexithymia. Alexithymia is thought to arise due to impaired interoception (the ability to perceive the internal state of one's body), raising the possibility that emotional signals are not perceived and thus not integrated into decision-making in those with alexithymia and that therefore reduced framing effects in ASD are a product of co-occurring alexithymia rather than ASD per se. Accordingly, the present study compared framing effects in autistic individuals with neurotypical controls matched for alexithymia. Results showed a marked deviation between groups. The framing effect was, in line with previous data, significantly smaller in autistic individuals, and there was no relationship between alexithymia or interoception and decision-making in the ASD group. In the neurotypical group, however, the size of the framing effect was associated with alexithymia and interoception, even after controlling for autistic traits. These results demonstrate that although framing effects are associated with interoception and alexithymia in the neurotypical population, emotional and interoceptive signals have less impact upon the decision-making process in ASD.

A simple method for estimating frequency response corrections for eddy covariance systems

Treesearch

W. J. Massman

2000-01-01

A simple analytical formula is developed for estimating the frequency attenuation of eddy covariance fluxes due to sensor response, path-length averaging, sensor separation, signal processing, and flux averaging periods. Although it is an approximation based on flat terrain cospectra, this analytical formula should have broader applicability than just flat-terrain...

Time Resolved Filtered Rayleigh Scattering Measurement of a Centrifugally Loaded Buoyant Jet

DTIC Science & Technology

2011-03-01

61 Figure 51. Sample CO2 Process Data: (a) Percent Concentration, ( b ) Concentration Profile, (c) Jet’s Trajectory...Standard Deviation and ( b ) Mean ................................. 64 Figure 54. Rayleigh-Scattering Signal Due to Air Associated with the First and...Second Laser Beams: (a) Raw Images and ( b ) Intensity Counts ........................................................................ 65 Figure 55

Improving Signal Detection using Allan and Theo Variances

NASA Astrophysics Data System (ADS)

Hardy, Andrew; Broering, Mark; Korsch, Wolfgang

2017-09-01

Precision measurements often deal with small signals buried within electronic noise. Extracting these signals can be enhanced through digital signal processing. Improving these techniques provide signal to noise ratios. Studies presently performed at the University of Kentucky are utilizing the electro-optic Kerr effect to understand cell charging effects within ultra-cold neutron storage cells. This work is relevant for the neutron electric dipole moment (nEDM) experiment at Oak Ridge National Laboratory. These investigations, and future investigations in general, will benefit from the illustrated improved analysis techniques. This project will showcase various methods for determining the optimum duration that data should be gathered for. Typically, extending the measuring time of an experimental run reduces the averaged noise. However, experiments also encounter drift due to fluctuations which mitigate the benefits of extended data gathering. Through comparing FFT averaging techniques, along with Allan and Theo variance measurements, quantifiable differences in signal detection will be presented. This research is supported by DOE Grants: DE-FG02-99ER411001, DE-AC05-00OR22725.

Comparison of digital signal-signal beat interference compensation techniques in direct-detection subcarrier modulation systems.

PubMed

Li, Zhe; Erkilinc, M Sezer; Galdino, Lidia; Shi, Kai; Thomsen, Benn C; Bayvel, Polina; Killey, Robert I

2016-12-12

Single-polarization direct-detection transceivers may offer advantages compared to digital coherent technology for some metro, back-haul, access and inter-data center applications since they offer low-cost and complexity solutions. However, a direct-detection receiver introduces nonlinearity upon photo detection, since it is a square-law device, which results in signal distortion due to signal-signal beat interference (SSBI). Consequently, it is desirable to develop effective and low-cost SSBI compensation techniques to improve the performance of such transceivers. In this paper, we compare the performance of a number of recently proposed digital signal processing-based SSBI compensation schemes, including the use of single- and two-stage linearization filters, an iterative linearization filter and a SSBI estimation and cancellation technique. Their performance is assessed experimentally using a 7 × 25 Gb/s wavelength division multiplexed (WDM) single-sideband 16-QAM Nyquist-subcarrier modulation system operating at a net information spectral density of 2.3 (b/s)/Hz.

Efficient Sparse Signal Transmission over a Lossy Link Using Compressive Sensing

PubMed Central

Wu, Liantao; Yu, Kai; Cao, Dongyu; Hu, Yuhen; Wang, Zhi

2015-01-01

Reliable data transmission over lossy communication link is expensive due to overheads for error protection. For signals that have inherent sparse structures, compressive sensing (CS) is applied to facilitate efficient sparse signal transmissions over lossy communication links without data compression or error protection. The natural packet loss in the lossy link is modeled as a random sampling process of the transmitted data, and the original signal will be reconstructed from the lossy transmission results using the CS-based reconstruction method at the receiving end. The impacts of packet lengths on transmission efficiency under different channel conditions have been discussed, and interleaving is incorporated to mitigate the impact of burst data loss. Extensive simulations and experiments have been conducted and compared to the traditional automatic repeat request (ARQ) interpolation technique, and very favorable results have been observed in terms of both accuracy of the reconstructed signals and the transmission energy consumption. Furthermore, the packet length effect provides useful insights for using compressed sensing for efficient sparse signal transmission via lossy links. PMID:26287195

FFT swept filtering: a bias-free method for processing fringe signals in absolute gravimeters

NASA Astrophysics Data System (ADS)

Křen, Petr; Pálinkáš, Vojtech; Mašika, Pavel; Val'ko, Miloš

2018-05-01

Absolute gravimeters, based on laser interferometry, are widely used for many applications in geoscience and metrology. Although currently the most accurate FG5 and FG5X gravimeters declare standard uncertainties at the level of 2-3 μGal, their inherent systematic errors affect the gravity reference determined by international key comparisons based predominately on the use of FG5-type instruments. The measurement results for FG5-215 and FG5X-251 clearly showed that the measured g-values depend on the size of the fringe signal and that this effect might be approximated by a linear regression with a slope of up to 0.030 μGal/mV . However, these empirical results do not enable one to identify the source of the effect or to determine a reasonable reference fringe level for correcting g-values in an absolute sense. Therefore, both gravimeters were equipped with new measuring systems (according to Křen et al. in Metrologia 53:27-40, 2016. https://doi.org/10.1088/0026-1394/53/1/27 applied for FG5), running in parallel with the original systems. The new systems use an analogue-to-digital converter HS5 to digitize the fringe signal and a new method of fringe signal analysis based on FFT swept bandpass filtering. We demonstrate that the source of the fringe size effect is connected to a distortion of the fringe signal due to the electronic components used in the FG5(X) gravimeters. To obtain a bias-free g-value, the FFT swept method should be applied for the determination of zero-crossings. A comparison of g-values obtained from the new and the original systems clearly shows that the original system might be biased by approximately 3-5 μGal due to improperly distorted fringe signal processing.

Joint Maximum Likelihood Time Delay Estimation of Unknown Event-Related Potential Signals for EEG Sensor Signal Quality Enhancement

PubMed Central

Kim, Kyungsoo; Lim, Sung-Ho; Lee, Jaeseok; Kang, Won-Seok; Moon, Cheil; Choi, Ji-Woong

2016-01-01

Electroencephalograms (EEGs) measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI) studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR) is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP) signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE) schemes based on a joint maximum likelihood (ML) criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°. PMID:27322267

Artifact Removal from Biosignal using Fixed Point ICA Algorithm for Pre-processing in Biometric Recognition

NASA Astrophysics Data System (ADS)

Mishra, Puneet; Singla, Sunil Kumar

2013-01-01

In the modern world of automation, biological signals, especially Electroencephalogram (EEG) and Electrocardiogram (ECG), are gaining wide attention as a source of biometric information. Earlier studies have shown that EEG and ECG show versatility with individuals and every individual has distinct EEG and ECG spectrum. EEG (which can be recorded from the scalp due to the effect of millions of neurons) may contain noise signals such as eye blink, eye movement, muscular movement, line noise, etc. Similarly, ECG may contain artifact like line noise, tremor artifacts, baseline wandering, etc. These noise signals are required to be separated from the EEG and ECG signals to obtain the accurate results. This paper proposes a technique for the removal of eye blink artifact from EEG and ECG signal using fixed point or FastICA algorithm of Independent Component Analysis (ICA). For validation, FastICA algorithm has been applied to synthetic signal prepared by adding random noise to the Electrocardiogram (ECG) signal. FastICA algorithm separates the signal into two independent components, i.e. ECG pure and artifact signal. Similarly, the same algorithm has been applied to remove the artifacts (Electrooculogram or eye blink) from the EEG signal.

Coherent and Noncoherent Joint Processing of Sonar for Detection of Small Targets in Shallow Water.

PubMed

Pan, Xiang; Jiang, Jingning; Li, Si; Ding, Zhenping; Pan, Chen; Gong, Xianyi

2018-04-10

A coherent-noncoherent joint processing framework is proposed for active sonar to combine diversity gain and beamforming gain for detection of a small target in shallow water environments. Sonar utilizes widely-spaced arrays to sense environments and illuminate a target of interest from multiple angles. Meanwhile, it exploits spatial diversity for time-reversal focusing to suppress reverberation, mainly strong bottom reverberation. For enhancement of robustness of time-reversal focusing, an adaptive iterative strategy is utilized in the processing framework. A probing signal is firstly transmitted and echoes of a likely target are utilized as steering vectors for the second transmission. With spatial diversity, target bearing and range are estimated using a broadband signal model. Numerical simulations show that the novel sonar outperforms the traditional phased-array sonar due to benefits of spatial diversity. The effectiveness of the proposed framework has been validated by localization of a small target in at-lake experiments.

Astrocytic control of synaptic function.

PubMed

Papouin, Thomas; Dunphy, Jaclyn; Tolman, Michaela; Foley, Jeannine C; Haydon, Philip G

2017-03-05

Astrocytes intimately interact with synapses, both morphologically and, as evidenced in the past 20 years, at the functional level. Ultrathin astrocytic processes contact and sometimes enwrap the synaptic elements, sense synaptic transmission and shape or alter the synaptic signal by releasing signalling molecules. Yet, the consequences of such interactions in terms of information processing in the brain remain very elusive. This is largely due to two major constraints: (i) the exquisitely complex, dynamic and ultrathin nature of distal astrocytic processes that renders their investigation highly challenging and (ii) our lack of understanding of how information is encoded by local and global fluctuations of intracellular calcium concentrations in astrocytes. Here, we will review the existing anatomical and functional evidence of local interactions between astrocytes and synapses, and how it underlies a role for astrocytes in the computation of synaptic information.This article is part of the themed issue 'Integrating Hebbian and homeostatic plasticity'. © 2017 The Author(s).

Endoplasmic Reticulum Stress, Calcium Dysregulation and Altered Protein Translation: Intersection of Processes That Contribute to Cancer Cachexia Induced Skeletal Muscle Wasting.

PubMed

Isaac, Stephanie T; Tan, Timothy C; Polly, Patsie

2016-01-01

Cancer cachexia is a debilitating paraneoplastic wasting syndrome characterized by skeletal muscle depletion and unintentional weight loss. It affects up to 50-80% of patients with cancer and directly accounts for one-quarter of cancer-related deaths due to cardio-respiratory failure. Muscle weakness, one of the hallmarks of this syndrome, has been postulated to be due to a combination of muscle breakdown, dysfunction and decrease in the ability to repair, with effective treatment strategies presently limited. Excessive inflammatory cytokine levels due to the host-tumor interaction, such as Interleukin (IL)-6 and Tumor Necrosis Factor (TNF)-α, are hypothesised to drive this pathological process but the specific mechanisms by which these cytokines produce skeletal muscle dysfunction in cancer cachexia remain undefined. Endoplasmic Reticulum (ER) stress and the associated disruptions in calcium signaling have been implicated in cytokine-mediated disruptions in skeletal muscle and function. Disrupted ER stress-related processes such as the Unfolded Protein Response (UPR), calcium homeostasis and altered muscle protein synthesis have been reported in clinical and experimental cachexia and other inflammation-driven muscle diseases such as myositis, potentially suggesting a link between increased IL-6 and TNF-α and ER stress in skeletal muscle cells. As the concept of upregulated ER stress in skeletal muscle cells due to elevated cytokines is novel and potentially very relevant to our understanding of cancer cachexia, this review aims to examine the potential relationship between inflammatory cytokine mediated muscle breakdown and ER stress, in the context of cancer cachexia, and to discuss the molecular signaling pathways underpinning this pathology.

Modeling VLF signal modulation during solar flares with GEANT4 Monte Carlo simulation, a simple chemical model and LWPC

NASA Astrophysics Data System (ADS)

Palit, Sourav; Chakrabarti, Sandip Kumar; Pal, Sujay; Basak, Tamal

Extra ionization by X-rays during solar flares affects VLF signal propagation through D-region ionosphere. Ionization produced in the lower ionosphere due to X-ray spectra of solar flares are simulated with an efficient detector simulation program, GEANT4. The balancing between the ionization and loss processes, causing the lower ionosphere to settle back to its undisturbed state is handled with a simple chemical model consisting of four broad species of ion densities. Using the electron densities, modified VLF signal amplitude is then computed with LWPC code. VLF signal along NWC (Australia) to IERC/ICSP (India) propagation path is examined during a M and a X-type solar flares and observational deviations are compared with simulated results. The agreement is found to be excellent.

Real-time optical fiber digital speckle pattern interferometry for industrial applications

NASA Astrophysics Data System (ADS)

Chan, Robert K.; Cheung, Y. M.; Lo, C. H.; Tam, T. K.

1997-03-01

There is current interest, especially in the industrial sector, to use the digital speckle pattern interferometry (DSPI) technique to measure surface stress. Indeed, many publications in the subject are evident of the growing interests in the field. However, to bring the technology to industrial use requires the integration of several emerging technologies, viz. optics, feedback control, electronics, imaging processing and digital signal processing. Due to the highly interdisciplinary nature of the technique, successful implementation and development require expertise in all of the fields. At Baptist University, under the funding of a major industrial grant, we are developing the technology for the industrial sector. Our system fully exploits optical fibers and diode lasers in the design to enable practical and rugged systems suited for industrial applications. Besides the development in optics, we have broken away from the reliance of a microcomputer PC platform for both image capture and processing, and have developed a digital signal processing array system that can handle simultaneous and independent image capture/processing with feedback control. The system, named CASPA for 'cascadable architecture signal processing array,' is a third generation development system that utilizes up to 7 digital signal processors has proved to be a very powerful system. With our CASPA we are now in a better position to developing novel optical measurement systems for industrial application that may require different measurement systems to operate concurrently and requiring information exchange between the systems. Applications in mind such as simultaneous in-plane and out-of-plane DSPI image capture/process, vibrational analysis with interactive DSPI and phase shifting control of optical systems are a few good examples of the potentials.

On the use of fractional order PK-PD models

NASA Astrophysics Data System (ADS)

Ionescu, Clara; Copot, Dana

2017-01-01

Quantifying and controlling depth of anesthesia is a challenging process due to lack of measurement technology for direct effects of drug supply into the body. Efforts are being made to develop new sensor techniques and new horizons are explored for modeling this intricate process. This paper introduces emerging tools available on the ‘engineering market’ imported from the area of fractional calculus. A novel interpretation of the classical drug-effect curve is given, enabling linear control. This enables broadening the horizon of signal processing and control techniques and suggests future research lines.

Cochlear implants: a remarkable past and a brilliant future

PubMed Central

Wilson, Blake S.; Dorman, Michael F.

2013-01-01

The aims of this paper are to (i) provide a brief history of cochlear implants; (ii) present a status report on the current state of implant engineering and the levels of speech understanding enabled by that engineering; (iii) describe limitations of current signal processing strategies and (iv) suggest new directions for research. With current technology the “average” implant patient, when listening to predictable conversations in quiet, is able to communicate with relative ease. However, in an environment typical of a workplace the average patient has a great deal of difficulty. Patients who are “above average” in terms of speech understanding, can achieve 100% correct scores on the most difficult tests of speech understanding in quiet but also have significant difficulty when signals are presented in noise. The major factors in these outcomes appear to be (i) a loss of low-frequency, fine structure information possibly due to the envelope extraction algorithms common to cochlear implant signal processing; (ii) a limitation in the number of effective channels of stimulation due to overlap in electric fields from electrodes, and (iii) central processing deficits, especially for patients with poor speech understanding. Two recent developments, bilateral implants and combined electric and acoustic stimulation, have promise to remediate some of the difficulties experienced by patients in noise and to reinstate low-frequency fine structure information. If other possibilities are realized, e.g., electrodes that emit drugs to inhibit cell death following trauma and to induce the growth of neurites toward electrodes, then the future is very bright indeed. PMID:18616994

A study of discrete control signal fault conditions in the shuttle DPS

NASA Technical Reports Server (NTRS)

Reddi, S. S.; Retter, C. T.

1976-01-01

An analysis of the effects of discrete failures on the data processing subsystem is presented. A functional description of each discrete together with a list of software modules that use this discrete are included. A qualitative description of the consequences that may ensue due to discrete failures is given followed by a probabilistic reliability analysis of the data processing subsystem. Based on the investigation conducted, recommendations were made to improve the reliability of the subsystem.

WE-G-204-01: BEST IN PHYSICS (IMAGING): Effect of Image Processing Parameters On Nodule Detectability in Chest Radiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Little, K; Lu, Z; MacMahon, H

Purpose: To investigate the effect of varying system image processing parameters on lung nodule detectability in digital radiography. Methods: An anthropomorphic chest phantom was imaged in the posterior-anterior position using a GE Discovery XR656 digital radiography system. To simulate lung nodules, a polystyrene board with 6.35mm diameter PMMA spheres was placed adjacent to the phantom (into the x-ray path). Due to magnification, the projected simulated nodules had a diameter in the radiographs of approximately 7.5 mm. The images were processed using one of GE’s default chest settings (Factory3) and reprocessed by varying the “Edge” and “Tissue Contrast” processing parameters, whichmore » were the two user-configurable parameters for a single edge and contrast enhancement algorithm. For each parameter setting, the nodule signals were calculated by subtracting the chest-only image from the image with simulated nodules. Twenty nodule signals were averaged, Gaussian filtered, and radially averaged in order to generate an approximately noiseless signal. For each processing parameter setting, this noise-free signal and 180 background samples from across the lung were used to estimate ideal observer performance in a signal-known-exactly detection task. Performance was estimated using a channelized Hotelling observer with 10 Laguerre-Gauss channel functions. Results: The “Edge” and “Tissue Contrast” parameters each had an effect on the detectability as calculated by the model observer. The CHO-estimated signal detectability ranged from 2.36 to 2.93 and was highest for “Edge” = 4 and “Tissue Contrast” = −0.15. In general, detectability tended to decrease as “Edge” was increased and as “Tissue Contrast” was increased. A human observer study should be performed to validate the relation to human detection performance. Conclusion: Image processing parameters can affect lung nodule detection performance in radiography. While validation with a human observer study is needed, model observer detectability for common tasks could provide a means for optimizing image processing parameters.« less

A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection

NASA Astrophysics Data System (ADS)

Bechet, P.; Mitran, R.; Munteanu, M.

2013-08-01

Non-contact methods for the assessment of vital signs are of great interest for specialists due to the benefits obtained in both medical and special applications, such as those for surveillance, monitoring, and search and rescue. This paper investigates the possibility of implementing a digital processing algorithm based on the MUSIC (Multiple Signal Classification) parametric spectral estimation in order to reduce the observation time needed to accurately measure the heart rate. It demonstrates that, by proper dimensioning the signal subspace, the MUSIC algorithm can be optimized in order to accurately assess the heart rate during an 8-28 s time interval. The validation of the processing algorithm performance was achieved by minimizing the mean error of the heart rate after performing simultaneous comparative measurements on several subjects. In order to calculate the error the reference value of heart rate was measured using a classic measurement system through direct contact.

A robust nonlinear filter for image restoration.

PubMed

Koivunen, V

1995-01-01

A class of nonlinear regression filters based on robust estimation theory is introduced. The goal of the filtering is to recover a high-quality image from degraded observations. Models for desired image structures and contaminating processes are employed, but deviations from strict assumptions are allowed since the assumptions on signal and noise are typically only approximately true. The robustness of filters is usually addressed only in a distributional sense, i.e., the actual error distribution deviates from the nominal one. In this paper, the robustness is considered in a broad sense since the outliers may also be due to inappropriate signal model, or there may be more than one statistical population present in the processing window, causing biased estimates. Two filtering algorithms minimizing a least trimmed squares criterion are provided. The design of the filters is simple since no scale parameters or context-dependent threshold values are required. Experimental results using both real and simulated data are presented. The filters effectively attenuate both impulsive and nonimpulsive noise while recovering the signal structure and preserving interesting details.

Simulation of optical signaling among nano-bio-sensors: enhancing of bioimaging contrast.

PubMed

SalmanOgli, A; Behzadi, S; Rostami, A

2014-09-01

In this article, the nanoparticle-dye systems is designed and simulated to illustrate the possibility of enhancement in optical imaging contrast. For this, the firefly optimization technique is used as an optical signaling mechanism among agents (nanoparticle-dye) because fireflies attract together due to their flashing light and optical signaling that is produced by a process of bioluminescence (also it has been investigated that other parameters such as neural response and brain function have essential role in attracting fireflies to each other). The first parameter is coincided with our work, because the nanoparticle-dye systems have ability to augment of received light and its amplification cause that the designed complex system act as a brightness particle. This induced behavior of nanoparticles can be considered as an optical communication and signaling. Indeed by functionalization of nanoparticles and then due to higher brightness of the tumor site because of active targeting, the other particles can be guided to reach toward the target point and the signaling among agents is done by optical relation similar to firefly nature. Moreover, the fundamental of this work is the use of surface plasmon resonance and plasmons hybridization, in which photonic signals can be manipulated on the nanoscale and can be used in biomedical applications such as electromagnetic field enhancement. Finally, it can be mentioned that by simultaneously using plasmon hybridization, near-field augmentation, and firefly algorithm, the optical imaging contrast can be impressively improved.

plasticity of TGF-β signaling

PubMed Central

2011-01-01

Background The family of TGF-β ligands is large and its members are involved in many different signaling processes. These signaling processes strongly differ in type with TGF-β ligands eliciting both sustained or transient responses. Members of the TGF-β family can also act as morphogen and cellular responses would then be expected to provide a direct read-out of the extracellular ligand concentration. A number of different models have been proposed to reconcile these different behaviours. We were interested to define the set of minimal modifications that are required to change the type of signal processing in the TGF-β signaling network. Results To define the key aspects for signaling plasticity we focused on the core of the TGF-β signaling network. With the help of a parameter screen we identified ranges of kinetic parameters and protein concentrations that give rise to transient, sustained, or oscillatory responses to constant stimuli, as well as those parameter ranges that enable a proportional response to time-varying ligand concentrations (as expected in the read-out of morphogens). A combination of a strong negative feedback and fast shuttling to the nucleus biases signaling to a transient rather than a sustained response, while oscillations were obtained if ligand binding to the receptor is weak and the turn-over of the I-Smad is fast. A proportional read-out required inefficient receptor activation in addition to a low affinity of receptor-ligand binding. We find that targeted modification of single parameters suffices to alter the response type. The intensity of a constant signal (i.e. the ligand concentration), on the other hand, affected only the strength but not the type of the response. Conclusions The architecture of the TGF-β pathway enables the observed signaling plasticity. The observed range of signaling outputs to TGF-β ligand in different cell types and under different conditions can be explained with differences in cellular protein concentrations and with changes in effective rate constants due to cross-talk with other signaling pathways. It will be interesting to uncover the exact cellular differences as well as the details of the cross-talks in future work. PMID:22051045

Electronic voltage and current transformers testing device.

PubMed

Pan, Feng; Chen, Ruimin; Xiao, Yong; Sun, Weiming

2012-01-01

A method for testing electronic instrument transformers is described, including electronic voltage and current transformers (EVTs, ECTs) with both analog and digital outputs. A testing device prototype is developed. It is based on digital signal processing of the signals that are measured at the secondary outputs of the tested transformer and the reference transformer when the same excitation signal is fed to their primaries. The test that estimates the performance of the prototype has been carried out at the National Centre for High Voltage Measurement and the prototype is approved for testing transformers with precision class up to 0.2 at the industrial frequency (50 Hz or 60 Hz). The device is suitable for on-site testing due to its high accuracy, simple structure and low-cost hardware.

Development of performance criteria for advanced Viking seismic experiments

NASA Technical Reports Server (NTRS)

1972-01-01

The characteristics and requirements of the seismic instrument for mapping the internal structure of the planet Mars are briefly described. The types of signals expected to exist are microseismic background generated by wind and pressure variations and thermal effects, disturbances of or in the landed vehicle, signals caused by faulting and volcanic activity, and signals due to meteoritic impacts. The advanced instrument package should include a short-period vertical component system, a long-period or wide-band 3-component system, a high frequency vertical component system, and a system for detection and rejection of lander noises. The Viking '75, Surveyor, and Apollo systems are briefly described as potential instruments to be considered for modification. Data processing and control systems are also summarized.

Analytical estimation of laser phase noise induced BER floor in coherent receiver with digital signal processing.

PubMed

Vanin, Evgeny; Jacobsen, Gunnar

2010-03-01

The Bit-Error-Ratio (BER) floor caused by the laser phase noise in the optical fiber communication system with differential quadrature phase shift keying (DQPSK) and coherent detection followed by digital signal processing (DSP) is analytically evaluated. An in-phase and quadrature (I&Q) receiver with a carrier phase recovery using DSP is considered. The carrier phase recovery is based on a phase estimation of a finite sum (block) of the signal samples raised to the power of four and the phase unwrapping at transitions between blocks. It is demonstrated that errors generated at block transitions cause the dominating contribution to the system BER floor when the impact of the additive noise is negligibly small in comparison with the effect of the laser phase noise. Even the BER floor in the case when the phase unwrapping is omitted is analytically derived and applied to emphasize the crucial importance of this signal processing operation. The analytical results are verified by full Monte Carlo simulations. The BER for another type of DQPSK receiver operation, which is based on differential phase detection, is also obtained in the analytical form using the principle of conditional probability. The principle of conditional probability is justified in the case of differential phase detection due to statistical independency of the laser phase noise induced signal phase error and the additive noise contributions. Based on the achieved analytical results the laser linewidth tolerance is calculated for different system cases.

Detection of essential hypertension with physiological signals from wearable devices.

PubMed

Ghosh, Arindam; Torres, Juan Manuel Mayor; Danieli, Morena; Riccardi, Giuseppe

2015-08-01

Early detection of essential hypertension can support the prevention of cardiovascular disease, a leading cause of death. The traditional method of identification of hypertension involves periodic blood pressure measurement using brachial cuff-based measurement devices. While these devices are non-invasive, they require manual setup for each measurement and they are not suitable for continuous monitoring. Research has shown that physiological signals such as Heart Rate Variability, which is a measure of the cardiac autonomic activity, is correlated with blood pressure. Wearable devices capable of measuring physiological signals such as Heart Rate, Galvanic Skin Response, Skin Temperature have recently become ubiquitous. However, these signals are not accurate and are prone to noise due to different artifacts. In this paper a) we present a data collection protocol for continuous non-invasive monitoring of physiological signals from wearable devices; b) we implement signal processing techniques for signal estimation; c) we explore how the continuous monitoring of these physiological signals can be used to identify hypertensive patients; d) We conduct a pilot study with a group of normotensive and hypertensive patients to test our techniques. We show that physiological signals extracted from wearable devices can distinguish between these two groups with high accuracy.

Impact of wave propagation delay on latency in optical communication systems

NASA Astrophysics Data System (ADS)

Kawanishi, Tetsuya; Kanno, Atsushi; Yoshida, Yuki; Kitayama, Ken-ichi

2012-12-01

Latency is an important figure to describe performance of transmission systems for particular applications, such as data transfer for earthquake early warning, transaction for financial businesses, interactive services such as online games, etc. Latency consists of delay due to signal processing at nodes and transmitters, and of signal propagation delay due to propagation of electromagnetic waves. The lower limit of the latency in transmission systems using conventional single mode fibers (SMFs) depends on wave propagation speed in the SMFs which is slower than c. Photonic crystal fibers, holly fibers and large core fibers can have low effective refractive indices, and can transfer light faster than in SMFs. In free-space optical systems, signals propagate with the speed c, so that the latency could be smaller than in optical fibers. For example, LEO satellites would transmit data faster than optical submarine cables, when the transmission distance is longer than a few thousand kilometers. This paper will discuss combination of various transmission media to reduce negative impact of the latency, as well as applications of low-latency systems.

Identification of the structure parameters using short-time non-stationary stochastic excitation

NASA Astrophysics Data System (ADS)

Jarczewska, Kamila; Koszela, Piotr; Śniady, PaweŁ; Korzec, Aleksandra

2011-07-01

In this paper, we propose an approach to the flexural stiffness or eigenvalue frequency identification of a linear structure using a non-stationary stochastic excitation process. The idea of the proposed approach lies within time domain input-output methods. The proposed method is based on transforming the dynamical problem into a static one by integrating the input and the output signals. The output signal is the structure reaction, i.e. structure displacements due to the short-time, irregular load of random type. The systems with single and multiple degrees of freedom, as well as continuous systems are considered.

How Chemical Synthesis of Ubiquitin Conjugates Helps To Understand Ubiquitin Signal Transduction.

PubMed

Hameed, Dharjath S; Sapmaz, Aysegul; Ovaa, Huib

2017-03-15

Ubiquitin (Ub) is a small post-translational modifier protein involved in a myriad of biochemical processes including DNA damage repair, proteasomal proteolysis, and cell cycle control. Ubiquitin signaling pathways have not been completely deciphered due to the complex nature of the enzymes involved in ubiquitin conjugation and deconjugation. Hence, probes and assay reagents are important to get a better understanding of this pathway. Recently, improvements have been made in synthesis procedures of Ub derivatives. In this perspective, we explain various research reagents available and how chemical synthesis has made an important contribution to Ub research.

Investigation of coherent receiver designs in high-speed optical inter-satellite links using digital signal processing

NASA Astrophysics Data System (ADS)

Schaefer, S.; Gregory, M.; Rosenkranz, W.

2017-09-01

Due to higher data rates, better data security and unlicensed spectral usage optical inter-satellite links (OISL) offer an attractive alternative to conventional RF-communication. However, the very high transmission distances necessitate an optical receiver design enabling high receiver sensitivity which requires careful carrier synchronization and a quasi-coherent detection scheme.

Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks

PubMed Central

Wang, Xue; Wang, Sheng; Bi, Dao-Wei; Ma, Jun-Jie

2007-01-01

Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.

Waveguide device and method for making same

DOEpatents

Forman, Michael A [San Francisco, CA

2007-08-14

A monolithic micromachined waveguide device or devices with low-loss, high-power handling, and near-optical frequency ranges is set forth. The waveguide and integrated devices are capable of transmitting near-optical frequencies due to optical-quality sidewall roughness. The device or devices are fabricated in parallel, may be mass produced using a LIGA manufacturing process, and may include a passive component such as a diplexer and/or an active capping layer capable of particularized signal processing of the waveforms propagated by the waveguide.

Video enhancement method with color-protection post-processing

NASA Astrophysics Data System (ADS)

Kim, Youn Jin; Kwak, Youngshin

2015-01-01

The current study is aimed to propose a post-processing method for video enhancement by adopting a color-protection technique. The color-protection intends to attenuate perceptible artifacts due to over-enhancements in visually sensitive image regions such as low-chroma colors, including skin and gray objects. In addition, reducing the loss in color texture caused by the out-of-color-gamut signals is also taken into account. Consequently, color reproducibility of video sequences could be remarkably enhanced while the undesirable visual exaggerations are minimized.

Statistical 21-cm Signal Separation via Gaussian Process Regression Analysis

NASA Astrophysics Data System (ADS)

Mertens, F. G.; Ghosh, A.; Koopmans, L. V. E.

2018-05-01

Detecting and characterizing the Epoch of Reionization and Cosmic Dawn via the redshifted 21-cm hyperfine line of neutral hydrogen will revolutionize the study of the formation of the first stars, galaxies, black holes and intergalactic gas in the infant Universe. The wealth of information encoded in this signal is, however, buried under foregrounds that are many orders of magnitude brighter. These must be removed accurately and precisely in order to reveal the feeble 21-cm signal. This requires not only the modeling of the Galactic and extra-galactic emission, but also of the often stochastic residuals due to imperfect calibration of the data caused by ionospheric and instrumental distortions. To stochastically model these effects, we introduce a new method based on `Gaussian Process Regression' (GPR) which is able to statistically separate the 21-cm signal from most of the foregrounds and other contaminants. Using simulated LOFAR-EoR data that include strong instrumental mode-mixing, we show that this method is capable of recovering the 21-cm signal power spectrum across the entire range k = 0.07 - 0.3 {h cMpc^{-1}}. The GPR method is most optimal, having minimal and controllable impact on the 21-cm signal, when the foregrounds are correlated on frequency scales ≳ 3 MHz and the rms of the signal has σ21cm ≳ 0.1 σnoise. This signal separation improves the 21-cm power-spectrum sensitivity by a factor ≳ 3 compared to foreground avoidance strategies and enables the sensitivity of current and future 21-cm instruments such as the Square Kilometre Array to be fully exploited.

Analog Module Architecture for Space-Qualified Field-Programmable Mixed-Signal Arrays

NASA Technical Reports Server (NTRS)

Edwards, R. Timothy; Strohbehn, Kim; Jaskulek, Steven E.; Katz, Richard

1999-01-01

Spacecraft require all manner of both digital and analog circuits. Onboard digital systems are constructed almost exclusively from field-programmable gate array (FPGA) circuits providing numerous advantages over discrete design including high integration density, high reliability, fast turn-around design cycle time, lower mass, volume, and power consumption, and lower parts acquisition and flight qualification costs. Analog and mixed-signal circuits perform tasks ranging from housekeeping to signal conditioning and processing. These circuits are painstakingly designed and built using discrete components due to a lack of options for field-programmability. FPAA (Field-Programmable Analog Array) and FPMA (Field-Programmable Mixed-signal Array) parts exist but not in radiation-tolerant technology and not necessarily in an architecture optimal for the design of analog circuits for spaceflight applications. This paper outlines an architecture proposed for an FPAA fabricated in an existing commercial digital CMOS process used to make radiation-tolerant antifuse-based FPGA devices. The primary concerns are the impact of the technology and the overall array architecture on the flexibility of programming, the bandwidth available for high-speed analog circuits, and the accuracy of the components for high-performance applications.

Challenges and opportunities for heavy scalar searches in the tt¯ channel at the LHC

DOE PAGES

Carena, Marcela; Liu, Zhen

2016-11-25

Heavy scalar and pseudoscalar resonance searches through themore » $$gg\\rightarrow S\\rightarrow t\\bar t$$ process are challenging due to the peculiar behavior of the large interference effects with the standard model $$t\\bar t$$ background. Such effects generate non-trivial lineshapes from additional relative phases between the signal and background amplitudes. We provide the analytic expressions for the differential cross sections to understand the interference effects in the heavy scalar signal lineshapes. We extend our study to the case of CP-violation and further consider the effect of bottom quarks in the production and decay processes. We also evaluate the contributions from additional particles to the gluon fusion production process, such as stops and vector-like quarks, that could lead to significant changes in the behavior of the signal lineshapes. Taking into account the large interference effects, we perform lineshape searches at the LHC and discuss the importance of the systematic uncertainties and smearing effects. Lastly, we present projected sensitivities for two LHC performance scenarios to probe the $$gg\\rightarrow S \\rightarrow t\\bar t$$ channel in various models.« less

Adaptive threshold shearlet transform for surface microseismic data denoising

NASA Astrophysics Data System (ADS)

Tang, Na; Zhao, Xian; Li, Yue; Zhu, Dan

2018-06-01

Random noise suppression plays an important role in microseismic data processing. The microseismic data is often corrupted by strong random noise, which would directly influence identification and location of microseismic events. Shearlet transform is a new multiscale transform, which can effectively process the low magnitude of microseismic data. In shearlet domain, due to different distributions of valid signals and random noise, shearlet coefficients can be shrunk by threshold. Therefore, threshold is vital in suppressing random noise. The conventional threshold denoising algorithms usually use the same threshold to process all coefficients, which causes noise suppression inefficiency or valid signals loss. In order to solve above problems, we propose the adaptive threshold shearlet transform (ATST) for surface microseismic data denoising. In the new algorithm, we calculate the fundamental threshold for each direction subband firstly. In each direction subband, the adjustment factor is obtained according to each subband coefficient and its neighboring coefficients, in order to adaptively regulate the fundamental threshold for different shearlet coefficients. Finally we apply the adaptive threshold to deal with different shearlet coefficients. The experimental denoising results of synthetic records and field data illustrate that the proposed method exhibits better performance in suppressing random noise and preserving valid signal than the conventional shearlet denoising method.

Wnt affects symmetry and morphogenesis during post-embryonic development in colonial chordates.

PubMed

Di Maio, Alessandro; Setar, Leah; Tiozzo, Stefano; De Tomaso, Anthony W

2015-01-01

Wnt signaling is one of the earliest and most highly conserved regulatory pathways for the establishment of the body axes during regeneration and early development. In regeneration, body axes determination occurs independently of tissue rearrangement and early developmental cues. Modulation of the Wnt signaling in either process has shown to result in unusual body axis phenotypes. Botryllus schlosseri is a colonial ascidian that can regenerate its entire body through asexual budding. This processes leads to an adult body via a stereotypical developmental pathway (called blastogenesis), without proceeding through any embryonic developmental stages. In this study, we describe the role of the canonical Wnt pathway during the early stages of asexual development. We characterized expression of three Wnt ligands (Wnt2B, Wnt5A, and Wnt9A) by in situ hybridization and qRT-PCR. Chemical manipulation of the pathway resulted in atypical budding due to the duplication of the A/P axes, supernumerary budding, and loss of the overall cell apical-basal polarity. Our results suggest that Wnt signaling is used for equivalent developmental processes both during embryogenesis and asexual development in an adult organism, suggesting that patterning mechanisms driving morphogenesis are conserved, independent of embryonic, or regenerative development.

A crossover trial comparing wide dynamic range compression and frequency compression in hearing aids for tinnitus therapy.

PubMed

Hodgson, Shirley-Anne; Herdering, Regina; Singh Shekhawat, Giriraj; Searchfield, Grant D

2017-01-01

It has been suggested that frequency lowering may be a superior tinnitus reducing digital signal processing (DSP) strategy in hearing aids than conventional amplification. A crossover trial was undertaken to determine if frequency compression (FC) was superior to wide dynamic range compression (WDRC) in reducing tinnitus. A 6-8-week crossover trial of two digital signal-processing techniques (WDRC and 2 WDRC with FC) was undertaken in 16 persons with high-frequency sensorineural hearing loss and chronic tinnitus. WDRC resulted in larger improvements in Tinnitus Functional Index and rating scale scores than WDRC with FC. The tinnitus improvements obtained with both processing types appear to be due to reduced hearing handicap and possibly decreased tinnitus audibility. Hearing aids are useful assistive devices in the rehabilitation of tinnitus. FC was very successful in a few individuals but was not superior to WDRC across the sample. It is recommended that WDRC remain as the default first choice tinnitus hearing aid processing strategy for tinnitus. FC should be considered as one of the many other options for selection based on individual hearing needs. Implications of Rehabilitation Hearing aids can significantly reduce the effects of tinnitus after 6-8 weeks of use. Addition of frequency compression digital signal processing does not appear superior to standard amplitude compression alone. Improvements in tinnitus were correlated with reductions in hearing handicap.

Method to improve the blade tip-timing accuracy of fiber bundle sensor under varying tip clearance

NASA Astrophysics Data System (ADS)

Duan, Fajie; Zhang, Jilong; Jiang, Jiajia; Guo, Haotian; Ye, Dechao

2016-01-01

Blade vibration measurement based on the blade tip-timing method has become an industry-standard procedure. Fiber bundle sensors are widely used for tip-timing measurement. However, the variation of clearance between the sensor and the blade will bring a tip-timing error to fiber bundle sensors due to the change in signal amplitude. This article presents methods based on software and hardware to reduce the error caused by the tip clearance change. The software method utilizes both the rising and falling edges of the tip-timing signal to determine the blade arrival time, and a calibration process suitable for asymmetric tip-timing signals is presented. The hardware method uses an automatic gain control circuit to stabilize the signal amplitude. Experiments are conducted and the results prove that both methods can effectively reduce the impact of tip clearance variation on the blade tip-timing and improve the accuracy of measurements.

Signal and noise modeling in confocal laser scanning fluorescence microscopy.

PubMed

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.

Seismic and acoustic signal identification algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

LADD,MARK D.; ALAM,M. KATHLEEN; SLEEFE,GERARD E.

2000-04-03

This paper will describe an algorithm for detecting and classifying seismic and acoustic signals for unattended ground sensors. The algorithm must be computationally efficient and continuously process a data stream in order to establish whether or not a desired signal has changed state (turned-on or off). The paper will focus on describing a Fourier based technique that compares the running power spectral density estimate of the data to a predetermined signature in order to determine if the desired signal has changed state. How to establish the signature and the detection thresholds will be discussed as well as the theoretical statisticsmore » of the algorithm for the Gaussian noise case with results from simulated data. Actual seismic data results will also be discussed along with techniques used to reduce false alarms due to the inherent nonstationary noise environments found with actual data.« less

A pause site for RNA polymerase II is associated with termination of transcription.

PubMed Central

Enriquez-Harris, P; Levitt, N; Briggs, D; Proudfoot, N J

1991-01-01

Termination of transcription by RNA polymerase II has been postulated to involve a pausing process. We have identified such a pause signal, 350 bp into the 3' flanking region of the human alpha 2 globin gene at a position where termination is thought to occur. We show that this pause signal enhances the utilization of an upstream poly(A) site which is otherwise out-competed by a stronger downstream poly(A) site. We also demonstrate that the pause site rescues a poly(A) site that is inactive due to its location within an intron. Using nuclear run-on analysis we show that elongating RNA polymerase II molecules accumulate over this pause signal. Furthermore we show that when the pause site is positioned immediately downstream of a strong poly(A) signal, significant levels of transcription termination take place. Images PMID:2050120

Electromyogram whitening for improved classification accuracy in upper limb prosthesis control.

PubMed

Liu, Lukai; Liu, Pu; Clancy, Edward A; Scheme, Erik; Englehart

2013-09-01

Time and frequency domain features of the surface electromyogram (EMG) signal acquired from multiple channels have frequently been investigated for use in controlling upper-limb prostheses. A common control method is EMG-based motion classification. We propose the use of EMG signal whitening as a preprocessing step in EMG-based motion classification. Whitening decorrelates the EMG signal and has been shown to be advantageous in other EMG applications including EMG amplitude estimation and EMG-force processing. In a study of ten intact subjects and five amputees with up to 11 motion classes and ten electrode channels, we found that the coefficient of variation of time domain features (mean absolute value, average signal length and normalized zero crossing rate) was significantly reduced due to whitening. When using these features along with autoregressive power spectrum coefficients, whitening added approximately five percentage points to classification accuracy when small window lengths were considered.

VLSI implementation of a new LMS-based algorithm for noise removal in ECG signal

NASA Astrophysics Data System (ADS)

Satheeskumaran, S.; Sabrigiriraj, M.

2016-06-01

Least mean square (LMS)-based adaptive filters are widely deployed for removing artefacts in electrocardiogram (ECG) due to less number of computations. But they posses high mean square error (MSE) under noisy environment. The transform domain variable step-size LMS algorithm reduces the MSE at the cost of computational complexity. In this paper, a variable step-size delayed LMS adaptive filter is used to remove the artefacts from the ECG signal for improved feature extraction. The dedicated digital Signal processors provide fast processing, but they are not flexible. By using field programmable gate arrays, the pipelined architectures can be used to enhance the system performance. The pipelined architecture can enhance the operation efficiency of the adaptive filter and save the power consumption. This technique provides high signal-to-noise ratio and low MSE with reduced computational complexity; hence, it is a useful method for monitoring patients with heart-related problem.

Magnetoencephalographic imaging of deep corticostriatal network activity during a rewards paradigm.

PubMed

Kanal, Eliezer Y; Sun, Mingui; Ozkurt, Tolga E; Jia, Wenyan; Sclabassi, Robert

2009-01-01

The human rewards network is a complex system spanning both cortical and subcortical regions. While much is known about the functions of the various components of the network, research on the behavior of the network as a whole has been stymied due to an inability to detect signals at a high enough temporal resolution from both superficial and deep network components simultaneously. In this paper, we describe the application of magnetoencephalographic imaging (MEG) combined with advanced signal processing techniques to this problem. Using data collected while subjects performed a rewards-related gambling paradigm demonstrated to activate the rewards network, we were able to identify neural signals which correspond to deep network activity. We also show that this signal was not observable prior to filtration. These results suggest that MEG imaging may be a viable tool for the detection of deep neural activity.

A unique role of endogenous visual-spatial attention in rapid processing of multiple targets

PubMed Central

Guzman, Emmanuel; Grabowecky, Marcia; Palafox, German; Suzuki, Satoru

2012-01-01

Visual spatial attention can be exogenously captured by a salient stimulus or can be endogenously allocated by voluntary effort. Whether these two attention modes serve distinctive functions is debated, but for processing of single targets the literature suggests superiority of exogenous attention (it is faster acting and serves more functions). We report that endogenous attention uniquely contributes to processing of multiple targets. For speeded visual discrimination, response times are faster for multiple redundant targets than for single targets due to probability summation and/or signal integration. This redundancy gain was unaffected when attention was exogenously diverted from the targets, but was completely eliminated when attention was endogenously diverted. This was not due to weaker manipulation of exogenous attention because our exogenous and endogenous cues similarly affected overall response times. Thus, whereas exogenous attention is superior for processing single targets, endogenous attention plays a unique role in allocating resources crucial for rapid concurrent processing of multiple targets. PMID:21517209

Continuous detection of weak sensory signals in afferent spike trains: the role of anti-correlated interspike intervals in detection performance.

PubMed

Goense, J B M; Ratnam, R

2003-10-01

An important problem in sensory processing is deciding whether fluctuating neural activity encodes a stimulus or is due to variability in baseline activity. Neurons that subserve detection must examine incoming spike trains continuously, and quickly and reliably differentiate signals from baseline activity. Here we demonstrate that a neural integrator can perform continuous signal detection, with performance exceeding that of trial-based procedures, where spike counts in signal- and baseline windows are compared. The procedure was applied to data from electrosensory afferents of weakly electric fish (Apteronotus leptorhynchus), where weak perturbations generated by small prey add approximately 1 spike to a baseline of approximately 300 spikes s(-1). The hypothetical postsynaptic neuron, modeling an electrosensory lateral line lobe cell, could detect an added spike within 10-15 ms, achieving near ideal detection performance (80-95%) at false alarm rates of 1-2 Hz, while trial-based testing resulted in only 30-35% correct detections at that false alarm rate. The performance improvement was due to anti-correlations in the afferent spike train, which reduced both the amplitude and duration of fluctuations in postsynaptic membrane activity, and so decreased the number of false alarms. Anti-correlations can be exploited to improve detection performance only if there is memory of prior decisions.

Nutritional Countermeasures Targeting Reactive Oxygen Species in Cancer: From Mechanisms to Biomarkers and Clinical Evidence

PubMed Central

Samoylenko, Anatoly; Hossain, Jubayer Al; Mennerich, Daniela; Kellokumpu, Sakari; Hiltunen, Jukka Kalervo

2013-01-01

Abstract Reactive oxygen species (ROS) exert various biological effects and contribute to signaling events during physiological and pathological processes. Enhanced levels of ROS are highly associated with different tumors, a Western lifestyle, and a nutritional regime. The supplementation of food with traditional antioxidants was shown to be protective against cancer in a number of studies both in vitro and in vivo. However, recent large-scale human trials in well-nourished populations did not confirm the beneficial role of antioxidants in cancer, whereas there is a well-established connection between longevity of several human populations and increased amount of antioxidants in their diets. Although our knowledge about ROS generators, ROS scavengers, and ROS signaling has improved, the knowledge about the direct link between nutrition, ROS levels, and cancer is limited. These limitations are partly due to lack of standardized reliable ROS measurement methods, easily usable biomarkers, knowledge of ROS action in cellular compartments, and individual genetic predispositions. The current review summarizes ROS formation due to nutrition with respect to macronutrients and antioxidant micronutrients in the context of cancer and discusses signaling mechanisms, used biomarkers, and its limitations along with large-scale human trials. Antioxid. Redox Signal. 19, 2157–2196. PMID:23458328

Development and programming of Geophonino: A low cost Arduino-based seismic recorder for vertical geophones

NASA Astrophysics Data System (ADS)

Soler-Llorens, J. L.; Galiana-Merino, J. J.; Giner-Caturla, J.; Jauregui-Eslava, P.; Rosa-Cintas, S.; Rosa-Herranz, J.

2016-09-01

The commercial data acquisition systems used for seismic exploration are usually expensive equipment. In this work, a low cost data acquisition system (Geophonino) has been developed for recording seismic signals from a vertical geophone. The signal goes first through an instrumentation amplifier, INA155, which is suitable for low amplitude signals like the seismic noise, and an anti-aliasing filter based on the MAX7404 switched-capacitor filter. After that, the amplified and filtered signal is digitized and processed by Arduino Due and registered in an SD memory card. Geophonino is configured for continuous registering, where the sampling frequency, the amplitude gain and the registering time are user-defined. The complete prototype is an open source and open hardware system. It has been tested by comparing the registered signals with the ones obtained through different commercial data recording systems and different kind of geophones. The obtained results show good correlation between the tested measurements, presenting Geophonino as a low-cost alternative system for seismic data recording.

Photon correlation in single-photon frequency upconversion.

PubMed

Gu, Xiaorong; Huang, Kun; Pan, Haifeng; Wu, E; Zeng, Heping

2012-01-30

We experimentally investigated the intensity cross-correlation between the upconverted photons and the unconverted photons in the single-photon frequency upconversion process with multi-longitudinal mode pump and signal sources. In theoretical analysis, with this multi-longitudinal mode of both signal and pump sources system, the properties of the signal photons could also be maintained as in the single-mode frequency upconversion system. Experimentally, based on the conversion efficiency of 80.5%, the joint probability of simultaneously detecting at upconverted and unconverted photons showed an anti-correlation as a function of conversion efficiency which indicated the upconverted photons were one-to-one from the signal photons. While due to the coherent state of the signal photons, the intensity cross-correlation function g(2)(0) was shown to be equal to unity at any conversion efficiency, agreeing with the theoretical prediction. This study will benefit the high-speed wavelength-tunable quantum state translation or photonic quantum interface together with the mature frequency tuning or longitudinal mode selection techniques.

Analysis of cerebral vessels dynamics using experimental data with missed segments

NASA Astrophysics Data System (ADS)

Pavlova, O. N.; Abdurashitov, A. S.; Ulanova, M. V.; Shihalov, G. M.; Semyachkina-Glushkovskaya, O. V.; Pavlov, A. N.

2018-04-01

Physiological signals often contain various bad segments that occur due to artifacts, failures of the recording equipment or varying experimental conditions. The related experimental data need to be preprocessed to avoid such parts of recordings. In the case of few bad segments, they can simply be removed from the signal and its analysis is further performed. However, when there are many extracted segments, the internal structure of the analyzed physiological process may be destroyed, and it is unclear whether such signal can be used in diagnostic-related studies. In this paper we address this problem for the case of cerebral vessels dynamics. We perform analysis of simulated data in order to reveal general features of quantifying scaling features of complex signals with distinct correlation properties and show that the effects of data loss are significantly different for experimental data with long-range correlations and anti-correlations. We conclude that the cerebral vessels dynamics is significantly less sensitive to missed data fragments as compared with signals with anti-correlated statistics.

A Novel DFT-Based DOA Estimation by a Virtual Array Extension Using Simple Multiplications for FMCW Radar

PubMed Central

Kim, Bongseok; Kim, Sangdong; Lee, Jonghun

2018-01-01

We propose a novel discrete Fourier transform (DFT)-based direction of arrival (DOA) estimation by a virtual array extension using simple multiplications for frequency modulated continuous wave (FMCW) radar. DFT-based DOA estimation is usually employed in radar systems because it provides the advantage of low complexity for real-time signal processing. In order to enhance the resolution of DOA estimation or to decrease the missing detection probability, it is essential to have a considerable number of channel signals. However, due to constraints of space and cost, it is not easy to increase the number of channel signals. In order to address this issue, we increase the number of effective channel signals by generating virtual channel signals using simple multiplications of the given channel signals. The increase in channel signals allows the proposed scheme to detect DOA more accurately than the conventional scheme while using the same number of channel signals. Simulation results show that the proposed scheme achieves improved DOA estimation compared to the conventional DFT-based method. Furthermore, the effectiveness of the proposed scheme in a practical environment is verified through the experiment. PMID:29758016

A space-based classification system for RF transients

NASA Astrophysics Data System (ADS)

Moore, K. R.; Call, D.; Johnson, S.; Payne, T.; Ford, W.; Spencer, K.; Wilkerson, J. F.; Baumgart, C.

The FORTE (Fast On-Orbit Recording of Transient Events) small satellite is scheduled for launch in mid 1995. The mission is to measure and classify VHF (30-300 MHz) electromagnetic pulses, primarily due to lightning, within a high noise environment dominated by continuous wave carriers such as TV and FM stations. The FORTE Event Classifier will use specialized hardware to implement signal processing and neural network algorithms that perform onboard classification of RF transients and carriers. Lightning events will also be characterized with optical data telemetered to the ground. A primary mission science goal is to develop a comprehensive understanding of the correlation between the optical flash and the VHF emissions from lightning. By combining FORTE measurements with ground measurements and/or active transmitters, other science issues can be addressed. Examples include the correlation of global precipitation rates with lightning flash rates and location, the effects of large scale structures within the ionosphere (such as traveling ionospheric disturbances and horizontal gradients in the total electron content) on the propagation of broad bandwidth RF signals, and various areas of lightning physics. Event classification is a key feature of the FORTE mission. Neural networks are promising candidates for this application. The authors describe the proposed FORTE Event Classifier flight system, which consists of a commercially available digital signal processing board and a custom board, and discuss work on signal processing and neural network algorithms.

Iron-mediated redox modulation in neural plasticity

PubMed Central

Muñoz, Pablo

2012-01-01

The role of iron in brain physiology has focused on the neuropathological, effects due to iron-induced oxidative stress. However, our recent work has established a physiological relationship between the iron-mediated oxidative modification and normal neuronal function. Our results obtained from hippocampal neurons, suggest that iron-generated reactive species oxygen (ROS) are involved in calcium signaling initiated by stimulation of NMDA receptors. This signal is amplified by ryanodine receptors (RyR), a redox- sensitive calcium channel, allowing the phosphorylation and nuclear translocation of ERK1/2. Furthermore, using electrophysiological approaches, we showed that iron is required for basal synaptic transmission and full expression of long-term potentiation, a type of synaptic plasticity. Our data combined suggest that the oxidative effect of iron is critical to activate processes that are downstream of NMDAR activation. Finally, due to the high reactivity of DNA with iron-generated ROS, we hypothesize an additional function of iron in gene regulation. PMID:22808323

Tissue Pulsatility Imaging of Cerebral Vasoreactivity during Hyperventilation

PubMed Central

Kucewicz, John C.; Dunmire, Barbrina; Giardino, Nicholas D.; Leotta, Daniel F.; Paun, Marla; Dager, Stephen R.; Beach, Kirk W.

2008-01-01

Tissue Pulsatility Imaging (TPI) is an ultrasonic technique that is being developed at the University of Washington to measure tissue displacement or strain due to blood flow over the cardiac and respiratory cycles. This technique is based in principle on plethysmography, an older non-ultrasound technology for measuring expansion of a whole limb or body part due to perfusion. TPI adapts tissue Doppler signal processing methods to measure the “plethysmographic” signal from hundreds or thousands of sample volumes in an ultrasound image plane. This paper presents a feasibility study to determine if TPI can be used to assess cerebral vasoreactivity. Ultrasound data were collected transcranially through the temporal acoustic window from four subjects before, during, and after voluntary hyperventilation. In each subject, decreases in tissue pulsatility during hyperventilation were observed that were statistically correlated with the subject’s end-tidal CO2 measurements. PMID:18336991

Regulatory Peptides in Plants.

PubMed

Vanyushin, B F; Ashapkin, V V; Aleksandrushkina, N I

2017-02-01

Many different peptides regulating cell differentiation, growth, and development are found in plants. Peptides participate in regulation of plant ontogenesis starting from pollination, pollen tube growth, and the very early stages of embryogenesis, including formation of embryo and endosperm. They direct differentiation of meristematic stem cells, formation of tissues and individual organs, take part in regulation of aging, fruit maturation, and abscission of plant parts associated with apoptosis. Biological activity of peptides is observed at very low concentrations, and it has mainly signal nature and hormonal character. "Mature" peptides appear mainly due to processing of protein precursors with (or without) additional enzymatic modifications. Plant peptides differ in origin, structure, and functional properties. Their specific action is due to binding with respective receptors and interactions with various proteins and other factors. Peptides can also regulate physiological functions by direct peptide-protein interactions. Peptide action is coordinated with the action of known phytohormones (auxins, cytokinins, and others); thus, peptides control phytohormonal signal pathways.

Performance Analysis of a Hardware Implemented Complex Signal Kurtosis Radio-Frequency Interference Detector

NASA Technical Reports Server (NTRS)

Schoenwald, Adam J.; Bradley, Damon C.; Mohammed, Priscilla N.; Piepmeier, Jeffrey R.; Wong, Mark

2016-01-01

Radio-frequency interference (RFI) is a known problem for passive remote sensing as evidenced in the L-band radiometers SMOS, Aquarius and more recently, SMAP. Various algorithms have been developed and implemented on SMAP to improve science measurements. This was achieved by the use of a digital microwave radiometer. RFI mitigation becomes more challenging for microwave radiometers operating at higher frequencies in shared allocations. At higher frequencies larger bandwidths are also desirable for lower measurement noise further adding to processing challenges. This work focuses on finding improved RFI mitigation techniques that will be effective at additional frequencies and at higher bandwidths. To aid the development and testing of applicable detection and mitigation techniques, a wide-band RFI algorithm testing environment has been developed using the Reconfigurable Open Architecture Computing Hardware System (ROACH) built by the Collaboration for Astronomy Signal Processing and Electronics Research (CASPER) Group. The testing environment also consists of various test equipment used to reproduce typical signals that a radiometer may see including those with and without RFI. The testing environment permits quick evaluations of RFI mitigation algorithms as well as show that they are implementable in hardware. The algorithm implemented is a complex signal kurtosis detector which was modeled and simulated. The complex signal kurtosis detector showed improved performance over the real kurtosis detector under certain conditions. The real kurtosis is implemented on SMAP at 24 MHz bandwidth. The complex signal kurtosis algorithm was then implemented in hardware at 200 MHz bandwidth using the ROACH. In this work, performance of the complex signal kurtosis and the real signal kurtosis are compared. Performance evaluations and comparisons in both simulation as well as experimental hardware implementations were done with the use of receiver operating characteristic (ROC) curves. The complex kurtosis algorithm has the potential to reduce data rate due to onboard processing in addition to improving RFI detection performance.

Ciliates learn to diagnose and correct classical error syndromes in mating strategies

PubMed Central

Clark, Kevin B.

2013-01-01

Preconjugal ciliates learn classical repetition error-correction codes to safeguard mating messages and replies from corruption by “rivals” and local ambient noise. Because individual cells behave as memory channels with Szilárd engine attributes, these coding schemes also might be used to limit, diagnose, and correct mating-signal errors due to noisy intracellular information processing. The present study, therefore, assessed whether heterotrich ciliates effect fault-tolerant signal planning and execution by modifying engine performance, and consequently entropy content of codes, during mock cell–cell communication. Socially meaningful serial vibrations emitted from an ambiguous artificial source initiated ciliate behavioral signaling performances known to advertise mating fitness with varying courtship strategies. Microbes, employing calcium-dependent Hebbian-like decision making, learned to diagnose then correct error syndromes by recursively matching Boltzmann entropies between signal planning and execution stages via “power” or “refrigeration” cycles. All eight serial contraction and reversal strategies incurred errors in entropy magnitude by the execution stage of processing. Absolute errors, however, subtended expected threshold values for single bit-flip errors in three-bit replies, indicating coding schemes protected information content throughout signal production. Ciliate preparedness for vibrations selectively and significantly affected the magnitude and valence of Szilárd engine performance during modal and non-modal strategy corrective cycles. But entropy fidelity for all replies mainly improved across learning trials as refinements in engine efficiency. Fidelity neared maximum levels for only modal signals coded in resilient three-bit repetition error-correction sequences. Together, these findings demonstrate microbes can elevate survival/reproductive success by learning to implement classical fault-tolerant information processing in social contexts. PMID:23966987

Electrochemical Biosensors - Sensor Principles and Architectures

PubMed Central

Grieshaber, Dorothee; MacKenzie, Robert; Vörös, Janos; Reimhult, Erik

2008-01-01

Quantification of biological or biochemical processes are of utmost importance for medical, biological and biotechnological applications. However, converting the biological information to an easily processed electronic signal is challenging due to the complexity of connecting an electronic device directly to a biological environment. Electrochemical biosensors provide an attractive means to analyze the content of a biological sample due to the direct conversion of a biological event to an electronic signal. Over the past decades several sensing concepts and related devices have been developed. In this review, the most common traditional techniques, such as cyclic voltammetry, chronoamperometry, chronopotentiometry, impedance spectroscopy, and various field-effect transistor based methods are presented along with selected promising novel approaches, such as nanowire or magnetic nanoparticle-based biosensing. Additional measurement techniques, which have been shown useful in combination with electrochemical detection, are also summarized, such as the electrochemical versions of surface plasmon resonance, optical waveguide lightmode spectroscopy, ellipsometry, quartz crystal microbalance, and scanning probe microscopy. The signal transduction and the general performance of electrochemical sensors are often determined by the surface architectures that connect the sensing element to the biological sample at the nanometer scale. The most common surface modification techniques, the various electrochemical transduction mechanisms, and the choice of the recognition receptor molecules all influence the ultimate sensitivity of the sensor. New nanotechnology-based approaches, such as the use of engineered ion-channels in lipid bilayers, the encapsulation of enzymes into vesicles, polymersomes, or polyelectrolyte capsules provide additional possibilities for signal amplification. In particular, this review highlights the importance of the precise control over the delicate interplay between surface nano-architectures, surface functionalization and the chosen sensor transducer principle, as well as the usefulness of complementary characterization tools to interpret and to optimize the sensor response. PMID:27879772

Brassinosteroid signaling-dependent root responses to prolonged elevated ambient temperature.

PubMed

Martins, Sara; Montiel-Jorda, Alvaro; Cayrel, Anne; Huguet, Stéphanie; Roux, Christine Paysant-Le; Ljung, Karin; Vert, Grégory

2017-08-21

Due to their sessile nature, plants have to cope with and adjust to their fluctuating environment. Temperature elevation stimulates the growth of Arabidopsis aerial parts. This process is mediated by increased biosynthesis of the growth-promoting hormone auxin. How plant roots respond to elevated ambient temperature is however still elusive. Here we present strong evidence that temperature elevation impinges on brassinosteroid hormone signaling to alter root growth. We show that elevated temperature leads to increased root elongation, independently of auxin or factors known to drive temperature-mediated shoot growth. We further demonstrate that brassinosteroid signaling regulates root responses to elevated ambient temperature. Increased growth temperature specifically impacts on the level of the brassinosteroid receptor BRI1 to downregulate brassinosteroid signaling and mediate root elongation. Our results establish that BRI1 integrates temperature and brassinosteroid signaling to regulate root growth upon long-term changes in environmental conditions associated with global warming.Moderate heat stimulates the growth of Arabidopsis shoots in an auxin-dependent manner. Here, Martins et al. show that elevated ambient temperature modifies root growth by reducing the BRI1 brassinosteroid-receptor protein level and downregulating brassinosteroid signaling.

Improved EEG Event Classification Using Differential Energy.

PubMed

Harati, A; Golmohammadi, M; Lopez, S; Obeid, I; Picone, J

2015-12-01

Feature extraction for automatic classification of EEG signals typically relies on time frequency representations of the signal. Techniques such as cepstral-based filter banks or wavelets are popular analysis techniques in many signal processing applications including EEG classification. In this paper, we present a comparison of a variety of approaches to estimating and postprocessing features. To further aid in discrimination of periodic signals from aperiodic signals, we add a differential energy term. We evaluate our approaches on the TUH EEG Corpus, which is the largest publicly available EEG corpus and an exceedingly challenging task due to the clinical nature of the data. We demonstrate that a variant of a standard filter bank-based approach, coupled with first and second derivatives, provides a substantial reduction in the overall error rate. The combination of differential energy and derivatives produces a 24 % absolute reduction in the error rate and improves our ability to discriminate between signal events and background noise. This relatively simple approach proves to be comparable to other popular feature extraction approaches such as wavelets, but is much more computationally efficient.

Methods to detect, characterize, and remove motion artifact in resting state fMRI

PubMed Central

Power, Jonathan D; Mitra, Anish; Laumann, Timothy O; Snyder, Abraham Z; Schlaggar, Bradley L; Petersen, Steven E

2013-01-01

Head motion systematically alters correlations in resting state functional connectivity fMRI (RSFC). In this report we examine impact of motion on signal intensity and RSFC correlations. We find that motion-induced signal changes (1) are often complex and variable waveforms, (2) are often shared across nearly all brain voxels, and (3) often persist more than 10 seconds after motion ceases. These signal changes, both during and after motion, increase observed RSFC correlations in a distance-dependent manner. Motion-related signal changes are not removed by a variety of motion-based regressors, but are effectively reduced by global signal regression. We link several measures of data quality to motion, changes in signal intensity, and changes in RSFC correlations. We demonstrate that improvements in data quality measures during processing may represent cosmetic improvements rather than true correction of the data. We demonstrate a within-subject, censoring-based artifact removal strategy based on volume censoring that reduces group differences due to motion to chance levels. We note conditions under which group-level regressions do and do not correct motion-related effects. PMID:23994314

Effects of wear on structure-sensitive magnetic properties of ceramic ferrite in contact with magnetic tape

NASA Technical Reports Server (NTRS)

Miyoshi, K.; Buckley, D. H.; Tanaka, K.

1985-01-01

Wear experiments and electron microscopy and diffraction studies were conducted to examine the wear and deformed layers in single-crystal Mn-Zn (ceramic) ferrite magnetic head material in contact with magnetic tape and the effects of that contact on magnetic properties. The crystalline state of the single-crystal magnetic head was changed drastically during the sliding process. A nearly amorphous structure was produced on its wear surface. Deformation in the surficial layer of the magnetic head was a critical factor in readback signal loss above 2.5 dB. The signal output level was reduced as applied normal load was increased. Considerable plastic flow occurred on the magnetic tape surface with sliding, and the signal loss due to the tape wear was approximately 1 dB.

Ecological prediction with nonlinear multivariate time-frequency functional data models

USGS Publications Warehouse

Yang, Wen-Hsi; Wikle, Christopher K.; Holan, Scott H.; Wildhaber, Mark L.

2013-01-01

Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.

Electronic Voltage and Current Transformers Testing Device

PubMed Central

Pan, Feng; Chen, Ruimin; Xiao, Yong; Sun, Weiming

2012-01-01

A method for testing electronic instrument transformers is described, including electronic voltage and current transformers (EVTs, ECTs) with both analog and digital outputs. A testing device prototype is developed. It is based on digital signal processing of the signals that are measured at the secondary outputs of the tested transformer and the reference transformer when the same excitation signal is fed to their primaries. The test that estimates the performance of the prototype has been carried out at the National Centre for High Voltage Measurement and the prototype is approved for testing transformers with precision class up to 0.2 at the industrial frequency (50 Hz or 60 Hz). The device is suitable for on-site testing due to its high accuracy, simple structure and low-cost hardware. PMID:22368510

Effect of signal jitter on the spectrum of rotor impulsive noise

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.

1987-01-01

The effect of randomness or jitter of the acoustic waveform on the spectrum of rotor impulsive noise is studied because of its importance for data interpretation. An acoustic waveform train is modelled representing rotor impulsive noise. The amplitude, shape, and period between occurrences of individual pulses are allowed to be randomized assuming normal probability distributions. Results, in terms of the standard deviations of the variable quantities, are given for the autospectrum as well as special processed spectra designed to separate harmonic and broadband rotor noise components. Consideration is given to the effect of accuracy in triggering or keying to a rotor one per revolution signal. An example is given showing the resultant spectral smearing at the high frequencies due to the pulse signal period variability.

Effect of signal jitter on the spectrum of rotor impulsive noise

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.

1988-01-01

The effect of randomness or jitter of the acoustic waveform on the spectrum of rotor impulsive noise is studied because of its importance for data interpretation. An acoustic waveform train is modeled representing rotor impulsive noise. The amplitude, shape, and period between occurrences of individual pulses are allowed to be randomized assuming normal probability distributions. Results, in terms of the standard deviations of the variable quantities, are given for the autospectrum as well as special processed spectra designed to separate harmonic and broadband rotor noise components. Consideration is given to the effect of accuracy in triggering or keying to a rotor one per revolution signal. An example is given showing the resultant spectral smearing at the high frequencies due to the pulse signal period variability.

Attenuation of dopamine-modulated prefrontal value signals underlies probabilistic reward learning deficits in old age

PubMed Central

Axelsson, Jan; Riklund, Katrine; Nyberg, Lars; Dayan, Peter; Bäckman, Lars

2017-01-01

Probabilistic reward learning is characterised by individual differences that become acute in aging. This may be due to age-related dopamine (DA) decline affecting neural processing in striatum, prefrontal cortex, or both. We examined this by administering a probabilistic reward learning task to younger and older adults, and combining computational modelling of behaviour, fMRI and PET measurements of DA D1 availability. We found that anticipatory value signals in ventromedial prefrontal cortex (vmPFC) were attenuated in older adults. The strength of this signal predicted performance beyond age and was modulated by D1 availability in nucleus accumbens. These results uncover that a value-anticipation mechanism in vmPFC declines in aging, and that this mechanism is associated with DA D1 receptor availability. PMID:28870286

Sources and Radiation Patterns of Volcano-Acoustic Signals Investigated with Field-Scale Chemical Explosions

NASA Astrophysics Data System (ADS)

Bowman, D. C.; Lees, J. M.; Taddeucci, J.; Graettinger, A. H.; Sonder, I.; Valentine, G.

2014-12-01

We investigate the processes that give rise to complex acoustic signals during volcanic blasts by monitoring buried chemical explosions with infrasound and audio range microphones, strong motion sensors, and high speed imagery. Acoustic waveforms vary with scaled depth of burial (SDOB, units in meters per cube root of joules), ranging from high amplitude, impulsive, gas expansion dominated signals at low SDOB to low amplitude, longer duration, ground motion dominated signals at high SDOB. Typically, the sudden upward acceleration of the substrate above the blast produces the first acoustic arrival, followed by a second pulse due to the eruption of pressurized gas at the surface. Occasionally, a third overpressure occurs when displaced material decelerates upon impact with the ground. The transition between ground motion dominated and gas release dominated acoustics ranges between 0.0038-0.0018 SDOB, respectively. For example, one explosion registering an SDOB=0.0031 produced two overpressure pulses of approximately equal amplitude, one due to ground motion, the other to gas release. Recorded volcano infrasound has also identified distinct ground motion and gas release components during explosions at Sakurajima, Santiaguito, and Karymsky volcanoes. Our results indicate that infrasound records may provide a proxy for the depth and energy of these explosions. Furthermore, while magma fragmentation models indicate the possibility of several explosions during a single vulcanian eruption (Alidibirov, Bull Volc., 1994), our results suggest that a single explosion can also produce complex acoustic signals. Thus acoustic records alone cannot be used to distinguish between single explosions and multiple closely-spaced blasts at volcanoes. Results from a series of lateral blasts during the 2014 field experiment further indicates whether vent geometry can produce directional acoustic radiation patterns like those observed at Tungarahua volcano (Kim et al., GJI, 2012). Beside infrasonic radiation, our multiparametric dataset also allowed us to investigate other acoustic processes relevant for explosive eruptions, including shock-wave generation and audible sound radiation, and to link them to the starting conditions and evolution of the blasts.

Design and Experimental Evaluation of a Non-Invasive Microwave Head Imaging System for Intracranial Haemorrhage Detection

PubMed Central

Mobashsher, A. T.; Bialkowski, K. S.; Abbosh, A. M.; Crozier, S.

2016-01-01

An intracranial haemorrhage is a life threatening medical emergency, yet only a fraction of the patients receive treatment in time, primarily due to the transport delay in accessing diagnostic equipment in hospitals such as Magnetic Resonance Imaging or Computed Tomography. A mono-static microwave head imaging system that can be carried in an ambulance for the detection and localization of intracranial haemorrhage is presented. The system employs a single ultra-wideband antenna as sensing element to transmit signals in low microwave frequencies towards the head and capture backscattered signals. The compact and low-profile antenna provides stable directional radiation patterns over the operating bandwidth in both near and far-fields. Numerical analysis of the head imaging system with a realistic head model in various situations is performed to realize the scattering mechanism of haemorrhage. A modified delay-and-summation back-projection algorithm, which includes effects of surface waves and a distance-dependent effective permittivity model, is proposed for signal and image post-processing. The efficacy of the automated head imaging system is evaluated using a 3D-printed human head phantom with frequency dispersive dielectric properties including emulated haemorrhages with different sizes located at different depths. Scattered signals are acquired with a compact transceiver in a mono-static circular scanning profile. The reconstructed images demonstrate that the system is capable of detecting haemorrhages as small as 1 cm3. While quantitative analyses reveal that the quality of images gradually degrades with the increase of the haemorrhage’s depth due to the reduction of signal penetration inside the head; rigorous statistical analysis suggests that substantial improvement in image quality can be obtained by increasing the data samples collected around the head. The proposed head imaging prototype along with the processing algorithm demonstrates its feasibility for potential use in ambulances as an effective and low cost diagnostic tool to assure timely triaging of intracranial hemorrhage patients. PMID:27073994

Tracking signal test to monitor an intelligent time series forecasting model

NASA Astrophysics Data System (ADS)

Deng, Yan; Jaraiedi, Majid; Iskander, Wafik H.

2004-03-01

Extensive research has been conducted on the subject of Intelligent Time Series forecasting, including many variations on the use of neural networks. However, investigation of model adequacy over time, after the training processes is completed, remains to be fully explored. In this paper we demonstrate a how a smoothed error tracking signals test can be incorporated into a neuro-fuzzy model to monitor the forecasting process and as a statistical measure for keeping the forecasting model up-to-date. The proposed monitoring procedure is effective in the detection of nonrandom changes, due to model inadequacy or lack of unbiasedness in the estimation of model parameters and deviations from the existing patterns. This powerful detection device will result in improved forecast accuracy in the long run. An example data set has been used to demonstrate the application of the proposed method.

Non-Invasive UWB Sensing of Astronauts' Breathing Activity

PubMed Central

Baldi, Marco; Cerri, Graziano; Chiaraluce, Franco; Eusebi, Lorenzo; Russo, Paola

2015-01-01

The use of a UWB system for sensing breathing activity of astronauts must account for many critical issues specific to the space environment. The aim of this paper is twofold. The first concerns the definition of design constraints about the pulse amplitude and waveform to transmit, as well as the immunity requirements of the receiver. The second issue concerns the assessment of the procedures and the characteristics of the algorithms to use for signal processing to retrieve the breathing frequency and respiration waveform. The algorithm has to work correctly in the presence of surrounding electromagnetic noise due to other sources in the environment. The highly reflecting walls increase the difficulty of the problem and the hostile scenario has to be accurately characterized. Examples of signal processing techniques able to recover breathing frequency in significant and realistic situations are shown and discussed. PMID:25558995

Anti-jamming Technology in Small Satellite Communication

NASA Astrophysics Data System (ADS)

Jia, Zixiang

2018-01-01

Small satellite communication has an increasingly important position among the wireless communications due to the advantages of low cost and high technology. However, in view of the case that its relay station stays outside the earth, its uplink may face interference from malicious signal frequently. Here this paper classified enumerates existing interferences, and proposes channel signals as main interference by comparison. Based on a basic digital communication process, then this paper discusses the possible anti - jamming techniques that commonly be realized at all stages in diverse processes, and comes to the conclusion that regarding the spread spectrum technology and antenna anti-jamming technology as fundamental direction of future development. This work provides possible thought for the design of new small satellite communication system with the coexistence of multi - technologies. This basic popular science can be consulted for people interested in small satellite communication.

State of the art in perceptual design of hearing aids

NASA Astrophysics Data System (ADS)

Edwards, Brent W.; van Tasell, Dianne J.

2002-05-01

Hearing aid capabilities have increased dramatically over the past six years, in large part due to the development of small, low-power digital signal processing chips suitable for hearing aid applications. As hearing aid signal processing capabilities increase, there will be new opportunities to apply perceptually based knowledge to technological development. Most hearing loss compensation techniques in today's hearing aids are based on simple estimates of audibility and loudness. As our understanding of the psychoacoustical and physiological characteristics of sensorineural hearing loss improves, the result should be improved design of hearing aids and fitting methods. The state of the art in hearing aids will be reviewed, including form factors, user requirements, and technology that improves speech intelligibility, sound quality, and functionality. General areas of auditory perception that remain unaddressed by current hearing aid technology will be discussed.

Space-Time Processing for Tactical Mobile Ad Hoc Networks

DTIC Science & Technology

2009-08-01

the results for the standard 8 bits per pixel ( bpp ) 512512 Lena image [3] with a transmission rate of 0.375 bpp . To compare the image quality, we...use peak-signal-to-noise ratio (PSNR), defined as  DE 2255 log10PSNR  (dB) (2) where 255 is due to the 8 bpp image

A simple solution for model comparison in bold imaging: the special case of reward prediction error and reward outcomes.

PubMed

Erdeniz, Burak; Rohe, Tim; Done, John; Seidler, Rachael D

2013-01-01

Conventional neuroimaging techniques provide information about condition-related changes of the BOLD (blood-oxygen-level dependent) signal, indicating only where and when the underlying cognitive processes occur. Recently, with the help of a new approach called "model-based" functional neuroimaging (fMRI), researchers are able to visualize changes in the internal variables of a time varying learning process, such as the reward prediction error or the predicted reward value of a conditional stimulus. However, despite being extremely beneficial to the imaging community in understanding the neural correlates of decision variables, a model-based approach to brain imaging data is also methodologically challenging due to the multicollinearity problem in statistical analysis. There are multiple sources of multicollinearity in functional neuroimaging including investigations of closely related variables and/or experimental designs that do not account for this. The source of multicollinearity discussed in this paper occurs due to correlation between different subjective variables that are calculated very close in time. Here, we review methodological approaches to analyzing such data by discussing the special case of separating the reward prediction error signal from reward outcomes.

At the interface of antioxidant signalling and cellular function: Key polyphenol effects

PubMed Central

Kerimi, Asimina

2016-01-01

The hypothesis that dietary (poly)phenols promote well‐being by improving chronic disease‐risk biomarkers, such as endothelial dysfunction, chronic inflammation and plasma uric acid, is the subject of intense current research, involving human interventions studies, animal models and in vitro mechanistic work. The original claim that benefits were due to the direct antioxidant properties of (poly)phenols has been mostly superseded by detailed mechanistic studies on specific molecular targets. Nevertheless, many proposed mechanisms in vivo and in vitro are due to modulation of oxidative processes, often involving binding to specific proteins and effects on cell signalling. We review the molecular mechanisms for 3 actions of (poly)phenols on oxidative processes where there is evidence in vivo from human intervention or animal studies. (1) Effects of (poly) phenols on pathways of chronic inflammation leading to prevention of some of the damaging effects associated with the metabolic syndrome. (2) Interaction of (poly)phenols with endothelial cells and smooth muscle cells, leading to effects on blood pressure and endothelial dysfunction, and consequent reduction in cardiovascular disease risk. (3) The inhibition of xanthine oxidoreductase leading to modulation of intracellular superoxide and plasma uric acid, a risk factor for developing type 2 diabetes. PMID:26887821

A Stimulated Raman Scattering CMOS Pixel Using a High-Speed Charge Modulator and Lock-in Amplifier.

PubMed

Lioe, De Xing; Mars, Kamel; Kawahito, Shoji; Yasutomi, Keita; Kagawa, Keiichiro; Yamada, Takahiro; Hashimoto, Mamoru

2016-04-13

A complementary metal-oxide semiconductor (CMOS) lock-in pixel to observe stimulated Raman scattering (SRS) using a high speed lateral electric field modulator (LEFM) for photo-generated charges and in-pixel readout circuits is presented. An effective SRS signal generated after the SRS process is very small and needs to be extracted from an extremely large offset due to a probing laser signal. In order to suppress the offset components while amplifying high-frequency modulated small SRS signal components, the lock-in pixel uses a high-speed LEFM for demodulating the SRS signal, resistor-capacitor low-pass filter (RC-LPF) and switched-capacitor (SC) integrator with a fully CMOS differential amplifier. AC (modulated) components remained in the RC-LPF outputs are eliminated by the phase-adjusted sampling with the SC integrator and the demodulated DC (unmodulated) components due to the SRS signal are integrated over many samples in the SC integrator. In order to suppress further the residual offset and the low frequency noise (1/f noise) components, a double modulation technique is introduced in the SRS signal measurements, where the phase of high-frequency modulated laser beam before irradiation of a specimen is modulated at an intermediate frequency and the demodulation is done at the lock-in pixel output. A prototype chip for characterizing the SRS lock-in pixel is implemented and a successful operation is demonstrated. The reduction effects of residual offset and 1/f noise components are confirmed by the measurements. A ratio of the detected small SRS to offset a signal of less than 10(-)⁵ is experimentally demonstrated, and the SRS spectrum of a Benzonitrile sample is successfully observed.

Performance Analysis for Channel Estimation With 1-Bit ADC and Unknown Quantization Threshold

NASA Astrophysics Data System (ADS)

Stein, Manuel S.; Bar, Shahar; Nossek, Josef A.; Tabrikian, Joseph

2018-05-01

In this work, the problem of signal parameter estimation from measurements acquired by a low-complexity analog-to-digital converter (ADC) with $1$-bit output resolution and an unknown quantization threshold is considered. Single-comparator ADCs are energy-efficient and can be operated at ultra-high sampling rates. For analysis of such systems, a fixed and known quantization threshold is usually assumed. In the symmetric case, i.e., zero hard-limiting offset, it is known that in the low signal-to-noise ratio (SNR) regime the signal processing performance degrades moderately by ${2}/{\\pi}$ ($-1.96$ dB) when comparing to an ideal $\\infty$-bit converter. Due to hardware imperfections, low-complexity $1$-bit ADCs will in practice exhibit an unknown threshold different from zero. Therefore, we study the accuracy which can be obtained with receive data processed by a hard-limiter with unknown quantization level by using asymptotically optimal channel estimation algorithms. To characterize the estimation performance of these nonlinear algorithms, we employ analytic error expressions for different setups while modeling the offset as a nuisance parameter. In the low SNR regime, we establish the necessary condition for a vanishing loss due to missing offset knowledge at the receiver. As an application, we consider the estimation of single-input single-output wireless channels with inter-symbol interference and validate our analysis by comparing the analytic and experimental performance of the studied estimation algorithms. Finally, we comment on the extension to multiple-input multiple-output channel models.

A design of Si-based nanoplasmonic structure as an antenna and reception amplifier for visible light communication

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, J. H.; Lin, Z. Y.; Liu, P.

2014-10-21

Visible light communication has been widely investigated due to its larger bandwidth and higher bit rate, and it can combine with the indoor illumination system that makes it more convenient to carry out. Receiving and processing the visible light signal on chip request for nanophotonics devices performing well. However, conventional optical device cannot be used for light-on-chip integration at subwavelength dimensions due to the diffraction limit. Herein, we propose a design of Si-based nanoplasmonic structure as an antenna and reception amplifier for visible light communication based on the interaction between Si nanoparticle and Au nanorod. This device integrates the uniquemore » scattering property of high-refractive index dielectric Si nanoparticles, whose scattering spectrum is dependent on the particle size, with the localized surface plasmon resonance of Au nanorod. We calculated the spectra collected by plane detector and near field distribution of nanostructure, and theoretically demonstrate that the proposed device can act as good receiver, amplifier and superlens during the visible light signal receiving and processing. Besides, unlike some other designs of nanoantenna devices focused less on how to detect the signals, our hybrid nanoantenna can realize the transfer between the scattering source and the detector effectively by Au nanorod waveguides. These findings suggest that the designed nanoplasmonic structure is expected to be used in on-chip nanophotonics as antenna, spectral splitter and demultiplexer for visible light communication.« less

CORRECTING FOR INTERSTELLAR SCATTERING DELAY IN HIGH-PRECISION PULSAR TIMING: SIMULATION RESULTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palliyaguru, Nipuni; McLaughlin, Maura; Stinebring, Daniel

2015-12-20

Light travel time changes due to gravitational waves (GWs) may be detected within the next decade through precision timing of millisecond pulsars. Removal of frequency-dependent interstellar medium (ISM) delays due to dispersion and scattering is a key issue in the detection process. Current timing algorithms routinely correct pulse times of arrival (TOAs) for time-variable delays due to cold plasma dispersion. However, none of the major pulsar timing groups correct for delays due to scattering from multi-path propagation in the ISM. Scattering introduces a frequency-dependent phase change in the signal that results in pulse broadening and arrival time delays. Any methodmore » to correct the TOA for interstellar propagation effects must be based on multi-frequency measurements that can effectively separate dispersion and scattering delay terms from frequency-independent perturbations such as those due to a GW. Cyclic spectroscopy, first described in an astronomical context by Demorest (2011), is a potentially powerful tool to assist in this multi-frequency decomposition. As a step toward a more comprehensive ISM propagation delay correction, we demonstrate through a simulation that we can accurately recover impulse response functions (IRFs), such as those that would be introduced by multi-path scattering, with a realistic signal-to-noise ratio (S/N). We demonstrate that timing precision is improved when scatter-corrected TOAs are used, under the assumptions of a high S/N and highly scattered signal. We also show that the effect of pulse-to-pulse “jitter” is not a serious problem for IRF reconstruction, at least for jitter levels comparable to those observed in several bright pulsars.« less

Real-time nondestructive monitoring of the gas tungsten arc welding (GTAW) process by combined airborne acoustic emission and non-contact ultrasonics

NASA Astrophysics Data System (ADS)

Zhang, Lu; Basantes-Defaz, Alexandra-Del-Carmen; Abbasi, Zeynab; Yuhas, Donald; Ozevin, Didem; Indacochea, Ernesto

2018-03-01

Welding is a key manufacturing process for many industries and may introduce defects into the welded parts causing significant negative impacts, potentially ruining high-cost pieces. Therefore, a real-time process monitoring method is important to implement for avoiding producing a low-quality weld. Due to high surface temperature and possible contamination of surface by contact transducers, the welding process should be monitored via non-contact transducers. In this paper, airborne acoustic emission (AE) transducers tuned at 60 kHz and non-contact ultrasonic testing (UT) transducers tuned at 500 kHz are implemented for real time weld monitoring. AE is a passive nondestructive evaluation method that listens for the process noise, and provides information about the uniformity of manufacturing process. UT provides more quantitative information about weld defects. One of the most common weld defects as burn-through is investigated. The influences of weld defects on AE signatures (time-driven data) and UT signals (received signal energy, change in peak frequency) are presented. The level of burn-through damage is defined by using single method or combine AE/UT methods.

Mechanism on brain information processing: Energy coding

NASA Astrophysics Data System (ADS)

Wang, Rubin; Zhang, Zhikang; Jiao, Xianfa

2006-09-01

According to the experimental result of signal transmission and neuronal energetic demands being tightly coupled to information coding in the cerebral cortex, the authors present a brand new scientific theory that offers a unique mechanism for brain information processing. They demonstrate that the neural coding produced by the activity of the brain is well described by the theory of energy coding. Due to the energy coding model's ability to reveal mechanisms of brain information processing based upon known biophysical properties, they cannot only reproduce various experimental results of neuroelectrophysiology but also quantitatively explain the recent experimental results from neuroscientists at Yale University by means of the principle of energy coding. Due to the theory of energy coding to bridge the gap between functional connections within a biological neural network and energetic consumption, they estimate that the theory has very important consequences for quantitative research of cognitive function.

Towards Intelligent Interpretation of Low Strain Pile Integrity Testing Results Using Machine Learning Techniques.

PubMed

Cui, De-Mi; Yan, Weizhong; Wang, Xiao-Quan; Lu, Lie-Min

2017-10-25

Low strain pile integrity testing (LSPIT), due to its simplicity and low cost, is one of the most popular NDE methods used in pile foundation construction. While performing LSPIT in the field is generally quite simple and quick, determining the integrity of the test piles by analyzing and interpreting the test signals (reflectograms) is still a manual process performed by experienced experts only. For foundation construction sites where the number of piles to be tested is large, it may take days before the expert can complete interpreting all of the piles and delivering the integrity assessment report. Techniques that can automate test signal interpretation, thus shortening the LSPIT's turnaround time, are of great business value and are in great need. Motivated by this need, in this paper, we develop a computer-aided reflectogram interpretation (CARI) methodology that can interpret a large number of LSPIT signals quickly and consistently. The methodology, built on advanced signal processing and machine learning technologies, can be used to assist the experts in performing both qualitative and quantitative interpretation of LSPIT signals. Specifically, the methodology can ease experts' interpretation burden by screening all test piles quickly and identifying a small number of suspected piles for experts to perform manual, in-depth interpretation. We demonstrate the methodology's effectiveness using the LSPIT signals collected from a number of real-world pile construction sites. The proposed methodology can potentially enhance LSPIT and make it even more efficient and effective in quality control of deep foundation construction.

The high accuracy data processing system of laser interferometry signals based on MSP430

NASA Astrophysics Data System (ADS)

Qi, Yong-yue; Lin, Yu-chi; Zhao, Mei-rong

2009-07-01

Generally speaking there are two orthogonal signals used in single-frequency laser interferometer for differentiating direction and electronic subdivision. However there usually exist three errors with the interferential signals: zero offsets error, unequal amplitude error and quadrature phase shift error. These three errors have a serious impact on subdivision precision. Based on Heydemann error compensation algorithm, it is proposed to achieve compensation of the three errors. Due to complicated operation of the Heydemann mode, a improved arithmetic is advanced to decrease the calculating time effectively in accordance with the special characteristic that only one item of data will be changed in each fitting algorithm operation. Then a real-time and dynamic compensatory circuit is designed. Taking microchip MSP430 as the core of hardware system, two input signals with the three errors are turned into digital quantity by the AD7862. After data processing in line with improved arithmetic, two ideal signals without errors are output by the AD7225. At the same time two original signals are turned into relevant square wave and imported to the differentiating direction circuit. The impulse exported from the distinguishing direction circuit is counted by the timer of the microchip. According to the number of the pulse and the soft subdivision the final result is showed by LED. The arithmetic and the circuit are adopted to test the capability of a laser interferometer with 8 times optical path difference and the measuring accuracy of 12-14nm is achieved.

Error reduction study employing a pseudo-random binary sequence for use in acoustic pyrometry of gases

NASA Astrophysics Data System (ADS)

Ewan, B. C. R.; Ireland, S. N.

2000-12-01

Acoustic pyrometry uses the temperature dependence of sound speed in materials to measure temperature. This is normally achieved by measuring the transit time for a sound signal over a known path length and applying the material relation between temperature and velocity to extract an "average" temperature. Sources of error associated with the measurement of mean transit time are discussed in implementing the technique in gases, one of the principal causes being background noise in typical industrial environments. A number of transmitted signal and processing strategies which can be used in the area are examined and the expected error in mean transit time associated with each technique is quantified. Transmitted signals included pulses, pure frequencies, chirps, and pseudorandom binary sequences (prbs), while processing involves edge detection and correlation. Errors arise through the misinterpretation of the positions of edge arrival or correlation peaks due to instantaneous deviations associated with background noise and these become more severe as signal to noise amplitude ratios decrease. Population errors in the mean transit time are estimated for the different measurement strategies and it is concluded that PRBS combined with correlation can provide the lowest errors when operating in high noise environments. The operation of an instrument based on PRBS transmitted signals is described and test results under controlled noise conditions are presented. These confirm the value of the strategy and demonstrate that measurements can be made with signal to noise amplitude ratios down to 0.5.

The Juvenile Hafnium Isotope Signal as a Record of Supercontinent Cycles.

PubMed

Gardiner, Nicholas J; Kirkland, Christopher L; Van Kranendonk, Martin J

2016-12-07

Hf isotope ratios measured in igneous zircon are controlled by magmatic source, which may be linked to tectonic setting. Over the 200-500 Myr periodicity of the supercontinent cycle - the principal geological phenomenon controlling prevailing global tectonic style - juvenile Hf signals, i.e. most radiogenic, are typically measured in zircon from granites formed in arc settings (crustal growth), and evolved zircon Hf signals in granites formed in continent-collision settings (crustal reworking). Interrogations of Hf datasets for excursions related to Earth events commonly use the median value, however this may be equivocal due to magma mixing. The most juvenile part of the Hf signal is less influenced by crustal in-mixing, and arguably a more sensitive archive of Earth's geodynamic state. We analyze the global Hf dataset for this juvenile signal, statistically correlating supercontinent amalgamation intervals with evolved Hf episodes, and breakup leading to re-assembly with juvenile Hf episodes. The juvenile Hf signal is more sensitive to Pangaea and Rodinia assembly, its amplitude increasing with successive cycles to a maximum with Gondwana assembly which may reflect enhanced subduction-erosion. We demonstrate that the juvenile Hf signal carries important information on prevailing global magmatic style, and thus tectonic processes.

The Juvenile Hafnium Isotope Signal as a Record of Supercontinent Cycles

NASA Astrophysics Data System (ADS)

Gardiner, Nicholas J.; Kirkland, Christopher L.; van Kranendonk, Martin J.

2016-12-01

Hf isotope ratios measured in igneous zircon are controlled by magmatic source, which may be linked to tectonic setting. Over the 200-500 Myr periodicity of the supercontinent cycle - the principal geological phenomenon controlling prevailing global tectonic style - juvenile Hf signals, i.e. most radiogenic, are typically measured in zircon from granites formed in arc settings (crustal growth), and evolved zircon Hf signals in granites formed in continent-collision settings (crustal reworking). Interrogations of Hf datasets for excursions related to Earth events commonly use the median value, however this may be equivocal due to magma mixing. The most juvenile part of the Hf signal is less influenced by crustal in-mixing, and arguably a more sensitive archive of Earth’s geodynamic state. We analyze the global Hf dataset for this juvenile signal, statistically correlating supercontinent amalgamation intervals with evolved Hf episodes, and breakup leading to re-assembly with juvenile Hf episodes. The juvenile Hf signal is more sensitive to Pangaea and Rodinia assembly, its amplitude increasing with successive cycles to a maximum with Gondwana assembly which may reflect enhanced subduction-erosion. We demonstrate that the juvenile Hf signal carries important information on prevailing global magmatic style, and thus tectonic processes.

A Modified Empirical Wavelet Transform for Acoustic Emission Signal Decomposition in Structural Health Monitoring.

PubMed

Dong, Shaopeng; Yuan, Mei; Wang, Qiusheng; Liang, Zhiling

2018-05-21

The acoustic emission (AE) method is useful for structural health monitoring (SHM) of composite structures due to its high sensitivity and real-time capability. The main challenge, however, is how to classify the AE data into different failure mechanisms because the detected signals are affected by various factors. Empirical wavelet transform (EWT) is a solution for analyzing the multi-component signals and has been used to process the AE data. In order to solve the spectrum separation problem of the AE signals, this paper proposes a novel modified separation method based on local window maxima (LWM) algorithm. It searches the local maxima of the Fourier spectrum in a proper window, and automatically determines the boundaries of spectrum segmentations, which helps to eliminate the impact of noise interference or frequency dispersion in the detected signal and obtain the meaningful empirical modes that are more related to the damage characteristics. Additionally, both simulation signal and AE signal from the composite structures are used to verify the effectiveness of the proposed method. Finally, the experimental results indicate that the proposed method performs better than the original EWT method in identifying different damage mechanisms of composite structures.

A Modified Empirical Wavelet Transform for Acoustic Emission Signal Decomposition in Structural Health Monitoring

PubMed Central

Dong, Shaopeng; Yuan, Mei; Wang, Qiusheng; Liang, Zhiling

2018-01-01

The acoustic emission (AE) method is useful for structural health monitoring (SHM) of composite structures due to its high sensitivity and real-time capability. The main challenge, however, is how to classify the AE data into different failure mechanisms because the detected signals are affected by various factors. Empirical wavelet transform (EWT) is a solution for analyzing the multi-component signals and has been used to process the AE data. In order to solve the spectrum separation problem of the AE signals, this paper proposes a novel modified separation method based on local window maxima (LWM) algorithm. It searches the local maxima of the Fourier spectrum in a proper window, and automatically determines the boundaries of spectrum segmentations, which helps to eliminate the impact of noise interference or frequency dispersion in the detected signal and obtain the meaningful empirical modes that are more related to the damage characteristics. Additionally, both simulation signal and AE signal from the composite structures are used to verify the effectiveness of the proposed method. Finally, the experimental results indicate that the proposed method performs better than the original EWT method in identifying different damage mechanisms of composite structures. PMID:29883411

Venus flytrap carnivorous lifestyle builds on herbivore defense strategies

PubMed Central

Becker, Dirk; Larisch, Christina; Kreuzer, Ines; Escalante-Perez, Maria; Schulze, Waltraud X.; Ankenbrand, Markus; Van de Weyer, Anna-Lena; Krol, Elzbieta; Al-Rasheid, Khaled A.; Mithöfer, Axel; Weber, Andreas P.; Schultz, Jörg

2016-01-01

Although the concept of botanical carnivory has been known since Darwin's time, the molecular mechanisms that allow animal feeding remain unknown, primarily due to a complete lack of genomic information. Here, we show that the transcriptomic landscape of the Dionaea trap is dramatically shifted toward signal transduction and nutrient transport upon insect feeding, with touch hormone signaling and protein secretion prevailing. At the same time, a massive induction of general defense responses is accompanied by the repression of cell death–related genes/processes. We hypothesize that the carnivory syndrome of Dionaea evolved by exaptation of ancient defense pathways, replacing cell death with nutrient acquisition. PMID:27197216

Phase sensitive amplification in integrated waveguides (Conference Presentation)

NASA Astrophysics Data System (ADS)

Schroeder, Jochen B.; Zhang, Youngbin; Husko, Chad A.; LeFrancois, Simon; Eggleton, Benjamin J.

2017-02-01

Phase sensitive amplification (PSA) is an attractive technology for integrated all-optical signal processing, due to it's potential for noiseless amplification, phase regeneration and generation of squeezed light. In this talk I will review our results on implementing four-wave-mixing based PSA inside integrated photonic devices. In particular I will discuss PSA in chalcogenide ridge waveguides and silicon slow-light photonic crystals. We achieve PSA in both pump- and signal-degenerate schemes with maximum extinction ratios of 11 (silicon) and 18 (chalcogenide) dB. I will further discuss the influence of two-photon absorption and free carrier effects on the performance of silicon-based PSAs.

Large signal design - Performance and simulation of a 3 W C-band GaAs power MMIC

NASA Astrophysics Data System (ADS)

White, Paul M.; Hendrickson, Mary A.; Chang, Wayne H.; Curtice, Walter R.

1990-04-01

This paper describes a C-band GaAs power MMIC amplifier that achieved a gain of 17 dB and 1 dB compressed CW power output of 34 dBm across a 4.5-6.25-GHz frequency range, without design iteration. The first-pass design success was achieved due to the application of a harmonic balance simulator to define the optimum output load, using a large-signal FET model determined statistically on a well controlled foundry-ready process line. The measured performance was close to that predicted by a full harmonic balance circuit analysis.

A wideband, high-resolution spectrum analyzer

NASA Technical Reports Server (NTRS)

Quirk, M. P.; Wilck, H. C.; Garyantes, M. F.; Grimm, M. J.

1988-01-01

A two-million-channel, 40 MHz bandwidth, digital spectrum analyzer under development at the Jet Propulsion Laboratory is described. The analyzer system will serve as a prototype processor for the sky survey portion of NASA's Search for Extraterrestrial Intelligence program and for other applications in the Deep Space Network. The analyzer digitizes an analog input, performs a 2 (sup 21) point Discrete Fourier Transform, accumulates the output power, normalizes the output to remove frequency-dependent gain, and automates simple signal detection algorithms. Due to its built-in frequency-domain processing functions and configuration flexibility, the analyzer is a very powerful tool for real-time signal analysis.

A wide-band high-resolution spectrum analyzer.

PubMed

Quirk, M P; Garyantes, M F; Wilck, H C; Grimm, M J

1988-12-01

This paper describes a two-million-channel 40-MHz-bandwidth, digital spectrum analyzer under development at the Jet Propulsion Laboratory. The analyzer system will serve as a prototype processor for the sky survey portion of NASA's Search for Extraterrestrial Intelligence program and for other applications in the Deep Space Network. The analyzer digitizes an analog input, performs a 2(21)-point, Discrete Fourier Transform, accumulates the output power, normalizes the output to remove frequency-dependent gain, and automates simple signal detection algorithms. Due to its built-in frequency-domain processing functions and configuration flexibility, the analyzer is a very powerful tool for real-time signal analysis and detection.

Fetal Electrocardiogram Extraction and Analysis Using Adaptive Noise Cancellation and Wavelet Transformation Techniques.

PubMed

Sutha, P; Jayanthi, V E

2017-12-08

Birth defect-related demise is mainly due to congenital heart defects. In the earlier stage of pregnancy, fetus problem can be identified by finding information about the fetus to avoid stillbirths. The gold standard used to monitor the health status of the fetus is by Cardiotachography(CTG), cannot be used for long durations and continuous monitoring. There is a need for continuous and long duration monitoring of fetal ECG signals to study the progressive health status of the fetus using portable devices. The non-invasive method of electrocardiogram recording is one of the best method used to diagnose fetal cardiac problem rather than the invasive methods.The monitoring of the fECG requires development of a miniaturized hardware and a efficient signal processing algorithms to extract the fECG embedded in the mother ECG. The paper discusses a prototype hardware developed to monitor and record the raw mother ECG signal containing the fECG and a signal processing algorithm to extract the fetal Electro Cardiogram signal. We have proposed two methods of signal processing, first is based on the Least Mean Square (LMS) Adaptive Noise Cancellation technique and the other method is based on the Wavelet Transformation technique. A prototype hardware was designed and developed to acquire the raw ECG signal containing the mother and fetal ECG and the signal processing techniques were used to eliminate the noises and extract the fetal ECG and the fetal Heart Rate Variability was studied. Both the methods were evaluated with the signal acquired from a fetal ECG simulator, from the Physionet database and that acquired from the subject. Both the methods are evaluated by finding heart rate and its variability, amplitude spectrum and mean value of extracted fetal ECG. Also the accuracy, sensitivity and positive predictive value are also determined for fetal QRS detection technique. In this paper adaptive filtering technique uses Sign-sign LMS algorithm and wavelet techniques with Daubechies wavelet, employed along with de noising techniques for the extraction of fetal Electrocardiogram.Both the methods are having good sensitivity and accuracy. In adaptive method the sensitivity is 96.83, accuracy 89.87, wavelet sensitivity is 95.97 and accuracy is 88.5. Additionally, time domain parameters from the plot of heart rate variability of mother and fetus are analyzed.

Coherent and Noncoherent Joint Processing of Sonar for Detection of Small Targets in Shallow Water

PubMed Central

Jiang, Jingning; Li, Si; Ding, Zhenping; Pan, Chen; Gong, Xianyi

2018-01-01

A coherent-noncoherent joint processing framework is proposed for active sonar to combine diversity gain and beamforming gain for detection of a small target in shallow water environments. Sonar utilizes widely-spaced arrays to sense environments and illuminate a target of interest from multiple angles. Meanwhile, it exploits spatial diversity for time-reversal focusing to suppress reverberation, mainly strong bottom reverberation. For enhancement of robustness of time-reversal focusing, an adaptive iterative strategy is utilized in the processing framework. A probing signal is firstly transmitted and echoes of a likely target are utilized as steering vectors for the second transmission. With spatial diversity, target bearing and range are estimated using a broadband signal model. Numerical simulations show that the novel sonar outperforms the traditional phased-array sonar due to benefits of spatial diversity. The effectiveness of the proposed framework has been validated by localization of a small target in at-lake experiments. PMID:29642637

A direct temporal domain approach for ultrafast optical signal processing and its implementation using planar lightwave circuits

NASA Astrophysics Data System (ADS)

Xia, Bing

Ultrafast optical signal processing, which shares the same fundamental principles of electrical signal processing, can realize numerous important functionalities required in both academic research and industry. Due to the extremely fast processing speed, all-optical signal processing and pulse shaping have been widely used in ultrafast telecommunication networks, photonically-assisted RFlmicro-meter waveform generation, microscopy, biophotonics, and studies on transient and nonlinear properties of atoms and molecules. In this thesis, we investigate two types of optical spectrally-periodic (SP) filters that can be fabricated on planar lightwave circuits (PLC) to perform pulse repetition rate multiplication (PRRM) and arbitrary optical waveform generation (AOWG). First, we present a direct temporal domain approach for PRRM using SP filters. We show that the repetition rate of an input pulse train can be multiplied by a factor N using an optical filter with a free spectral range that does not need to be constrained to an integer multiple of N. Furthermore, the amplitude of each individual output pulse can be manipulated separately to form an arbitrary envelope at the output by optimizing the impulse response of the filter. Next, we use lattice-form Mach-Zehnder interferometers (LF-MZI) to implement the temporal domain approach for PRRM. The simulation results show that PRRM with uniform profiles, binary-code profiles and triangular profiles can be achieved. Three silica based LF-MZIs are designed and fabricated, which incorporate multi-mode interference (MMI) couplers and phase shifters. The experimental results show that 40 GHz pulse trains with a uniform envelope pattern, a binary code pattern "1011" and a binary code pattern "1101" are generated from a 10 GHz input pulse train. Finally, we investigate 2D ring resonator arrays (RRA) for ultraf ast optical signal processing. We design 2D RRAs to generate a pair of pulse trains with different binary-code patterns simultaneously from a single pulse train at a low repetition rate. We also design 2D RRAs for AOWG using the modified direct temporal domain approach. To demonstrate the approach, we provide numerical examples to illustrate the generation of two very different waveforms (square waveform and triangular waveform) from the same hyperbolic secant input pulse train. This powerful technique based on SP filters can be very useful for ultrafast optical signal processing and pulse shaping.

Single-chip microcomputer for image processing in the photonic measuring system

NASA Astrophysics Data System (ADS)

Smoleva, Olga S.; Ljul, Natalia Y.

2002-04-01

The non-contact measuring system has been designed for rail- track parameters control on the Moscow Metro. It detects some significant parameters: rail-track width, rail-track height, gage, rail-slums, crosslevel, pickets, and car speed. The system consists of three subsystems: non-contact system of rail-track width, height, and gage inspection, non-contact system of rail-slums inspection and subsystem for crosslevel, speed, and pickets detection. Data from subsystems is transferred to pre-processing unit. In order to process data received from subsystems, the single-chip signal processor ADSP-2185 must be used due to providing required processing speed. After data will be processed, it is send to PC, which processes it and outputs it in the readable form.

Sequential Bayesian geoacoustic inversion for mobile and compact source-receiver configuration.

PubMed

Carrière, Olivier; Hermand, Jean-Pierre

2012-04-01

Geoacoustic characterization of wide areas through inversion requires easily deployable configurations including free-drifting platforms, underwater gliders and autonomous vehicles, typically performing repeated transmissions during their course. In this paper, the inverse problem is formulated as sequential Bayesian filtering to take advantage of repeated transmission measurements. Nonlinear Kalman filters implement a random-walk model for geometry and environment and an acoustic propagation code in the measurement model. Data from MREA/BP07 sea trials are tested consisting of multitone and frequency-modulated signals (bands: 0.25-0.8 and 0.8-1.6 kHz) received on a shallow vertical array of four hydrophones 5-m spaced drifting over 0.7-1.6 km range. Space- and time-coherent processing are applied to the respective signal types. Kalman filter outputs are compared to a sequence of global optimizations performed independently on each received signal. For both signal types, the sequential approach is more accurate but also more efficient. Due to frequency diversity, the processing of modulated signals produces a more stable tracking. Although an extended Kalman filter provides comparable estimates of the tracked parameters, the ensemble Kalman filter is necessary to properly assess uncertainty. In spite of mild range dependence and simplified bottom model, all tracked geoacoustic parameters are consistent with high-resolution seismic profiling, core logging P-wave velocity, and previous inversion results with fixed geometries.

Memory and learning behaviors mimicked in nanogranular SiO2-based proton conductor gated oxide-based synaptic transistors

NASA Astrophysics Data System (ADS)

Wan, Chang Jin; Zhu, Li Qiang; Zhou, Ju Mei; Shi, Yi; Wan, Qing

2013-10-01

In neuroscience, signal processing, memory and learning function are established in the brain by modifying ionic fluxes in neurons and synapses. Emulation of memory and learning behaviors of biological systems by nanoscale ionic/electronic devices is highly desirable for building neuromorphic systems or even artificial neural networks. Here, novel artificial synapses based on junctionless oxide-based protonic/electronic hybrid transistors gated by nanogranular phosphorus-doped SiO2-based proton-conducting films are fabricated on glass substrates by a room-temperature process. Short-term memory (STM) and long-term memory (LTM) are mimicked by tuning the pulse gate voltage amplitude. The LTM process in such an artificial synapse is due to the proton-related interfacial electrochemical reaction. Our results are highly desirable for building future neuromorphic systems or even artificial networks via electronic elements.In neuroscience, signal processing, memory and learning function are established in the brain by modifying ionic fluxes in neurons and synapses. Emulation of memory and learning behaviors of biological systems by nanoscale ionic/electronic devices is highly desirable for building neuromorphic systems or even artificial neural networks. Here, novel artificial synapses based on junctionless oxide-based protonic/electronic hybrid transistors gated by nanogranular phosphorus-doped SiO2-based proton-conducting films are fabricated on glass substrates by a room-temperature process. Short-term memory (STM) and long-term memory (LTM) are mimicked by tuning the pulse gate voltage amplitude. The LTM process in such an artificial synapse is due to the proton-related interfacial electrochemical reaction. Our results are highly desirable for building future neuromorphic systems or even artificial networks via electronic elements. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr02987e

The effects of solar incidence angle over digital processing of LANDSAT data

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Novo, E. M. L. M.

1983-01-01

A technique to extract the topography modulation component from digital data is described. The enhancement process is based on the fact that the pixel contains two types of information: (1) reflectance variation due to the target; (2) reflectance variation due to the topography. In order to enhance the signal variation due to topography, the technique recommends the extraction from original LANDSAT data of the component resulting from target reflectance. Considering that the role of topographic modulation over the pixel information will vary with solar incidence angle, the results of this technique of digital processing will differ from one season to another, mainly in highly dissected topography. In this context, the effects of solar incidence angle over the topographic modulation technique were evaluated. Two sets of MSS/LANDSAT data, with solar elevation angles varying from 22 to 41 deg were selected to implement the digital processing at the Image-100 System. A secondary watershed (Rio Bocaina) draining into Rio Paraiba do Sul (Sao Paulo State) was selected as a test site. The results showed that the technique used was more appropriate to MSS data acquired under higher Sun elevation angles. Topographic modulation components applied to low Sun elevation angles lessens rather than enhances topography.

Chordin and dickkopf-1b are essential for the formation of head structures through activation of the FGF signaling pathway in zebrafish.

PubMed

Tanaka, Shingo; Hosokawa, Hiroshi; Weinberg, Eric S; Maegawa, Shingo

2017-04-15

The ability of the Spemann organizer to induce dorsal axis formation is dependent on downstream factors of the maternal Wnt/β-catenin signaling pathway. The fibroblast growth factor (FGF) signaling pathway has been identified as one of the downstream components of the maternal Wnt/β-catenin signaling pathway. The ability of the FGF signaling pathway to induce the formation of a dorsal axis with a complete head structure requires chordin (chd) expression; however, the molecular mechanisms involved in this developmental process, due to activation of FGF signaling, remain unclear. In this study, we showed that activation of the FGF signaling pathway induced the formation of complete head structures through the expression of chd and dickkopf-1b (dkk1b). Using the organizer-deficient maternal mutant, ichabod, we identified dkk1b as a novel downstream factor in the FGF signaling pathway. We also demonstrate that dkk1b expression is necessary, after activation of the FGF signaling pathway, to induce neuroectoderm patterning along the anteroposterior (AP) axis and for formation of complete head structures. Co-injection of chd and dkk1b mRNA resulted in the formation of a dorsal axis with a complete head structure in ichabod embryos, confirming the role of these factors in this developmental process. Unexpectedly, we found that chd induced dkk1b expression in ichabod embryos at the shield stage. However, chd failed to maintain dkk1b expression levels in cells of the shield and, subsequently, in the cells of the prechordal plate after mid-gastrula stage. In contrast, activation of the FGF signaling pathway maintained the dkk1b expression from the beginning of gastrulation to early somitogenesis. In conclusion, activation of the FGF signaling pathway induces the formation of a dorsal axis with a complete head structure through the expression of chd and subsequent maintenance of dkk1b expression levels. Copyright © 2017 Elsevier Inc. All rights reserved.

Spectrum interrogation of fiber acoustic sensor based on self-fitting and differential method.

PubMed

Fu, Xin; Lu, Ping; Ni, Wenjun; Liao, Hao; Wang, Shun; Liu, Deming; Zhang, Jiangshan

2017-02-20

In this article, we propose an interrogation method of fiber acoustic sensor to recover the time-domain signal from the sensor spectrum. The optical spectrum of the sensor will show a ripple waveform when responding to acoustic signal due to the scanning process in a certain wavelength range. The reason behind this phenomenon is the dynamic variation of the sensor spectrum while the intensity of different wavelength is acquired at different time in a scanning period. The frequency components can be extracted from the ripple spectrum assisted by the wavelength scanning speed. The signal is able to be recovered by differential between the ripple spectrum and its self-fitted curve. The differential process can eliminate the interference caused by environmental perturbations such as temperature or refractive index (RI), etc. The proposed method is appropriate for fiber acoustic sensors based on gratings or interferometers. A long period grating (LPG) is adopted as an acoustic sensor head to prove the feasibility of the interrogation method in experiment. The ability to compensate the environmental fluctuations is also demonstrated.

Scaling Behavior in Mitochondrial Redox Fluctuations

PubMed Central

Ramanujan, V. Krishnan; Biener, Gabriel; Herman, Brian A.

2006-01-01

Scale-invariant long-range correlations have been reported in fluctuations of time-series signals originating from diverse processes such as heart beat dynamics, earthquakes, and stock market data. The common denominator of these apparently different processes is a highly nonlinear dynamics with competing forces and distinct feedback species. We report for the first time an experimental evidence for scaling behavior in NAD(P)H signal fluctuations in isolated mitochondria and intact cells isolated from the liver of a young (5-month-old) mouse. Time-series data were collected by two-photon imaging of mitochondrial NAD(P)H fluorescence and signal fluctuations were quantitatively analyzed for statistical correlations by detrended fluctuation analysis and spectral power analysis. Redox [NAD(P)H / NAD(P)+] fluctuations in isolated mitochondria and intact liver cells were found to display nonrandom, long-range correlations. These correlations are interpreted as arising due to the regulatory dynamics operative in Krebs' cycle enzyme network and electron transport chain in the mitochondria. This finding may provide a novel basis for understanding similar regulatory networks that govern the nonequilibrium properties of living cells. PMID:16565066

Multiple calmodulin-like proteins in Arabidopsis are induced by insect-derived (Spodoptera littoralis) oral secretion

PubMed Central

Vadassery, Jyothilakshmi; Scholz, Sandra S.; Mithöfer, Axel

2012-01-01

In plant cells, diverse environmental changes often induce transient elevation in the intracellular calcium concentrations, which are involved in signaling pathways leading to the respective cellular reactions. Therefore, these calcium elevations need to be deciphered into specific downstream responses. Calmodulin-like-proteins (CMLs) are calcium-sensing proteins present only in higher plants. They are involved in signaling processes induced by both abiotic as well as biotic stress factors. However, the role of CMLs in the interaction of plants with herbivorous insects is almost unknown. Here we show that in Arabidopsis thaliana a number of CMLs genes (CML9, 11,12,16,17 and 23) are upregulated due to treatments with oral secretion of larvae of the herbivorous insect Spodoptera littoralis. We identified that these genes belong to two groups that respond with different kinetics to the treatment with oral secretion. Our data indicate that signaling networks involving multiple CMLs very likely have important functions in plant defense against insect herbivores, in addition to their involvement in many other stress-induced processes in plants. PMID:22902684

Mutual information identifies spurious Hurst phenomena in resting state EEG and fMRI data

NASA Astrophysics Data System (ADS)

von Wegner, Frederic; Laufs, Helmut; Tagliazucchi, Enzo

2018-02-01

Long-range memory in time series is often quantified by the Hurst exponent H , a measure of the signal's variance across several time scales. We analyze neurophysiological time series from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state experiments with two standard Hurst exponent estimators and with the time-lagged mutual information function applied to discretized versions of the signals. A confidence interval for the mutual information function is obtained from surrogate Markov processes with equilibrium distribution and transition matrix identical to the underlying signal. For EEG signals, we construct an additional mutual information confidence interval from a short-range correlated, tenth-order autoregressive model. We reproduce the previously described Hurst phenomenon (H >0.5 ) in the analytical amplitude of alpha frequency band oscillations, in EEG microstate sequences, and in fMRI signals, but we show that the Hurst phenomenon occurs without long-range memory in the information-theoretical sense. We find that the mutual information function of neurophysiological data behaves differently from fractional Gaussian noise (fGn), for which the Hurst phenomenon is a sufficient condition to prove long-range memory. Two other well-characterized, short-range correlated stochastic processes (Ornstein-Uhlenbeck, Cox-Ingersoll-Ross) also yield H >0.5 , whereas their mutual information functions lie within the Markovian confidence intervals, similar to neural signals. In these processes, which do not have long-range memory by construction, a spurious Hurst phenomenon occurs due to slow relaxation times and heteroscedasticity (time-varying conditional variance). In summary, we find that mutual information correctly distinguishes long-range from short-range dependence in the theoretical and experimental cases discussed. Our results also suggest that the stationary fGn process is not sufficient to describe neural data, which seem to belong to a more general class of stochastic processes, in which multiscale variance effects produce Hurst phenomena without long-range dependence. In our experimental data, the Hurst phenomenon and long-range memory appear as different system properties that should be estimated and interpreted independently.

Silk scaffolds with tunable mechanical capability for cell differentiation

PubMed Central

Bai, Shumeng; Han, Hongyan; Huang, Xiaowei; Xu, Weian; Kaplan, David L.; Zhu, Hesun; Lu, Qiang

2015-01-01

Bombyx mori silk fibroin is a promising biomaterial for tissue regeneration and is usually considered an “inert” material with respect to actively regulating cell differentiation due to few specific cell signaling peptide domains in the primary sequence and the generally stiffer mechanical properties due to crystalline content formed in processing. In the present study, silk fibroin porous 3D scaffolds with nanostructures and tunable stiffness were generated via a silk fibroin nanofiber-assisted lyophilization process. The silk fibroin nanofibers with high β-sheet content were added into the silk fibroin solutions to modulate the self-assembly, and to directly induce water-insoluble scaffold formation after lyophilization. Unlike previously reported silk fibroin scaffold formation processes, these new scaffolds had lower overall β-sheet content and softer mechanical properties for improved cell compatibility. The scaffold stiffness could be further tuned to match soft tissue mechanical properties, which resulted in different differentiation outcomes with rat bone marrow-derived mesenchymal stem cells towards myogenic and endothelial cells, respectively. Therefore, these silk fibroin scaffolds regulate cell differentiation outcomes due to their mechanical features. PMID:25858557

Processing Functional Near Infrared Spectroscopy Signal with a Kalman Filter to Assess Working Memory during Simulated Flight.

PubMed

Durantin, Gautier; Scannella, Sébastien; Gateau, Thibault; Delorme, Arnaud; Dehais, Frédéric

2015-01-01

Working memory (WM) is a key executive function for operating aircraft, especially when pilots have to recall series of air traffic control instructions. There is a need to implement tools to monitor WM as its limitation may jeopardize flight safety. An innovative way to address this issue is to adopt a Neuroergonomics approach that merges knowledge and methods from Human Factors, System Engineering, and Neuroscience. A challenge of great importance for Neuroergonomics is to implement efficient brain imaging techniques to measure the brain at work and to design Brain Computer Interfaces (BCI). We used functional near infrared spectroscopy as it has been already successfully tested to measure WM capacity in complex environment with air traffic controllers (ATC), pilots, or unmanned vehicle operators. However, the extraction of relevant features from the raw signal in ecological environment is still a critical issue due to the complexity of implementing real-time signal processing techniques without a priori knowledge. We proposed to implement the Kalman filtering approach, a signal processing technique that is efficient when the dynamics of the signal can be modeled. We based our approach on the Boynton model of hemodynamic response. We conducted a first experiment with nine participants involving a basic WM task to estimate the noise covariances of the Kalman filter. We then conducted a more ecological experiment in our flight simulator with 18 pilots who interacted with ATC instructions (two levels of difficulty). The data was processed with the same Kalman filter settings implemented in the first experiment. This filter was benchmarked with a classical pass-band IIR filter and a Moving Average Convergence Divergence (MACD) filter. Statistical analysis revealed that the Kalman filter was the most efficient to separate the two levels of load, by increasing the observed effect size in prefrontal areas involved in WM. In addition, the use of a Kalman filter increased the performance of the classification of WM levels based on brain signal. The results suggest that Kalman filter is a suitable approach for real-time improvement of near infrared spectroscopy signal in ecological situations and the development of BCI.

Processing Functional Near Infrared Spectroscopy Signal with a Kalman Filter to Assess Working Memory during Simulated Flight

PubMed Central

Durantin, Gautier; Scannella, Sébastien; Gateau, Thibault; Delorme, Arnaud; Dehais, Frédéric

2016-01-01

Working memory (WM) is a key executive function for operating aircraft, especially when pilots have to recall series of air traffic control instructions. There is a need to implement tools to monitor WM as its limitation may jeopardize flight safety. An innovative way to address this issue is to adopt a Neuroergonomics approach that merges knowledge and methods from Human Factors, System Engineering, and Neuroscience. A challenge of great importance for Neuroergonomics is to implement efficient brain imaging techniques to measure the brain at work and to design Brain Computer Interfaces (BCI). We used functional near infrared spectroscopy as it has been already successfully tested to measure WM capacity in complex environment with air traffic controllers (ATC), pilots, or unmanned vehicle operators. However, the extraction of relevant features from the raw signal in ecological environment is still a critical issue due to the complexity of implementing real-time signal processing techniques without a priori knowledge. We proposed to implement the Kalman filtering approach, a signal processing technique that is efficient when the dynamics of the signal can be modeled. We based our approach on the Boynton model of hemodynamic response. We conducted a first experiment with nine participants involving a basic WM task to estimate the noise covariances of the Kalman filter. We then conducted a more ecological experiment in our flight simulator with 18 pilots who interacted with ATC instructions (two levels of difficulty). The data was processed with the same Kalman filter settings implemented in the first experiment. This filter was benchmarked with a classical pass-band IIR filter and a Moving Average Convergence Divergence (MACD) filter. Statistical analysis revealed that the Kalman filter was the most efficient to separate the two levels of load, by increasing the observed effect size in prefrontal areas involved in WM. In addition, the use of a Kalman filter increased the performance of the classification of WM levels based on brain signal. The results suggest that Kalman filter is a suitable approach for real-time improvement of near infrared spectroscopy signal in ecological situations and the development of BCI. PMID:26834607

Evaluation of 14 global GIA forward models using a novel GPS dataset and GRACE

NASA Astrophysics Data System (ADS)

Bamber, J. L.; Schumacher, M.; Sha, Z.; Rougier, J.; King, M. A.; Khan, S. A.; Shum, C. K.; Luthcke, S. B.

2017-12-01

Observed mass movement from GRACE and vertical land motion from a global network of permanent GPS stations are used in a data driven approach to estimate GIA signals without introducing any assumptions about Earth structure nor ice loading history. Satellite data and in-situ observations are combined using a multivariate spatiotemporal model within a Bayesian Hierarchical Modelling (BHM) framework. In this study, the GPS data set of the Nevada Geodetic Laboratory (NGL) is used as the starting point for providing an observational estimate of global GIA uplift rates. A novel fully automatic post-processing strategy is developed to correct for non-GIA artifacts, including: (i) outlier detection (e.g. due to icing of Choke Ring Antennas or the antenna being buried in snow); (ii) automatic removal of reported and unreported jumps due to geophysical and hardware issues (a refinement of the jump database provided by NGL); and (iii) filtering for GPS stations that observe primarily the GIA signal rather than unwanted local effects (e.g., unmodelled loading effects from land hydrology, atmosphere, or tides). In order to accurately account for the elastic response of the Earth's crust over Antarctica and Greenland, uplift rates in these regions were corrected for the contemporary ice mass loading impact on elastic deformation using high-resolution ice mass balance time series. The novel global GPS data set shows a clean GIA signal at all post-processed stations and is therefore suitable to investigate the behavior of global GIA forward models. In addition, NASA's GSFC GRACE global mascon solutions are employed. The equal area 1x1 degree gridded mascons are spatially aggregated for larger regions to account for their spatial error correlations. Both the GPS and GRACE datasets are combined with prior information about spatial wavelengths of GIA signals obtained from the ICE-6G model within the BHM framework to solve for GIA. The results are compared with 14 global GIA forward model solutions to identify statistically significant deviations between the forward and inverse solutions, which may be due to either uncertain mantle rheology and/or ice loading history/magnitude.

Gear wear monitoring by modulation signal bispectrum based on motor current signal analysis

NASA Astrophysics Data System (ADS)

Zhang, Ruiliang; Gu, Fengshou; Mansaf, Haram; Wang, Tie; Ball, Andrew D.

2017-09-01

Gears are important mechanical components for power transmissions. Tooth wear is one of the most common failure modes, which can present throughout a gear's lifetime. It is significant to accurately monitor gear wear progression in order to take timely predictive maintenances. Motor current signature analysis (MCSA) is an effective and non-intrusive approach which is able to monitor faults from both electrical and mechanical systems. However, little research has been reported in monitoring the gear wear and estimating its severity based on MCSA. This paper presents a novel gear wear monitoring method through a modulation signal bispectrum based motor current signal analysis (MSB-MCSA). For a steady gear transmission, it is inevitable to exist load and speed oscillations due to various errors including wears. These oscillations can induce small modulations in the current signals of the driving motor. MSB is particularly effective in characterising such small modulation signals. Based on these understandings, the monitoring process was implemented based on the current signals from a run-to-failure test of an industrial two stages helical gearbox under a moderate accelerated fatigue process. At the initial operation of the test, MSB analysis results showed that the peak values at the bifrequencies of gear rotations and the power supply can be effective monitoring features for identifying faulty gears and wear severity as they exhibit agreeable changes with gear loads. A monotonically increasing trend established by these features allows a clear indication of the gear wear progression. The dismantle inspection at 477 h of operation, made when one of the monitored features is about 123% higher than its baseline, has found that there are severe scuffing wear marks on a number of tooth surfaces on the driving gear, showing that the gear endures a gradual wear process during its long test operation. Therefore, it is affirmed that the MSB-MSCA approach proposed is reliable and accurate for monitoring gear wear deterioration.

SEMICONDUCTOR TECHNOLOGY A signal processing method for the friction-based endpoint detection system of a CMP process

NASA Astrophysics Data System (ADS)

Chi, Xu; Dongming, Guo; Zhuji, Jin; Renke, Kang

2010-12-01

A signal processing method for the friction-based endpoint detection system of a chemical mechanical polishing (CMP) process is presented. The signal process method uses the wavelet threshold denoising method to reduce the noise contained in the measured original signal, extracts the Kalman filter innovation from the denoised signal as the feature signal, and judges the CMP endpoint based on the feature of the Kalman filter innovation sequence during the CMP process. Applying the signal processing method, the endpoint detection experiments of the Cu CMP process were carried out. The results show that the signal processing method can judge the endpoint of the Cu CMP process.

Mitochondria and Reactive Oxygen Species: Physiology and Pathophysiology

PubMed Central

Bolisetty, Subhashini; Jaimes, Edgar A.

2013-01-01

The air that we breathe contains nearly 21% oxygen, most of which is utilized by mitochondria during respiration. While we cannot live without it, it was perceived as a bane to aerobic organisms due to the generation of reactive oxygen and nitrogen metabolites by mitochondria and other cellular compartments. However, this dogma was challenged when these species were demonstrated to modulate cellular responses through altering signaling pathways. In fact, since this discovery of a dichotomous role of reactive species in immune function and signal transduction, research in this field grew at an exponential pace and the pursuit for mechanisms involved began. Due to a significant number of review articles present on the reactive species mediated cell death, we have focused on emerging novel pathways such as autophagy, signaling and maintenance of the mitochondrial network. Despite its role in several processes, increased reactive species generation has been associated with the origin and pathogenesis of a plethora of diseases. While it is tempting to speculate that anti-oxidant therapy would protect against these disorders, growing evidence suggests that this may not be true. This further supports our belief that these reactive species play a fundamental role in maintenance of cellular and tissue homeostasis. PMID:23528859

RAZOR: A Compression and Classification Solution for the Internet of Things

PubMed Central

Danieletto, Matteo; Bui, Nicola; Zorzi, Michele

2014-01-01

The Internet of Things is expected to increase the amount of data produced and exchanged in the network, due to the huge number of smart objects that will interact with one another. The related information management and transmission costs are increasing and becoming an almost unbearable burden, due to the unprecedented number of data sources and the intrinsic vastness and variety of the datasets. In this paper, we propose RAZOR, a novel lightweight algorithm for data compression and classification, which is expected to alleviate both aspects by leveraging the advantages offered by data mining methods for optimizing communications and by enhancing information transmission to simplify data classification. In particular, RAZOR leverages the concept of motifs, recurrent features used for signal categorization, in order to compress data streams: in such a way, it is possible to achieve compression levels of up to an order of magnitude, while maintaining the signal distortion within acceptable bounds and allowing for simple lightweight distributed classification. In addition, RAZOR is designed to keep the computational complexity low, in order to allow its implementation in the most constrained devices. The paper provides results about the algorithm configuration and a performance comparison against state-of-the-art signal processing techniques. PMID:24451454

Encountering bird alarms in full-stare IRSTs

NASA Astrophysics Data System (ADS)

de Jong, Arie N.; Winkel, Hans; Kemp, Rob A. W.

2000-12-01

Birds are a potential source of frequent false alarms in Infrared Search and Track (IRST) systems. One reason is that the signals, generated by birds at short ranges (1-2 km) in IR sensors may be of the same magnitude as the signals generated by real targets (missiles) at long ranges (10-20 km). Another reason is that new generations of IRSTs have more sensitivity which brings more birds within the detection range. Furthermore military operations tend to be held more and more in coastal zones, where the frequency of occurrence of birds is greater than in the open ocean. Finally, the variety in type of birds and their flight characteristics and signature is larger. In the paper attention is spent on the IR signatures of birds in various backgrounds, including rapid variations in signature due to wing motions. Basically, these fluctuations and the flight pattern of a bird provide opportunities to encounter bird alarms in next generation IRSTs, using multiple Focal Plan Array cameras with high frame rates. One has to take into account in this process the difference between signal variations due to wing motions and scintillation for long range targets above the horizon.

The role of the actin cytoskeleton in calcium signaling in starfish oocytes.

PubMed

Santella, Luigia; Puppo, Agostina; Chun, Jong Tai

2008-01-01

Ca2+ is the most universal second messenger in cells from the very first moment of fertilization. In all animal species, fertilized eggs exhibit massive mobilization of intracellular Ca2+ to orchestrate the initial events of development. Echinoderm eggs have been an excellent model system for studying fertilization and the cell cycle due to their large size and abundance. In preparation for fertilization, the cell cycle-arrested oocytes must undergo meiotic maturation. Studies of starfish oocytes have shown that Ca2+ signaling is intimately involved in this process. Our knowledge of the molecular mechanism of meiotic maturation and fertilization has expanded greatly in the past two decades due to the discovery of cell cycle-related kinases and Ca2+-mobilizing second messengers. However, the molecular details of their actions await elucidation of other cellular elements that assist in the creation and transduction of Ca2+ signals. In this regard, the actin cytoskeleton, the receptors for second messengers and the Ca2+-binding proteins also require more attention. This article reviews the physiological significance and the mechanism of intracellular Ca2+ mobilization in starfish oocytes during maturation and fertilization.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Chunfa, E-mail: chunfa.huang@case.edu; Department of Medicine, Case Western Reserve University; Rammelkamp Center for Research and Education, MetroHealth System Campus, Cleveland, OH 44106

The glomerular capillary wall, composed of endothelial cells, the glomerular basement membrane and the podocytes, is continually subjected to hemodynamic force arising from tractional stress due to blood pressure and shear stress due to blood flow. Exposure of glomeruli to abnormal hemodynamic force such as hyperfiltration is associated with glomerular injury and progressive renal disease, and the conversion of mechanical stimuli to chemical signals in the regulation of the process is poorly understood in podocytes. By examining DNA fragmentation, apoptotic nuclear changes and cytochrome c release, we found that shear stress induced cell apoptosis in cultured podocytes. Meanwhile, podocytes exposedmore » to shear stress also stimulated c-Src phosphorylation, phospholipase D (PLD) activation and mammalian target of rapamycin (mTOR) signaling. Using the antibodies against c-Src, PLD{sub 1}, and PLD{sub 2} to perform reciprocal co-immunoprecipitations and in vitro PLD activity assay, our data indicated that c-Src interacted with and activated PLD{sub 1} but not PLD{sub 2}. The inhibition of shear stress-induced c-Src phosphorylation by PP{sub 2} (a specific inhibitor of c-Src kinase) resulted in reduced PLD activity. Phosphatidic acid, produced by shear stress-induced PLD activation, stimulated mTOR signaling, and caused podocyte hypertrophy and apoptosis.« less

A smart multisensor approach to assist blind people in specific urban navigation tasks.

PubMed

Ando, B

2008-12-01

Visually impaired people are often discouraged in using electronic aids due to complexity of operation, large amount of training, nonoptimized degree of information provided to the user, and high cost. In this paper, a new multisensor architecture is discussed, which would help blind people to perform urban mobility tasks. The device is based on a multisensor strategy and adopts smart signal processing.

Processes of 30-90 days sea surface temperature variability in the northern Indian Ocean during boreal summer

NASA Astrophysics Data System (ADS)

Vialard, J.; Jayakumar, A.; Gnanaseelan, C.; Lengaigne, M.; Sengupta, D.; Goswami, B. N.

2012-05-01

During summer, the northern Indian Ocean exhibits significant atmospheric intraseasonal variability associated with active and break phases of the monsoon in the 30-90 days band. In this paper, we investigate mechanisms of the Sea Surface Temperature (SST) signature of this atmospheric variability, using a combination of observational datasets and Ocean General Circulation Model sensitivity experiments. In addition to the previously-reported intraseasonal SST signature in the Bay of Bengal, observations show clear SST signals in the Arabian Sea related to the active/break cycle of the monsoon. As the atmospheric intraseasonal oscillation moves northward, SST variations appear first at the southern tip of India (day 0), then in the Somali upwelling region (day 10), northern Bay of Bengal (day 19) and finally in the Oman upwelling region (day 23). The Bay of Bengal and Oman signals are most clearly associated with the monsoon active/break index, whereas the relationship with signals near Somali upwelling and the southern tip of India is weaker. In agreement with previous studies, we find that heat flux variations drive most of the intraseasonal SST variability in the Bay of Bengal, both in our model (regression coefficient, 0.9, against ~0.25 for wind stress) and in observations (0.8 regression coefficient); ~60% of the heat flux variation is due do shortwave radiation and ~40% due to latent heat flux. On the other hand, both observations and model results indicate a prominent role of dynamical oceanic processes in the Arabian Sea. Wind-stress variations force about 70-100% of SST intraseasonal variations in the Arabian Sea, through modulation of oceanic processes (entrainment, mixing, Ekman pumping, lateral advection). Our ~100 km resolution model suggests that internal oceanic variability (i.e. eddies) contributes substantially to intraseasonal variability at small-scale in the Somali upwelling region, but does not contribute to large-scale intraseasonal SST variability due to its small spatial scale and random phase relation to the active-break monsoon cycle. The effect of oceanic eddies; however, remains to be explored at a higher spatial resolution.

Automated sleep stage detection with a classical and a neural learning algorithm--methodological aspects.

PubMed

Schwaibold, M; Schöchlin, J; Bolz, A

2002-01-01

For classification tasks in biosignal processing, several strategies and algorithms can be used. Knowledge-based systems allow prior knowledge about the decision process to be integrated, both by the developer and by self-learning capabilities. For the classification stages in a sleep stage detection framework, three inference strategies were compared regarding their specific strengths: a classical signal processing approach, artificial neural networks and neuro-fuzzy systems. Methodological aspects were assessed to attain optimum performance and maximum transparency for the user. Due to their effective and robust learning behavior, artificial neural networks could be recommended for pattern recognition, while neuro-fuzzy systems performed best for the processing of contextual information.

Global Infrasound Association Based on Probabilistic Clutter Categorization

NASA Astrophysics Data System (ADS)

Arora, N. S.; Mialle, P.

2015-12-01

The IDC collects waveforms from a global network of infrasound sensors maintained by the IMS, and automatically detects signal onsets and associates them to form event hypotheses. However, a large number of signal onsets are due to local clutter sources such as microbaroms (from standing waves in the oceans), waterfalls, dams, gas flares, surf (ocean breaking waves) etc. These sources are either too diffuse or too local to form events. Worse still, the repetitive nature of this clutter leads to a large number of false event hypotheses due to the random matching of clutter at multiple stations. Previous studies, for example [1], have worked on categorization of clutter using long term trends on detection azimuth, frequency, and amplitude at each station. In this work we continue the same line of reasoning to build a probabilistic model of clutter that is used as part of NET-VISA [2], a Bayesian approach to network processing. The resulting model is a fusion of seismic, hydro-acoustic and infrasound processing built on a unified probabilistic framework. Notes: The attached figure shows all the unassociated arrivals detected at IMS station I09BR for 2012 distributed by azimuth and center frequency. (The title displays the bandwidth of the kernel density estimate along the azimuth and frequency dimensions).This plot shows multiple micro-barom sources as well as other sources of infrasound clutter. A diverse clutter-field such as this one is quite common for most IMS infrasound stations, and it highlights the dangers of forming events without due consideration of this source of noise. References: [1] Infrasound categorization Towards a statistics-based approach. J. Vergoz, P. Gaillard, A. Le Pichon, N. Brachet, and L. Ceranna. ITW 2011 [2] NET-VISA: Network Processing Vertically Integrated Seismic Analysis. N. S. Arora, S. Russell, and E. Sudderth. BSSA 2013.

Use of multitemporal InSAR data to develop geohazard scenarios for Bandung, Western Java, Indonesia

NASA Astrophysics Data System (ADS)

Salvi, Stefano; Tolomei, Cristiano; Duro, Javier; Pezzo, Giuseppe; Koudogbo, Fifamè

2015-04-01

The Greater Bandung metropolitan area is the second largest urban area in Indonesia, with a population of 8.6 million. It is subject to a variety of geohazards: volcanic hazards from seven active volcanoes within a radius of 50 km; high flood hazards, seismic hazard due to crustal active faults, the best known being the 30-km long Lembang fault, 10 km North of the city centre; subsidence hazards due to strong aquifer depletion; landslide hazard in the surrounding high country. In the framework of the FP7 RASOR project, multitemporal satellite SAR data have been processed over Bandung, Western Java. We used the SBAS InSAR technique (Berardino et al., 2002) to process two ALOS-1 datasets, to investigate the various sources of surface deformation acting in the area in the period 2008-2011. Persistent Scatterer Interferometry (PSI) has also been applied to achieve ground motion measurements with millimetric precision and high accuracy. The PSI processing technique considers a system of points that reflect the radar signal from the satellite continuously through the time. It makes use of differential interferometric phase measurements to generate long term terrain deformation and digital surface model maps. The GlobalSARTM algorithms developed by Altamira Information are applied to COSMO-SkyMed data acquired to measure ground motion over the area of interest. Strong ground displacements (up to 7 cm/yr) due to groundwater abstraction have been measured in the Bandung basin. The identification of long wavelength signals from tectonic sources is difficult due to the limited InSAR coherence outside of the urban environment. Limited deformation is observed also in the Tangkuban Perahu volcano to the north. The spatial and temporal distribution of the ground motion is important supporting information for the generation of long term subsidence and flood hazard scenarios.

A simple predistortion technique for suppression of nonlinear effects in periodic signals generated by nonlinear transducers

NASA Astrophysics Data System (ADS)

Novak, A.; Simon, L.; Lotton, P.

2018-04-01

Mechanical transducers, such as shakers, loudspeakers and compression drivers that are used as excitation devices to excite acoustical or mechanical nonlinear systems under test are imperfect. Due to their nonlinear behaviour, unwanted contributions appear at their output besides the wanted part of the signal. Since these devices are used to study nonlinear systems, it should be required to measure properly the systems under test by overcoming the influence of the nonlinear excitation device. In this paper, a simple method that corrects distorted output signal of the excitation device by means of predistortion of its input signal is presented. A periodic signal is applied to the input of the excitation device and, from analysing the output signal of the device, the input signal is modified in such a way that the undesirable spectral components in the output of the excitation device are cancelled out after few iterations of real-time processing. The experimental results provided on an electrodynamic shaker show that the spectral purity of the generated acceleration output approaches 100 dB after few iterations (1 s). This output signal, applied to the system under test, is thus cleaned from the undesirable components produced by the excitation device; this is an important condition to ensure a correct measurement of the nonlinear system under test.

Interpretation of interference signals in label free integrated interferometric biosensors

NASA Astrophysics Data System (ADS)

Heikkinen, Hanna; Wang, Meng; Okkonen, Matti; Hast, Jukka; Myllylä, Risto

2006-02-01

In the future fast, simple and reliable biosensors will be needed to detect various analytes from different biosamples. This is due to fact that the needs of traditional health care are changing. In the future homecare of patients and peoples' responsibility for their own health will increase. Also, different wellness applications need new parameters to be analysed, reducing costs of traditional health care, which are increasing rapidly. One fascinating and promising sensor type for these applications is an integrated optical interferometric immunosensor, which is manufactured using organic materials. The use of organic materials opens up enormous possibilities to develop different biochemical functions. In label free biosensors the measurement is based on detecting changes in refractive index, which typically are in the range of 10 -6-10 -8 [1]. In this research, theoretically generated interferograms are used to compare various signal processing methods. The goal is to develop an efficient method to analyse the interferogram. Different time domain signal processing methods are studied to determine the measuring resolution and efficiency of these methods. A low cost CCD -element is used in detecting the interferogram dynamics. It was found that in most of the signal processing methods the measuring resolution was mainly limited by pixel size. With calculation of Pearson's correlation coefficient, subpixel resolution was achieved which means that nanometer range optical path differences can be measured. This results in the refractive index resolution of the order of 10 -7.

Split-spectrum processing technique for SNR enhancement of ultrasonic guided wave.

PubMed

Pedram, Seyed Kamran; Fateri, Sina; Gan, Lu; Haig, Alex; Thornicroft, Keith

2018-02-01

Ultrasonic guided wave (UGW) systems are broadly used in several branches of industry where the structural integrity is of concern. In those systems, signal interpretation can often be challenging due to the multi-modal and dispersive propagation of UGWs. This results in degradation of the signals in terms of signal-to-noise ratio (SNR) and spatial resolution. This paper employs the split-spectrum processing (SSP) technique in order to enhance the SNR and spatial resolution of UGW signals using the optimized filter bank parameters in real time scenario for pipe inspection. SSP technique has already been developed for other applications such as conventional ultrasonic testing for SNR enhancement. In this work, an investigation is provided to clarify the sensitivity of SSP performance to the filter bank parameter values for UGWs such as processing bandwidth, filter bandwidth, filter separation and a number of filters. As a result, the optimum values are estimated to significantly improve the SNR and spatial resolution of UGWs. The proposed method is synthetically and experimentally compared with conventional approaches employing different SSP recombination algorithms. The Polarity Thresholding (PT) and PT with Minimization (PTM) algorithms were found to be the best recombination algorithms. They substantially improved the SNR up to 36.9dB and 38.9dB respectively. The outcome of the work presented in this paper paves the way to enhance the reliability of UGW inspections. Copyright © 2017 Elsevier B.V. All rights reserved.

Role of nitric oxide in pheromone-mediated intraspecific communication in mice.

PubMed

Agustín-Pavón, Carmen; Martínez-Ricós, Joana; Martínez-García, Fernando; Lanuza, Enrique

2009-12-07

Nitric oxide is known to take part in the control of sexual and agonistic behaviours. This is usually attributed to its role in neural transmission in the hypothalamus and other structures of the limbic system. However, socio-sexual behaviours in rodents are mainly directed by chemical signals detected by the vomeronasal system, and nitric oxide is abundant in key structures along the vomeronasal pathway. Thus, here we check whether pharmacological treatments interfering with nitrergic transmission could affect socio-sexual behaviour by impairing the processing of chemical signals. Treatment with an inhibitor of nitric oxide synthesis (Nomega-Nitro-l-arginine methyl ester hydrochloride, L-NAME, 100mg/kg) blocks the innate preference displayed by female mice for sexual pheromones contained in male-soiled bedding, with a lower dose of the drug (50mg/kg) having no effect. Animals treated with the high dose of L-NAME show no reduction of olfactory discrimination of male urine in a habituation-dishabituation test, thus suggesting that the effect of the drug on the preference for male pheromones is not due to an inability to detect male urine. Alternatively, it may result from an alteration in processing the reinforcing value of pheromones as sexual signals. These results add a new piece of evidence to our understanding of the neurochemistry of intraspecific chemical communication in rodents, and suggest that the role of nitric oxide in socio-sexual behaviours should be re-evaluated taking into account the involvement of this neuromodulator in the processing of chemical signals.

The Applicability of Incoherent Array Processing to IMS Seismic Array Stations

NASA Astrophysics Data System (ADS)

Gibbons, S. J.

2012-04-01

The seismic arrays of the International Monitoring System for the CTBT differ greatly in size and geometry, with apertures ranging from below 1 km to over 60 km. Large and medium aperture arrays with large inter-site spacings complicate the detection and estimation of high frequency phases since signals are often incoherent between sensors. Many such phases, typically from events at regional distances, remain undetected since pipeline algorithms often consider only frequencies low enough to allow coherent array processing. High frequency phases that are detected are frequently attributed qualitatively incorrect backazimuth and slowness estimates and are consequently not associated with the correct event hypotheses. This can lead to missed events both due to a lack of contributing phase detections and by corruption of event hypotheses by spurious detections. Continuous spectral estimation can be used for phase detection and parameter estimation on the largest aperture arrays, with phase arrivals identified as local maxima on beams of transformed spectrograms. The estimation procedure in effect measures group velocity rather than phase velocity and the ability to estimate backazimuth and slowness requires that the spatial extent of the array is large enough to resolve time-delays between envelopes with a period of approximately 4 or 5 seconds. The NOA, AKASG, YKA, WRA, and KURK arrays have apertures in excess of 20 km and spectrogram beamforming on these stations provides high quality slowness estimates for regional phases without additional post-processing. Seven arrays with aperture between 10 and 20 km (MJAR, ESDC, ILAR, KSRS, CMAR, ASAR, and EKA) can provide robust parameter estimates subject to a smoothing of the resulting slowness grids, most effectively achieved by convolving the measured slowness grids with the array response function for a 4 or 5 second period signal. The MJAR array in Japan recorded high SNR Pn signals for both the 2006 and 2009 North Korea nuclear tests but, due to signal incoherence, failed to contribute to the automatic event detections. It is demonstrated that the smoothed incoherent slowness estimates for the MJAR Pn phases for both tests indicate unambiguously the correct type of phase and a backazimuth estimate within 5 degrees of the great-circle backazimuth. The detection part of the algorithm is applicable to all IMS arrays, and spectrogram-based processing may offer a reduction in the false alarm rate for high frequency signals. Significantly, the local maxima of the scalar functions derived from the transformed spectrogram beams provide good estimates of the signal onset time. High frequency energy is of greater significance for lower event magnitudes and in, for example, the cavity decoupling detection evasion scenario. There is a need to characterize propagation paths with low attenuation of high frequency energy and situations in which parameter estimation on array stations fails.

I. Advances in NMR Signal Processing. II. Spin Dynamics in Quantum Dissipative Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Yung-Ya

1998-11-01

Part I. Advances in IVMR Signal Processing. Improvements of sensitivity and resolution are two major objects in the development of NMR/MRI. A signal enhancement method is first presented which recovers signal from noise by a judicious combination of a priordmowledge to define the desired feasible solutions and a set theoretic estimation for restoring signal properties that have been lost due to noise contamination. The effect of noise can be significantly mitigated through the process of iteratively modifying the noisy data set to the smallest degree necessary so that it possesses a collection of prescribed properties and also lies closest tomore » the original data set. A novel detection-estimation scheme is then introduced to analyze noisy and/or strongly damped or truncated FIDs. Based on exponential modeling, the number of signals is detected based on information estimated using the matrix pencil method. theory and the spectral parameters are Part II. Spin Dynamics in body dipole-coupled systems Quantum Dissipative Systems. Spin dynamics in manyconstitutes one of the most fundamental problems in magnetic resonance and condensed-matter physics. Its many-spin nature precludes any rigorous treatment. ‘Therefore, the spin-boson model is adopted to describe in the rotating frame the influence of the dipolar local fields on a tagged spin. Based on the polaronic transform and a perturbation treatment, an analytical solution is derived, suggesting the existence of self-trapped states in the. strong coupling limit, i.e., when transverse local field >> longitudinal local field. Such nonlinear phenomena originate from the joint action of the lattice fluctuations and the reaction field. Under semiclassical approximation, it is found that the main effect of the reaction field is the renormalization of the Hamiltonian of interest. Its direct consequence is the two-step relaxation process: the spin is initially localized in a quasiequilibrium state, which is later detrapped by the lattice fluctuations in an extended time scale. Lowtemperature measurements and classical-spin simulations are carried out to verify the above analysis. To promote the implementation and future study on the topics described in this thesis, program packages of advanced NMR signal processing and many-spin FID simulations are summarized and listed in the Appendix.« less

Validity Using Pump-Probe Pulses to Determine the Optical Response of Niobate Crystals

NASA Technical Reports Server (NTRS)

Liu, Huimin; Jia, Weiyi

1997-01-01

A variety of niobate crystals have found their places in nonlinear optical applications as well as in laser devices. In recent years much attention has been paid to study the ultrafast optical response in a variety of photorefractive crystals such as KTa(1-x)Nb(x)O3 and KNbO3 crystals, glasses, semiconductors and polymers for applications in optical switching, information processing, optical computing, and all-optical device systems. Third-order optical nonlinearity is the most important property for realization of all-optical switching. Therefore experiments have been performed on the third order susceptibility using a variety of techniques such as the third-order harmonic generation, EFISH and degenerate four-wave mixing(DFWM). The latter has been conducted with a variety of pump wavelengths and with nanosecond, picosecond and femtosecond pulses. Niobate crystals, such as potassium niobate KNbO3, potassium tantalate niobate KTN family (KTa(1-x)Nb(x)O3), strontium barium niobate SBN (Sr(x)Ba(1-x)Nb2O6) and potassium-sodium niobate SBN (KNSBN) are attractive due to their photorefractive properties for application in optical storage and processing. The pulsed probe experiments performed on theses materials have suggested two types of time responses. These responses have been associated with an coherent response due to Chi(sup 3), and a long lived component due to excited state population. Recent study of DFWM on KNbO3 and KTN family reveals that the long lived component of those crystals depends on the crystal orientation. A slowly decaying signal is observable when the grating vector K(sub g) is not perpendicular to the C-axis of those photorefractive crystals', otherwise the optical response signal would be only a narrow coherent peak with FWHM equal to the cross-correlation width of the write beam pulses. Based on this understanding, we study the photodynamical process of a variety of niobate crystals using DFWM in a Kg perpindicular to C geometry with a ps-YAG: Nd laser operating at 532nm. However, the discrepancies in numerical estimations of Chi(sup 3) in these materials and other nonlinear optical media have resulted in a number of discussions. In order to better understand the photodynamical process of niobate crystals after an short pulse excitation we analyze the factors governing the coherent signal and present the DFWM spectra of niobate crystals.

XUV pulse effect on signal modulations of harmonic spectra from H2+ and T2+

NASA Astrophysics Data System (ADS)

Feng, Liqiang; Liu, Hang; Kapteyn, Henry J.; Feng, April Y.

2018-05-01

The effects of signal modulations on the molecular high-order harmonic generations in H2^{+ } and T2+ have been theoretically investigated. It is found that with the introduction of the XUV pulse, due to the absorption of the extra XUV photons in the recombination process, multiplateaus on the harmonic spectra, separated by the XUV photon energy can be found. Moreover, this multiplateau structure is insensitive to the wavelength of the XUV pulse. In shorter pulse duration, the intensities of the multiplateaus from H2+ are higher than those from T2+; while in longer pulse duration, the opposite results can be found. Finally, by changing the delay time of the XUV pulse, the signal modulations (including the amplitude and the frequency modulations) of the multiplateaus can be controlled.

Vascular Sap Proteomics: Providing Insight into Long-Distance Signaling during Stress

PubMed Central

Carella, Philip; Wilson, Daniel C.; Kempthorne, Christine J.; Cameron, Robin K.

2016-01-01

The plant vascular system, composed of the xylem and phloem, is important for the transport of water, mineral nutrients, and photosynthate throughout the plant body. The vasculature is also the primary means by which developmental and stress signals move from one organ to another. Due to practical and technological limitations, proteomics analysis of xylem and phloem sap has been understudied in comparison to accessible sample types such as leaves and roots. However, recent advances in sample collection techniques and mass spectrometry technology are making it possible to comprehensively analyze vascular sap proteomes. In this mini-review, we discuss the emerging field of vascular sap proteomics, with a focus on recent comparative studies to identify vascular proteins that may play roles in long-distance signaling and other processes during stress responses in plants. PMID:27242852

The Quirky Collider Signals of Folded Supersymmetry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burdman, Gustavo; Chacko, Z.; Goh, Hock-Seng

2008-08-01

We investigate the collider signals associated with scalar quirks ('squirks') in folded supersymmetric models. As opposed to regular superpartners in supersymmetric models these particles are uncolored, but are instead charged under a new confining group, leading to radically different collider signals. Due to the new strong dynamics, squirks that are pair produced do not hadronize separately, but rather form a highly excited bound state. The excited 'squirkonium' loses energy to radiation before annihilating back into Standard Model particles. We calculate the branching fractions into various channels for this process, which is prompt on collider time-scales. The most promising annihilation channelmore » for discovery is W+photon which dominates for squirkonium near its ground state. We demonstrate the feasibility of the LHC search, showing that the mass peak is visible above the SM continuum background and estimate the discovery reach.« less

[INVITED] Signal and noise in Laser Induced Breakdown Spectroscopy: An introductory review

NASA Astrophysics Data System (ADS)

Tognoni, Elisabetta; Cristoforetti, Gabriele

2016-05-01

Laser Induced Breakdown Spectroscopy (LIBS) has become a very popular technique for elemental analysis thanks to its ease of use. However, LIBS users often report poor repeatability of the signal, due to shot-to-shot fluctuations, and consequent not satisfactory limits of detection. In many practical cases, these shortcomings are difficult to control because the signal is affected by several noise sources that cannot be reduced simultaneously. Hopefully, there is a large amount of knowledge, accumulated during several decades, that can provide guidelines to reduce the effect of the single sources of fluctuations. Experimental setup and measurement settings can be optimized on purpose. Spectral data can be processed in order to better exploit the information contained. In the current paper several approaches to improve the analytical figures-of-merit are reviewed and the respective advantages and drawbacks are discussed.

Network Anomaly Detection Based on Wavelet Analysis

NASA Astrophysics Data System (ADS)

Lu, Wei; Ghorbani, Ali A.

2008-12-01

Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

Practical Designs of Brain-Computer Interfaces Based on the Modulation of EEG Rhythms

NASA Astrophysics Data System (ADS)

Wang, Yijun; Gao, Xiaorong; Hong, Bo; Gao, Shangkai

A brain-computer interface (BCI) is a communication channel which does not depend on the brain's normal output pathways of peripheral nerves and muscles [1-3]. It supplies paralyzed patients with a new approach to communicate with the environment. Among various brain monitoring methods employed in current BCI research, electroencephalogram (EEG) is the main interest due to its advantages of low cost, convenient operation and non-invasiveness. In present-day EEG-based BCIs, the following signals have been paid much attention: visual evoked potential (VEP), sensorimotor mu/beta rhythms, P300 evoked potential, slow cortical potential (SCP), and movement-related cortical potential (MRCP). Details about these signals can be found in chapter "Brain Signals for Brain-Computer Interfaces". These systems offer some practical solutions (e.g., cursor movement and word processing) for patients with motor disabilities.

A Robust Distributed Multipoint Fiber Optic Gas Sensor System Based on AGC Amplifier Structure.

PubMed

Zhu, Cunguang; Wang, Rende; Tao, Xuechen; Wang, Guangwei; Wang, Pengpeng

2016-07-28

A harsh environment-oriented distributed multipoint fiber optic gas sensor system realized by automatic gain control (AGC) technology is proposed. To improve the photoelectric signal reliability, the electronic variable gain can be modified in real time by an AGC closed-loop feedback structure to compensate for optical transmission loss which is caused by the fiber bend loss or other reasons. The deviation of the system based on AGC structure is below 4.02% when photoelectric signal decays due to fiber bending loss for bending radius of 5 mm, which is 20 times lower than the ordinary differential system. In addition, the AGC circuit with the same electric parameters can keep the baseline intensity of signals in different channels of the distributed multipoint sensor system at the same level. This avoids repetitive calibrations and streamlines the installation process.

Mutation of KREMEN1, a modulator of Wnt signaling, is responsible for ectodermal dysplasia including oligodontia in Palestinian families.

PubMed

Issa, Yasmin A; Kamal, Lara; Rayyan, Amal Abu; Dweik, Dima; Pierce, Sarah; Lee, Ming K; King, Mary-Claire; Walsh, Tom; Kanaan, Moien

2016-10-01

Tooth development is controlled by the same processes that regulate formation of other ectodermal structures. Mutations in the genes underlying these processes may cause ectodermal dysplasia, including severe absence of primary or permanent teeth. Four consanguineous Palestinian families presented with oligodontia and hair and skin features of ectodermal dysplasia. Appearance of ectodermal dysplasia was consistent with autosomal recessive inheritance. Exome sequencing followed by genotyping of 56 informative relatives in the 4 families suggests that the phenotype is due to homozygosity for KREMEN1 p.F209S (c.626 T>C) on chromosome 22 at g.29,521,399 (hg19). The variant occurs in the highly conserved extracellular WSC domain of KREMEN1, which is known to be a high affinity receptor of Dickkopf-1, a component of the Dickkopf-Kremen-LRP6 complex, and a potent regulator of Wnt signaling. The Wnt signaling pathway is critical to development of ectodermal structures. Mutations in WNT10A, LRP6, EDA, and other genes in this pathway lead to tooth agenesis with or without other ectodermal anomalies. Our results implicate KREMEN1 for the first time in a human disorder and provide additional details on the role of the Wnt signaling in ectodermal and dental development.

Research on signal processing of shock absorber test bench based on zero-phase filter

NASA Astrophysics Data System (ADS)

Wu, Yi; Ding, Guoqing

2017-10-01

The quality of force-displacement diagram is significant to help evaluate the performance of shock absorbers. Damping force sampling data is often interfered by Gauss white noise, 50Hz power interference and its harmonic wave during the process of testing; data de-noising has become the core problem of drawing true, accurate and real-time indicator diagram. The noise and interference can be filtered out through generic IIR or FIR low-pass filter, but addition phase lag of useful signal will be caused due to the inherent attribute of IIR and FIR filter. The paper uses FRR method to realize zero-phase digital filtering in a software way based on mutual cancellation of phase lag between the forward and reverse sequences after through the filter. High-frequency interference above 40Hz are filtered out completely and noise attenuation is more than -40dB, with no additional phase lag. The method is able to restore the true signal as far as possible. Theoretical simulation and practical test indicate high-frequency noises have been effectively inhibited in multiple typical speed cases, signal-to-noise ratio being greatly improved; the curve in indicator diagram has better smoothness and fidelity. The FRR algorithm has low computational complexity, fast running time, and can be easily transplanted in multiple platforms.

All-optical control of light on a graphene-on-silicon nitride chip using thermo-optic effect.

PubMed

Qiu, Ciyuan; Yang, Yuxing; Li, Chao; Wang, Yifang; Wu, Kan; Chen, Jianping

2017-12-06

All-optical signal processing avoids the conversion between optical signals and electronic signals and thus has the potential to achieve a power efficient photonic system. Micro-scale all-optical devices for light manipulation are the key components in the all-optical signal processing and have been built on the semiconductor platforms (e.g., silicon and III-V semiconductors). However, the two-photon absorption (TPA) effect and the free-carrier absorption (FCA) effect in these platforms deteriorate the power handling and limit the capability to realize complex functions. Instead, silicon nitride (Si 3 N 4 ) provides a possibility to realize all-optical large-scale integrated circuits due to its insulator nature without TPA and FCA. In this work, we investigate the physical dynamics of all-optical control on a graphene-on-Si 3 N 4 chip based on thermo-optic effect. In the experimental demonstration, a switching response time constant of 253.0 ns at a switching energy of ~50 nJ is obtained with a device dimension of 60 μm × 60 μm, corresponding to a figure of merit (FOM) of 3.0 nJ mm. Detailed coupled-mode theory based analysis on the thermo-optic effect of the device has been performed.

Signal processing and general purpose data acquisition system for on-line tomographic measurements

NASA Astrophysics Data System (ADS)

Murari, A.; Martin, P.; Hemming, O.; Manduchi, G.; Marrelli, L.; Taliercio, C.; Hoffmann, A.

1997-01-01

New analog signal conditioning electronics and data acquisition systems have been developed for the soft x-ray and bolometric tomography diagnostic in the reverse field pinch experiment (RFX). For the soft x-ray detectors the analog signal processing includes a fully differential current to voltage conversion, with up to a 200 kHz bandwidth. For the bolometers, a 50 kHz carrier frequency amplifier allows a maximum bandwidth of 10 kHz. In both cases the analog signals are digitized with a 1 MHz sampling rate close to the diagnostic and are transmitted via a transparent asynchronous xmitter/receiver interface (TAXI) link to purpose built Versa Module Europa (VME) modules which perform data acquisition. A software library has been developed for data preprocessing and tomographic reconstruction. It has been written in C language and is self-contained, i.e., no additional mathematical library is required. The package is therefore platform-free: in particular it can perform online analysis in a real-time application, such as continuous display and feedback, and is portable for long duration fusion or other physical experiments. Due to the modular organization of the library, new preprocessing and analysis modules can be easily integrated in the environment. This software is implemented in RFX over three different platforms: open VMS, digital Unix, and VME 68040 CPU.

The pivotal role of abscisic acid signaling during transition from seed maturation to germination.

PubMed

Yan, An; Chen, Zhong

2017-05-01

Seed maturation and germination are two continuous developmental processes that link two distinct generations in spermatophytes; the precise genetic control of these two processes is, therefore, crucially important for the survival of the next generation. Pieces of experimental evidence accumulated so far indicate that a concerted action of endogenous signals and environmental cues is required to govern these processes. Plant hormone abscisic acid (ABA) has been suggested to play a predominant role in directing seed maturation and maintaining seed dormancy under unfavorable environmental conditions until antagonized by gibberellins (GA) and certain environmental cues to allow the commencement of seed germination when environmental conditions are favorable; therefore, the balance of ABA and GA is a major determinant of the timing of seed germination. Due to the advent of new technologies and system biology approaches, molecular studies are beginning to draw a picture of the sophisticated genetic network that drives seed maturation during the past decade, though the picture is still incomplete and many details are missing. In this review, we summarize recent advances in ABA signaling pathway in the regulation of seed maturation as well as the transition from seed maturation to germination, and highlight the importance of system biology approaches in the study of seed maturation.

Envelope filter sequence to delete blinks and overshoots.

PubMed

Merino, Manuel; Gómez, Isabel María; Molina, Alberto J

2015-05-30

Eye movements have been used in control interfaces and as indicators of somnolence, workload and concentration. Different techniques can be used to detect them: we focus on the electrooculogram (EOG) in which two kinds of interference occur: blinks and overshoots. While they both draw bell-shaped waveforms, blinks are caused by the eyelid, whereas overshoots occur due to target localization error and are placed on saccade. They need to be extracted from the EOG to increase processing effectiveness. This paper describes off- and online processing implementations based on lower envelope for removing bell-shaped noise; they are compared with a 300-ms-median filter. Techniques were analyzed using two kinds of EOG data: those modeled from our own design, and real signals. Using a model signal allowed to compare filtered outputs with ideal data, so that it was possible to quantify processing precision to remove noise caused by blinks, overshoots, and general interferences. We analyzed the ability to delete blinks and overshoots, and waveform preservation. Our technique had a high capacity for reducing interference amplitudes (>97%), even exceeding median filter (MF) results. However, the MF obtained better waveform preservation, with a smaller dependence on fixation width. The proposed technique is better at deleting blinks and overshoots than the MF in model and real EOG signals.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kirfel, Jutta; Pantelis, Dimitrios; Kabba, Mustapha

Four and one half LIM domain protein FHL2 participates in many cellular processes involved in tissue repair such as regulation of gene expression, cytoarchitecture, cell adhesion, migration and signal transduction. The repair process after wounding is initiated by the release of peptides and bioactive lipids. These molecules induce synthesis and deposition of a provisional extracellular matrix. We showed previously that sphingosine-1-phosphate (S1P) triggers a signal transduction cascade mediating nuclear translocation of FHL2 in response to activation of the RhoA GTPase. Our present study shows that FHL2 is an important signal transducer influencing the outcome of intestinal anastomotic healing. Early woundmore » healing is accompanied by reconstitution and remodelling of the extracellular matrix and collagen is primarily responsible for wound strength. Our results show that impaired intestinal wound healing in Fhl2-deficient mice is due to disturbed collagen III metabolism. Impaired collagen III synthesis reduced the mechanical stability of the anastomoses and led to lower bursting pressure in Fhl2-deficient mice after surgery. Our data confirm that FHL2 is an important factor regulating collagen expression in the early phase of wound healing, and thereby is critically involved in the physiologic process of anastomosis healing after bowel surgery and thus may represent a new therapeutic target.« less

BCI Competition IV – Data Set I: Learning Discriminative Patterns for Self-Paced EEG-Based Motor Imagery Detection

PubMed Central

Zhang, Haihong; Guan, Cuntai; Ang, Kai Keng; Wang, Chuanchu

2012-01-01

Detecting motor imagery activities versus non-control in brain signals is the basis of self-paced brain-computer interfaces (BCIs), but also poses a considerable challenge to signal processing due to the complex and non-stationary characteristics of motor imagery as well as non-control. This paper presents a self-paced BCI based on a robust learning mechanism that extracts and selects spatio-spectral features for differentiating multiple EEG classes. It also employs a non-linear regression and post-processing technique for predicting the time-series of class labels from the spatio-spectral features. The method was validated in the BCI Competition IV on Dataset I where it produced the lowest prediction error of class labels continuously. This report also presents and discusses analysis of the method using the competition data set. PMID:22347153

ATS-6 - Preliminary results from the 13/18-GHz COMSAT Propagation Experiment

NASA Technical Reports Server (NTRS)

Hyde, G.

1975-01-01

The 13/18-GHz COMSAT Propagation Experiment (CPE) is reviewed, the data acquisition and processing are discussed, and samples of preliminary results are presented. The need for measurements of both hydrometeor-induced attenuation statistics and diversity effectiveness is brought out. The facilitation of the experiment - CPE dual frequency and diversity site location, the CPE ground transmit terminals, the CPE transponder on Applications Technology Satellite-6 (ATS-6), and the CPE receive and data acquisition system - is briefly examined. The on-line preprocessing of the received signal is reviewed, followed by a discussion of the off-line processing of this database to remove signal fluctuations not due to hydrometeors. Finally, samples of the results of first-level analysis of the resultant data for the 18-GHz diversity site near Boston, Mass., and for the dual frequency 13/18-GHz site near Detroit, Mich., are presented and discussed.

Solution-Processed Flexible Organic Ferroelectric Phototransistor.

PubMed

Zhao, Qiang; Wang, Hanlin; Jiang, Lang; Zhen, Yonggang; Dong, Huanli; Hu, Wenping

2017-12-20

In this article, we demonstrate ferroelectric insulator, P(VDF-TrFE), can be integrated with red light sensitive polymeric semiconductor, P(DPP-TzBT), toward ferroelectric organic phototransistors (OPTs). This ferroelectricity-modulated phototransistor possesses different nonvolatile and tunable dark current states due to P(VDF-TrFE)'s remnant polarization. As a result, the OPT is endowed with a tunable dark current level ranging from 1 nA to 100 nA. Once the OPT is programmed or electrically polarized, its photo-to-dark (signal-to-noise) ratio can be "flexible" during photodetection process, without gate bias application. This kind of organic ferroelectric phototransistor has great potential in detecting wide ranges of light signals with good linearity. Moreover, its tuning mechanism discussed in this work can be helpful to understand the operation mechanism of organic phototransistor (OPT). It can be promising for novel photodetection application in plastic electronic devices.

Photoluminescence quenching processes by NO2 adsorption in ZnO nanostructured films

NASA Astrophysics Data System (ADS)

Cretı, A.; Valerini, D.; Taurino, A.; Quaranta, F.; Lomascolo, M.; Rella, R.

2012-04-01

The optical response by NO2 gas adsorption at different concentrations has been investigated, at room temperature, in ZnO nanostructured films grown by controlled vapor phase deposition. The variation (quenching) in the photoluminescence signal from excitonic and defects bands, due to the interactions between the oxidizing gas molecules and the sample surface, has been detected and dynamic responses and calibration curves as a function of gas concentration have been obtained and analyzed for each band. We showed that the sensing response results larger in excitonic band than in defect one and that the emission signal rises from two different quenchable and unquenchable states. A simple model was proposed in order to explain the quenching processes on the emission intensity and to correlate them to the morphological features of the samples. Finally, the reversibility of the quenching effects has also been tested at high gas concentration.

Hebbian learning in a model with dynamic rate-coded neurons: an alternative to the generative model approach for learning receptive fields from natural scenes.

PubMed

Hamker, Fred H; Wiltschut, Jan

2007-09-01

Most computational models of coding are based on a generative model according to which the feedback signal aims to reconstruct the visual scene as close as possible. We here explore an alternative model of feedback. It is derived from studies of attention and thus, probably more flexible with respect to attentive processing in higher brain areas. According to this model, feedback implements a gain increase of the feedforward signal. We use a dynamic model with presynaptic inhibition and Hebbian learning to simultaneously learn feedforward and feedback weights. The weights converge to localized, oriented, and bandpass filters similar as the ones found in V1. Due to presynaptic inhibition the model predicts the organization of receptive fields within the feedforward pathway, whereas feedback primarily serves to tune early visual processing according to the needs of the task.

Coherent blue emission generated by Rb two-photon excitation using diode and femtosecond lasers

NASA Astrophysics Data System (ADS)

Lopez, Jesus P.; Moreno, Marco P.; de Miranda, Marcio H. G.; Vianna, Sandra S.

2017-04-01

The coherent blue light generated in rubidium vapor due to the combined action of an ultrashort pulse train and a continuous wave diode laser is investigated. Each step of the two-photon transition 5S-5P{}3/2-5D is excited by one of the lasers, and the induced coherence between the 5S and 6P{}3/2 states is responsible for generating the blue beam. Measurements of the excitation spectrum reveal the frequency comb structure and allow us to identify the resonant modes responsible for inducing the nonlinear process. Further, each resonant mode excites a different group of atoms, making the process selective in atomic velocity. The signal dependency on the atomic density is characterized by a sharp growth and a rapid saturation. We also show that for high intensity of the diode laser, the Stark shift at resonance causes the signal suppression observed at low atomic density.

Neural correlates of combinatorial semantic processing of literal and figurative noun noun compound words.

PubMed

Forgács, Bálint; Bohrn, Isabel; Baudewig, Jürgen; Hofmann, Markus J; Pléh, Csaba; Jacobs, Arthur M

2012-11-15

The right hemisphere's role in language comprehension is supported by results from several neuropsychology and neuroimaging studies. Special interest surrounds right temporoparietal structures, which are thought to be involved in processing novel metaphorical expressions, primarily due to the coarse semantic coding of concepts. In this event related fMRI experiment we aimed at assessing the extent of semantic distance processing in the comprehension of figurative meaning to clarify the role of the right hemisphere. Four categories of German noun noun compound words were presented in a semantic decision task: a) conventional metaphors; b) novel metaphors; c) conventional literal, and; d) novel literal expressions, controlled for length, frequency, imageability, arousal, and emotional valence. Conventional literal and metaphorical compounds increased BOLD signal change in right temporoparietal regions, suggesting combinatorial semantic processing, in line with the coarse semantic coding theory, but at odds with the graded salience hypothesis. Both novel literal and novel metaphorical expressions increased activity in left inferior frontal areas, presumably as a result of phonetic, morphosyntactic, and semantic unification processes, challenging predictions regarding right hemispheric involvement in processing unusual meanings. Meanwhile, both conventional and novel metaphorical expressions induced BOLD signal change in left hemispherical regions, suggesting that even novel metaphor processing involves more than linking semantically distant concepts. Copyright © 2012 Elsevier Inc. All rights reserved.

Llamas: Large-area microphone arrays and sensing systems

NASA Astrophysics Data System (ADS)

Sanz-Robinson, Josue

Large-area electronics (LAE) provides a platform to build sensing systems, based on distributing large numbers of densely spaced sensors over a physically-expansive space. Due to their flexible, "wallpaper-like" form factor, these systems can be seamlessly deployed in everyday spaces. They go beyond just supplying sensor readings, but rather they aim to transform the wealth of data from these sensors into actionable inferences about our physical environment. This requires vertically integrated systems that span the entirety of the signal processing chain, including transducers and devices, circuits, and signal processing algorithms. To this end we develop hybrid LAE / CMOS systems, which exploit the complementary strengths of LAE, enabling spatially distributed sensors, and CMOS ICs, providing computational capacity for signal processing. To explore the development of hybrid sensing systems, based on vertical integration across the signal processing chain, we focus on two main drivers: (1) thin-film diodes, and (2) microphone arrays for blind source separation: 1) Thin-film diodes are a key building block for many applications, such as RFID tags or power transfer over non-contact inductive links, which require rectifiers for AC-to-DC conversion. We developed hybrid amorphous / nanocrystalline silicon diodes, which are fabricated at low temperatures (<200 °C) to be compatible with processing on plastic, and have high current densities (5 A/cm2 at 1 V) and high frequency operation (cutoff frequency of 110 MHz). 2) We designed a system for separating the voices of multiple simultaneous speakers, which can ultimately be fed to a voice-command recognition engine for controlling electronic systems. On a device level, we developed flexible PVDF microphones, which were used to create a large-area microphone array. On a circuit level we developed localized a-Si TFT amplifiers, and a custom CMOS IC, for system control, sensor readout and digitization. On a signal processing level we developed an algorithm for blind source separation in a real, reverberant room, based on beamforming and binary masking. It requires no knowledge about the location of the speakers or microphones. Instead, it uses cluster analysis techniques to determine the time delays for beamforming; thus, adapting to the unique acoustic environment of the room.

Characteristics and limitations of GPS L1 observations from submerged antennas - Theoretical investigation in snow, ice, and freshwater and practical observations within a freshwater layer

NASA Astrophysics Data System (ADS)

Steiner, Ladina; Meindl, Michael; Geiger, Alain

2018-05-01

Observations from a submerged GNSS antenna underneath a snowpack need to be analyzed to investigate its potential for snowpack characterization. The magnitude of the main interaction processes involved in the GPS L1 signal propagation through different layers of snow, ice, or freshwater is examined theoretically in the present paper. For this purpose, the GPS signal penetration depth, attenuation, reflection, refraction as well as the excess path length are theoretically investigated. Liquid water exerts the largest influence on GPS signal propagation through a snowpack. An experiment is thus set up with a submerged geodetic GPS antenna to investigate the influence of liquid water on the GPS observations. The experimental results correspond well with theory and show that the GPS signal penetrates the liquid water up to three centimeters. The error in the height component due to the signal propagation delay in water can be corrected with a newly derived model. The water level above the submerged antenna could also be estimated.

Spatiotemporal transcriptome provides insights into early fruit development of tomato (Solanum lycopersicum).

PubMed

Zhang, Shuaibin; Xu, Meng; Qiu, Zhengkun; Wang, Ketao; Du, Yongchen; Gu, Lianfeng; Cui, Xia

2016-03-18

Early fruit development is crucial for crop production in tomato. After fertilization, the ovary undergoes cell division and cell expansion before maturation. Although the roles of regulatory signals such as hormone and carbohydrate during early fruit development have been studied, the spatial distribution and the sequential initiation of these regulatory signals still need to be explored. Using the tomato cultivar 'Moneymaker', we analyzed the transcriptome of the ovule and the ovary wall/pericarp dissected from four different stages of the early developing fruits by stereoscope. These datasets give us the whole picture about the spatial and temporal signal distribution in early development of ovule and pericarp. Our results indicate that the hormone signal was initiated in both ovule and pericarp after fertilization. After that, different signals were activated in ovule and pericarp due to their distinct developmental processes. Our study provides spatiotemporal regulatory landscape of gene expression with sequential information which was not studied by previous work and further strengthens the comprehension of the regulatory and metabolic events controlling early fruit development.

Domestic horses send signals to humans when they face with an unsolvable task.

PubMed

Ringhofer, Monamie; Yamamoto, Shinya

2017-05-01

Some domestic animals are thought to be skilled at social communication with humans due to the process of domestication. Horses, being in close relationship with humans, similar to dogs, might be skilled at communication with humans. Previous studies have indicated that they are sensitive to bodily signals and the attentional state of humans; however, there are few studies that investigate communication with humans and responses to the knowledge state of humans. Our first question was whether and how horses send signals to their potentially helpful but ignorant caretakers in a problem-solving situation where a food item was hidden in a bucket that was accessible only to the caretakers. We then examined whether horses alter their behaviours on the basis of the caretakers' knowledge of where the food was hidden. We found that horses communicated to their caretakers using visual and tactile signals. The signalling behaviour of the horses significantly increased in conditions where the caretakers had not seen the hiding of the food. These results suggest that horses alter their communicative behaviour towards humans in accordance with humans' knowledge state.

Compressive sensing of signals generated in plastic scintillators in a novel J-PET instrument

NASA Astrophysics Data System (ADS)

Raczyński, L.; Moskal, P.; Kowalski, P.; Wiślicki, W.; Bednarski, T.; Białas, P.; Czerwiński, E.; Gajos, A.; Kapłon, Ł.; Kochanowski, A.; Korcyl, G.; Kowal, J.; Kozik, T.; Krzemień, W.; Kubicz, E.; Niedźwiecki, Sz.; Pałka, M.; Rudy, Z.; Rundel, O.; Salabura, P.; Sharma, N. G.; Silarski, M.; Słomski, A.; Smyrski, J.; Strzelecki, A.; Wieczorek, A.; Zieliński, M.; Zoń, N.

2015-06-01

The J-PET scanner, which allows for single bed imaging of the whole human body, is currently under development at the Jagiellonian University. The discussed detector offers improvement of the Time of Flight (TOF) resolution due to the use of fast plastic scintillators and dedicated electronics allowing for sampling in the voltage domain of signals with durations of few nanoseconds. In this paper we show that recovery of the whole signal, based on only a few samples, is possible. In order to do that, we incorporate the training signals into the Tikhonov regularization framework and we perform the Principal Component Analysis decomposition, which is well known for its compaction properties. The method yields a simple closed form analytical solution that does not require iterative processing. Moreover, from the Bayes theory the properties of regularized solution, especially its covariance matrix, may be easily derived. This is the key to introduce and prove the formula for calculations of the signal recovery error. In this paper we show that an average recovery error is approximately inversely proportional to the number of acquired samples.

FGF signaling refines Wnt gradients to regulate the patterning of taste papillae.

PubMed

Prochazkova, Michaela; Häkkinen, Teemu J; Prochazka, Jan; Spoutil, Frantisek; Jheon, Andrew H; Ahn, Youngwook; Krumlauf, Robb; Jernvall, Jukka; Klein, Ophir D

2017-06-15

The patterning of repeated structures is a major theme in developmental biology, and the inter-relationship between spacing and size of such structures is an unresolved issue. Fungiform papillae are repeated epithelial structures that house taste buds on the anterior tongue. Here, we report that FGF signaling is a crucial regulator of fungiform papillae development. We found that mesenchymal FGF10 controls the size of the papillary area, while overall patterning remains unchanged. Our results show that FGF signaling negatively affects the extent of canonical Wnt signaling, which is the main activation pathway during fungiform papillae development; however, this effect does not occur at the level of gene transcription. Rather, our experimental data, together with computational modeling, indicate that FGF10 modulates the range of Wnt effects, likely via induction of Sostdc1 expression. We suggest that modification of the reach of Wnt signaling could be due to local changes in morphogen diffusion, representing a novel mechanism in this tissue context, and we propose that this phenomenon might be involved in a broader array of mammalian developmental processes. © 2017. Published by The Company of Biologists Ltd.

Radar wideband digital beamforming based on time delay and phase compensation

NASA Astrophysics Data System (ADS)

Fu, Wei; Jiang, Defu

2018-07-01

In conventional phased array radars, analogue time delay devices and phase shifters have been used for wideband beamforming. These methods suffer from insertion losses, gain mismatches and delay variations, and they occupy a large chip area. To solve these problems, a compact architecture of digital array antennas based on subarrays was considered. In this study, the receiving beam patterns of wideband linear frequency modulation (LFM) signals were constructed by applying analogue stretch processing via mixing with delayed reference signals at the subarray level. Subsequently, narrowband digital time delaying and phase compensation of the tone signals were implemented with reduced arithmetic complexity. Due to the differences in amplitudes, phases and time delays between channels, severe performance degradation of the beam patterns occurred without corrections. To achieve good beamforming performance, array calibration was performed in each channel to adjust the amplitude, frequency and phase of the tone signal. Using a field-programmable gate array, wideband LFM signals and finite impulse response filters with continuously adjustable time delays were implemented in a polyphase structure. Simulations and experiments verified the feasibility and effectiveness of the proposed digital beamformer.

Energy Analysis of Decoders for Rakeness-Based Compressed Sensing of ECG Signals.

PubMed

Pareschi, Fabio; Mangia, Mauro; Bortolotti, Daniele; Bartolini, Andrea; Benini, Luca; Rovatti, Riccardo; Setti, Gianluca

2017-12-01

In recent years, compressed sensing (CS) has proved to be effective in lowering the power consumption of sensing nodes in biomedical signal processing devices. This is due to the fact the CS is capable of reducing the amount of data to be transmitted to ensure correct reconstruction of the acquired waveforms. Rakeness-based CS has been introduced to further reduce the amount of transmitted data by exploiting the uneven distribution to the sensed signal energy. Yet, so far no thorough analysis exists on the impact of its adoption on CS decoder performance. The latter point is of great importance, since body-area sensor network architectures may include intermediate gateway nodes that receive and reconstruct signals to provide local services before relaying data to a remote server. In this paper, we fill this gap by showing that rakeness-based design also improves reconstruction performance. We quantify these findings in the case of ECG signals and when a variety of reconstruction algorithms are used either in a low-power microcontroller or a heterogeneous mobile computing platform.

Ephrin-A/EphA specific co-adaptation as a novel mechanism in topographic axon guidance

PubMed Central

Fiederling, Felix; Weschenfelder, Markus; Fritz, Martin; von Philipsborn, Anne; Bastmeyer, Martin; Weth, Franco

2017-01-01

Genetic hardwiring during brain development provides computational architectures for innate neuronal processing. Thus, the paradigmatic chick retinotectal projection, due to its neighborhood preserving, topographic organization, establishes millions of parallel channels for incremental visual field analysis. Retinal axons receive targeting information from quantitative guidance cue gradients. Surprisingly, novel adaptation assays demonstrate that retinal growth cones robustly adapt towards ephrin-A/EphA forward and reverse signals, which provide the major mapping cues. Computational modeling suggests that topographic accuracy and adaptability, though seemingly incompatible, could be reconciled by a novel mechanism of coupled adaptation of signaling channels. Experimentally, we find such ‘co-adaptation’ in retinal growth cones specifically for ephrin-A/EphA signaling. Co-adaptation involves trafficking of unliganded sensors between the surface membrane and recycling endosomes, and is presumably triggered by changes in the lipid composition of membrane microdomains. We propose that co-adaptative desensitization eventually relies on guidance sensor translocation into cis-signaling endosomes to outbalance repulsive trans-signaling. DOI: http://dx.doi.org/10.7554/eLife.25533.001 PMID:28722651

Modeling the Atmospheric Phase Effects of a Digital Antenna Array Communications System

NASA Technical Reports Server (NTRS)

Tkacenko, A.

2006-01-01

In an antenna array system such as that used in the Deep Space Network (DSN) for satellite communication, it is often necessary to account for the effects due to the atmosphere. Typically, the atmosphere induces amplitude and phase fluctuations on the transmitted downlink signal that invalidate the assumed stationarity of the signal model. The degree to which these perturbations affect the stationarity of the model depends both on parameters of the atmosphere, including wind speed and turbulence strength, and on parameters of the communication system, such as the sampling rate used. In this article, we focus on modeling the atmospheric phase fluctuations in a digital antenna array communications system. Based on a continuous-time statistical model for the atmospheric phase effects, we show how to obtain a related discrete-time model based on sampling the continuous-time process. The effects of the nonstationarity of the resulting signal model are investigated using the sample matrix inversion (SMI) algorithm for minimum mean-squared error (MMSE) equalization of the received signal

Genetic Alterations of the Thrombopoietin/MPL/JAK2 Axis Impacting Megakaryopoiesis.

PubMed

Plo, Isabelle; Bellanné-Chantelot, Christine; Mosca, Matthieu; Mazzi, Stefania; Marty, Caroline; Vainchenker, William

2017-01-01

Megakaryopoiesis is an original and complex cell process which leads to the formation of platelets. The homeostatic production of platelets is mainly regulated and controlled by thrombopoietin (TPO) and the TPO receptor (MPL)/JAK2 axis. Therefore, any hereditary or acquired abnormality affecting this signaling axis can result in thrombocytosis or thrombocytopenia. Thrombocytosis can be due to genetic alterations that affect either the intrinsic MPL signaling through gain-of-function (GOF) activity ( MPL, JAK2, CALR ) and loss-of-function (LOF) activity of negative regulators ( CBL, LNK ) or the extrinsic MPL signaling by THPO GOF mutations leading to increased TPO synthesis. Alternatively, thrombocytosis may paradoxically result from mutations of MPL leading to an abnormal MPL trafficking, inducing increased TPO levels by alteration of its clearance. In contrast, thrombocytopenia can also result from LOF THPO or MPL mutations, which cause a complete defect in MPL trafficking to the cell membrane, impaired MPL signaling or stability, defects in the TPO/MPL interaction, or an absence of TPO production.

Genetic Alterations of the Thrombopoietin/MPL/JAK2 Axis Impacting Megakaryopoiesis

PubMed Central

Plo, Isabelle; Bellanné-Chantelot, Christine; Mosca, Matthieu; Mazzi, Stefania; Marty, Caroline; Vainchenker, William

2017-01-01

Megakaryopoiesis is an original and complex cell process which leads to the formation of platelets. The homeostatic production of platelets is mainly regulated and controlled by thrombopoietin (TPO) and the TPO receptor (MPL)/JAK2 axis. Therefore, any hereditary or acquired abnormality affecting this signaling axis can result in thrombocytosis or thrombocytopenia. Thrombocytosis can be due to genetic alterations that affect either the intrinsic MPL signaling through gain-of-function (GOF) activity (MPL, JAK2, CALR) and loss-of-function (LOF) activity of negative regulators (CBL, LNK) or the extrinsic MPL signaling by THPO GOF mutations leading to increased TPO synthesis. Alternatively, thrombocytosis may paradoxically result from mutations of MPL leading to an abnormal MPL trafficking, inducing increased TPO levels by alteration of its clearance. In contrast, thrombocytopenia can also result from LOF THPO or MPL mutations, which cause a complete defect in MPL trafficking to the cell membrane, impaired MPL signaling or stability, defects in the TPO/MPL interaction, or an absence of TPO production. PMID:28955303

Fringe pattern information retrieval using wavelets

NASA Astrophysics Data System (ADS)

Sciammarella, Cesar A.; Patimo, Caterina; Manicone, Pasquale D.; Lamberti, Luciano

2005-08-01

Two-dimensional phase modulation is currently the basic model used in the interpretation of fringe patterns that contain displacement information, moire, holographic interferometry, speckle techniques. Another way to look to these two-dimensional signals is to consider them as frequency modulated signals. This alternative interpretation has practical implications similar to those that exist in radio engineering for handling frequency modulated signals. Utilizing this model it is possible to obtain frequency information by using the energy approach introduced by Ville in 1944. A natural complementary tool of this process is the wavelet methodology. The use of wavelet makes it possible to obtain the local values of the frequency in a one or two dimensional domain without the need of previous phase retrieval and differentiation. Furthermore from the properties of wavelets it is also possible to obtain at the same time the phase of the signal with the advantage of a better noise removal capabilities and the possibility of developing simpler algorithms for phase unwrapping due to the availability of the derivative of the phase.

VLC-beacon detection with an under-sampled ambient light sensor

NASA Astrophysics Data System (ADS)

Green, Jacob; Pérez-Olivas, Huetzin; Martínez-Díaz, Saúl; García-Márquez, Jorge; Domínguez-González, Carlos; Santiago-Montero, Raúl; Guan, Hongyu; Rozenblat, Marc; Topsu, Suat

2017-08-01

LEDs will replace in a near future the current worldwide lighting mainly due to their low production-cost and energy-saving assets. Visible light communications (VLC) will turn gradually the existing lighting network into a communication network. Nowadays VLC transceivers can be found in some commercial centres in Europe; some of them broadcast continuously an identification tag that contains its coordinate position. In such a case, the transceiver acts as a geolocation beacon. Nevertheless, mobile transceivers represent a challenge in the VLC communication chain, as smartphones have not integrated yet a VLC customized detection stage. In order to make current smartphones capable to detect VLC broadcasted signals, their Ambient Light Sensor (ALS) is adapted as a VLC detector. For this to be achieved, lighting transceivers need to adapt their modulation scheme. For instance, frequencies representing start bit, 1, and 0 logic values can be set to avoid flicker from illumination and to permit detecting the under-sampled signal. Decoding the signal requires a multiple steps real-time signal processing as shown here.

Clinical system for non-invasive in situ monitoring of gases in the human paranasal sinuses.

PubMed

Lewander, Märta; Guan, Zuguang; Svanberg, Katarina; Svanberg, Sune; Svensson, Tomas

2009-06-22

We present a portable system for non-invasive, simultaneous sensing of molecular oxygen (O(2)) and water vapor (H(2)O) in the human paranasal cavities. The system is based on high-resolution tunable diode laser spectroscopy (TDLAS) and digital wavelength modulation spectroscopy (dWMS). Since optical interference and non-ideal tuning of the diode lasers render signal processing complex, we focus on Fourier analysis of dWMS signals and procedures for removal of background signals. Clinical data are presented, and exhibit a significant improvement in signal-to-noise with respect to earlier work. The in situ detection limit, in terms of absorption fraction, is about 5x10(-5) for oxygen and 5x10(-4) for water vapor, but varies between patients due to differences in light attenuation. In addition, we discuss the use of water vapor as a reference in quantification of in situ oxygen concentration in detail. In particular, light propagation aspects are investigated by employing photon time-of-flight spectroscopy.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Mechanism for propagation of rate signals through a 10-layer feedforward neuronal network

NASA Astrophysics Data System (ADS)

Li, Jie; Yu, Wan-Qing; Xu, Ding; Liu, Feng; Wang, Wei

2009-12-01

Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feedforward network composed of Hodgkin-Huxley (HH) neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant τsyn varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of τsyn, suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks.

Solar cycle signal in air temperature in North America - Amplitude, gradient, phase and distribution

NASA Technical Reports Server (NTRS)

Currie, R. G.

1981-01-01

The considered investigation was motivated by three factors. One is related to an extension of single-channel MESA to multi-channel by Strand (1977), Morf et al. (1978), and Jones (1978). MESA is a high-resolution signal processing and spectrum analysis technique due to Burg (1975). The considered developments resulted in the discovery of the 11-year solar cycle signal in the change of the length of day by Currie (1980, 1981). They also led Currie (1981) to study the phase spectrum of the 11-year term in height H of sea level. The investigation tries to clarify the phase relations among the involved parameters. The second factor is connected with an application of the linear time domain technique used by Currie (1981) to temperature records to obtain more accurate information regarding the signal amplitude. The third factor of motivation is related to increases in the number of stations available for an analysis, the greater average length of the records, and the more accurate data set.

Retained energy-based coding for EEG signals.

PubMed

Bazán-Prieto, Carlos; Blanco-Velasco, Manuel; Cárdenas-Barrera, Julián; Cruz-Roldán, Fernando

2012-09-01

The recent use of long-term records in electroencephalography is becoming more frequent due to its diagnostic potential and the growth of novel signal processing methods that deal with these types of recordings. In these cases, the considerable volume of data to be managed makes compression necessary to reduce the bit rate for transmission and storage applications. In this paper, a new compression algorithm specifically designed to encode electroencephalographic (EEG) signals is proposed. Cosine modulated filter banks are used to decompose the EEG signal into a set of subbands well adapted to the frequency bands characteristic of the EEG. Given that no regular pattern may be easily extracted from the signal in time domain, a thresholding-based method is applied for quantizing samples. The method of retained energy is designed for efficiently computing the threshold in the decomposition domain which, at the same time, allows the quality of the reconstructed EEG to be controlled. The experiments are conducted over a large set of signals taken from two public databases available at Physionet and the results show that the compression scheme yields better compression than other reported methods. Copyright © 2011 IPEM. Published by Elsevier Ltd. All rights reserved.

High-frequency signal and noise estimates of CSR GRACE RL04

NASA Astrophysics Data System (ADS)

Bonin, Jennifer A.; Bettadpur, Srinivas; Tapley, Byron D.

2012-12-01

A sliding window technique is used to create daily-sampled Gravity Recovery and Climate Experiment (GRACE) solutions with the same background processing as the official CSR RL04 monthly series. By estimating over shorter time spans, more frequent solutions are made using uncorrelated data, allowing for higher frequency resolution in addition to daily sampling. Using these data sets, high-frequency GRACE errors are computed using two different techniques: assuming the GRACE high-frequency signal in a quiet area of the ocean is the true error, and computing the variance of differences between multiple high-frequency GRACE series from different centers. While the signal-to-noise ratios prove to be sufficiently high for confidence at annual and lower frequencies, at frequencies above 3 cycles/year the signal-to-noise ratios in the large hydrological basins looked at here are near 1.0. Comparisons with the GLDAS hydrological model and high frequency GRACE series developed at other centers confirm CSR GRACE RL04's poor ability to accurately and reliably measure hydrological signal above 3-9 cycles/year, due to the low power of the large-scale hydrological signal typical at those frequencies compared to the GRACE errors.

Correlator data analysis for the array feed compensation system

NASA Technical Reports Server (NTRS)

Iijima, B.; Fort, D.; Vilnrotter, V.

1994-01-01

The real-time array feed compensation system is currently being evaluated at DSS 13. This system recovers signal-to-noise ratio (SNR) loss due to mechanical antenna deformations by using an array of seven Ka-band (33.7-GHz) horns to collect the defocused signal fields. The received signals are downconverted and digitized, in-phase and quadrature samples are generated, and combining weights are applied before the samples are recombined. It is shown that when optimum combining weights are employed, the SNR of the combined signal approaches the sum of the channel SNR's. The optimum combining weights are estimated directly from the signals in each channel by the Real-Time Block 2 (RTB2) correlator; since it was designed for very-long-baseline interferometer (VLBI) applications, it can process broadband signals as well as tones to extract the required weight estimates. The estimation algorithms for the optimum combining weights are described for tones and broadband sources. Data recorded in correlator output files can also be used off-line to estimate combiner performance by estimating the SNR in each channel, which was done for data taken during a Jupiter track at DSS 13.

Extraction of Qualitative Features from Sensor Data Using Windowed Fourier Transform

NASA Technical Reports Server (NTRS)

Amini, Abolfazl M.; Figueroa, Fenando

2003-01-01

In this paper, we use Matlab to model the health monitoring of a system through the information gathered from sensors. This implies assessment of the condition of the system components. Once a normal mode of operation is established any deviation from the normal behavior indicates a change. This change may be due to a malfunction of an element, a qualitative change, or a change due to a problem with another element in the network. For example, if one sensor indicates that the temperature in the tank has experienced a step change then a pressure sensor associated with the process in the tank should also experience a step change. The step up and step down as well as sensor disturbances are assumed to be exponential. An RC network is used to model the main process, which is step-up (charging), drift, and step-down (discharging). The sensor disturbances and spike are added while the system is in drift. The system is allowed to run for a period equal to three time constant of the main process before changes occur. Then each point of the signal is selected with a trailing data collected previously. Two trailing lengths of data are selected, one equal to two time constants of the main process and the other equal to two time constants of the sensor disturbance. Next, the DC is removed from each set of data and then the data are passed through a window followed by calculation of spectra for each set. In order to extract features the signal power, peak, and spectrum are plotted vs time. The results indicate distinct shapes corresponding to each process. The study is also carried out for a number of Gaussian distributed noisy cases.

Global scale stratospheric processes as measured by the infrasound IMS network

NASA Astrophysics Data System (ADS)

Le Pichon, A.; Ceranna, L.; Kechut, P.

2012-12-01

IMS infrasound array data are routinely processed at the International Data Center (IDC). The wave parameters of the detected signals are estimated with the Progressive Multi-Channel Correlation method (PMCC). We have processed continuous recordings from 41 certified IMS stations from 2005 to 2010 in the 0.01-5 Hz frequency band using a new implementation of the PMCC algorithm. Microbaroms are the dominant source of signals near-continuously and globally detected. The observed azimuthal seasonal trend correlates well with the variation of the effective sound speed ratio (Veff-ratio) which is a proxy for the combined effects of refraction due to sound speed gradients and advection due to along-path stratospheric wind on infrasound propagation. Systematic correlations between infrasound parameters (e.g. number of detections, amplitude) and Veff-ratio calculated at different ranges of altitudes are performed. Combined with propagation modeling, we show that such an analysis enables a characterization of the wind and temperature structure above the stratosphere and may provide detailed information on upper atmospheric processes (e.g., large-scale planetary waves, stratospheric warming effects) from the seasonal trend to short time scale variability. We discuss the potential benefit of long-term infrasound monitoring to infer stratospheric processes for the first time on a global scale. This study suggests poorly resolved stratospheric wind fluctuations at low latitude regions with strengths of horizontal wind structures underestimated by at least ~10 m/s. It is expected that this correlation between infrasound observations and the state-of-the-art atmospheric specifications will allow to statistically quantify the spatial and temporal resolutions of the wind structures at different ranges of altitudes, latitudes and time scales.

Label-free detection of circulating melanoma cells by in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Wang, Xiaoling; Yang, Ping; Liu, Rongrong; Niu, Zhenyu; Suo, Yuanzhen; He, Hao; Gao, Wenyuan; Tang, Shuo; Wei, Xunbin

2016-03-01

Melanoma is a malignant tumor of melanocytes. Melanoma cells have high light absorption due to melanin highly contained in melanoma cells. This property is employed for the detection of circulating melanoma cell by in vivo photoacoustic flow cytometry (PAFC), which is based on photoacoustic effect. Compared to in vivo flow cytometry based on fluorescence, PAFC can employ high melanin content of melanoma cells as endogenous biomarkers to detect circulating melanoma cells in vivo. We have developed in vitro experiments to prove the ability of PAFC system of detecting photoacoustic signals from melanoma cells. For in vivo experiments, we have constructed a model of melanoma tumor bearing mice by inoculating highly metastatic murine melanoma cancer cells, B16F10 with subcutaneous injection. PA signals are detected in the blood vessels of mouse ears in vivo. The raw signal detected from target cells often contains some noise caused by electronic devices, such as background noise and thermal noise. We choose the Wavelet denoising method to effectively distinguish the target signal from background noise. Processing in time domain and frequency domain would be combined to analyze the signal after denoising. This algorithm contains time domain filter and frequency transformation. The frequency spectrum image of the signal contains distinctive features that can be used to analyze the property of target cells or particles. The processing methods have a great potential for analyzing signals accurately and rapidly. By counting circulating melanoma cells termly, we obtain the number variation of circulating melanoma cells as melanoma metastasized. Those results show that PAFC is a noninvasive and label-free method to detect melanoma metastases in blood or lymph circulation.

Surface code—biophysical signals for apoptotic cell clearance

NASA Astrophysics Data System (ADS)

Biermann, Mona; Maueröder, Christian; Brauner, Jan M.; Chaurio, Ricardo; Janko, Christina; Herrmann, Martin; Muñoz, Luis E.

2013-12-01

Apoptotic cell death and the clearance of dying cells play an important and physiological role in embryonic development and normal tissue turnover. In contrast to necrosis, apoptosis proceeds in an anti-inflammatory manner. It is orchestrated by the timed release and/or exposure of so-called ‘find-me’, ‘eat me’ and ‘tolerate me’ signals. Mononuclear phagocytes are attracted by various ‘find-me’ signals, including proteins, nucleotides, and phospholipids released by the dying cell, whereas the involvement of granulocytes is prevented via ‘stay away’ signals. The exposure of anionic phospholipids like phosphatidylserine (PS) by apoptotic cells on the outer leaflet of the plasma membrane is one of the main ‘eat me’ signals. PS is recognized by a number of innate receptors as well as by soluble bridging molecules on the surface of phagocytes. Importantly, phagocytes are able to discriminate between viable and apoptotic cells both exposing PS. Due to cytoskeleton remodeling PS has a higher lateral mobility on the surfaces of apoptotic cells thereby promoting receptor clustering on the phagocyte. PS not only plays an important role in the engulfment process, but also acts as ‘tolerate me’ signal inducing the release of anti-inflammatory cytokines by phagocytes. An efficient and fast clearance of apoptotic cells is required to prevent secondary necrosis and leakage of intracellular danger signals into the surrounding tissue. Failure or prolongation of the clearance process leads to the release of intracellular antigens into the periphery provoking inflammation and development of systemic inflammatory autoimmune disease like systemic lupus erythematosus. Here we review the current findings concerning apoptosis-inducing pathways, important players of apoptotic cell recognition and clearance as well as the role of membrane remodeling in the engulfment of apoptotic cells by phagocytes.

Arrestin-2 and arrestin-3 differentially modulate locomotor responses and sensitization to amphetamine.

PubMed

Zurkovsky, Lilia; Sedaghat, Katayoun; Ahmed, M Rafiuddin; Gurevich, Vsevolod V; Gurevich, Eugenia V

2017-07-15

Arrestins play a prominent role in shutting down signaling via G protein-coupled receptors. In recent years, a signaling role for arrestins independent of their function in receptor desensitization has been discovered. Two ubiquitously expressed arrestin isoforms, arrestin-2 and arrestin-3, perform similarly in the desensitization process and share many signaling functions, enabling them to substitute for one another. However, signaling roles specific to each isoform have also been described. Mice lacking arrestin-3 (ARR3KO) were reported to show blunted acute responsiveness to the locomotor stimulatory effect of amphetamine (AMPH). It has been suggested that mice with deletion of arrestin-2 display a similar phenotype. Here we demonstrate that the AMPH-induced locomotion of male ARR3KO mice is reduced over the 7-day treatment period and during AMPH challenge after a 7-day withdrawal. The data are consistent with impaired locomotor sensitization to AMPH and suggest a role for arrestin-3-mediated signaling in the sensitization process. In contrast, male ARR2KO mice showed enhanced early responsiveness to AMPH and the lack of further sensitization, suggesting a role for impaired receptor desensitization. The comparison of mice possessing one allele of arrestin-3 and no arrestin-2 with ARR2KO littermates revealed reduced activity of the former line, consistent with a contribution of arrestin-3-mediated signaling to AMPH responses. Surprisingly, ARR3KO mice with one arrestin-2 allele showed significantly reduced locomotor responses to AMPH combined with lower novelty-induced locomotion, as compared to the ARR3KO line. These data suggest that one allele of arrestin-2 is unable to support normal locomotor behavior due to signaling and/or developmental defects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Event-related cerebral hemodynamics reveal target-specific resource allocation for both "go" and "no-go" response-based vigilance tasks.

PubMed

Shaw, Tyler H; Funke, Matthew E; Dillard, Michael; Funke, Gregory J; Warm, Joel S; Parasuraman, Raja

2013-08-01

Transcranial Doppler sonography was used to measure cerebral blood flow velocity (CBFV) in the right and left cerebral hemispheres during the performance of a 50-min visual vigilance session. Observers monitored a simulated flight of unmanned aerial vehicles for cases in which one of the vehicles was flying in an inappropriate direction relative to its cohorts. Two types of vigilance tasks were employed: a traditional task in which observers made button press ("go") responses to critical signals, and a modification of the traditional task called the Sustained Attention to Response Task (SART) in which "go" responses acknowledged nonsignal events and response withholding ("no-go") signified signal detection. Signal detections and global CBFV scores declined over time. In addition, fine-grained event-related analyses revealed that the detection of signals was accompanied by an elevation of CBFV that was not present with missed signals. As was the case with the global scores, the magnitude of the transient CBFV increments associated with signal detection also declined over time, and these findings were independent of task type. The results support the view of CBFV as an index of the cognitive evaluation of stimulus significance, and a resource model of vigilance in which the need for continuous attention produces a depletion of information-processing assets that are not replenished as the task progresses. Further, temporal declines in the magnitude of event-related CBFV in response to critical signals only is evidence that the decrement function in vigilance is due to attentional processing and not specific task elements such as the required response format. Copyright © 2013. Published by Elsevier Inc.

Laser Welding Process Monitoring Systems: Advanced Signal Analysis for Quality Assurance

NASA Astrophysics Data System (ADS)

D'Angelo, Giuseppe

Laser material processing today is widely used in industry. Especially laser welding became one of the key-technologies, e. g., for the automotive sector. This is due to the improvement and development of new laser sources and the increasing knowledge gained at countless scientific research projects. Nevertheless, it is still not possible to use the full potential of this technology. Therefore, the introduction and application of quality-assuring systems is required. For a long time, the statement "the best sensor is no sensor" was often heard. Today, a change of paradigm can be observed. On the one hand, ISO 9000 and other by law enforced regulations have led to the understanding that quality monitoring is an essential tool in modern manufacturing and necessary in order to keep production results in deterministic boundaries. On the other hand, rising quality requirements not only set higher and higher requirements for the process technology but also demand qualityassurance measures which ensure the reliable recognition of process faults. As a result, there is a need for reliable online detection and correction of welding faults by means of an in-process monitoring. The chapter describes an advanced signals analysis technique to extract information from signals detected, during the laser welding process, by optical sensors. The technique is based on the method of reassignment which was first applied to the spectrogram by Kodera, Gendrin and de Villedary22,23 and later generalized to any bilinear time-frequency representation by Auger and Flandrin.24 Key to the method is a nonlinear convolution where the value of the convolution is not placed at the center of the convolution kernel but rather reassigned to the center of mass of the function within the kernel. The resulting reassigned representation yields significantly improved components localization. We compare the proposed time-frequency distributions by analyzing signals detected during the laser welding of tailored blanks, demonstrating the advantages of the reassigned representation, giving practical applicability to the proposed method.

The Timing and Effort of Lexical Access in Natural and Degraded Speech

PubMed Central

Wagner, Anita E.; Toffanin, Paolo; Başkent, Deniz

2016-01-01

Understanding speech is effortless in ideal situations, and although adverse conditions, such as caused by hearing impairment, often render it an effortful task, they do not necessarily suspend speech comprehension. A prime example of this is speech perception by cochlear implant users, whose hearing prostheses transmit speech as a significantly degraded signal. It is yet unknown how mechanisms of speech processing deal with such degraded signals, and whether they are affected by effortful processing of speech. This paper compares the automatic process of lexical competition between natural and degraded speech, and combines gaze fixations, which capture the course of lexical disambiguation, with pupillometry, which quantifies the mental effort involved in processing speech. Listeners’ ocular responses were recorded during disambiguation of lexical embeddings with matching and mismatching durational cues. Durational cues were selected due to their substantial role in listeners’ quick limitation of the number of lexical candidates for lexical access in natural speech. Results showed that lexical competition increased mental effort in processing natural stimuli in particular in presence of mismatching cues. Signal degradation reduced listeners’ ability to quickly integrate durational cues in lexical selection, and delayed and prolonged lexical competition. The effort of processing degraded speech was increased overall, and because it had its sources at the pre-lexical level this effect can be attributed to listening to degraded speech rather than to lexical disambiguation. In sum, the course of lexical competition was largely comparable for natural and degraded speech, but showed crucial shifts in timing, and different sources of increased mental effort. We argue that well-timed progress of information from sensory to pre-lexical and lexical stages of processing, which is the result of perceptual adaptation during speech development, is the reason why in ideal situations speech is perceived as an undemanding task. Degradation of the signal or the receiver channel can quickly bring this well-adjusted timing out of balance and lead to increase in mental effort. Incomplete and effortful processing at the early pre-lexical stages has its consequences on lexical processing as it adds uncertainty to the forming and revising of lexical hypotheses. PMID:27065901

Towards Intelligent Interpretation of Low Strain Pile Integrity Testing Results Using Machine Learning Techniques

PubMed Central

Cui, De-Mi; Wang, Xiao-Quan; Lu, Lie-Min

2017-01-01

Low strain pile integrity testing (LSPIT), due to its simplicity and low cost, is one of the most popular NDE methods used in pile foundation construction. While performing LSPIT in the field is generally quite simple and quick, determining the integrity of the test piles by analyzing and interpreting the test signals (reflectograms) is still a manual process performed by experienced experts only. For foundation construction sites where the number of piles to be tested is large, it may take days before the expert can complete interpreting all of the piles and delivering the integrity assessment report. Techniques that can automate test signal interpretation, thus shortening the LSPIT’s turnaround time, are of great business value and are in great need. Motivated by this need, in this paper, we develop a computer-aided reflectogram interpretation (CARI) methodology that can interpret a large number of LSPIT signals quickly and consistently. The methodology, built on advanced signal processing and machine learning technologies, can be used to assist the experts in performing both qualitative and quantitative interpretation of LSPIT signals. Specifically, the methodology can ease experts’ interpretation burden by screening all test piles quickly and identifying a small number of suspected piles for experts to perform manual, in-depth interpretation. We demonstrate the methodology’s effectiveness using the LSPIT signals collected from a number of real-world pile construction sites. The proposed methodology can potentially enhance LSPIT and make it even more efficient and effective in quality control of deep foundation construction. PMID:29068431

Differential pulse amplitude modulation for multiple-input single-output OWVLC

NASA Astrophysics Data System (ADS)

Yang, S. H.; Kwon, D. H.; Kim, S. J.; Son, Y. H.; Han, S. K.

2015-01-01

White light-emitting diodes (LEDs) are widely used for lighting due to their energy efficiency, eco-friendly, and small size than previously light sources such as incandescent, fluorescent bulbs and so on. Optical wireless visible light communication (OWVLC) based on LED merges lighting and communications in applications such as indoor lighting, traffic signals, vehicles, and underwater communications because LED can be easily modulated. However, physical bandwidth of LED is limited about several MHz by slow time constant of the phosphor and characteristics of device. Therefore, using the simplest modulation format which is non-return-zero on-off-keying (NRZ-OOK), the data rate reaches only to dozens Mbit/s. Thus, to improve the transmission capacity, optical filtering and pre-, post-equalizer are adapted. Also, high-speed wireless connectivity is implemented using spectrally efficient modulation methods: orthogonal frequency division multiplexing (OFDM) or discrete multi-tone (DMT). However, these modulation methods need additional digital signal processing such as FFT and IFFT, thus complexity of transmitter and receiver is increasing. To reduce the complexity of transmitter and receiver, we proposed a novel modulation scheme which is named differential pulse amplitude modulation. The proposed modulation scheme transmits different NRZ-OOK signals with same amplitude and unit time delay using each LED chip, respectively. The `N' parallel signals from LEDs are overlapped and directly detected at optical receiver. Received signal is demodulated by power difference between unit time slots. The proposed scheme can overcome the bandwidth limitation of LEDs and data rate can be improved according to number of LEDs without complex digital signal processing.

SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals.

PubMed

Xiong, Jiping; Cai, Lisang; Wang, Fei; He, Xiaowei

2017-03-03

Although wrist-type photoplethysmographic (hereafter referred to as WPPG) sensor signals can measure heart rate quite conveniently, the subjects' hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

A contactless approach for respiratory gating in PET using continuous-wave radar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ersepke, Thomas, E-mail: Thomas.Ersepke@rub.de; Büther, Florian; Heß, Mirco

Purpose: Respiratory gating is commonly used to reduce motion artifacts in positron emission tomography (PET). Clinically established methods for respiratory gating in PET require contact to the patient or a direct optical line between the sensor and the patient’s torso and time consuming preparation. In this work, a contactless method for capturing a respiratory signal during PET is presented based on continuous-wave radar. Methods: The proposed method relies on the principle of emitting an electromagnetic wave and detecting the phase shift of the reflected wave, modulated due to the respiratory movement of the patient’s torso. A 24 GHz carrier frequencymore » was chosen allowing wave propagation through plastic and clothing with high reflections at the skin surface. A detector module and signal processing algorithms were developed to extract a quantitative respiratory signal. The sensor was validated using a high precision linear table. During volunteer measurements and [{sup 18}F] FDG PET scans, the radar sensor was positioned inside the scanner bore of a PET/computed tomography scanner. As reference, pressure belt (one volunteer), depth camera-based (two volunteers, two patients), and PET data-driven (six patients) signals were acquired simultaneously and the signal correlation was quantified. Results: The developed system demonstrated a high measurement accuracy for movement detection within the submillimeter range. With the proposed method, small displacements of 25 μm could be detected, not considerably influenced by clothing or blankets. From the patient studies, the extracted respiratory radar signals revealed high correlation (Pearson correlation coefficient) to those derived from the external pressure belt and depth camera signals (r = 0.69–0.99) and moderate correlation to those of the internal data-driven signals (r = 0.53–0.70). In some cases, a cardiac signal could be visualized, due to the representation of the mechanical heart motion on the skin. Conclusions: Accurate respiratory signals were obtained successfully by the proposed method with high spatial and temporal resolution. By working without contact and passing through clothing and blankets, this approach minimizes preparation time and increases the convenience of the patient during the scan.« less

Reduced-Order Modeling and Wavelet Analysis of Turbofan Engine Structural Response Due to Foreign Object Damage (FOD) Events

NASA Technical Reports Server (NTRS)

Turso, James; Lawrence, Charles; Litt, Jonathan

2004-01-01

The development of a wavelet-based feature extraction technique specifically targeting FOD-event induced vibration signal changes in gas turbine engines is described. The technique performs wavelet analysis of accelerometer signals from specified locations on the engine and is shown to be robust in the presence of significant process and sensor noise. It is envisioned that the technique will be combined with Kalman filter thermal/health parameter estimation for FOD-event detection via information fusion from these (and perhaps other) sources. Due to the lack of high-frequency FOD-event test data in the open literature, a reduced-order turbofan structural model (ROM) was synthesized from a finite element model modal analysis to support the investigation. In addition to providing test data for algorithm development, the ROM is used to determine the optimal sensor location for FOD-event detection. In the presence of significant noise, precise location of the FOD event in time was obtained using the developed wavelet-based feature.

Reduced-Order Modeling and Wavelet Analysis of Turbofan Engine Structural Response Due to Foreign Object Damage "FOD" Events

NASA Technical Reports Server (NTRS)

Turso, James A.; Lawrence, Charles; Litt, Jonathan S.

2007-01-01

The development of a wavelet-based feature extraction technique specifically targeting FOD-event induced vibration signal changes in gas turbine engines is described. The technique performs wavelet analysis of accelerometer signals from specified locations on the engine and is shown to be robust in the presence of significant process and sensor noise. It is envisioned that the technique will be combined with Kalman filter thermal/ health parameter estimation for FOD-event detection via information fusion from these (and perhaps other) sources. Due to the lack of high-frequency FOD-event test data in the open literature, a reduced-order turbofan structural model (ROM) was synthesized from a finite-element model modal analysis to support the investigation. In addition to providing test data for algorithm development, the ROM is used to determine the optimal sensor location for FOD-event detection. In the presence of significant noise, precise location of the FOD event in time was obtained using the developed wavelet-based feature.

Mechanisms of Nuclear Export in Cancer and Resistance to Chemotherapy.

PubMed

El-Tanani, Mohamed; Dakir, El-Habib; Raynor, Bethany; Morgan, Richard

2016-03-14

Tumour suppressor proteins, such as p53, BRCA1, and ABC, play key roles in preventing the development of a malignant phenotype, but those that function as transcriptional regulators need to enter the nucleus in order to function. The export of proteins between the nucleus and cytoplasm is complex. It occurs through nuclear pores and exported proteins need a nuclear export signal (NES) to bind to nuclear exportin proteins, including CRM1 (Chromosomal Region Maintenance protein 1), and the energy for this process is provided by the RanGTP/RanGDP gradient. Due to the loss of DNA repair and cell cycle checkpoints, drug resistance is a major problem in cancer treatment, and often an initially successful treatment will fail due to the development of resistance. An important mechanism underlying resistance is nuclear export, and a number of strategies that can prevent nuclear export may reverse resistance. Examples include inhibitors of CRM1, antibodies to the nuclear export signal, and alteration of nuclear pore structure. Each of these are considered in this review.

Spin-dependent electrical conduction in a pentacene Schottky diode explored by electrically detected magnetic resonance

NASA Astrophysics Data System (ADS)

Fukuda, Kunito; Asakawa, Naoki

2017-02-01

Reported is the observation of dark spin-dependent electrical conduction in a Schottky barrier diode with pentacene (PSBD) using electrically detected magnetic resonance at room temperature. It is suggested that spin-dependent conduction exists in pentacene thin films, which is explored by examining the anisotropic linewidth of the EDMR signal and current density-voltage (J-V) measurements. The EDMR spectrum can be decomposed to Gaussian and Lorentzian components. The dependency of the two signals on the applied voltage was consistent with the current density-voltage (J-V) of the PSBD rather than that of the electron-only device of Al/pentacene/Al, indicating that the spin-dependent conduction is due to bipolaron formation associated with hole polaronic hopping processes. The applied-voltage dependence of the ratio of intensity of the Gaussian line to the Lorentzian may infer that increasing current density should make conducting paths more dispersive, thereby resulting in an increased fraction of the Gaussian line due to the higher dispersive g-factor.

Cross-Approximate Entropy parallel computation on GPUs for biomedical signal analysis. Application to MEG recordings.

PubMed

Martínez-Zarzuela, Mario; Gómez, Carlos; Díaz-Pernas, Francisco Javier; Fernández, Alberto; Hornero, Roberto

2013-10-01

Cross-Approximate Entropy (Cross-ApEn) is a useful measure to quantify the statistical dissimilarity of two time series. In spite of the advantage of Cross-ApEn over its one-dimensional counterpart (Approximate Entropy), only a few studies have applied it to biomedical signals, mainly due to its high computational cost. In this paper, we propose a fast GPU-based implementation of the Cross-ApEn that makes feasible its use over a large amount of multidimensional data. The scheme followed is fully scalable, thus maximizes the use of the GPU despite of the number of neural signals being processed. The approach consists in processing many trials or epochs simultaneously, with independence of its origin. In the case of MEG data, these trials can proceed from different input channels or subjects. The proposed implementation achieves an average speedup greater than 250× against a CPU parallel version running on a processor containing six cores. A dataset of 30 subjects containing 148 MEG channels (49 epochs of 1024 samples per channel) can be analyzed using our development in about 30min. The same processing takes 5 days on six cores and 15 days when running on a single core. The speedup is much larger if compared to a basic sequential Matlab(®) implementation, that would need 58 days per subject. To our knowledge, this is the first contribution of Cross-ApEn measure computation using GPUs. This study demonstrates that this hardware is, to the day, the best option for the signal processing of biomedical data with Cross-ApEn. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Research to Operations of Ionospheric Scintillation Detection and Forecasting

NASA Astrophysics Data System (ADS)

Jones, J.; Scro, K.; Payne, D.; Ruhge, R.; Erickson, B.; Andorka, S.; Ludwig, C.; Karmann, J.; Ebelhar, D.

Ionospheric Scintillation refers to random fluctuations in phase and amplitude of electromagnetic waves caused by a rapidly varying refractive index due to turbulent features in the ionosphere. Scintillation of transionospheric UHF and L-Band radio frequency signals is particularly troublesome since this phenomenon can lead to degradation of signal strength and integrity that can negatively impact satellite communications and navigation, radar, or radio signals from other systems that traverse or interact with the ionosphere. Although ionospheric scintillation occurs in both the equatorial and polar regions of the Earth, the focus of this modeling effort is on equatorial scintillation. The ionospheric scintillation model is data-driven in a sense that scintillation observations are used to perform detection and characterization of scintillation structures. These structures are then propagated to future times using drift and decay models to represent the natural evolution of ionospheric scintillation. The impact on radio signals is also determined by the model and represented in graphical format to the user. A frequency scaling algorithm allows for impact analysis on frequencies other than the observation frequencies. The project began with lab-grade software and through a tailored Agile development process, deployed operational-grade code to a DoD operational center. The Agile development process promotes adaptive promote adaptive planning, evolutionary development, early delivery, continuous improvement, regular collaboration with the customer, and encourage rapid and flexible response to customer-driven changes. The Agile philosophy values individuals and interactions over processes and tools, working software over comprehensive documentation, customer collaboration over contract negotiation, and responding to change over following a rigid plan. The end result was an operational capability that met customer expectations. Details of the model and the process of operational integration are discussed as well as lessons learned to improve performance on future projects.

Electromagnetic spectrum management system

DOEpatents

Seastrand, Douglas R.

2017-01-31

A system for transmitting a wireless countermeasure signal to disrupt third party communications is disclosed that include an antenna configured to receive wireless signals and transmit wireless counter measure signals such that the wireless countermeasure signals are responsive to the received wireless signals. A receiver processes the received wireless signals to create processed received signal data while a spectrum control module subtracts known source signal data from the processed received signal data to generate unknown source signal data. The unknown source signal data is based on unknown wireless signals, such as enemy signals. A transmitter is configured to process the unknown source signal data to create countermeasure signals and transmit a wireless countermeasure signal over the first antenna or a second antenna to thereby interfere with the unknown wireless signals.

Studies of Minerals, Organic and Biogenic Materials through Time-Resolved Raman Spectroscopy

NASA Technical Reports Server (NTRS)

Garcia, Christopher S.; Abedin, M. Nurul; Ismail, Syed; Sharma, Shiv K.; Misra, Anupam K.; Nyugen, Trac; Elsayed-Ali, hani

2009-01-01

A compact remote Raman spectroscopy system was developed at NASA Langley Research center and was previously demonstrated for its ability to identify chemical composition of various rocks and minerals. In this study, the Raman sensor was utilized to perform time-resolved Raman studies of various samples such as minerals and rocks, Azalea leaves and a few fossil samples. The Raman sensor utilizes a pulsed 532 nm Nd:YAG laser as excitation source, a 4-inch telescope to collect the Raman-scattered signal from a sample several meters away, a spectrograph equipped with a holographic grating, and a gated intensified CCD (ICCD) camera system. Time resolved Raman measurements were carried out by varying the gate delay with fixed short gate width of the ICCD camera, allowing measurement of both Raman signals and fluorescence signals. Rocks and mineral samples were characterized including marble, which contain CaCO3. Analysis of the results reveals the short (approx.10-13 s) lifetime of the Raman process, and shows that Raman spectra of some mineral samples contain fluorescence emission due to organic impurities. Also analyzed were a green (pristine) and a yellow (decayed) sample of Gardenia leaves. It was observed that the fluorescence signals from the green and yellow leaf samples showed stronger signals compared to the Raman lines. Moreover, it was also observed that the fluorescence of the green leaf was more intense and had a shorter lifetime than that of the yellow leaf. For the fossil samples, Raman shifted lines could not be observed due the presence of very strong short-lived fluorescence.

Modeling Nonlinear Errors in Surface Electromyography Due To Baseline Noise: A New Methodology

PubMed Central

Law, Laura Frey; Krishnan, Chandramouli; Avin, Keith

2010-01-01

The surface electromyographic (EMG) signal is often contaminated by some degree of baseline noise. It is customary for scientists to subtract baseline noise from the measured EMG signal prior to further analyses based on the assumption that baseline noise adds linearly to the observed EMG signal. The stochastic nature of both the baseline and EMG signal, however, may invalidate this assumption. Alternately, “true” EMG signals may be either minimally or nonlinearly affected by baseline noise. This information is particularly relevant at low contraction intensities when signal-to-noise ratios (SNR) may be lowest. Thus, the purpose of this simulation study was to investigate the influence of varying levels of baseline noise (approximately 2 – 40 % maximum EMG amplitude) on mean EMG burst amplitude and to assess the best means to account for signal noise. The simulations indicated baseline noise had minimal effects on mean EMG activity for maximum contractions, but increased nonlinearly with increasing noise levels and decreasing signal amplitudes. Thus, the simple baseline noise subtraction resulted in substantial error when estimating mean activity during low intensity EMG bursts. Conversely, correcting EMG signal as a nonlinear function of both baseline and measured signal amplitude provided highly accurate estimates of EMG amplitude. This novel nonlinear error modeling approach has potential implications for EMG signal processing, particularly when assessing co-activation of antagonist muscles or small amplitude contractions where the SNR can be low. PMID:20869716

Detection of changes in SEMG signals with myofascial pain using the pattern-classifier

NASA Astrophysics Data System (ADS)

Jiang, Ching-Fen; Huang, Pao-Tieh

2013-10-01

Myofascial pain on the upper back (MFPUB) has been a common occupational hazard associated with consistent computer use. Investigations into any sort neuromuscular functional changes due to myofascial pain are rare. This study aims to differentiate the wavelet energy patterns of the surface electromyography signals measured from 30 normal and 26 patient subjects using the K-means clustering process. The results show that the wavelet energy pattern of patient subjects was different to that of normal subject and reveals a sensitivity of 57.69% at a specificity of 76.67% in the identification of myofascial pain. Therefore, this model could provide a reliable feature for clinical diagnosis of myofascial pain.

Potential Antitumor Effects of Pomegranates and Its Ingredients.

PubMed

Rahmani, Arshad H; Alsahli, Mohammed A; Almatroodi, Saleh A

2017-01-01

The treatment based on plant or plant derivatives is a promising strategy in the killing of cancers cells. Moreover, wide-ranging finding has established that medicinal plant and its ingredient modulate several cells signaling pathways or inhibiting the carcinogenesis process. In this vista, pomegranates fruits, seeds and peels illustrate cancer preventive role seems to be due to rich source of antioxidant and other valuable ingredients. Furthermore, anti-tumour activities of pomegranates have been evidences through the modulation of cell signaling pathways including transcription factor, apoptosis and angiogenesis. In this review article, anti-tumor activity of pomegranates and its components or its different type of extracts are described to understand the mechanism of action of pomegranates in cancer therapy.

Cardiac arrhythmia beat classification using DOST and PSO tuned SVM.

PubMed

Raj, Sandeep; Ray, Kailash Chandra; Shankar, Om

2016-11-01

The increase in the number of deaths due to cardiovascular diseases (CVDs) has gained significant attention from the study of electrocardiogram (ECG) signals. These ECG signals are studied by the experienced cardiologist for accurate and proper diagnosis, but it becomes difficult and time-consuming for long-term recordings. Various signal processing techniques are studied to analyze the ECG signal, but they bear limitations due to the non-stationary behavior of ECG signals. Hence, this study aims to improve the classification accuracy rate and provide an automated diagnostic solution for the detection of cardiac arrhythmias. The proposed methodology consists of four stages, i.e. filtering, R-peak detection, feature extraction and classification stages. In this study, Wavelet based approach is used to filter the raw ECG signal, whereas Pan-Tompkins algorithm is used for detecting the R-peak inside the ECG signal. In the feature extraction stage, discrete orthogonal Stockwell transform (DOST) approach is presented for an efficient time-frequency representation (i.e. morphological descriptors) of a time domain signal and retains the absolute phase information to distinguish the various non-stationary behavior ECG signals. Moreover, these morphological descriptors are further reduced in lower dimensional space by using principal component analysis and combined with the dynamic features (i.e based on RR-interval of the ECG signals) of the input signal. This combination of two different kinds of descriptors represents each feature set of an input signal that is utilized for classification into subsequent categories by employing PSO tuned support vector machines (SVM). The proposed methodology is validated on the baseline MIT-BIH arrhythmia database and evaluated under two assessment schemes, yielding an improved overall accuracy of 99.18% for sixteen classes in the category-based and 89.10% for five classes (mapped according to AAMI standard) in the patient-based assessment scheme respectively to the state-of-art diagnosis. The results reported are further compared to the existing methodologies in literature. The proposed feature representation of cardiac signals based on symmetrical features along with PSO based optimization technique for the SVM classifier reported an improved classification accuracy in both the assessment schemes evaluated on the benchmark MIT-BIH arrhythmia database and hence can be utilized for automated computer-aided diagnosis of cardiac arrhythmia beats. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Auditory Models for Speech Analysis

DTIC Science & Technology

1988-01-01

to encode stimulus frequency by firing in period with the clicks, up to a critical value. (Godfrey ct al., 1975). Some binaural processing appears to...masking experiments avoid sinosoiVs since a sinusoidal signal combined with a sinusoidal masker can cause " beats " due to regular fluctuations in the...such as sound localisation (Lyon, 1983). Jeffress (1956) proposed a binaural localisation model where the "mechanism receives impulses from corresponding

Future electro-optical sensors and processing in urban operations

NASA Astrophysics Data System (ADS)

Grönwall, Christina; Schwering, Piet B.; Rantakokko, Jouni; Benoist, Koen W.; Kemp, Rob A. W.; Steinvall, Ove; Letalick, Dietmar; Björkert, Stefan

2013-10-01

In the electro-optical sensors and processing in urban operations (ESUO) study we pave the way for the European Defence Agency (EDA) group of Electro-Optics experts (IAP03) for a common understanding of the optimal distribution of processing functions between the different platforms. Combinations of local, distributed and centralized processing are proposed. In this way one can match processing functionality to the required power, and available communication systems data rates, to obtain the desired reaction times. In the study, three priority scenarios were defined. For these scenarios, present-day and future sensors and signal processing technologies were studied. The priority scenarios were camp protection, patrol and house search. A method for analyzing information quality in single and multi-sensor systems has been applied. A method for estimating reaction times for transmission of data through the chain of command has been proposed and used. These methods are documented and can be used to modify scenarios, or be applied to other scenarios. Present day data processing is organized mainly locally. Very limited exchange of information with other platforms is present; this is performed mainly at a high information level. Main issues that arose from the analysis of present-day systems and methodology are the slow reaction time due to the limited field of view of present-day sensors and the lack of robust automated processing. Efficient handover schemes between wide and narrow field of view sensors may however reduce the delay times. The main effort in the study was in forecasting the signal processing of EO-sensors in the next ten to twenty years. Distributed processing is proposed between hand-held and vehicle based sensors. This can be accompanied by cloud processing on board several vehicles. Additionally, to perform sensor fusion on sensor data originating from different platforms, and making full use of UAV imagery, a combination of distributed and centralized processing is essential. There is a central role for sensor fusion of heterogeneous sensors in future processing. The changes that occur in the urban operations of the future due to the application of these new technologies will be the improved quality of information, with shorter reaction time, and with lower operator load.

Optical signal processing for enabling high-speed, highly spectrally efficient and high capacity optical systems

NASA Astrophysics Data System (ADS)

Fazal, Muhammad Irfan

The unabated demand for more capacity due to the ever-increasing internet traffic dictates that the boundaries of the state of the art maybe pushed to send more data through the network. Traditionally, this need has been satisfied by multiple wavelengths (wavelength division multiplexing), higher order modulation formats and coherent communication (either individually or combined together). WDM has the ability to reduce cost by using multiple channels within the same physical fiber, and with EDFA amplifiers, the need for O-E-O regenerators is eliminated. Moreover the availability of multiple colors allows for wavelength-based routing and network planning. Higher order modulation formats increases the capacity of the link by their ability to encode data in both the phase and amplitude of light, thereby increasing the bits/sec/Hz as compared to simple on-off keyed format. Coherent communications has also emerged as a primary means of transmitting and receiving optical data due to its support of formats that utilize both phase and amplitude to further increase the spectral efficiency of the optical channel, including quadrature amplitude modulation (QAM) and quadrature phase shift keying (QPSK). Polarization multiplexing of channels can double capacity by allowing two channels to share the same wavelength by propagating on orthogonal polarization axis and is easily supported in coherent systems where the polarization tracking can be performed in the digital domain. Furthermore, the forthcoming IEEE 100 Gbit/s Ethernet Standard, 802.3ba, provides greater bandwidth, higher data rates, and supports a mixture of modulation formats. In particular, Pol-MUX QPSK is increasingly becoming the industry's format of choice as the high spectral efficiency allows for 100 Gbit/s transmission while still occupying the current 50 GHz/channel allocation of current 10 Gbit/s OOK fiber systems. In this manner, 100 Gbit/s transfer speeds using current fiber links, amplifiers, and filters may be possible. Recently, interest has increased in exploring the spatial dimension of light to increase capacity, both in fiber as well as free-space communication channels. The orbital angular momentum (OAM) of light, carried by Laguerre-Gaussian (LG) beams have the interesting property that, in theory, an infinite number of OAMs can be transmitted; which due to its inherent orthogonality will not affect each other. Thus, in theory, one can increase the channel capacity arbitrarily. However, in practice, the device dimensions will reduce the number of OAMs used. In addition to advanced modulation formats, it is expected that optical signal processing may play a role in the future development of more efficient optical transmission systems. The hope is that performing signal processing in the optical domain may reduce optical-to-electronic conversion inefficiencies, eliminate bottlenecks and take advantage of the ultrahigh bandwidth inherent in optics. While 40 to 50 Gbit/s electronic components are the peak of commercial technology and 100 Gbit/s capable RF components are still in their infancy, optical signal processing of these high-speed data signals may provide a potential solution. Furthermore, any optical processing system or sub-system must be capable of handling the wide array of data formats and data rates that networks may employ. The work presented in this Ph.D. dissertation attempts at addressing the issue of optical processing for advanced optical modulation formats, and particularly explores the state of the art in increasing the capacity of an optical link by a combination of wavelength/phase/polarization/OAM dimensions of light. Spatial multiplexing and demultiplexing of both coherently and directly detected signals at the 100 Gbit/s Ethernet standard is addressed. The application of a continuously tunable all-optical delay for all-optical functionality like time-slot interchange at high data-rates is presented. Moreover the interplay of chirp generated by differently cross-phase modulation wavelength-convertors based on SOA-MZI with the residual dispersion of a fiber link is studied and the optimal operating conditions are explored

A magnetoencephalography study of multi-modal processing of pain anticipation in primary sensory cortices.

PubMed

Gopalakrishnan, R; Burgess, R C; Plow, E B; Floden, D P; Machado, A G

2015-09-24

Pain anticipation plays a critical role in pain chronification and results in disability due to pain avoidance. It is important to understand how different sensory modalities (auditory, visual or tactile) may influence pain anticipation as different strategies could be applied to mitigate anticipatory phenomena and chronification. In this study, using a countdown paradigm, we evaluated with magnetoencephalography the neural networks associated with pain anticipation elicited by different sensory modalities in normal volunteers. When encountered with well-established cues that signaled pain, visual and somatosensory cortices engaged the pain neuromatrix areas early during the countdown process, whereas the auditory cortex displayed delayed processing. In addition, during pain anticipation, the visual cortex displayed independent processing capabilities after learning the contextual meaning of cues from associative and limbic areas. Interestingly, cross-modal activation was also evident and strong when visual and tactile cues signaled upcoming pain. Dorsolateral prefrontal cortex and mid-cingulate cortex showed significant activity during pain anticipation regardless of modality. Our results show pain anticipation is processed with great time efficiency by a highly specialized and hierarchical network. The highest degree of higher-order processing is modulated by context (pain) rather than content (modality) and rests within the associative limbic regions, corroborating their intrinsic role in chronification. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Process and system - A dual definition, revisited with consequences in metrology

NASA Astrophysics Data System (ADS)

Ruhm, K. H.

2010-07-01

Lets assert that metrology life could be easier scientifically as well as technologically, if we, intentionally, would make an explicit distinction between two outstanding domains, namely the given, really existent domain of processes and the just virtually existent domain of systems, the latter of which is designed and used by the human mind. The abstract domain of models, by which we map the manifold reality of processes, is itself part of the domain of systems. Models support comprehension and communication, although they are normally extreme simplifications of properties and behaviour of a concrete reality. So, systems and signals represent processes and quantities, which are described by means of Signal and System Theory as well as by Stochastics and Statistics. The following presentation of this new, demanding and somehow irritating definition of the terms process and system as a dual pair is unusual indeed, but it opens the door widely to a better and more consistent discussion and understanding of manifold scientific tools in many areas. Metrology [4] is one of the important fields of concern due to many reasons: One group of the soft and hard links between the domain of processes and the domain of systems is realised by concepts of measurement science on the one hand and by instrumental tools of measurement technology on the other hand.

A Robust Dynamic Heart-Rate Detection Algorithm Framework During Intense Physical Activities Using Photoplethysmographic Signals

PubMed Central

Song, Jiajia; Li, Dan; Ma, Xiaoyuan; Teng, Guowei; Wei, Jianming

2017-01-01

Dynamic accurate heart-rate (HR) estimation using a photoplethysmogram (PPG) during intense physical activities is always challenging due to corruption by motion artifacts (MAs). It is difficult to reconstruct a clean signal and extract HR from contaminated PPG. This paper proposes a robust HR-estimation algorithm framework that uses one-channel PPG and tri-axis acceleration data to reconstruct the PPG and calculate the HR based on features of the PPG and spectral analysis. Firstly, the signal is judged by the presence of MAs. Then, the spectral peaks corresponding to acceleration data are filtered from the periodogram of the PPG when MAs exist. Different signal-processing methods are applied based on the amount of remaining PPG spectral peaks. The main MA-removal algorithm (NFEEMD) includes the repeated single-notch filter and ensemble empirical mode decomposition. Finally, HR calibration is designed to ensure the accuracy of HR tracking. The NFEEMD algorithm was performed on the 23 datasets from the 2015 IEEE Signal Processing Cup Database. The average estimation errors were 1.12 BPM (12 training datasets), 2.63 BPM (10 testing datasets) and 1.87 BPM (all 23 datasets), respectively. The Pearson correlation was 0.992. The experiment results illustrate that the proposed algorithm is not only suitable for HR estimation during continuous activities, like slow running (13 training datasets), but also for intense physical activities with acceleration, like arm exercise (10 testing datasets). PMID:29068403

Dynamical states, possibilities and propagation of stress signal

PubMed Central

Malik, Md. Zubbair; Ali, Shahnawaz; Singh, Soibam Shyamchand; Ishrat, Romana; Singh, R. K. Brojen

2017-01-01

The stress driven dynamics of Notch-Wnt-p53 cross-talk is subjected to a few possible dynamical states governed by simple fractal rules, and allowed to decide its own fate by choosing one of these states which are contributed from long range correlation with varied fluctuations due to active molecular interaction. The topological properties of the networks corresponding to these dynamical states have hierarchical features with assortive structure. The stress signal driven by nutlin and modulated by mediator GSK3 acts as anti-apoptotic signal in this system, whereas, the stress signal driven by Axin and modulated by GSK3 behaves as anti-apoptotic for a certain range of Axin and GSK3 interaction, and beyond which the signal acts as favor-apoptotic signal. However, this stress system prefers to stay in an active dynamical state whose counterpart complex network is closest to hierarchical topology with exhibited roles of few interacting hubs. During the propagation of stress signal, the system allows the propagator pathway to inherit all possible properties of the state to the receiver pathway/pathways with slight modifications, indicating efficient information processing and democratic sharing of responsibilities in the system via cross-talk. The increase in the number of cross-talk pathways in the system favors to establish self-organization. PMID:28106087

The Juvenile Hafnium Isotope Signal as a Record of Supercontinent Cycles

PubMed Central

Gardiner, Nicholas J.; Kirkland, Christopher L.; Van Kranendonk, Martin J.

2016-01-01

Hf isotope ratios measured in igneous zircon are controlled by magmatic source, which may be linked to tectonic setting. Over the 200–500 Myr periodicity of the supercontinent cycle - the principal geological phenomenon controlling prevailing global tectonic style - juvenile Hf signals, i.e. most radiogenic, are typically measured in zircon from granites formed in arc settings (crustal growth), and evolved zircon Hf signals in granites formed in continent-collision settings (crustal reworking). Interrogations of Hf datasets for excursions related to Earth events commonly use the median value, however this may be equivocal due to magma mixing. The most juvenile part of the Hf signal is less influenced by crustal in-mixing, and arguably a more sensitive archive of Earth’s geodynamic state. We analyze the global Hf dataset for this juvenile signal, statistically correlating supercontinent amalgamation intervals with evolved Hf episodes, and breakup leading to re-assembly with juvenile Hf episodes. The juvenile Hf signal is more sensitive to Pangaea and Rodinia assembly, its amplitude increasing with successive cycles to a maximum with Gondwana assembly which may reflect enhanced subduction-erosion. We demonstrate that the juvenile Hf signal carries important information on prevailing global magmatic style, and thus tectonic processes. PMID:27924946

Kramers-Kronig receiver operable without digital upsampling.

PubMed

Bo, Tianwai; Kim, Hoon

2018-05-28

The Kramers-Kronig (KK) receiver is capable of retrieving the phase information of optical single-sideband (SSB) signal from the optical intensity when the optical signal satisfies the minimum phase condition. Thus, it is possible to direct-detect the optical SSB signal without suffering from the signal-signal beat interference and linear transmission impairments. However, due to the spectral broadening induced by nonlinear operations in the conventional KK algorithm, it is necessary to employ the digital upsampling at the beginning of the digital signal processing (DSP). The increased number of samples at the DSP would hinder the real-time implementation of this attractive receiver. Hence, we propose a new DSP algorithm for KK receiver operable at 2 samples per symbol. We adopt a couple of mathematical approximations to avoid the use of nonlinear operations such as logarithm and exponential functions. By using the proposed algorithm, we demonstrate the transmission of 112-Gb/s SSB orthogonal frequency-division-multiplexed signal over an 80-km fiber link. The results show that the proposed algorithm operating at 2 samples per symbol exhibits similar performance to the conventional KK one operating at 6 samples per symbol. We also present the error analysis of the proposed algorithm for KK receiver in comparison with the conventional one.

Dynamical states, possibilities and propagation of stress signal.

PubMed

Malik, Md Zubbair; Ali, Shahnawaz; Singh, Soibam Shyamchand; Ishrat, Romana; Singh, R K Brojen

2017-01-20

The stress driven dynamics of Notch-Wnt-p53 cross-talk is subjected to a few possible dynamical states governed by simple fractal rules, and allowed to decide its own fate by choosing one of these states which are contributed from long range correlation with varied fluctuations due to active molecular interaction. The topological properties of the networks corresponding to these dynamical states have hierarchical features with assortive structure. The stress signal driven by nutlin and modulated by mediator GSK3 acts as anti-apoptotic signal in this system, whereas, the stress signal driven by Axin and modulated by GSK3 behaves as anti-apoptotic for a certain range of Axin and GSK3 interaction, and beyond which the signal acts as favor-apoptotic signal. However, this stress system prefers to stay in an active dynamical state whose counterpart complex network is closest to hierarchical topology with exhibited roles of few interacting hubs. During the propagation of stress signal, the system allows the propagator pathway to inherit all possible properties of the state to the receiver pathway/pathways with slight modifications, indicating efficient information processing and democratic sharing of responsibilities in the system via cross-talk. The increase in the number of cross-talk pathways in the system favors to establish self-organization.

Multi-purpose ECG telemetry system.

PubMed

Marouf, Mohamed; Vukomanovic, Goran; Saranovac, Lazar; Bozic, Miroslav

2017-06-19

The Electrocardiogram ECG is one of the most important non-invasive tools for cardiac diseases diagnosis. Taking advantage of the developed telecommunication infrastructure, several approaches that address the development of telemetry cardiac devices were introduced recently. Telemetry ECG devices allow easy and fast ECG monitoring of patients with suspected cardiac issues. Choosing the right device with the desired working mode, signal quality, and the device cost are still the main obstacles to massive usage of these devices. In this paper, we introduce design, implementation, and validation of a multi-purpose telemetry system for recording, transmission, and interpretation of ECG signals in different recording modes. The system consists of an ECG device, a cloud-based analysis pipeline, and accompanied mobile applications for physicians and patients. The proposed ECG device's mechanical design allows laypersons to easily record post-event short-term ECG signals, using dry electrodes without any preparation. Moreover, patients can use the device to record long-term signals in loop and holter modes, using wet electrodes. In order to overcome the problem of signal quality fluctuation due to using different electrodes types and different placements on subject's chest, customized ECG signal processing and interpretation pipeline is presented for each working mode. We present the evaluation of the novel short-term recorder design. Recording of an ECG signal was performed for 391 patients using a standard 12-leads golden standard ECG and the proposed patient-activated short-term post-event recorder. In the validation phase, a sample of validation signals followed peer review process wherein two experts annotated the signals in terms of signal acceptability for diagnosis.We found that 96% of signals allow detecting arrhythmia and other signal's abnormal changes. Additionally, we compared and presented the correlation coefficient and the automatic QRS delineation results of both short-term post-event recorder and 12-leads golden standard ECG recorder. The proposed multi-purpose ECG device allows physicians to choose the working mode of the same device according to the patient status. The proposed device was designed to allow patients to manage the technical requirements of both working modes. Post-event short-term ECG recording using the proposed design provide physicians reliable three ECG leads with direct symptom-rhythm correlation.

Electromagnetic spectrum management system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seastrand, Douglas R.

A system for transmitting a wireless countermeasure signal to disrupt third party communications is disclosed that include an antenna configured to receive wireless signals and transmit wireless counter measure signals such that the wireless countermeasure signals are responsive to the received wireless signals. A receiver processes the received wireless signals to create processed received signal data while a spectrum control module subtracts known source signal data from the processed received signal data to generate unknown source signal data. The unknown source signal data is based on unknown wireless signals, such as enemy signals. A transmitter is configured to process themore » unknown source signal data to create countermeasure signals and transmit a wireless countermeasure signal over the first antenna or a second antenna to thereby interfere with the unknown wireless signals.« less

Using Seismic Signals to Forecast Volcanic Processes

NASA Astrophysics Data System (ADS)

Salvage, R.; Neuberg, J. W.

2012-04-01

Understanding seismic signals generated during volcanic unrest have the ability to allow scientists to more accurately predict and understand active volcanoes since they are intrinsically linked to rock failure at depth (Voight, 1988). In particular, low frequency long period signals (LP events) have been related to the movement of fluid and the brittle failure of magma at depth due to high strain rates (Hammer and Neuberg, 2009). This fundamentally relates to surface processes. However, there is currently no physical quantitative model for determining the likelihood of an eruption following precursory seismic signals, or the timing or type of eruption that will ensue (Benson et al., 2010). Since the beginning of its current eruptive phase, accelerating LP swarms (< 10 events per hour) have been a common feature at Soufriere Hills volcano, Montserrat prior to surface expressions such as dome collapse or eruptions (Miller et al., 1998). The dynamical behaviour of such swarms can be related to accelerated magma ascent rates since the seismicity is thought to be a consequence of magma deformation as it rises to the surface. In particular, acceleration rates can be successfully used in collaboration with the inverse material failure law; a linear relationship against time (Voight, 1988); in the accurate prediction of volcanic eruption timings. Currently, this has only been investigated for retrospective events (Hammer and Neuberg, 2009). The identification of LP swarms on Montserrat and analysis of their dynamical characteristics allows a better understanding of the nature of the seismic signals themselves, as well as their relationship to surface processes such as magma extrusion rates. Acceleration and deceleration rates of seismic swarms provide insights into the plumbing system of the volcano at depth. The application of the material failure law to multiple LP swarms of data allows a critical evaluation of the accuracy of the method which further refines current understanding of the relationship between seismic signals and volcanic eruptions. It is hoped that such analysis will assist the development of real time forecasting models.

The Auditory-Brainstem Response to Continuous, Non-repetitive Speech Is Modulated by the Speech Envelope and Reflects Speech Processing

PubMed Central

Reichenbach, Chagit S.; Braiman, Chananel; Schiff, Nicholas D.; Hudspeth, A. J.; Reichenbach, Tobias

2016-01-01

The auditory-brainstem response (ABR) to short and simple acoustical signals is an important clinical tool used to diagnose the integrity of the brainstem. The ABR is also employed to investigate the auditory brainstem in a multitude of tasks related to hearing, such as processing speech or selectively focusing on one speaker in a noisy environment. Such research measures the response of the brainstem to short speech signals such as vowels or words. Because the voltage signal of the ABR has a tiny amplitude, several hundred to a thousand repetitions of the acoustic signal are needed to obtain a reliable response. The large number of repetitions poses a challenge to assessing cognitive functions due to neural adaptation. Here we show that continuous, non-repetitive speech, lasting several minutes, may be employed to measure the ABR. Because the speech is not repeated during the experiment, the precise temporal form of the ABR cannot be determined. We show, however, that important structural features of the ABR can nevertheless be inferred. In particular, the brainstem responds at the fundamental frequency of the speech signal, and this response is modulated by the envelope of the voiced parts of speech. We accordingly introduce a novel measure that assesses the ABR as modulated by the speech envelope, at the fundamental frequency of speech and at the characteristic latency of the response. This measure has a high signal-to-noise ratio and can hence be employed effectively to measure the ABR to continuous speech. We use this novel measure to show that the ABR is weaker to intelligible speech than to unintelligible, time-reversed speech. The methods presented here can be employed for further research on speech processing in the auditory brainstem and can lead to the development of future clinical diagnosis of brainstem function. PMID:27303286

Signal existence verification (SEV) for GPS low received power signal detection using the time-frequency approach.

PubMed

Jan, Shau-Shiun; Sun, Chih-Cheng

2010-01-01

The detection of low received power of global positioning system (GPS) signals in the signal acquisition process is an important issue for GPS applications. Improving the miss-detection problem of low received power signal is crucial, especially for urban or indoor environments. This paper proposes a signal existence verification (SEV) process to detect and subsequently verify low received power GPS signals. The SEV process is based on the time-frequency representation of GPS signal, and it can capture the characteristic of GPS signal in the time-frequency plane to enhance the GPS signal acquisition performance. Several simulations and experiments are conducted to show the effectiveness of the proposed method for low received power signal detection. The contribution of this work is that the SEV process is an additional scheme to assist the GPS signal acquisition process in low received power signal detection, without changing the original signal acquisition or tracking algorithms.

Biological nitric oxide signalling: chemistry and terminology

PubMed Central

Heinrich, Tassiele A; da Silva, Roberto S; Miranda, Katrina M; Switzer, Christopher H; Wink, David A; Fukuto, Jon M

2013-01-01

Biological nitrogen oxide signalling and stress is an area of extreme clinical, pharmacological, toxicological, biochemical and chemical research interest. The utility of nitric oxide and derived species as signalling agents is due to their novel and vast chemical interactions with a variety of biological targets. Herein, the chemistry associated with the interaction of the biologically relevant nitrogen oxide species with fundamental biochemical targets is discussed. Specifically, the chemical interactions of nitrogen oxides with nucleophiles (e.g. thiols), metals (e.g. hemeproteins) and paramagnetic species (e.g. dioxygen and superoxide) are addressed. Importantly, the terms associated with the mechanisms by which NO (and derived species) react with their respective biological targets have been defined by numerous past chemical studies. Thus, in order to assist researchers in referring to chemical processes associated with nitrogen oxide biology, the vernacular associated with these chemical interactions is addressed. PMID:23617570

Tunable protease-activatable virus nanonodes.

PubMed

Judd, Justin; Ho, Michelle L; Tiwari, Abhinav; Gomez, Eric J; Dempsey, Christopher; Van Vliet, Kim; Igoshin, Oleg A; Silberg, Jonathan J; Agbandje-McKenna, Mavis; Suh, Junghae

2014-05-27

We explored the unique signal integration properties of the self-assembling 60-mer protein capsid of adeno-associated virus (AAV), a clinically proven human gene therapy vector, by engineering proteolytic regulation of virus-receptor interactions such that processing of the capsid by proteases is required for infection. We find the transfer function of our engineered protease-activatable viruses (PAVs), relating the degree of proteolysis (input) to PAV activity (output), is highly nonlinear, likely due to increased polyvalency. By exploiting this dynamic polyvalency, in combination with the self-assembly properties of the virus capsid, we show that mosaic PAVs can be constructed that operate under a digital AND gate regime, where two different protease inputs are required for virus activation. These results show viruses can be engineered as signal-integrating nanoscale nodes whose functional properties are regulated by multiple proteolytic signals with easily tunable and predictable response surfaces, a promising development toward advanced control of gene delivery.

Tunable Protease-Activatable Virus Nanonodes

PubMed Central

2015-01-01

We explored the unique signal integration properties of the self-assembling 60-mer protein capsid of adeno-associated virus (AAV), a clinically proven human gene therapy vector, by engineering proteolytic regulation of virus–receptor interactions such that processing of the capsid by proteases is required for infection. We find the transfer function of our engineered protease-activatable viruses (PAVs), relating the degree of proteolysis (input) to PAV activity (output), is highly nonlinear, likely due to increased polyvalency. By exploiting this dynamic polyvalency, in combination with the self-assembly properties of the virus capsid, we show that mosaic PAVs can be constructed that operate under a digital AND gate regime, where two different protease inputs are required for virus activation. These results show viruses can be engineered as signal-integrating nanoscale nodes whose functional properties are regulated by multiple proteolytic signals with easily tunable and predictable response surfaces, a promising development toward advanced control of gene delivery. PMID:24796495

Neurons for hunger and thirst transmit a negative-valence teaching signal.

PubMed

Betley, J Nicholas; Xu, Shengjin; Cao, Zhen Fang Huang; Gong, Rong; Magnus, Christopher J; Yu, Yang; Sternson, Scott M

2015-05-14

Homeostasis is a biological principle for regulation of essential physiological parameters within a set range. Behavioural responses due to deviation from homeostasis are critical for survival, but motivational processes engaged by physiological need states are incompletely understood. We examined motivational characteristics of two separate neuron populations that regulate energy and fluid homeostasis by using cell-type-specific activity manipulations in mice. We found that starvation-sensitive AGRP neurons exhibit properties consistent with a negative-valence teaching signal. Mice avoided activation of AGRP neurons, indicating that AGRP neuron activity has negative valence. AGRP neuron inhibition conditioned preference for flavours and places. Correspondingly, deep-brain calcium imaging revealed that AGRP neuron activity rapidly reduced in response to food-related cues. Complementary experiments activating thirst-promoting neurons also conditioned avoidance. Therefore, these need-sensing neurons condition preference for environmental cues associated with nutrient or water ingestion, which is learned through reduction of negative-valence signals during restoration of homeostasis.

Polynomial-interpolation algorithm for van der Pauw Hall measurement in a metal hydride film

NASA Astrophysics Data System (ADS)

Koon, D. W.; Ares, J. R.; Leardini, F.; Fernández, J. F.; Ferrer, I. J.

2008-10-01

We apply a four-term polynomial-interpolation extension of the van der Pauw Hall measurement technique to a 330 nm Mg-Pd bilayer during both absorption and desorption of hydrogen at room temperature. We show that standard versions of the van der Pauw DC Hall measurement technique produce an error of over 100% due to a drifting offset signal and can lead to unphysical interpretations of the physical processes occurring in this film. The four-term technique effectively removes this source of error, even when the offset signal is drifting by an amount larger than the Hall signal in the time interval between successive measurements. This technique can be used to increase the resolution of transport studies of any material in which the resistivity is rapidly changing, particularly when the material is changing from metallic to insulating behavior.

Electromagnetic radiations from laser interaction with gas-filled Hohlraum

NASA Astrophysics Data System (ADS)

Yang, Ming; Yang, Yongmei; Li, Tingshuai; Yi, Tao; Wang, Chuanke; Liu, Shenye; Jiang, Shaoen; Ding, Yongkun

2018-01-01

The emission of intensive electromagnetic pulse (EMP) due to laser-target interactions at the ShenGuang-III laser facility has been evaluated by probes. EMP signals measured using the small discone antennas demonstrated two variation trends including a bilateral oscillation wave and a unilateral oscillation wave. The new trend of unilateral oscillation could be attributed to the hohlraum structure and low-Z gas in the hohlraum. The EMP waveform showed multiple peaks when the gas-filled hohlraum was shot by the high-power laser. Comparing the EMP signals with the verification of stimulated Raman scattering energy and hard x-ray energy spectrum, we found that the intensity of EMP signals decreased with the increase of the hohlraum size. The current results are expected to offer preliminary information to study physical processes on laser injecting gas-filled hohlraums in the National Ignition Facility implementation.

Simulation and analysis on ultrasonic testing for the cement grouting defects of the corrugated pipe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qingbang, Han; Ling, Chen; Changping, Zhu

2014-02-18

The defects exist in the cement grouting process of prestressed corrugated pipe may directly impair the bridge safety. In this paper, sound fields propagation in concrete structures with corrugated pipes and the influence of various different defects are simulated and analyzed using finite element method. The simulation results demonstrate a much complex propagation characteristic due to multiple reflection, refraction and scattering, where the scattering signals caused by metal are very strong, while the signals scattered by an air bubble are weaker. The influence of defect both in time and frequency domain are found through deconvolution treatment. In the time domain,more » the deconvolution signals correspond to larger defect display a larger head wave amplitude and shorter arrive time than those of smaller defects; in the frequency domain, larger defect also shows a stronger amplitude, lower center frequency and lower cutoff frequency.« less

Exploitation of Ubiquitous Wi-Fi Devices as Building Blocks for Improvised Motion Detection Systems.

PubMed

Soldovieri, Francesco; Gennarelli, Gianluca

2016-02-27

This article deals with a feasibility study on the detection of human movements in indoor scenarios based on radio signal strength variations. The sensing principle exploits the fact that the human body interacts with wireless signals, introducing variations of the radiowave fields due to shadowing and multipath phenomena. As a result, human motion can be inferred from fluctuations of radiowave power collected by a receiving terminal. In this paper, we investigate the potentialities of widely available wireless communication devices in order to develop an improvised motion detection system (IMDS). Experimental tests are performed in an indoor environment by using a smartphone as a Wi-Fi access point and a laptop with dedicated software as a receiver. Simple detection strategies tailored for real-time operation are implemented to process the received signal strength measurements. The achieved results confirm the potentialities of the simple system here proposed to reliably detect human motion in operational conditions.

Structural health monitoring of plates with surface features using guided ultrasonic waves

NASA Astrophysics Data System (ADS)

Fromme, P.

2009-03-01

Distributed array systems for guided ultrasonic waves offer an efficient way for the long-term monitoring of the structural integrity of large plate-like structures. The measurement concept involving baseline subtraction has been demonstrated under laboratory conditions. For the application to real technical structures it needs to be shown that the methodology works equally well in the presence of structural and surface features. Problems employing this structural health monitoring concept can occur due to the presence of additional changes in the signal reflected at undamaged parts of the structure. The influence of the signal processing parameters and transducer placement on the damage detection and localization accuracy is discussed. The use of permanently attached, distributed sensors for the A0 Lamb wave mode has been investigated. Results are presented using experimental data obtained from laboratory measurements and Finite Element simulated signals for a large steel plate with a welded stiffener.

Costas loop lock detection in the advanced receiver

NASA Technical Reports Server (NTRS)

Mileant, A.; Hinedi, S.

1989-01-01

The advanced receiver currently being developed uses a Costas digital loop to demodulate the subcarrier. Previous analyses of lock detector algorithms for Costas loops have ignored the effects of the inherent correlation between the samples of the phase-error process. Accounting for this correlation is necessary to achieve the desired lock-detection probability for a given false-alarm rate. Both analysis and simulations are used to quantify the effects of phase correlation on lock detection for the square-law and the absolute-value type detectors. Results are obtained which depict the lock-detection probability as a function of loop signal-to-noise ratio for a given false-alarm rate. The mathematical model and computer simulation show that the square-law detector experiences less degradation due to phase jitter than the absolute-value detector and that the degradation in detector signal-to-noise ratio is more pronounced for square-wave than for sine-wave signals.

Vibration signal correction of unbalanced rotor due to angular speed fluctuation

NASA Astrophysics Data System (ADS)

Cao, Hongrui; He, Dong; Xi, Songtao; Chen, Xuefeng

2018-07-01

The rotating speed of a rotor is hardly constant in practice due to angular speed fluctuation, which affects the balancing accuracy of the rotor. In this paper, the effect of angular speed fluctuation on vibration responses of the unbalanced rotor is analyzed quantitatively. Then, a vibration signal correction method based on zoom synchrosqueezing transform (ZST) and tacholess order tracking is proposed. The instantaneous angular speed (IAS) of the rotor is extracted by the ZST firstly and then used to calculate the instantaneous phase. The vibration signal is further resampled in angular domain to reduce the effect of angular speed fluctuation. The signal obtained in angular domain is transformed into order domain using discrete Fourier transform (DFT) to estimate the amplitude and phase of the vibration signal. Simulated and experimental results show that the proposed method can successfully correct the amplitude and phase of the vibration signal due to angular speed fluctuation.

A study of rain effects on radar scattering from water waves

NASA Technical Reports Server (NTRS)

Bliven, Larry F.; Giovanangeli, Jean-Paul; Norcross, George

1988-01-01

Results are presented from a laboratory investigation of microwave power return due to rain-generated short waves on a wind wave surface. The wind wave tank, sensor, and data processing methods used in the study are described. The study focuses on the response of a 36-GHz radar system, orientated 30 deg from nadir and pointing upwind, to surface waves generated by various combinations of rain and wind. The results show stronger radar signal levels due to short surface waves generated by rain impacting the wind wave surface, supporting the results of Moore et al. (1979) for a 14-GHz radar.

Thermosensory signaling by TRPM is processed by brain serotonergic neurons to produce planarian thermotaxis.

PubMed

Inoue, Takeshi; Yamashita, Taiga; Agata, Kiyokazu

2014-11-19

For most organisms, sensitive recognition of even slight changes in environmental temperature is essential for adjusting their behavioral strategies to ensure homeostasis and survival. However, much remains to be understood about the molecular and cellular processes that regulate thermosensation and the corresponding behavioral responses. Planarians display clear thermotaxis, although they have a relatively simple brain. Here, we devised a quantitative thermotaxis assay and unraveled a neural pathway involved in planarian thermotaxis by combinatory behavioral assays and RNAi analysis. We found that thermosensory neurons that expressed a planarian Dugesia japonica homolog of the Transient Receptor Potential Melastatin family a (DjTRPMa) gene were required for the thermotaxis. Interestingly, although these thermosensory neurons are distributed throughout their body, planarians with a dysfunctional brain due to regeneration-dependent conditional gene knockdown (Readyknock) of the synaptotagmin gene completely lost their thermotactic behavior. These results suggest that brain function is required as a central processor for the thermosensory response. Therefore, we investigated the type(s) of brain neurons involved in processing the thermal signals by gene knockdown of limiting enzymes for neurotransmitter biosynthesis in the brain. We found that serotonergic neurons with dendrites that were elongated toward DjTRPMa-expressing thermosensory neurons might be required for the processing of signals from thermosensory neurons that results in thermotaxis. These results suggest that serotonergic neurons in the brain may interact with thermosensory neurons activated by TRPM ion channels to produce thermotaxis in planarians. Copyright © 2014 the authors 0270-6474/14/3415701-14$15.00/0.

Singularity detection by wavelet approach: application to electrocardiogram signal

NASA Astrophysics Data System (ADS)

Jalil, Bushra; Beya, Ouadi; Fauvet, Eric; Laligant, Olivier

2010-01-01

In signal processing, the region of abrupt changes contains the most of the useful information about the nature of the signal. The region or the points where these changes occurred are often termed as singular point or singular region. The singularity is considered to be an important character of the signal, as it refers to the discontinuity and interruption present in the signal and the main purpose of the detection of such singular point is to identify the existence, location and size of those singularities. Electrocardiogram (ECG) signal is used to analyze the cardiovascular activity in the human body. However the presence of noise due to several reasons limits the doctor's decision and prevents accurate identification of different pathologies. In this work we attempt to analyze the ECG signal with energy based approach and some heuristic methods to segment and identify different signatures inside the signal. ECG signal has been initially denoised by empirical wavelet shrinkage approach based on Steins Unbiased Risk Estimate (SURE). At the second stage, the ECG signal has been analyzed by Mallat approach based on modulus maximas and Lipschitz exponent computation. The results from both approaches has been discussed and important aspects has been highlighted. In order to evaluate the algorithm, the analysis has been done on MIT-BIH Arrhythmia database; a set of ECG data records sampled at a rate of 360 Hz with 11 bit resolution over a 10mv range. The results have been examined and approved by medical doctors.

System for monitoring an industrial or biological process

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.; Vilim, Rick B.; White, Andrew M.

1998-01-01

A method and apparatus for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time length. The industrial signals are adjusted over the time length relative to the reference signals, the phase shift of the industrial signals is optimized to the reference signals and the resulting signals output for analysis by systems such as SPRT.

System for monitoring an industrial or biological process

DOEpatents

Gross, K.C.; Wegerich, S.W.; Vilim, R.B.; White, A.M.

1998-06-30

A method and apparatus are disclosed for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time length. The industrial signals are adjusted over the time length relative to the reference signals, the phase shift of the industrial signals is optimized to the reference signals and the resulting signals output for analysis by systems such as SPRT. 49 figs.

Fuzzy Logic-Based Audio Pattern Recognition

NASA Astrophysics Data System (ADS)

Malcangi, M.

2008-11-01

Audio and audio-pattern recognition is becoming one of the most important technologies to automatically control embedded systems. Fuzzy logic may be the most important enabling methodology due to its ability to rapidly and economically model such application. An audio and audio-pattern recognition engine based on fuzzy logic has been developed for use in very low-cost and deeply embedded systems to automate human-to-machine and machine-to-machine interaction. This engine consists of simple digital signal-processing algorithms for feature extraction and normalization, and a set of pattern-recognition rules manually tuned or automatically tuned by a self-learning process.

Stability of Intercellular Exchange of Biochemical Substances Affected by Variability of Environmental Parameters

NASA Astrophysics Data System (ADS)

Mihailović, Dragutin T.; Budinčević, Mirko; Balaž, Igor; Mihailović, Anja

Communication between cells is realized by exchange of biochemical substances. Due to internal organization of living systems and variability of external parameters, the exchange is heavily influenced by perturbations of various parameters at almost all stages of the process. Since communication is one of essential processes for functioning of living systems it is of interest to investigate conditions for its stability. Using previously developed simplified model of bacterial communication in a form of coupled difference logistic equations we investigate stability of exchange of signaling molecules under variability of internal and external parameters.

Analog-to-digital conversion as a source of drifts in displacements derived from digital recordings of ground acceleration

USGS Publications Warehouse

Boore, D.M.

2003-01-01

Displacements obtained from double integration of digitally recorded ground accelerations often show drifts much larger than those expected for the true ground displacements. These drifts might be due to many things, including dynamic elastic ground tilt, inelastic ground deformation, hysteresis in the instruments, and cross feed due to misalignment of nominally orthogonal sensors. This article shows that even if those effects were not present, the analog-to-digital conversion (ADC) process can produce apparent "pulses" and offsets in the acceleration baseline if the ground motion is slowly varying compared with the quantization level of the digitization. Such slowly varying signals can be produced by constant offsets that do not coincide with a quantization level and by near- and intermediate-field terms in the wave field radiated from earthquakes. Double integration of these apparent pulses and offsets leads to drifts in the displacements similar to those found in processing real recordings. These effects decrease in importance as the resolution of the ADC process increases.

Active disturbance rejection controller for chemical reactor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Both, Roxana; Dulf, Eva H.; Muresan, Cristina I., E-mail: roxana.both@aut.utcluj.ro

2015-03-10

In the petrochemical industry, the synthesis of 2 ethyl-hexanol-oxo-alcohols (plasticizers alcohol) is of high importance, being achieved through hydrogenation of 2 ethyl-hexenal inside catalytic trickle bed three-phase reactors. For this type of processes the use of advanced control strategies is suitable due to their nonlinear behavior and extreme sensitivity to load changes and other disturbances. Due to the complexity of the mathematical model an approach was to use a simple linear model of the process in combination with an advanced control algorithm which takes into account the model uncertainties, the disturbances and command signal limitations like robust control. However themore » resulting controller is complex, involving cost effective hardware. This paper proposes a simple integer-order control scheme using a linear model of the process, based on active disturbance rejection method. By treating the model dynamics as a common disturbance and actively rejecting it, active disturbance rejection control (ADRC) can achieve the desired response. Simulation results are provided to demonstrate the effectiveness of the proposed method.« less

Analysis of Seasonal Signal in GPS Short-Baseline Time Series

NASA Astrophysics Data System (ADS)

Wang, Kaihua; Jiang, Weiping; Chen, Hua; An, Xiangdong; Zhou, Xiaohui; Yuan, Peng; Chen, Qusen

2018-04-01

Proper modeling of seasonal signals and their quantitative analysis are of interest in geoscience applications, which are based on position time series of permanent GPS stations. Seasonal signals in GPS short-baseline (< 2 km) time series, if they exist, are mainly related to site-specific effects, such as thermal expansion of the monument (TEM). However, only part of the seasonal signal can be explained by known factors due to the limited data span, the GPS processing strategy and/or the adoption of an imperfect TEM model. In this paper, to better understand the seasonal signal in GPS short-baseline time series, we adopted and processed six different short-baselines with data span that varies from 2 to 14 years and baseline length that varies from 6 to 1100 m. To avoid seasonal signals that are overwhelmed by noise, each of the station pairs is chosen with significant differences in their height (> 5 m) or type of the monument. For comparison, we also processed an approximately zero baseline with a distance of < 1 m and identical monuments. The daily solutions show that there are apparent annual signals with annual amplitude of 1 mm (maximum amplitude of 1.86 ± 0.17 mm) on almost all of the components, which are consistent with the results from previous studies. Semi-annual signal with a maximum amplitude of 0.97 ± 0.25 mm is also present. The analysis of time-correlated noise indicates that instead of flicker (FL) or random walk (RW) noise, band-pass-filtered (BP) noise is valid for approximately 40% of the baseline components, and another 20% of the components can be best modeled by a combination of the first-order Gauss-Markov (FOGM) process plus white noise (WN). The TEM displacements are then modeled by considering the monument height of the building structure beneath the GPS antenna. The median contributions of TEM to the annual amplitude in the vertical direction are 84% and 46% with and without additional parts of the monument, respectively. Obvious annual signals with amplitude > 0.4 mm in the horizontal direction are observed in five short-baselines, and the amplitudes exceed 1 mm in four of them. These horizontal seasonal signals are likely related to the propagation of daily/sub-daily TEM displacement or other signals related to the site environment. Mismodeling of the tropospheric delay may also introduce spurious seasonal signals with annual amplitudes of 5 and 2 mm, respectively, for two short-baselines with elevation differences greater than 100 m. The results suggest that the monument height of the additional part of a typical GPS station should be considered when estimating the TEM displacement and that the tropospheric delay should be modeled cautiously, especially with station pairs with apparent elevation differences. The scheme adopted in this paper is expected to explicate more seasonal signals in GPS coordinate time series, particularly in the vertical direction.

Visual signal detection in structured backgrounds. II. Effects of contrast gain control, background variations, and white noise

NASA Technical Reports Server (NTRS)

Eckstein, M. P.; Ahumada, A. J. Jr; Watson, A. B.

1997-01-01

Studies of visual detection of a signal superimposed on one of two identical backgrounds show performance degradation when the background has high contrast and is similar in spatial frequency and/or orientation to the signal. To account for this finding, models include a contrast gain control mechanism that pools activity across spatial frequency, orientation and space to inhibit (divisively) the response of the receptor sensitive to the signal. In tasks in which the observer has to detect a known signal added to one of M different backgrounds grounds due to added visual noise, the main sources of degradation are the stochastic noise in the image and the suboptimal visual processing. We investigate how these two sources of degradation (contrast gain control and variations in the background) interact in a task in which the signal is embedded in one of M locations in a complex spatially varying background (structured background). We use backgrounds extracted from patient digital medical images. To isolate effects of the fixed deterministic background (the contrast gain control) from the effects of the background variations, we conduct detection experiments with three different background conditions: (1) uniform background, (2) a repeated sample of structured background, and (3) different samples of structured background. Results show that human visual detection degrades from the uniform background condition to the repeated background condition and degrades even further in the different backgrounds condition. These results suggest that both the contrast gain control mechanism and the background random variations degrade human performance in detection of a signal in a complex, spatially varying background. A filter model and added white noise are used to generate estimates of sampling efficiencies, an equivalent internal noise, an equivalent contrast-gain-control-induced noise, and an equivalent noise due to the variations in the structured background.

Signal processing using sparse derivatives with applications to chromatograms and ECG

NASA Astrophysics Data System (ADS)

Ning, Xiaoran

In this thesis, we investigate the sparsity exist in the derivative domain. Particularly, we focus on the type of signals which posses up to Mth (M > 0) order sparse derivatives. Efforts are put on formulating proper penalty functions and optimization problems to capture properties related to sparse derivatives, searching for fast, computationally efficient solvers. Also the effectiveness of these algorithms are applied to two real world applications. In the first application, we provide an algorithm which jointly addresses the problems of chromatogram baseline correction and noise reduction. The series of chromatogram peaks are modeled as sparse with sparse derivatives, and the baseline is modeled as a low-pass signal. A convex optimization problem is formulated so as to encapsulate these non-parametric models. To account for the positivity of chromatogram peaks, an asymmetric penalty function is also utilized with symmetric penalty functions. A robust, computationally efficient, iterative algorithm is developed that is guaranteed to converge to the unique optimal solution. The approach, termed Baseline Estimation And Denoising with Sparsity (BEADS), is evaluated and compared with two state-of-the-art methods using both simulated and real chromatogram data. Promising result is obtained. In the second application, a novel Electrocardiography (ECG) enhancement algorithm is designed also based on sparse derivatives. In the real medical environment, ECG signals are often contaminated by various kinds of noise or artifacts, for example, morphological changes due to motion artifact, non-stationary noise due to muscular contraction (EMG), etc. Some of these contaminations severely affect the usefulness of ECG signals, especially when computer aided algorithms are utilized. By solving the proposed convex l1 optimization problem, artifacts are reduced by modeling the clean ECG signal as a sum of two signals whose second and third-order derivatives (differences) are sparse respectively. At the end, the algorithm is applied to a QRS detection system and validated using the MIT-BIH Arrhythmia database (109452 anotations), resulting a sensitivity of Se = 99.87%$ and a positive prediction of +P = 99.88%.

Regulation mechanisms in mixed and pure culture microbial fermentation.

PubMed

Hoelzle, Robert D; Virdis, Bernardino; Batstone, Damien J

2014-11-01

Mixed-culture fermentation is a key central process to enable next generation biofuels and biocommodity production due to economic and process advantages over application of pure cultures. However, a key limitation to the application of mixed-culture fermentation is predicting culture product response, related to metabolic regulation mechanisms. This is also a limitation in pure culture bacterial fermentation. This review evaluates recent literature in both pure and mixed culture studies with a focus on understanding how regulation and signaling mechanisms interact with metabolic routes and activity. In particular, we focus on how microorganisms balance electron sinking while maximizing catabolic energy generation. Analysis of these mechanisms and their effect on metabolism dynamics is absent in current models of mixed-culture fermentation. This limits process prediction and control, which in turn limits industrial application of mixed-culture fermentation. A key mechanism appears to be the role of internal electron mediating cofactors, and related regulatory signaling. This may determine direction of electrons towards either hydrogen or reduced organics as end-products and may form the basis for future mechanistic models. © 2014 Wiley Periodicals, Inc.

An adaptive confidence limit for periodic non-steady conditions fault detection

NASA Astrophysics Data System (ADS)

Wang, Tianzhen; Wu, Hao; Ni, Mengqi; Zhang, Milu; Dong, Jingjing; Benbouzid, Mohamed El Hachemi; Hu, Xiong

2016-05-01

System monitoring has become a major concern in batch process due to the fact that failure rate in non-steady conditions is much higher than in steady ones. A series of approaches based on PCA have already solved problems such as data dimensionality reduction, multivariable decorrelation, and processing non-changing signal. However, if the data follows non-Gaussian distribution or the variables contain some signal changes, the above approaches are not applicable. To deal with these concerns and to enhance performance in multiperiod data processing, this paper proposes a fault detection method using adaptive confidence limit (ACL) in periodic non-steady conditions. The proposed ACL method achieves four main enhancements: Longitudinal-Standardization could convert non-Gaussian sampling data to Gaussian ones; the multiperiod PCA algorithm could reduce dimensionality, remove correlation, and improve the monitoring accuracy; the adaptive confidence limit could detect faults under non-steady conditions; the fault sections determination procedure could select the appropriate parameter of the adaptive confidence limit. The achieved result analysis clearly shows that the proposed ACL method is superior to other fault detection approaches under periodic non-steady conditions.

Reduced specificity in emotion judgment in people with autism spectrum disorder

PubMed Central

Wang, Shuo; Adolphs, Ralph

2017-01-01

There is a conflicting literature on facial emotion processing in autism spectrum disorder (ASD): both typical and atypical performance have been reported, and inconsistencies in the literature may stem from different processes examined (emotion judgment, face perception, fixations) as well as differences in participant populations. Here we conducted a detailed investigation of the ability to discriminate graded emotions shown in morphs of fear-happy faces, in a well-characterized high-functioning sample of participants with ASD and matched controls. Signal detection approaches were used in the analyses, and concurrent high-resolution eye-tracking was collected. Although people with ASD had typical thresholds for categorical fear and confidence judgments, their psychometric specificity to detect emotions across the entire range of intensities was reduced. However, fixation patterns onto the stimuli were typical and could not account for the reduced specificity of emotion judgment. Together, our results argue for a subtle and specific deficit in emotion perception in ASD that, from a signal detection perspective, is best understood as a reduced specificity due to increased noise in central processing of the face stimuli. PMID:28343960

A Sensor Data Fusion System Based on k-Nearest Neighbor Pattern Classification for Structural Health Monitoring Applications

PubMed Central

Vitola, Jaime; Pozo, Francesc; Tibaduiza, Diego A.; Anaya, Maribel

2017-01-01

Civil and military structures are susceptible and vulnerable to damage due to the environmental and operational conditions. Therefore, the implementation of technology to provide robust solutions in damage identification (by using signals acquired directly from the structure) is a requirement to reduce operational and maintenance costs. In this sense, the use of sensors permanently attached to the structures has demonstrated a great versatility and benefit since the inspection system can be automated. This automation is carried out with signal processing tasks with the aim of a pattern recognition analysis. This work presents the detailed description of a structural health monitoring (SHM) system based on the use of a piezoelectric (PZT) active system. The SHM system includes: (i) the use of a piezoelectric sensor network to excite the structure and collect the measured dynamic response, in several actuation phases; (ii) data organization; (iii) advanced signal processing techniques to define the feature vectors; and finally; (iv) the nearest neighbor algorithm as a machine learning approach to classify different kinds of damage. A description of the experimental setup, the experimental validation and a discussion of the results from two different structures are included and analyzed. PMID:28230796

A Sensor Data Fusion System Based on k-Nearest Neighbor Pattern Classification for Structural Health Monitoring Applications.

PubMed

Vitola, Jaime; Pozo, Francesc; Tibaduiza, Diego A; Anaya, Maribel

2017-02-21

Civil and military structures are susceptible and vulnerable to damage due to the environmental and operational conditions. Therefore, the implementation of technology to provide robust solutions in damage identification (by using signals acquired directly from the structure) is a requirement to reduce operational and maintenance costs. In this sense, the use of sensors permanently attached to the structures has demonstrated a great versatility and benefit since the inspection system can be automated. This automation is carried out with signal processing tasks with the aim of a pattern recognition analysis. This work presents the detailed description of a structural health monitoring (SHM) system based on the use of a piezoelectric (PZT) active system. The SHM system includes: (i) the use of a piezoelectric sensor network to excite the structure and collect the measured dynamic response, in several actuation phases; (ii) data organization; (iii) advanced signal processing techniques to define the feature vectors; and finally; (iv) the nearest neighbor algorithm as a machine learning approach to classify different kinds of damage. A description of the experimental setup, the experimental validation and a discussion of the results from two different structures are included and analyzed.

Cortical mechanisms for afterimage formation: evidence from interocular grouping

PubMed Central

Dong, Bo; Holm, Linus; Bao, Min

2017-01-01

Whether the retinal process alone or retinal and cortical processes jointly determine afterimage (AI) formation has long been debated. Based on the retinal rebound responses, recent work proposes that afterimage signals are exclusively generated in the retina, although later modified by cortical mechanisms. We tested this notion with the method of “indirect proof”. Each eye was presented with a 2-by-2 checkerboard of horizontal and vertical grating patches. Each corresponding patch of the two checkerboards was perpendicular to each other, which produces binocular rivalry, and can generate percepts ranging from complete interocular grouping to either monocular pattern. The monocular percepts became more frequent with higher contrast. Due to adaptation, the visual system is less sensitive during the AIs than during the inductions with AI-similar contrast. If the retina is the only origin of AIs, comparable contrast appearance would require stronger retinal signals in the AIs than in the inductions, thus leading to more frequent monocular percepts in the AIs than in the inductions. Surprisingly, subjects saw the fully coherent stripes significantly more often in AIs. Our results thus contradict the retinal generation notion, and suggest that in addition to the retina, cortex is directly involved in the generation of AI signals. PMID:28112230

Optical fiber pressure sensors for adaptive wings

NASA Astrophysics Data System (ADS)

Duncan, Paul G.; Jones, Mark E.; Shinpaugh, Kevin A.; Poland, Stephen H.; Murphy, Kent A.; Claus, Richard O.

1997-06-01

Optical fiber pressure sensors have been developed for use on a structurally-adaptive `smart wing'; further details of the design, fabrication and testing of the smart wing concept are presented in companion papers. This paper describes the design, construction, and performance of the pressure sensor and a combined optical and electronic signal processing system implemented to permit the measurement of a large number of sensors distributed over the control surfaces of a wing. Optical fiber pressure sensors were implemented due to anticipated large electromagnetic interference signals within the operational environment. The sensors utilized the principle of the extrinsic Fabry-Perot interferometer (EFPI) already developed for the measurement of strain and temperature. Here, the cavity is created inside a micromachined hollow-core tube with a silicon diaphragm at one end. The operation of the sensor is similar to that of the EFPI strain gage also discussed in several papers at this conference. The limitations placed upon the performance of the digital signal processing system were determined by the required pressure range of the sensors and the cycle time of the control system used to adaptively modify the shape of the wing. Sensor calibration and the results of testing performed are detailed.

Assessing denoising strategies to increase signal to noise ratio in spinal cord and in brain cortical and subcortical regions

NASA Astrophysics Data System (ADS)

Maugeri, L.; Moraschi, M.; Summers, P.; Favilla, S.; Mascali, D.; Cedola, A.; Porro, C. A.; Giove, F.; Fratini, M.

2018-02-01

Functional Magnetic Resonance Imaging (fMRI) based on Blood Oxygenation Level Dependent (BOLD) contrast has become one of the most powerful tools in neuroscience research. On the other hand, fMRI approaches have seen limited use in the study of spinal cord and subcortical brain regions (such as the brainstem and portions of the diencephalon). Indeed obtaining good BOLD signal in these areas still represents a technical and scientific challenge, due to poor control of physiological noise and to a limited overall quality of the functional series. A solution can be found in the combination of optimized experimental procedures at acquisition stage, and well-adapted artifact mitigation procedures in the data processing. In this framework, we studied two different data processing strategies to reduce physiological noise in cortical and subcortical brain regions and in the spinal cord, based on the aCompCor and RETROICOR denoising tools respectively. The study, performed in healthy subjects, was carried out using an ad hoc isometric motor task. We observed an increased signal to noise ratio in the denoised functional time series in the spinal cord and in the subcortical brain region.

A two-step along-track spectral analysis for estimating the magnetic signals of magnetospheric ring current from Swarm data

NASA Astrophysics Data System (ADS)

Martinec, Zdeněk; Velímský, Jakub; Haagmans, Roger; Šachl, Libor

2018-02-01

This study deals with the analysis of Swarm vector magnetic field measurements in order to estimate the magnetic field of magnetospheric ring current. For a single Swarm satellite, the magnetic measurements are processed by along-track spectral analysis on a track-by-track basis. The main and lithospheric magnetic fields are modelled by the CHAOS-6 field model and subtracted from the along-track Swarm magnetic data. The mid-latitude residual signal is then spectrally analysed and extrapolated to the polar regions. The resulting model of the magnetosphere (model MME) is compared to the existing Swarm Level 2 magnetospheric field model (MMA_SHA_2C). The differences of up to 10 nT are found on the nightsides Swarm data from 2014 April 8 to May 10, which are due to different processing schemes used to construct the two magnetospheric magnetic field models. The forward-simulated magnetospheric magnetic field generated by the external part of model MME then demonstrates the consistency of the separation of the Swarm along-track signal into the external and internal parts by the two-step along-track spectral analysis.

Information processing in network architecture of genome controlled signal transduction circuit. A proposed theoretical explanation.

PubMed

Chakraborty, Chiranjib; Sarkar, Bimal Kumar; Patel, Pratiksha; Agoramoorthy, Govindasamy

2012-01-01

In this paper, Shannon information theory has been applied to elaborate cell signaling. It is proposed that in the cellular network architecture, four components viz. source (DNA), transmitter (mRNA), receiver (protein) and destination (another protein) are involved. The message transmits from source (DNA) to transmitter (mRNA) and then passes through a noisy channel reaching finally the receiver (protein). The protein synthesis process is here considered as the noisy channel. Ultimately, signal is transmitted from receiver to destination (another protein). The genome network architecture elements were compared with genetic alphabet L = {A, C, G, T} with a biophysical model based on the popular Shannon information theory. This study found the channel capacity as maximum for zero error (sigma = 0) and at this condition, transition matrix becomes a unit matrix with rank 4. The transition matrix will be erroneous and finally at sigma = 1 channel capacity will be localized maxima with a value of 0.415 due to the increased value at sigma. On the other hand, minima exists at sigma = 0.75, where all transition probabilities become 0.25 and uncertainty will be maximum resulting in channel capacity with the minima value of zero.

Gear fault diagnosis based on the structured sparsity time-frequency analysis

NASA Astrophysics Data System (ADS)

Sun, Ruobin; Yang, Zhibo; Chen, Xuefeng; Tian, Shaohua; Xie, Yong

2018-03-01

Over the last decade, sparse representation has become a powerful paradigm in mechanical fault diagnosis due to its excellent capability and the high flexibility for complex signal description. The structured sparsity time-frequency analysis (SSTFA) is a novel signal processing method, which utilizes mixed-norm priors on time-frequency coefficients to obtain a fine match for the structure of signals. In order to extract the transient feature from gear vibration signals, a gear fault diagnosis method based on SSTFA is proposed in this work. The steady modulation components and impulsive components of the defective gear vibration signals can be extracted simultaneously by choosing different time-frequency neighborhood and generalized thresholding operators. Besides, the time-frequency distribution with high resolution is obtained by piling different components in the same diagram. The diagnostic conclusion can be made according to the envelope spectrum of the impulsive components or by the periodicity of impulses. The effectiveness of the method is verified by numerical simulations, and the vibration signals registered from a gearbox fault simulator and a wind turbine. To validate the efficiency of the presented methodology, comparisons are made among some state-of-the-art vibration separation methods and the traditional time-frequency analysis methods. The comparisons show that the proposed method possesses advantages in separating feature signals under strong noise and accounting for the inner time-frequency structure of the gear vibration signals.

Development of a Double-Gauss Lens Based Setup for Optoacoustic Applications

PubMed Central

Choi, Hojong; Ryu, Jae-Myung; Yeom, Jung-Yeol

2017-01-01

In optoacoustic (photoacoustic) systems, different echo signal intensities such as amplitudes, center frequencies, and bandwidths need to be compensated by utilizing variable gain or time-gain compensation amplifiers. However, such electronic components can increase system complexities and signal noise levels. In this paper, we introduce a double-Gauss lens to generate a large field of view with uniform light intensity due to the low chromatic aberrations of the lens, thus obtaining uniform echo signal intensities across the field of view of the optoacoustic system. In order to validate the uniformity of the echo signal intensities in the system, an in-house transducer was placed at various positions above a tissue sample and echo signals were measured and compared with each other. The custom designed double-Gauss lens demonstrated negligible light intensity variation (±1.5%) across the illumination field of view (~2 cm diameter). When the transducer was used to measure echo signal from an eye of a bigeye tuna within a range of ±1 cm, the peak-to-peak amplitude, center frequency, and their −6 dB bandwidth variations were less than 2 mV, 1 MHz, and 6%, respectively. The custom designed double-Gauss lens can provide uniform light beam across a wide area while generating insignificant echo signal variations, and thus can lower the burden of the receiving electronics or signal processing in the optoacoustic system. PMID:28273794

Titanium dioxide nanowire sensor array integration on CMOS platform using deterministic assembly.

PubMed

Gall, Oren Z; Zhong, Xiahua; Schulman, Daniel S; Kang, Myungkoo; Razavieh, Ali; Mayer, Theresa S

2017-06-30

Nanosensor arrays have recently received significant attention due to their utility in a wide range of applications, including gas sensing, fuel cells, internet of things, and portable health monitoring systems. Less attention has been given to the production of sensor platforms in the μW range for ultra-low power applications. Here, we discuss how to scale the nanosensor energy demand by developing a process for integration of nanowire sensing arrays on a monolithic CMOS chip. This work demonstrates an off-chip nanowire fabrication method; subsequently nanowires link to a fused SiO 2 substrate using electric-field assisted directed assembly. The nanowire resistances shown in this work have the highest resistance uniformity reported to date of 18%, which enables a practical roadmap towards the coupling of nanosensors to CMOS circuits and signal processing systems. The article also presents the utility of optimizing annealing conditions of the off-chip metal-oxides prior to CMOS integration to avoid limitations of thermal budget and process incompatibility. In the context of the platform demonstrated here, directed assembly is a powerful tool that can realize highly uniform, cross-reactive arrays of different types of metal-oxide nanosensors suited for gas discrimination and signal processing systems.

Titanium dioxide nanowire sensor array integration on CMOS platform using deterministic assembly

NASA Astrophysics Data System (ADS)

Gall, Oren Z.; Zhong, Xiahua; Schulman, Daniel S.; Kang, Myungkoo; Razavieh, Ali; Mayer, Theresa S.

2017-06-01

Nanosensor arrays have recently received significant attention due to their utility in a wide range of applications, including gas sensing, fuel cells, internet of things, and portable health monitoring systems. Less attention has been given to the production of sensor platforms in the μW range for ultra-low power applications. Here, we discuss how to scale the nanosensor energy demand by developing a process for integration of nanowire sensing arrays on a monolithic CMOS chip. This work demonstrates an off-chip nanowire fabrication method; subsequently nanowires link to a fused SiO2 substrate using electric-field assisted directed assembly. The nanowire resistances shown in this work have the highest resistance uniformity reported to date of 18%, which enables a practical roadmap towards the coupling of nanosensors to CMOS circuits and signal processing systems. The article also presents the utility of optimizing annealing conditions of the off-chip metal-oxides prior to CMOS integration to avoid limitations of thermal budget and process incompatibility. In the context of the platform demonstrated here, directed assembly is a powerful tool that can realize highly uniform, cross-reactive arrays of different types of metal-oxide nanosensors suited for gas discrimination and signal processing systems.

Improving the Response of Accelerometers for Automotive Applications by Using LMS Adaptive Filters: Part II

PubMed Central

Hernandez, Wilmar; de Vicente, Jesús; Sergiyenko, Oleg Y.; Fernández, Eduardo

2010-01-01

In this paper, the fast least-mean-squares (LMS) algorithm was used to both eliminate noise corrupting the important information coming from a piezoresisitive accelerometer for automotive applications, and improve the convergence rate of the filtering process based on the conventional LMS algorithm. The response of the accelerometer under test was corrupted by process and measurement noise, and the signal processing stage was carried out by using both conventional filtering, which was already shown in a previous paper, and optimal adaptive filtering. The adaptive filtering process relied on the LMS adaptive filtering family, which has shown to have very good convergence and robustness properties, and here a comparative analysis between the results of the application of the conventional LMS algorithm and the fast LMS algorithm to solve a real-life filtering problem was carried out. In short, in this paper the piezoresistive accelerometer was tested for a multi-frequency acceleration excitation. Due to the kind of test conducted in this paper, the use of conventional filtering was discarded and the choice of one adaptive filter over the other was based on the signal-to-noise ratio improvement and the convergence rate. PMID:22315579

The influence of laser pulse duration and energy on ICP-MS signal intensity, elemental fractionation, and particle size distribution in NIR fs-LA-ICP-MS

PubMed Central

Diwakar, Prasoon K.; Harilal, Sivanandan S.; LaHaye, Nicole L.; Hassanein, Ahmed; Kulkarni, Pramod

2015-01-01

Laser parameters, typically wavelength, pulse width, irradiance, repetition rate, and pulse energy, are critical parameters which influence the laser ablation process and thereby influence the LA-ICP-MS signal. In recent times, femtosecond laser ablation has gained popularity owing to the reduction in fractionation related issues and improved analytical performance which can provide matrix-independent sampling. The advantage offered by fs-LA is due to shorter pulse duration of the laser as compared to the phonon relaxation time and heat diffusion time. Hence the thermal effects are minimized in fs-LA. Recently, fs-LA-ICP-MS demonstrated improved analytical performance as compared to ns-LA-ICP-MS, but detailed mechanisms and processes are still not clearly understood. Improvement of fs-LA-ICP-MS over ns-LA-ICP-MS elucidates the importance of laser pulse duration and related effects on the ablation process. In this study, we have investigated the influence of laser pulse width (40 fs to 0.3 ns) and energy on LA-ICP-MS signal intensity and repeatability using a brass sample. Experiments were performed in single spot ablation mode as well as rastering ablation mode to monitor the Cu/Zn ratio. The recorded ICP-MS signal was correlated with total particle counts generated during laser ablation as well as particle size distribution. Our results show the importance of pulse width effects in the fs regime that becomes more pronounced when moving from femtosecond to picosecond and nanosecond regimes. PMID:26664120

Matched signal detection on graphs: Theory and application to brain imaging data classification.

PubMed

Hu, Chenhui; Sepulcre, Jorge; Johnson, Keith A; Fakhri, Georges E; Lu, Yue M; Li, Quanzheng

2016-01-15

Motivated by recent progress in signal processing on graphs, we have developed a matched signal detection (MSD) theory for signals with intrinsic structures described by weighted graphs. First, we regard graph Laplacian eigenvalues as frequencies of graph-signals and assume that the signal is in a subspace spanned by the first few graph Laplacian eigenvectors associated with lower eigenvalues. The conventional matched subspace detector can be applied to this case. Furthermore, we study signals that may not merely live in a subspace. Concretely, we consider signals with bounded variation on graphs and more general signals that are randomly drawn from a prior distribution. For bounded variation signals, the test is a weighted energy detector. For the random signals, the test statistic is the difference of signal variations on associated graphs, if a degenerate Gaussian distribution specified by the graph Laplacian is adopted. We evaluate the effectiveness of the MSD on graphs both with simulated and real data sets. Specifically, we apply MSD to the brain imaging data classification problem of Alzheimer's disease (AD) based on two independent data sets: 1) positron emission tomography data with Pittsburgh compound-B tracer of 30 AD and 40 normal control (NC) subjects, and 2) resting-state functional magnetic resonance imaging (R-fMRI) data of 30 early mild cognitive impairment and 20 NC subjects. Our results demonstrate that the MSD approach is able to outperform the traditional methods and help detect AD at an early stage, probably due to the success of exploiting the manifold structure of the data. Copyright © 2015. Published by Elsevier Inc.

Time-frequency analysis of time-varying modulated signals based on improved energy separation by iterative generalized demodulation

NASA Astrophysics Data System (ADS)

Feng, Zhipeng; Chu, Fulei; Zuo, Ming J.

2011-03-01

Energy separation algorithm is good at tracking instantaneous changes in frequency and amplitude of modulated signals, but it is subject to the constraints of mono-component and narrow band. In most cases, time-varying modulated vibration signals of machinery consist of multiple components, and have so complicated instantaneous frequency trajectories on time-frequency plane that they overlap in frequency domain. For such signals, conventional filters fail to obtain mono-components of narrow band, and their rectangular decomposition of time-frequency plane may split instantaneous frequency trajectories thus resulting in information loss. Regarding the advantage of generalized demodulation method in decomposing multi-component signals into mono-components, an iterative generalized demodulation method is used as a preprocessing tool to separate signals into mono-components, so as to satisfy the requirements by energy separation algorithm. By this improvement, energy separation algorithm can be generalized to a broad range of signals, as long as the instantaneous frequency trajectories of signal components do not intersect on time-frequency plane. Due to the good adaptability of energy separation algorithm to instantaneous changes in signals and the mono-component decomposition nature of generalized demodulation, the derived time-frequency energy distribution has fine resolution and is free from cross term interferences. The good performance of the proposed time-frequency analysis is illustrated by analyses of a simulated signal and the on-site recorded nonstationary vibration signal of a hydroturbine rotor during a shut-down transient process, showing that it has potential to analyze time-varying modulated signals of multi-components.

Linking the optically monitored channel evolution with tremor like seismic activity during aero-fracturing in a very fine granular medium

NASA Astrophysics Data System (ADS)

Turkaya, Semih; Toussaint, Renaud; Kvalheim Eriksen, Fredrik; Zecevic, Megan; Daniel, Guillaume

2014-05-01

The characterization and comprehension of rock deformation processes due to fluid flow is a challenging problem with numerous applications in many fields. This phenomenon has received an ever-increasing attention in Earth Science, Physics, with many applications in natural hazard understanding, mitigation or forecast (e.g. earthquakes, landslides with hydrological control,volcanic eruptions), or in the industry, as CO2 sequestration. Even though the fluids and rocks are relatively easier to understand individually, the coupled behaviour of porous media with a dynamic fluid flow makes the system difficult to comprehend. The dynamic interaction between flow and the porous media, rapid changes in the local porosity due to the compaction and migration of the porous material, fracturing due to the momentum exchange in fast flow, make understanding of such a complex system a challenge. In this study, analogue models are developed to predict and control the mechanical stability of rock and soil formations during the injection or extraction of fluids. The models are constructed and calibrated based on the experimental data acquired. This experimental data obtained from solid-fluid interaction are monitored using a combination of techniques, both from geophysics and from experimental fluid mechanics. The experimental setup consists of a rectangular Hele-Shaw cell with three closed boundaries and one semi-permeable boundary which enables the flow of the fluid but not the solid particles. Non expanding polystyrene beads around 80μm size are used as solid particles and air is used as the intruding fluid. During the experiments, the fluid is injected steadily (or injected and suddenly stopped to see the pushback in a setup with four impermeable boundaries) into the system from the point opposite to the semi-permeable boundary so that the fluid penetrates into the solid and makes a way via creating channels, fractures or directly using the pore network to the semi-permeable boundary. The acoustic signals emitted during the mentioned solid-fluid interactions are recorded by various sensors - i.e. Piezoelectric Shock Accelerometer (Freq. range: 1Hz - 26kHz) and Piezoelectrical Sensors (Freq. range: 100kHz - 1MHz) with a sampling rate of 1MHz - on the Hele-Shaw cell. After the experiment, those signals are compared and investigated further in both time and frequency domains. Moreover, by using different techniques localization of the acoustic emissions are done and compared. Furthermore, during the experiments pictures of the Hele-Shaw cell are taken using a high speed camera. Thus, it is possible to visualize the solid-fluid interaction and to process images to gather information about the mechanical properties of the solid partition. The link between the visual and the mechanical wave signals is investigated. The spectrum of the signal is observed to be strongly affected by the size and shape of deforming channels created during the process. The power of the recorded signal is related to the integrated deformation rate in the process. Fast avalanches and rearrangements of grains at small scales are related to high frequency (above 10 kHz) acoustic emissions.

Systems, Methods and Apparatus for Position Sensor Digital Conditioning Electronics

NASA Technical Reports Server (NTRS)

Howard, David E. (Inventor); Alhorn, Dean C. (Inventor); Smith, Dennis A. (Inventor); Dutton, Kenneth R. (Inventor)

2012-01-01

Systems, methods and apparatus are provided through which in some implementations determine the amplitude of an amplitude modulated signal, modulated by the position of an object being sensed. In some aspects, the apparatus accepts an excitation signal and the amplitude modulated signal and divides the amplitude modulated by the excitation signal to produce an output signal that is proportional to the position of the object being sensed. In other aspects, the division is performed only when the excitation signal is non-zero, such as close to the peaks in the excitation signal. In other aspects, the excitation signal and amplitude modulated signal are degraded due to an air gap and the degraded signals are used to correct for amplitude fluctuations due to the air gap, and produce an output signal, tolerant of the air gaps, that is proportional to the position of the object being sensed.

Cross-talk of WNT and FGF signaling pathways at GSK3beta to regulate beta-catenin and SNAIL signaling cascades.

PubMed

Katoh, Masuko; Katoh, Masaru

2006-09-01

WNT and FGF signaling pathways cross-talk during a variety of cellular processes, such as human colorectal carcinogenesis, mouse mammary tumor virus (MMTV)-induced carcinogenesis, E2A-Pbx-induced leukemogenesis, early embryogenesis, body-axis formation, limb-bud formation, and neurogenesis. Canonical WNT signals are transduced through Frizzled receptor and LRP5/6 coreceptor to downregulate GSK3beta (GSK3B) activity not depending on Ser 9 phosphorylation. FGF signals are transduced through FGF receptor to the FRS2-GRB2-GAB1-PI3K-AKT signaling cascade to downregulate GSK3beta activity depending on Ser 9 phosphorylation. Because GSK3beta-dependent phosphorylation of beta-catenin and SNAIL leads to FBXW1 (betaTRCP)-mediated ubiquitination and degradation, GSK3beta downregulation results in the stabilization and the nuclear accumulation of beta-catenin and SNAIL. Nuclear beta-catenin is complexed with TCF/LEF, Legless (BCL9 or BCL9L) and PYGO (PYGO1 or PYGO2) to activate transcription of CCND1, MYC, FGF18 and FGF20 genes for the cell-fate determination. Nuclear SNAIL represses transcription of CDH1 gene, encoding E-cadherin, to induce the epithelial-mesenchymal transition (EMT). Mammary carcinogenesis in MMTV-Wnt1 transgenic mice is accelerated by MMTV infection due to MMTV integration around Fgf3-Fgf4 or Fgf8 loci, and mammary carcinogenesis in MMTV-Fgf3 transgenic mice due to MMTV integration around Wnt1-Wnt10b locus. Coactivation of WNT and FGF signaling pathways in tumors leads to more malignant phenotypes. Single nucleotide polymorphism (SNP) and copy number polymorphism (CNP) of WNT and FGF signaling molecules could be utilized as screening method of cancer predisposition. cDNA-PCR, microarray or ELISA reflecting aberrant activation of WNT and FGF signaling pathways could be developed as novel cancer-related biomarkers for diagnosis, prognosis, and therapy. Cocktail therapy using WNT and FGF inhibitors, such as small-molecule compounds and human neutralizing antibodies, should be developed to increase the efficacy of chemotherapy through the inhibition of recurrence by destructing cancer stem cells.

Proteomics of vitamin B12 processing.

PubMed

Hannibal, Luciana; DiBello, Patricia M; Jacobsen, Donald W

2013-03-01

The causes of cobalamin (B12, Cbl) deficiency are multifactorial. Whether nutritional due to poor dietary intake, or functional due to impairments in absorption or intracellular processing and trafficking events, the major symptoms of Cbl deficiency include megaloblastic anemia, neurological deterioration and in extreme cases, failure to thrive and death. The common biomarkers of Cbl deficiency (hyperhomocysteinemia and methylmalonic acidemia) are extremely valuable diagnostic indicators of the condition, but little is known about the changes that occur at the protein level. A mechanistic explanation bridging the physiological changes associated with functional B12 deficiency with its intracellular processers and carriers is lacking. In this article, we will cover the effects of B12 deficiency in a cblC-disrupted background (also referred to as MMACHC) as a model of functional Cbl deficiency. As will be shown, major protein changes involve the cytoskeleton, the neurological system as well as signaling and detoxification pathways. Supplementation of cultured MMACHC-mutant cells with hydroxocobalamin (HOCbl) failed to restore these variants to the normal phenotype, suggesting that a defective Cbl processing pathway produces irreversible changes at the protein level.

Multipath detection with the combination of SNR measurements - Example from urban environment

NASA Astrophysics Data System (ADS)

Špánik, Peter; Hefty, Ján

2017-12-01

Multipath is one of the most severe station-dependent error sources in both static and kinematic positioning. Relatively new and simple detection technique using the Signal-to-Noise (SNR) measurements on three frequencies will be presented based on idea of Strode and Groves. Exploitation of SNR measurements is benefi cial especially for their unambiguous character. Method is based on the fact that SNR values are closely linked with estimation of pseudo-ranges and phase measurements during signal correlation processing. Due to this connection, combination of SNR values can be used to detect anomalous behavior in received signal, however some kind of calibration in low multipath environment has to be done previously. In case of multipath, phase measurements on different frequencies will not be affected in the same manner. Specular multipath, e.g. from building wall introduces additional path delay which is interpreted differently on each of the used carrier, due to different wavelengths. Experimental results of multipath detection in urban environment will be presented. Originally proposed method is designed to work with three different frequencies in each epoch, thus only utilization of GPS Block II-F and Galileo satellites is possible. Simplification of detection statistics to use only two frequencies is made and results using GPS and GLONASS systems are presented along with results obtained using original formula.

Network capability estimation. Vela network evaluation and automatic processing research. Technical report. [NETWORTH

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snell, N.S.

1976-09-24

NETWORTH is a computer program which calculates the detection and location capability of seismic networks. A modified version of NETWORTH has been developed. This program has been used to evaluate the effect of station 'downtime', the signal amplitude variance, and the station detection threshold upon network detection capability. In this version all parameters may be changed separately for individual stations. The capability of using signal amplitude corrections has been added. The function of amplitude corrections is to remove possible bias in the magnitude estimate due to inhomogeneous signal attenuation. These corrections may be applied to individual stations, individual epicenters, ormore » individual station/epicenter combinations. An option has been added to calculate the effect of station 'downtime' upon network capability. This study indicates that, if capability loss due to detection errors can be minimized, then station detection threshold and station reliability will be the fundamental limits to network performance. A baseline network of thirteen stations has been performed. These stations are as follows: Alaskan Long Period Array, (ALPA); Ankara, (ANK); Chiang Mai, (CHG); Korean Seismic Research Station, (KSRS); Large Aperture Seismic Array, (LASA); Mashhad, (MSH); Mundaring, (MUN); Norwegian Seismic Array, (NORSAR); New Delhi, (NWDEL); Red Knife, Ontario, (RK-ON); Shillong, (SHL); Taipei, (TAP); and White Horse, Yukon, (WH-YK).« less

Optical feedback-induced light modulation for fiber-based laser ablation.

PubMed

Kang, Hyun Wook

2014-11-01

Optical fibers have been used as a minimally invasive tool in various medical fields. However, due to excessive heat accumulation, the distal end of a fiber often suffers from severe melting or devitrification, leading to the eventual fiber failure during laser treatment. In order to minimize thermal damage at the fiber tip, an optical feedback sensor was developed and tested ex vivo. Porcine kidney tissue was used to evaluate the feasibility of optical feedback in terms of signal activation, ablation performance, and light transmission. Testing various signal thresholds demonstrated that 3 V was relatively appropriate to trigger the feedback sensor and to prevent the fiber deterioration during kidney tissue ablation. Based upon the development of temporal signal signatures, full contact mode rapidly activated the optical feedback sensor possibly due to heat accumulation. Modulated light delivery induced by optical feedback diminished ablation efficiency by 30% in comparison with no feedback case. However, long-term transmission results validated that laser ablation assisted with optical feedback was able to almost consistently sustain light delivery to the tissue as well as ablation efficiency. Therefore, an optical feedback sensor can be a feasible tool to protect optical fiber tips by minimizing debris contamination and delaying thermal damage process and to ensure more efficient and safer laser-induced tissue ablation.

Understanding and eliminating artifact signals from diffusely scattered pump beam in measurements of rough samples by time-domain thermoreflectance (TDTR).

PubMed

Sun, Bo; Koh, Yee Kan

2016-06-01

Time-domain thermoreflectance (TDTR) is a pump-probe technique frequently applied to measure the thermal transport properties of bulk materials, nanostructures, and interfaces. One of the limitations of TDTR is that it can only be employed to samples with a fairly smooth surface. For rough samples, artifact signals are collected when the pump beam in TDTR measurements is diffusely scattered by the rough surface into the photodetector, rendering the TDTR measurements invalid. In this paper, we systemically studied the factors affecting the artifact signals due to the pump beam leaked into the photodetector and thus established the origin of the artifact signals. We find that signals from the leaked pump beam are modulated by the probe beam due to the phase rotation induced in the photodetector by the illumination of the probe beam. As a result of the modulation, artifact signals due to the leaked pump beam are registered in TDTR measurements as the out-of-phase signals. We then developed a simple approach to eliminate the artifact signals due to the leaked pump beam. We verify our leak-pump correction approach by measuring the thermal conductivity of a rough InN sample, when the signals from the leaked pump beam are significant. We also discuss the advantages of our new method over the two-tint approach and its limitations. Our new approach enables measurements of the thermal conductivity of rough samples using TDTR.

Understanding and eliminating artifact signals from diffusely scattered pump beam in measurements of rough samples by time-domain thermoreflectance (TDTR)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Bo; Koh, Yee Kan, E-mail: mpekyk@nus.edu.sg; Centre of Advanced 2D Materials, National University of Singapore, Singapore 117542

Time-domain thermoreflectance (TDTR) is a pump-probe technique frequently applied to measure the thermal transport properties of bulk materials, nanostructures, and interfaces. One of the limitations of TDTR is that it can only be employed to samples with a fairly smooth surface. For rough samples, artifact signals are collected when the pump beam in TDTR measurements is diffusely scattered by the rough surface into the photodetector, rendering the TDTR measurements invalid. In this paper, we systemically studied the factors affecting the artifact signals due to the pump beam leaked into the photodetector and thus established the origin of the artifact signals.more » We find that signals from the leaked pump beam are modulated by the probe beam due to the phase rotation induced in the photodetector by the illumination of the probe beam. As a result of the modulation, artifact signals due to the leaked pump beam are registered in TDTR measurements as the out-of-phase signals. We then developed a simple approach to eliminate the artifact signals due to the leaked pump beam. We verify our leak-pump correction approach by measuring the thermal conductivity of a rough InN sample, when the signals from the leaked pump beam are significant. We also discuss the advantages of our new method over the two-tint approach and its limitations. Our new approach enables measurements of the thermal conductivity of rough samples using TDTR.« less

Balanced detection for self-mixing interferometry to improve signal-to-noise ratio

NASA Astrophysics Data System (ADS)

Zhao, Changming; Norgia, Michele; Li, Kun

2018-01-01

We apply balanced detection to self-mixing interferometry for displacement and vibration measurement, using two photodiodes for implementing a differential acquisition. The method is based on the phase opposition of the self-mixing signal measured between the two laser diode facet outputs. The balanced signal obtained by enlarging the self-mixing signal, also by canceling of the common-due noises mainly due to disturbances on laser supply and transimpedance amplifier. Experimental results demonstrate the signal-to-noise ratio significantly improves, with almost twice signals enhancement and more than half noise decreasing. This method allows for more robust, longer-distance measurement systems, especially using fringe-counting.

NF-κB signaling mechanisms in HTLV-1-induced adult T-cell leukemia/lymphoma.

PubMed

Harhaj, Edward William; Giam, Chou-Zen

2018-05-03

The human T-cell leukemia virus type 1 (HTLV-1) is a complex deltaretrovirus linked to adult T-cell leukemia/lymphoma (ATLL), a fatal CD4+ malignancy in 3-5% of infected individuals. The HTLV-1 Tax regulatory protein plays indispensable roles in regulating viral gene expression and activating cellular signaling pathways that drive the proliferation and clonal expansion of T cells bearing HTLV-1 proviral integrations. Tax is a potent activator of NF-κB, a key signaling pathway that is essential for the survival and proliferation of HTLV-1 infected T cells. However, constitutive NF-κB activation by Tax also triggers a senescence response, suggesting the possibility that only T cells capable of overcoming NF-κB-induced senescence can selectively undergo clonal expansion after HTLV-1 infection. Tax expression is often silenced in the majority of ATLL due to genetic alterations in the tax gene or DNA hypermethylation of the 5'-LTR. Despite the loss of Tax, NF-κB activation remains persistently activated in ATLL due to somatic mutations in genes in the T/B-cell receptor (T/BCR) and NF-κB signaling pathways. In this review, we focus on the key events driving Tax-dependent and independent mechanisms of NF-κB activation during the multi-step process leading to ATLL. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Optical signal processing

NASA Technical Reports Server (NTRS)

Casasent, D.

1978-01-01

The article discusses several optical configurations used for signal processing. Electronic-to-optical transducers are outlined, noting fixed window transducers and moving window acousto-optic transducers. Folded spectrum techniques are considered, with reference to wideband RF signal analysis, fetal electroencephalogram analysis, engine vibration analysis, signal buried in noise, and spatial filtering. Various methods for radar signal processing are described, such as phased-array antennas, the optical processing of phased-array data, pulsed Doppler and FM radar systems, a multichannel one-dimensional optical correlator, correlations with long coded waveforms, and Doppler signal processing. Means for noncoherent optical signal processing are noted, including an optical correlator for speech recognition and a noncoherent optical correlator.

Magnetic Resonance Microscopy of Human and Porcine Neurons and Cellular Processes

PubMed Central

Flint, Jeremy J.; Hansen, Brian; Portnoy, Sharon; Lee, Choong-Heon; King, Michael A.; Fey, Michael; Vincent, Franck; Stanisz, Greg J; Vestergaard-Poulsen, Peter; Blackband, Stephen J

2012-01-01

With its unparalleled ability to safely generate high-contrast images of soft tissues, magnetic resonance imaging (MRI) has remained at the forefront of diagnostic clinical medicine. Unfortunately due to resolution limitations, clinical scans are most useful for detecting macroscopic structural changes associated with a small number of pathologies. Moreover, due to a longstanding inability to directly observe magnetic resonance (MR) signal behavior at the cellular level, such information is poorly characterized and generally must be inferred. With the advent of the MR microscope in 1986 came the ability to measure MR signal properties of theretofore unobservable tissue structures. Recently, further improvements in hardware technology have made possible the ability to visualize mammalian cellular structure. In the current study, we expand upon previous work by imaging the neuronal cell bodies and processes of human and porcine α-motor neurons. Complimentary imaging studies are conducted in pig tissue in order to demonstrate qualitative similarities to human samples. Also, apparent diffusion coefficient (ADC) maps were generated inside porcine α-motor neuron cell bodies and portions of their largest processes (mean = 1.7±0.5 μm2/ms based on 53 pixels) as well as in areas containing a mixture of extracellular space, microvasculature, and neuropil (0.59±0.37 μm2/ms based on 33 pixels). Three-dimensional reconstruction of MR images containing α-motor neurons shows the spatial arrangement of neuronal projections between adjacent cells. Such advancements in imaging portend the ability to construct accurate models of MR signal behavior based on direct observation and measurement of the components which comprise functional tissues. These tools would not only be useful for improving our interpretation of macroscopic MRI performed in the clinic, but they could potentially be used to develop new methods of differential diagnosis to aid in the early detection of a multitude of neuropathologies. PMID:22281672

Integrin beta1-mediated matrix assembly and signaling are critical for the normal development and function of the kidney glomerulus.

PubMed

Kanasaki, Keizo; Kanda, Yoshiko; Palmsten, Kristin; Tanjore, Harikrishna; Lee, Soo Bong; Lebleu, Valerie S; Gattone, Vincent H; Kalluri, Raghu

2008-01-15

The human kidneys filter 180 l of blood every day via about 2.5 million glomeruli. The three layers of the glomerular filtration apparatus consist of fenestrated endothelium, specialized extracellular matrix known as the glomerular basement membrane (GBM) and the podocyte foot processes with their modified adherens junctions known as the slit diaphragm (SD). In this study we explored the contribution of podocyte beta1 integrin signaling for normal glomerular function. Mice with podocyte specific deletion of integrin beta1 (podocin-Cre beta1-fl/fl mice) are born normal but cannot complete postnatal renal development. They exhibit detectable proteinuria on day 1 and die within a week. The kidneys of podocin-Cre beta1-fl/fl mice exhibit normal glomerular endothelium but show severe GBM defects with multilaminations and splitting including podocyte foot process effacement. The integrin linked kinase (ILK) is a downstream mediator of integrin beta1 activity in epithelial cells. To further explore whether integrin beta1-mediated signaling facilitates proper glomerular filtration, we generated mice deficient of ILK in the podocytes (podocin-Cre ILK-fl/fl mice). These mice develop normally but exhibit postnatal proteinuria at birth and die within 15 weeks of age due to renal failure. Collectively, our studies demonstrate that podocyte beta1 integrin and ILK signaling is critical for postnatal development and function of the glomerular filtration apparatus.

Direct Digital Demultiplexing of Analog TDM Signals for Cable Reduction in Ultrasound Imaging Catheters

PubMed Central

Carpenter, Thomas M.; Rashid, M. Wasequr; Ghovanloo, Maysam; Cowell, David M. J.; Freear, Steven; Degertekin, F. Levent

2016-01-01

In real-time catheter based 3D ultrasound imaging applications, gathering data from the transducer arrays is difficult as there is a restriction on cable count due to the diameter of the catheter. Although area and power hungry multiplexing circuits integrated at the catheter tip are used in some applications, these are unsuitable for use in small sized catheters for applications like intracardiac imaging. Furthermore, the length requirement for catheters and limited power available to on-chip cable drivers leads to limited signal strength at the receiver end. In this paper an alternative approach using Analog Time Division Multiplexing (TDM) is presented which addresses the cable restrictions of ultrasound catheters. A novel digital demultiplexing technique is also described which allows for a reduction in the number of analog signal processing stages required. The TDM and digital demultiplexing schemes are demonstrated for an intracardiac imaging system that would operate in the 4 MHz to 11 MHz range. A TDM integrated circuit (IC) with 8:1 multiplexer is interfaced with a fast ADC through a micro-coaxial catheter cable bundle, and processed with an FPGA RTL simulation. Input signals to the TDM IC are recovered with −40 dB crosstalk between channels on the same micro-coax, showing the feasibility of this system for ultrasound imaging applications. PMID:27116738

Use of Genetically-encoded Calcium Indicators for Live Cell Calcium Imaging and Localization in Virus-infected Cells

PubMed Central

Perry, Jacob L.; Ramachandran, Nina K.; Utama, Budi; Hyser, Joseph M.

2015-01-01

Calcium signaling is a ubiquitous and versatile process involved in nearly every cellular process, and exploitation of host calcium signals is a common strategy used by viruses to facilitate replication and cause disease. Small molecule fluorescent calcium dyes have been used by many to examine changes in host cell calcium signaling and calcium channel activation during virus infections, but disadvantages of these dyes, including poor loading and poor long-term retention, complicate analysis of calcium imaging in virus-infected cells due to changes in cell physiology and membrane integrity. The recent expansion of genetically-encoded calcium indicators (GECIs), including blue and red-shifted color variants and variants with calcium affinities appropriate for calcium storage organelles like the endoplasmic reticulum (ER), make the use of GECIs an attractive alternative for calcium imaging in the context of virus infections. Here we describe the development and testing of cell lines stably expressing both green cytoplasmic (GCaMP5G and GCaMP6s) and red ER-targeted (RCEPIAer) GECIs. Using three viruses (rotavirus, poliovirus and respiratory syncytial virus) previously shown to disrupt host calcium homeostasis, we show the GECI cell lines can be used to detect simultaneous cytoplasmic and ER calcium signals. Further, we demonstrate the GECI expression has sufficient stability to enable long-term confocal imaging of both cytoplasmic and ER calcium during the course of virus infections. PMID:26344758

Inhibition of host extracellular signal-regulated kinase (ERK) activation decreases new world alphavirus multiplication in infected cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Voss, Kelsey; Amaya, Moushimi; Mueller, Claudius

New World alphaviruses belonging to the family Togaviridae are classified as emerging infectious agents and Category B select agents. Our study is focused on the role of the host extracellular signal-regulated kinase (ERK) in the infectious process of New World alphaviruses. Infection of human cells by Venezuelan equine encephalitis virus (VEEV) results in the activation of the ERK-signaling cascade. Inhibition of ERK1/2 by the small molecule inhibitor Ag-126 results in inhibition of viral multiplication. Ag-126-mediated inhibition of VEEV was due to potential effects on early and late stages of the infectious process. While expression of viral proteins was down-regulated inmore » Ag-126 treated cells, we did not observe any influence of Ag-126 on the nuclear distribution of capsid. Finally, Ag-126 exerted a broad-spectrum inhibitory effect on New World alphavirus multiplication, thus indicating that the host kinase, ERK, is a broad-spectrum candidate for development of novel therapeutics against New World alphaviruses. - Highlights: • VEEV infection activated multiple components of the ERK signaling cascade. • Inhibition of ERK activation using Ag-126 inhibited VEEV multiplication. • Activation of ERK by Ceramide C6 increased infectious titers of TC-83. • Ag-126 inhibited virulent strains of all New World alphaviruses. • Ag-126 treatment increased percent survival of infected cells.« less

Detecting Dewatering of Peatland Pastures Using Sentinel-1 Satellite Radar Interferometry.

NASA Astrophysics Data System (ADS)

Heuff, F.; Samiei-Esfahany, S.; van Leijen, F. J.; Hanssen, R. F.

2017-12-01

The Netherlands are famous for their polders and the draining of soils to be used as pastures. Around 30% of the pastures are situated on peat soils, mostly in the western part of the Netherlands. Peat is composed of organic materials that oxidize and emit greenhouse gases when exposed to air. Oxidation of peat soils results in volume reduction and subsequent subsidence. As a result, the groundwater level rises relative to the surface. Consequently, the soil needs to be dewatered to keep it sufficiently dry for farming, resulting in more oxidation, and therefore more subsidence. This process is bound to continue until the peat soils have disappeared completely. The societal cost of land subsidence due to peat soils are estimated to be 5200 million euro for urban areas and 200 million euro for peatland pastures, for a period until 2050. Measuring the subsidence is not straightforward, if not impossible, with conventional geodetic means as soft soils make it impossible to install fixed benchmarks for repeated surveying. Also, due to the very fast temporal decorrelation over pastures, conventional InSAR approaches cannot measure a signal due to loss of coherence. Here we deploy a complete set of available SAR data from Sentinel-1, Radarsat-2 and TerraSAR-X to estimate the spatio-temporally varying subsidence signal due to the dewatering of peatland pastures over the western part of the Netherlands. We compute the InSAR coherence matrix for all possible interferometric combination, and compute an equivalent single-master stack to estimate the subsidence. Using terrain and land-use defined coherence estimation areas we optimize the phase estimation over areas severely affected by temporal decorrelation. This leads to a first estimate of deformation signals correlated with ancient shallow soil structures due to fluviatile structures. We use the methodology to investigate the effect of advanced local drainage schemes to slow down the subsidence phenomena.

Advances in the FTU collective Thomson scattering system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bin, W., E-mail: wbin@ifp.cnr.it; Bruschi, A.; Grosso, G.

The new collective Thomson scattering diagnostic installed on the Frascati Tokamak Upgrade device started its first operations in 2014. The ongoing experiments investigate the presence of signals synchronous with rotating tearing mode islands, possibly due to parametric decay processes, and phenomena affecting electron cyclotron beam absorption or scattering measurements. The radiometric system, diagnostic layout, and data acquisition system were improved accordingly. The present status and near-term developments of the diagnostic are presented.

Common Aperture Techniques for Imaging Electro-Optical Sensors (CATIES).

DTIC Science & Technology

1980-02-01

milliradians ) at the 5.33:1 zoom point. The zoom optics contain five elements with two moveable air -spaced doublets for accomplishing the zoom function...included in the electrical and optical design but due to funding limitations, system safety requirements during the testing phase and lack of long-term...determined during the system testing phase to be conducted by the Air Force. Limited electronic signal processing (split screen and video mix) was

Applied digital signal processing systems for vortex flowmeter with digital signal processing.

PubMed

Xu, Ke-Jun; Zhu, Zhi-Hai; Zhou, Yang; Wang, Xiao-Fen; Liu, San-Shan; Huang, Yun-Zhi; Chen, Zhi-Yuan

2009-02-01

The spectral analysis is combined with digital filter to process the vortex sensor signal for reducing the effect of disturbance at low frequency from pipe vibrations and increasing the turndown ratio. Using digital signal processing chip, two kinds of digital signal processing systems are developed to implement these algorithms. One is an integrative system, and the other is a separated system. A limiting amplifier is designed in the input analog condition circuit to adapt large amplitude variation of sensor signal. Some technique measures are taken to improve the accuracy of the output pulse, speed up the response time of the meter, and reduce the fluctuation of the output signal. The experimental results demonstrate the validity of the digital signal processing systems.

T-cell lymphomas associated gene expression signature: Bioinformatics analysis based on gene expression Omnibus.

PubMed

Zhou, Lei-Lei; Xu, Xiao-Yue; Ni, Jie; Zhao, Xia; Zhou, Jian-Wei; Feng, Ji-Feng

2018-06-01

Due to the low incidence and the heterogeneity of subtypes, the biological process of T-cell lymphomas is largely unknown. Although many genes have been detected in T-cell lymphomas, the role of these genes in biological process of T-cell lymphomas was not further analyzed. Two qualified datasets were downloaded from Gene Expression Omnibus database. The biological functions of differentially expressed genes were evaluated by gene ontology enrichment and KEGG pathway analysis. The network for intersection genes was constructed by the cytoscape v3.0 software. Kaplan-Meier survival curves and log-rank test were employed to assess the association between differentially expressed genes and clinical characters. The intersection mRNAs were proved to be associated with fundamental processes of T-cell lymphoma cells. These intersection mRNAs were involved in the activation of some cancer-related pathways, including PI3K/AKT, Ras, JAK-STAT, and NF-kappa B signaling pathway. PDGFRA, CXCL12, and CCL19 were the most significant central genes in the signal-net analysis. The results of survival analysis are not entirely credible. Our findings uncovered aberrantly expressed genes and a complex RNA signal network in T-cell lymphomas and indicated cancer-related pathways involved in disease initiation and progression, providing a new insight for biotargeted therapy in T-cell lymphomas. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Contemporary ultrasonic signal processing approaches for nondestructive evaluation of multilayered structures

NASA Astrophysics Data System (ADS)

Zhang, Guang-Ming; Harvey, David M.

2012-03-01

Various signal processing techniques have been used for the enhancement of defect detection and defect characterisation. Cross-correlation, filtering, autoregressive analysis, deconvolution, neural network, wavelet transform and sparse signal representations have all been applied in attempts to analyse ultrasonic signals. In ultrasonic nondestructive evaluation (NDE) applications, a large number of materials have multilayered structures. NDE of multilayered structures leads to some specific problems, such as penetration, echo overlap, high attenuation and low signal-to-noise ratio. The signals recorded from a multilayered structure are a class of very special signals comprised of limited echoes. Such signals can be assumed to have a sparse representation in a proper signal dictionary. Recently, a number of digital signal processing techniques have been developed by exploiting the sparse constraint. This paper presents a review of research to date, showing the up-to-date developments of signal processing techniques made in ultrasonic NDE. A few typical ultrasonic signal processing techniques used for NDE of multilayered structures are elaborated. The practical applications and limitations of different signal processing methods in ultrasonic NDE of multilayered structures are analysed.

Neural Processing of Musical and Vocal Emotions Through Cochlear Implants Simulation.

PubMed

Ahmed, Duha G; Paquette, Sebastian; Zeitouni, Anthony; Lehmann, Alexandre

2018-05-01

Cochlear implants (CIs) partially restore the sense of hearing in the deaf. However, the ability to recognize emotions in speech and music is reduced due to the implant's electrical signal limitations and the patient's altered neural pathways. Electrophysiological correlations of these limitations are not yet well established. Here we aimed to characterize the effect of CIs on auditory emotion processing and, for the first time, directly compare vocal and musical emotion processing through a CI-simulator. We recorded 16 normal hearing participants' electroencephalographic activity while listening to vocal and musical emotional bursts in their original form and in a degraded (CI-simulated) condition. We found prolonged P50 latency and reduced N100-P200 complex amplitude in the CI-simulated condition. This points to a limitation in encoding sound signals processed through CI simulation. When comparing the processing of vocal and musical bursts, we found a delay in latency with the musical bursts compared to the vocal bursts in both conditions (original and CI-simulated). This suggests that despite the cochlear implants' limitations, the auditory cortex can distinguish between vocal and musical stimuli. In addition, it adds to the literature supporting the complexity of musical emotion. Replicating this study with actual CI users might lead to characterizing emotional processing in CI users and could ultimately help develop optimal rehabilitation programs or device processing strategies to improve CI users' quality of life.

Coherent Detection of High-Rate Optical PPM Signals

NASA Technical Reports Server (NTRS)

Vilnrotter, Victor; Fernandez, Michela Munoz

2006-01-01

A method of coherent detection of high-rate pulse-position modulation (PPM) on a received laser beam has been conceived as a means of reducing the deleterious effects of noise and atmospheric turbulence in free-space optical communication using focal-plane detector array technologies. In comparison with a receiver based on direct detection of the intensity modulation of a PPM signal, a receiver based on the present method of coherent detection performs well at much higher background levels. In principle, the coherent-detection receiver can exhibit quantum-limited performance despite atmospheric turbulence. The key components of such a receiver include standard receiver optics, a laser that serves as a local oscillator, a focal-plane array of photodetectors, and a signal-processing and data-acquisition assembly needed to sample the focal-plane fields and reconstruct the pulsed signal prior to detection. The received PPM-modulated laser beam and the local-oscillator beam are focused onto the photodetector array, where they are mixed in the detection process. The two lasers are of the same or nearly the same frequency. If the two lasers are of different frequencies, then the coherent detection process is characterized as heterodyne and, using traditional heterodyne-detection terminology, the difference between the two laser frequencies is denoted the intermediate frequency (IF). If the two laser beams are of the same frequency and remain aligned in phase, then the coherent detection process is characterized as homodyne (essentially, heterodyne detection at zero IF). As a result of the inherent squaring operation of each photodetector, the output current includes an IF component that contains the signal modulation. The amplitude of the IF component is proportional to the product of the local-oscillator signal amplitude and the PPM signal amplitude. Hence, by using a sufficiently strong local-oscillator signal, one can make the PPM-modulated IF signal strong enough to overcome thermal noise in the receiver circuits: this is what makes it possible to achieve near-quantum-limited detection in the presence of strong background. Following quantum-limited coherent detection, the outputs of the individual photodetectors are automatically aligned in phase by use of one or more adaptive array compensation algorithms [e.g., the least-mean-square (LMS) algorithm]. Then the outputs are combined and the resulting signal is processed to extract the high-rate information, as though the PPM signal were received by a single photodetector. In a continuing series of experiments to test this method (see Fig. 1), the local oscillator has a wavelength of 1,064 nm, and another laser is used as a signal transmitter at a slightly different wavelength to establish an IF of about 6 MHz. There are 16 photodetectors in a 4 4 focal-plane array; the detector outputs are digitized at a sampling rate of 25 MHz, and the signals in digital form are combined by use of the LMS algorithm. Convergence of the adaptive combining algorithm in the presence of simulated atmospheric turbulence for optical PPM signals has already been demonstrated in the laboratory; the combined output is shown in Fig. 2(a), and Fig. 2(b) shows the behavior of the phase of the combining weights as a function of time (or samples). We observe that the phase of the weights has a sawtooth shape due to the continuously changing phase in the down-converted output, which is not exactly at zero frequency. Detailed performance analysis of this coherent free-space optical communication system in the presence of simulated atmospheric turbulence is currently under way.

AOD furnace splash soft-sensor in the smelting process based on improved BP neural network

NASA Astrophysics Data System (ADS)

Ma, Haitao; Wang, Shanshan; Wu, Libin; Yu, Ying

2017-11-01

In view of argon oxygen refining low carbon ferrochrome production process, in the splash of smelting process as the research object, based on splash mechanism analysis in the smelting process , using multi-sensor information fusion and BP neural network modeling techniques is proposed in this paper, using the vibration signal, the audio signal and the flame image signal in the furnace as the characteristic signal of splash, the vibration signal, the audio signal and the flame image signal in the furnace integration and modeling, and reconstruct splash signal, realize the splash soft measurement in the smelting process, the simulation results show that the method can accurately forecast splash type in the smelting process, provide a new method of measurement for forecast splash in the smelting process, provide more accurate information to control splash.

Telling good from bad news: ADHD differentially affects processing of positive and negative feedback during guessing.

PubMed

van Meel, Catharina S; Oosterlaan, Jaap; Heslenfeld, Dirk J; Sergeant, Joseph A

2005-01-01

Neuroimaging studies on ADHD suggest abnormalities in brain regions associated with decision-making and reward processing such as the anterior cingulate cortex (ACC) and orbitofrontal cortex. Recently, event-related potential (ERP) studies demonstrated that the ACC is involved in processing feedback signals during guessing and gambling. The resulting negative deflection, the 'feedback-related negativity' (FRN) has been interpreted as reflecting an error in reward prediction. In the present study, ERPs elicited by positive and negative feedback were recorded in children with ADHD and normal controls during guessing. 'Correct' and 'incorrect' guesses resulted in respectively monetary gains and losses. The FRN amplitude to losses was more pronounced in the ADHD group than in normal controls. Positive and negative feedback differentially affected long latency components in the ERP waveforms of normal controls, but not ADHD children. These later deflections might be related to further emotional or strategic processing. The present findings suggest an enhanced sensitivity to unfavourable outcomes in children with ADHD, probably due to abnormalities in mesolimbic reward circuits. In addition, further processing, such as affective evaluation and the assessment of future consequences of the feedback signal seems to be altered in ADHD. These results may further help understanding the neural basis of decision-making deficits in ADHD.

Development of the 10-11 July 2015 two-stage sequence of multiple emplacements of pyroclastic density currents at Volcán de Colima, México: Insight from associated seismic signals

NASA Astrophysics Data System (ADS)

Zobin, Vyacheslav M.

2018-02-01

The 10-11 July 2015 partial collapses of the lava dome in the crater of Volcán de Colima, México, were accompanied by a sequence of two-stage multiple PDCs, separated by a 15-h interval, with a total bulk volume of 14.2 × 106 m3 of fragmentary material and runout distances reaching 9.1 and 10.3 km, respectively (Reyes-Dávila et al., 2016). Broad-band seismic signals, associated with the PDCs and recorded at seismic station EZ5 installed at a distance of 4 km from the crater, were used for analysis of the 20-h eruption process. This process included two stages of the multiple PDCs emplacements, two one-hour periods of preliminary events to each of the stages, and the inter-stage period. Analysis of seismic signals allowed us to identify the types of volcanic events composing this eruption episode and estimate their quantitative characteristics and spectral parameters of generated seismic signals. It was shown that the seismic signals produced by PDCs emplacements, recorded during the two stages, were characterized by different characteristics. The second stage PDCs had radiated greater seismic energy than the PDCs emplaced during the first stage. Spectral analysis of the seismic signals, produced by PDCs, indicates a clearly separation in frequency content at 1.95 Hz between the higher-frequency events of the first stage and the lower-frequency events of the second stage of the PDCs emplacements. The obtained difference in the spectral contents of the seismic signals, produced by the movement of two multiple PDCs, may be supposed as a consequence of the proposed relative difference in the volumes of the PDCs of two multiple sequences due to a difference in the level of radiated seismic energy and a change in bottom conditions of the ravines during their passing along the ravines. Results of seismic study were used in discussion of the nature of the two-stage eruptive process.

GNSS software receiver sampling noise and clock jitter performance and impact analysis

NASA Astrophysics Data System (ADS)

Chen, Jian Yun; Feng, XuZhe; Li, XianBin; Wu, GuangYao

2015-02-01

In the design of a multi-frequency multi-constellation GNSS software defined radio receivers is becoming more and more popular due to its simple architecture, flexible configuration and good coherence in multi-frequency signal processing. It plays an important role in navigation signal processing and signal quality monitoring. In particular, GNSS software defined radio receivers driving the sampling clock of analogue-to-digital converter (ADC) by FPGA implies that a more flexible radio transceiver design is possible. According to the concept of software defined radio (SDR), the ideal is to digitize as close to the antenna as possible. Whereas the carrier frequency of GNSS signal is of the frequency of GHz, converting at this frequency is expensive and consumes more power. Band sampling method is a cheaper, more effective alternative. When using band sampling method, it is possible to sample a RF signal at twice the bandwidth of the signal. Unfortunately, as the other side of the coin, the introduction of SDR concept and band sampling method induce negative influence on the performance of the GNSS receivers. ADC's suffer larger sampling clock jitter generated by FPGA; and low sampling frequency introduces more noise to the receiver. Then the influence of sampling noise cannot be neglected. The paper analyzes the sampling noise, presents its influence on the carrier noise ratio, and derives the ranging error by calculating the synchronization error of the delay locked loop. Simulations aiming at each impact factors of sampling-noise-induced ranging error are performed. Simulation and experiment results show that if the target ranging accuracy is at the level of centimeter, the quantization length should be no less than 8 and the sampling clock jitter should not exceed 30ps.

Fiber-distributed Ultra-wideband noise radar with steerable power spectrum and colorless base station.

PubMed

Zheng, Jianyu; Wang, Hui; Fu, Jianbin; Wei, Li; Pan, Shilong; Wang, Lixian; Liu, Jianguo; Zhu, Ninghua

2014-03-10

A fiber-distributed Ultra-wideband (UWB) noise radar was achieved, which consists of a chaotic UWB noise source based on optoelectronic oscillator (OEO), a fiber-distributed transmission link, a colorless base station (BS), and a cross-correlation processing module. Due to a polarization modulation based microwave photonic filter and an electrical UWB pass-band filter embedded in the feedback loop of the OEO, the power spectrum of chaotic UWB signal could be shaped and notch-filtered to avoid the spectrum-overlay-induced interference to the narrow band signals. Meanwhile, the wavelength-reusing could be implemented in the BS by means of the distributed polarization modulation-to-intensity modulation conversion. The experimental comparison for range finding was carried out as the chaotic UWB signal was notch-filtered at 5.2 GHz and 7.8 GHz or not. Measured results indicate that space resolution with cm-level could be realized after 3-km fiber transmission thanks to the excellent self-correlation property of the UWB noise signal provided by the OEO. The performance deterioration of the radar raised by the energy loss of the notch-filtered noise signal was negligible.

Tacholess order-tracking approach for wind turbine gearbox fault detection

NASA Astrophysics Data System (ADS)

Wang, Yi; Xie, Yong; Xu, Guanghua; Zhang, Sicong; Hou, Chenggang

2017-09-01

Monitoring of wind turbines under variable-speed operating conditions has become an important issue in recent years. The gearbox of a wind turbine is the most important transmission unit; it generally exhibits complex vibration signatures due to random variations in operating conditions. Spectral analysis is one of the main approaches in vibration signal processing. However, spectral analysis is based on a stationary assumption and thus inapplicable to the fault diagnosis of wind turbines under variable-speed operating conditions. This constraint limits the application of spectral analysis to wind turbine diagnosis in industrial applications. Although order-tracking methods have been proposed for wind turbine fault detection in recent years, current methods are only applicable to cases in which the instantaneous shaft phase is available. For wind turbines with limited structural spaces, collecting phase signals with tachometers or encoders is difficult. In this study, a tacholess order-tracking method for wind turbines is proposed to overcome the limitations of traditional techniques. The proposed method extracts the instantaneous phase from the vibration signal, resamples the signal at equiangular increments, and calculates the order spectrum for wind turbine fault identification. The effectiveness of the proposed method is experimentally validated with the vibration signals of wind turbines.

Species-specific beaked whale echolocation signals.

PubMed

Baumann-Pickering, Simone; McDonald, Mark A; Simonis, Anne E; Solsona Berga, Alba; Merkens, Karlina P B; Oleson, Erin M; Roch, Marie A; Wiggins, Sean M; Rankin, Shannon; Yack, Tina M; Hildebrand, John A

2013-09-01

Beaked whale echolocation signals are mostly frequency-modulated (FM) upsweep pulses and appear to be species specific. Evolutionary processes of niche separation may have driven differentiation of beaked whale signals used for spatial orientation and foraging. FM pulses of eight species of beaked whales were identified, as well as five distinct pulse types of unknown species, but presumed to be from beaked whales. Current evidence suggests these five distinct but unidentified FM pulse types are also species-specific and are each produced by a separate species. There may be a relationship between adult body length and center frequency with smaller whales producing higher frequency signals. This could be due to anatomical and physiological restraints or it could be an evolutionary adaption for detection of smaller prey for smaller whales with higher resolution using higher frequencies. The disadvantage of higher frequencies is a shorter detection range. Whales echolocating with the highest frequencies, or broadband, likely lower source level signals also use a higher repetition rate, which might compensate for the shorter detection range. Habitat modeling with acoustic detections should give further insights into how niches and prey may have shaped species-specific FM pulse types.

Models of crk adaptor proteins in cancer.

PubMed

Bell, Emily S; Park, Morag

2012-05-01

The Crk family of adaptor proteins (CrkI, CrkII, and CrkL), originally discovered as the oncogene fusion product, v-Crk, of the CT10 chicken retrovirus, lacks catalytic activity but engages with multiple signaling pathways through their SH2 and SH3 domains. Crk proteins link upstream tyrosine kinase and integrin-dependent signals to downstream effectors, acting as adaptors in diverse signaling pathways and cellular processes. Crk proteins are now recognized to play a role in the malignancy of many human cancers, stimulating renewed interest in their mechanism of action in cancer progression. The contribution of Crk signaling to malignancy has been predominantly studied in fibroblasts and in hematopoietic models and more recently in epithelial models. A mechanistic understanding of Crk proteins in cancer progression in vivo is still poorly understood in part due to the highly pleiotropic nature of Crk signaling. Recent advances in the structural organization of Crk domains, new roles in kinase regulation, and increased knowledge of the mechanisms and frequency of Crk overexpression in human cancers have provided an incentive for further study in in vivo models. An understanding of the mechanisms through which Crk proteins act as oncogenic drivers could have important implications in therapeutic targeting.

Application of time-reversal guided waves to field bridge testing for baseline-free damage diagnosis

NASA Astrophysics Data System (ADS)

Kim, S. B.; Sohn, H.

2006-03-01

There is ongoing research at Carnegie Mellon University to develop a "baseline-free" nondestructive evaluation technique. The uniqueness of this baseline-free diagnosis lies in that certain types of damage can be identified without direct comparison of test signals with previously stored baseline signals. By relaxing dependency on the past baseline data, false positive indications of damage, which might take place due to varying operational and environmental conditions of in-service structures, can be minimized. This baseline-free diagnosis technique is developed based on the concept of a time reversal process (TRP). According to the TRP, an input signal at an original excitation location can be reconstructed if a response signal obtained from another point is emitted back to the original point after being reversed in a time domain. Damage diagnosis lies in the premise that the time reversibility breaks down when a certain type of defect such as nonlinear damage exists along the wave propagation path. Then, the defect can be sensed by examining a reconstructed signal after the TRP. In this paper, the feasibility of the proposed NDT technique is investigated using actual test data obtained from the Buffalo Creek Bridge in Pennsylvania.

Chemical activation of Wnt/β-catenin signalling inhibits innervation and causes skeletal tissue malformations during axolotl limb regeneration.

PubMed

Wischin, Sabina; Castañeda-Patlán, Cristina; Robles-Flores, Martha; Chimal-Monroy, Jesús

2017-04-01

Limb regeneration involves several interrelated physiological processes in which a particular signalling pathway may play a variety of functions. Blocking the function of Wnt/β-catenin signalling during limb regeneration inhibits regeneration in axolotls (Ambystoma mexicanum). Limb development shares many features with limb regeneration, and Wnt/β-catenin activation has different effects depending on the developmental stage. The aim of this study was to evaluate whether Wnt/β-catenin signalling activation during axolotl limb regeneration has different effects when activated at different stages of regeneration. To evaluate this hypothesis, we treated amputated axolotls with a Wnt agonist chemical at different stages of limb regeneration. The results showed that limb regeneration was inhibited when the treatment began before blastema formation. Under these conditions, blastema formation was hindered, possibly due to the lack of innervation. On the other hand, when axolotls were treated after blastema formation and immediately before the onset of morphogenesis, we observed structural disorganization in skeletal formation. In conclusion, we found that limb regeneration was differentially affected depending on the stage at which the Wnt signalling pathway was activated. Copyright © 2017 Elsevier B.V. All rights reserved.

The Ceramide Transporter CERT is Involved in Muscle Insulin Signaling Defects Under Lipotoxic Conditions.

PubMed

Bandet, Cécile L; Mahfouz, Rana; Véret, Julien; Sotiropoulos, Athanassia; Poirier, Maxime; Giussani, Paola; Campana, Mélanie; Philippe, Erwann; Blachnio-Zabielska, Agnieszka; Ballaire, Raphaëlle; Le Liepvre, Xavier; Bourron, Olivier; Berkeš, Dušan; Górski, Jan; Ferré, Pascal; Le Stunff, Hervé; Foufelle, Fabienne; Hajduch, Eric

2018-05-14

One main mechanism of insulin resistance (IR), a key feature of type-2 diabetes, is the accumulation of saturated fatty acids (FA) in muscles of obese and type-2 diabetic patients. Understanding the mechanism underlying lipid-induced IR is therefore a crucial challenge. Saturated FA are metabolized into lipid-derivatives called ceramides and their accumulation plays a central role in the development of muscle IR. Ceramides are produced in the endoplasmic reticulum (ER) and transported to the Golgi through a transporter called CERT, where they are converted into different sphingolipid species. We show here that CERT protein expression is reduced in all insulin resistance models studied due to a caspase-dependent cleavage. Inhibiting CERT activity in vitro potentiates the deleterious action of lipotoxicity on insulin signaling whereas overexpression of CERT in vitro or in vivo increases muscle ceramide content and improves insulin signaling. In addition, inhibition of caspase activity prevents ceramide-induced insulin signaling defects in C2C12 muscle cells. Altogether, these results demonstrate the importance of a physiological ER to Golgi ceramide traffic to preserve muscle cell insulin signaling and identifies CERT as a major actor in this process. © 2018 by the American Diabetes Association.