Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance

PubMed Central

Poplová, Michaela; Sovka, Pavel

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal. PMID:29216207

SPF45-related SPLICING FACTOR FOR PHYTOCHROME SIGNALING promotes photomorphogensis by regulating pre-mRNA splicing in arabidopsis

USDA-ARS?s Scientific Manuscript database

Light signals regulate plant growth and development by controlling a plethora of gene expression changes. Post-transcriptional regulation, especially pre-mRNA processing, is a key modulator of gene expression; however, the molecular mechanisms linking pre-mRNA processing and light signaling are not ...

Communication system with adaptive noise suppression

NASA Technical Reports Server (NTRS)

Kozel, David (Inventor); Devault, James A. (Inventor); Birr, Richard B. (Inventor)

2007-01-01

A signal-to-noise ratio dependent adaptive spectral subtraction process eliminates noise from noise-corrupted speech signals. The process first pre-emphasizes the frequency components of the input sound signal which contain the consonant information in human speech. Next, a signal-to-noise ratio is determined and a spectral subtraction proportion adjusted appropriately. After spectral subtraction, low amplitude signals can be squelched. A single microphone is used to obtain both the noise-corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoiced frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Spectral subtraction may be performed on a composite noise-corrupted signal, or upon individual sub-bands of the noise-corrupted signal. Pre-averaging of the input signal's magnitude spectrum over multiple time frames may be performed to reduce musical noise.

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

Lentine, Anthony L.; Cox, Jonathan Albert

Methods and systems for stabilizing a resonant modulator include receiving pre-modulation and post-modulation portions of a carrier signal, determining the average power from these portions, comparing an average input power to the average output power, and operating a heater coupled to the modulator based on the comparison. One system includes a pair of input structures, one or more processing elements, a comparator, and a control element. The input structures are configured to extract pre-modulation and post-modulation portions of a carrier signal. The processing elements are configured to determine average powers from the extracted portions. The comparator is configured to comparemore » the average input power and the average output power. The control element operates a heater coupled to the modulator based on the comparison.« less

Directional dual-tree rational-dilation complex wavelet transform.

PubMed

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

2014-01-01

Dyadic discrete wavelet transform (DWT) has been used successfully in processing signals having non-oscillatory transient behaviour. However, due to the low Q-factor property of their wavelet atoms, the dyadic DWT is less effective in processing oscillatory signals such as embolic signals (ESs). ESs are extracted from quadrature Doppler signals, which are the output of Doppler ultrasound systems. In order to process ESs, firstly, a pre-processing operation known as phase filtering for obtaining directional signals from quadrature Doppler signals must be employed. Only then, wavelet based methods can be applied to these directional signals for further analysis. In this study, a directional dual-tree rational-dilation complex wavelet transform, which can be applied directly to quadrature signals and has the ability of extracting directional information during analysis, is introduced.

Effects of pre-experimental knowledge on recognition memory.

PubMed

Bird, Chris M; Davies, Rachel A; Ward, Jamie; Burgess, Neil

2011-01-01

The influence of pre-experimental autobiographical knowledge on recognition memory was investigated using as memoranda faces that were either personally known or unknown to the participant. Under a dual process theory, such knowledge boosted both recollection- and familiarity-based recognition judgements. Under an unequal variance signal detection model, pre-experimental knowledge increased both the variance and the separation of the target and foil memory strength distributions, boosting hits and correct rejections. Thus, pre-experimental knowledge has profound effects on the multiple, interacting processes that subserve recognition memory, and likely in the neural systems that underpin them.

High frequency signal acquisition and control system based on DSP+FPGA

NASA Astrophysics Data System (ADS)

Liu, Xiao-qi; Zhang, Da-zhi; Yin, Ya-dong

2017-10-01

This paper introduces a design and implementation of high frequency signal acquisition and control system based on DSP + FPGA. The system supports internal/external clock and internal/external trigger sampling. It has a maximum sampling rate of 400MBPS and has a 1.4GHz input bandwidth for the ADC. Data can be collected continuously or periodically in systems and they are stored in DDR2. At the same time, the system also supports real-time acquisition, the collected data after digital frequency conversion and Cascaded Integrator-Comb (CIC) filtering, which then be sent to the CPCI bus through the high-speed DSP, can be assigned to the fiber board for subsequent processing. The system integrates signal acquisition and pre-processing functions, which uses high-speed A/D, high-speed DSP and FPGA mixed technology and has a wide range of uses in data acquisition and recording. In the signal processing, the system can be seamlessly connected to the dedicated processor board. The system has the advantages of multi-selectivity, good scalability and so on, which satisfies the different requirements of different signals in different projects.

Detecting the tipping points in a three-state model of complex diseases by temporal differential networks.

PubMed

Chen, Pei; Li, Yongjun; Liu, Xiaoping; Liu, Rui; Chen, Luonan

2017-10-26

The progression of complex diseases, such as diabetes and cancer, is generally a nonlinear process with three stages, i.e., normal state, pre-disease state, and disease state, where the pre-disease state is a critical state or tipping point immediately preceding the disease state. Traditional biomarkers aim to identify a disease state by exploiting the information of differential expressions for the observed molecules, but may fail to detect a pre-disease state because there are generally little significant differences between the normal and pre-disease states. Thus, it is challenging to signal the pre-disease state, which actually implies the disease prediction. In this work, by exploiting the information of differential associations among the observed molecules between the normal and pre-disease states, we propose a temporal differential network based computational method to accurately signal the pre-disease state or predict the occurrence of severe disease. The theoretical foundation of this work is the quantification of the critical state using dynamical network biomarkers. Considering that there is one stationary Markov process before reaching the tipping point, a novel index, inconsistency score (I-score), is proposed to quantitatively measure the change of the stationary processes from the normal state so as to detect the onset of pre-disease state. In other words, a drastic increase of I-score implies the high inconsistency with the preceding stable state and thus signals the upcoming critical transition. This approach is applied to the simulated and real datasets of three diseases, which demonstrates the effectiveness of our method for predicting the deterioration into disease states. Both functional analysis and pathway enrichment also validate the computational results from the perspectives of both molecules and networks. At the molecular network level, this method provides a computational way of unravelling the underlying mechanism of the dynamical progression when a biological system is near the tipping point, and thus detecting the early-warning signal of the imminent critical transition, which may help to achieve timely intervention. Moreover, the rewiring of differential networks effectively extracts discriminatively interpretable features, and systematically demonstrates the dynamical change of a biological system.

A novel time-domain signal processing algorithm for real time ventricular fibrillation detection

NASA Astrophysics Data System (ADS)

Monte, G. E.; Scarone, N. C.; Liscovsky, P. O.; Rotter S/N, P.

2011-12-01

This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies.

49 CFR 234.261 - Highway traffic signal pre-emption.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 4 2013-10-01 2013-10-01 false Highway traffic signal pre-emption. 234.261..., AND EMERGENCY NOTIFICATION SYSTEMS Maintenance, Inspection, and Testing Inspections and Tests § 234.261 Highway traffic signal pre-emption. Highway traffic signal pre-emption interconnections, for which...

49 CFR 234.261 - Highway traffic signal pre-emption.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false Highway traffic signal pre-emption. 234.261..., AND EMERGENCY NOTIFICATION SYSTEMS Maintenance, Inspection, and Testing Inspections and Tests § 234.261 Highway traffic signal pre-emption. Highway traffic signal pre-emption interconnections, for which...

49 CFR 234.261 - Highway traffic signal pre-emption.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 4 2012-10-01 2012-10-01 false Highway traffic signal pre-emption. 234.261..., AND EMERGENCY NOTIFICATION SYSTEMS Maintenance, Inspection, and Testing Inspections and Tests § 234.261 Highway traffic signal pre-emption. Highway traffic signal pre-emption interconnections, for which...

A real time mobile-based face recognition with fisherface methods

NASA Astrophysics Data System (ADS)

Arisandi, D.; Syahputra, M. F.; Putri, I. L.; Purnamawati, S.; Rahmat, R. F.; Sari, P. P.

2018-03-01

Face Recognition is a field research in Computer Vision that study about learning face and determine the identity of the face from a picture sent to the system. By utilizing this face recognition technology, learning process about people’s identity between students in a university will become simpler. With this technology, student won’t need to browse student directory in university’s server site and look for the person with certain face trait. To obtain this goal, face recognition application use image processing methods consist of two phase, pre-processing phase and recognition phase. In pre-processing phase, system will process input image into the best image for recognition phase. Purpose of this pre-processing phase is to reduce noise and increase signal in image. Next, to recognize face phase, we use Fisherface Methods. This methods is chosen because of its advantage that would help system of its limited data. Therefore from experiment the accuracy of face recognition using fisherface is 90%.

[Application of the mixed programming with Labview and Matlab in biomedical signal analysis].

PubMed

Yu, Lu; Zhang, Yongde; Sha, Xianzheng

2011-01-01

This paper introduces the method of mixed programming with Labview and Matlab, and applies this method in a pulse wave pre-processing and feature detecting system. The method has been proved suitable, efficient and accurate, which has provided a new kind of approach for biomedical signal analysis.

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.

Extraction of fetal ECG signal by an improved method using extended Kalman smoother framework from single channel abdominal ECG signal.

PubMed

Panigrahy, D; Sahu, P K

2017-03-01

This paper proposes a five-stage based methodology to extract the fetal electrocardiogram (FECG) from the single channel abdominal ECG using differential evolution (DE) algorithm, extended Kalman smoother (EKS) and adaptive neuro fuzzy inference system (ANFIS) framework. The heart rate of the fetus can easily be detected after estimation of the fetal ECG signal. The abdominal ECG signal contains fetal ECG signal, maternal ECG component, and noise. To estimate the fetal ECG signal from the abdominal ECG signal, removal of the noise and the maternal ECG component presented in it is necessary. The pre-processing stage is used to remove the noise from the abdominal ECG signal. The EKS framework is used to estimate the maternal ECG signal from the abdominal ECG signal. The optimized parameters of the maternal ECG components are required to develop the state and measurement equation of the EKS framework. These optimized maternal ECG parameters are selected by the differential evolution algorithm. The relationship between the maternal ECG signal and the available maternal ECG component in the abdominal ECG signal is nonlinear. To estimate the actual maternal ECG component present in the abdominal ECG signal and also to recognize this nonlinear relationship the ANFIS is used. Inputs to the ANFIS framework are the output of EKS and the pre-processed abdominal ECG signal. The fetal ECG signal is computed by subtracting the output of ANFIS from the pre-processed abdominal ECG signal. Non-invasive fetal ECG database and set A of 2013 physionet/computing in cardiology challenge database (PCDB) are used for validation of the proposed methodology. The proposed methodology shows a sensitivity of 94.21%, accuracy of 90.66%, and positive predictive value of 96.05% from the non-invasive fetal ECG database. The proposed methodology also shows a sensitivity of 91.47%, accuracy of 84.89%, and positive predictive value of 92.18% from the set A of PCDB.

Optimization of the Design of Pre-Signal System Using Improved Cellular Automaton

PubMed Central

Li, Yan; Li, Ke; Tao, Siran; Chen, Kuanmin

2014-01-01

The pre-signal system can improve the efficiency of intersection approach under rational design. One of the main obstacles in optimizing the design of pre-signal system is that driving behaviors in the sorting area cannot be well evaluated. The NaSch model was modified by considering slow probability, turning-deceleration rules, and lane changing rules. It was calibrated with field observed data to explore the interactions among design parameters. The simulation results of the proposed model indicate that the length of sorting area, traffic demand, signal timing, and lane allocation are the most important influence factors. The recommendations of these design parameters are demonstrated. The findings of this paper can be foundations for the design of pre-signal system and show promising improvement in traffic mobility. PMID:25435871

Identification and human condition analysis based on the human voice analysis

NASA Astrophysics Data System (ADS)

Mieshkov, Oleksandr Yu.; Novikov, Oleksandr O.; Novikov, Vsevolod O.; Fainzilberg, Leonid S.; Kotyra, Andrzej; Smailova, Saule; Kozbekova, Ainur; Imanbek, Baglan

2017-08-01

The paper presents a two-stage biotechnical system for human condition analysis that is based on analysis of human voice signal. At the initial stage, the voice signal is pre-processed and its characteristics in time domain are determined. At the first stage, the developed system is capable of identifying the person in the database on the basis of the extracted characteristics. At the second stage, the model of a human voice is built on the basis of the real voice signals after clustering the whole database.

A peptide export-import control circuit modulating bacterial development regulates protein phosphatases of the phosphorelay.

PubMed

Perego, M

1997-08-05

The phosphorelay signal transduction system activates developmental transcription in sporulation of Bacillus subtilis by phosphorylation of aspartyl residues of the Spo0F and Spo0A response regulators. The phosphorylation level of these response regulators is determined by the opposing activities of protein kinases and protein aspartate phosphatases that interpret positive and negative signals for development in a signal integration circuit. The RapA protein aspartate phosphatase of the phosphorelay is regulated by a peptide that directly inhibits its activity. This peptide is proteolytically processed from an inactive pre-inhibitor protein encoded in the phrA gene. The pre-inhibitor is cleaved by the protein export apparatus to a putative pro-inhibitor that is further processed to the active inhibitor peptide and internalized by the oligopeptide permease. This export-import circuit is postulated to be a mechanism for timing phosphatase activity where the processing enzymes regulate the rate of formation of the active inhibitor. The processing events may, in turn, be controlled by a regulatory hierarchy. Chromosome sequencing has revealed several other phosphatase-prepeptide gene pairs in B. subtilis, suggesting that the use of this mechanism may be widespread in signal transduction.

A peptide export–import control circuit modulating bacterial development regulates protein phosphatases of the phosphorelay

PubMed Central

Perego, Marta

1997-01-01

The phosphorelay signal transduction system activates developmental transcription in sporulation of Bacillus subtilis by phosphorylation of aspartyl residues of the Spo0F and Spo0A response regulators. The phosphorylation level of these response regulators is determined by the opposing activities of protein kinases and protein aspartate phosphatases that interpret positive and negative signals for development in a signal integration circuit. The RapA protein aspartate phosphatase of the phosphorelay is regulated by a peptide that directly inhibits its activity. This peptide is proteolytically processed from an inactive pre-inhibitor protein encoded in the phrA gene. The pre-inhibitor is cleaved by the protein export apparatus to a putative pro-inhibitor that is further processed to the active inhibitor peptide and internalized by the oligopeptide permease. This export–import circuit is postulated to be a mechanism for timing phosphatase activity where the processing enzymes regulate the rate of formation of the active inhibitor. The processing events may, in turn, be controlled by a regulatory hierarchy. Chromosome sequencing has revealed several other phosphatase–prepeptide gene pairs in B. subtilis, suggesting that the use of this mechanism may be widespread in signal transduction. PMID:9238025

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.

The ATLAS Level-1 Calorimeter Trigger: PreProcessor implementation and performance

NASA Astrophysics Data System (ADS)

Åsman, B.; Achenbach, R.; Allbrooke, B. M. M.; Anders, G.; Andrei, V.; Büscher, V.; Bansil, H. S.; Barnett, B. M.; Bauss, B.; Bendtz, K.; Bohm, C.; Bracinik, J.; Brawn, I. P.; Brock, R.; Buttinger, W.; Caputo, R.; Caughron, S.; Cerrito, L.; Charlton, D. G.; Childers, J. T.; Curtis, C. J.; Daniells, A. C.; Davis, A. O.; Davygora, Y.; Dorn, M.; Eckweiler, S.; Edmunds, D.; Edwards, J. P.; Eisenhandler, E.; Ellis, K.; Ermoline, Y.; Föhlisch, F.; Faulkner, P. J. W.; Fedorko, W.; Fleckner, J.; French, S. T.; Gee, C. N. P.; Gillman, A. R.; Goeringer, C.; Hülsing, T.; Hadley, D. R.; Hanke, P.; Hauser, R.; Heim, S.; Hellman, S.; Hickling, R. S.; Hidvégi, A.; Hillier, S. J.; Hofmann, J. I.; Hristova, I.; Ji, W.; Johansen, M.; Keller, M.; Khomich, A.; Kluge, E.-E.; Koll, J.; Laier, H.; Landon, M. P. J.; Lang, V. S.; Laurens, P.; Lepold, F.; Lilley, J. N.; Linnemann, J. T.; Müller, F.; Müller, T.; Mahboubi, K.; Martin, T. A.; Mass, A.; Meier, K.; Meyer, C.; Middleton, R. P.; Moa, T.; Moritz, S.; Morris, J. D.; Mudd, R. D.; Narayan, R.; zur Nedden, M.; Neusiedl, A.; Newman, P. R.; Nikiforov, A.; Ohm, C. C.; Perera, V. J. O.; Pfeiffer, U.; Plucinski, P.; Poddar, S.; Prieur, D. P. F.; Qian, W.; Rieck, P.; Rizvi, E.; Sankey, D. P. C.; Schäfer, U.; Scharf, V.; Schmitt, K.; Schröder, C.; Schultz-Coulon, H.-C.; Schumacher, C.; Schwienhorst, R.; Silverstein, S. B.; Simioni, E.; Snidero, G.; Staley, R. J.; Stamen, R.; Stock, P.; Stockton, M. C.; Tan, C. L. A.; Tapprogge, S.; Thomas, J. P.; Thompson, P. D.; Thomson, M.; True, P.; Watkins, P. M.; Watson, A. T.; Watson, M. F.; Weber, P.; Wessels, M.; Wiglesworth, C.; Williams, S. L.

2012-12-01

The PreProcessor system of the ATLAS Level-1 Calorimeter Trigger (L1Calo) receives about 7200 analogue signals from the electromagnetic and hadronic components of the calorimetric detector system. Lateral division results in cells which are pre-summed to so-called Trigger Towers of size 0.1 × 0.1 along azimuth (phi) and pseudorapidity (η). The received calorimeter signals represent deposits of transverse energy. The system consists of 124 individual PreProcessor modules that digitise the input signals for each LHC collision, and provide energy and timing information to the digital processors of the L1Calo system, which identify physics objects forming much of the basis for the full ATLAS first level trigger decision. This paper describes the architecture of the PreProcessor, its hardware realisation, functionality, and performance.

The design and implementation of signal decomposition system of CL multi-wavelet transform based on DSP builder

NASA Astrophysics Data System (ADS)

Huang, Yan; Wang, Zhihui

2015-12-01

With the development of FPGA, DSP Builder is widely applied to design system-level algorithms. The algorithm of CL multi-wavelet is more advanced and effective than scalar wavelets in processing signal decomposition. Thus, a system of CL multi-wavelet based on DSP Builder is designed for the first time in this paper. The system mainly contains three parts: a pre-filtering subsystem, a one-level decomposition subsystem and a two-level decomposition subsystem. It can be converted into hardware language VHDL by the Signal Complier block that can be used in Quartus II. After analyzing the energy indicator, it shows that this system outperforms Daubenchies wavelet in signal decomposition. Furthermore, it has proved to be suitable for the implementation of signal fusion based on SoPC hardware, and it will become a solid foundation in this new field.

Development of multichannel analyzer using sound card ADC for nuclear spectroscopy system

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

Ibrahim, Maslina Mohd; Yussup, Nolida; Lombigit, Lojius

This paper describes the development of Multi-Channel Analyzer (MCA) using sound card analogue to digital converter (ADC) for nuclear spectroscopy system. The system was divided into a hardware module and a software module. Hardware module consist of detector NaI (Tl) 2” by 2”, Pulse Shaping Amplifier (PSA) and a build in ADC chip from readily available in any computers’ sound system. The software module is divided into two parts which are a pre-processing of raw digital input and the development of the MCA software. Band-pass filter and baseline stabilization and correction were implemented for the pre-processing. For the MCA development,more » the pulse height analysis method was used to process the signal before displaying it using histogram technique. The development and tested result for using the sound card as an MCA are discussed.« less

Sensor, signal, and image informatics - state of the art and current topics.

PubMed

Lehmann, T M; Aach, T; Witte, H

2006-01-01

The number of articles published annually in the fields of biomedical signal and image acquisition and processing is increasing. Based on selected examples, this survey aims at comprehensively demonstrating the recent trends and developments. Four articles are selected for biomedical data acquisition covering topics such as dose saving in CT, C-arm X-ray imaging systems for volume imaging, and the replacement of dose-intensive CT-based diagnostic with harmonic ultrasound imaging. Regarding biomedical signal analysis (BSA), the four selected articles discuss the equivalence of different time-frequency approaches for signal analysis, an application to Cochlea implants, where time-frequency analysis is applied for controlling the replacement system, recent trends for fusion of different modalities, and the role of BSA as part of a brain machine interfaces. To cover the broad spectrum of publications in the field of biomedical image processing, six papers are focused. Important topics are content-based image retrieval in medical applications, automatic classification of tongue photographs from traditional Chinese medicine, brain perfusion analysis in single photon emission computed tomography (SPECT), model-based visualization of vascular trees, and virtual surgery, where enhanced visualization and haptic feedback techniques are combined with a sphere-filled model of the organ. The selected papers emphasize the five fields forming the chain of biomedical data processing: (1) data acquisition, (2) data reconstruction and pre-processing, (3) data handling, (4) data analysis, and (5) data visualization. Fields 1 and 2 form the sensor informatics, while fields 2 to 5 form signal or image informatics with respect to the nature of the data considered. Biomedical data acquisition and pre-processing, as well as data handling, analysis and visualization aims at providing reliable tools for decision support that improve the quality of health care. Comprehensive evaluation of the processing methods and their reliable integration in routine applications are future challenges in the field of sensor, signal and image informatics.

lop-DWI: A Novel Scheme for Pre-Processing of Diffusion-Weighted Images in the Gradient Direction Domain.

PubMed

Sepehrband, Farshid; Choupan, Jeiran; Caruyer, Emmanuel; Kurniawan, Nyoman D; Gal, Yaniv; Tieng, Quang M; McMahon, Katie L; Vegh, Viktor; Reutens, David C; Yang, Zhengyi

2014-01-01

We describe and evaluate a pre-processing method based on a periodic spiral sampling of diffusion-gradient directions for high angular resolution diffusion magnetic resonance imaging. Our pre-processing method incorporates prior knowledge about the acquired diffusion-weighted signal, facilitating noise reduction. Periodic spiral sampling of gradient direction encodings results in an acquired signal in each voxel that is pseudo-periodic with characteristics that allow separation of low-frequency signal from high frequency noise. Consequently, it enhances local reconstruction of the orientation distribution function used to define fiber tracks in the brain. Denoising with periodic spiral sampling was tested using synthetic data and in vivo human brain images. The level of improvement in signal-to-noise ratio and in the accuracy of local reconstruction of fiber tracks was significantly improved using our method.

Non-parallel coevolution of sender and receiver in the acoustic communication system of treefrogs.

PubMed

Schul, Johannes; Bush, Sarah L

2002-09-07

Advertisement calls of closely related species often differ in quantitative features such as the repetition rate of signal units. These differences are important in species recognition. Current models of signal-receiver coevolution predict two possible patterns in the evolution of the mechanism used by receivers to recognize the call: (i) classical sexual selection models (Fisher process, good genes/indirect benefits, direct benefits models) predict that close relatives use qualitatively similar signal recognition mechanisms tuned to different values of a call parameter; and (ii) receiver bias models (hidden preference, pre-existing bias models) predict that if different signal recognition mechanisms are used by sibling species, evidence of an ancestral mechanism will persist in the derived species, and evidence of a pre-existing bias will be detectable in the ancestral species. We describe qualitatively different call recognition mechanisms in sibling species of treefrogs. Whereas Hyla chrysoscelis uses pulse rate to recognize male calls, Hyla versicolor uses absolute measurements of pulse duration and interval duration. We found no evidence of either hidden preferences or pre-existing biases. The results are compared with similar data from katydids (Tettigonia sp.). In both taxa, the data are not adequately explained by current models of signal-receiver coevolution.

A survey on signals and systems in ambulatory blood pressure monitoring using pulse transit time.

PubMed

Buxi, Dilpreet; Redouté, Jean-Michel; Yuce, Mehmet Rasit

2015-03-01

Blood pressure monitoring based on pulse transit or arrival time has been the focus of much research in order to design ambulatory blood pressure monitors. The accuracy of these monitors is limited by several challenges, such as acquisition and processing of physiological signals as well as changes in vascular tone and the pre-ejection period. In this work, a literature survey covering recent developments is presented in order to identify gaps in the literature. The findings of the literature are classified according to three aspects. These are the calibration of pulse transit/arrival times to blood pressure, acquisition and processing of physiological signals and finally, the design of fully integrated blood pressure measurement systems. Alternative technologies as well as locations for the measurement of the pulse wave signal should be investigated in order to improve the accuracy during calibration. Furthermore, the integration and validation of monitoring systems needs to be improved in current ambulatory blood pressure monitors.

Advances in the pathophysiology of pre-eclampsia and related podocyte injury

PubMed Central

Craici, Iasmina M.; Wagner, Steven J.; Weissgerber, Tracey L.; Grande, Joseph P.; Garovic, Vesna D.

2014-01-01

Pre-eclampsia is a pregnancy-specific hypertensive disorder that may lead to serious maternal and fetal complications. It is a multisystem disease that is commonly, but not always, accompanied by proteinuria. Its cause(s) remain unknown, and delivery remains the only definitive treatment. It is increasingly recognized that many pathophysiological processes contribute to this syndrome, with different signaling pathways converging at the point of systemic endothelial dysfunction, hypertension, and proteinuria. Different animal models of pre-eclampsia have proven utility for specific aspects of pre-eclampsia research, and offer insights into pathophysiology and treatment possibilities. Therapeutic interventions that specifically target these pathways may optimize pre-eclampsia management and may improve fetal and maternal outcomes. In addition, recent findings regarding placental, endothelial, and podocyte pathophysiology in pre-eclampsia provide unique and exciting possibilities for improved diagnostic accuracy. Emerging evidence suggests that testing for urinary podocytes or their markers may facilitate the prediction and diagnosis of pre-eclampsia. In this review, we explore recent research regarding placental, endothelial, and podocyte pathophysiology. We further discuss new signaling and genetic pathways that may contribute to pre-eclampsia pathophysiology, emerging screening and diagnostic strategies, and potential targeted interventions. PMID:24573315

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.

Improvement on vibration measurement performance of laser self-mixing interference by using a pre-feedback mirror

NASA Astrophysics Data System (ADS)

Zhu, Wei; Chen, Qianghua; Wang, Yanghong; Luo, Huifu; Wu, Huan; Ma, Binwu

2018-06-01

In the laser self-mixing interference vibration measurement system, the self mixing interference signal is usually weak so that it can be hardly distinguished from the environmental noise. In order to solve this problem, we present a self-mixing interference optical path with a pre-feedback mirror, a pre-feedback mirror is added between the object and the collimator lens, corresponding feedback light enters into the inner cavity of the laser and the interference by the pre-feedback mirror occurs. The pre-feedback system is established after that. The self-mixing interference theoretical model with a pre-feedback based on the F-P model is derived. The theoretical analysis shows that the amplitude of the intensity of the interference signal can be improved by 2-4 times. The influence factors of system are also discussed. The experiment results show that the amplitude of the signal is greatly improved, which agrees with the theoretical analysis.

WAMS measurements pre-processing for detecting low-frequency oscillations in power systems

NASA Astrophysics Data System (ADS)

Kovalenko, P. Y.

2017-07-01

Processing the data received from measurement systems implies the situation when one or more registered values stand apart from the sample collection. These values are referred to as “outliers”. The processing results may be influenced significantly by the presence of those in the data sample under consideration. In order to ensure the accuracy of low-frequency oscillations detection in power systems the corresponding algorithm has been developed for the outliers detection and elimination. The algorithm is based on the concept of the irregular component of measurement signal. This component comprises measurement errors and is assumed to be Gauss-distributed random. The median filtering is employed to detect the values lying outside the range of the normally distributed measurement error on the basis of a 3σ criterion. The algorithm has been validated involving simulated signals and WAMS data as well.

EARLINET Single Calculus Chain - technical - Part 1: Pre-processing of raw lidar data

NASA Astrophysics Data System (ADS)

D'Amico, Giuseppe; Amodeo, Aldo; Mattis, Ina; Freudenthaler, Volker; Pappalardo, Gelsomina

2016-02-01

In this paper we describe an automatic tool for the pre-processing of aerosol lidar data called ELPP (EARLINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of ELPP, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns.

Motor imaginary-based brain-machine interface design using programmable logic controllers for the disabled.

PubMed

Jeyabalan, Vickneswaran; Samraj, Andrews; Loo, Chu Kiong

2010-10-01

Aiming at the implementation of brain-machine interfaces (BMI) for the aid of disabled people, this paper presents a system design for real-time communication between the BMI and programmable logic controllers (PLCs) to control an electrical actuator that could be used in devices to help the disabled. Motor imaginary signals extracted from the brain’s motor cortex using an electroencephalogram (EEG) were used as a control signal. The EEG signals were pre-processed by means of adaptive recursive band-pass filtrations (ARBF) and classified using simplified fuzzy adaptive resonance theory mapping (ARTMAP) in which the classified signals are then translated into control signals used for machine control via the PLC. A real-time test system was designed using MATLAB for signal processing, KEP-Ware V4 OLE for process control (OPC), a wireless local area network router, an Omron Sysmac CPM1 PLC and a 5 V/0.3A motor. This paper explains the signal processing techniques, the PLC's hardware configuration, OPC configuration and real-time data exchange between MATLAB and PLC using the MATLAB OPC toolbox. The test results indicate that the function of exchanging real-time data can be attained between the BMI and PLC through OPC server and proves that it is an effective and feasible method to be applied to devices such as wheelchairs or electronic equipment.

Hydrologic response of catchments to precipitation: Quantification of mechanical carriers and origins of water

NASA Astrophysics Data System (ADS)

Park, Y.-J.; Sudicky, E. A.; Brookfield, A. E.; Jones, J. P.

2011-12-01

Precipitation-induced overland and groundwater flow and mixing processes are quantified to analyze the temporal (event and pre-event water) and spatial (groundwater discharge and overland runoff) origins of water entering a stream. Using a distributed-parameter control volume finite-element simulator that can simultaneously solve the fully coupled partial differential equations describing 2-D Manning and 3-D Darcian flow and advective-dispersive transport, mechanical flow (driven by hydraulic potential) and tracer-based hydrograph separation (driven by dispersive mixing as well as mechanical flow) are simulated in response to precipitation events in two cross sections oriented parallel and perpendicular to a stream. The results indicate that as precipitation becomes more intense, the subsurface mechanical flow contributions tend to become less significant relative to the total pre-event stream discharge. Hydrodynamic mixing can play an important role in enhancing pre-event tracer signals in the stream. This implies that temporally tagged chemical signals introduced into surface-subsurface flow systems from precipitation may not be strong enough to detect the changes in the subsurface flow system. It is concluded that diffusive/dispersive mixing, capillary fringe groundwater ridging, and macropore flow can influence the temporal sources of water in the stream, but any sole mechanism may not fully explain the strong pre-event water discharge. Further investigations of the influence of heterogeneity, residence time, geomorphology, and root zone processes are required to confirm the conclusions of this study.

Hydrologic response of catchments to precipitation: Quantification of mechanical carriers and origins of water

USGS Publications Warehouse

Park, Y.-J.; Sudicky, E.A.; Brookfield, A.E.; Jones, J.P.

2011-01-01

Precipitation-induced overland and groundwater flow and mixing processes are quantified to analyze the temporal (event and pre-event water) and spatial (groundwater discharge and overland runoff) origins of water entering a stream. Using a distributed-parameter control volume finite-element simulator that can simultaneously solve the fully coupled partial differential equations describing 2-D Manning and 3-D Darcian flow and advective-dispersive transport, mechanical flow (driven by hydraulic potential) and tracer-based hydrograph separation (driven by dispersive mixing as well as mechanical flow) are simulated in response to precipitation events in two cross sections oriented parallel and perpendicular to a stream. The results indicate that as precipitation becomes more intense, the subsurface mechanical flow contributions tend to become less significant relative to the total pre-event stream discharge. Hydrodynamic mixing can play an important role in enhancing pre-event tracer signals in the stream. This implies that temporally tagged chemical signals introduced into surface-subsurface flow systems from precipitation may not be strong enough to detect the changes in the subsurface flow system. It is concluded that diffusive/dispersive mixing, capillary fringe groundwater ridging, and macropore flow can influence the temporal sources of water in the stream, but any sole mechanism may not fully explain the strong pre-event water discharge. Further investigations of the influence of heterogeneity, residence time, geomorphology, and root zone processes are required to confirm the conclusions of this study. Copyright 2011 by the American Geophysical Union.

Ultrasonic sensor based defect detection and characterisation of ceramics.

PubMed

Kesharaju, Manasa; Nagarajah, Romesh; Zhang, Tonzhua; Crouch, Ian

2014-01-01

Ceramic tiles, used in body armour systems, are currently inspected visually offline using an X-ray technique that is both time consuming and very expensive. The aim of this research is to develop a methodology to detect, locate and classify various manufacturing defects in Reaction Sintered Silicon Carbide (RSSC) ceramic tiles, using an ultrasonic sensing technique. Defects such as free silicon, un-sintered silicon carbide material and conventional porosity are often difficult to detect using conventional X-radiography. An alternative inspection system was developed to detect defects in ceramic components using an Artificial Neural Network (ANN) based signal processing technique. The inspection methodology proposed focuses on pre-processing of signals, de-noising, wavelet decomposition, feature extraction and post-processing of the signals for classification purposes. This research contributes to developing an on-line inspection system that would be far more cost effective than present methods and, moreover, assist manufacturers in checking the location of high density areas, defects and enable real time quality control, including the implementation of accept/reject criteria. Copyright © 2013 Elsevier B.V. All rights reserved.

Advanced digital signal processing for short-haul and access network

NASA Astrophysics Data System (ADS)

Zhang, Junwen; Yu, Jianjun; Chi, Nan

2016-02-01

Digital signal processing (DSP) has been proved to be a successful technology recently in high speed and high spectrum-efficiency optical short-haul and access network, which enables high performances based on digital equalizations and compensations. In this paper, we investigate advanced DSP at the transmitter and receiver side for signal pre-equalization and post-equalization in an optical access network. A novel DSP-based digital and optical pre-equalization scheme has been proposed for bandwidth-limited high speed short-distance communication system, which is based on the feedback of receiver-side adaptive equalizers, such as least-mean-squares (LMS) algorithm and constant or multi-modulus algorithms (CMA, MMA). Based on this scheme, we experimentally demonstrate 400GE on a single optical carrier based on the highest ETDM 120-GBaud PDM-PAM-4 signal, using one external modulator and coherent detection. A line rate of 480-Gb/s is achieved, which enables 20% forward-error correction (FEC) overhead to keep the 400-Gb/s net information rate. The performance after fiber transmission shows large margin for both short range and metro/regional networks. We also extend the advanced DSP for short haul optical access networks by using high order QAMs. We propose and demonstrate a high speed multi-band CAP-WDM-PON system on intensity modulation, direct detection and digital equalizations. A hybrid modified cascaded MMA post-equalization schemes are used to equalize the multi-band CAP-mQAM signals. Using this scheme, we successfully demonstrates 550Gb/s high capacity WDMPON system with 11 WDM channels, 55 sub-bands, and 10-Gb/s per user in the downstream over 40-km SMF.

Audio signal analysis for tool wear monitoring in sheet metal stamping

NASA Astrophysics Data System (ADS)

Ubhayaratne, Indivarie; Pereira, Michael P.; Xiang, Yong; Rolfe, Bernard F.

2017-02-01

Stamping tool wear can significantly degrade product quality, and hence, online tool condition monitoring is a timely need in many manufacturing industries. Even though a large amount of research has been conducted employing different sensor signals, there is still an unmet demand for a low-cost easy to set up condition monitoring system. Audio signal analysis is a simple method that has the potential to meet this demand, but has not been previously used for stamping process monitoring. Hence, this paper studies the existence and the significance of the correlation between emitted sound signals and the wear state of sheet metal stamping tools. The corrupting sources generated by the tooling of the stamping press and surrounding machinery have higher amplitudes compared to that of the sound emitted by the stamping operation itself. Therefore, a newly developed semi-blind signal extraction technique was employed as a pre-processing technique to mitigate the contribution of these corrupting sources. The spectral analysis results of the raw and extracted signals demonstrate a significant qualitative relationship between wear progression and the emitted sound signature. This study lays the basis for employing low-cost audio signal analysis in the development of a real-time industrial tool condition monitoring system.

Signal Processing and Interpretation Using Multilevel Signal Abstractions.

DTIC Science & Technology

1986-06-01

mappings expressed in the Fourier domain. Pre- viously proposed causal analysis techniques for diagnosis are based on the analysis of intermediate data ...can be processed either as individual one-dimensional waveforms or as multichannel data 26 I P- - . . . ." " ." h9. for source detection and direction...microphone data . The signal processing for both spectral analysis of microphone signals and direc- * tion determination of acoustic sources involves

Multi-step EMG Classification Algorithm for Human-Computer Interaction

NASA Astrophysics Data System (ADS)

Ren, Peng; Barreto, Armando; Adjouadi, Malek

A three-electrode human-computer interaction system, based on digital processing of the Electromyogram (EMG) signal, is presented. This system can effectively help disabled individuals paralyzed from the neck down to interact with computers or communicate with people through computers using point-and-click graphic interfaces. The three electrodes are placed on the right frontalis, the left temporalis and the right temporalis muscles in the head, respectively. The signal processing algorithm used translates the EMG signals during five kinds of facial movements (left jaw clenching, right jaw clenching, eyebrows up, eyebrows down, simultaneous left & right jaw clenching) into five corresponding types of cursor movements (left, right, up, down and left-click), to provide basic mouse control. The classification strategy is based on three principles: the EMG energy of one channel is typically larger than the others during one specific muscle contraction; the spectral characteristics of the EMG signals produced by the frontalis and temporalis muscles during different movements are different; the EMG signals from adjacent channels typically have correlated energy profiles. The algorithm is evaluated on 20 pre-recorded EMG signal sets, using Matlab simulations. The results show that this method provides improvements and is more robust than other previous approaches.

An energy ratio feature extraction method for optical fiber vibration signal

NASA Astrophysics Data System (ADS)

Sheng, Zhiyong; Zhang, Xinyan; Wang, Yanping; Hou, Weiming; Yang, Dan

2018-03-01

The intrusion events in the optical fiber pre-warning system (OFPS) are divided into two types which are harmful intrusion event and harmless interference event. At present, the signal feature extraction methods of these two types of events are usually designed from the view of the time domain. However, the differences of time-domain characteristics for different harmful intrusion events are not obvious, which cannot reflect the diversity of them in detail. We find that the spectrum distribution of different intrusion signals has obvious differences. For this reason, the intrusion signal is transformed into the frequency domain. In this paper, an energy ratio feature extraction method of harmful intrusion event is drawn on. Firstly, the intrusion signals are pre-processed and the power spectral density (PSD) is calculated. Then, the energy ratio of different frequency bands is calculated, and the corresponding feature vector of each type of intrusion event is further formed. The linear discriminant analysis (LDA) classifier is used to identify the harmful intrusion events in the paper. Experimental results show that the algorithm improves the recognition rate of the intrusion signal, and further verifies the feasibility and validity of the algorithm.

Field-quadrature and photon-number correlations produced by parametric processes.

PubMed

McKinstrie, C J; Karlsson, M; Tong, Z

2010-09-13

In a previous paper [Opt. Express 13, 4986 (2005)], formulas were derived for the field-quadrature and photon-number variances produced by multiple-mode parametric processes. In this paper, formulas are derived for the quadrature and number correlations. The number formulas are used to analyze the properties of basic devices, such as two-mode amplifiers, attenuators and frequency convertors, and composite systems made from these devices, such as cascaded parametric amplifiers and communication links. Amplifiers generate idlers that are correlated with the amplified signals, or correlate pre-existing pairs of modes, whereas attenuators decorrelate pre-existing modes. Both types of device modify the signal-to-noise ratios (SNRs) of the modes on which they act. Amplifiers decrease or increase the mode SNRs, depending on whether they are operated in phase-insensitive (PI) or phase-sensitive (PS) manners, respectively, whereas attenuators always decrease these SNRs. Two-mode PS links are sequences of transmission fibers (attenuators) followed by two-mode PS amplifiers. Not only do these PS links have noise figures that are 6-dB lower than those of the corresponding PI links, they also produce idlers that are (almost) completely correlated with the signals. By detecting the signals and idlers, one can eliminate the effects of electronic noise in the detectors.

Novel sonar signal processing tool using Shannon entropy

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

Quazi, A.H.

1996-06-01

Traditionally, conventional signal processing extracts information from sonar signals using amplitude, signal energy or frequency domain quantities obtained using spectral analysis techniques. The object is to investigate an alternate approach which is entirely different than that of traditional signal processing. This alternate approach is to utilize the Shannon entropy as a tool for the processing of sonar signals with emphasis on detection, classification, and localization leading to superior sonar system performance. Traditionally, sonar signals are processed coherently, semi-coherently, and incoherently, depending upon the a priori knowledge of the signals and noise. Here, the detection, classification, and localization technique will bemore » based on the concept of the entropy of the random process. Under a constant energy constraint, the entropy of a received process bearing finite number of sample points is maximum when hypothesis H{sub 0} (that the received process consists of noise alone) is true and decreases when correlated signal is present (H{sub 1}). Therefore, the strategy used for detection is: (I) Calculate the entropy of the received data; then, (II) compare the entropy with the maximum value; and, finally, (III) make decision: H{sub 1} is assumed if the difference is large compared to pre-assigned threshold and H{sub 0} is otherwise assumed. The test statistics will be different between entropies under H{sub 0} and H{sub 1}. Here, we shall show the simulated results for detecting stationary and non-stationary signals in noise, and results on detection of defects in a Plexiglas bar using an ultrasonic experiment conducted by Hughes. {copyright} {ital 1996 American Institute of Physics.}« less

Signal acquisition and analysis for cortical control of neuroprosthetics.

PubMed

Tillery, Stephen I Helms; Taylor, Dawn M

2004-12-01

Work in cortically controlled neuroprosthetic systems has concentrated on decoding natural behaviors from neural activity, with the idea that if the behavior could be fully decoded it could be duplicated using an artificial system. Initial estimates from this approach suggested that a high-fidelity signal comprised of many hundreds of neurons would be required to control a neuroprosthetic system successfully. However, recent studies are showing hints that these systems can be controlled effectively using only a few tens of neurons. Attempting to decode the pre-existing relationship between neural activity and natural behavior is not nearly as important as choosing a decoding scheme that can be more readily deployed and trained to generate the desired actions of the artificial system. These artificial systems need not resemble or behave similarly to any natural biological system. Effective matching of discrete and continuous neural command signals to appropriately configured device functions will enable effective control of both natural and abstract artificial systems using compatible thought processes.

EARLINET Single Calculus Chain - technical - Part 1: Pre-processing of raw lidar data

NASA Astrophysics Data System (ADS)

D'Amico, G.; Amodeo, A.; Mattis, I.; Freudenthaler, V.; Pappalardo, G.

2015-10-01

In this paper we describe an automatic tool for the pre-processing of lidar data called ELPP (EARLINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. The ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, the ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. The ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of the ELPP module, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of the ELPP module is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of the ELPP module. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. The ELPP module has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns.

Pre-emphasis determination for an S-band constant bandwidth FM/FM station

NASA Technical Reports Server (NTRS)

Wallace, G. R.; Salter, W. E.

1972-01-01

Pre-emphasis schedules are given for 11 constant-bandwidth FM subcarriers modulating an S band transmitter at three receiver signal to noise ratios (i.e., 9, 15, and 25 dB). The criterion for establishing these pre-emphasis curves is the achievement, at various receiver intermediate frequency signal to noise ratios, of equal receiver output signal to noise ratios for all channels. It is realized that these curves may not be the optimum pre-emphasis curves based on overall efficiency or maximum utilization of the allotted spectrum, but they are near-optimum for data with channels which require equal output signal to noise ratios, such as spectral densities. The empirically derived results are compared with a simplified, analytically derived schedule and the primary differences are explained. The S band pre-emphasis schedule differs from the lower frequency VHF case. Since most proportional bandwidth and constant bandwidth systems use ground based recorders and some use flight recorders (as the Saturn systems did on VHF proportional bandwidth telemetry), the effects of these recorders are discussed and a modified pre-emphasis schedule is presented showing the results of this study phase.

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.

Hippocampal Protein Kinase C Signaling Mediates the Short-Term Memory Impairment Induced by Delta9-Tetrahydrocannabinol.

PubMed

Busquets-Garcia, Arnau; Gomis-González, Maria; Salgado-Mendialdúa, Victòria; Galera-López, Lorena; Puighermanal, Emma; Martín-García, Elena; Maldonado, Rafael; Ozaita, Andrés

2018-04-01

Cannabis affects cognitive performance through the activation of the endocannabinoid system, and the molecular mechanisms involved in this process are poorly understood. Using the novel object-recognition memory test in mice, we found that the main psychoactive component of cannabis, delta9-tetrahydrocannabinol (THC), alters short-term object-recognition memory specifically involving protein kinase C (PKC)-dependent signaling. Indeed, the systemic or intra-hippocampal pre-treatment with the PKC inhibitors prevented the short-term, but not the long-term, memory impairment induced by THC. In contrast, systemic pre-treatment with mammalian target of rapamycin complex 1 inhibitors, known to block the amnesic-like effects of THC on long-term memory, did not modify such a short-term cognitive deficit. Immunoblot analysis revealed a transient increase in PKC signaling activity in the hippocampus after THC treatment. Thus, THC administration induced the phosphorylation of a specific Ser residue in the hydrophobic-motif at the C-terminal tail of several PKC isoforms. This significant immunoreactive band that paralleled cognitive performance did not match in size with the major PKC isoforms expressed in the hippocampus except for PKCθ. Moreover, THC transiently enhanced the phosphorylation of the postsynaptic calmodulin-binding protein neurogranin in a PKC dependent manner. These data demonstrate that THC alters short-term object-recognition memory through hippocampal PKC/neurogranin signaling.

Probabilistic Reasoning Over Seismic Time Series: Volcano Monitoring by Hidden Markov Models at Mt. Etna

NASA Astrophysics Data System (ADS)

Cassisi, Carmelo; Prestifilippo, Michele; Cannata, Andrea; Montalto, Placido; Patanè, Domenico; Privitera, Eugenio

2016-07-01

From January 2011 to December 2015, Mt. Etna was mainly characterized by a cyclic eruptive behavior with more than 40 lava fountains from New South-East Crater. Using the RMS (Root Mean Square) of the seismic signal recorded by stations close to the summit area, an automatic recognition of the different states of volcanic activity (QUIET, PRE-FOUNTAIN, FOUNTAIN, POST-FOUNTAIN) has been applied for monitoring purposes. Since values of the RMS time series calculated on the seismic signal are generated from a stochastic process, we can try to model the system generating its sampled values, assumed to be a Markov process, using Hidden Markov Models (HMMs). HMMs analysis seeks to recover the sequence of hidden states from the observations. In our framework, observations are characters generated by the Symbolic Aggregate approXimation (SAX) technique, which maps RMS time series values with symbols of a pre-defined alphabet. The main advantages of the proposed framework, based on HMMs and SAX, with respect to other automatic systems applied on seismic signals at Mt. Etna, are the use of multiple stations and static thresholds to well characterize the volcano states. Its application on a wide seismic dataset of Etna volcano shows the possibility to guess the volcano states. The experimental results show that, in most of the cases, we detected lava fountains in advance.

A rigorous analysis of digital pre-emphasis and DAC resolution for interleaved DAC Nyquist-WDM signal generation in high-speed coherent optical transmission systems

NASA Astrophysics Data System (ADS)

Weng, Yi; Wang, Junyi; He, Xuan; Pan, Zhongqi

2018-02-01

The Nyquist spectral shaping techniques facilitate a promising solution to enhance spectral efficiency (SE) and further reduce the cost-per-bit in high-speed wavelength-division multiplexing (WDM) transmission systems. Hypothetically, any Nyquist WDM signals with arbitrary shapes can be generated by the use of the digital signal processing (DSP) based electrical filters (E-filter). Nonetheless, in actual 100G/ 200G coherent systems, the performance as well as DSP complexity are increasingly restricted by cost and power consumption. Henceforward it is indispensable to optimize DSP to accomplish the preferred performance at the least complexity. In this paper, we systematically investigated the minimum requirements and challenges of Nyquist WDM signal generation, particularly for higher-order modulation formats, including 16 quadrature amplitude modulation (QAM) or 64QAM. A variety of interrelated parameters, such as channel spacing and roll-off factor, have been evaluated to optimize the requirements of the digital-to-analog converter (DAC) resolution and transmitter E-filter bandwidth. The impact of spectral pre-emphasis has been predominantly enhanced via the proposed interleaved DAC architecture by at least 4%, and hence reducing the required optical signal to noise ratio (OSNR) at a bit error rate (BER) of 10-3 by over 0.45 dB at a channel spacing of 1.05 symbol rate and an optimized roll-off factor of 0.1. Furthermore, the requirements of sampling rate for different types of super-Gaussian E-filters are discussed for 64QAM Nyquist WDM transmission systems. Finally, the impact of the non-50% duty cycle error between sub-DACs upon the quality of the generated signals for the interleaved DAC structure has been analyzed.

Self-organised criticality via retro-synaptic signals

NASA Astrophysics Data System (ADS)

Hernandez-Urbina, Victor; Herrmann, J. Michael

2016-12-01

The brain is a complex system par excellence. In the last decade the observation of neuronal avalanches in neocortical circuits suggested the presence of self-organised criticality in brain networks. The occurrence of this type of dynamics implies several benefits to neural computation. However, the mechanisms that give rise to critical behaviour in these systems, and how they interact with other neuronal processes such as synaptic plasticity are not fully understood. In this paper, we present a long-term plasticity rule based on retro-synaptic signals that allows the system to reach a critical state in which clusters of activity are distributed as a power-law, among other observables. Our synaptic plasticity rule coexists with other synaptic mechanisms such as spike-timing-dependent plasticity, which implies that the resulting synaptic modulation captures not only the temporal correlations between spiking times of pre- and post-synaptic units, which has been suggested as requirement for learning and memory in neural systems, but also drives the system to a state of optimal neural information processing.

On the occurrence and strength of multi-frequency multi-GNSS Ionospheric Scintillations in Indian sector during declining phase of solar cycle 24

NASA Astrophysics Data System (ADS)

Srinivasu, V. K. D.; Dashora, N.; Prasad, D. S. V. V. D.; Niranjan, K.; Gopi Krishna, S.

2018-04-01

This study presents unique perspectives of occurrence and strength of low latitude ionospheric scintillations on multiple signals of Global Navigation Satellite System (GNSS) and its frequency dependence using continuous observation records of 780 nights. A robust comparative analysis is performed using scintillation index, S4 and its variation during pre-midnight and post-midnight duration from a GNSS receiver located at Waltair (17.7°N, 83.3°E), India, covering period from July 2014 to August 2016. The results, generally exhibit the impact of declining phase of solar cycle 24 on occurrence and strength of scintillations, which, however, is evidently different over different frequencies transmitted from different GNSS systems. A deeper quantitative analysis uniquely reveals that apart from the solar cycle and seasonal effects, the number of visible satellites of a selected GNSS markedly affect the occurrence and also the strength. Processing scheme of adopting 6 hourly time windows of pre-midnight and post-midnight brought a novel result that the strength and occurrence of strong scintillations decrease with declining solar activity during pre-midnight hours but remarkably increase for moderate and weak scintillations during post-midnight. The physical processes that dominate the post-midnight equatorial ionosphere are invoked to explain such variations that are special during declining solar activity. Finally, inter-GNSS signal analysis in terms of the effect of strong, moderate and weak scintillations is presented with due consideration of number of satellite passes affected and frequency dependence of mean S4. The quantitative results of this study emphasize for the first time effect of low latitude scintillation on GNSS signals in Indian zone under changing background solar and seasonal conditions.

Programmable noise bandwidth reduction by means of digital averaging

NASA Technical Reports Server (NTRS)

Poklemba, John J. (Inventor)

1993-01-01

Predetection noise bandwidth reduction is effected by a pre-averager capable of digitally averaging the samples of an input data signal over two or more symbols, the averaging interval being defined by the input sampling rate divided by the output sampling rate. As the averaged sample is clocked to a suitable detector at a much slower rate than the input signal sampling rate the noise bandwidth at the input to the detector is reduced, the input to the detector having an improved signal to noise ratio as a result of the averaging process, and the rate at which such subsequent processing must operate is correspondingly reduced. The pre-averager forms a data filter having an output sampling rate of one sample per symbol of received data. More specifically, selected ones of a plurality of samples accumulated over two or more symbol intervals are output in response to clock signals at a rate of one sample per symbol interval. The pre-averager includes circuitry for weighting digitized signal samples using stored finite impulse response (FIR) filter coefficients. A method according to the present invention is also disclosed.

CMOS image sensor with contour enhancement

NASA Astrophysics Data System (ADS)

Meng, Liya; Lai, Xiaofeng; Chen, Kun; Yuan, Xianghui

2010-10-01

Imitating the signal acquisition and processing of vertebrate retina, a CMOS image sensor with bionic pre-processing circuit is designed. Integration of signal-process circuit on-chip can reduce the requirement of bandwidth and precision of the subsequent interface circuit, and simplify the design of the computer-vision system. This signal pre-processing circuit consists of adaptive photoreceptor, spatial filtering resistive network and Op-Amp calculation circuit. The adaptive photoreceptor unit with a dynamic range of approximately 100 dB has a good self-adaptability for the transient changes in light intensity instead of intensity level itself. Spatial low-pass filtering resistive network used to mimic the function of horizontal cell, is composed of the horizontal resistor (HRES) circuit and OTA (Operational Transconductance Amplifier) circuit. HRES circuit, imitating dendrite of the neuron cell, comprises of two series MOS transistors operated in weak inversion region. Appending two diode-connected n-channel transistors to a simple transconductance amplifier forms the OTA Op-Amp circuit, which provides stable bias voltage for the gate of MOS transistors in HRES circuit, while serves as an OTA voltage follower to provide input voltage for the network nodes. The Op-Amp calculation circuit with a simple two-stage Op-Amp achieves the image contour enhancing. By adjusting the bias voltage of the resistive network, the smoothing effect can be tuned to change the effect of image's contour enhancement. Simulations of cell circuit and 16×16 2D circuit array are implemented using CSMC 0.5μm DPTM CMOS process.

TID measurement using oblique transmissions of HF pulses

NASA Astrophysics Data System (ADS)

Galkin, Ivan; Reinisch, Bodo; Huang, Xueqin; Paznukhov, Vadym; Hamel, Ryan; Kozlov, Alexander; Belehaki, Anna

2017-04-01

The Traveling Ionospheric Disturbance (TID), a wave-like signature of moving plasma density modulation in the ionosphere, is widely acknowledged for its utility in backtracking the anomalous events responsible for the TID generation, and as a major inconvenience to high-frequency (HF) operational systems because of its deleterious impact on the accuracy of navigation and geolocation. The pilot project "Net-TIDE" for the real-time detection and evaluation of TIDs began its operation in 2016 based on the remote-sensing data from synchronized, network-coordinated HF sounding between pairs of DPS4D ionosondes at five participating observatories in Europe. Measurement of all signal properties (Doppler frequency, angle of arrival, and time-of-flight from transmitter to receiver) proved to be instrumental in detecting the TID and deducing the TID parameters: amplitude, wavelength, phase velocity, and direction of propagation. Processing of the measured HF signal data required a specialized signal processing technique that is capable of consistently extracting different signals that have propagated along different ionospheric paths. The multi-path signal environment proved to be the greatest challenge for the reliable TID specification by Net-TIDE, demanding the development of an intelligent system for "signal tracking". The intelligent system is based on a neural network model of a pre-attentive vision capable of extracting continuous signal tracks from the multi-path signal ensemble. Specific examples of the Net-TIDE algorithm suite operation and its suitability for a fully automated TID warning service are discussed.

Real Time Data Acquisition and Online Signal Processing for Magnetoencephalography

NASA Astrophysics Data System (ADS)

Rongen, H.; Hadamschek, V.; Schiek, M.

2006-06-01

To establish improved therapies for patients suffering from severe neurological and psychiatric diseases, a demand controlled and desynchronizing brain-pacemaker has been developed with techniques from statistical physics and nonlinear dynamics. To optimize the novel therapeutic approach, brain activity is investigated with a Magnetoencephalography (MEG) system prior to surgery. For this, a real time data acquisition system for a 148 channel MEG and online signal processing for artifact rejection, filtering, cross trial phase resetting analysis and three-dimensional (3-D) reconstruction of the cerebral current sources was developed. The developed PCI bus hardware is based on a FPGA and DSP design, using the benefits from both architectures. The reconstruction and visualization of the 3-D volume data is done by the PC which hosts the real time DAQ and pre-processing board. The framework of the MEG-online system is introduced and the architecture of the real time DAQ board and online reconstruction is described. In addition we show first results with the MEG-Online system for the investigation of dynamic brain activities in relation to external visual stimulation, based on test data sets.

Natural time analysis of critical phenomena: The case of pre-fracture electromagnetic emissions

NASA Astrophysics Data System (ADS)

Potirakis, S. M.; Karadimitrakis, A.; Eftaxias, K.

2013-06-01

Criticality of complex systems reveals itself in various ways. One way to monitor a system at critical state is to analyze its observable manifestations using the recently introduced method of natural time. Pre-fracture electromagnetic (EM) emissions, in agreement to laboratory experiments, have been consistently detected in the MHz band prior to significant earthquakes. It has been proposed that these emissions stem from the fracture of the heterogeneous materials surrounding the strong entities (asperities) distributed along the fault, preventing the relative slipping. It has also been proposed that the fracture of heterogeneous material could be described in analogy to the critical phase transitions in statistical physics. In this work, the natural time analysis is for the first time applied to the pre-fracture MHz EM signals revealing their critical nature. Seismicity and pre-fracture EM emissions should be two sides of the same coin concerning the earthquake generation process. Therefore, we also examine the corresponding foreshock seismic activity, as another manifestation of the same complex system at critical state. We conclude that the foreshock seismicity data present criticality features as well.

Natural time analysis of critical phenomena: the case of pre-fracture electromagnetic emissions.

PubMed

Potirakis, S M; Karadimitrakis, A; Eftaxias, K

2013-06-01

Criticality of complex systems reveals itself in various ways. One way to monitor a system at critical state is to analyze its observable manifestations using the recently introduced method of natural time. Pre-fracture electromagnetic (EM) emissions, in agreement to laboratory experiments, have been consistently detected in the MHz band prior to significant earthquakes. It has been proposed that these emissions stem from the fracture of the heterogeneous materials surrounding the strong entities (asperities) distributed along the fault, preventing the relative slipping. It has also been proposed that the fracture of heterogeneous material could be described in analogy to the critical phase transitions in statistical physics. In this work, the natural time analysis is for the first time applied to the pre-fracture MHz EM signals revealing their critical nature. Seismicity and pre-fracture EM emissions should be two sides of the same coin concerning the earthquake generation process. Therefore, we also examine the corresponding foreshock seismic activity, as another manifestation of the same complex system at critical state. We conclude that the foreshock seismicity data present criticality features as well.

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

Agnes, P.; Albuquerque, I. F. M.; Alexander, T.

The DarkSide-50 experiment at the Laboratori Nazionali del Gran Sasso is a search for dark matter using a dual phase time projection chamber with 50 kg of low radioactivity argon as target. Light signals from interactions in the argon are detected by a system of 38 photo-multiplier tubes (PMTs), 19 above and 19 below the TPC volume inside the argon cryostat. We describe the electronics which processes the signals from the photo-multipliers, the trigger system which identifies events of interest, and the data-acquisition system which records the data for further analysis. The electronics include resistive voltage dividers on the PMTs,more » custom pre-amplifiers mounted directly on the PMT voltage dividers in the liquid argon, and custom amplifier/discriminators (at room temperature). After amplification, the PMT signals are digitized in CAEN waveform digitizers, and CAEN logic modules are used to construct the trigger, the data acquisition system for the TPC is based on the Fermilab "artdaq" software. The system has been in operation since early 2014.« less

Prewarping techniques in imaging: applications in nanotechnology and biotechnology

NASA Astrophysics Data System (ADS)

Poonawala, Amyn; Milanfar, Peyman

2005-03-01

In all imaging systems, the underlying process introduces undesirable distortions that cause the output signal to be a warped version of the input. When the input to such systems can be controlled, pre-warping techniques can be employed which consist of systematically modifying the input such that it cancels out (or compensates for) the process losses. In this paper, we focus on the mask (reticle) design problem for 'optical micro-lithography', a process similar to photographic printing used for transferring binary circuit patterns onto silicon wafers. We use a pixel-based mask representation and model the above process as a cascade of convolution (aerial image formation) and thresholding (high-contrast recording) operations. The pre-distorted mask is obtained by minimizing the norm of the difference between the 'desired' output image and the 'reproduced' output image. We employ the regularization framework to ensure that the resulting masks are close-to-binary as well as simple and easy to fabricate. Finally, we provide insight into two additional applications of pre-warping techniques. First is 'e-beam lithography', used for fabricating nano-scale structures, and second is 'electronic visual prosthesis' which aims at providing limited vision to the blind by using a prosthetic retinally implanted chip capable of electrically stimulating the retinal neuron cells.

On the importance of preserving the harmonics and neighboring partials prior to vocoder processing: implications for cochlear implants.

PubMed

Hu, Yi; Loizou, Philipos C

2010-01-01

Pre-processing based noise-reduction algorithms used for cochlear implants (CIs) can sometimes introduce distortions which are carried through the vocoder stages of CI processing. While the background noise may be notably suppressed, the harmonic structure and/or spectral envelope of the signal may be distorted. The present study investigates the potential of preserving the signal's harmonic structure in voiced segments (e.g., vowels) as a means of alleviating the negative effects of pre-processing. The hypothesis tested is that preserving the harmonic structure of the signal is crucial for subsequent vocoder processing. The implications of preserving either the main harmonic components occurring at multiples of F0 or the main harmonics along with adjacent partials are investigated. This is done by first pre-processing noisy speech with a conventional noise-reduction algorithm, regenerating the harmonics, and vocoder processing the stimuli with eight channels of stimulation in steady speech-shaped noise. Results indicated that preserving the main low-frequency harmonics (spanning 1 or 3 kHz) alone was not beneficial. Preserving, however, the harmonic structure of the stimulus, i.e., the main harmonics along with the adjacent partials, was found to be critically important and provided substantial improvements (41 percentage points) in intelligibility.

A customizable system for real-time image processing using the Blackfin DSProcessor and the MicroC/OS-II real-time kernel

NASA Astrophysics Data System (ADS)

Coffey, Stephen; Connell, Joseph

2005-06-01

This paper presents a development platform for real-time image processing based on the ADSP-BF533 Blackfin processor and the MicroC/OS-II real-time operating system (RTOS). MicroC/OS-II is a completely portable, ROMable, pre-emptive, real-time kernel. The Blackfin Digital Signal Processors (DSPs), incorporating the Analog Devices/Intel Micro Signal Architecture (MSA), are a broad family of 16-bit fixed-point products with a dual Multiply Accumulate (MAC) core. In addition, they have a rich instruction set with variable instruction length and both DSP and MCU functionality thus making them ideal for media based applications. Using the MicroC/OS-II for task scheduling and management, the proposed system can capture and process raw RGB data from any standard 8-bit greyscale image sensor in soft real-time and then display the processed result using a simple PC graphical user interface (GUI). Additionally, the GUI allows configuration of the image capture rate and the system and core DSP clock rates thereby allowing connectivity to a selection of image sensors and memory devices. The GUI also allows selection from a set of image processing algorithms based in the embedded operating system.

AC Initiation System.

DTIC Science & Technology

An ac initiation system is described which uses three ac transmission signals interlocked for safety by frequency, phase, and power discrimination...The ac initiation system is pre-armed by the application of two ac signals have the proper phases, and activates a load when an ac power signal of the proper frequency and power level is applied. (Author)

Exploring the complementarity of THz pulse imaging and DCE-MRIs: Toward a unified multi-channel classification and a deep learning framework.

PubMed

Yin, X-X; Zhang, Y; Cao, J; Wu, J-L; Hadjiloucas, S

2016-12-01

We provide a comprehensive account of recent advances in biomedical image analysis and classification from two complementary imaging modalities: terahertz (THz) pulse imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The work aims to highlight underlining commonalities in both data structures so that a common multi-channel data fusion framework can be developed. Signal pre-processing in both datasets is discussed briefly taking into consideration advances in multi-resolution analysis and model based fractional order calculus system identification. Developments in statistical signal processing using principal component and independent component analysis are also considered. These algorithms have been developed independently by the THz-pulse imaging and DCE-MRI communities, and there is scope to place them in a common multi-channel framework to provide better software standardization at the pre-processing de-noising stage. A comprehensive discussion of feature selection strategies is also provided and the importance of preserving textural information is highlighted. Feature extraction and classification methods taking into consideration recent advances in support vector machine (SVM) and extreme learning machine (ELM) classifiers and their complex extensions are presented. An outlook on Clifford algebra classifiers and deep learning techniques suitable to both types of datasets is also provided. The work points toward the direction of developing a new unified multi-channel signal processing framework for biomedical image analysis that will explore synergies from both sensing modalities for inferring disease proliferation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Exploratory data analysis of acceleration signals to select light-weight and accurate features for real-time activity recognition on smartphones.

PubMed

Khan, Adil Mehmood; Siddiqi, Muhammad Hameed; Lee, Seok-Won

2013-09-27

Smartphone-based activity recognition (SP-AR) recognizes users' activities using the embedded accelerometer sensor. Only a small number of previous works can be classified as online systems, i.e., the whole process (pre-processing, feature extraction, and classification) is performed on the device. Most of these online systems use either a high sampling rate (SR) or long data-window (DW) to achieve high accuracy, resulting in short battery life or delayed system response, respectively. This paper introduces a real-time/online SP-AR system that solves this problem. Exploratory data analysis was performed on acceleration signals of 6 activities, collected from 30 subjects, to show that these signals are generated by an autoregressive (AR) process, and an accurate AR-model in this case can be built using a low SR (20 Hz) and a small DW (3 s). The high within class variance resulting from placing the phone at different positions was reduced using kernel discriminant analysis to achieve position-independent recognition. Neural networks were used as classifiers. Unlike previous works, true subject-independent evaluation was performed, where 10 new subjects evaluated the system at their homes for 1 week. The results show that our features outperformed three commonly used features by 40% in terms of accuracy for the given SR and DW.

Paroxysmal atrial fibrillation prediction based on HRV analysis and non-dominated sorting genetic algorithm III.

PubMed

Boon, K H; Khalil-Hani, M; Malarvili, M B

2018-01-01

This paper presents a method that able to predict the paroxysmal atrial fibrillation (PAF). The method uses shorter heart rate variability (HRV) signals when compared to existing methods, and achieves good prediction accuracy. PAF is a common cardiac arrhythmia that increases the health risk of a patient, and the development of an accurate predictor of the onset of PAF is clinical important because it increases the possibility to electrically stabilize and prevent the onset of atrial arrhythmias with different pacing techniques. We propose a multi-objective optimization algorithm based on the non-dominated sorting genetic algorithm III for optimizing the baseline PAF prediction system, that consists of the stages of pre-processing, HRV feature extraction, and support vector machine (SVM) model. The pre-processing stage comprises of heart rate correction, interpolation, and signal detrending. After that, time-domain, frequency-domain, non-linear HRV features are extracted from the pre-processed data in feature extraction stage. Then, these features are used as input to the SVM for predicting the PAF event. The proposed optimization algorithm is used to optimize the parameters and settings of various HRV feature extraction algorithms, select the best feature subsets, and tune the SVM parameters simultaneously for maximum prediction performance. The proposed method achieves an accuracy rate of 87.7%, which significantly outperforms most of the previous works. This accuracy rate is achieved even with the HRV signal length being reduced from the typical 30 min to just 5 min (a reduction of 83%). Furthermore, another significant result is the sensitivity rate, which is considered more important that other performance metrics in this paper, can be improved with the trade-off of lower specificity. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of pre- and pro-sequence of thaumatin on the secretion by Pichia pastoris.

PubMed

Ide, Nobuyuki; Masuda, Tetsuya; Kitabatake, Naofumi

2007-11-23

Thaumatin is a 22-kDa sweet-tasting protein containing eight disulfide bonds. When thaumatin is expressed in Pichia pastoris using the thaumatin cDNA fused with both the alpha-factor signal sequence and the Kex2 protease cleavage site from Saccharomyces cerevisiae, the N-terminal sequence of the secreted thaumatin molecule is not processed correctly. To examine the role of the thaumatin cDNA-encoded N-terminal pre-sequence and C-terminal pro-sequence on the processing of thaumatin and efficiency of thaumatin production in P. pastoris, four expression plasmids with different pre-sequence and pro-sequence were constructed and transformed into P. pastoris. The transformants containing pre-thaumatin gene that has the native plant signal, secreted thaumatin molecules in the medium. The N-terminal amino acid sequence of the secreted thaumatin molecule was processed correctly. The production yield of thaumatin was not affected by the C-terminal pro-sequence, and the pro-sequence was not processed in P. pastoris, indicating that pro-sequence is not necessary for thaumatin synthesis.

Digital stethoscope system: the feasibility of cardiac auscultation

NASA Astrophysics Data System (ADS)

Pariaszewska, Katarzyna; Młyńczak, Marcel; Niewiadomski, Wiktor; Cybulski, Gerard

2013-10-01

The application of the digital stethoscope system is a new tendency in methods of cardiac auscultation. Heart sounds, generated by the fluctuations of blood velocity and vibrations of muscle structure, are an important signal in the primary diagnosis of heart diseases. Since the XIXs century for physical examination an analog stethoscope was used, but the development of microelectronics enable the construction of digital stethoscopes which started modern phonocardiography. The typical hardware of the system could be divided into analog and digital parts, respectively. The first one consists of microphone and pre-amplifier. The second one contains a microcontroller with peripherals for data saving and transmission. Usually the specialized software is applied for the signal acquisition and digital signal processing (filtering, spectral analysis and others). This paper presents an overview of methods used in cardiac auscultation and expected developing path in the future. It also contains the description of our digital stethoscope system, which is planned to be used in poliphysiographical studies.

Pericytes of the neurovascular unit: Key functions and signaling pathways

PubMed Central

Sweeney, Melanie D.; Ayyadurai, Shiva; Zlokovic, Berislav V.

2017-01-01

Pericytes are vascular mural cells embedded in the basement membrane of blood microvessels. They extend their processes along capillaries, pre-capillary arterioles, and post-capillary venules. The central nervous system (CNS) pericytes are uniquely positioned within the neurovascular unit between endothelial cells, astrocytes, and neurons. They integrate, coordinate, and process signals from their neighboring cells to generate diverse functional responses that are critical for CNS functions in health and disease including regulation of the blood-brain barrier permeability, angiogenesis, clearance of toxic metabolites, capillary hemodynamic responses, neuroinflammation, and stem cell activity. Here, we examine the key signaling pathways between pericytes and their neighboring endothelial cells, astrocytes, and neurons that control neurovascular functions. We also review the role of pericytes in different CNS disorders including rare monogenic diseases and complex neurological disorders such as Alzheimer's disease and brain tumors. Finally, we discuss directions for future studies. PMID:27227366

Adaptive Wiener filtering for improved acquisition of distortion product otoacoustic emissions.

PubMed

Ozdamar, O; Delgado, R E; Rahman, S; Lopez, C

1998-01-01

An innovative acoustic noise canceling method using adaptive Wiener filtering (AWF) was developed for improved acquisition of distortion product otoacoustic emissions (DPOAEs). The system used one microphone placed in the test ear for the primary signal. Noise reference signals were obtained from three different sources: (a) pre-stimulus response from the test ear microphone, (b) post-stimulus response from a microphone placed near the head of the subject and (c) post-stimulus response obtained from a microphone placed in the subject's nontest ear. In order to improve spectral estimation, block averaging of a different number of single sweep responses was used. DPOAE data were obtained from 11 ears of healthy newborns in a well-baby nursery of a hospital under typical noise conditions. Simultaneously obtained recordings from all three microphones were digitized, stored and processed off-line to evaluate the effects of AWF with respect to DPOAE detection and signal-to-noise ratio (SNR) improvement. Results show that compared to standard DPOAE processing, AWF improved signal detection and improved SNR.

Differential effects of ADORA2A gene variations in pre-attentive visual sensory memory subprocesses.

PubMed

Beste, Christian; Stock, Ann-Kathrin; Ness, Vanessa; Epplen, Jörg T; Arning, Larissa

2012-08-01

The ADORA2A gene encodes the adenosine A(2A) receptor that is highly expressed in the striatum where it plays a role in modulating glutamatergic and dopaminergic transmission. Glutamatergic signaling has been suggested to play a pivotal role in cognitive functions related to the pre-attentive processing of external stimuli. Yet, the precise molecular mechanism of these processes is poorly understood. Therefore, we aimed to investigate whether ADORA2A gene variation has modulating effects on visual pre-attentive sensory memory processing. Studying two polymorphisms, rs5751876 and rs2298383, in 199 healthy control subjects who performed a partial-report paradigm, we find that ADORA2A variation is associated with differences in the efficiency of pre-attentive sensory memory sub-processes. We show that especially the initial visual availability of stimulus information is rendered more efficiently in the homozygous rare genotype groups. Processes related to the transfer of information into working memory and the duration of visual sensory (iconic) memory are compromised in the homozygous rare genotype groups. Our results show a differential genotype-dependent modulation of pre-attentive sensory memory sub-processes. Hence, we assume that this modulation may be due to differential effects of increased adenosine A(2A) receptor signaling on glutamatergic transmission and striatal medium spiny neuron (MSN) interaction. Copyright © 2011 Elsevier B.V. and ECNP. All rights reserved.

Heart Sound Biometric System Based on Marginal Spectrum Analysis

PubMed Central

Zhao, Zhidong; Shen, Qinqin; Ren, Fangqin

2013-01-01

This work presents a heart sound biometric system based on marginal spectrum analysis, which is a new feature extraction technique for identification purposes. This heart sound identification system is comprised of signal acquisition, pre-processing, feature extraction, training, and identification. Experiments on the selection of the optimal values for the system parameters are conducted. The results indicate that the new spectrum coefficients result in a significant increase in the recognition rate of 94.40% compared with that of the traditional Fourier spectrum (84.32%) based on a database of 280 heart sounds from 40 participants. PMID:23429515

Computer-Aided Modeling and Analysis of Power Processing Systems (CAMAPPS), phase 1

NASA Technical Reports Server (NTRS)

Kim, S.; Lee, J.; Cho, B. H.; Lee, F. C.

1986-01-01

The large-signal behaviors of a regulator depend largely on the type of power circuit topology and control. Thus, for maximum flexibility, it is best to develop models for each functional block a independent modules. A regulator can then be configured by collecting appropriate pre-defined modules for each functional block. In order to complete the component model generation for a comprehensive spacecraft power system, the following modules were developed: solar array switching unit and control; shunt regulators; and battery discharger. The capability of each module is demonstrated using a simplified Direct Energy Transfer (DET) system. Large-signal behaviors of solar array power systems were analyzed. Stability of the solar array system operating points with a nonlinear load is analyzed. The state-plane analysis illustrates trajectories of the system operating point under various conditions. Stability and transient responses of the system operating near the solar array's maximum power point are also analyzed. The solar array system mode of operation is described using the DET spacecraft power system. The DET system is simulated for various operating conditions. Transfer of the software program CAMAPPS (Computer Aided Modeling and Analysis of Power Processing Systems) to NASA/GSFC (Goddard Space Flight Center) was accomplished.

System performance enhancement with pre-distorted OOFDM signal waveforms in DM/DD systems.

PubMed

Sánchez, C; Ortega, B; Capmany, J

2014-03-24

In this work we propose a pre-distortion technique for the mitigation of the nonlinear distortion present in directly modulated/detected OOFDM systems and explore the system performance achieved under varying system parameters. Simulation results show that the proposed pre-distortion technique efficiently mitigates the nonlinear distortion, achieving transmission information rates around 40 Gbits/s and 18.5 Gbits/s over 40 km and 100 km of single mode fiber links, respectively, under optimum operating conditions. Moreover, the proposed pre-distortion technique can potentially provide higher system performance to that obtained with nonlinear equalization at the receiver.

The recursive combination filter approach of pre-processing for the estimation of standard deviation of RR series.

PubMed

Mishra, Alok; Swati, D

2015-09-01

Variation in the interval between the R-R peaks of the electrocardiogram represents the modulation of the cardiac oscillations by the autonomic nervous system. This variation is contaminated by anomalous signals called ectopic beats, artefacts or noise which mask the true behaviour of heart rate variability. In this paper, we have proposed a combination filter of recursive impulse rejection filter and recursive 20% filter, with recursive application and preference of replacement over removal of abnormal beats to improve the pre-processing of the inter-beat intervals. We have tested this novel recursive combinational method with median method replacement to estimate the standard deviation of normal to normal (SDNN) beat intervals of congestive heart failure (CHF) and normal sinus rhythm subjects. This work discusses the improvement in pre-processing over single use of impulse rejection filter and removal of abnormal beats for heart rate variability for the estimation of SDNN and Poncaré plot descriptors (SD1, SD2, and SD1/SD2) in detail. We have found the 22 ms value of SDNN and 36 ms value of SD2 descriptor of Poincaré plot as clinical indicators in discriminating the normal cases from CHF cases. The pre-processing is also useful in calculation of Lyapunov exponent which is a nonlinear index as Lyapunov exponents calculated after proposed pre-processing modified in a way that it start following the notion of less complex behaviour of diseased states.

Development of Advanced Signal Processing and Source Imaging Methods for Superparamagnetic Relaxometry

PubMed Central

Huang, Ming-Xiong; Anderson, Bill; Huang, Charles W.; Kunde, Gerd J.; Vreeland, Erika C.; Huang, Jeffrey W.; Matlashov, Andrei N.; Karaulanov, Todor; Nettles, Christopher P.; Gomez, Andrew; Minser, Kayla; Weldon, Caroline; Paciotti, Giulio; Harsh, Michael; Lee, Roland R.; Flynn, Edward R.

2017-01-01

Superparamagnetic Relaxometry (SPMR) is a highly sensitive technique for the in vivo detection of tumor cells and may improve early stage detection of cancers. SPMR employs superparamagnetic iron oxide nanoparticles (SPION). After a brief magnetizing pulse is used to align the SPION, SPMR measures the time decay of SPION using Super-conducting Quantum Interference Device (SQUID) sensors. Substantial research has been carried out in developing the SQUID hardware and in improving the properties of the SPION. However, little research has been done in the pre-processing of sensor signals and post-processing source modeling in SPMR. In the present study, we illustrate new pre-processing tools that were developed to: 1) remove trials contaminated with artifacts, 2) evaluate and ensure that a single decay process associated with bounded SPION exists in the data, 3) automatically detect and correct flux jumps, and 4) accurately fit the sensor signals with different decay models. Furthermore, we developed an automated approach based on multi-start dipole imaging technique to obtain the locations and magnitudes of multiple magnetic sources, without initial guesses from the users. A regularization process was implemented to solve the ambiguity issue related to the SPMR source variables. A procedure based on reduced chi-square cost-function was introduced to objectively obtain the adequate number of dipoles that describe the data. The new pre-processing tools and multi-start source imaging approach have been successfully evaluated using phantom data. In conclusion, these tools and multi-start source modeling approach substantially enhance the accuracy and sensitivity in detecting and localizing sources from the SPMR signals. Furthermore, multi-start approach with regularization provided robust and accurate solutions for a poor SNR condition similar to the SPMR detection sensitivity in the order of 1000 cells. We believe such algorithms will help establishing the industrial standards for SPMR when applying the technique in pre-clinical and clinical settings. PMID:28072579

The electronics, trigger and data acquisition system for the liquid argon time projection chamber of the DarkSide-50 search for dark matter

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

Agnes, P.; Albuquerque, I. F. M.; Alexander, T.

The DarkSide-50 experiment at the Laboratori Nazionali del Gran Sasso is a search for dark matter using a dual phase time projection chamber with 50 kg of low radioactivity argon as target. Light signals from interactions in the argon are detected by a system of 38 photo-multiplier tubes (PMTs), 19 above and 19 below the TPC volume inside the argon cryostat. We describe the electronics which processes the signals from the photo-multipliers, the trigger system which identifies events of interest, and the data-acquisition system which records the data for further analysis. The electronics include resistive voltage dividers on the PMTs,more » custom pre-amplifiers mounted directly on the PMT voltage dividers in the liquid argon, and custom amplifier/discriminators (at room temperature). After amplification, the PMT signals are digitized in CAEN waveform digitizers, and CAEN logic modules are used to construct the trigger, the data acquisition system for the TPC is based on the Fermilab "artdaq" software. The system has been in operation since early 2014.« less

The electronics, trigger and data acquisition system for the liquid argon time projection chamber of the DarkSide-50 search for dark matter

NASA Astrophysics Data System (ADS)

Agnes, P.; Albuquerque, I. F. M.; Alexander, T.; Alton, A. K.; Arisaka, K.; Asner, D. M.; Ave, M.; Back, H. O.; Baldin, B.; Biery, K.; Bocci, V.; Bonfini, G.; Bonivento, W.; Bossa, M.; Bottino, B.; Brigatti, A.; Brodsky, J.; Budano, F.; Bussino, S.; Cadeddu, M.; Cadoni, M.; Calaprice, F.; Canci, N.; Candela, A.; Cao, H.; Caravati, M.; Cariello, M.; Carlini, M.; Catalanotti, S.; Cataudella, V.; Cavalcante, P.; Chepurnov, A.; Cicaló, C.; Cocco, A. G.; Covone, G.; Crippa, L.; D'Angelo, D.; D'Incecco, M.; Davini, S.; de Candia, A.; De Cecco, S.; De Deo, M.; De Filippis, G.; De Rosa, G.; De Vincenzi, M.; Derbin, A.; Devoto, A.; Di Eusanio, F.; Dionisi, C.; Di Pietro, G.; Edkins, E.; Empl, A.; Fan, A.; Fiorillo, G.; Fomenko, K.; Forster, G.; Franco, D.; Gabriele, F.; Galbiati, C.; Giagu, S.; Giganti, C.; Giovanetti, G. K.; Goretti, A. M.; Granato, F.; Grandi, L.; Gromov, M.; Guan, M.; Guardincerri, Y.; Hackett, B. R.; Herner, K. R.; Hughes, D.; Humble, P.; Hungerford, E. V.; Ianni, A.; Ianni, A.; James, I.; Johnson, T. N.; Keeter, K.; Kendziora, C. L.; Kobychev, V.; Koh, G.; Korablev, D.; Korga, G.; Kubankin, A.; Li, X.; Lissia, M.; Loer, B.; Lombardi, P.; Longo, G.; Luitz, S.; Ma, Y.; Machado, A.; Machulin, I. N.; Mandarano, A.; Mari, S. M.; Maricic, J.; Marini, L.; Martoff, C. J.; Meyers, P. D.; Miletic, T.; Milincic, R.; Montanari, D.; Monte, A.; Montuschi, M.; Monzani, M. E.; Mosteiro, P.; Mount, B. J.; Muratova, V. N.; Musico, P.; Navrer Agasson, A.; Nelson, A.; Odrowski, S.; Oleinik, A.; Orsini, M.; Ortica, F.; Pagani, L.; Pallavicini, M.; Pantic, E.; Parmeggiano, S.; Pelczar, K.; Pelliccia, N.; Pocar, A.; Pordes, S.; Pugachev, D. A.; Qian, H.; Randle, K.; Ranucci, G.; Razeti, M.; Razeto, A.; Reinhold, B.; Renshaw, A. L.; Rescigno, M.; Riffard, Q.; Romani, A.; Rossi, B.; Rossi, N.; Rountree, S. D.; Sablone, D.; Saggese, P.; Saldanha, R.; Sands, W.; Sangiorgio, S.; Savarese, C.; Schlitzer, B.; Segreto, E.; Semenov, D. A.; Shields, E.; Singh, P. N.; Skorokhvatov, M. D.; Smirnov, O.; Sotnikov, A.; Stanford, C.; Suvorov, Y.; Tartaglia, R.; Tatarowicz, J.; Testera, G.; Tonazzo, A.; Trinchese, P.; Unzhakov, E. V.; Verducci, M.; Vishneva, A.; Vogelaar, R. B.; Wada, M.; Walker, S.; Wang, H.; Wang, Y.; Watson, A. W.; Westerdale, S.; Wojcik, M. M.; Xiang, X.; Xiao, X.; Xu, J.; Yang, C.; Yoo, J.; Zavatarelli, S.; Zec, A.; Zhong, W.; Zhu, C.; Zuzel, G.

2017-12-01

The DarkSide-50 experiment at the Laboratori Nazionali del Gran Sasso is a search for dark matter using a dual phase time projection chamber with 50 kg of low radioactivity argon as target. Light signals from interactions in the argon are detected by a system of 38 photo-multiplier tubes (PMTs), 19 above and 19 below the TPC volume inside the argon cryostat. We describe the electronics which processes the signals from the photo-multipliers, the trigger system which identifies events of interest, and the data-acquisition system which records the data for further analysis. The electronics include resistive voltage dividers on the PMTs, custom pre-amplifiers mounted directly on the PMT voltage dividers in the liquid argon, and custom amplifier/discriminators (at room temperature). After amplification, the PMT signals are digitized in CAEN waveform digitizers, and CAEN logic modules are used to construct the trigger; the data acquisition system for the TPC is based on the Fermilab artdaq software. The system has been in operation since early 2014.

The electronics, trigger and data acquisition system for the liquid argon time projection chamber of the DarkSide-50 search for dark matter

DOE PAGES

Agnes, P.; Albuquerque, I. F. M.; Alexander, T.; ...

2017-12-01

The DarkSide-50 experiment at the Laboratori Nazionali del Gran Sasso is a search for dark matter using a dual phase time projection chamber with 50 kg of low radioactivity argon as target. Light signals from interactions in the argon are detected by a system of 38 photo-multiplier tubes (PMTs), 19 above and 19 below the TPC volume inside the argon cryostat. We describe the electronics which processes the signals from the photo-multipliers, the trigger system which identifies events of interest, and the data-acquisition system which records the data for further analysis. The electronics include resistive voltage dividers on the PMTs,more » custom pre-amplifiers mounted directly on the PMT voltage dividers in the liquid argon, and custom amplifier/discriminators (at room temperature). After amplification, the PMT signals are digitized in CAEN waveform digitizers, and CAEN logic modules are used to construct the trigger, the data acquisition system for the TPC is based on the Fermilab "artdaq" software. The system has been in operation since early 2014.« less

Evaluation of pre-emption and transition strategies for Northern Virginia Smart Traffic Signal Systems (NVSTSS).

DOT National Transportation Integrated Search

2008-01-01

Modern traffic signal control systems provide emergency vehicle preemption (EVP) capabilities by utilizing advanced sensors and communication technologies. EVP strategies are widely implemented by urban transportation management agencies. One of the ...

Fusion of spectral models for dynamic modeling of sEMG and skeletal muscle force.

PubMed

Potluri, Chandrasekhar; Anugolu, Madhavi; Chiu, Steve; Urfer, Alex; Schoen, Marco P; Naidu, D Subbaram

2012-01-01

In this paper, we present a method of combining spectral models using a Kullback Information Criterion (KIC) data fusion algorithm. Surface Electromyographic (sEMG) signals and their corresponding skeletal muscle force signals are acquired from three sensors and pre-processed using a Half-Gaussian filter and a Chebyshev Type- II filter, respectively. Spectral models - Spectral Analysis (SPA), Empirical Transfer Function Estimate (ETFE), Spectral Analysis with Frequency Dependent Resolution (SPFRD) - are extracted from sEMG signals as input and skeletal muscle force as output signal. These signals are then employed in a System Identification (SI) routine to establish the dynamic models relating the input and output. After the individual models are extracted, the models are fused by a probability based KIC fusion algorithm. The results show that the SPFRD spectral models perform better than SPA and ETFE models in modeling the frequency content of the sEMG/skeletal muscle force data.

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.

Signal Processing Methods for Liquid Rocket Engine Combustion Stability Assessments

NASA Technical Reports Server (NTRS)

Kenny, R. Jeremy; Lee, Erik; Hulka, James R.; Casiano, Matthew

2011-01-01

The J2X Gas Generator engine design specifications include dynamic, spontaneous, and broadband combustion stability requirements. These requirements are verified empirically based high frequency chamber pressure measurements and analyses. Dynamic stability is determined with the dynamic pressure response due to an artificial perturbation of the combustion chamber pressure (bomb testing), and spontaneous and broadband stability are determined from the dynamic pressure responses during steady operation starting at specified power levels. J2X Workhorse Gas Generator testing included bomb tests with multiple hardware configurations and operating conditions, including a configuration used explicitly for engine verification test series. This work covers signal processing techniques developed at Marshall Space Flight Center (MSFC) to help assess engine design stability requirements. Dynamic stability assessments were performed following both the CPIA 655 guidelines and a MSFC in-house developed statistical-based approach. The statistical approach was developed to better verify when the dynamic pressure amplitudes corresponding to a particular frequency returned back to pre-bomb characteristics. This was accomplished by first determining the statistical characteristics of the pre-bomb dynamic levels. The pre-bomb statistical characterization provided 95% coverage bounds; these bounds were used as a quantitative measure to determine when the post-bomb signal returned to pre-bomb conditions. The time for post-bomb levels to acceptably return to pre-bomb levels was compared to the dominant frequency-dependent time recommended by CPIA 655. Results for multiple test configurations, including stable and unstable configurations, were reviewed. Spontaneous stability was assessed using two processes: 1) characterization of the ratio of the peak response amplitudes to the excited chamber acoustic mode amplitudes and 2) characterization of the variability of the peak response's frequency over the test duration. This characterization process assists in evaluating the discreteness of a signal as well as the stability of the chamber response. Broadband stability was assessed using a running root-mean-square evaluation. These techniques were also employed, in a comparative analysis, on available Fastrac data, and these results are presented here.

Diagnosing Breast Cancer with Microwave Technology: remaining challenges and potential solutions with machine learning.

PubMed

Oliveira, Bárbara L; Godinho, Daniela; O'Halloran, Martin; Glavin, Martin; Jones, Edward; Conceição, Raquel C

2018-05-19

Currently, breast cancer often requires invasive biopsies for diagnosis, motivating researchers to design and develop non-invasive and automated diagnosis systems. Recent microwave breast imaging studies have shown how backscattered signals carry relevant information about the shape of a tumour, and tumour shape is often used with current imaging modalities to assess malignancy. This paper presents a comprehensive analysis of microwave breast diagnosis systems which use machine learning to learn characteristics of benign and malignant tumours. The state-of-the-art, the main challenges still to overcome and potential solutions are outlined. Specifically, this work investigates the benefit of signal pre-processing on diagnostic performance, and proposes a new set of extracted features that capture the tumour shape information embedded in a signal. This work also investigates if a relationship exists between the antenna topology in a microwave system and diagnostic performance. Finally, a careful machine learning validation methodology is implemented to guarantee the robustness of the results and the accuracy of performance evaluation.

Flow-based analysis using microfluidics-chemiluminescence systems.

PubMed

Al Lawati, Haider A J

2013-01-01

This review will discuss various approaches and techniques in which analysis using microfluidics-chemiluminescence systems (MF-CL) has been reported. A variety of applications is examined, including environmental, pharmaceutical, biological, food and herbal analysis. Reported uses of CL reagents, sample introduction techniques, sample pretreatment methods, CL signal enhancement and detection systems are discussed. A hydrodynamic pumping system is predominately used for these applications. However, several reports are available in which electro-osmotic (EO) pumping has been implemented. Various sample pretreatment methods have been used, including liquid-liquid extraction, solid-phase extraction and molecularly imprinted polymers. A wide range of innovative techniques has been reported for CL signal enhancement. Most of these techniques are based on enhancement of the mixing process in the microfluidics channels, which leads to enhancement of the CL signal. However, other techniques are also reported, such as mirror reaction, liquid core waveguide, on-line pre-derivatization and the use of an opaque white chip with a thin transparent seal. Photodetectors are the most commonly used detectors; however, other detection systems have also been used, including integrated electrochemiluminescence (ECL) and organic photodiodes (OPDs). Copyright © 2012 John Wiley & Sons, Ltd.

Stochastic subspace identification for operational modal analysis of an arch bridge

NASA Astrophysics Data System (ADS)

Loh, Chin-Hsiung; Chen, Ming-Che; Chao, Shu-Hsien

2012-04-01

In this paer the application of output-only system identification technique, known as Stochastic Subspace Identification (SSI) algorithms, for civil infrastructures is carried out. The ability of covariance driven stochastic subspace identification (SSI-COV) was proved through the analysis of the ambient data of an arch bridge under operational condition. A newly developed signal processing technique, Singular Spectrum analysis (SSA), capable to smooth noisy signals, is adopted for pre-processing the recorded data before the SSI. The conjunction of SSA and SSICOV provides a useful criterion for the system order determination. With the aim of estimating accurate modal parameters of the structure in off-line analysis, a stabilization diagram is constructed by plotting the identified poles of the system with increasing the size of data Hankel matrix. Identification task of a real structure, Guandu Bridge, is carried out to identify the system natural frequencies and mode shapes. The uncertainty of the identified model parameters from output-only measurement of the bridge under operation condition, such as temperature and traffic loading conditions, is discussed.

Experimental validation of A-mode ultrasound acquisition system for computer assisted orthopaedic surgery

NASA Astrophysics Data System (ADS)

De Lorenzo, Danilo; De Momi, Elena; Beretta, Elisa; Cerveri, Pietro; Perona, Franco; Ferrigno, Giancarlo

2009-02-01

Computer Assisted Orthopaedic Surgery (CAOS) systems improve the results and the standardization of surgical interventions. Anatomical landmarks and bone surface detection is straightforward to either register the surgical space with the pre-operative imaging space and to compute biomechanical parameters for prosthesis alignment. Surface points acquisition increases the intervention invasiveness and can be influenced by the soft tissue layer interposition (7-15mm localization errors). This study is aimed at evaluating the accuracy of a custom-made A-mode ultrasound (US) system for non invasive detection of anatomical landmarks and surfaces. A-mode solutions eliminate the necessity of US images segmentation, offers real-time signal processing and requires less invasive equipment. The system consists in a single transducer US probe optically tracked, a pulser/receiver and an FPGA-based board, which is responsible for logic control command generation and for real-time signal processing and three custom-made board (signal acquisition, blanking and synchronization). We propose a new calibration method of the US system. The experimental validation was then performed measuring the length of known-shape polymethylmethacrylate boxes filled with pure water and acquiring bone surface points on a bovine bone phantom covered with soft-tissue mimicking materials. Measurement errors were computed through MR and CT images acquisitions of the phantom. Points acquisition on bone surface with the US system demonstrated lower errors (1.2mm) than standard pointer acquisition (4.2mm).

In-situ Condition Monitoring of Components in Small Modular Reactors Using Process and Electrical Signature Analysis. Final report, volume 1. Development of experimental flow control loop, data analysis and plant monitoring

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

Upadhyaya, Belle; Hines, J. Wesley; Damiano, Brian

The research and development under this project was focused on the following three major objectives: Objective 1: Identification of critical in-vessel SMR components for remote monitoring and development of their low-order dynamic models, along with a simulation model of an integral pressurized water reactor (iPWR). Objective 2: Development of an experimental flow control loop with motor-driven valves and pumps, incorporating data acquisition and on-line monitoring interface. Objective 3: Development of stationary and transient signal processing methods for electrical signatures, machinery vibration, and for characterizing process variables for equipment monitoring. This objective includes the development of a data analysis toolbox. Themore » following is a summary of the technical accomplishments under this project: - A detailed literature review of various SMR types and electrical signature analysis of motor-driven systems was completed. A bibliography of literature is provided at the end of this report. Assistance was provided by ORNL in identifying some key references. - A review of literature on pump-motor modeling and digital signal processing methods was performed. - An existing flow control loop was upgraded with new instrumentation, data acquisition hardware and software. The upgrading of the experimental loop included the installation of a new submersible pump driven by a three-phase induction motor. All the sensors were calibrated before full-scale experimental runs were performed. - MATLAB-Simulink model of a three-phase induction motor and pump system was completed. The model was used to simulate normal operation and fault conditions in the motor-pump system, and to identify changes in the electrical signatures. - A simulation model of an integral PWR (iPWR) was updated and the MATLAB-Simulink model was validated for known transients. The pump-motor model was interfaced with the iPWR model for testing the impact of primary flow perturbations (upsets) on plant parameters and the pump electrical signatures. Additionally, the reactor simulation is being used to generate normal operation data and data with instrumentation faults and process anomalies. A frequency controller was interfaced with the motor power supply in order to vary the electrical supply frequency. The experimental flow control loop was used to generate operational data under varying motor performance characteristics. Coolant leakage events were simulated by varying the bypass loop flow rate. The accuracy of motor power calculation was improved by incorporating the power factor, computed from motor current and voltage in each phase of the induction motor.- A variety of experimental runs were made for steady-state and transient pump operating conditions. Process, vibration, and electrical signatures were measured using a submersible pump with variable supply frequency. High correlation was seen between motor current and pump discharge pressure signal; similar high correlation was exhibited between pump motor power and flow rate. Wide-band analysis indicated high coherence (in the frequency domain) between motor current and vibration signals. - Wide-band operational data from a PWR were acquired from AMS Corporation and used to develop time-series models, and to estimate signal spectrum and sensor time constant. All the data were from different pressure transmitters in the system, including primary and secondary loops. These signals were pre-processed using the wavelet transform for filtering both low-frequency and high-frequency bands. This technique of signal pre-processing provides minimum distortion of the data, and results in a more optimal estimation of time constants of plant sensors using time-series modeling techniques.« less

Model-Based Fault Diagnosis for Turboshaft Engines

NASA Technical Reports Server (NTRS)

Green, Michael D.; Duyar, Ahmet; Litt, Jonathan S.

1998-01-01

Tests are described which, when used to augment the existing periodic maintenance and pre-flight checks of T700 engines, can greatly improve the chances of uncovering a problem compared to the current practice. These test signals can be used to expose and differentiate between faults in various components by comparing the responses of particular engine variables to the expected. The responses can be processed on-line in a variety of ways which have been shown to reveal and identify faults. The combination of specific test signals and on-line processing methods provides an ad hoc approach to the isolation of faults which might not otherwise be detected during pre-flight checkout.

Prospective Validation of Pre-earthquake Atmospheric Signals and Their Potential for Short–term Earthquake Forecasting

NASA Astrophysics Data System (ADS)

Ouzounov, Dimitar; Pulinets, Sergey; Hattori, Katsumi; Lee, Lou; Liu, Tiger; Kafatos, Menas

2015-04-01

We are presenting the latest development in multi-sensors observations of short-term pre-earthquake phenomena preceding major earthquakes. Our challenge question is: "Whether such pre-earthquake atmospheric/ionospheric signals are significant and could be useful for early warning of large earthquakes?" To check the predictive potential of atmospheric pre-earthquake signals we have started to validate anomalous ionospheric / atmospheric signals in retrospective and prospective modes. The integrated satellite and terrestrial framework (ISTF) is our method for validation and is based on a joint analysis of several physical and environmental parameters (Satellite thermal infrared radiation (STIR), electron concentration in the ionosphere (GPS/TEC), radon/ion activities, air temperature and seismicity patterns) that were found to be associated with earthquakes. The science rationale for multidisciplinary analysis is based on concept Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) [Pulinets and Ouzounov, 2011], which explains the synergy of different geospace processes and anomalous variations, usually named short-term pre-earthquake anomalies. Our validation processes consist in two steps: (1) A continuous retrospective analysis preformed over two different regions with high seismicity- Taiwan and Japan for 2003-2009 (2) Prospective testing of STIR anomalies with potential for M5.5+ events. The retrospective tests (100+ major earthquakes, M>5.9, Taiwan and Japan) show STIR anomalous behavior before all of these events with false negatives close to zero. False alarm ratio for false positives is less then 25%. The initial prospective testing for STIR shows systematic appearance of anomalies in advance (1-30 days) to the M5.5+ events for Taiwan, Kamchatka-Sakhalin (Russia) and Japan. Our initial prospective results suggest that our approach show a systematic appearance of atmospheric anomalies, one to several days prior to the largest earthquakes That feature could be further studied and tested for prospective early warnings based on the multi-sensors detection of pre-earthquake atmospheric signals.

Architectural design for a low cost FPGA-based traffic signal detection system in vehicles

NASA Astrophysics Data System (ADS)

López, Ignacio; Salvador, Rubén; Alarcón, Jaime; Moreno, Félix

2007-05-01

In this paper we propose an architecture for an embedded traffic signal detection system. Development of Advanced Driver Assistance Systems (ADAS) is one of the major trends of research in automotion nowadays. Examples of past and ongoing projects in the field are CHAMELEON ("Pre-Crash Application all around the vehicle" IST 1999-10108), PREVENT (Preventive and Active Safety Applications, FP6-507075, http://www.prevent-ip.org/) and AVRT in the US (Advanced Vision-Radar Threat Detection (AVRT): A Pre-Crash Detection and Active Safety System). It can be observed a major interest in systems for real-time analysis of complex driving scenarios, evaluating risk and anticipating collisions. The system will use a low cost CCD camera on the dashboard facing the road. The images will be processed by an Altera Cyclone family FPGA. The board does median and Sobel filtering of the incoming frames at PAL rate, and analyzes them for several categories of signals. The result is conveyed to the driver. The scarce resources provided by the hardware require an architecture developed for optimal use. The system will use a combination of neural networks and an adapted blackboard architecture. Several neural networks will be used in sequence for image analysis, by reconfiguring a single, generic hardware neural network in the FPGA. This generic network is optimized for speed, in order to admit several executions within the frame rate. The sequence will follow the execution cycle of the blackboard architecture. The global, blackboard architecture being developed and the hardware architecture for the generic, reconfigurable FPGA perceptron will be explained in this paper. The project is still at an early stage. However, some hardware implementation results are already available and will be offered in the paper.

A Triadic Neurocognitive Approach to Addiction for Clinical Interventions

PubMed Central

Noël, Xavier; Brevers, Damien; Bechara, Antoine

2013-01-01

According to the triadic neurocognitive model of addiction to drugs (e.g., cocaine) and non-drugs (e.g., gambling), weakened “willpower” associated with these behaviors is the product of an abnormal functioning in one or more of three key neural and cognitive systems: (1) an amygdala-striatum dependent system mediating automatic, habitual, and salient behaviors; (2) a prefrontal cortex dependent system important for self-regulation and forecasting the future consequences of a behavior; and (3) an insula dependent system for the reception of interoceptive signals and their translation into feeling states (such as urge and craving), which in turn plays a strong influential role in decision-making and impulse control processes related to uncertainty, risk, and reward. The described three-systems account for poor decision-making (i.e., prioritizing short-term consequences of a decisional option) and stimulus-driven actions, thus leading to a more elevated risk for relapse. Finally, this article elaborates on the need for “personalized” clinical model-based interventions targeting interactions between implicit processes, interoceptive signaling, and supervisory function aimed at helping individuals become less governed by immediate situations and automatic pre-potent responses, and more influenced by systems involved in the pursuit of future valued goals. PMID:24409155

Face recognition increases during saccade preparation.

PubMed

Lin, Hai; Rizak, Joshua D; Ma, Yuan-ye; Yang, Shang-chuan; Chen, Lin; Hu, Xin-tian

2014-01-01

Face perception is integral to human perception system as it underlies social interactions. Saccadic eye movements are frequently made to bring interesting visual information, such as faces, onto the fovea for detailed processing. Just before eye movement onset, the processing of some basic features, such as the orientation, of an object improves at the saccade landing point. Interestingly, there is also evidence that indicates faces are processed in early visual processing stages similar to basic features. However, it is not known whether this early enhancement of processing includes face recognition. In this study, three experiments were performed to map the timing of face presentation to the beginning of the eye movement in order to evaluate pre-saccadic face recognition. Faces were found to be similarly processed as simple objects immediately prior to saccadic movements. Starting ∼ 120 ms before a saccade to a target face, independent of whether or not the face was surrounded by other faces, the face recognition gradually improved and the critical spacing of the crowding decreased as saccade onset was approaching. These results suggest that an upcoming saccade prepares the visual system for new information about faces at the saccade landing site and may reduce the background in a crowd to target the intended face. This indicates an important role of pre-saccadic eye movement signals in human face recognition.

A microprocessor based anti-aliasing filter for a PCM system

NASA Technical Reports Server (NTRS)

Morrow, D. C.; Sandlin, D. R.

1984-01-01

Described is the design and evaluation of a microprocessor based digital filter. The filter was made to investigate the feasibility of a digital replacement for the analog pre-sampling filters used in telemetry systems at the NASA Ames-Dryden Flight Research Facility (DFRF). The digital filter will utilize an Intel 2920 Analog Signal Processor (ASP) chip. Testing includes measurements of: (1) the filter frequency response and, (2) the filter signal resolution. The evaluation of the digital filter was made on the basis of circuit size, projected environmental stability and filter resolution. The 2920 based digital filter was found to meet or exceed the pre-sampling filter specifications for limited signal resolution applications.

Exploring the physical layer frontiers of cellular uplink: The Vienna LTE-A Uplink Simulator.

PubMed

Zöchmann, Erich; Schwarz, Stefan; Pratschner, Stefan; Nagel, Lukas; Lerch, Martin; Rupp, Markus

Communication systems in practice are subject to many technical/technological constraints and restrictions. Multiple input, multiple output (MIMO) processing in current wireless communications, as an example, mostly employs codebook-based pre-coding to save computational complexity at the transmitters and receivers. In such cases, closed form expressions for capacity or bit-error probability are often unattainable; effects of realistic signal processing algorithms on the performance of practical communication systems rather have to be studied in simulation environments. The Vienna LTE-A Uplink Simulator is a 3GPP LTE-A standard compliant MATLAB-based link level simulator that is publicly available under an academic use license, facilitating reproducible evaluations of signal processing algorithms and transceiver designs in wireless communications. This paper reviews research results that have been obtained by means of the Vienna LTE-A Uplink Simulator, highlights the effects of single-carrier frequency-division multiplexing (as the distinguishing feature to LTE-A downlink), extends known link adaptation concepts to uplink transmission, shows the implications of the uplink pilot pattern for gathering channel state information at the receiver and completes with possible future research directions.

Effects of Pre-Experimental Knowledge on Recognition Memory

ERIC Educational Resources Information Center

Bird, Chris M.; Davies, Rachel A.; Ward, Jamie; Burgess, Neil

2011-01-01

The influence of pre-experimental autobiographical knowledge on recognition memory was investigated using as memoranda faces that were either personally known or unknown to the participant. Under a dual process theory, such knowledge boosted both recollection- and familiarity-based recognition judgements. Under an unequal variance signal detection…

Purinergic modulation of preBötzinger complex inspiratory rhythm in rodents: the interaction between ATP and adenosine

PubMed Central

Zwicker, J D; Rajani, V; Hahn, L B; Funk, G D

2011-01-01

Abstract ATP signalling in the CNS is mediated by a three-part system comprising the actions of ATP (and ADP) at P2 receptors (P2Rs), adenosine (ADO) at P1 receptors (P1Rs), and ectonucleotidases that degrade ATP into ADO. ATP excites preBötzinger complex (preBötC) inspiratory rhythm-generating networks where its release attenuates the hypoxic depression of breathing. Its metabolite, ADO, inhibits breathing through unknown mechanisms that may involve the preBötC. Our objective is to understand the dynamics of this signalling system and its influence on preBötC networks. We show that the preBötC of mouse and rat is sensitive to P2Y1 purinoceptor (P2Y1R) activation, responding with a >2-fold increase in frequency. Remarkably, the mouse preBötC is insensitive to ATP. Only after block of A1 ADORs is the ATP-evoked, P2Y1R-mediated frequency increase observed. This demonstrates that ATP is rapidly degraded to ADO, which activates inhibitory A1Rs, counteracting the P2Y1R-mediated excitation. ADO sensitivity of mouse preBötC was confirmed by a frequency decrease that was absent in rat. Differential ectonucleotidase activities are likely to contribute to the negligible ATP sensitivity of mouse preBötC. Real-time PCR analysis of ectonucleotidase isoforms in preBötC punches revealed TNAP (degrades ATP to ADO) or ENTPDase2 (favours production of excitatory ADP) as the primary constituent in mouse and rat, respectively. These data further establish the sensitivity of this vital network to P2Y1R-mediated excitation, emphasizing that individual components of the three-part signalling system dramatically alter network responses to ATP. Data also suggest therapeutic potential may derive from methods that alter the ATP–ADO balance to favour the excitatory actions of ATP. PMID:21788352

Is transcranial direct current stimulation a potential method for improving response inhibition?☆

PubMed Central

Kwon, Yong Hyun; Kwon, Jung Won

2013-01-01

Inhibitory control of movement in motor learning requires the ability to suppress an inappropriate action, a skill needed to stop a planned or ongoing motor response in response to changes in a variety of environments. This study used a stop-signal task to determine whether transcranial direct-current stimulation over the pre-supplementary motor area alters the reaction time in motor inhibition. Forty healthy subjects were recruited for this study and were randomly assigned to either the transcranial direct-current stimulation condition or a sham-transcranial direct-current stimulation condition. All subjects consecutively performed the stop-signal task before, during, and after the delivery of anodal transcranial direct-current stimulation over the pre-supplementary motor area (pre-transcranial direct-current stimulation phase, transcranial direct-current stimulation phase, and post-transcranial direct-current stimulation phase). Compared to the sham condition, there were significant reductions in the stop-signal processing times during and after transcranial direct-current stimulation, and change times were significantly greater in the transcranial direct-current stimulation condition. There was no significant change in go processing-times during or after transcranial direct-current stimulation in either condition. Anodal transcranial direct-current stimulation was feasibly coupled to an interactive improvement in inhibitory control. This coupling led to a decrease in the stop-signal process time required for the appropriate responses between motor execution and inhibition. However, there was no transcranial direct-current stimulation effect on the no-signal reaction time during the stop-signal task. Transcranial direct-current stimulation can adjust certain behaviors, and it could be a useful clinical intervention for patients who have difficulties with response inhibition. PMID:25206399

Is transcranial direct current stimulation a potential method for improving response inhibition?

PubMed

Kwon, Yong Hyun; Kwon, Jung Won

2013-04-15

Inhibitory control of movement in motor learning requires the ability to suppress an inappropriate action, a skill needed to stop a planned or ongoing motor response in response to changes in a variety of environments. This study used a stop-signal task to determine whether transcranial direct-current stimulation over the pre-supplementary motor area alters the reaction time in motor inhibition. Forty healthy subjects were recruited for this study and were randomly assigned to either the transcranial direct-current stimulation condition or a sham-transcranial direct-current stimulation condition. All subjects consecutively performed the stop-signal task before, during, and after the delivery of anodal transcranial direct-current stimulation over the pre-supplementary motor area (pre-transcranial direct-current stimulation phase, transcranial direct-current stimulation phase, and post-transcranial direct-current stimulation phase). Compared to the sham condition, there were significant reductions in the stop-signal processing times during and after transcranial direct-current stimulation, and change times were significantly greater in the transcranial direct-current stimulation condition. There was no significant change in go processing-times during or after transcranial direct-current stimulation in either condition. Anodal transcranial direct-current stimulation was feasibly coupled to an interactive improvement in inhibitory control. This coupling led to a decrease in the stop-signal process time required for the appropriate responses between motor execution and inhibition. However, there was no transcranial direct-current stimulation effect on the no-signal reaction time during the stop-signal task. Transcranial direct-current stimulation can adjust certain behaviors, and it could be a useful clinical intervention for patients who have difficulties with response inhibition.

Laquinimod dampens hyperactive cytokine production in Huntington's disease patient myeloid cells.

PubMed

Dobson, Lucianne; Träger, Ulrike; Farmer, Ruth; Hayardeny, Liat; Loupe, Pippa; Hayden, Michael R; Tabrizi, Sarah J

2016-06-01

Huntington's disease (HD) is a neurodegenerative condition characterized by pathology in the brain and peripheral tissues. Hyperactivity of the innate immune system, due in part to NFκB pathway dysregulation, is an early and active component of HD. Evidence suggests targeting immune disruption may slow disease progression. Laquinimod is an orally active immunomodulator that down-regulates proinflammatory cytokine production in peripheral blood mononuclear cells, and in the brain down-regulates astrocytic and microglial activation by modulating NFκB signalling. Laquinimod had beneficial effects on inflammation, brain atrophy and disease progression in multiple sclerosis (MS) in two phase III clinical trials. This study investigated the effects of laquinimod on hyperactive proinflammatory cytokine release and NFκB signalling in HD patient myeloid cell cultures. Monocytes from manifest (manHD) and pre-manifest (preHD) HD gene carriers and healthy volunteers (HV) were treated with laquinimod and stimulated with lipopolysaccharide. After 24 h pre-treatment with 5 μM laquinimod, manHD monocytes released lower levels of IL-1β, IL-5, IL-8, IL-10, IL-13 and TNFα in response to stimulation. PreHD monocytes released lower levels of IL-8, IL-10 and IL-13, with no reduction observed in HV monocytes. The effects of laquinimod on dysfunctional NFκB signalling in HD was assessed by inhibitor of kappa B (IκB) degradation kinetics, nuclear translocation of NFκB and interactions between IκB kinase (IKK) and HTT, in HD myeloid cells. No differences were observed between laquinimod-treated and untreated conditions. These results provide evidence that laquinimod dampens hyper-reactive cytokine release from manHD and preHD monocytes, with a much reduced effect on HV monocytes. Evidence suggests targeting CNS and peripheral immune disruption may slow Huntington's disease (HD) neurodegenerative processes. The effects of laquinimod, an orally active immunomodulator, on hyperactive cytokine release and dysfunctional NFκB signalling in stimulated myeloid cell cultures from pre-manifest and manifest HD gene carriers and healthy volunteers were investigated. Laquinimod dampened cytokine release but did not impact NFκB signalling. Read the Editorial Highlight for this article on page 670. © 2016 The Authors. Journal of Neurochemistry published by John Wiley & Sons Ltd on behalf of International Society for Neurochemistry.

Pulse Shaped 8-PSK Bandwidth Efficiency and Spectral Spike Elimination

NASA Technical Reports Server (NTRS)

Tao, Jian-Ping

1998-01-01

The most bandwidth-efficient communication methods are imperative to cope with the congested frequency bands. Pulse shaping methods have excellent effects on narrowing bandwidth and increasing band utilization. The position of the baseband filters for the pulse shaping is crucial. Post-modulation pulse shaping (a low pass filter is located after the modulator) can change signals from constant envelope to non-constant envelope, and non-constant envelope signals through non-linear device (a SSPA or TWT) can further spread the power spectra. Pre-modulation pulse shaping (a filter is located before the modulator) will have constant envelope. These two pulse shaping methods have different effects on narrowing the bandwidth and producing bit errors. This report studied the effect of various pre-modulation pulse shaping filters with respect to bandwidth, spectral spikes and bit error rate. A pre-modulation pulse shaped 8-ary Phase Shift Keying (8PSK) modulation was used throughout the simulations. In addition to traditional pulse shaping filters, such as Bessel, Butterworth and Square Root Raised Cosine (SRRC), other kinds of filters or pulse waveforms were also studied in the pre-modulation pulse shaping method. Simulations were conducted by using the Signal Processing Worksystem (SPW) software package on HP workstations which simulated the power spectral density of pulse shaped 8-PSK signals, end to end system performance and bit error rates (BERS) as a function of Eb/No using pulse shaping in an AWGN channel. These results are compared with the post-modulation pulse shaped 8-PSK results. The simulations indicate traditional pulse shaping filters used in pre-modulation pulse shaping may produce narrower bandwidth, but with worse BER than those in post-modulation pulse shaping. Theory and simulations show pre- modulation pulse shaping could also produce discrete line power spectra (spikes) at regular frequency intervals. These spikes may cause interference with adjacent channel and reduce power efficiency. Some particular pulses (filters), such as trapezoid and pulses with different transits (such as weighted raised cosine transit) were found to reduce bandwidth and not generate spectral spikes. Although a solid state power amplifier (SSPA) was simulated in the non-linear (saturation) region, output power spectra did not spread due to the constant envelope 8-PSK signals.

Effectiveness of an Expert System for Astronaut Assistance on a Sleep Experiment

NASA Technical Reports Server (NTRS)

Heher, Dennis; Callini, Gianluca; Essig, Susanne M.; Young, Laurence R.; Koga, Dennis (Technical Monitor)

1998-01-01

Principal Investigator-in-a-Box ([PI]) is an expert system designed to train and assist astronauts with the performance of an experiment outside their field of expertise, particularly when contact with the Principal Investigators on the ground is limited or impossible. In the current case, [PI] was designed to assist with the calibration and troubleshooting procedures of the Neurolab Sleep and Respiration Experiment during the pre-sleep period of no ground contact. It displays physiological signals in real time during the pre-sleep instrumentation period, and alerts the astronauts when a poor signal quality is detected. Results of the first study indicated a beneficial effect of [PI] and training in reducing anomaly detection time and the number of undetected anomalies. For the in-flight performance, excluding the saturated signals, the expert system had an 84.2% detection accuracy, and the questionnaires filled out by the astronauts showed positive crew reactions to the expert system.

Sensing system for detection and control of deposition on pendant tubes in recovery and power boilers

DOEpatents

Kychakoff, George [Maple Valley, WA; Afromowitz, Martin A [Mercer Island, WA; Hogle, Richard E [Olympia, WA

2008-10-14

A system for detection and control of deposition on pendant tubes in recovery and power boilers includes one or more deposit monitoring sensors operating in infrared regions of about 4 or 8.7 microns and directly producing images of the interior of the boiler, or producing feeding signals to a data processing system for information to enable a distributed control system by which the boilers are operated to operate said boilers more efficiently. The data processing system includes an image pre-processing circuit in which a 2-D image formed by the video data input is captured, and includes a low pass filter for performing noise filtering of said video input. It also includes an image compensation system for array compensation to correct for pixel variation and dead cells, etc., and for correcting geometric distortion. An image segmentation module receives a cleaned image from the image pre-processing circuit for separating the image of the recovery boiler interior into background, pendant tubes, and deposition. It also accomplishes thresholding/clustering on gray scale/texture and makes morphological transforms to smooth regions, and identifies regions by connected components. An image-understanding unit receives a segmented image sent from the image segmentation module and matches derived regions to a 3-D model of said boiler. It derives a 3-D structure the deposition on pendant tubes in the boiler and provides the information about deposits to the plant distributed control system for more efficient operation of the plant pendant tube cleaning and operating systems.

Discrete wavelet-aided delineation of PCG signal events via analysis of an area curve length-based decision statistic.

PubMed

Homaeinezhad, M R; Atyabi, S A; Daneshvar, E; Ghaffari, A; Tahmasebi, M

2010-12-01

The aim of this study is to describe a robust unified framework for segmentation of the phonocardiogram (PCG) signal sounds based on the false-alarm probability (FAP) bounded segmentation of a properly calculated detection measure. To this end, first the original PCG signal is appropriately pre-processed and then, a fixed sample size sliding window is moved on the pre-processed signal. In each slid, the area under the excerpted segment is multiplied by its curve-length to generate the Area Curve Length (ACL) metric to be used as the segmentation decision statistic (DS). Afterwards, histogram parameters of the nonlinearly enhanced DS metric are used for regulation of the α-level Neyman-Pearson classifier for FAP-bounded delineation of the PCG events. The proposed method was applied to all 85 records of Nursing Student Heart Sounds database (NSHSDB) including stenosis, insufficiency, regurgitation, gallop, septal defect, split sound, rumble, murmur, clicks, friction rub and snap disorders with different sampling frequencies. Also, the method was applied to the records obtained from an electronic stethoscope board designed for fulfillment of this study in the presence of high-level power-line noise and external disturbing sounds and as the results, no false positive (FP) or false negative (FN) errors were detected. High noise robustness, acceptable detection-segmentation accuracy of PCG events in various cardiac system conditions, and having no parameters dependency to the acquisition sampling frequency can be mentioned as the principal virtues and abilities of the proposed ACL-based PCG events detection-segmentation algorithm.

Effects of set-size and selective spatial attention on motion processing.

PubMed

Dobkins, K R; Bosworth, R G

2001-05-01

In order to investigate the effects of divided attention and selective spatial attention on motion processing, we obtained direction-of-motion thresholds using a stochastic motion display under various attentional manipulations and stimulus durations (100-600 ms). To investigate divided attention, we compared motion thresholds obtained when a single motion stimulus was presented in the visual field (set-size=1) to those obtained when the motion stimulus was presented amongst three confusable noise distractors (set-size=4). The magnitude of the observed detriment in performance with an increase in set-size from 1 to 4 could be accounted for by a simple decision model based on signal detection theory, which assumes that attentional resources are not limited in capacity. To investigate selective attention, we compared motion thresholds obtained when a valid pre-cue alerted the subject to the location of the to-be-presented motion stimulus to those obtained when no pre-cue was provided. As expected, the effect of pre-cueing was large when the visual field contained noise distractors, an effect we attribute to "noise reduction" (i.e. the pre-cue allows subjects to exclude irrelevant distractors that would otherwise impair performance). In the single motion stimulus display, we found a significant benefit of pre-cueing only at short durations (< or =150 ms), a result that can potentially be explained by a "time-to-orient" hypothesis (i.e. the pre-cue improves performance by eliminating the time it takes to orient attention to a peripheral stimulus at its onset, thereby increasing the time spent processing the stimulus). Thus, our results suggest that the visual motion system can analyze several stimuli simultaneously without limitations on sensory processing per se, and that spatial pre-cueing serves to reduce the effects of distractors and perhaps increase the effective processing time of the stimulus.

Multi-parameter Observations and Validation of Pre-earthquake Atmospheric Signals

NASA Astrophysics Data System (ADS)

Ouzounov, D.; Pulinets, S. A.; Hattori, K.; Mogi, T.; Kafatos, M.

2014-12-01

We are presenting the latest development in multi-sensors observations of short-term pre-earthquake phenomena preceding major earthquakes. We are exploring the potential of pre-seismic atmospheric and ionospheric signals to alert for large earthquakes. To achieve this, we start validating anomalous ionospheric /atmospheric signals in retrospective and prospective modes. The integrated satellite and terrestrial framework (ISTF) is our method for validation and is based on a joint analysis of several physical and environmental parameters (Satellite thermal infrared radiation (OLR), electron concentration in the ionosphere (GPS/TEC), VHF-bands radio waves, radon/ion activities, air temperature and seismicity patterns) that were found to be associated with earthquakes. The science rationale for multidisciplinary analysis is based on concept Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) [Pulinets and Ouzounov, 2011], which explains the synergy of different geospace processes and anomalous variations, usually named short-term pre-earthquake anomalies. Our validation processes consist in two steps: (1) A continuous retrospective analysis preformed over two different regions with high seismicity- Taiwan and Japan for 2003-2009 The retrospective tests (100+ major earthquakes, M>5.9, Taiwan and Japan) show OLR anomalous behavior before all of these events with no false negatives. False alarm ratio for false positives is less then 25%. (2) Prospective testing using multiple parameters with potential for M5.5+ events. The initial testing shows systematic appearance of atmospheric anomalies in advance (days) to the M5.5+ events for Taiwan and Japan (Honshu and Hokkaido areas). Our initial prospective results suggest that our approach show a systematic appearance of atmospheric anomalies, one to several days prior to the largest earthquakes That feature could be further studied and tested for advancing the multi-sensors detection of pre-earthquake atmospheric signals.

An INS/WiFi Indoor Localization System Based on the Weighted Least Squares.

PubMed

Chen, Jian; Ou, Gang; Peng, Ao; Zheng, Lingxiang; Shi, Jianghong

2018-05-07

For smartphone indoor localization, an INS/WiFi hybrid localization system is proposed in this paper. Acceleration and angular velocity are used to estimate step lengths and headings. The problem with INS is that positioning errors grow with time. Using radio signal strength as a fingerprint is a widely used technology. The main problem with fingerprint matching is mismatching due to noise. Taking into account the different shortcomings and advantages, inertial sensors and WiFi from smartphones are integrated into indoor positioning. For a hybrid localization system, pre-processing techniques are used to enhance the WiFi signal quality. An inertial navigation system limits the range of WiFi matching. A Multi-dimensional Dynamic Time Warping (MDTW) is proposed to calculate the distance between the measured signals and the fingerprint in the database. A MDTW-based weighted least squares (WLS) is proposed for fusing multiple fingerprint localization results to improve positioning accuracy and robustness. Using four modes (calling, dangling, handheld and pocket), we carried out walking experiments in a corridor, a study room and a library stack room. Experimental results show that average localization accuracy for the hybrid system is about 2.03 m.

An INS/WiFi Indoor Localization System Based on the Weighted Least Squares

PubMed Central

Chen, Jian; Ou, Gang; Zheng, Lingxiang; Shi, Jianghong

2018-01-01

For smartphone indoor localization, an INS/WiFi hybrid localization system is proposed in this paper. Acceleration and angular velocity are used to estimate step lengths and headings. The problem with INS is that positioning errors grow with time. Using radio signal strength as a fingerprint is a widely used technology. The main problem with fingerprint matching is mismatching due to noise. Taking into account the different shortcomings and advantages, inertial sensors and WiFi from smartphones are integrated into indoor positioning. For a hybrid localization system, pre-processing techniques are used to enhance the WiFi signal quality. An inertial navigation system limits the range of WiFi matching. A Multi-dimensional Dynamic Time Warping (MDTW) is proposed to calculate the distance between the measured signals and the fingerprint in the database. A MDTW-based weighted least squares (WLS) is proposed for fusing multiple fingerprint localization results to improve positioning accuracy and robustness. Using four modes (calling, dangling, handheld and pocket), we carried out walking experiments in a corridor, a study room and a library stack room. Experimental results show that average localization accuracy for the hybrid system is about 2.03 m. PMID:29735960

Analysis for signal-to-noise ratio of hyper-spectral imaging FTIR interferometer

NASA Astrophysics Data System (ADS)

Li, Xun-niu; Zheng, Wei-jian; Lei, Zheng-gang; Wang, Hai-yang; Fu, Yan-peng

2013-08-01

Signal-to-noise Ratio of hyper-spectral imaging FTIR interferometer system plays a decisive role on the performance of the instrument. It is necessary to analyze them in the development process. Based on the simplified target/background model, the energy transfer model of the LWIR hyper-spectral imaging interferometer has been discussed. The noise equivalent spectral radiance (NESR) and its influencing factors of the interferometer system was analyzed, and the signal-to-noise（SNR） was calculated by using the properties of NESR and incident radiance. In a typical application environment, using standard atmospheric model of USA(1976 COESA) as a background, and set a reasonable target/background temperature difference, and take Michelson spatial modulation Fourier Transform interferometer as an example, the paper had calculated the NESR and the SNR of the interferometer system which using the commercially LWIR cooled FPA and UFPA detector. The system noise sources of the instrument were also analyzed in the paper. The results of those analyses can be used to optimize and pre-estimate the performance of the interferometer system, and analysis the applicable conditions of use different detectors. It has important guiding significance for the LWIR interferometer spectrometer design.

Surface Electromyography Signal Processing and Classification Techniques

PubMed Central

Chowdhury, Rubana H.; Reaz, Mamun B. I.; Ali, Mohd Alauddin Bin Mohd; Bakar, Ashrif A. A.; Chellappan, Kalaivani; Chang, Tae. G.

2013-01-01

Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above. PMID:24048337

Vehicle Position Estimation Based on Magnetic Markers: Enhanced Accuracy by Compensation of Time Delays.

PubMed

Byun, Yeun-Sub; Jeong, Rag-Gyo; Kang, Seok-Won

2015-11-13

The real-time recognition of absolute (or relative) position and orientation on a network of roads is a core technology for fully automated or driving-assisted vehicles. This paper presents an empirical investigation of the design, implementation, and evaluation of a self-positioning system based on a magnetic marker reference sensing method for an autonomous vehicle. Specifically, the estimation accuracy of the magnetic sensing ruler (MSR) in the up-to-date estimation of the actual position was successfully enhanced by compensating for time delays in signal processing when detecting the vertical magnetic field (VMF) in an array of signals. In this study, the signal processing scheme was developed to minimize the effects of the distortion of measured signals when estimating the relative positional information based on magnetic signals obtained using the MSR. In other words, the center point in a 2D magnetic field contour plot corresponding to the actual position of magnetic markers was estimated by tracking the errors between pre-defined reference models and measured magnetic signals. The algorithm proposed in this study was validated by experimental measurements using a test vehicle on a pilot network of roads. From the results, the positioning error was found to be less than 0.04 m on average in an operational test.

Vehicle Position Estimation Based on Magnetic Markers: Enhanced Accuracy by Compensation of Time Delays

PubMed Central

Byun, Yeun-Sub; Jeong, Rag-Gyo; Kang, Seok-Won

2015-01-01

The real-time recognition of absolute (or relative) position and orientation on a network of roads is a core technology for fully automated or driving-assisted vehicles. This paper presents an empirical investigation of the design, implementation, and evaluation of a self-positioning system based on a magnetic marker reference sensing method for an autonomous vehicle. Specifically, the estimation accuracy of the magnetic sensing ruler (MSR) in the up-to-date estimation of the actual position was successfully enhanced by compensating for time delays in signal processing when detecting the vertical magnetic field (VMF) in an array of signals. In this study, the signal processing scheme was developed to minimize the effects of the distortion of measured signals when estimating the relative positional information based on magnetic signals obtained using the MSR. In other words, the center point in a 2D magnetic field contour plot corresponding to the actual position of magnetic markers was estimated by tracking the errors between pre-defined reference models and measured magnetic signals. The algorithm proposed in this study was validated by experimental measurements using a test vehicle on a pilot network of roads. From the results, the positioning error was found to be less than 0.04 m on average in an operational test. PMID:26580622

Hydrogen Peroxide and Polyamines Act as Double Edged Swords in Plant Abiotic Stress Responses.

PubMed

Gupta, Kamala; Sengupta, Atreyee; Chakraborty, Mayukh; Gupta, Bhaskar

2016-01-01

The specific genetic changes through which plants adapt to the multitude of environmental stresses are possible because of the molecular regulations in the system. These intricate regulatory mechanisms once unveiled will surely raise interesting questions. Polyamines and hydrogen peroxide have been suggested to be important signaling molecules during biotic and abiotic stresses. Hydrogen peroxide plays a versatile role from orchestrating physiological processes to stress response. It helps to achieve acclimatization and tolerance to stress by coordinating intra-cellular and systemic signaling systems. Polyamines, on the other hand, are low molecular weight polycationic aliphatic amines, which have been implicated in various stress responses. It is quite interesting to note that both hydrogen peroxide and polyamines have a fine line of inter-relation between them since the catabolic pathways of the latter releases hydrogen peroxide. In this review we have tried to illustrate the roles and their multifaceted functions of these two important signaling molecules based on current literature. This review also highlights the fact that over accumulation of hydrogen peroxide and polyamines can be detrimental for plant cells leading to toxicity and pre-mature cell death.

Low-noise front-end electronics for detection of intermediate-frequency weak light signals

NASA Astrophysics Data System (ADS)

Lin, Cunbao; Yan, Shuhua; Du, Zhiguang; Wei, Chunhua; Wang, Guochao

2015-02-01

A novel low-noise front-end electronics was proposed for detection of light signals with intensity about 10 μW and frequency above 2.7 MHz. The direct current (DC) power supply, pre-amplifier and main-amplifier were first designed, simulated and then realized. Small-size components were used to make the power supply small, and the pre-amplifier and main-amplifier were the least capacitors to avoid the phase shift of the signals. The performance of the developed front-end electronics was verified in cross-grating diffraction experiments. The results indicated that the output peak-topeak noise of the +/-5 V DC power supply was about 2 mV, and the total output current was 1.25 A. The signal-to-noise ratio (SNR) of the output signal of the pre-amplifier was about 50 dB, and it increased to nearly 60 dB after the mainamplifier, which means this front-end electronics was especially suitable for using in the phase-sensitive and integrated precision measurement systems.

Structural health monitoring feature design by genetic programming

NASA Astrophysics Data System (ADS)

Harvey, Dustin Y.; Todd, Michael D.

2014-09-01

Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and other high-capital or life-safety critical structures. Conventional data processing involves pre-processing and extraction of low-dimensional features from in situ time series measurements. The features are then input to a statistical pattern recognition algorithm to perform the relevant classification or regression task necessary to facilitate decisions by the SHM system. Traditional design of signal processing and feature extraction algorithms can be an expensive and time-consuming process requiring extensive system knowledge and domain expertise. Genetic programming, a heuristic program search method from evolutionary computation, was recently adapted by the authors to perform automated, data-driven design of signal processing and feature extraction algorithms for statistical pattern recognition applications. The proposed method, called Autofead, is particularly suitable to handle the challenges inherent in algorithm design for SHM problems where the manifestation of damage in structural response measurements is often unclear or unknown. Autofead mines a training database of response measurements to discover information-rich features specific to the problem at hand. This study provides experimental validation on three SHM applications including ultrasonic damage detection, bearing damage classification for rotating machinery, and vibration-based structural health monitoring. Performance comparisons with common feature choices for each problem area are provided demonstrating the versatility of Autofead to produce significant algorithm improvements on a wide range of problems.

Comparison of the impedance cardiogram with continuous wave radar using body-contact antennas.

PubMed

Buxi, Dilpreet; Dugar, Rahul; Redoute, Jean-Michel; Yuce, Mehmet Rasit

2017-07-01

This paper describes a continuous wave (CW) radar system with body-contact antennas and basic signal processing. The goal is to assess the signals' reproducibility across different subjects as well as a respiration cycle. Radar signals using body-contact antennas with a carrier frequency of 868 MHz are used to acquire the cardiac activity at the sternum. The radar I and Q channel signals are combined to form their magnitude. Signals are collected from six healthy males during paced breathing conditions. The electrocardiogram (ECG) and impedance cardiogram (ICG) signals are acquired simultaneously as reference. The chosen feature in the radar signal is the maximum of its second derivative, which is closest to the ICG B-point. The median and mean absolute errors in pre-ejection period (PEP) in milliseconds between the ICG's B-point and chosen feature in the radar signal range from -6-119.7 ms and 7.8-62.3 ms for all subjects. The results indicate that a reproducible radar signal is obtained from all six subjects. More work is needed on understanding the origin of the radar signals using ultrasound as a comparison.

Signal analysis and radioholographic methods for airborne radio occultations

NASA Astrophysics Data System (ADS)

Wang, Kuo-Nung

Global Positioning System (GPS) radio occultation (RO) is an atmospheric sounding technique utilizing the change in propagation direction and delay of the GPS signal to measure refractivity, which provides information on temperature and humidity. The GPS-RO technique is now operational on several Low Earth Orbiting (LEO) satellite missions. Nevertheless, when observing localized transient events, such as tropical storms, current LEO satellite systems cannot provide sufficiently high temporal and spatial resolution soundings. An airborne RO (ARO) system has therefore been developed for localized GPS-RO campaigns. The open-loop (OL) tracking in post-processing is used to cross-correlates the received Global Navigation Satellite System (GNSS) signal with an internally generated local carrier signal predicted from a Doppler model and extract the atmospheric refractivity information. OL tracking also allows robust processing of rising GPS signals using backward tracking, which will double the observed occultation event numbers. RO signals in the lower troposphere are adversely affected by rapid phase accelerations and severe signal power fading, however. The negative bias caused by low signal-to-noise ratio (SNR) and multipath ray propagation limits the depth of tracking in the atmosphere. Therefore, we developed a model relating the SNR to the variance in the residual phase of the observed signal produced from OL tracking, and its applicability to airborne data is demonstrated. We then apply this model to set a threshold on refractivity retrieval, based upon the cumulative unwrapping error bias, to determine the altitude limit for reliable signal tracking. To enhance the SNR and decrease the unwrapping error rate, the CIRA-Q climatological model and signal residual phase pre-filtering are utilized to process the ARO residual phase. This more accurately modeled phase and less noisy received signal are shown to greatly reduce the bias caused by unwrapping error at lower altitude. On the other hand, to process the superimposed signal in the lower troposphere with its highly variable moisture distribution, Radio-Holographic (RH) methods such as Phase Matching (PM) have been adapted for ARO platforms to untangle the bending angle of each signal path. Under the assumption of spherically symmetric atmosphere, ARO PM can identify different subsignals using the Method of the Stationary Phase (MSP) and determine the arrival angle for each impact parameter. As a result, each subsignal can be distinguished and its corresponding bending angle can be retrieved without producing a negative bias. The refractivity retrieval results using ARO PM are compared to those using the traditional Geometrical Optics (GO) method. The improvements are shown and discussed in the dissertation. We applied these new methods to the received ARO data collected by the GNSS instrument system for multistatic and occultation sensing (GISMOS) in the 2010 PREDepression Investigation of Cloud systems (PREDICT) campaign. A data set of 5 research flights with 57 occultation events during the formation stage of the Hurricane Karl are processed and analyzed. In this research, the refractivity fractional difference with ERA-I model can be maintained at an average 2% above a height of 2km with a climatological model and ARO PM. Compared to the traditional geometrical optics (GO) method without climatological method assistance, the new ARO processing can effectively decrease the refractivity negative bias and significantly improve the retrieval depth of ARO.

Comparing Binaural Pre-processing Strategies III

PubMed Central

Warzybok, Anna; Ernst, Stephan M. A.

2015-01-01

A comprehensive evaluation of eight signal pre-processing strategies, including directional microphones, coherence filters, single-channel noise reduction, binaural beamformers, and their combinations, was undertaken with normal-hearing (NH) and hearing-impaired (HI) listeners. Speech reception thresholds (SRTs) were measured in three noise scenarios (multitalker babble, cafeteria noise, and single competing talker). Predictions of three common instrumental measures were compared with the general perceptual benefit caused by the algorithms. The individual SRTs measured without pre-processing and individual benefits were objectively estimated using the binaural speech intelligibility model. Ten listeners with NH and 12 HI listeners participated. The participants varied in age and pure-tone threshold levels. Although HI listeners required a better signal-to-noise ratio to obtain 50% intelligibility than listeners with NH, no differences in SRT benefit from the different algorithms were found between the two groups. With the exception of single-channel noise reduction, all algorithms showed an improvement in SRT of between 2.1 dB (in cafeteria noise) and 4.8 dB (in single competing talker condition). Model predictions with binaural speech intelligibility model explained 83% of the measured variance of the individual SRTs in the no pre-processing condition. Regarding the benefit from the algorithms, the instrumental measures were not able to predict the perceptual data in all tested noise conditions. The comparable benefit observed for both groups suggests a possible application of noise reduction schemes for listeners with different hearing status. Although the model can predict the individual SRTs without pre-processing, further development is necessary to predict the benefits obtained from the algorithms at an individual level. PMID:26721922

Indirectly sensing accelerator beam currents for limiting maximum beam current magnitude

DOEpatents

Bogaty, J.M.; Clifft, B.E.; Bollinger, L.M.

1995-08-08

A beam current limiter is disclosed for sensing and limiting the beam current in a particle accelerator, such as a cyclotron or linear accelerator, used in scientific research and medical treatment. A pair of independently operable capacitive electrodes sense the passage of charged particle bunches to develop an RF signal indicative of the beam current magnitude produced at the output of a bunched beam accelerator. The RF signal produced by each sensing electrode is converted to a variable DC voltage indicative of the beam current magnitude. The variable DC voltages thus developed are compared to each other to verify proper system function and are further compared to known references to detect beam currents in excess of pre-established limits. In the event of a system malfunction, or if the detected beam current exceeds pre-established limits, the beam current limiter automatically inhibits further accelerator operation. A high Q tank circuit associated with each sensing electrode provides a narrow system bandwidth to reduce noise and enhance dynamic range. System linearity is provided by injecting, into each sensing electrode, an RF signal that is offset from the bunching frequency by a pre-determined beat frequency to ensure that subsequent rectifying diodes operate in a linear response region. The system thus provides a large dynamic range in combination with good linearity. 6 figs.

Indirectly sensing accelerator beam currents for limiting maximum beam current magnitude

DOEpatents

Bogaty, John M.; Clifft, Benny E.; Bollinger, Lowell M.

1995-01-01

A beam current limiter for sensing and limiting the beam current in a particle accelerator, such as a cyclotron or linear accelerator, used in scientific research and medical treatment. A pair of independently operable capacitive electrodes sense the passage of charged particle bunches to develop an RF signal indicative of the beam current magnitude produced at the output of a bunched beam accelerator. The RF signal produced by each sensing electrode is converted to a variable DC voltage indicative of the beam current magnitude. The variable DC voltages thus developed are compared to each other to verify proper system function and are further compared to known references to detect beam currents in excess of pre-established limits. In the event of a system malfunction, or if the detected beam current exceeds pre-established limits, the beam current limiter automatically inhibits further accelerator operation. A high Q tank circuit associated with each sensing electrode provides a narrow system bandwidth to reduce noise and enhance dynamic range. System linearity is provided by injecting, into each sensing electrode, an RF signal that is offset from the bunching frequency by a pre-determined beat frequency to ensure that subsequent rectifying diodes operate in a linear response region. The system thus provides a large dynamic range in combination with good linearity.

Selective catalytic reduction system and process using a pre-sulfated zirconia binder

DOEpatents

Sobolevskiy, Anatoly; Rossin, Joseph A.

2010-06-29

A selective catalytic reduction (SCR) process with a palladium catalyst for reducing NOx in a gas, using hydrogen as a reducing agent is provided. The process comprises contacting the gas stream with a catalyst system, the catalyst system comprising (ZrO.sub.2)SO.sub.4, palladium, and a pre-sulfated zirconia binder. The inclusion of a pre-sulfated zirconia binder substantially increases the durability of a Pd-based SCR catalyst system. A system for implementing the disclosed process is further provided.

Simulation-based robust optimization for signal timing and setting.

DOT National Transportation Integrated Search

2009-12-30

The performance of signal timing plans obtained from traditional approaches for : pre-timed (fixed-time or actuated) control systems is often unstable under fluctuating traffic : conditions. This report develops a general approach for optimizing the ...

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.

RFI Detection and Mitigation using Independent Component Analysis as a Pre-Processor

NASA Technical Reports Server (NTRS)

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

2016-01-01

Radio-frequency interference (RFI) has negatively impacted scientific measurements of passive remote sensing satellites. This has been observed in the L-band radiometers Soil Moisture and Ocean Salinity (SMOS), Aquarius and more recently, Soil Moisture Active Passive (SMAP). RFI has also been observed at higher frequencies such as K band. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements. This work explores the use of Independent Component Analysis (ICA) as a blind source separation (BSS) technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

Modeling Sound Processing in Cochlear Nuclei

NASA Astrophysics Data System (ADS)

Meddis, Ray

2003-03-01

The cochlear nucleus is an obligatory relay nucleus between the ear and the rest of the brain. It consists of many different types of neurons each responding differently to the same stimulus. Much is known about the wiring diagram of the system but it has so far proved difficult to characterise the signal processing that is going on or what purpose it serves. The solution to this problem is a pre-requisite of any attempt to produce a practical electronic simulation that exploits the brain's unique capacity to recognise the significance of acoustic events and generate appropriate responses. This talk will explain the different types of neural cell and specify hypotheses as to their various functions. Cell-types vary in terms of their size and shape as well as the number and type of minute electrical currents that flow across the cell membranes. Computer models will also be used to illustrate how the physical substrate (the wet-ware) is used to achieve its signal-processing goals.

Microprocessor-based multichannel flutter monitor using dynamic strain gage signals

NASA Technical Reports Server (NTRS)

Smalley, R. R.

1976-01-01

Two microprocessor-based multichannel monitors for monitoring strain gage signals during aerodynamic instability (flutter) testing in production type turbojet engines were described. One system monitors strain gage signals in the time domain and gives an output indication whenever the signal amplitude of any gage exceeds a pre-set alarm or abort level for that particular gage. The second system monitors the strain gage signals in the frequency domain and therefore is able to use both the amplitude and frequency information. Thus, an alarm signal is given whenever the spectral content of the strain gage signal exceeds, at any point, its corresponding amplitude vs. frequency limit profiles. Each system design is described with details on design trade-offs, hardware, software, and operating experience.

Toward Expanding Tremor Observations in the Northern San Andreas Fault System in the 1990s

NASA Astrophysics Data System (ADS)

Damiao, L. G.; Dreger, D. S.; Nadeau, R. M.; Taira, T.; Guilhem, A.; Luna, B.; Zhang, H.

2015-12-01

The connection between tremor activity and active fault processes continues to expand our understanding of deep fault zone properties and deformation, the tectonic process, and the relationship of tremor to the occurrence of larger earthquakes. Compared to tremors in subduction zones, known tremor signals in California are ~5 to ~10 smaller in amplitude and duration. These characteristics, in addition to scarce geographic coverage, lack of continuous data (e.g., before mid-2001 at Parkfield), and absence of instrumentation sensitive enough to monitor these events have stifled tremor detection. The continuous monitoring of these events over a relatively short time period in limited locations may lead to a parochial view of the tremor phenomena and its relationship to fault, tectonic, and earthquake processes. To help overcome this, we have embarked on a project to expand the geographic and temporal scope of tremor observation along the Northern SAF system using available continuous seismic recordings from a broad array of 100s of surface seismic stations from multiple seismic networks. Available data for most of these stations also extends back into the mid-1990s. Processing and analysis of tremor signal from this large and low signal-to-noise dataset requires a heavily automated, data-science type approach and specialized techniques for identifying and extracting reliable data. We report here on the automated, envelope based methodology we have developed. We finally compare our catalog results with pre-existing tremor catalogs in the Parkfield area.

Emotional stress recognition using a new fusion link between electroencephalogram and peripheral signals

PubMed Central

Hosseini, Seyyed Abed; Khalilzadeh, Mohammad Ali; Naghibi-Sistani, Mohammad Bagher; Homam, Seyyed Mehran

2015-01-01

Background: This paper proposes a new emotional stress assessment system using multi-modal bio-signals. Electroencephalogram (EEG) is the reflection of brain activity and is widely used in clinical diagnosis and biomedical research. Methods: We design an efficient acquisition protocol to acquire the EEG signals in five channels (FP1, FP2, T3, T4 and Pz) and peripheral signals such as blood volume pulse, skin conductance (SC) and respiration, under images induction (calm-neutral and negatively excited) for the participants. The visual stimuli images are selected from the subset International Affective Picture System database. The qualitative and quantitative evaluation of peripheral signals are used to select suitable segments of EEG signals for improving the accuracy of signal labeling according to emotional stress states. After pre-processing, wavelet coefficients, fractal dimension, and Lempel-Ziv complexity are used to extract the features of the EEG signals. The vast number of features leads to the problem of dimensionality, which is solved using the genetic algorithm as a feature selection method. Results: The results show that the average classification accuracy is 89.6% for two categories of emotional stress states using the support vector machine (SVM). Conclusion: This is a great improvement in results compared to other similar researches. We achieve a noticeable improvement of 11.3% in accuracy using SVM classifier, in compared to previous studies. Therefore, a new fusion between EEG and peripheral signals are more robust in comparison to the separate signals. PMID:26622979

Emotional stress recognition using a new fusion link between electroencephalogram and peripheral signals.

PubMed

Hosseini, Seyyed Abed; Khalilzadeh, Mohammad Ali; Naghibi-Sistani, Mohammad Bagher; Homam, Seyyed Mehran

2015-07-06

This paper proposes a new emotional stress assessment system using multi-modal bio-signals. Electroencephalogram (EEG) is the reflection of brain activity and is widely used in clinical diagnosis and biomedical research. We design an efficient acquisition protocol to acquire the EEG signals in five channels (FP1, FP2, T3, T4 and Pz) and peripheral signals such as blood volume pulse, skin conductance (SC) and respiration, under images induction (calm-neutral and negatively excited) for the participants. The visual stimuli images are selected from the subset International Affective Picture System database. The qualitative and quantitative evaluation of peripheral signals are used to select suitable segments of EEG signals for improving the accuracy of signal labeling according to emotional stress states. After pre-processing, wavelet coefficients, fractal dimension, and Lempel-Ziv complexity are used to extract the features of the EEG signals. The vast number of features leads to the problem of dimensionality, which is solved using the genetic algorithm as a feature selection method. The results show that the average classification accuracy is 89.6% for two categories of emotional stress states using the support vector machine (SVM). This is a great improvement in results compared to other similar researches. We achieve a noticeable improvement of 11.3% in accuracy using SVM classifier, in compared to previous studies. Therefore, a new fusion between EEG and peripheral signals are more robust in comparison to the separate signals.

Signal Statistics and Maximum Likelihood Sequence Estimation in Intensity Modulated Fiber Optic Links Containing a Single Optical Pre-amplifier.

PubMed

Alić, Nikola; Papen, George; Saperstein, Robert; Milstein, Laurence; Fainman, Yeshaiahu

2005-06-13

Exact signal statistics for fiber-optic links containing a single optical pre-amplifier are calculated and applied to sequence estimation for electronic dispersion compensation. The performance is evaluated and compared with results based on the approximate chi-square statistics. We show that detection in existing systems based on exact statistics can be improved relative to using a chi-square distribution for realistic filter shapes. In contrast, for high-spectral efficiency systems the difference between the two approaches diminishes, and performance tends to be less dependent on the exact shape of the filter used.

Discrete fourier transform (DFT) analysis for applications using iterative transform methods

NASA Technical Reports Server (NTRS)

Dean, Bruce H. (Inventor)

2012-01-01

According to various embodiments, a method is provided for determining aberration data for an optical system. The method comprises collecting a data signal, and generating a pre-transformation algorithm. The data is pre-transformed by multiplying the data with the pre-transformation algorithm. A discrete Fourier transform of the pre-transformed data is performed in an iterative loop. The method further comprises back-transforming the data to generate aberration data.

Convolutional neural networks for event-related potential detection: impact of the architecture.

PubMed

Cecotti, H

2017-07-01

The detection of brain responses at the single-trial level in the electroencephalogram (EEG) such as event-related potentials (ERPs) is a difficult problem that requires different processing steps to extract relevant discriminant features. While most of the signal and classification techniques for the detection of brain responses are based on linear algebra, different pattern recognition techniques such as convolutional neural network (CNN), as a type of deep learning technique, have shown some interests as they are able to process the signal after limited pre-processing. In this study, we propose to investigate the performance of CNNs in relation of their architecture and in relation to how they are evaluated: a single system for each subject, or a system for all the subjects. More particularly, we want to address the change of performance that can be observed between specifying a neural network to a subject, or by considering a neural network for a group of subjects, taking advantage of a larger number of trials from different subjects. The results support the conclusion that a convolutional neural network trained on different subjects can lead to an AUC above 0.9 by using an appropriate architecture using spatial filtering and shift invariant layers.

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.

Registration in a radon system of signals related to the Tohoku Earthquake

NASA Astrophysics Data System (ADS)

Steinitz, Gideon; Piatibratova, Oksana; Kotlarsky, Peter

2013-04-01

The behavior of radon (Rn-222) within confined volumes of air is examined experimentally at the GSI (Jerusalem) since several years. In these experiments a relatively high level of radon is maintained by diffusion from a source via a tube and radiation from it is measured using nuclear detectors. In difference with the expected, nuclear radiation from the radon (progeny) shows: a) temporal variations (signals) spanning annual to daily scale; b) directionality of the nuclear radiation reflected as inverse signal patterns in the east-west versus north-south directions. The experimental setup at the GSI lab consists of a leak tight stainless steel (SS) canister (3.53 l) fed with radon by diffusing via SS tube (0.8 m) from a commercial source (RaCl2; 103 kBq). Four identical gamma detectors (2×2") were placed around its central horizontal plane of the canister, at the primary geographic directions, and a further detector (36×76 mm) was placed along the vertical axis of the canister. Count rates (1-minute intervals) were acquired by a datalogger. The system was used in this configuration in a series of experiments conducted from May 2009 to June 2012. An experiment was operating from 30.1.2011 to 22.3.11. The host gas in this experiment was argon at a pressure of ~1 atmosphere. Distinctive short term periodic (STP) signals with periods of 2-3 hours (frequencies in the range of 9-12 CPD) occur in a time interval of three days in association with the Tohoku earthquake (TE; 11.3.2011) and possibly also with its pre-shock. The STP signals occur from around 6 hours prior to the TE and are maintained to around 48 hours after the TE. These signals are observed at all five sensors and are superimposed on the DR signals with relative amplitudes of around 20%. They exhibit differing forms and phase at the different sensors, located at different directions around the canister. The pattern is similar but not identical to the spatial manifestation of form and phase of the DR signal in such experiments, indicating a communality of the driving mechanism. Similar short term signals have not been encountered in other experiments using this configuration, nor at any of the other configurations. Both DR and STP signals are due neither to mechanical nor to local environmental influences on the experimental system. The DR signals have recently been interpreted to be due to a remote influence on the radon system, possible by a component in solar irradiance. Concerning the TE the implications are: 1. The overall progression of the TE (Mw=9) event is also associated with a non-mechanical geodynamic process which is reflected by nuclear radiation features of radon in air. This process is modifying (superimposed) the driver of the primary DR signal of the radon system. 2. The influencing process is operating at a global scale, but at this stage it remains open whether the effect is transferred to the experimental setup via the solid earth and/or the atmosphere. 3. Detection of such phenomena is possible in radon systems of specific configuration the parameters of which are so far undetermined. 4. The possibility is raised that a pre-cursor of the TE has been detected. Concerning the radon system the implications are: 1. Results obtained by the GSI group indicate that nuclear radiation from radon (and progeny) inside a confined volume of air varies spatially and temporally at time scales from annually to daily. The geophysical drivers of these signals are unclear at this stage. The new experimental results demonstrate that the same radon system is responding to further geophysical drivers operating at a time scale of 2-3 hours. 2. The results further demonstrate the potential of investigations utilizing enhanced radon levels within confined volumes for detection of a new type of time varying geophysical phenomena. References: Steinitz, G., Piatibratova, O., Kotlarsky, P., 2011. Possible effect of solar tides on radon signals. Journal of Environmental Radioactivity, 102, 749-765. doi: 10.1016/j.jenvrad.2011.04.002. Sturrock, P.A., Steinitz, G., Fischbach, E., Javorsek, D. and Jenkins, J.H., 2012. Analysis of Gamma Radiation from a Radon Source: Indications of a Solar Influence. Journal of Astroparticle Physics, 35/1, 18-25.

Xanthomonas campestris cell-cell signalling molecule DSF (diffusible signal factor) elicits innate immunity in plants and is suppressed by the exopolysaccharide xanthan.

PubMed

Kakkar, Akanksha; Nizampatnam, Narasimha Rao; Kondreddy, Anil; Pradhan, Binod Bihari; Chatterjee, Subhadeep

2015-11-01

Several secreted and surface-associated conserved microbial molecules are recognized by the host to mount the defence response. One such evolutionarily well-conserved bacterial process is the production of cell-cell signalling molecules which regulate production of multiple virulence functions by a process known as quorum sensing. Here it is shown that a bacterial fatty acid cell-cell signalling molecule, DSF (diffusible signal factor), elicits innate immunity in plants. The DSF family of signalling molecules are highly conserved among many phytopathogenic bacteria belonging to the genus Xanthomonas as well as in opportunistic animal pathogens. Using Arabidopsis, Nicotiana benthamiana, and rice as model systems, it is shown that DSF induces a hypersensitivity reaction (HR)-like response, programmed cell death, the accumulation of autofluorescent compounds, hydrogen peroxide production, and the expression of the PATHOGENESIS-RELATED1 (PR-1) gene. Furthermore, production of the DSF signalling molecule in Pseudomonas syringae, a non-DSF-producing plant pathogen, induces the innate immune response in the N. benthamiana host plant and also affects pathogen growth. By pre- and co-inoculation of DSF, it was demonstrated that the DSF-induced plant defence reduces disease severity and pathogen growth in the host plant. In this study, it was further demonstrated that wild-type Xanthomonas campestris suppresses the DSF-induced innate immunity by secreting xanthan, the main component of extracellular polysaccharide. The results indicate that plants have evolved to recognize a widely conserved bacterial communication system and may have played a role in the co-evolution of host recognition of the pathogen and the communication machinery. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Xanthomonas campestris cell–cell signalling molecule DSF (diffusible signal factor) elicits innate immunity in plants and is suppressed by the exopolysaccharide xanthan

PubMed Central

Kakkar, Akanksha; Nizampatnam, Narasimha Rao; Kondreddy, Anil; Pradhan, Binod Bihari; Chatterjee, Subhadeep

2015-01-01

Several secreted and surface-associated conserved microbial molecules are recognized by the host to mount the defence response. One such evolutionarily well-conserved bacterial process is the production of cell–cell signalling molecules which regulate production of multiple virulence functions by a process known as quorum sensing. Here it is shown that a bacterial fatty acid cell–cell signalling molecule, DSF (diffusible signal factor), elicits innate immunity in plants. The DSF family of signalling molecules are highly conserved among many phytopathogenic bacteria belonging to the genus Xanthomonas as well as in opportunistic animal pathogens. Using Arabidopsis, Nicotiana benthamiana, and rice as model systems, it is shown that DSF induces a hypersensitivity reaction (HR)-like response, programmed cell death, the accumulation of autofluorescent compounds, hydrogen peroxide production, and the expression of the PATHOGENESIS-RELATED1 (PR-1) gene. Furthermore, production of the DSF signalling molecule in Pseudomonas syringae, a non-DSF-producing plant pathogen, induces the innate immune response in the N. benthamiana host plant and also affects pathogen growth. By pre- and co-inoculation of DSF, it was demonstrated that the DSF-induced plant defence reduces disease severity and pathogen growth in the host plant. In this study, it was further demonstrated that wild-type Xanthomonas campestris suppresses the DSF-induced innate immunity by secreting xanthan, the main component of extracellular polysaccharide. The results indicate that plants have evolved to recognize a widely conserved bacterial communication system and may have played a role in the co-evolution of host recognition of the pathogen and the communication machinery. PMID:26248667

49 CFR 234.261 - Highway traffic signal pre-emption.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Maintenance, Inspection, and Testing Inspections and Tests § 234.261 Highway traffic signal pre-emption. Highway traffic signal pre-emption interconnections, for which a railroad has maintenance responsibility... 49 Transportation 4 2010-10-01 2010-10-01 false Highway traffic signal pre-emption. 234.261...

49 CFR 234.261 - Highway traffic signal pre-emption.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Maintenance, Inspection, and Testing Inspections and Tests § 234.261 Highway traffic signal pre-emption. Highway traffic signal pre-emption interconnections, for which a railroad has maintenance responsibility... 49 Transportation 4 2011-10-01 2011-10-01 false Highway traffic signal pre-emption. 234.261...

Signal processing techniques for the U.S. Army Research Laboratory stepped frequency ultra-wideband radar

NASA Astrophysics Data System (ADS)

Nguyen, Lam

2017-05-01

The U.S. Army Research Laboratory (ARL) recently designed and tested a new prototype radar, the Spectrally Agile Frequency-Incrementing Reconfigurable (SAFIRE) radar system, based on a stepped-frequency architecture to address issues associated with our previous impulse-based radars. This is a low-frequency ultra-wideband (UWB) radar with frequencies spanning from 300 to 2000 MHz. Mounted on a vehicle, the radar can be configured in either sidelooking or forward-looking synthetic aperture radar (SAR) mode. We recently conducted our first experiment at Yuma Proving Grounds (YPG). This paper summarizes the radar configurations, parameters, and SAR geometry. The radar data and other noise sources, to include the self-interference signals and radio-frequency interference (RFI) noise sources, are presented and characterized in both the raw (pre-focus) and SAR imagery domains. This paper also describes our signal processing techniques for extracting noise from radar data, as well as the SAR imaging algorithms for forming SAR imagery in both forward- and side-looking modes. Finally, this paper demonstrates our spectral recovery technique and results for a radar operating in a spectrally restricted environment.

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.

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

Active elimination of radio frequency interference for improved signal-to-noise ratio for in-situ NMR experiments in strong magnetic field gradients

NASA Astrophysics Data System (ADS)

Ibrahim, M.; Pardi, C. I.; Brown, T. W. C.; McDonald, P. J.

2018-02-01

Improvement in the signal-to-noise ratio of Nuclear Magnetic Resonance (NMR) systems may be achieved either by increasing the signal amplitude or by decreasing the noise. The noise has multiple origins - not all of which are strictly "noise": incoherent thermal noise originating in the probe and pre-amplifiers, probe ring down or acoustic noise and coherent externally broadcast radio frequency transmissions. The last cannot always be shielded in open access experiments. In this paper, we show that pulsed, low radio-frequency data communications are a significant source of broadcast interference. We explore two signal processing methods of de-noising short T2∗ NMR experiments corrupted by these communications: Linear Predictive Coding (LPC) and the Discrete Wavelet Transform (DWT). Results are shown for numerical simulations and experiments conducted under controlled conditions with pseudo radio frequency interference. We show that both the LPC and DWT methods have merit.

Self-enforcing Feedback Activation between BCL6 and Pre-B Cell Receptor Signaling Defines a Distinct Subtype of Acute Lymphoblastic Leukemia

PubMed Central

Geng, Huimin; Hurtz, Christian; Lenz, Kyle B.; Chen, Zhengshan; Baumjohann, Dirk; Thompson, Sarah; Goloviznina, Natalya; Chen, Wei-Yi; Huan, Jianya; LaTocha, Dorian; Ballabio, Erica; Xiao, Gang; Lee, Jae-Woong; Deucher, Anne; Qi, Zhongxia; Park, Eugene; Huang, Chuanxin; Nahar, Rahul; Kweon, Soo-Mi; Shojaee, Seyedmehdi; Chan, Lai N.; Yu, Jingwei; Kornblau, Steven M.; Bijl, Janetta J.; Ye, B. Hilda; Ansel, Mark; Paietta, Elisabeth; Melnick, Ari; Hunger, Stephen P.; Kurre, Peter; Tyner, Jeffrey W.; Loh, Mignon L.; Roeder, Robert G.; Druker, Brian J.; Burger, Jan. A.; Milne, Thomas A.; Chang, Bill H.; Müschen, Markus

2015-01-01

SUMMARY Studying 830 pre-B ALL cases from four clinical trials, we found that human ALL can be divided into two fundamentally distinct subtypes based on pre-BCR function. While absent in the majority of ALL cases, tonic pre-BCR signaling was found in 112 cases (13.5%). In these cases, tonic pre-BCR signaling induced activation of BCL6, which in turn increased pre-BCR signaling output at the transcriptional level. Interestingly, inhibition of pre-BCR-related tyrosine kinases reduced constitutive BCL6 expression and selectively killed patient-derived pre-BCR+ ALL cells. These findings identify a genetically and phenotypically distinct subset of human ALL that critically depends on tonic pre-BCR signaling. In vivo treatment studies suggested that pre-BCR tyrosine kinase inhibitors are useful for the treatment of patients with pre-BCR+ ALL. PMID:25759025

Nonlinear Complexity Analysis of Brain fMRI Signals in Schizophrenia

PubMed Central

Sokunbi, Moses O.; Gradin, Victoria B.; Waiter, Gordon D.; Cameron, George G.; Ahearn, Trevor S.; Murray, Alison D.; Steele, Douglas J.; Staff, Roger T.

2014-01-01

We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H). 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV) criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI data of both groups of participants were pre-processed, the entropy characterized and the Hurst exponent extracted. Whole brain entropy and H maps of the groups were generated and analysed. The results after adjusting for age and sex differences together show that patients with schizophrenia exhibited higher complexity than healthy controls, at mean whole brain and regional levels. Also, both Sample entropy and Hurst exponent agree that patients with schizophrenia have more complex fMRI signals than healthy controls. These results suggest that schizophrenia is associated with more complex signal patterns when compared to healthy controls, supporting the increase in complexity hypothesis, where system complexity increases with age or disease, and also consistent with the notion that schizophrenia is characterised by a dysregulation of the nonlinear dynamics of underlying neuronal systems. PMID:24824731

Pre-Lingual Communication and Attachment Behavior.

ERIC Educational Resources Information Center

Modarressi, Taghi; McCulloch, Duncan

Infant's crying may have an important mediating role in the formation of attachment behavior. The earliest vocalizations are discussed in terms of an acoustic communications model in which the baby's vocal repertoire becomes incorporated into a closed-loop, feedback system with his mother. Certain pre-lingual "signals" may be associated with those…

Layer by layer: complex analysis with OCT technology

NASA Astrophysics Data System (ADS)

Florin, Christian

2017-03-01

Standard visualisation systems capture two- dimensional images and need more or less fast image processing systems. Now, the ASP Array (Actives sensor pixel array) opens a new world in imaging. On the ASP array, each pixel is provided with its own lens and with its own signal pre-processing. The OCT technology works in "real time" with highest accuracy. In the ASP array systems functionalities of the data acquisition and signal processing are even integrated onto the "pixel level". For the extraction of interferometric features, the time-of-flight principle (TOF) is used. The ASP architecture offers the demodulation of the optical signal within a pixel with up to 100 kHz and the reconstruction of the amplitude and its phase. The dynamics of image capture with the ASP array is higher by two orders of magnitude in comparison with conventional image sensors!!! The OCT- Technology allows a topographic imaging in real time with an extremely high geometric spatial resolution. The optical path length is generated by an axial movement of the reference mirror. The amplitude-modulated optical signal and the carrier frequency are proportional to the scan rate and contains the depth information. Each maximum of the signal envelope corresponds to a reflection (or scattering) within a sample. The ASP array produces at same time 300 * 300 axial Interferorgrams which touch each other on all sides. The signal demodulation for detecting the envelope is not limited by the frame rate of the ASP array in comparison to standard OCT systems. If an optical signal arrives to a pixel of the ASP Array an electrical signal is generated. The background is faded to saturation of pixels by high light intensity to avoid. The sampled signal is integrated continuously multiplied by a signal of the same frequency and two paths whose phase is shifted by 90 degrees from each other are averaged. The outputs of the two paths are routed to the PC, where the envelope amplitude and the phase calculate a three-dimensional tomographic image. For 3D measuring technique specially designed ASP- arrays with a very high image rate are available. If ASP- Arrays are coupled with the OCT method, layer thicknesses can be determined without contact, sealing seams can be inspected or geometrical shapes can be measured. From a stack of hundreds of single OCT images, interesting images can be selected and fed to the computer to analyse them.

Intracortical multiplication of thalamocortical signals in mouse auditory cortex.

PubMed

Li, Ling-yun; Li, Ya-tang; Zhou, Mu; Tao, Huizhong W; Zhang, Li I

2013-09-01

Cortical processing of sensory information begins with the transformation of thalamically relayed signals. We optogenetically silenced intracortical circuits to isolate thalamic inputs to layer 4 neurons and found that intracortical excitation linearly amplified thalamocortical responses underlying frequency and direction selectivity, with spectral range and tuning preserved, and prolonged the response duration. This signal pre-amplification and prolongation enhanced the salience of thalamocortically relayed information and ensured its robust, faithful and more persistent representation.

Data acquisition and processing in the ATLAS tile calorimeter phase-II upgrade demonstrator

NASA Astrophysics Data System (ADS)

Valero, A.; Tile Calorimeter System, ATLAS

2017-10-01

The LHC has planned a series of upgrades culminating in the High Luminosity LHC which will have an average luminosity 5-7 times larger than the nominal Run 2 value. The ATLAS Tile Calorimeter will undergo an upgrade to accommodate the HL-LHC parameters. The TileCal readout electronics will be redesigned, introducing a new readout strategy. A Demonstrator program has been developed to evaluate the new proposed readout architecture and prototypes of all the components. In the Demonstrator, the detector data received in the Tile PreProcessors (PPr) are stored in pipeline buffers and upon the reception of an external trigger signal the data events are processed, packed and readout in parallel through the legacy ROD system, the new Front-End Link eXchange system and an ethernet connection for monitoring purposes. This contribution describes in detail the data processing and the hardware, firmware and software components of the TileCal Demonstrator readout system.

Experimental phase synchronization detection in non-phase coherent chaotic systems by using the discrete complex wavelet approach

NASA Astrophysics Data System (ADS)

Ferreira, Maria Teodora; Follmann, Rosangela; Domingues, Margarete O.; Macau, Elbert E. N.; Kiss, István Z.

2017-08-01

Phase synchronization may emerge from mutually interacting non-linear oscillators, even under weak coupling, when phase differences are bounded, while amplitudes remain uncorrelated. However, the detection of this phenomenon can be a challenging problem to tackle. In this work, we apply the Discrete Complex Wavelet Approach (DCWA) for phase assignment, considering signals from coupled chaotic systems and experimental data. The DCWA is based on the Dual-Tree Complex Wavelet Transform (DT-CWT), which is a discrete transformation. Due to its multi-scale properties in the context of phase characterization, it is possible to obtain very good results from scalar time series, even with non-phase-coherent chaotic systems without state space reconstruction or pre-processing. The method correctly predicts the phase synchronization for a chemical experiment with three locally coupled, non-phase-coherent chaotic processes. The impact of different time-scales is demonstrated on the synchronization process that outlines the advantages of DCWA for analysis of experimental data.

Pre-seismic geomagnetic and ionosphere signatures related to the Mw5.7 earthquake occurred in Vrancea zone on September 24, 2016

NASA Astrophysics Data System (ADS)

Stanica, Dragos Armand; Stanica, Dumitru; Błęcki, Jan; Ernst, Tomasz; Jóźwiak, Waldemar; Słomiński, Jan

2018-02-01

To emphasize the relationship between the pre-seismic geomagnetic signals and Vrancea seismicity, in this work it is hypothesized that before an earthquake initiation, the high stress reached into seismogenic volume generates dehydration of the rocks and fracturing processes followed by release of electric charges along the faulting systems, which lead to resistivity changes. These changes were explored on September 2016 by the normalized function Bzn obtained from the geomagnetic data recorded in ULF range (0.001-0.0083 Hz). A statistical analysis was also performed to discriminate on the new Bzn* time series a pre-seismic signature related to the Mw5.7 earthquake. Significant anomalous behavior of Bzn* was identified on September 21, with 3 days prior to the onset of the seismic event. Similar information is provided by registrations of the magnetic and electron concentration variations in the ionosphere over the Vrancea zone, by Swarm satellites, 4 days and 1 day before the earthquake.

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.

An adaptive deep-coupled GNSS/INS navigation system with hybrid pre-filter processing

NASA Astrophysics Data System (ADS)

Wu, Mouyan; Ding, Jicheng; Zhao, Lin; Kang, Yingyao; Luo, Zhibin

2018-02-01

The deep-coupling of a global navigation satellite system (GNSS) with an inertial navigation system (INS) can provide accurate and reliable navigation information. There are several kinds of deeply-coupled structures. These can be divided mainly into coherent and non-coherent pre-filter based structures, which have their own strong advantages and disadvantages, especially in accuracy and robustness. In this paper, the existing pre-filters of the deeply-coupled structures are analyzed and modified to improve them firstly. Then, an adaptive GNSS/INS deeply-coupled algorithm with hybrid pre-filters processing is proposed to combine the advantages of coherent and non-coherent structures. An adaptive hysteresis controller is designed to implement the hybrid pre-filters processing strategy. The simulation and vehicle test results show that the adaptive deeply-coupled algorithm with hybrid pre-filters processing can effectively improve navigation accuracy and robustness, especially in a GNSS-challenged environment.

Features of CRISPR-Cas Regulation Key to Highly Efficient and Temporally-Specific crRNA Production.

PubMed

Rodic, Andjela; Blagojevic, Bojana; Djordjevic, Magdalena; Severinov, Konstantin; Djordjevic, Marko

2017-01-01

Bacterial immune systems, such as CRISPR-Cas or restriction-modification (R-M) systems, affect bacterial pathogenicity and antibiotic resistance by modulating horizontal gene flow. A model system for CRISPR-Cas regulation, the Type I-E system from Escherichia coli , is silent under standard laboratory conditions and experimentally observing the dynamics of CRISPR-Cas activation is challenging. Two characteristic features of CRISPR-Cas regulation in E. coli are cooperative transcription repression of cas gene and CRISPR array promoters, and fast non-specific degradation of full length CRISPR transcripts (pre-crRNA). In this work, we use computational modeling to understand how these features affect the system expression dynamics. Signaling which leads to CRISPR-Cas activation is currently unknown, so to bypass this step, we here propose a conceptual setup for cas expression activation, where cas genes are put under transcription control typical for a restriction-modification (R-M) system and then introduced into a cell. Known transcription regulation of an R-M system is used as a proxy for currently unknown CRISPR-Cas transcription control, as both systems are characterized by high cooperativity, which is likely related to similar dynamical constraints of their function. We find that the two characteristic CRISPR-Cas control features are responsible for its temporally-specific dynamical response, so that the system makes a steep (switch-like) transition from OFF to ON state with a time-delay controlled by pre-crRNA degradation rate. We furthermore find that cooperative transcription regulation qualitatively leads to a cross-over to a regime where, at higher pre-crRNA processing rates, crRNA generation approaches the limit of an infinitely abrupt system induction. We propose that these dynamical properties are associated with rapid expression of CRISPR-Cas components and efficient protection of bacterial cells against foreign DNA. In terms of synthetic applications, the setup proposed here should allow highly efficient expression of small RNAs in a narrow time interval, with a specified time-delay with respect to the signal onset.

Design and Verification of a Digital Controller for a 2-Piece Hemispherical Resonator Gyroscope.

PubMed

Lee, Jungshin; Yun, Sung Wook; Rhim, Jaewook

2016-04-20

A Hemispherical Resonator Gyro (HRG) is the Coriolis Vibratory Gyro (CVG) that measures rotation angle or angular velocity using Coriolis force acting the vibrating mass. A HRG can be used as a rate gyro or integrating gyro without structural modification by simply changing the control scheme. In this paper, differential control algorithms are designed for a 2-piece HRG. To design a precision controller, the electromechanical modelling and signal processing must be pre-performed accurately. Therefore, the equations of motion for the HRG resonator with switched harmonic excitations are derived with the Duhamel Integral method. Electromechanical modeling of the resonator, electric module and charge amplifier is performed by considering the mode shape of a thin hemispherical shell. Further, signal processing and control algorithms are designed. The multi-flexing scheme of sensing, driving cycles and x, y-axis switching cycles is appropriate for high precision and low maneuverability systems. The differential control scheme is easily capable of rejecting the common mode errors of x, y-axis signals and changing the rate integrating mode on basis of these studies. In the rate gyro mode the controller is composed of Phase-Locked Loop (PLL), amplitude, quadrature and rate control loop. All controllers are designed on basis of a digital PI controller. The signal processing and control algorithms are verified through Matlab/Simulink simulations. Finally, a FPGA and DSP board with these algorithms is verified through experiments.

Resistance exercise increases intramuscular NF-κb signaling in untrained males.

PubMed

Townsend, Jeremy R; Stout, Jeffrey R; Jajtner, Adam R; Church, David D; Beyer, Kyle S; Oliveira, Leonardo P; La Monica, Michael B; Riffe, Joshua J; Muddle, Tyler W D; Baker, Kayla M; Fukuda, David H; Roberts, Michael D; Hoffman, Jay R

2016-12-01

The NF-κB signaling pathway regulates multiple cellular processes following exercise stress. This study aims to examine the effects of an acute lower-body resistance exercise protocol and subsequent recovery on intramuscular NF-κB signaling. Twenty-eight untrained males were assigned to either a control (CON; n = 11) or exercise group (EX; n = 17) and completed a lower-body resistance exercise protocol consisting of the back squat, leg press, and leg extension exercises. Skeletal muscle microbiopsies were obtained from the vastus lateralis pre-exercise (PRE), 1-hour (1H), 5-hours (5H), and 48-hours (48H) post-resistance exercise. Multiplex signaling assay kits (EMD Millipore, Billerica, MA, USA) were used to quantify the total protein (TNFR1, c-Myc) or phosphorylation status of proteins belonging to the NF-κB signaling pathway (IKKa/b, IkBα, NF-κB) using multiplex protein assay. Repeated measures ANOVA analysis was used to determine the effects of the exercise bout on intramuscular signaling at each time point. Additionally, change scores were analyzed by magnitude based inferences to determine a mechanistic interpretation. Repeated measures ANOVA indicated a trend for a two-way interaction between the EX and CON Group (p = 0.064) for c-Myc post resistance exercise. Magnitude based inference analysis suggest a "Very Likely" increase in total c-Myc from PRE-5H and a "Likely" increase in IkBα phosphorylation from PRE-5H post-resistance exercise. Results indicated that c-Myc transcription factor is elevated following acute intense resistance exercise in untrained males. Future studies should examine the role that post-resistance exercise NF-κβ signaling plays in c-Myc induction, ribosome biogenesis and skeletal muscle regeneration.

Deep sequencing reveals complex mechanisms of diapause preparation in the invasive mosquito, Aedes albopictus.

PubMed

Poelchau, Monica F; Reynolds, Julie A; Elsik, Christine G; Denlinger, David L; Armbruster, Peter A

2013-05-22

Seasonal environments present fundamental physiological challenges to a wide range of insects. Many temperate insects surmount the exigencies of winter by undergoing photoperiodic diapause, in which photoperiod provides a token cue that initiates an alternative developmental programme leading to dormancy. Pre-diapause is a crucial preparatory phase of this process, preceding developmental arrest. However, the regulatory and physiological mechanisms of diapause preparation are largely unknown. Using high-throughput gene expression profiling in the Asian tiger mosquito, Aedes albopictus, we reveal major shifts in endocrine signalling, cell proliferation, metabolism, energy production and cellular structure across pre-diapause development. While some hallmarks of diapause, such as insulin signalling and stress response, were not important at the transcriptional level, two genes, Pepck and PCNA, appear to show diapause-induced transcriptional changes across insect taxa. These processes demonstrate physiological commonalities between Ae. albopictus pre-diapause and diapause strategies across insects, and support the idea of a genetic 'toolkit' for diapause. Observations of gene expression trends from a comparative developmental perspective suggest that individual physiological processes are delayed against a background of a fixed morphological ontogeny. Our results demonstrate how deep sequencing can provide new insights into elusive molecular bases of complex ecological adaptations.

An in vivo model of epithelial to mesenchymal transition reveals a mitogenic switch

PubMed Central

Jahn, Stephan C.; Law, Mary E.; Corsino, Patrick E.; Parker, Nicole N.; Pham, Kien; Davis, Bradley J.; Lu, Jianrong; Law, Brian K.

2012-01-01

The epithelial to mesenchymal transition (EMT) is a process by which differentiated epithelial cells transition to a mesenchymal phenotype. EMT enables the escape of epithelial cells from the rigid structural constraints of the tissue architecture to a phenotype more amenable to cell migration and, therefore, invasion and metastasis. We characterized an in vivo model of EMT and discovered that marked changes in mitogenic signaling occurred during this process. DNA microarray analysis revealed that the expression of a number of genes varied significantly between post-EMT and pre-EMT breast cancer cells. Post-EMT cancer cells upregulated mRNA encoding c-Met and the PDGF and LPA receptors, and acquired increased responsiveness to HGF, PDGF, and LPA. This rendered the post-EMT cells responsive to the growth inhibitory effects of HGF, PDGF, and LPA receptor inhibitors/antagonists. Furthermore, post- EMT cells exhibited decreased basal Raf and Erk phosphorylation, and in comparison to pre-EMT cells, their proliferation was poorly inhibited by a MEK inhibitor. These studies suggest that therapies need to be designed to target both pre-EMT and post-EMT cancer cells and that signaling changes in post- EMT cells may allow them to take advantage of paracrine signaling from the stroma in vivo. PMID:22906417

Discrete wavelet transform: a tool in smoothing kinematic data.

PubMed

Ismail, A R; Asfour, S S

1999-03-01

Motion analysis systems typically introduce noise to the displacement data recorded. Butterworth digital filters have been used to smooth the displacement data in order to obtain smoothed velocities and accelerations. However, this technique does not yield satisfactory results, especially when dealing with complex kinematic motions that occupy the low- and high-frequency bands. The use of the discrete wavelet transform, as an alternative to digital filters, is presented in this paper. The transform passes the original signal through two complementary low- and high-pass FIR filters and decomposes the signal into an approximation function and a detail function. Further decomposition of the signal results in transforming the signal into a hierarchy set of orthogonal approximation and detail functions. A reverse process is employed to perfectly reconstruct the signal (inverse transform) back from its approximation and detail functions. The discrete wavelet transform was applied to the displacement data recorded by Pezzack et al., 1977. The smoothed displacement data were twice differentiated and compared to Pezzack et al.'s acceleration data in order to choose the most appropriate filter coefficients and decomposition level on the basis of maximizing the percentage of retained energy (PRE) and minimizing the root mean square error (RMSE). Daubechies wavelet of the fourth order (Db4) at the second decomposition level showed better results than both the biorthogonal and Coiflet wavelets (PRE = 97.5%, RMSE = 4.7 rad s-2). The Db4 wavelet was then used to compress complex displacement data obtained from a noisy mathematically generated function. Results clearly indicate superiority of this new smoothing approach over traditional filters.

The Drake Equation

NASA Astrophysics Data System (ADS)

Vakoch, Douglas A.; Dowd, Matthew F.; Drake, Frank

2015-07-01

List of contributors; Foreword Frank Drake; Preface; Acknowledgements; Introduction Steven Dick; 1. Rate of formation of stars suitable for the development of intelligent life, R*, pre-1961 David DeVorkin; 2. Rate of formation of stars suitable for the development of intelligent life, R*, 1961 to the present Patrick François and Danielle Briot; 3. Fraction of stars with planetary systems, fp, pre-1961 Matthew F. Dowd; 4. Fraction of stars with planetary systems, fp, 1961 to the present Chris Impey; 5. Number of planets, per solar system, with an environment suitable for life, ne, pre-1961 Florence Raulin Cerceau; 6. Number of planets, per solar system, with an environment suitable for life, ne, 1961 to the present Danielle Briot and Jean Schneider; 7. Fraction of suitable planets on which life actually appears, fl, pre-1961 Stephané Tirard; 8. Fraction of suitable planets on which life actually appears, fl, 1961 to the present David J. Des Marais; 9. Fraction of life-bearing planets on which intelligent life emerges, fl, pre-1961 Michael Crowe; 10. Fraction of life-bearing planets on which intelligent life emerges, fl, 1961 to the present Lori Marino; 11. Fraction of civilizations that develop a technology that releases detectable signs of their existence into space, fc, pre-1961 Florence Raulin Cerceau; 12. Fraction of civilizations that develop a technology that releases detectable signs of their existence into space, fc, 1961 to the present Seth Shostak; 13. Length of time such civilizations release detectable signals into space, L, pre-1961 David Dunér; 14. Length of time such civilizations release detectable signals into space, L, 1961 to the present Garry Chick; Afterword Paul Davies; Index.

Notch signaling drives multiple myeloma induced osteoclastogenesis

PubMed Central

Colombo, Michela; Thümmler, Katja; Mirandola, Leonardo; Garavelli, Silvia; Todoerti, Katia; Apicella, Luana; Lazzari, Elisa; Lancellotti, Marialuigia; Platonova, Natalia; Akbar, Moeed; Chiriva-Internati, Maurizio; Soutar, Richard; Neri, Antonino; Goodyear, Carl S.; Chiaramonte, Raffaella

2014-01-01

Multiple myeloma (MM) is closely associated with bone destruction. Once migrated to the bone marrow, MM cells unbalance bone formation and resorption via the recruitment and maturation of osteoclast precursors. The Notch pathway plays a key role in different types of cancer and drives several biological processes relevant in MM, including cell localization within the bone marrow, proliferation, survival and pharmacological resistance. Here we present evidences that MM can efficiently drive osteoclastogenesis by contemporaneously activating Notch signaling on tumor cells and osteoclasts through the aberrant expression of Notch ligands belonging to the Jagged family. Active Notch signaling in MM cells induces the secretion of the key osteoclastogenic factor, RANKL, which can be boosted in the presence of stromal cells. In turn, MM cells-derived RANKL causes the upregulation of its receptor, RANK, and Notch2 in pre-osteoclasts. Notch2 stimulates osteoclast differentiation by promoting autocrine RANKL signaling. Finally, MM cells through Jagged ligands expression can also activate Notch signaling in pre-osteoclast by direct contact. Such synergism between tumor cells and pre-osteoclasts in MM-induced osteoclastogenesis can be disrupted by silencing tumor-derived Jagged1 and 2. These results make the Jagged ligands new promising therapeutic targets in MM to contrast bone disease and the associated co-morbidities. PMID:25257302

Invariance algorithms for processing NDE signals

NASA Astrophysics Data System (ADS)

Mandayam, Shreekanth; Udpa, Lalita; Udpa, Satish S.; Lord, William

1996-11-01

Signals that are obtained in a variety of nondestructive evaluation (NDE) processes capture information not only about the characteristics of the flaw, but also reflect variations in the specimen's material properties. Such signal changes may be viewed as anomalies that could obscure defect related information. An example of this situation occurs during in-line inspection of gas transmission pipelines. The magnetic flux leakage (MFL) method is used to conduct noninvasive measurements of the integrity of the pipe-wall. The MFL signals contain information both about the permeability of the pipe-wall and the dimensions of the flaw. Similar operational effects can be found in other NDE processes. This paper presents algorithms to render NDE signals invariant to selected test parameters, while retaining defect related information. Wavelet transform based neural network techniques are employed to develop the invariance algorithms. The invariance transformation is shown to be a necessary pre-processing step for subsequent defect characterization and visualization schemes. Results demonstrating the successful application of the method are presented.

A Comparative Investigation of the Combined Effects of Pre-Processing, Wavelength Selection, and Regression Methods on Near-Infrared Calibration Model Performance.

PubMed

Wan, Jian; Chen, Yi-Chieh; Morris, A Julian; Thennadil, Suresh N

2017-07-01

Near-infrared (NIR) spectroscopy is being widely used in various fields ranging from pharmaceutics to the food industry for analyzing chemical and physical properties of the substances concerned. Its advantages over other analytical techniques include available physical interpretation of spectral data, nondestructive nature and high speed of measurements, and little or no need for sample preparation. The successful application of NIR spectroscopy relies on three main aspects: pre-processing of spectral data to eliminate nonlinear variations due to temperature, light scattering effects and many others, selection of those wavelengths that contribute useful information, and identification of suitable calibration models using linear/nonlinear regression . Several methods have been developed for each of these three aspects and many comparative studies of different methods exist for an individual aspect or some combinations. However, there is still a lack of comparative studies for the interactions among these three aspects, which can shed light on what role each aspect plays in the calibration and how to combine various methods of each aspect together to obtain the best calibration model. This paper aims to provide such a comparative study based on four benchmark data sets using three typical pre-processing methods, namely, orthogonal signal correction (OSC), extended multiplicative signal correction (EMSC) and optical path-length estimation and correction (OPLEC); two existing wavelength selection methods, namely, stepwise forward selection (SFS) and genetic algorithm optimization combined with partial least squares regression for spectral data (GAPLSSP); four popular regression methods, namely, partial least squares (PLS), least absolute shrinkage and selection operator (LASSO), least squares support vector machine (LS-SVM), and Gaussian process regression (GPR). The comparative study indicates that, in general, pre-processing of spectral data can play a significant role in the calibration while wavelength selection plays a marginal role and the combination of certain pre-processing, wavelength selection, and nonlinear regression methods can achieve superior performance over traditional linear regression-based calibration.

Infrared Imagery of Shuttle (IRIS). Task 2, summary report

NASA Technical Reports Server (NTRS)

Chocol, C. J.

1978-01-01

End-to-end tests of a 16 element indium antimonide sensor array and 10 channels of associated electronic signal processing were completed. Quantitative data were gathered on system responsivity, frequency response, noise, stray capacitance effects, and sensor paralleling. These tests verify that the temperature accuracies, predicted in the Task 1 study, can be obtained with a very carefully designed electro-optical flight system. Pre-flight and inflight calibration of a high quality are mandatory to obtain these accuracies. Also, optical crosstalk in the array-dewar assembly must be carefully eliminated by its design. Tests of the scaled up tracking system reticle also demonstrate that the predicted tracking system accuracies can be met in the flight system. In addition, improvements in the reticle pattern and electronics are possible, which will reduce the complexity of the flight system and increase tracking accuracy.

Mesenchymal Inflammation Drives Genotoxic Stress in Hematopoietic Stem Cells and Predicts Disease Evolution in Human Pre-leukemia.

PubMed

Zambetti, Noemi A; Ping, Zhen; Chen, Si; Kenswil, Keane J G; Mylona, Maria A; Sanders, Mathijs A; Hoogenboezem, Remco M; Bindels, Eric M J; Adisty, Maria N; Van Strien, Paulina M H; van der Leije, Cindy S; Westers, Theresia M; Cremers, Eline M P; Milanese, Chiara; Mastroberardino, Pier G; van Leeuwen, Johannes P T M; van der Eerden, Bram C J; Touw, Ivo P; Kuijpers, Taco W; Kanaar, Roland; van de Loosdrecht, Arjan A; Vogl, Thomas; Raaijmakers, Marc H G P

2016-11-03

Mesenchymal niche cells may drive tissue failure and malignant transformation in the hematopoietic system, but the underlying molecular mechanisms and relevance to human disease remain poorly defined. Here, we show that perturbation of mesenchymal cells in a mouse model of the pre-leukemic disorder Shwachman-Diamond syndrome (SDS) induces mitochondrial dysfunction, oxidative stress, and activation of DNA damage responses in hematopoietic stem and progenitor cells. Massive parallel RNA sequencing of highly purified mesenchymal cells in the SDS mouse model and a range of human pre-leukemic syndromes identified p53-S100A8/9-TLR inflammatory signaling as a common driving mechanism of genotoxic stress. Transcriptional activation of this signaling axis in the mesenchymal niche predicted leukemic evolution and progression-free survival in myelodysplastic syndrome (MDS), the principal leukemia predisposition syndrome. Collectively, our findings identify mesenchymal niche-induced genotoxic stress in heterotypic stem and progenitor cells through inflammatory signaling as a targetable determinant of disease outcome in human pre-leukemia. Copyright © 2016 Elsevier Inc. All rights reserved.

Profiling Pre-MicroRNA and Mature MicroRNA Expressions Using a Single Microarray and Avoiding Separate Sample Preparation

PubMed Central

Gan, Lin; Denecke, Bernd

2013-01-01

Mature microRNA is a crucial component in the gene expression regulation network. At the same time, microRNA gene expression and procession is regulated in a precise and collaborated way. Pre-microRNAs mediate products during the microRNA transcription process, they can provide hints of microRNA gene expression regulation or can serve as alternative biomarkers. To date, little effort has been devoted to pre-microRNA expression profiling. In this study, three human and three mouse microRNA profile data sets, based on the Affymetrix miRNA 2.0 array, have been re-analyzed for both mature and pre-microRNA signals as a primary test of parallel mature/pre-microRNA expression profiling on a single platform. The results not only demonstrated a glimpse of pre-microRNA expression in human and mouse, but also the relationship of microRNA expressions between pre- and mature forms. The study also showed a possible application of currently available microRNA microarrays in profiling pre-microRNA expression in a time and cost effective manner. PMID:27605179

An Integrated Monitoring System of Pre-earthquake Processes in Peloponnese, Greece

NASA Astrophysics Data System (ADS)

Karastathis, V. K.; Tsinganos, K.; Kafatos, M.; Eleftheriou, G.; Ouzounov, D.; Mouzakiotis, E.; Papadopoulos, G. A.; Voulgaris, N.; Bocchini, G. M.; Liakopoulos, S.; Aspiotis, T.; Gika, F.; Tselentis, A.; Moshou, A.; Psiloglou, B.

2017-12-01

One of the controversial issues in the contemporary seismology is the ability of radon accumulation monitoring to provide reliable earthquake forecasting. Although there are many examples in the literature showing radon increase before earthquakes, skepticism arises from instability of the measurements, false alarms, difficulties in interpretation caused by the weather influence (eg. rainfall) and difficulties on the consideration an irrefutable theoretical background of the phenomenon.We have developed and extensively tested a multi parameter network aimed for studying of the pre-earthquake processes and operating as a part of integrated monitoring system in the high seismicity area of the Western Hellenic Arc (SW Peloponnese, Greece). The prototype consists of four components: A real-time monitoring system of Radon accumulation. It consists of three gamma radiation detectors [NaI(Tl) scintillators] A nine-station seismic array to monitor the microseismicity in the offshore area of the Hellenic arc. The processing of the data is based on F-K and beam-forming techniques. Real-time weather monitoring systems for air temperature, relative humidity, precipitation and pressure. Thermal radiation emission from AVHRR/NOAA-18 polar orbit satellite observation. The project revolved around the idea of jointly studying the emission of Radon that has been proven in many cases as a reliable indicator of the possible time of an event, with the accurate location of the foreshock activity detected by the seismic array that can be a more reliable indicator of the possible position of an event. In parallel a satellite thermal anomaly detection technique has been used for monitoring of larger magnitude events (possible indicator for strong events M ≥5.0.). The first year of operations revealed a number of pre-seismic radon variation anomalies before several local earthquakes (M>3.6). The Radon increases systematically before the larger events.Details about the overall performance in registration of pre-seismic signals in Peloponnese region, along with two distant but very strong earthquakes in Jun 12, 2017 M6.3 and Jul 20, 2017 M6.6 in Greece will be discussed.

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal

PubMed Central

Ramkumar, Barathram; Sabarimalai Manikandan, M.

2017-01-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal. PMID:28529758

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

PubMed

Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

2017-02-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

Centrifugal unbalance detection system

DOEpatents

Cordaro, Joseph V.; Reeves, George; Mets, Michael

2002-01-01

A system consisting of an accelerometer sensor attached to a centrifuge enclosure for sensing vibrations and outputting a signal in the form of a sine wave with an amplitude and frequency that is passed through a pre-amp to convert it to a voltage signal, a low pass filter for removing extraneous noise, an A/D converter and a processor and algorithm for operating on the signal, whereby the algorithm interprets the amplitude and frequency associated with the signal and once an amplitude threshold has been exceeded the algorithm begins to count cycles during a predetermined time period and if a given number of complete cycles exceeds the frequency threshold during the predetermined time period, the system shuts down the centrifuge.

A computerized self-compensating system for ultrasonic inspection of airplane structures

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

Komsky, I.N.; Achenbach, J.D.; Hagemaier, D.

1993-12-31

Application of a self-compensating technique for ultrasonic inspection of airplane structures makes it possible not only to detect cracks in the different layers of joints but also to obtain information on crack sizes. A prototype computerized ultrasonic system, which utilizes the self-compensating method, has been developed for non-destructive inspection of multilayered airplane structures with in-between sealants, such as bolted joints in tail connections. Industrial applications of the system would require deployment of commercially available portable modules for data acquisition and processing. A portable ultrasonic flaw detector EPOCH II manual scanners and HandiScan, and SQL and FCS software modules form themore » PC-based TestPro system have been selected for initial tests. A pair of contact angle-beam transducers were used to generate shear waves in the material. Both hardware and software components of the system have been modified for the application in conjunction with the self-compensating technique. The system has bene tested on two calibration specimens with artificial flaws of different sizes in internal layers of multilayered structures. Ultrasonic signals transmitted through and reflected from the artificial flaws have bene discriminated and characterized using multiple time domain amplitude gates. Then the ratios of the reflection and transmission coefficients, R/T, were calculated for several positions of the transducers. Inspection of measured R/T curves shows it is difficult to visually associate curve shapes with corresponding flaw sizes and orientation. Hence for online classification of these curve shapes, application of an adaptive signal classifier was considered. Several different types and configurations of the classifiers, including a neural network, have been tested. Test results showed that improved performance of the classifier can be achieved by combination of a back-propagation neural network with a signal pre-processing module.« less

RNA Seq analysis for transcriptome profiling in response to classical swine fever vaccination in indigenous and crossbred pigs.

PubMed

Pathak, Shalu Kumari; Kumar, Amit; Bhuwana, G; Sah, Vaishali; Upmanyu, Vikramadiya; Tiwari, A K; Sahoo, A P; Sahoo, A R; Wani, Sajjad A; Panigrahi, Manjit; Sahoo, N R; Kumar, Ravi

2017-09-01

In present investigation, differential expression of transcriptome after classical swine fever (CSF) vaccination has been explored at the cellular level in crossbred and indigenous (desi) piglets. RNA Sequencing by Expectation-Maximization (RSEM) package was used to quantify gene expression from RNA Sequencing data, and differentially expressed genes (DEGs) were identified using EBSeq, DESeq2, and edgeR softwares. After analysis, 5222, 6037, and 6210 common DEGs were identified in indigenous post-vaccinated verses pre-vaccinated, crossbred post-vaccinated verses pre-vaccinated, and post-vaccinated crossbred verses indigenous pigs, respectively. Functional annotation of these DEGs showed enrichment of antigen processing-cross presentation, B cell receptor signaling, T cell receptor signaling, NF-κB signaling, and TNF signaling pathways. The interaction network among the immune genes included more number of genes with greater connectivity in vaccinated crossbred than the indigenous piglets. Higher expression of IRF3, IL1β, TAP1, CSK, SLA2, SLADM, and NF-kB in crossbred piglets in comparison to indigenous explains the better humoral response observed in crossbred piglets. Here, we predicted that the processed CSFV antigen through the T cell receptor signaling cascade triggers the B cell receptor-signaling pathway to finally activate MAPK kinase and NF-κB signaling pathways in B cell. This activation results in expression of genes/transcription factors that lead to B cell ontogeny, auto immunity and immune response through antibody production. Further, immunologically important genes were validated by qRT-PCR.

Extraction of ECG signal with adaptive filter for hearth abnormalities detection

NASA Astrophysics Data System (ADS)

Turnip, Mardi; Saragih, Rijois. I. E.; Dharma, Abdi; Esti Kusumandari, Dwi; Turnip, Arjon; Sitanggang, Delima; Aisyah, Siti

2018-04-01

This paper demonstrates an adaptive filter method for extraction ofelectrocardiogram (ECG) feature in hearth abnormalities detection. In particular, electrocardiogram (ECG) is a recording of the heart's electrical activity by capturing a tracingof cardiac electrical impulse as it moves from the atrium to the ventricles. The applied algorithm is to evaluate and analyze ECG signals for abnormalities detection based on P, Q, R and S peaks. In the first phase, the real-time ECG data is acquired and pre-processed. In the second phase, the procured ECG signal is subjected to feature extraction process. The extracted features detect abnormal peaks present in the waveform. Thus the normal and abnormal ECG signal could be differentiated based on the features extracted.

Fully chip-embedded automation of a multi-step lab-on-a-chip process using a modularized timer circuit.

PubMed

Kang, Junsu; Lee, Donghyeon; Heo, Young Jin; Chung, Wan Kyun

2017-11-07

For highly-integrated microfluidic systems, an actuation system is necessary to control the flow; however, the bulk of actuation devices including pumps or valves has impeded the broad application of integrated microfluidic systems. Here, we suggest a microfluidic process control method based on built-in microfluidic circuits. The circuit is composed of a fluidic timer circuit and a pneumatic logic circuit. The fluidic timer circuit is a serial connection of modularized timer units, which sequentially pass high pressure to the pneumatic logic circuit. The pneumatic logic circuit is a NOR gate array designed to control the liquid-controlling process. By using the timer circuit as a built-in signal generator, multi-step processes could be done totally inside the microchip without any external controller. The timer circuit uses only two valves per unit, and the number of process steps can be extended without limitation by adding timer units. As a demonstration, an automation chip has been designed for a six-step droplet treatment, which entails 1) loading, 2) separation, 3) reagent injection, 4) incubation, 5) clearing and 6) unloading. Each process was successfully performed for a pre-defined step-time without any external control device.

A computational approach to real-time image processing for serial time-encoded amplified microscopy

NASA Astrophysics Data System (ADS)

Oikawa, Minoru; Hiyama, Daisuke; Hirayama, Ryuji; Hasegawa, Satoki; Endo, Yutaka; Sugie, Takahisa; Tsumura, Norimichi; Kuroshima, Mai; Maki, Masanori; Okada, Genki; Lei, Cheng; Ozeki, Yasuyuki; Goda, Keisuke; Shimobaba, Tomoyoshi

2016-03-01

High-speed imaging is an indispensable technique, particularly for identifying or analyzing fast-moving objects. The serial time-encoded amplified microscopy (STEAM) technique was proposed to enable us to capture images with a frame rate 1,000 times faster than using conventional methods such as CCD (charge-coupled device) cameras. The application of this high-speed STEAM imaging technique to a real-time system, such as flow cytometry for a cell-sorting system, requires successively processing a large number of captured images with high throughput in real time. We are now developing a high-speed flow cytometer system including a STEAM camera. In this paper, we describe our approach to processing these large amounts of image data in real time. We use an analog-to-digital converter that has up to 7.0G samples/s and 8-bit resolution for capturing the output voltage signal that involves grayscale images from the STEAM camera. Therefore the direct data output from the STEAM camera generates 7.0G byte/s continuously. We provided a field-programmable gate array (FPGA) device as a digital signal pre-processor for image reconstruction and finding objects in a microfluidic channel with high data rates in real time. We also utilized graphics processing unit (GPU) devices for accelerating the calculation speed of identification of the reconstructed images. We built our prototype system, which including a STEAM camera, a FPGA device and a GPU device, and evaluated its performance in real-time identification of small particles (beads), as virtual biological cells, owing through a microfluidic channel.

Simulating GPS radio signal to synchronize network--a new technique for redundant timing.

PubMed

Shan, Qingxiao; Jun, Yang; Le Floch, Jean-Michel; Fan, Yaohui; Ivanov, Eugene N; Tobar, Michael E

2014-07-01

Currently, many distributed systems such as 3G mobile communications and power systems are time synchronized with a Global Positioning System (GPS) signal. If there is a GPS failure, it is difficult to realize redundant timing, and thus time-synchronized devices may fail. In this work, we develop time transfer by simulating GPS signals, which promises no extra modification to original GPS-synchronized devices. This is achieved by applying a simplified GPS simulator for synchronization purposes only. Navigation data are calculated based on a pre-assigned time at a fixed position. Pseudo-range data which describes the distance change between the space vehicle (SV) and users are calculated. Because real-time simulation requires heavy-duty computations, we use self-developed software optimized on a PC to generate data, and save the data onto memory disks while the simulator is operating. The radio signal generation is similar to the SV at an initial position, and the frequency synthesis of the simulator is locked to a pre-assigned time. A filtering group technique is used to simulate the signal transmission delay corresponding to the SV displacement. Each SV generates a digital baseband signal, where a unique identifying code is added to the signal and up-converted to generate the output radio signal at the centered frequency of 1575.42 MHz (L1 band). A prototype with a field-programmable gate array (FPGA) has been built and experiments have been conducted to prove that we can realize time transfer. The prototype has been applied to the CDMA network for a three-month long experiment. Its precision has been verified and can meet the requirements of most telecommunication systems.

Identifying the fingerprints of the anthropogenic component of land use/land cover changes on regional climate of the USA high plains

NASA Astrophysics Data System (ADS)

Mutiibwa, D.; Irmak, S.

2011-12-01

The majority of recent climate change studies have largely focused on detection and attribution of anthropogenic forcings of greenhouse gases, aerosols, stratospheric and tropospheric ozone. However, there is growing evidence that land cover/land use (LULC) change can significantly impact atmospheric processes from local to regional weather and climate variability. Human activities such as conversion of natural ecosystem to croplands and urban-centers, deforestation and afforestation impact biophysical properties of the land surfaces including albedo, energy balance, moisture-holding capacity of soil, and surface roughness. Alterations in these properties affect the heat and moisture exchanges between the land surface and atmospheric boundary layer, and ultimately impact the climate system. The challenge is to demonstrate that LULC changes produce a signal that can be discerned from natural climate noise. In this study, we attempt to detect the signature of anthropogenic forcing of LULC change on climate on regional scale. The signal projector investigated for detecting the signature of LULC changes on regional climate of the High Plains of the USA is the Normalized Difference Vegetation Index (NDVI). NDVI is an indicator that captures short and long-term geographical distribution of vegetation surfaces. The study develops an enhanced signal processing procedure to maximize the signal to noise ratio by introducing a pre-filtering technique of ARMA processes on the investigated climate and signal variables, before applying the optimal fingerprinting technique to detect the signals of LULC changes on observed climate, temperature, in the High Plains. The intent is to filter out as much noise as possible while still retaining the essential features of the signal by making use of the known characteristics of the noise and the anticipated signal. The study discusses the approach of identifying and suppressing the autocorrelation in optimal fingerprint analysis by applying linear transformation of ARMA processes to the analysis variables. With the assumption that natural climate variability is a near stationary process, the pre-filters are developed to generate stationary residuals. The High Plains region although impacted by droughts over the last three decades has had an increase in agricultural lands, both irrigated and non-irrigated. The study shows that for the most part of the High Plains region there is significant influence of evaporative cooling on regional climate during the summer months. As the vegetation coverage increases coupled with increased in irrigation application, the regional daytime surface energy in summer is increasingly redistributed into latent heat flux which increases the effect of evaporative cooling on summer temperatures. We included the anthropogenic forcing of CO2 on regional climate with the main purpose of surpassing the radiative heating effect of greenhouse gases from natural climate noise, to enhance the LULC signal-to-noise ratio. The warming signal due to greenhouse gas forcing is observed to be weakest in the central part of the High Plains. The results showed that the CO2 signal in the region was weak or is being surpassed by the evaporative cooling effect.

Selection and stopping in voluntary action: A meta-analysis and combined fMRI study☆

PubMed Central

Rae, Charlotte L.; Hughes, Laura E.; Weaver, Chelan; Anderson, Michael C.; Rowe, James B.

2014-01-01

Voluntary action control requires selection of appropriate responses and stopping of inappropriate responses. Selection and stopping are often investigated separately, but they appear to recruit similar brain regions, including the pre-supplementary motor area (preSMA) and inferior frontal gyrus. We therefore examined the evidence for overlap of selection and stopping using two approaches: a meta-analysis of existing studies of selection and stopping, and a novel within-subject fMRI study in which action selection and a stop signal task were combined factorially. The novel fMRI study also permitted us to investigate hypotheses regarding a common mechanism for selection and stopping. The preSMA was identified by both methods as common to selection and stopping. However, stopping a selected action did not recruit preSMA more than stopping a specified action, nor did stop signal reaction times differ significantly across the two conditions. These findings suggest that the preSMA supports both action selection and stopping, but the two processes may not require access to a common inhibition mechanism. Instead, the preSMA might represent information about potential actions that is used in both action selection and stopping in order to resolve conflict between competing available responses. PMID:24128740

Feasibility of clinical magnetoencephalography (MEG) functional mapping in the presence of dental artefacts.

PubMed

Hillebrand, A; Fazio, P; de Munck, J C; van Dijk, B W

2013-01-01

To evaluate the viability of MEG source reconstruction in the presence of large interference due to orthodontic material. We recorded the magnetic fields following a simple hand movement and following electrical stimulation of the median nerve (somatosensory evoked field -SEF). These two tasks were performed twice, once with and once without artificial dental artefacts. Temporal Signal Space Separation (tSSS) was applied to spatially filter the data and source reconstruction was performed according to standard procedures for pre-surgical mapping of eloquent cortex, applying dipole fitting to the SEF data and beamforming to the hand movement data. Comparing the data with braces to the data without braces, the observed distances between the activations following hand movement in the two conditions were on average 6.4 and 4.5 mm for the left and right hand, respectively, whereas the dipole localisation errors for the SEF were 4.1 and 5.4 mm, respectively. Without tSSS it was generally not possible to obtain reliable dipole fit or beamforming results when wearing braces. We confirm that tSSS is a required and effective pre-processing step for data recorded with the Elekta-MEG system. Moreover, we have shown that even the presence of large interference from orthodontic material does not significantly alter the results from dipole localisation or beamformer analysis, provided the data are spatially filtered by tSSS. State-of-the-art signal processing techniques enable the use of MEG for pre-surgical evaluation in a much larger clinical population than previously thought possible. Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Neural predictors and mechanisms of cognitive behavioral therapy on threat processing in social anxiety disorder.

PubMed

Klumpp, Heide; Fitzgerald, Daniel A; Phan, K Luan

2013-08-01

Cognitive behavioral therapy (CBT) is "gold standard" psychotherapy for social anxiety disorder (SAD). Cognitive models posit that preferential processing of threat mediates excessive forms of anxiety, which is supported by exaggerated amygdala, insula, and cortical reactivity to threatening socio-emotional signals in SAD. However, little is known about neural predictors of CBT success or the mechanisms by which CBT exerts its therapeutic effects. Functional magnetic resonance imaging (fMRI) was conducted during responses to social signals of threat (fearful/angry faces) against positive signals (happy faces) in 14 patients with SAD before and after 12 weeks of CBT. For comparison, 14 healthy control (HC) participants also underwent two fMRI scans, 12 weeks apart. Whole-brain voxel-wise analyses showed therapeutic success was predicted by enhanced pre-treatment activation to threatening faces in higher-order visual (superior and middle temporal gyrus), cognitive, and emotion processing areas (dorsal anterior cingulate cortex, dorsomedial prefrontal cortex). Moreover, a group by time interaction was revealed in prefrontal regions (dorsomedial, medial gyrus) and insula. The interaction was driven by relatively greater activity during threat processing in SAD, which significantly reduced after CBT but did not significantly predict response to CBT. Therefore, pre-treatment cortical hyperactivity to social threat signals may serve as a prognostic indicator of CBT success in SAD. Collectively, CBT-related brain changes involved a reduction in activity in insula, prefrontal, and extrastriate regions. Results are consistent with cognitive models, which associate decreases in threat processing bias with recovery. Copyright © 2013 Elsevier Inc. All rights reserved.

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.

Industrial Raman gas sensing for real-time system control

NASA Astrophysics Data System (ADS)

Buric, M.; Mullen, J.; Chorpening, B.; Woodruff, S.

2014-06-01

Opportunities exist to improve on-line process control in energy applications with a fast, non-destructive measurement of gas composition. Here, we demonstrate a Raman sensing system which is capable of reporting the concentrations of numerous species simultaneously with sub-percent accuracy and sampling times below one-second for process control applications in energy or chemical production. The sensor is based upon a hollow-core capillary waveguide with a 300 micron bore with reflective thin-film metal and dielectric linings. The effect of using such a waveguide in a Raman process is to integrate Raman photons along the length of the sample-filled waveguide, thus permitting the acquisition of very large Raman signals for low-density gases in a short time. The resultant integrated Raman signals can then be used for quick and accurate analysis of a gaseous mixture. The sensor is currently being tested for energy applications such as coal gasification, turbine control, well-head monitoring for exploration or production, and non-conventional gas utilization. In conjunction with an ongoing commercialization effort, the researchers have recently completed two prototype instruments suitable for hazardous area operation and testing. Here, we report pre-commercialization testing of those field prototypes for control applications in gasification or similar processes. Results will be discussed with respect to accuracy, calibration requirements, gas sampling techniques, and possible control strategies of industrial significance.

EMG-Torque correction on Human Upper extremity using Evolutionary Computation

NASA Astrophysics Data System (ADS)

JL, Veronica; Parasuraman, S.; Khan, M. K. A. Ahamed; Jeba DSingh, Kingsly

2016-09-01

There have been many studies indicating that control system of rehabilitative robot plays an important role in determining the outcome of the therapy process. Existing works have done the prediction of feedback signal in the controller based on the kinematics parameters and EMG readings of upper limb's skeletal system. Kinematics and kinetics based control signal system is developed by reading the output of the sensors such as position sensor, orientation sensor and F/T (Force/Torque) sensor and there readings are to be compared with the preceding measurement to decide on the amount of assistive force. There are also other works that incorporated the kinematics parameters to calculate the kinetics parameters via formulation and pre-defined assumptions. Nevertheless, these types of control signals analyze the movement of the upper limb only based on the movement of the upper joints. They do not anticipate the possibility of muscle plasticity. The focus of the paper is to make use of the kinematics parameters and EMG readings of skeletal system to predict the individual torque of upper extremity's joints. The surface EMG signals are fed into different mathematical models so that these data can be trained through Genetic Algorithm (GA) to find the best correlation between EMG signals and torques acting on the upper limb's joints. The estimated torque attained from the mathematical models is called simulated output. The simulated output will then be compared with the actual individual joint which is calculated based on the real time kinematics parameters of the upper movement of the skeleton when the muscle cells are activated. The findings from this contribution are extended into the development of the active control signal based controller for rehabilitation robot.

Third-Order Spectral Techniques for the Diagnosis of Motor Bearing Condition Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Yang, D.-M.; Stronach, A. F.; MacConnell, P.; Penman, J.

2002-03-01

This paper addresses the development of a novel condition monitoring procedure for rolling element bearings which involves a combination of signal processing, signal analysis and artificial intelligence methods. Seven approaches based on power spectrum, bispectral and bicoherence vibration analyses are investigated as signal pre-processing techniques for application in the diagnosis of a number of induction motor rolling element bearing conditions. The bearing conditions considered are a normal bearing and bearings with cage and inner and outer race faults. The vibration analysis methods investigated are based on the power spectrum, the bispectrum, the bicoherence, the bispectrum diagonal slice, the bicoherence diagonal slice, the summed bispectrum and the summed bicoherence. Selected features are extracted from the vibration signatures so obtained and these are used as inputs to an artificial neural network trained to identify the bearing conditions. Quadratic phase coupling (QPC), examined using the magnitude of bispectrum and bicoherence and biphase, is shown to be absent from the bearing system and it is therefore concluded that the structure of the bearing vibration signatures results from inter-modulation effects. In order to test the proposed procedure, experimental data from a bearing test rig are used to develop an example diagnostic system. Results show that the bearing conditions examined can be diagnosed with a high success rate, particularly when using the summed bispectrum signatures.

A pre-marketing ALT signal predicts post-marketing liver safety.

PubMed

Moylan, Cynthia A; Suzuki, Ayako; Papay, Julie I; Yuen, Nancy A; Ames, Michael; Hunt, Christine M

2012-08-01

Drug induced liver injury during drug development is evidenced by a higher incidence of serum alanine aminotransferase (ALT) elevations in treated versus placebo populations and termed an "ALT signal". We sought to quantify whether an ALT signal in pre-marketing clinical trials predicted post-marketing hepatotoxicity. Incidence of ALT elevations (ALT ≥ 3 times upper limits normal [× ULN]) for drug and placebo of new chemical entities and approved drugs associated with hepatotoxicity was calculated using the Food and Drug Administration (FDA) website. Post-marketing liver safety events were identified using the FDA Adverse Event Reporting System (AERS). The association of FDA AERS signal score (EB05 ≥ 2) and excess risk of pre-marketing ALT elevation (difference in incidence of ALT ≥ 3× ULN in treated versus placebo) was examined. An ALT signal of ≥ 1.2% was significantly associated with a post-marketing liver safety signal (p ≤ 0.013) and a 71.4% positive predictive value. An absent ALT signal was associated with a high likelihood of post-marketing liver safety; negative predictive value of 89.7%. Daily drug dose information improved the prediction of post-marketing liver safety. A cut-off of 1.2% increase in ALT ≥ 3× ULN in treated versus placebo groups provides an easily calculated method for predicting post-marketing liver safety. Published by Elsevier Inc.

Gas turbine engine control system

NASA Technical Reports Server (NTRS)

Idelchik, Michael S. (Inventor)

1991-01-01

A control system and method of controlling a gas turbine engine. The control system receives an error signal and processes the error signal to form a primary fuel control signal. The control system also receives at least one anticipatory demand signal and processes the signal to form an anticipatory fuel control signal. The control system adjusts the value of the anticipatory fuel control signal based on the value of the error signal to form an adjusted anticipatory signal and then the adjusted anticipatory fuel control signal and the primary fuel control signal are combined to form a fuel command signal.

Wavelet analysis to decompose a vibration simulation signal to improve pre-distribution testing of packaging

NASA Astrophysics Data System (ADS)

Griffiths, K. R.; Hicks, B. J.; Keogh, P. S.; Shires, D.

2016-08-01

In general, vehicle vibration is non-stationary and has a non-Gaussian probability distribution; yet existing testing methods for packaging design employ Gaussian distributions to represent vibration induced by road profiles. This frequently results in over-testing and/or over-design of the packaging to meet a specification and correspondingly leads to wasteful packaging and product waste, which represent 15bn per year in the USA and €3bn per year in the EU. The purpose of the paper is to enable a measured non-stationary acceleration signal to be replaced by a constructed signal that includes as far as possible any non-stationary characteristics from the original signal. The constructed signal consists of a concatenation of decomposed shorter duration signals, each having its own kurtosis level. Wavelet analysis is used for the decomposition process into inner and outlier signal components. The constructed signal has a similar PSD to the original signal, without incurring excessive acceleration levels. This allows an improved and more representative simulated input signal to be generated that can be used on the current generation of shaker tables. The wavelet decomposition method is also demonstrated experimentally through two correlation studies. It is shown that significant improvements over current international standards for packaging testing are achievable; hence the potential for more efficient packaging system design is possible.

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

Pierre, John W.; Wies, Richard; Trudnowski, Daniel

Time-synchronized measurements provide rich information for estimating a power-system's electromechanical modal properties via advanced signal processing. This information is becoming critical for the improved operational reliability of interconnected grids. A given mode's properties are described by its frequency, damping, and shape. Modal frequencies and damping are useful indicators of power-system stress, usually declining with increased load or reduced grid capacity. Mode shape provides critical information for operational control actions. This project investigated many advanced techniques for power system identification from measured data focusing on mode frequency and damping ratio estimation. Investigators from the three universities coordinated their effort with Pacificmore » Northwest National Laboratory (PNNL). Significant progress was made on developing appropriate techniques for system identification with confidence intervals and testing those techniques on field measured data and through simulation. Experimental data from the western area power system was provided by PNNL and Bonneville Power Administration (BPA) for both ambient conditions and for signal injection tests. Three large-scale tests were conducted for the western area in 2005 and 2006. Measured field PMU (Phasor Measurement Unit) data was provided to the three universities. A 19-machine simulation model was enhanced for testing the system identification algorithms. Extensive simulations were run with this model to test the performance of the algorithms. University of Wyoming researchers participated in four primary activities: (1) Block and adaptive processing techniques for mode estimation from ambient signals and probing signals, (2) confidence interval estimation, (3) probing signal design and injection method analysis, and (4) performance assessment and validation from simulated and field measured data. Subspace based methods have been use to improve previous results from block processing techniques. Bootstrap techniques have been developed to estimate confidence intervals for the electromechanical modes from field measured data. Results were obtained using injected signal data provided by BPA. A new probing signal was designed that puts more strength into the signal for a given maximum peak to peak swing. Further simulations were conducted on a model based on measured data and with the modifications of the 19-machine simulation model. Montana Tech researchers participated in two primary activities: (1) continued development of the 19-machine simulation test system to include a DC line; and (2) extensive simulation analysis of the various system identification algorithms and bootstrap techniques using the 19 machine model. Researchers at the University of Alaska-Fairbanks focused on the development and testing of adaptive filter algorithms for mode estimation using data generated from simulation models and on data provided in collaboration with BPA and PNNL. There efforts consist of pre-processing field data, testing and refining adaptive filter techniques (specifically the Least Mean Squares (LMS), the Adaptive Step-size LMS (ASLMS), and Error Tracking (ET) algorithms). They also improved convergence of the adaptive algorithms by using an initial estimate from block processing AR method to initialize the weight vector for LMS. Extensive testing was performed on simulated data from the 19 machine model. This project was also extensively involved in the WECC (Western Electricity Coordinating Council) system wide tests carried out in 2005 and 2006. These tests involved injecting known probing signals into the western power grid. One of the primary goals of these tests was the reliable estimation of electromechanical mode properties from measured PMU data. Applied to the system were three types of probing inputs: (1) activation of the Chief Joseph Dynamic Brake, (2) mid-level probing at the Pacific DC Intertie (PDCI), and (3) low-level probing on the PDCI. The Chief Joseph Dynamic Brake is a 1400 MW disturbance to the system and is injected for a half of a second. For the mid and low-level probing, the Celilo terminal of the PDCI is modulated with a known probing signal. Similar but less extensive tests were conducted in June of 2000. The low-level probing signals were designed at the University of Wyoming. A number of important design factors are considered. The designed low-level probing signal used in the tests is a multi-sine signal. Its frequency content is focused in the range of the inter-area electromechanical modes. The most frequently used of these low-level multi-sine signals had a period of over two minutes, a root-mean-square (rms) value of 14 MW, and a peak magnitude of 20 MW. Up to 15 cycles of this probing signal were injected into the system resulting in a processing gain of 15. The resulting measured response at points throughout the system was not much larger than the ambient noise present in the measurements.« less

Design of signal reception and processing system of embedded ultrasonic endoscope

NASA Astrophysics Data System (ADS)

Li, Ming; Yu, Feng; Zhang, Ruiqiang; Li, Yan; Chen, Xiaodong; Yu, Daoyin

2009-11-01

Embedded Ultrasonic Endoscope, based on embedded microprocessor and embedded real-time operating system, sends a micro ultrasonic probe into coelom through the biopsy channel of the Electronic Endoscope to get the fault histology features of digestive organs by rotary scanning, and acquires the pictures of the alimentary canal mucosal surface. At the same time, ultrasonic signals are processed by signal reception and processing system, forming images of the full histology of the digestive organs. Signal Reception and Processing System is an important component of Embedded Ultrasonic Endoscope. However, the traditional design, using multi-level amplifiers and special digital processing circuits to implement signal reception and processing, is no longer satisfying the standards of high-performance, miniaturization and low power requirements that embedded system requires, and as a result of the high noise that multi-level amplifier brought, the extraction of small signal becomes hard. Therefore, this paper presents a method of signal reception and processing based on double variable gain amplifier and FPGA, increasing the flexibility and dynamic range of the Signal Reception and Processing System, improving system noise level, and reducing power consumption. Finally, we set up the embedded experiment system, using a transducer with the center frequency of 8MHz to scan membrane samples, and display the image of ultrasonic echo reflected by each layer of membrane, with a frame rate of 5Hz, verifying the correctness of the system.

Audio reproduction for personal ambient home assistance: concepts and evaluations for normal-hearing and hearing-impaired persons.

PubMed

Huber, Rainer; Meis, Markus; Klink, Karin; Bartsch, Christian; Bitzer, Joerg

2014-01-01

Within the Lower Saxony Research Network Design of Environments for Ageing (GAL), a personal activity and household assistant (PAHA), an ambient reminder system, has been developed. One of its central output modality to interact with the user is sound. The study presented here evaluated three different system technologies for sound reproduction using up to five loudspeakers, including the "phantom source" concept. Moreover, a technology for hearing loss compensation for the mostly older users of the PAHA was implemented and evaluated. Evaluation experiments with 21 normal hearing and hearing impaired test subjects were carried out. The results show that after direct comparison of the sound presentation concepts, the presentation by the single TV speaker was most preferred, whereas the phantom source concept got the highest acceptance ratings as far as the general concept is concerned. The localization accuracy of the phantom source concept was good as long as the exact listening position was known to the algorithm and speech stimuli were used. Most subjects preferred the original signals over the pre-processed, dynamic-compressed signals, although processed speech was often described as being clearer.

Feature selection for wearable smartphone-based human activity recognition with able bodied, elderly, and stroke patients.

PubMed

Capela, Nicole A; Lemaire, Edward D; Baddour, Natalie

2015-01-01

Human activity recognition (HAR), using wearable sensors, is a growing area with the potential to provide valuable information on patient mobility to rehabilitation specialists. Smartphones with accelerometer and gyroscope sensors are a convenient, minimally invasive, and low cost approach for mobility monitoring. HAR systems typically pre-process raw signals, segment the signals, and then extract features to be used in a classifier. Feature selection is a crucial step in the process to reduce potentially large data dimensionality and provide viable parameters to enable activity classification. Most HAR systems are customized to an individual research group, including a unique data set, classes, algorithms, and signal features. These data sets are obtained predominantly from able-bodied participants. In this paper, smartphone accelerometer and gyroscope sensor data were collected from populations that can benefit from human activity recognition: able-bodied, elderly, and stroke patients. Data from a consecutive sequence of 41 mobility tasks (18 different tasks) were collected for a total of 44 participants. Seventy-six signal features were calculated and subsets of these features were selected using three filter-based, classifier-independent, feature selection methods (Relief-F, Correlation-based Feature Selection, Fast Correlation Based Filter). The feature subsets were then evaluated using three generic classifiers (Naïve Bayes, Support Vector Machine, j48 Decision Tree). Common features were identified for all three populations, although the stroke population subset had some differences from both able-bodied and elderly sets. Evaluation with the three classifiers showed that the feature subsets produced similar or better accuracies than classification with the entire feature set. Therefore, since these feature subsets are classifier-independent, they should be useful for developing and improving HAR systems across and within populations.

Feature Selection for Wearable Smartphone-Based Human Activity Recognition with Able bodied, Elderly, and Stroke Patients

PubMed Central

2015-01-01

Human activity recognition (HAR), using wearable sensors, is a growing area with the potential to provide valuable information on patient mobility to rehabilitation specialists. Smartphones with accelerometer and gyroscope sensors are a convenient, minimally invasive, and low cost approach for mobility monitoring. HAR systems typically pre-process raw signals, segment the signals, and then extract features to be used in a classifier. Feature selection is a crucial step in the process to reduce potentially large data dimensionality and provide viable parameters to enable activity classification. Most HAR systems are customized to an individual research group, including a unique data set, classes, algorithms, and signal features. These data sets are obtained predominantly from able-bodied participants. In this paper, smartphone accelerometer and gyroscope sensor data were collected from populations that can benefit from human activity recognition: able-bodied, elderly, and stroke patients. Data from a consecutive sequence of 41 mobility tasks (18 different tasks) were collected for a total of 44 participants. Seventy-six signal features were calculated and subsets of these features were selected using three filter-based, classifier-independent, feature selection methods (Relief-F, Correlation-based Feature Selection, Fast Correlation Based Filter). The feature subsets were then evaluated using three generic classifiers (Naïve Bayes, Support Vector Machine, j48 Decision Tree). Common features were identified for all three populations, although the stroke population subset had some differences from both able-bodied and elderly sets. Evaluation with the three classifiers showed that the feature subsets produced similar or better accuracies than classification with the entire feature set. Therefore, since these feature subsets are classifier-independent, they should be useful for developing and improving HAR systems across and within populations. PMID:25885272

A comprehensive analysis of 3′ end sequencing data sets reveals novel polyadenylation signals and the repressive role of heterogeneous ribonucleoprotein C on cleavage and polyadenylation

PubMed Central

Gruber, Andreas J.; Schmidt, Ralf; Gruber, Andreas R.; Martin, Georges; Ghosh, Souvik; Belmadani, Manuel; Keller, Walter

2016-01-01

Alternative polyadenylation (APA) is a general mechanism of transcript diversification in mammals, which has been recently linked to proliferative states and cancer. Different 3′ untranslated region (3′ UTR) isoforms interact with different RNA-binding proteins (RBPs), which modify the stability, translation, and subcellular localization of the corresponding transcripts. Although the heterogeneity of pre-mRNA 3′ end processing has been established with high-throughput approaches, the mechanisms that underlie systematic changes in 3′ UTR lengths remain to be characterized. Through a uniform analysis of a large number of 3′ end sequencing data sets, we have uncovered 18 signals, six of which are novel, whose positioning with respect to pre-mRNA cleavage sites indicates a role in pre-mRNA 3′ end processing in both mouse and human. With 3′ end sequencing we have demonstrated that the heterogeneous ribonucleoprotein C (HNRNPC), which binds the poly(U) motif whose frequency also peaks in the vicinity of polyadenylation (poly(A)) sites, has a genome-wide effect on poly(A) site usage. HNRNPC-regulated 3′ UTRs are enriched in ELAV-like RBP 1 (ELAVL1) binding sites and include those of the CD47 gene, which participate in the recently discovered mechanism of 3′ UTR–dependent protein localization (UDPL). Our study thus establishes an up-to-date, high-confidence catalog of 3′ end processing sites and poly(A) signals, and it uncovers an important role of HNRNPC in regulating 3′ end processing. It further suggests that U-rich elements mediate interactions with multiple RBPs that regulate different stages in a transcript's life cycle. PMID:27382025

Coordinated pre-preemption of traffic signals to enhance railroad grade crossing safety in urban areas and estimation of train impacts to arterial travel time delay.

DOT National Transportation Integrated Search

2014-01-01

This research project investigated the potential for using advanced features of traffic signal system software platforms : (ATMS.now), prevalent in Florida, to alleviate safety and mobility problems at highway-railroad at-grade crossings and : adjace...

The design of CMOS general-purpose analog front-end circuit with tunable gain and bandwidth for biopotential signal recording systems.

PubMed

Chen, Wei-Ming; Yang, Wen-Chia; Tsai, Tzung-Yun; Chiueh, Herming; Wu, Chung-Yu

2011-01-01

In this paper an 8-channel CMOS general-purpose analog front-end (AFE) circuit with tunable gain and bandwidth for biopotential signal recording systems is presented. The proposed AFE consists of eight chopper stabilized pre-amplifiers, an 8-to-1 analog multiplexer, and a programmable gain amplifier. It can be used to sense and amplify different kinds of biopotential signals, such as electrocorticogram (ECoG), electrocardiogram (ECG) and electromyogram (EMG). The AFE chip is designed and fabricated in 0.18-μm CMOS technology. The measured maximum gain of AFE is 60.8 dB. The low cutoff frequency can achieve as low as 0.8 Hz and high cutoff frequency can be adjusted from 200 Hz to 10 kHz to suit for different kinds of biopotential signals. The measured input-referred noise is 0.9 μV(rms), with the power consumption of 18μW per channel at 1.8-V power supply. And the noise efficiency factor (NEF) is only 1.3 for pre-amplifier.

On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP.

PubMed

Winkler, Irene; Debener, Stefan; Müller, Klaus-Robert; Tangermann, Michael

2015-01-01

Standard artifact removal methods for electroencephalographic (EEG) signals are either based on Independent Component Analysis (ICA) or they regress out ocular activity measured at electrooculogram (EOG) channels. Successful ICA-based artifact reduction relies on suitable pre-processing. Here we systematically evaluate the effects of high-pass filtering at different frequencies. Offline analyses were based on event-related potential data from 21 participants performing a standard auditory oddball task and an automatic artifactual component classifier method (MARA). As a pre-processing step for ICA, high-pass filtering between 1-2 Hz consistently produced good results in terms of signal-to-noise ratio (SNR), single-trial classification accuracy and the percentage of `near-dipolar' ICA components. Relative to no artifact reduction, ICA-based artifact removal significantly improved SNR and classification accuracy. This was not the case for a regression-based approach to remove EOG artifacts.

Neurotrophin Propeptides: Biological Functions and Molecular Mechanisms.

PubMed

Rafieva, Lola M; Gasanov, Eugene V

2016-01-01

Neurotrophins constitute a family of growth factors that play a key role in the regulation of the development and function of the central and peripheral nervous systems. A common feature of all the neurotrophins is their synthesis in cells as long precursors (pre-pro-neurotrophins) that contain an N-terminal signal peptide, a following propeptide and the mature neurotrophin. Although the signal peptide functions have been well studied, the role of neurotrophin propeptides is not so clear. Here, we briefly summarize the biochemistry of neurotrophin propeptides, including their role as folding-assistants for the mature factor and their role in processing and in secretion of neurotrophins. In the main part of the review we summarize our current state of knowledge of the biological activity of neurotrophin propeptides, their possible mechanisms of action, and their potential influence on the activity of the mature neurotrophins.

Single-Chip FPGA Azimuth Pre-Filter for SAR

NASA Technical Reports Server (NTRS)

Gudim, Mimi; Cheng, Tsan-Huei; Madsen, Soren; Johnson, Robert; Le, Charles T-C; Moghaddam, Mahta; Marina, Miguel

2005-01-01

A field-programmable gate array (FPGA) on a single lightweight, low-power integrated-circuit chip has been developed to implement an azimuth pre-filter (AzPF) for a synthetic-aperture radar (SAR) system. The AzPF is needed to enable more efficient use of data-transmission and data-processing resources: In broad terms, the AzPF reduces the volume of SAR data by effectively reducing the azimuth resolution, without loss of range resolution, during times when end users are willing to accept lower azimuth resolution as the price of rapid access to SAR imagery. The data-reduction factor is selectable at a decimation factor, M, of 2, 4, 8, 16, or 32 so that users can trade resolution against processing and transmission delays. In principle, azimuth filtering could be performed in the frequency domain by use of fast-Fourier-transform processors. However, in the AzPF, azimuth filtering is performed in the time domain by use of finite-impulse-response filters. The reason for choosing the time-domain approach over the frequency-domain approach is that the time-domain approach demands less memory and a lower memory-access rate. The AzPF operates on the raw digitized SAR data. The AzPF includes a digital in-phase/quadrature (I/Q) demodulator. In general, an I/Q demodulator effects a complex down-conversion of its input signal followed by low-pass filtering, which eliminates undesired sidebands. In the AzPF case, the I/Q demodulator takes offset video range echo data to the complex baseband domain, ensuring preservation of signal phase through the azimuth pre-filtering process. In general, in an SAR I/Q demodulator, the intermediate frequency (fI) is chosen to be a quarter of the range-sampling frequency and the pulse-repetition frequency (fPR) is chosen to be a multiple of fI. The AzPF also includes a polyphase spatial-domain pre-filter comprising four weighted integrate-and-dump filters with programmable decimation factors and overlapping phases. To prevent aliasing of signals, the bandwidth of the AzPF is made 80 percent of fPR/M. The choice of four as the number of overlapping phases is justified by prior research in which it was shown that a filter of length 4M can effect an acceptable transfer function. The figure depicts prototype hardware comprising the AzPF and ancillary electronic circuits. The hardware was found to satisfy performance requirements in real-time tests at a sampling rate of 100 MHz.

Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

DOE PAGES

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika; ...

2016-01-19

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensormore » systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.« less

Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

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

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensormore » systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.« less

Biologically-based signal processing system applied to noise removal for signal extraction

DOEpatents

Fu, Chi Yung; Petrich, Loren I.

2004-07-13

The method and system described herein use a biologically-based signal processing system for noise removal for signal extraction. A wavelet transform may be used in conjunction with a neural network to imitate a biological system. The neural network may be trained using ideal data derived from physical principles or noiseless signals to determine to remove noise from the signal.

Treatment of hazardous landfill leachate using Fenton process followed by a combined (UASB/DHS) system.

PubMed

Ismail, Sherif; Tawfik, Ahmed

2016-01-01

Fenton process for pre-treatment of hazardous landfill leachate (HLL) was investigated. Total, particulate and soluble chemical oxygen demand (CODt, CODp and CODs) removal efficiency amounted to 67%, 47% and 64%, respectively, at pH value of 3.5, molar ratio (H2O2/Fe(2+)) of 5, H2O2 dosage of 25 ml/L and contact time of 15 min. Various treatment scenarios were attempted and focused on studying the effect of pre-catalytic oxidation process on the performance of up-flow anaerobic sludge blanket (UASB), UASB/down-flow hanging sponge (DHS) and DHS system. The results obtained indicated that pre-catalytic oxidation process improved the CODt removal efficiency in the UASB reactor by a value of 51.4%. Overall removal efficiencies of CODt, CODs and CODp were 80 ± 6%, 80 ± 7% and 78 ± 16% for UASB/DHS treating pre-catalytic oxidation effluent, respectively. The removal efficiencies of CODt, CODs and CODp were, respectively, decreased to 54 ± 2%, 49 ± 2% and 71 ± 16% for UASB/DHS system without pre-treatment. However, the results for the combined process (UASB/DHS) system is almost similar to those obtained for UASB reactor treating pre-catalytic oxidation effluent. The DHS system achieved average removal efficiencies of 52 ± 4% for CODt, 51 ± 4% for CODs and 52 ± 15% for CODp. A higher COD fractions removal was obtained when HLL was pre-treated by Fenton reagent. The combined processes provided a removal efficiency of 85 ± 1% for CODt, 85 ± 1% for CODs and 83 ± 8% for CODp. The DHS system is not only effective for organics degradation but also for ammonia oxidation. Almost complete ammonia (NH4-N) removal (92 ± 3.6%) was occurred and the nitrate production amounted to 37 ± 6 mg/L in the treated effluent. This study strongly recommends applying Fenton process followed by DHS system for treatment of HLL.

Inspection Tools

NASA Astrophysics Data System (ADS)

1989-01-01

A "NASA Tech Briefs" article describing an inspection tool and technique known as Optically Stimulated Electron Emission (OSEE) led to the formation of Photo Acoustic Technology, Inc. (PAT). PAT produces sensors and scanning systems which assure surface cleanliness prior to bonding, coating, painting, etc. The company's OP1000 series realtime pre-processing detection capability assures 100 percent surface quality testing. The technique involves brief exposure of the inspection surface to ultraviolet radiation. The energy interacts with the surface layer, causing free electrons to be emitted from the surface to be picked up by the detector. When contamination is present, it interferes with the electron flow in proportion to the thickness of the contaminant layer enabling measurement by system signal output. OP1000 systems operate in conventional atmospheres on all types of material and detect both organic and inorganic contamination.

Predicting seizures in untreated temporal lobe epilepsy using point-process nonlinear models of heartbeat dynamics.

PubMed

Valenza, G; Romigi, A; Citi, L; Placidi, F; Izzi, F; Albanese, M; Scilingo, E P; Marciani, M G; Duggento, A; Guerrisi, M; Toschi, N; Barbieri, R

2016-08-01

Symptoms of temporal lobe epilepsy (TLE) are frequently associated with autonomic dysregulation, whose underlying biological processes are thought to strongly contribute to sudden unexpected death in epilepsy (SUDEP). While abnormal cardiovascular patterns commonly occur during ictal events, putative patterns of autonomic cardiac effects during pre-ictal (PRE) periods (i.e. periods preceding seizures) are still unknown. In this study, we investigated TLE-related heart rate variability (HRV) through instantaneous, nonlinear estimates of cardiovascular oscillations during inter-ictal (INT) and PRE periods. ECG recordings from 12 patients with TLE were processed to extract standard HRV indices, as well as indices of instantaneous HRV complexity (dominant Lyapunov exponent and entropy) and higher-order statistics (bispectra) obtained through definition of inhomogeneous point-process nonlinear models, employing Volterra-Laguerre expansions of linear, quadratic, and cubic kernels. Experimental results demonstrate that the best INT vs. PRE classification performance (balanced accuracy: 73.91%) was achieved only when retaining the time-varying, nonlinear, and non-stationary structure of heartbeat dynamical features. The proposed approach opens novel important avenues in predicting ictal events using information gathered from cardiovascular signals exclusively.

Signal transduction and amplification through enzyme-triggered ligand release and accelerated catalysis.

PubMed

Goggins, Sean; Marsh, Barrie J; Lubben, Anneke T; Frost, Christopher G

2015-08-01

Signal transduction and signal amplification are both important mechanisms used within biological signalling pathways. Inspired by this process, we have developed a signal amplification methodology that utilises the selectivity and high activity of enzymes in combination with the robustness and generality of an organometallic catalyst, achieving a hybrid biological and synthetic catalyst cascade. A proligand enzyme substrate was designed to selectively self-immolate in the presence of the enzyme to release a ligand that can bind to a metal pre-catalyst and accelerate the rate of a transfer hydrogenation reaction. Enzyme-triggered catalytic signal amplification was then applied to a range of catalyst substrates demonstrating that signal amplification and signal transduction can both be achieved through this methodology.

Design and Verification of a Digital Controller for a 2-Piece Hemispherical Resonator Gyroscope

PubMed Central

Lee, Jungshin; Yun, Sung Wook; Rhim, Jaewook

2016-01-01

A Hemispherical Resonator Gyro (HRG) is the Coriolis Vibratory Gyro (CVG) that measures rotation angle or angular velocity using Coriolis force acting the vibrating mass. A HRG can be used as a rate gyro or integrating gyro without structural modification by simply changing the control scheme. In this paper, differential control algorithms are designed for a 2-piece HRG. To design a precision controller, the electromechanical modelling and signal processing must be pre-performed accurately. Therefore, the equations of motion for the HRG resonator with switched harmonic excitations are derived with the Duhamel Integral method. Electromechanical modeling of the resonator, electric module and charge amplifier is performed by considering the mode shape of a thin hemispherical shell. Further, signal processing and control algorithms are designed. The multi-flexing scheme of sensing, driving cycles and x, y-axis switching cycles is appropriate for high precision and low maneuverability systems. The differential control scheme is easily capable of rejecting the common mode errors of x, y-axis signals and changing the rate integrating mode on basis of these studies. In the rate gyro mode the controller is composed of Phase-Locked Loop (PLL), amplitude, quadrature and rate control loop. All controllers are designed on basis of a digital PI controller. The signal processing and control algorithms are verified through Matlab/Simulink simulations. Finally, a FPGA and DSP board with these algorithms is verified through experiments. PMID:27104539

SVM-Based System for Prediction of Epileptic Seizures from iEEG Signal

PubMed Central

Cherkassky, Vladimir; Lee, Jieun; Veber, Brandon; Patterson, Edward E.; Brinkmann, Benjamin H.; Worrell, Gregory A.

2017-01-01

Objective This paper describes a data-analytic modeling approach for prediction of epileptic seizures from intracranial electroencephalogram (iEEG) recording of brain activity. Even though it is widely accepted that statistical characteristics of iEEG signal change prior to seizures, robust seizure prediction remains a challenging problem due to subject-specific nature of data-analytic modeling. Methods Our work emphasizes understanding of clinical considerations important for iEEG-based seizure prediction, and proper translation of these clinical considerations into data-analytic modeling assumptions. Several design choices during pre-processing and post-processing are considered and investigated for their effect on seizure prediction accuracy. Results Our empirical results show that the proposed SVM-based seizure prediction system can achieve robust prediction of preictal and interictal iEEG segments from dogs with epilepsy. The sensitivity is about 90–100%, and the false-positive rate is about 0–0.3 times per day. The results also suggest good prediction is subject-specific (dog or human), in agreement with earlier studies. Conclusion Good prediction performance is possible only if the training data contain sufficiently many seizure episodes, i.e., at least 5–7 seizures. Significance The proposed system uses subject-specific modeling and unbalanced training data. This system also utilizes three different time scales during training and testing stages. PMID:27362758

Fast Sparse Coding for Range Data Denoising with Sparse Ridges Constraint.

PubMed

Gao, Zhi; Lao, Mingjie; Sang, Yongsheng; Wen, Fei; Ramesh, Bharath; Zhai, Ruifang

2018-05-06

Light detection and ranging (LiDAR) sensors have been widely deployed on intelligent systems such as unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) to perform localization, obstacle detection, and navigation tasks. Thus, research into range data processing with competitive performance in terms of both accuracy and efficiency has attracted increasing attention. Sparse coding has revolutionized signal processing and led to state-of-the-art performance in a variety of applications. However, dictionary learning, which plays the central role in sparse coding techniques, is computationally demanding, resulting in its limited applicability in real-time systems. In this study, we propose sparse coding algorithms with a fixed pre-learned ridge dictionary to realize range data denoising via leveraging the regularity of laser range measurements in man-made environments. Experiments on both synthesized data and real data demonstrate that our method obtains accuracy comparable to that of sophisticated sparse coding methods, but with much higher computational efficiency.

Bone marrow stromal-B cell interactions in polycyclic aromatic hydrocarbon-induced pro/pre-B cell apoptosis.

PubMed

Allan, Lenka L; Mann, Koren K; Matulka, Raymond A; Ryu, Heui-Young; Schlezinger, Jennifer J; Sherr, David H

2003-12-01

Environmental polycyclic aromatic hydrocarbons (PAH) and related halogenated hydrocarbons are immunotoxic in a variety of systems. In a model system of B lymphopoiesis, PAH exposure rapidly induces apoptosis in CD43- pre-B and CD43+ pro/pre-B cells. Apoptosis induction by 7,12-dimethylbenzo[a]anthracene (DMBA) is dependent upon AhR+ bone marrow stromal cells and likely involves DMBA metabolism within the stromal cell. However, it is not known if PAH-treated stromal cells release free metabolites or soluble factors that may directly induce B cell death or if the effector death signal is delivered by stromal cell-B cell contact. Here, we demonstrate that supernatants from DMBA-treated bone marrow stromal cells contain an activity capable of inducing apoptosis in pro/pre-B cells cocultured with stromal cells. This activity (1) is not produced when stromal cells are cotreated with DMBA and alpha-naphthoflavone (alpha-NF), an aryl hydrocarbon receptor (AhR) and cytochrome P-450 inhibitor, (2) is > or = 50 kDa, (3) is trypsin and heat sensitive, and (4) is dependent on AhR+ stromal cells, which in turn deliver the effector death signal to pro/pre-B cells. The results (1) argue against a role for a soluble, stromal cell-derived cytokine as the effector of PAH-induced pro/pre-B cell death, (2) exclude the possibility of a free metabolite acting directly on AhR- pro/pre-B cell targets, and (3) suggest the elaboration by stromal cells of a relatively stable, DMBA metabolite-protein complex capable of acting on other stromal cells at some distance. Collectively, these studies suggest that, while stromal cell products, e.g., metabolite-protein complexes, may affect the function of distant stromal cells, the effector death signal delivered by stromal cells to bone marrow B cells is mediated by cell-cell contact.

A new fibre optic pulse oximeter probe for monitoring splanchnic organ arterial blood oxygen saturation.

PubMed

Hickey, M; Samuels, N; Randive, N; Langford, R; Kyriacou, P A

2012-12-01

A new, continuous method of monitoring splanchnic organ oxygen saturation (SpO(2)) would make the early detection of inadequate tissue oxygenation feasible, reducing the risk of hypoperfusion, severe ischaemia, and, ultimately, death. In an attempt to provide such a device, a new fibre optic based reflectance pulse oximeter probe and processing system were developed followed by an in vivo evaluation of the technology on seventeen patients undergoing elective laparotomy. Photoplethysmographic (PPG) signals of good quality and high signal-to-noise ratio were obtained from the small bowel, large bowel, liver and stomach. Simultaneous peripheral PPG signals from the finger were also obtained for comparison purposes. Analysis of the amplitudes of all acquired PPG signals indicated much larger amplitudes for those signals obtained from splanchnic organs than those obtained from the finger. Estimated SpO(2) values for splanchnic organs showed good agreement with those obtained from the finger fibre optic probe and those obtained from a commercial device. These preliminary results suggest that a miniaturized 'indwelling' fibre optic sensor may be a suitable method for pre-operative and post-operative evaluation of splanchnic organ SpO(2) and their health. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

A Review of Classification Techniques of EMG Signals during Isotonic and Isometric Contractions

PubMed Central

Nazmi, Nurhazimah; Abdul Rahman, Mohd Azizi; Yamamoto, Shin-Ichiroh; Ahmad, Siti Anom; Zamzuri, Hairi; Mazlan, Saiful Amri

2016-01-01

In recent years, there has been major interest in the exposure to physical therapy during rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and human machine interface (HMI) applications. An automated system will guide the user to perform the training during rehabilitation independently. Advances in engineering have extended electromyography (EMG) beyond the traditional diagnostic applications to also include applications in diverse areas such as movement analysis. This paper gives an overview of the numerous methods available to recognize motion patterns of EMG signals for both isotonic and isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who would like to select the most appropriate methodology in classifying motion patterns, especially during different types of contractions. For feature extraction, the probability density function (PDF) of EMG signals will be the main interest of this study. Following that, a brief explanation of the different methods for pre-processing, feature extraction and classifying EMG signals will be compared in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above. PMID:27548165

Fiber-wireless transmission system of 108  Gb/sdata over 80 km fiber and 2×2multiple-input multiple-output wireless links at 100 GHz W-band frequency.

PubMed

Li, Xinying; Dong, Ze; Yu, Jianjun; Chi, Nan; Shao, Yufeng; Chang, G K

2012-12-15

We experimentally demonstrate a seamlessly integrated fiber-wireless system that delivers a 108  Gb/s signal through 80 km fiber and 1 m wireless transport over free space at 100 GHz adopting polarization-division-multiplexing quadrature-phase-shift-keying (PDM-QPSK) modulation and heterodyning coherent detection. The X- and Y-polarization components of the optical PDM-QPSK baseband signal are simultaneously upconverted to 100 GHz wireless carrier by optical polarization-diversity heterodyne beating, and then independently transmitted and received by two pairs of transmitter and receiver antennas, which form a 2×2 multiple-input multiple-output wireless link. At the wireless receiver, two-stage downconversion is performed firstly in the analog domain based on balanced mixer and sinusoidal radio frequency signal, and then in the digital domain based on digital signal processing (DSP). Polarization demultiplexing is realized by the constant modulus algorithm in the DSP part at the receiver. The bit-error ratio for the 108  Gb/s PDM-QPSK signal is less than the pre-forward-error-correction threshold of 3.8×10(-3) after both 1 m wireless delivery at 100 GHz and 80 km single-mode fiber-28 transmission. To our knowledge, this is the first demonstration to realize 100  Gb/s signal delivery through both fiber and wireless links at 100 GHz.

System and Method for Multi-Wavelength Optical Signal Detection

NASA Technical Reports Server (NTRS)

McGlone, Thomas D. (Inventor)

2017-01-01

The system and method for multi-wavelength optical signal detection enables the detection of optical signal levels significantly below those processed at the discrete circuit level by the use of mixed-signal processing methods implemented with integrated circuit technologies. The present invention is configured to detect and process small signals, which enables the reduction of the optical power required to stimulate detection networks, and lowers the required laser power to make specific measurements. The present invention provides an adaptation of active pixel networks combined with mixed-signal processing methods to provide an integer representation of the received signal as an output. The present invention also provides multi-wavelength laser detection circuits for use in various systems, such as a differential absorption light detection and ranging system.

Signal processing and electronic noise in LZ

NASA Astrophysics Data System (ADS)

Khaitan, D.

2016-03-01

The electronics of the LUX-ZEPLIN (LZ) experiment, the 10-tonne dark matter detector to be installed at the Sanford Underground Research Facility (SURF), consists of low-noise dual-gain amplifiers and a 100-MHz, 14-bit data acquisition system for the TPC PMTs. Pre-prototypes of the analog amplifiers and the 32-channel digitizers were tested extensively with simulated pulses that are similar to the prompt scintillation light and the electroluminescence signals expected in LZ. These studies are used to characterize the noise and to measure the linearity of the system. By increasing the amplitude of the test signals, the effect of saturating the amplifier and the digitizers was studied. The RMS ADC noise of the digitizer channels was measured to be 1.19± 0.01 ADCC. When a high-energy channel of the amplifier is connected to the digitizer, the measured noise remained virtually unchanged, while the noise added by a low-energy channel was estimated to be 0.38 ± 0.02 ADCC (46 ± 2 μV). A test facility is under construction to study saturation, mitigate noise and measure the performance of the LZ electronics and data acquisition chain.

ELAV, a Drosophila neuron-specific protein, mediates the generation of an alternatively spliced neural protein isoform.

PubMed

Koushika, S P; Lisbin, M J; White, K

1996-12-01

Tissue-specific alternative pre-mRNA splicing is a widely used mechanism for gene regulation and the generation of different protein isoforms, but relatively little is known about the factors and mechanisms that mediate this process. Tissue-specific RNA-binding proteins could mediate alternative pre-mRNA splicing. In Drosophila melanogaster, the RNA-binding protein encoded by the elav (embryonic lethal abnormal visual system) gene is a candidate for such a role. The ELAV protein is expressed exclusively in neurons, and is important for the formation and maintenance of the nervous system. In this study, photoreceptor neurons genetically depleted of ELAV, and elav-null central nervous system neurons, were analyzed immunocytochemically for the expression of neural proteins. In both situations, the lack of ELAV corresponded with a decrease in the immunohistochemical signal of the neural-specific isoform of Neuroglian, which is generated by alternative splicing. Furthermore, when ELAV was expressed ectopically in cells that normally express only the non-neural isoform of Neuroglian, we observed the generation of the neural isoform of Neuroglian. Drosophila ELAV promotes the generation of the neuron-specific isoform of Neuroglian by the regulation of pre-mRNA splicing. The findings reported in this paper demonstrate that ELAV is necessary, and the ectopic expression of ELAV in imaginal disc cells is sufficient, to mediate neuron-specific alternative splicing.

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.

Semantic memory retrieval circuit: role of pre-SMA, caudate, and thalamus.

PubMed

Hart, John; Maguire, Mandy J; Motes, Michael; Mudar, Raksha Anand; Chiang, Hsueh-Sheng; Womack, Kyle B; Kraut, Michael A

2013-07-01

We propose that pre-supplementary motor area (pre-SMA)-thalamic interactions govern processes fundamental to semantic retrieval of an integrated object memory. At the onset of semantic retrieval, pre-SMA initiates electrical interactions between multiple cortical regions associated with semantic memory subsystems encodings as indexed by an increase in theta-band EEG power. This starts between 100-150 ms after stimulus presentation and is sustained throughout the task. We posit that this activity represents initiation of the object memory search, which continues in searching for an object memory. When the correct memory is retrieved, there is a high beta-band EEG power increase, which reflects communication between pre-SMA and thalamus, designates the end of the search process and resultant in object retrieval from multiple semantic memory subsystems. This high beta signal is also detected in cortical regions. This circuit is modulated by the caudate nuclei to facilitate correct and suppress incorrect target memories. Copyright © 2012 Elsevier Inc. All rights reserved.

Operational calm and the optimum regulation of human working capacity

NASA Technical Reports Server (NTRS)

Ilin, Y. P.

1975-01-01

Muscle hardness measurements in a squeezing dynamometer test are interpreted for expressions of adjustment effects of the central nervous system in rapid response to a starting signal. It is shown that preliminary muscle tension leads to the transmission of inhibiting proprioceptive impulses to the nervous system centers and that the degree of pre-working changes depends on the individual's typological personality characteristics. Concentration of attention during the pre-working adjustment is considered the primary emotional factor that controls sensorimotor performance.

Apparatus and Method for Assessing Vestibulo-Ocular Function

NASA Technical Reports Server (NTRS)

Shelhamer, Mark J. (Inventor)

2015-01-01

A system for assessing vestibulo-ocular function includes a motion sensor system adapted to be coupled to a user's head; a data processing system configured to communicate with the motion sensor system to receive the head-motion signals; a visual display system configured to communicate with the data processing system to receive image signals from the data processing system; and a gain control device arranged to be operated by the user and to communicate gain adjustment signals to the data processing system.

Fourier Transform Spectrometer System

NASA Technical Reports Server (NTRS)

Campbell, Joel F. (Inventor)

2014-01-01

A Fourier transform spectrometer (FTS) data acquisition system includes an FTS spectrometer that receives a spectral signal and a laser signal. The system further includes a wideband detector, which is in communication with the FTS spectrometer and receives the spectral signal and laser signal from the FTS spectrometer. The wideband detector produces a composite signal comprising the laser signal and the spectral signal. The system further comprises a converter in communication with the wideband detector to receive and digitize the composite signal. The system further includes a signal processing unit that receives the composite signal from the converter. The signal processing unit further filters the laser signal and the spectral signal from the composite signal and demodulates the laser signal, to produce velocity corrected spectral data.

Can pharmaco-electroencephalography help improve survival of central nervous system drugs in early clinical development?

PubMed

Wilson, Frederick J; Leiser, Steven C; Ivarsson, Magnus; Christensen, Søren R; Bastlund, Jesper F

2014-03-01

Pharmaco-electroencephalography has significant yet unrealised promise as a translatable intermediate biomarker of central pharmacodynamic activity that could help reduce Phase 2 attrition in the development of central nervous system drugs. In an effort to understand its true potential, a framework for decision-making was proposed and the utility of pharmaco-electroencephalography was assessed through several case studies. A key finding was that lack of standardisation reduces the value of data pooling and meta-analyses and renders assessment of translatability difficult, limiting utility in all but simple cases. Pre-competitive collaboration is essential both to improving understanding of translation and developing modern signal processing techniques. Copyright © 2013 Elsevier Ltd. All rights reserved.

Quantitative Förster resonance energy transfer analysis for kinetic determinations of SUMO-specific protease.

PubMed

Liu, Yan; Song, Yang; Madahar, Vipul; Liao, Jiayu

2012-03-01

Förster resonance energy transfer (FRET) technology has been widely used in biological and biomedical research, and it is a very powerful tool for elucidating protein interactions in either dynamic or steady state. SUMOylation (the process of SUMO [small ubiquitin-like modifier] conjugation to substrates) is an important posttranslational protein modification with critical roles in multiple biological processes. Conjugating SUMO to substrates requires an enzymatic cascade. Sentrin/SUMO-specific proteases (SENPs) act as an endopeptidase to process the pre-SUMO or as an isopeptidase to deconjugate SUMO from its substrate. To fully understand the roles of SENPs in the SUMOylation cycle, it is critical to understand their kinetics. Here, we report a novel development of a quantitative FRET-based protease assay for SENP1 kinetic parameter determination. The assay is based on the quantitative analysis of the FRET signal from the total fluorescent signal at acceptor emission wavelength, which consists of three components: donor (CyPet-SUMO1) emission, acceptor (YPet) emission, and FRET signal during the digestion process. Subsequently, we developed novel theoretical and experimental procedures to determine the kinetic parameters, k(cat), K(M), and catalytic efficiency (k(cat)/K(M)) of catalytic domain SENP1 toward pre-SUMO1. Importantly, the general principles of this quantitative FRET-based protease kinetic determination can be applied to other proteases. Copyright © 2011 Elsevier Inc. All rights reserved.

An improved PSO-SVM model for online recognition defects in eddy current testing

NASA Astrophysics Data System (ADS)

Liu, Baoling; Hou, Dibo; Huang, Pingjie; Liu, Banteng; Tang, Huayi; Zhang, Wubo; Chen, Peihua; Zhang, Guangxin

2013-12-01

Accurate and rapid recognition of defects is essential for structural integrity and health monitoring of in-service device using eddy current (EC) non-destructive testing. This paper introduces a novel model-free method that includes three main modules: a signal pre-processing module, a classifier module and an optimisation module. In the signal pre-processing module, a kind of two-stage differential structure is proposed to suppress the lift-off fluctuation that could contaminate the EC signal. In the classifier module, multi-class support vector machine (SVM) based on one-against-one strategy is utilised for its good accuracy. In the optimisation module, the optimal parameters of classifier are obtained by an improved particle swarm optimisation (IPSO) algorithm. The proposed IPSO technique can improve convergence performance of the primary PSO through the following strategies: nonlinear processing of inertia weight, introductions of the black hole and simulated annealing model with extremum disturbance. The good generalisation ability of the IPSO-SVM model has been validated through adding additional specimen into the testing set. Experiments show that the proposed algorithm can achieve higher recognition accuracy and efficiency than other well-known classifiers and the superiorities are more obvious with less training set, which contributes to online application.

Enabling Functional Neural Circuit Simulations with Distributed Computing of Neuromodulated Plasticity

PubMed Central

Potjans, Wiebke; Morrison, Abigail; Diesmann, Markus

2010-01-01

A major puzzle in the field of computational neuroscience is how to relate system-level learning in higher organisms to synaptic plasticity. Recently, plasticity rules depending not only on pre- and post-synaptic activity but also on a third, non-local neuromodulatory signal have emerged as key candidates to bridge the gap between the macroscopic and the microscopic level of learning. Crucial insights into this topic are expected to be gained from simulations of neural systems, as these allow the simultaneous study of the multiple spatial and temporal scales that are involved in the problem. In particular, synaptic plasticity can be studied during the whole learning process, i.e., on a time scale of minutes to hours and across multiple brain areas. Implementing neuromodulated plasticity in large-scale network simulations where the neuromodulatory signal is dynamically generated by the network itself is challenging, because the network structure is commonly defined purely by the connectivity graph without explicit reference to the embedding of the nodes in physical space. Furthermore, the simulation of networks with realistic connectivity entails the use of distributed computing. A neuromodulated synapse must therefore be informed in an efficient way about the neuromodulatory signal, which is typically generated by a population of neurons located on different machines than either the pre- or post-synaptic neuron. Here, we develop a general framework to solve the problem of implementing neuromodulated plasticity in a time-driven distributed simulation, without reference to a particular implementation language, neuromodulator, or neuromodulated plasticity mechanism. We implement our framework in the simulator NEST and demonstrate excellent scaling up to 1024 processors for simulations of a recurrent network incorporating neuromodulated spike-timing dependent plasticity. PMID:21151370

Low power electromagnetic flowmeter providing accurate zero set

NASA Technical Reports Server (NTRS)

Fryer, T. B. (Inventor)

1971-01-01

A low power, small size electromagnetic flowmeter system is described which produces a zero output signal for zero flow. The system comprises an air core type electromagnetic flow transducer, a field current supply circuit for the transducer coils and a pre-amplifier and demodulation circuit connected to the output of the transducer. To prevent spurious signals at zero flow, separate, isolated power supplies are provided for the two circuits. The demodulator includes a pair of synchronous rectifiers which are controlled by signals from the field current supply circuit. Pulse transformer connected in front of the synchronous rectifiers provide isolation between the two circuits.

An investigation of pre-launch and in-flight STS range safety radio signal degradation and dropout

NASA Technical Reports Server (NTRS)

Mcdonald, Malcolm W.

1991-01-01

The range safety system (RSS) transmitters operate at a frequency of 416.500 MHz. The transmitting antennas transmit left circularly polarized waves, and the shuttle range safety system (SRSS) receiving antennas onboard the shuttle vehicle receive left circular polarization. Preliminary explanations are proposed for many of the observed fluctuations in signal levels. It is recommended that experiments and further investigation be performed to test the validity of certain of these explanations.

Utilization of extracellular information before ligand-receptor binding reaches equilibrium expands and shifts the input dynamic range

PubMed Central

Ventura, Alejandra C.; Bush, Alan; Vasen, Gustavo; Goldín, Matías A.; Burkinshaw, Brianne; Bhattacharjee, Nirveek; Folch, Albert; Brent, Roger; Chernomoretz, Ariel; Colman-Lerner, Alejandro

2014-01-01

Cell signaling systems sense and respond to ligands that bind cell surface receptors. These systems often respond to changes in the concentration of extracellular ligand more rapidly than the ligand equilibrates with its receptor. We demonstrate, by modeling and experiment, a general “systems level” mechanism cells use to take advantage of the information present in the early signal, before receptor binding reaches a new steady state. This mechanism, pre-equilibrium sensing and signaling (PRESS), operates in signaling systems in which the kinetics of ligand-receptor binding are slower than the downstream signaling steps, and it typically involves transient activation of a downstream step. In the systems where it operates, PRESS expands and shifts the input dynamic range, allowing cells to make different responses to ligand concentrations so high as to be otherwise indistinguishable. Specifically, we show that PRESS applies to the yeast directional polarization in response to pheromone gradients. Consideration of preexisting kinetic data for ligand-receptor interactions suggests that PRESS operates in many cell signaling systems throughout biology. The same mechanism may also operate at other levels in signaling systems in which a slow activation step couples to a faster downstream step. PMID:25172920

IGF system targeted therapy: Therapeutic opportunities for ovarian cancer.

PubMed

Liefers-Visser, J A L; Meijering, R A M; Reyners, A K L; van der Zee, A G J; de Jong, S

2017-11-01

The insulin-like growth factor (IGF) system comprises multiple growth factor receptors, including insulin-like growth factor 1 receptor (IGF-1R), insulin receptor (IR) -A and -B. These receptors are activated upon binding to their respective growth factor ligands, IGF-I, IGF-II and insulin, and play an important role in development, maintenance, progression, survival and chemotherapeutic response of ovarian cancer. In many pre-clinical studies anti-IGF-1R/IR targeted strategies proved effective in reducing growth of ovarian cancer models. In addition, anti-IGF-1R targeted strategies potentiated the efficacy of platinum based chemotherapy. Despite the vast amount of encouraging and promising pre-clinical data, anti-IGF-1R/IR targeted strategies lacked efficacy in the clinic. The question is whether targeting the IGF-1R/IR signaling pathway still holds therapeutic potential. In this review we address the complexity of the IGF-1R/IR signaling pathway, including receptor heterodimerization within and outside the IGF system and downstream signaling. Further, we discuss the implications of this complexity on current targeted strategies and indicate therapeutic opportunities for successful targeting of the IGF-1R/IR signaling pathway in ovarian cancer. Multiple-targeted approaches circumventing bidirectional receptor tyrosine kinase (RTK) compensation and prevention of system rewiring are expected to have more therapeutic potential. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

A model system for targeted drug release triggered by biomolecular signals logically processed through enzyme logic networks.

PubMed

Mailloux, Shay; Halámek, Jan; Katz, Evgeny

2014-03-07

A new Sense-and-Act system was realized by the integration of a biocomputing system, performing analytical processes, with a signal-responsive electrode. A drug-mimicking release process was triggered by biomolecular signals processed by different logic networks, including three concatenated AND logic gates or a 3-input OR logic gate. Biocatalytically produced NADH, controlled by various combinations of input signals, was used to activate the electrochemical system. A biocatalytic electrode associated with signal-processing "biocomputing" systems was electrically connected to another electrode coated with a polymer film, which was dissolved upon the formation of negative potential releasing entrapped drug-mimicking species, an enzyme-antibody conjugate, operating as a model for targeted immune-delivery and consequent "prodrug" activation. The system offers great versatility for future applications in controlled drug release and personalized medicine.

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

The effects of AMPA receptor blockade in the prelimbic cortex on systemic and ventral tegmental area opiate reward sensitivity.

PubMed

De Jaeger, Xavier; Bishop, Stephanie F; Ahmad, Tasha; Lyons, Danika; Ng, Garye Ami; Laviolette, Steven R

2013-02-01

The medial prefrontal cortex (mPFC) is a key neural region involved in opiate-related reward memory processing. AMPA receptor transmission in the mPFC modulates opiate-related reward memory processing, and chronic opiate exposure is associated with alterations in intra-mPFC AMPA receptor function. The objectives of this study were to examine how pharmacological blockade of AMPA receptor transmission in the prelimbic (PLC) division of the mPFC may modulate opiate reward memory acquisition and whether opiate exposure state may modulate the functional role of intra-PLC AMPA receptor transmission during opiate reward learning. Using an unbiased conditioned place preference (CPP) procedure in rats, we performed discrete, bilateral intra-PLC microinfusions of the AMPA receptor antagonist, 6,7-dinitroquinoxaline-2,3-dione, prior to behavioral morphine CPP conditioning, using sub-reward threshold conditioning doses of either systemic (0.05 mg/kg; i.p.) or intra-ventral tegmental area (VTA) morphine (250 ng/0.5 μl). We show that, in both opiate-naïve and opiate-dependent states, intra-PLC blockade of AMPA receptor transmission, but not the infralimbic cortex, increases the behavioral reward magnitude of systemic or intra-VTA morphine. This effect is dependent on dopamine (DA)ergic signaling because pre-administration of cis-(Z)-flupenthixol-dihydrochloride (α-flu), a broad-spectrum dopamine receptor antagonist, blocked the morphine-reward potentiating effects of AMPA receptor blockade. These findings suggest a critical role for intra-PLC AMPA receptor transmission in the processing of opiate reward signaling. Furthermore, blockade of AMPA transmission specifically within the PLC is capable of switching opiate reward processing to a DA-dependent reward system, independently of previous opiate exposure history.

Vitamin D and prebiotics may benefit the intestinal microbacteria and improve glucose homeostasis in prediabetes and type 2 diabetes.

PubMed

Barengolts, Elena

2013-01-01

To review the role of human large bowel microbacteria (microbiota) in the glucose homeostasis, to address vitamin D (VD) and prebiotics interactions with microbiota, and to summarize recent randomized clinical trials (RCTs) of VD and prebiotics supplementation in prediabetes (PreDM) and type 2 diabetes mellitus (T2DM). Primary literature was reviewed in the following areas: composition and activity of human microbiota associated with PreDM and T2DM, interactions between microbiota and glucose homeostasis, the interaction of microbiota with VD/prebiotics, and RCTs of VD/prebiotics in subjects with PreDM or T2DM. The human microbiota is comprised of 100 trillion bacteria with an aggregate genome that is 150-fold larger than the human genome. Data from the animal models and human studies reveal that an "obesogenic" diet results into the initial event of microbiota transformation from symbiosis to dysbiosis. The microbial antigens, such as Gram(-) bacteria and lipopolysaccharide (LPS), translocate to the host interior and trigger increased energy harvesting and Toll-like receptor (TLR) activation with subsequent inflammatory pathways signaling. The "double hit" of steatosis (ectopic fat accumulation) and "-itis" (inflammation) and contribution of "corisks" (e.g., vitamin D deficiency [VDD]) are required to activate molecular signaling, including impaired insulin signaling and secretion, that ends with T2DM and associated diseases. Dietary changes (e.g., prebiotics, VD supplementation) may ameliorate this process if initiated prior to the process becoming irreversible. Emerging evidence suggests an important role of microbiota in glucose homeostasis. VD supplementation and prebiotics may be useful in managing PreDM and T2DM.

Method and system for turbomachinery surge detection

DOEpatents

Faymon, David K.; Mays, Darrell C.; Xiong, Yufei

2004-11-23

A method and system for surge detection within a gas turbine engine, comprises: measuring the compressor discharge pressure (CDP) of the gas turbine over a period of time; determining a time derivative (CDP.sub.D ) of the measured (CDP) correcting the CDP.sub.D for altitude, (CDP.sub.DCOR); estimating a short-term average of CDP.sub.DCOR.sup.2 ; estimating a short-term average of CDP.sub.DCOR ; and determining a short-term variance of corrected CDP rate of change (CDP.sub.roc) based upon the short-term average of CDP.sub.DCOR and the short-term average of CDP.sub.DCOR.sup.2. The method and system then compares the short-term variance of corrected CDP rate of change with a pre-determined threshold (CDP.sub.proc) and signals an output when CDP.sub.roc >CDP.sub.proc. The method and system provides a signal of a surge within the gas turbine engine when CDP.sub.roc remains>CDP.sub.proc for pre-determined period of time.

Hybrid method based on singular value decomposition and embedded zero tree wavelet technique for ECG signal compression.

PubMed

Kumar, Ranjeet; Kumar, A; Singh, G K

2016-06-01

In the field of biomedical, it becomes necessary to reduce data quantity due to the limitation of storage in real-time ambulatory system and telemedicine system. Research has been underway since very beginning for the development of an efficient and simple technique for longer term benefits. This paper, presents an algorithm based on singular value decomposition (SVD), and embedded zero tree wavelet (EZW) techniques for ECG signal compression which deals with the huge data of ambulatory system. The proposed method utilizes the low rank matrix for initial compression on two dimensional (2-D) ECG data array using SVD, and then EZW is initiated for final compression. Initially, 2-D array construction has key issue for the proposed technique in pre-processing. Here, three different beat segmentation approaches have been exploited for 2-D array construction using segmented beat alignment with exploitation of beat correlation. The proposed algorithm has been tested on MIT-BIH arrhythmia record, and it was found that it is very efficient in compression of different types of ECG signal with lower signal distortion based on different fidelity assessments. The evaluation results illustrate that the proposed algorithm has achieved the compression ratio of 24.25:1 with excellent quality of signal reconstruction in terms of percentage-root-mean square difference (PRD) as 1.89% for ECG signal Rec. 100 and consumes only 162bps data instead of 3960bps uncompressed data. The proposed method is efficient and flexible with different types of ECG signal for compression, and controls quality of reconstruction. Simulated results are clearly illustrate the proposed method can play a big role to save the memory space of health data centres as well as save the bandwidth in telemedicine based healthcare systems. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Fluorescence Resonance Energy Transfer-Based Photonic Circuits Using Single-Stranded Tile Self-Assembly and DNA Strand Displacement.

PubMed

Zhang, Xuncai; Ying, Niu; Shen, Chaonan; Cui, Guangzhao

2017-02-01

Structural DNA nanotechnology has great potential in the fabrication of complicated nanostructures and devices capable of bio-sensing and logic function. A variety of nanostructures with desired shapes have been created in the past few decades. But the application of nanostructures remains to be fully studied. Here, we present a novel biological information processing system constructed on a self-assembled, spatially addressable single-stranded tile (SST) nanostructure as DNA nano-manipulation platform that created by SST self-assembly technology. Utilizing DNA strand displacement technology, the fluorescent dye that is pre-assembled in the nano-manipulation platform is transferred from the original position to the destination, which can achieve photonic logic circuits by FRET signal cascades, including logic AND, OR, and NOT gates. And this transfer process is successfully validated by visual DSD software. The transfer process proposed in this study may provide a novel method to design complicated biological information processing system constructed on a SST nanostructure, and can be further used to develop intelligent delivery of drug molecules in vivo.

A High Input Impedance Low Noise Integrated Front-End Amplifier for Neural Monitoring.

PubMed

Zhou, Zhijun; Warr, Paul A

2016-12-01

Within neural monitoring systems, the front-end amplifier forms the critical element for signal detection and pre-processing, which determines not only the fidelity of the biosignal, but also impacts power consumption and detector size. In this paper, a novel combined feedback loop-controlled approach is proposed to compensate for input leakage currents generated by low noise amplifiers when in integrated circuit form alongside signal leakage into the input bias network. This loop topology ensures the Front-End Amplifier (FEA) maintains a high input impedance across all manufacturing and operational variations. Measured results from a prototype manufactured on the AMS 0.35 [Formula: see text] CMOS technology is provided. This FEA consumes 3.1 [Formula: see text] in 0.042 [Formula: see text], achieves input impedance of 42 [Formula: see text], and 18.2 [Formula: see text] input-referred noise.

PepsNMR for 1H NMR metabolomic data pre-processing.

PubMed

Martin, Manon; Legat, Benoît; Leenders, Justine; Vanwinsberghe, Julien; Rousseau, Réjane; Boulanger, Bruno; Eilers, Paul H C; De Tullio, Pascal; Govaerts, Bernadette

2018-08-17

In the analysis of biological samples, control over experimental design and data acquisition procedures alone cannot ensure well-conditioned 1 H NMR spectra with maximal information recovery for data analysis. A third major element affects the accuracy and robustness of results: the data pre-processing/pre-treatment for which not enough attention is usually devoted, in particular in metabolomic studies. The usual approach is to use proprietary software provided by the analytical instruments' manufacturers to conduct the entire pre-processing strategy. This widespread practice has a number of advantages such as a user-friendly interface with graphical facilities, but it involves non-negligible drawbacks: a lack of methodological information and automation, a dependency of subjective human choices, only standard processing possibilities and an absence of objective quality criteria to evaluate pre-processing quality. This paper introduces PepsNMR to meet these needs, an R package dedicated to the whole processing chain prior to multivariate data analysis, including, among other tools, solvent signal suppression, internal calibration, phase, baseline and misalignment corrections, bucketing and normalisation. Methodological aspects are discussed and the package is compared to the gold standard procedure with two metabolomic case studies. The use of PepsNMR on these data shows better information recovery and predictive power based on objective and quantitative quality criteria. Other key assets of the package are workflow processing speed, reproducibility, reporting and flexibility, graphical outputs and documented routines. Copyright © 2018 Elsevier B.V. All rights reserved.

Introduction to Radar Signal and Data Processing: The Opportunity

DTIC Science & Technology

2006-09-01

SpA) Director of Analysis of Integrated Systems Group Via Tiburtina Km. 12.400 00131 Rome ITALY e.mail: afarina@selex-si.com Key words: radar...signal processing, data processing, adaptivity, space-time adaptive processing, knowledge based systems , CFAR. 1. SUMMARY This paper introduces to...the lecture series dedicated to the knowledge-based radar signal and data processing. Knowledge-based expert system (KBS) is in the realm of

A new mechanism for spatial pattern formation via lateral and protrusion-mediated lateral signalling

PubMed Central

Hunter, Ginger L.; Baum, Buzz

2016-01-01

Tissue organization and patterning are critical during development when genetically identical cells take on different fates. Lateral signalling plays an important role in this process by helping to generate self-organized spatial patterns in an otherwise uniform collection of cells. Recent data suggest that lateral signalling can be mediated both by junctional contacts between neighbouring cells and via cellular protrusions that allow non-neighbouring cells to interact with one another at a distance. However, it remains unclear precisely how signalling mediated by these distinct types of cell–cell contact can physically contribute to the generation of complex patterns without the assistance of diffusible morphogens or pre-patterns. To explore this question, in this work we develop a model of lateral signalling based on a single receptor/ligand pair as exemplified by Notch and Delta. We show that allowing the signalling kinetics to differ at junctional versus protrusion-mediated contacts, an assumption inspired by recent data which show that the cleavage of Notch in several systems requires both Delta binding and the application of mechanical force, permits individual cells to act to promote both lateral activation and lateral inhibition. Strikingly, under this model, in which Delta can sequester Notch, a variety of patterns resembling those typical of reaction–diffusion systems is observed, together with more unusual patterns that arise when we consider changes in signalling kinetics, and in the length and distribution of protrusions. Importantly, these patterns are self-organizing—so that local interactions drive tissue-scale patterning. Together, these data show that protrusions can, in principle, generate different types of patterns in addition to contributing to long-range signalling and to pattern refinement. PMID:27807273

Proposal of a model of mammalian neural induction

PubMed Central

Levine, Ariel J.; Brivanlou, Ali H.

2009-01-01

How does the vertebrate embryo make a nervous system? This complex question has been at the center of developmental biology for many years. The earliest step in this process – the induction of neural tissue – is intimately linked to patterning of the entire early embryo, and the molecular and embryological basis these processes are beginning to emerge. Here, we analyze classic and cutting-edge findings on neural induction in the mouse. We find that data from genetics, tissue explants, tissue grafting, and molecular marker expression support a coherent framework for mammalian neural induction. In this model, the gastrula organizer of the mouse embryo inhibits BMP signaling to allow neural tissue to form as a default fate – in the absence of instructive signals. The first neural tissue induced is anterior and subsequent neural tissue is posteriorized to form the midbrain, hindbrain, and spinal cord. The anterior visceral endoderm protects the pre-specified anterior neural fate from similar posteriorization, allowing formation of forebrain. This model is very similar to the default model of neural induction in the frog, thus bridging the evolutionary gap between amphibians and mammals. PMID:17585896

Management of pre-pubertal small ruminants: physiological basis and clinical approach.

PubMed

Valasi, I; Chadio, S; Fthenakis, G C; Amiridis, G S

2012-02-01

Puberty is a gradual process, during which animal reproductive competence is attained with respect to physiology, morphology and behaviour. Onset of puberty in small ruminants differs between sexes, due to early sexual differentiation in the control of steroid feedback systems and, thus, GnRH secretion. A number of puberty determinants have been identified, which include genetic factors, as well as endogenous signals, such as energy balance and environmental cues, whose dynamic interplay is responsible for the timing of puberty onset. Puberty timing affects reproduction through age at first lambing, which impacts on subsequent reproductive life and productivity of small ruminants. Thus, a greater knowledge of the mechanisms underlying puberty process would lead to optimisation of commonly applied strategies for selection of replacement animals. In addition, understanding reproductive responses of animals to exteroceptive factors, such as photoperiod, nutrition and socio-sexual signals, will enable development and improvement of those management tools that that will fulfil the requirements of a 'clean, green and ethical' production. Copyright © 2012 Elsevier B.V. All rights reserved.

Methods for Processing and Interpretation of AIS Signals Corrupted by Noise and Packet Collisions

NASA Astrophysics Data System (ADS)

Poļevskis, J.; Krastiņš, M.; Korāts, G.; Skorodumovs, A.; Trokšs, J.

2012-01-01

The authors deal with the operation of Automatic Identification System (AIS) used in the marine traffic monitoring to broadcast messages containing information about the vessel: id, payload, size, speed, destination etc., meant primarily for avoidance of ship collisions. To extend the radius of AIS operation, it is envisaged to dispose its receivers on satellites. However, in space, due to a large coverage area, interfering factors are especially pronounced - such as packet collision, Doppler's shift and noise impact on AIS message receiving, pre-processing and decoding. To assess the quality of an AIS receiver's operation, a test was carried out in which, varying automatically frequency, amplitude, noise, and other parameters, the data on the ability of the receiver's ability to decode AIS signals are collected. In the work, both hardware- and software-based AIS decoders were tested. As a result, quite satisfactory statistics has been gathered - both on the common and the differing features of such decoders when operating in space. To obtain reliable data on the software-defined radio AIS receivers, further research is envisaged.

A low-power current-reuse dual-band analog front-end for multi-channel neural signal recording.

PubMed

Sepehrian, H; Gosselin, B

2014-01-01

Thoroughly studying the brain activity of freely moving subjects requires miniature data acquisition systems to measure and wirelessly transmit neural signals in real time. In this application, it is mandatory to simultaneously record the bioelectrical activity of a large number of neurons to gain a better knowledge of brain functions. However, due to limitations in transferring the entire raw data to a remote base station, employing dedicated data reduction techniques to extract the relevant part of neural signals is critical to decrease the amount of data to transfer. In this work, we present a new dual-band neural amplifier to separate the neuronal spike signals (SPK) and the local field potential (LFP) simultaneously in the analog domain, immediately after the pre-amplification stage. By separating these two bands right after the pre-amplification stage, it is possible to process LFP and SPK separately. As a result, the required dynamic range of the entire channel, which is determined by the signal-to-noise ratio of the SPK signal of larger bandwidth, can be relaxed. In this design, a new current-reuse low-power low-noise amplifier and a new dual-band filter that separates SPK and LFP while saving capacitors and pseudo resistors. A four-channel dual-band (SPK, LFP) analog front-end capable of simultaneously separating SPK and LFP is implemented in a TSMC 0.18 μm technology. Simulation results present a total power consumption per channel of 3.1 μw for an input referred noise of 3.28 μV and a NEF for 2.07. The cutoff frequency of the LFP band is fc=280 Hz, and fL=725 Hz and fL=11.2 KHz for SPK, with 36 dB gain for LFP band 46 dB gain for SPK band.

Automatic Classification of volcano-seismic events based on Deep Neural Networks.

NASA Astrophysics Data System (ADS)

Titos Luzón, M.; Bueno Rodriguez, A.; Garcia Martinez, L.; Benitez, C.; Ibáñez, J. M.

2017-12-01

Seismic monitoring of active volcanoes is a popular remote sensing technique to detect seismic activity, often associated to energy exchanges between the volcano and the environment. As a result, seismographs register a wide range of volcano-seismic signals that reflect the nature and underlying physics of volcanic processes. Machine learning and signal processing techniques provide an appropriate framework to analyze such data. In this research, we propose a new classification framework for seismic events based on deep neural networks. Deep neural networks are composed by multiple processing layers, and can discover intrinsic patterns from the data itself. Internal parameters can be initialized using a greedy unsupervised pre-training stage, leading to an efficient training of fully connected architectures. We aim to determine the robustness of these architectures as classifiers of seven different types of seismic events recorded at "Volcán de Fuego" (Colima, Mexico). Two deep neural networks with different pre-training strategies are studied: stacked denoising autoencoder and deep belief networks. Results are compared to existing machine learning algorithms (SVM, Random Forest, Multilayer Perceptron). We used 5 LPC coefficients over three non-overlapping segments as training features in order to characterize temporal evolution, avoid redundancy and encode the signal, regardless of its duration. Experimental results show that deep architectures can classify seismic events with higher accuracy than classical algorithms, attaining up to 92% recognition accuracy. Pre-training initialization helps these models to detect events that occur simultaneously in time (such explosions and rockfalls), increase robustness against noisy inputs, and provide better generalization. These results demonstrate deep neural networks are robust classifiers, and can be deployed in real-environments to monitor the seismicity of restless volcanoes.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Optical transient monitor

NASA Astrophysics Data System (ADS)

Bernas, Martin; Páta, Petr; Hudec, René; Soldán, Jan; Rezek, Tomáš; Castro-Tirado, Alberto J.

1998-05-01

Although there are several optical GRB follow-up systems in operation and/or in development, some of them with a very short response time, they will never be able to provide true simultaneous (no delay) and pre-burst optical data for GRBs. We report on the development and tests of a monitoring experiment expected to be put into test operation in 1998. The system should detect Optical Transients down to mag 6-7 (few seconds duration assumed) over a wide field of view. The system is based on the double CCD wide-field cameras ST8. For the real time evaluation of the signal from both cameras, two TMS 320C40 processors are used. Using two channels differing in spectral sensitivity and processing of temporal sequence of images allows us to eliminate man-made objects and defects of the CCD electronics. The system is controlled by a standard PC computer.

"Chemical transformers" from nanoparticle ensembles operated with logic.

PubMed

Motornov, Mikhail; Zhou, Jian; Pita, Marcos; Gopishetty, Venkateshwarlu; Tokarev, Ihor; Katz, Evgeny; Minko, Sergiy

2008-09-01

The pH-responsive nanoparticles were coupled with information-processing enzyme-based systems to yield "smart" signal-responsive hybrid systems with built-in Boolean logic. The enzyme systems performed AND/OR logic operations, transducing biochemical input signals into reversible structural changes (signal-directed self-assembly) of the nanoparticle assemblies, thus resulting in the processing and amplification of the biochemical signals. The hybrid system mimics biological systems in effective processing of complex biochemical information, resulting in reversible changes of the self-assembled structures of the nanoparticles. The bioinspired approach to the nanostructured morphing materials could be used in future self-assembled molecular robotic systems.

CPSF30 at the Interface of Alternative Polyadenylation and Cellular Signaling in Plants

PubMed Central

Chakrabarti, Manohar; Hunt, Arthur G.

2015-01-01

Post-transcriptional processing, involving cleavage of precursor messenger RNA (pre mRNA), and further incorporation of poly(A) tail to the 3' end is a key step in the expression of genetic information. Alternative polyadenylation (APA) serves as an important check point for the regulation of gene expression. Recent studies have shown widespread prevalence of APA in diverse systems. A considerable amount of research has been done in characterizing different subunits of so-called Cleavage and Polyadenylation Specificity Factor (CPSF). In plants, CPSF30, an ortholog of the 30 kD subunit of mammalian CPSF is a key polyadenylation factor. CPSF30 in the model plant Arabidopsis thaliana was reported to possess unique biochemical properties. It was also demonstrated that poly(A) site choice in a vast majority of genes in Arabidopsis are CPSF30 dependent, suggesting a pivotal role of this gene in APA and subsequent regulation of gene expression. There are also indications of this gene being involved in oxidative stress and defense responses and in cellular signaling, suggesting a role of CPSF30 in connecting physiological processes and APA. This review will summarize the biochemical features of CPSF30, its role in regulating APA, and possible links with cellular signaling and stress response modules. PMID:26061761

System For Surveillance Of Spectral Signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.; Criss-Puszkiewicz, Cynthia; Wilks, Alan D.

2004-10-12

A method and system for monitoring at least one of a system, a process and a data source. A method and system have been developed for carrying out surveillance, testing and modification of an ongoing process or other source of data, such as a spectroscopic examination. A signal from the system under surveillance is collected and compared with a reference signal, a frequency domain transformation carried out for the system signal and reference signal, a frequency domain difference function established. The process is then repeated until a full range of data is accumulated over the time domain and a Sequential Probability Ratio Test ("SPRT") methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.

System For Surveillance Of Spectral Signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan; Criss-Puszkiewicz, Cynthia; Wilks, Alan D.

2003-04-22

A method and system for monitoring at least one of a system, a process and a data source. A method and system have been developed for carrying out surveillance, testing and modification of an ongoing process or other source of data, such as a spectroscopic examination. A signal from the system under surveillance is collected and compared with a reference signal, a frequency domain transformation carried out for the system signal and reference signal, a frequency domain difference function established. The process is then repeated until a full range of data is accumulated over the time domain and a Sequential Probability Ratio Test methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.

System for surveillance of spectral signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.; Criss-Puszkiewicz, Cynthia; Wilks, Alan D.

2006-02-14

A method and system for monitoring at least one of a system, a process and a data source. A method and system have been developed for carrying out surveillance, testing and modification of an ongoing process or other source of data, such as a spectroscopic examination. A signal from the system under surveillance is collected and compared with a reference signal, a frequency domain transformation carried out for the system signal and reference signal, a frequency domain difference function established. The process is then repeated until a full range of data is accumulated over the time domain and a Sequential Probability Ratio Test ("SPRT") methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.

System for surveillance of spectral signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.; Criss-Puszkiewicz, Cynthia; Wilks, Alan D.

2001-01-01

A method and system for monitoring at least one of a system, a process and a data source. A method and system have been developed for carrying out surveillance, testing and modification of an ongoing process or other source of data, such as a spectroscopic examination. A signal from the system under surveillance is collected and compared with a reference signal, a frequency domain transformation carried out for the system signal and reference signal, a frequency domain difference function established. The process is then repeated until a full range of data is accumulated over the time domain and a SPRT sequential probability ratio test methodology applied to determine a three-dimensional surface plot characteristic of the operating state of the system under surveillance.

An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers.

PubMed

Luo, Zhibin; Ding, Jicheng; Zhao, Lin; Wu, Mouyan

2017-11-18

Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration-which are the basis of tracking error estimation-are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (-0.25 cycle, 0.25 cycle) to (-0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio is less than 28.8 dB-Hz, in carrier frequency error estimation when carrier-to-noise density ratio is less than 20 dB-Hz, and in carrier phase error estimation when carrier-to-noise density belongs to (15, 23) dB-Hz ∪ (26, 50) dB-Hz.

An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers

PubMed Central

Luo, Zhibin; Ding, Jicheng; Zhao, Lin; Wu, Mouyan

2017-01-01

Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration—which are the basis of tracking error estimation—are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (−0.25 cycle, 0.25 cycle) to (−0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio is less than 28.8 dB-Hz, in carrier frequency error estimation when carrier-to-noise density ratio is less than 20 dB-Hz, and in carrier phase error estimation when carrier-to-noise density belongs to (15, 23) dB-Hz ∪ (26, 50) dB-Hz. PMID:29156581

Microwave Imaging Radar Reflectometer System Utilizing Digital Beam Forming

NASA Astrophysics Data System (ADS)

Hu, Fengqi; Li, Meijiao; Domier, Calvin W.; Liu, Xiaoguang; Luhmann, Neville C., Jr.

2016-10-01

Microwave Imaging Reflectometry is a radar-like technique developed to measure the electron density fluctuations in fusion plasmas. Phased Antenna Arrays can serve as electronically controlled ``lenses'' that can generate the required wavefronts by phase shifting and amplitude scaling, which is being realized in the digital domain with higher flexibility and faster processing speed. In the transmitter, the resolution of the phase control is 1.4 degrees and the amplitude control is 0.5 dB/ step. A V-band double-sided, printed bow tie antenna which exhibits 49% bandwidth (46 - 76 GHz) is employed. The antenna is fed by a microstrip transmission line for easy impedance matching. The simple structure and the small antenna are suitable for low cost fabrication, easy circuit integration, and phased antenna array multi-frequency applications. In the receiver part, a sub-array of 32 channels with 200 mil spacing is used to collect the scattered reflected signal from one unit spot on the plasma cutoff surface. Pre-amplification is used to control the noise level of the system and wire bondable components are used to accommodate the small spacing between each channel. After down converting, base band signals are digitized and processed in an FPGA module. U.S. Department of Energy Grant No. DE-FG02-99ER54531.

Signal processing in ultrasound. [for diagnostic medicine

NASA Technical Reports Server (NTRS)

Le Croissette, D. H.; Gammell, P. M.

1978-01-01

Signal is the term used to denote the characteristic in the time or frequency domain of the probing energy of the system. Processing of this signal in diagnostic ultrasound occurs as the signal travels through the ultrasonic and electrical sections of the apparatus. The paper discusses current signal processing methods, postreception processing, display devices, real-time imaging, and quantitative measurements in noninvasive cardiology. The possibility of using deconvolution in a single transducer system is examined, and some future developments using digital techniques are outlined.

A modular cell-based biosensor using engineered genetic logic circuits to detect and integrate multiple environmental signals

PubMed Central

Wang, Baojun; Barahona, Mauricio; Buck, Martin

2013-01-01

Cells perceive a wide variety of cellular and environmental signals, which are often processed combinatorially to generate particular phenotypic responses. Here, we employ both single and mixed cell type populations, pre-programmed with engineered modular cell signalling and sensing circuits, as processing units to detect and integrate multiple environmental signals. Based on an engineered modular genetic AND logic gate, we report the construction of a set of scalable synthetic microbe-based biosensors comprising exchangeable sensory, signal processing and actuation modules. These cellular biosensors were engineered using distinct signalling sensory modules to precisely identify various chemical signals, and combinations thereof, with a quantitative fluorescent output. The genetic logic gate used can function as a biological filter and an amplifier to enhance the sensing selectivity and sensitivity of cell-based biosensors. In particular, an Escherichia coli consortium-based biosensor has been constructed that can detect and integrate three environmental signals (arsenic, mercury and copper ion levels) via either its native two-component signal transduction pathways or synthetic signalling sensors derived from other bacteria in combination with a cell-cell communication module. We demonstrate how a modular cell-based biosensor can be engineered predictably using exchangeable synthetic gene circuit modules to sense and integrate multiple-input signals. This study illustrates some of the key practical design principles required for the future application of these biosensors in broad environmental and healthcare areas. PMID:22981411

GLAST Burst Monitor Signal Processing System

NASA Astrophysics Data System (ADS)

Bhat, P. Narayana; Briggs, Michael; Connaughton, Valerie; Diehl, Roland; Fishman, Gerald; Greiner, Jochen; Kippen, R. Marc; von Kienlin, Andreas; Kouveliotou, Chryssa; Lichti, Giselher; Meegan, Charles; Paciesas, William; Persyn, Steven; Preece, Robert; Steinle, Helmut; Wilson-Hodge, Colleen

2007-07-01

The onboard Data Processing Unit (DPU), designed and built by Southwest Research Institute, performs the high-speed data acquisition for GBM. The analog signals from each of the 14 detectors are digitized by high-speed multichannel analog data acquisition architecture. The streaming digital values resulting from a periodic (period of 104.2 ns) sampling of the analog signal by the individual ADCs are fed to a Field-Programmable Gate Array (FPGA). Real-time Digital Signal Processing (DSP) algorithms within the FPGA implement functions like filtering, thresholding, time delay and pulse height measurement. The spectral data with a 12-bit resolution are formatted according to the commandable look-up-table (LUT) and then sent to the High-Speed Science-Date Bus (HSSDB, speed=1.5 MB/s) to be telemetered to ground. The DSP offers a novel feature of a commandable & constant event deadtime. The ADC non-linearities have been calibrated so that the spectral data can be corrected during analysis. The best temporal resolution is 2 μs for the pre-burst & post-trigger time-tagged events (TTE) data. The time resolution of the binned data types is commandable from 64 msec to 1.024 s for the CTIME data (8 channel spectral resolution) and 1.024 to 32.768 s for the CSPEC data (128 channel spectral resolution). The pulse pile-up effects have been studied by Monte Carlo simulations. For a typical GRB, the possible shift in the Epeak value at high-count rates (~100 kHz) is ~1% while the change in the single power-law index could be up to 5%.

System and method for programmable bank selection for banked memory subsystems

DOEpatents

Blumrich, Matthias A.; Chen, Dong; Gara, Alan G.; Giampapa, Mark E.; Hoenicke, Dirk; Ohmacht, Martin; Salapura, Valentina; Sugavanam, Krishnan

2010-09-07

A programmable memory system and method for enabling one or more processor devices access to shared memory in a computing environment, the shared memory including one or more memory storage structures having addressable locations for storing data. The system comprises: one or more first logic devices associated with a respective one or more processor devices, each first logic device for receiving physical memory address signals and programmable for generating a respective memory storage structure select signal upon receipt of pre-determined address bit values at selected physical memory address bit locations; and, a second logic device responsive to each of the respective select signal for generating an address signal used for selecting a memory storage structure for processor access. The system thus enables each processor device of a computing environment memory storage access distributed across the one or more memory storage structures.

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Optical signal-processing systems based on anisotropic media

NASA Astrophysics Data System (ADS)

Kiyashko, B. V.

1995-10-01

Partially coherent optical systems for signal processing are considered. The transfer functions are formed in these systems by interference of polarised light transmitted by an anisotropic medium. It is shown that such systems can perform various integral transformations of both optical and electric signals, in particular, two-dimensional Fourier and Fresnel transformations, as well as spectral analysis of weak light sources. It is demonstrated that such systems have the highest luminosity and vibration immunity among the systems with interference formation of transfer functions. An experimental investigation is reported of the application of these systems in the processing of signals from a linear hydroacoustic antenna array, and in measurements of the optical spectrum and of the intrinsic noise.

Nano hydroxyapatite-blasted titanium surface affects pre-osteoblast morphology by modulating critical intracellular pathways.

PubMed

Bezerra, Fábio; Ferreira, Marcel R; Fontes, Giselle N; da Costa Fernandes, Célio Jr; Andia, Denise C; Cruz, Nilson C; da Silva, Rodrigo A; Zambuzzi, Willian F

2017-08-01

Although, intracellular signaling pathways are proposed to predict the quality of cell-surface relationship, this study addressed pre-osteoblast behavior in response to nano hydroxyapatite (HA)-blasted titanium (Ti) surface by exploring critical intracellular pathways and pre-osteoblast morphological change. Physicochemical properties were evaluated by atomic force microscopy (AFM) and wettability considering water contact angle of three differently texturized Ti surfaces: Machined (Mac), Dual acid-etching (DAE), and nano hydroxyapatite-blasted (nHA). The results revealed critical differences in surface topography, impacting the water contact angle and later the osteoblast performance. In order to evaluate the effect of those topographical characteristics on biological responses, we have seeded pre-osteoblast cells on the Ti discs for up to 4 h and subjected the cultures to biological analysis. First, we have observed pre-osteoblasts morphological changes resulting from the interaction with the Ti texturized surfaces whereas the cells cultured on nHA presented a more advanced spreading process when compared with the cells cultured on the other surfaces. These results argued us for analyzing the molecular machinery and thus, we have shown that nHA promoted a lower Bax/Bcl2 ratio, suggesting an interesting anti-apoptotic effect, maybe explained by the fact that HA is a natural element present in bone composition. Thereafter, we investigated the potential effect of those surfaces on promoting pre-osteoblast adhesion and survival signaling by performing crystal violet and immunoblotting approaches, respectively. Our results showed that nHA promoted a higher pre-osteoblast adhesion supported by up-modulating FAK and Src activations, both signaling transducers involved during eukaryotic cell adhesion. Also, we have shown Ras-Erk stimulation by the all evaluated surfaces. Finally, we showed that all Ti-texturing surfaces were able to promote osteoblast differentiation up to 10 days, when alkaline phosphatase (ALP) activity and osteogenic transcription factors were up-modulated. Altogether, our results showed for the first time that nano hydroxyapatite-blasted titanium surface promotes crucial intracellular signaling network responsible for cell adapting on the Ti-surface.Biotechnol. Bioeng. 2017;114: 1888-1898. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Dynamic pre-BCR homodimers fine-tune autonomous survival signals in B cell precursor acute lymphoblastic leukemia

PubMed Central

Erasmus, M. Frank; Matlawska-Wasowska, Ksenia; Kinjyo, Ichiko; Mahajan, Avanika; Winter, Stuart S.; Xu, Li; Horowitz, Michael; Lidke, Diane S.; Wilson, Bridget S.

2017-01-01

The pre-B cell receptor (pre-BCR) is an immature form of the BCR critical for early B lymphocyte development. It is composed of the membrane-bound immunoglobulin (Ig) heavy chain, surrogate light chain components, and the signaling subunits Igα and Igβ. We developed monovalent Quantum Dot (QD)-labeled probes specific for Igβ to study the behavior of pre-BCRs engaged in autonomous, ligand-independent signaling in live B cells. Single-particle tracking revealed that QD-labeled pre-BCRs engaged in transient, but frequent, homotypic interactions. Receptor motion was correlated at short separation distances, consistent with the formation of dimers and higher-order oligomers. Repeated encounters between diffusing pre-BCRs appeared to reflect transient co-confinement in plasma membrane domains. In human B cell precursor acute lymphoblastic leukemia (BCP-ALL) cells, we showed that frequent, short-lived, homotypic pre-BCR interactions stimulated survival signals, including expression of BCL6, which encodes a transcriptional repressor. These survival signals were blocked by inhibitory monovalent antigen-binding antibody fragments (Fabs) specific for the surrogate light chain components of the pre-BCR or by inhibitors of the tyrosine kinases Lyn and Syk. For comparison, we evaluated pre-BCR aggregation mediated by dimeric galectin-1, which has binding sites for carbohydrate and for the λ5 component of the surrogate light chain. Galectin-1 binding resulted in the formation of large, highly immobile pre-BCR aggregates, which was partially relieved by the addition of lactose to prevent the crosslinking of galectin-BCR complexes to other glycosylated membrane components. Analysis of the pre-BCR and its signaling partners suggested that they could be potential targets for combination therapy in BCP-ALL. PMID:27899526

Specific detection of the cleavage activity of mycobacterial enzymes using a quantum dot based DNA nanosensor

NASA Astrophysics Data System (ADS)

Jepsen, Morten Leth; Harmsen, Charlotte; Godbole, Adwait Anand; Nagaraja, Valakunja; Knudsen, Birgitta R.; Ho, Yi-Ping

2015-12-01

We present a quantum dot based DNA nanosensor specifically targeting the cleavage step in the reaction cycle of the essential DNA-modifying enzyme, mycobacterial topoisomerase I. The design takes advantages of the unique photophysical properties of quantum dots to generate visible fluorescence recovery upon specific cleavage by mycobacterial topoisomerase I. This report, for the first time, demonstrates the possibility to quantify the cleavage activity of the mycobacterial enzyme without the pre-processing sample purification or post-processing signal amplification. The cleavage induced signal response has also proven reliable in biological matrices, such as whole cell extracts prepared from Escherichia coli and human Caco-2 cells. It is expected that the assay may contribute to the clinical diagnostics of bacterial diseases, as well as the evaluation of treatment outcomes.We present a quantum dot based DNA nanosensor specifically targeting the cleavage step in the reaction cycle of the essential DNA-modifying enzyme, mycobacterial topoisomerase I. The design takes advantages of the unique photophysical properties of quantum dots to generate visible fluorescence recovery upon specific cleavage by mycobacterial topoisomerase I. This report, for the first time, demonstrates the possibility to quantify the cleavage activity of the mycobacterial enzyme without the pre-processing sample purification or post-processing signal amplification. The cleavage induced signal response has also proven reliable in biological matrices, such as whole cell extracts prepared from Escherichia coli and human Caco-2 cells. It is expected that the assay may contribute to the clinical diagnostics of bacterial diseases, as well as the evaluation of treatment outcomes. Electronic supplementary information (ESI) available: Characterization of the QD-based DNA Nanosensor. See DOI: 10.1039/c5nr06326d

Pilot implementation of a technologically advanced system for the optimization of pre-hospital, trauma patient care.

PubMed

Vagianos, Constantine E; Dimopoulou, Efi; Tsiftsis, Dimitrios; Spyropoulos, Charalambos; Spyrakopoulos, Panagiotis; Vagenas, Konstantinos

2010-07-01

Cooperation between medical informatics, wireless communication and pre-hospital emergency services is essential for the optimal pre-hospital patient treatment. The use of technological innovations improves medical care in the pre-hospital setting with regard to the organization of an integrated center, which coordinates all parties involved for the patient's best interest. A dispatch center was developed in the city of Patras, in southwestern Greece, equipped with a Geographic Information System (GIS), which immediately points out the location of emergency vehicles (EVs) on a digital map depicting the city plan. Additionally, three ambulances of the National Center of Immediate Aid (NCIA) were equipped with a decentralized traffic management system for the vehicle's traffic priority at signaled junctions. The system consisted of a cellular-based (GSM) telemedicine module, a Global Positioning System (GPS) and a web camera system in the vehicle cabin. The aforementioned system provided considerable assistance to the pre-hospital treatment first by selecting the ambulance closest to the accident's location and then by pinpointing the optimum route to the hospital, thus significantly reducing the overall transportation time. The project's objective to coordinate emergency hospital departments involved in the treatment of trauma patients with other emergency services by utilizing high technology was achieved within this interdisciplinary effort.

Achieving Accurate Automatic Sleep Staging on Manually Pre-processed EEG Data Through Synchronization Feature Extraction and Graph Metrics.

PubMed

Chriskos, Panteleimon; Frantzidis, Christos A; Gkivogkli, Polyxeni T; Bamidis, Panagiotis D; Kourtidou-Papadeli, Chrysoula

2018-01-01

Sleep staging, the process of assigning labels to epochs of sleep, depending on the stage of sleep they belong, is an arduous, time consuming and error prone process as the initial recordings are quite often polluted by noise from different sources. To properly analyze such data and extract clinical knowledge, noise components must be removed or alleviated. In this paper a pre-processing and subsequent sleep staging pipeline for the sleep analysis of electroencephalographic signals is described. Two novel methods of functional connectivity estimation (Synchronization Likelihood/SL and Relative Wavelet Entropy/RWE) are comparatively investigated for automatic sleep staging through manually pre-processed electroencephalographic recordings. A multi-step process that renders signals suitable for further analysis is initially described. Then, two methods that rely on extracting synchronization features from electroencephalographic recordings to achieve computerized sleep staging are proposed, based on bivariate features which provide a functional overview of the brain network, contrary to most proposed methods that rely on extracting univariate time and frequency features. Annotation of sleep epochs is achieved through the presented feature extraction methods by training classifiers, which are in turn able to accurately classify new epochs. Analysis of data from sleep experiments on a randomized, controlled bed-rest study, which was organized by the European Space Agency and was conducted in the "ENVIHAB" facility of the Institute of Aerospace Medicine at the German Aerospace Center (DLR) in Cologne, Germany attains high accuracy rates, over 90% based on ground truth that resulted from manual sleep staging by two experienced sleep experts. Therefore, it can be concluded that the above feature extraction methods are suitable for semi-automatic sleep staging.

EARLINET: potential operationality of a research network

NASA Astrophysics Data System (ADS)

Sicard, M.; D'Amico, G.; Comerón, A.; Mona, L.; Alados-Arboledas, L.; Amodeo, A.; Baars, H.; Belegante, L.; Binietoglou, I.; Bravo-Aranda, J. A.; Fernández, A. J.; Fréville, P.; García-Vizcaíno, D.; Giunta, A.; Granados-Muñoz, M. J.; Guerrero-Rascado, J. L.; Hadjimitsis, D.; Haefele, A.; Hervo, M.; Iarlori, M.; Kokkalis, P.; Lange, D.; Mamouri, R. E.; Mattis, I.; Molero, F.; Montoux, N.; Muñoz, A.; Muñoz Porcar, C.; Navas-Guzmán, F.; Nicolae, D.; Nisantzi, A.; Papagiannopoulos, N.; Papayannis, A.; Pereira, S.; Preißler, J.; Pujadas, M.; Rizi, V.; Rocadenbosch, F.; Sellegri, K.; Simeonov, V.; Tsaknakis, G.; Wagner, F.; Pappalardo, G.

2015-07-01

In the framework of ACTRIS summer 2012 measurement campaign (8 June-17 July 2012), EARLINET organized and performed a controlled exercise of feasibility to demonstrate its potential to perform operational, coordinated measurements and deliver products in near-real time. Eleven lidar stations participated to the exercise which started on 9 July 2012 at 06:00 UT and ended 72 h later on 12 July at 06:00 UT. For the first time the Single-Calculus Chain (SCC), the common calculus chain developed within EARLINET for the automatic evaluation of lidar data from raw signals up to the final products, was used. All stations sent in real time measurements of 1 h of duration to the SCC server in a predefined netcdf file format. The pre-processing of the data was performed in real time by the SCC while the optical processing was performed in near-real time after the exercise ended. 98 and 84 % of the files sent to SCC were successfully pre-processed and processed, respectively. Those percentages are quite large taking into account that no cloud screening was performed on lidar data. The paper shows time series of continuous and homogeneously obtained products retrieved at different levels of the SCC: range-square corrected signals (pre-processing) and daytime backscatter and nighttime extinction coefficient profiles (optical processing), as well as combined plots of all direct and derived optical products. The derived products include backscatter- and extinction-related Ångström exponents, lidar ratios and color ratios. The combined plots reveal extremely valuable for aerosol classification. The efforts made to define the measurements protocol and to configure properly the SCC pave the way for applying this protocol for specific applications such as the monitoring of special events, atmospheric modelling, climate research and calibration/validation activities of spaceborne observations.

Achieving Accurate Automatic Sleep Staging on Manually Pre-processed EEG Data Through Synchronization Feature Extraction and Graph Metrics

PubMed Central

Chriskos, Panteleimon; Frantzidis, Christos A.; Gkivogkli, Polyxeni T.; Bamidis, Panagiotis D.; Kourtidou-Papadeli, Chrysoula

2018-01-01

Sleep staging, the process of assigning labels to epochs of sleep, depending on the stage of sleep they belong, is an arduous, time consuming and error prone process as the initial recordings are quite often polluted by noise from different sources. To properly analyze such data and extract clinical knowledge, noise components must be removed or alleviated. In this paper a pre-processing and subsequent sleep staging pipeline for the sleep analysis of electroencephalographic signals is described. Two novel methods of functional connectivity estimation (Synchronization Likelihood/SL and Relative Wavelet Entropy/RWE) are comparatively investigated for automatic sleep staging through manually pre-processed electroencephalographic recordings. A multi-step process that renders signals suitable for further analysis is initially described. Then, two methods that rely on extracting synchronization features from electroencephalographic recordings to achieve computerized sleep staging are proposed, based on bivariate features which provide a functional overview of the brain network, contrary to most proposed methods that rely on extracting univariate time and frequency features. Annotation of sleep epochs is achieved through the presented feature extraction methods by training classifiers, which are in turn able to accurately classify new epochs. Analysis of data from sleep experiments on a randomized, controlled bed-rest study, which was organized by the European Space Agency and was conducted in the “ENVIHAB” facility of the Institute of Aerospace Medicine at the German Aerospace Center (DLR) in Cologne, Germany attains high accuracy rates, over 90% based on ground truth that resulted from manual sleep staging by two experienced sleep experts. Therefore, it can be concluded that the above feature extraction methods are suitable for semi-automatic sleep staging. PMID:29628883

Doppler-corrected differential detection system

NASA Technical Reports Server (NTRS)

Simon, Marvin K. (Inventor); Divsalar, Dariush (Inventor)

1991-01-01

Doppler in a communication system operating with a multiple differential phase-shift-keyed format (MDPSK) creates an adverse phase shift in an incoming signal. An open loop frequency estimation is derived from a Doppler-contaminated incoming signal. Based upon the recognition that, whereas the change in phase of the received signal over a full symbol contains both the differentially encoded data and the Doppler induced phase shift, the same change in phase over half a symbol (within a given symbol interval) contains only the Doppler induced phase shift, and the Doppler effect can be estimated and removed from the incoming signal. Doppler correction occurs prior to the receiver's final output of decoded data. A multiphase system can operate with two samplings per symbol interval at no penalty in signal-to-noise ratio provided that an ideal low pass pre-detection filter is employed, and two samples, at 1/4 and 3/4 of the symbol interval T sub s, are taken and summed together prior to incoming signal data detection.

EMGD-FE: an open source graphical user interface for estimating isometric muscle forces in the lower limb using an EMG-driven model

PubMed Central

2014-01-01

Background This paper describes the “EMG Driven Force Estimator (EMGD-FE)”, a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results. Results An example of the application’s functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown. Conclusions The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues. PMID:24708668

EMGD-FE: an open source graphical user interface for estimating isometric muscle forces in the lower limb using an EMG-driven model.

PubMed

Menegaldo, Luciano Luporini; de Oliveira, Liliam Fernandes; Minato, Kin K

2014-04-04

This paper describes the "EMG Driven Force Estimator (EMGD-FE)", a Matlab® graphical user interface (GUI) application that estimates skeletal muscle forces from electromyography (EMG) signals. Muscle forces are obtained by numerically integrating a system of ordinary differential equations (ODEs) that simulates Hill-type muscle dynamics and that utilises EMG signals as input. In the current version, the GUI can estimate the forces of lower limb muscles executing isometric contractions. Muscles from other parts of the body can be tested as well, although no default values for model parameters are provided. To achieve accurate evaluations, EMG collection is performed simultaneously with torque measurement from a dynamometer. The computer application guides the user, step-by-step, to pre-process the raw EMG signals, create inputs for the muscle model, numerically integrate the ODEs and analyse the results. An example of the application's functions is presented using the quadriceps femoris muscle. Individual muscle force estimations for the four components as well the knee isometric torque are shown. The proposed GUI can estimate individual muscle forces from EMG signals of skeletal muscles. The estimation accuracy depends on several factors, including signal collection and modelling hypothesis issues.

The Effects of Pre-processing Strategies for Pediatric Cochlear Implant Recipients

PubMed Central

Rakszawski, Bernadette; Wright, Rose; Cadieux, Jamie H.; Davidson, Lisa S.; Brenner, Christine

2016-01-01

Background Cochlear implants (CIs) have been shown to improve children’s speech recognition over traditional amplification when severe to profound sensorineural hearing loss is present. Despite improvements, understanding speech at low-level intensities or in the presence of background noise remains difficult. In an effort to improve speech understanding in challenging environments, Cochlear Ltd. offers pre-processing strategies that apply various algorithms prior to mapping the signal to the internal array. Two of these strategies include Autosensitivity Control™ (ASC) and Adaptive Dynamic Range Optimization (ADRO®). Based on previous research, the manufacturer’s default pre-processing strategy for pediatrics’ everyday programs combines ASC+ADRO®. Purpose The purpose of this study is to compare pediatric speech perception performance across various pre-processing strategies while applying a specific programming protocol utilizing increased threshold (T) levels to ensure access to very low-level sounds. Research Design This was a prospective, cross-sectional, observational study. Participants completed speech perception tasks in four pre-processing conditions: no pre-processing, ADRO®, ASC, ASC+ADRO®. Study Sample Eleven pediatric Cochlear Ltd. cochlear implant users were recruited: six bilateral, one unilateral, and four bimodal. Intervention Four programs, with the participants’ everyday map, were loaded into the processor with different pre-processing strategies applied in each of the four positions: no pre-processing, ADRO®, ASC, and ASC+ADRO®. Data Collection and Analysis Participants repeated CNC words presented at 50 and 70 dB SPL in quiet and HINT sentences presented adaptively with competing R-Space noise at 60 and 70 dB SPL. Each measure was completed as participants listened with each of the four pre-processing strategies listed above. Test order and condition were randomized. A repeated-measures analysis of variance (ANOVA) was used to compare each pre-processing strategy across group data. Critical differences were utilized to determine significant score differences between each pre-processing strategy for individual participants. Results For CNC words presented at 50 dB SPL, the group data revealed significantly better scores using ASC+ADRO® compared to all other pre-processing conditions while ASC resulted in poorer scores compared to ADRO® and ASC+ADRO®. Group data for HINT sentences presented in 70 dB SPL of R-Space noise revealed significantly improved scores using ASC and ASC+ADRO® compared to no pre-processing, with ASC+ADRO® scores being better than ADRO® alone scores. Group data for CNC words presented at 70 dB SPL and adaptive HINT sentences presented in 60 dB SPL of R-Space noise showed no significant difference among conditions. Individual data showed that the pre-processing strategy yielding the best scores varied across measures and participants. Conclusions Group data reveals an advantage with ASC+ADRO® for speech perception presented at lower levels and in higher levels of background noise. Individual data revealed that the optimal pre-processing strategy varied among participants; indicating that a variety of pre-processing strategies should be explored for each CI user considering his or her performance in challenging listening environments. PMID:26905529

Design of a dataway processor for a parallel image signal processing system

NASA Astrophysics Data System (ADS)

Nomura, Mitsuru; Fujii, Tetsuro; Ono, Sadayasu

1995-04-01

Recently, demands for high-speed signal processing have been increasing especially in the field of image data compression, computer graphics, and medical imaging. To achieve sufficient power for real-time image processing, we have been developing parallel signal-processing systems. This paper describes a communication processor called 'dataway processor' designed for a new scalable parallel signal-processing system. The processor has six high-speed communication links (Dataways), a data-packet routing controller, a RISC CORE, and a DMA controller. Each communication link operates at 8-bit parallel in a full duplex mode at 50 MHz. Moreover, data routing, DMA, and CORE operations are processed in parallel. Therefore, sufficient throughput is available for high-speed digital video signals. The processor is designed in a top- down fashion using a CAD system called 'PARTHENON.' The hardware is fabricated using 0.5-micrometers CMOS technology, and its hardware is about 200 K gates.

Free-running ADC- and FPGA-based signal processing method for brain PET using GAPD arrays

NASA Astrophysics Data System (ADS)

Hu, Wei; Choi, Yong; Hong, Key Jo; Kang, Jihoon; Jung, Jin Ho; Huh, Youn Suk; Lim, Hyun Keong; Kim, Sang Su; Kim, Byung-Tae; Chung, Yonghyun

2012-02-01

Currently, for most photomultiplier tube (PMT)-based PET systems, constant fraction discriminators (CFD) and time to digital converters (TDC) have been employed to detect gamma ray signal arrival time, whereas anger logic circuits and peak detection analog-to-digital converters (ADCs) have been implemented to acquire position and energy information of detected events. As compared to PMT the Geiger-mode avalanche photodiodes (GAPDs) have a variety of advantages, such as compactness, low bias voltage requirement and MRI compatibility. Furthermore, the individual read-out method using a GAPD array coupled 1:1 with an array scintillator can provide better image uniformity than can be achieved using PMT and anger logic circuits. Recently, a brain PET using 72 GAPD arrays (4×4 array, pixel size: 3 mm×3 mm) coupled 1:1 with LYSO scintillators (4×4 array, pixel size: 3 mm×3 mm×20 mm) has been developed for simultaneous PET/MRI imaging in our laboratory. Eighteen 64:1 position decoder circuits (PDCs) were used to reduce GAPD channel number and three off-the-shelf free-running ADC and field programmable gate array (FPGA) combined data acquisition (DAQ) cards were used for data acquisition and processing. In this study, a free-running ADC- and FPGA-based signal processing method was developed for the detection of gamma ray signal arrival time, energy and position information all together for each GAPD channel. For the method developed herein, three DAQ cards continuously acquired 18 channels of pre-amplified analog gamma ray signals and 108-bit digital addresses from 18 PDCs. In the FPGA, the digitized gamma ray pulses and digital addresses were processed to generate data packages containing pulse arrival time, baseline value, energy value and GAPD channel ID. Finally, these data packages were saved to a 128 Mbyte on-board synchronous dynamic random access memory (SDRAM) and then transferred to a host computer for coincidence sorting and image reconstruction. In order to evaluate the functionality of the developed signal processing method, energy and timing resolutions for brain PET were measured via the placement of a 6 μCi 22Na point source at the center of the PET scanner. Furthermore the PET image of the hot rod phantom (rod diameter: from 2.5 mm to 6.5 mm) with activity of 1 mCi was simulated, and then image acquisition experiment was performed using the brain PET. Measured average energy resolution for 1152 GAPD channels and system timing resolution were 19.5% (FWHM%) and 2.7 ns (FWHM), respectively. With regard to the acquisition of the hot rod phantom image, rods could be resolved down to a diameter of 2.5 mm, which was similar to simulated results. The experimental results demonstrated that the signal processing method developed herein was successfully implemented for brain PET. This reduced the complexity, cost and developing duration for PET system relative to normal PET electronics, and it will obviously be useful for the development of high-performance investigational PET systems.

Diagnostic quality driven physiological data collection for personal healthcare.

PubMed

Jea, David; Balani, Rahul; Hsu, Ju-Lan; Cho, Dae-Ki; Gerla, Mario; Srivastava, Mani B

2008-01-01

We believe that each individual is unique, and that it is necessary for diagnosis purpose to have a distinctive combination of signals and data features that fits the personal health status. It is essential to develop mechanisms for reducing the amount of data that needs to be transferred (to mitigate the troublesome periodically recharging of a device) while maintaining diagnostic accuracy. Thus, the system should not uniformly compress the collected physiological data, but compress data in a personalized fashion that preserves the 'important' signal features for each individual such that it is enough to make the diagnosis with a required high confidence level. We present a diagnostic quality driven mechanism for remote ECG monitoring, which enables a notation of priorities encoded into the wave segments. The priority is specified by the diagnosis engine or medical experts and is dynamic and individual dependent. The system pre-processes the collected physiological information according to the assigned priority before delivering to the backend server. We demonstrate that the proposed approach provides accurate inference results while effectively compressing the data.

Pre-lexical disorders in repetition conduction aphasia.

PubMed

Sidiropoulos, Kyriakos; de Bleser, Ria; Ackermann, Hermann; Preilowski, Bruno

2008-12-01

At the level of clinical speech/language evaluation, the repetition type of conduction aphasia is characterized by repetition difficulties concomitant with reduced short-term memory capacities, in the presence of fluent spontaneous speech as well as unimpaired naming and reading abilities. It is still unsettled which dysfunctions of the pre-lexical processing stage of spoken word recognition contribute to this syndrome and whether there is any relevant top-down impact of the mental lexicon upon the phonetic/phonological level of speech perception. In order to further specify the underlying pathomechanisms, a comprehensive battery of psycholinguistic tests was applied to a patient suffering from repetition conduction aphasia. The obtained results point at a pre-lexical disorder in this subject. To further specify the assumed pre-lexical dysfunction, computer simulations of single-word processing, based upon an interactive activation model (IAM), were conducted. An attenuation of the features-to-phonemes inhibition value was found to simulate the observed profile of psycholinguistic deficits. Conceivably, these pre-lexical disorders interfere with the task-dependent adjustment of the temporal windows of signal analysis, giving rise to compromised sequencing of auditory-verbal information.

Strobe Traffic Lights Warn of Approaching Emergency Vehicles

NASA Technical Reports Server (NTRS)

Bachelder, Aaron

2004-01-01

Strobe-enhanced traffic signals have been developed to aid in the preemption of road intersections for emergency vehicles. The strobe-enhanced traffic signals can be incorporated into both new and pre-existing traffic-control systems in which the traffic-signal heads are of a relatively new type based on arrays of light-emitting diodes (LEDs). The strobe-enhanced traffic signals offer a less expensive, less complex alternative to a recently developed system of LED-based warning signs placed next to traffic signals. Because of its visual complexity, the combination of traffic signals and warning signs is potentially confusing to motorists. The strobe-enhanced traffic signals present less visual clutter. In a given traffic-signal head, the strobe-enhanced traffic signal is embedded in the red LED array of the stop signal. Two strobe LED strips one horizontal and one vertical are made capable of operating separately from the rest of the red LED matrix. When no emergency vehicle is approaching, the red LED array functions as a normal stop signal: all the red LEDs are turned on and off together. When the intersection is to be preempted for an approaching emergency vehicle, only the LEDs in one of the strobe strips are lit, and are turned on in a sequence that indicates the direction of approach. For example (see figure), if an emergency vehicle approaches from the right, the strobe LEDs are lit in a sequence moving from right to left. Important to the success of strobe-enhanced traffic signals is conformance to city ordinances and close relation to pre-existing traffic standards. For instance, one key restriction is that new icons must not include arrows, so that motorists will not confuse new icons with conventional arrows that indicate allowed directions of movement. It is also critical that new displays like strobe-enhanced traffic signals be similar to displays used in traffic-control systems in large cities. For example, Charleston, South Carolina uses horizontal strobes on red traffic lights to alert motorists and thereby help motorists not to miss red lights. The one significant potential disadvantage of strobe-enhanced traffic lights is initial unfamiliarity on the part of motorists.

System for monitoring non-coincident, nonstationary process signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.

2005-01-04

An improved system for monitoring non-coincident, non-stationary, process signals. The mean, variance, and length of a reference signal is defined by an automated system, followed by the identification of the leading and falling edges of a monitored signal and the length of the monitored signal. The monitored signal is compared to the reference signal, and the monitored signal is resampled in accordance with the reference signal. The reference signal is then correlated with the resampled monitored signal such that the reference signal and the resampled monitored signal are coincident in time with each other. The resampled monitored signal is then compared to the reference signal to determine whether the resampled monitored signal is within a set of predesignated operating conditions.

Multi-label spacecraft electrical signal classification method based on DBN and random forest

PubMed Central

Li, Ke; Yu, Nan; Li, Pengfei; Song, Shimin; Wu, Yalei; Li, Yang; Liu, Meng

2017-01-01

In spacecraft electrical signal characteristic data, there exists a large amount of data with high-dimensional features, a high computational complexity degree, and a low rate of identification problems, which causes great difficulty in fault diagnosis of spacecraft electronic load systems. This paper proposes a feature extraction method that is based on deep belief networks (DBN) and a classification method that is based on the random forest (RF) algorithm; The proposed algorithm mainly employs a multi-layer neural network to reduce the dimension of the original data, and then, classification is applied. Firstly, we use the method of wavelet denoising, which was used to pre-process the data. Secondly, the deep belief network is used to reduce the feature dimension and improve the rate of classification for the electrical characteristics data. Finally, we used the random forest algorithm to classify the data and comparing it with other algorithms. The experimental results show that compared with other algorithms, the proposed method shows excellent performance in terms of accuracy, computational efficiency, and stability in addressing spacecraft electrical signal data. PMID:28486479

Multi-label spacecraft electrical signal classification method based on DBN and random forest.

PubMed

Li, Ke; Yu, Nan; Li, Pengfei; Song, Shimin; Wu, Yalei; Li, Yang; Liu, Meng

2017-01-01

In spacecraft electrical signal characteristic data, there exists a large amount of data with high-dimensional features, a high computational complexity degree, and a low rate of identification problems, which causes great difficulty in fault diagnosis of spacecraft electronic load systems. This paper proposes a feature extraction method that is based on deep belief networks (DBN) and a classification method that is based on the random forest (RF) algorithm; The proposed algorithm mainly employs a multi-layer neural network to reduce the dimension of the original data, and then, classification is applied. Firstly, we use the method of wavelet denoising, which was used to pre-process the data. Secondly, the deep belief network is used to reduce the feature dimension and improve the rate of classification for the electrical characteristics data. Finally, we used the random forest algorithm to classify the data and comparing it with other algorithms. The experimental results show that compared with other algorithms, the proposed method shows excellent performance in terms of accuracy, computational efficiency, and stability in addressing spacecraft electrical signal data.

FISSA: A neuropil decontamination toolbox for calcium imaging signals.

PubMed

Keemink, Sander W; Lowe, Scott C; Pakan, Janelle M P; Dylda, Evelyn; van Rossum, Mark C W; Rochefort, Nathalie L

2018-02-22

In vivo calcium imaging has become a method of choice to image neuronal population activity throughout the nervous system. These experiments generate large sequences of images. Their analysis is computationally intensive and typically involves motion correction, image segmentation into regions of interest (ROIs), and extraction of fluorescence traces from each ROI. Out of focus fluorescence from surrounding neuropil and other cells can strongly contaminate the signal assigned to a given ROI. In this study, we introduce the FISSA toolbox (Fast Image Signal Separation Analysis) for neuropil decontamination. Given pre-defined ROIs, the FISSA toolbox automatically extracts the surrounding local neuropil and performs blind-source separation with non-negative matrix factorization. Using both simulated and in vivo data, we show that this toolbox performs similarly or better than existing published methods. FISSA requires only little RAM, and allows for fast processing of large datasets even on a standard laptop. The FISSA toolbox is available in Python, with an option for MATLAB format outputs, and can easily be integrated into existing workflows. It is available from Github and the standard Python repositories.

Adaptive Gaussian mixture models for pre-screening in GPR data

NASA Astrophysics Data System (ADS)

Torrione, Peter; Morton, Kenneth, Jr.; Besaw, Lance E.

2011-06-01

Due to the large amount of data generated by vehicle-mounted ground penetrating radar (GPR) antennae arrays, advanced feature extraction and classification can only be performed on a small subset of data during real-time operation. As a result, most GPR based landmine detection systems implement "pre-screening" algorithms to processes all of the data generated by the antennae array and identify locations with anomalous signatures for more advanced processing. These pre-screening algorithms must be computationally efficient and obtain high probability of detection, but can permit a false alarm rate which might be higher than the total system requirements. Many approaches to prescreening have previously been proposed, including linear prediction coefficients, the LMS algorithm, and CFAR-based approaches. Similar pre-screening techniques have also been developed in the field of video processing to identify anomalous behavior or anomalous objects. One such algorithm, an online k-means approximation to an adaptive Gaussian mixture model (GMM), is particularly well-suited to application for pre-screening in GPR data due to its computational efficiency, non-linear nature, and relevance of the logic underlying the algorithm to GPR processing. In this work we explore the application of an adaptive GMM-based approach for anomaly detection from the video processing literature to pre-screening in GPR data. Results with the ARA Nemesis landmine detection system demonstrate significant pre-screening performance improvements compared to alternative approaches, and indicate that the proposed algorithm is a complimentary technique to existing methods.

Signal processing: opportunities for superconductive circuits

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

Ralston, R.W.

1985-03-01

Prime motivators in the evolution of increasingly sophisticated communication and detection systems are the needs for handling ever wider signal bandwidths and higher data processing speeds. These same needs drive the development of electronic device technology. Until recently the superconductive community has been tightly focused on digital devices for high speed computers. The purpose of this paper is to describe opportunities and challenges which exist for both analog and digital devices in a less familiar area, that of wideband signal processing. The function and purpose of analog signal-processing components, including matched filters, correlators and Fourier transformers, will be described andmore » examples of superconductive implementations given. A canonic signal-processing system is then configured using these components in combination with analog/digital converters and digital output circuits to highlight the important issues of dynamic range, accuracy and equivalent computation rate. Superconductive circuits hold promise for processing signals of 10-GHz bandwidth. Signal processing systems, however, can be properly designed and implemented only through a synergistic combination of the talents of device physicists, circuit designers, algorithm architects and system engineers. An immediate challenge to the applied superconductivity community is to begin sharing ideas with these other researchers.« less

Constrained maximum consistency multi-path mitigation

NASA Astrophysics Data System (ADS)

Smith, George B.

2003-10-01

Blind deconvolution algorithms can be useful as pre-processors for signal classification algorithms in shallow water. These algorithms remove the distortion of the signal caused by multipath propagation when no knowledge of the environment is available. A framework in which filters that produce signal estimates from each data channel that are as consistent with each other as possible in a least-squares sense has been presented [Smith, J. Acoust. Soc. Am. 107 (2000)]. This framework provides a solution to the blind deconvolution problem. One implementation of this framework yields the cross-relation on which EVAM [Gurelli and Nikias, IEEE Trans. Signal Process. 43 (1995)] and Rietsch [Rietsch, Geophysics 62(6) (1997)] processing are based. In this presentation, partially blind implementations that have good noise stability properties are compared using Classification Operating Characteristics (CLOC) analysis. [Work supported by ONR under Program Element 62747N and NRL, Stennis Space Center, MS.

Ibrutinib inhibits pre-BCR+ B-cell acute lymphoblastic leukemia progression by targeting BTK and BLK

PubMed Central

Kim, Ekaterina; Hurtz, Christian; Koehrer, Stefan; Wang, Zhiqiang; Balasubramanian, Sriram; Chang, Betty Y.; Müschen, Markus; Davis, R. Eric

2017-01-01

Targeting B-cell receptor (BCR) signaling is a successful therapeutic strategy in mature B-cell malignancies. Precursor BCR (pre-BCR) signaling, which is critical during normal B lymphopoiesis, also plays an important role in pre-BCR+ B cell acute lymphoblastic leukemia (B-ALL). Here, we investigated the activity and mechanism of action of the BTK inhibitor ibrutinib in preclinical models of B-ALL. Pre-BCR+ ALL cells were exquisitely sensitive to ibrutinib at therapeutically relevant drug concentrations. In pre-BCR+ ALL, ibrutinib thwarted autonomous and induced pre-BCR signaling, resulting in deactivation of PI3K/Akt signaling. Ibrutinib modulated the expression of pre-BCR regulators (PTPN6, CD22, CD72, and PKCβ) and substantially reduced BCL6 levels. Ibrutinib inhibited ALL cell migration toward CXCL12 and beneath marrow stromal cells and reduced CD44 expression. CRISPR-Cas9 gene editing revealed that both BTK and B lymphocyte kinase (BLK) are relevant targets of ibrutinib in pre-BCR+ ALL. Consequently, in mouse xenograft models of pre-BCR+ ALL, ibrutinib treatment significantly prolonged survival. Combination treatment of ibrutinib with dexamethasone or vincristine demonstrated synergistic activity against pre-BCR+ ALL. These data corroborate ibrutinib as a promising targeted agent for pre-BCR+ ALL and highlight the importance of ibrutinib effects on alternative kinase targets. PMID:28031181

Research on photodiode detector-based spatial transient light detection and processing system

NASA Astrophysics Data System (ADS)

Liu, Meiying; Wang, Hu; Liu, Yang; Zhao, Hui; Nan, Meng

2016-10-01

In order to realize real-time signal identification and processing of spatial transient light, the features and the energy of the captured target light signal are first described and quantitatively calculated. Considering that the transient light signal has random occurrence, a short duration and an evident beginning and ending, a photodiode detector based spatial transient light detection and processing system is proposed and designed in this paper. This system has a large field of view and is used to realize non-imaging energy detection of random, transient and weak point target under complex background of spatial environment. Weak signal extraction under strong background is difficult. In this paper, considering that the background signal changes slowly and the target signal changes quickly, filter is adopted for signal's background subtraction. A variable speed sampling is realized by the way of sampling data points with a gradually increased interval. The two dilemmas that real-time processing of large amount of data and power consumption required by the large amount of data needed to be stored are solved. The test results with self-made simulative signal demonstrate the effectiveness of the design scheme. The practical system could be operated reliably. The detection and processing of the target signal under the strong sunlight background was realized. The results indicate that the system can realize real-time detection of target signal's characteristic waveform and monitor the system working parameters. The prototype design could be used in a variety of engineering applications.

SPROC: A multiple-processor DSP IC

NASA Technical Reports Server (NTRS)

Davis, R.

1991-01-01

A large, single-chip, multiple-processor, digital signal processing (DSP) integrated circuit (IC) fabricated in HP-Cmos34 is presented. The innovative architecture is best suited for analog and real-time systems characterized by both parallel signal data flows and concurrent logic processing. The IC is supported by a powerful development system that transforms graphical signal flow graphs into production-ready systems in minutes. Automatic compiler partitioning of tasks among four on-chip processors gives the IC the signal processing power of several conventional DSP chips.

System and method for investigating sub-surface features of a rock formation with acoustic sources generating coded signals

DOEpatents

Vu, Cung Khac; Nihei, Kurt; Johnson, Paul A; Guyer, Robert; Ten Cate, James A; Le Bas, Pierre-Yves; Larmat, Carene S

2014-12-30

A system and a method for investigating rock formations includes generating, by a first acoustic source, a first acoustic signal comprising a first plurality of pulses, each pulse including a first modulated signal at a central frequency; and generating, by a second acoustic source, a second acoustic signal comprising a second plurality of pulses. A receiver arranged within the borehole receives a detected signal including a signal being generated by a non-linear mixing process from the first-and-second acoustic signal in a non-linear mixing zone within the intersection volume. The method also includes-processing the received signal to extract the signal generated by the non-linear mixing process over noise or over signals generated by a linear interaction process, or both.

Digital Signal Processing Based Biotelemetry Receivers

NASA Technical Reports Server (NTRS)

Singh, Avtar; Hines, John; Somps, Chris

1997-01-01

This is an attempt to develop a biotelemetry receiver using digital signal processing technology and techniques. The receiver developed in this work is based on recovering signals that have been encoded using either Pulse Position Modulation (PPM) or Pulse Code Modulation (PCM) technique. A prototype has been developed using state-of-the-art digital signal processing technology. A Printed Circuit Board (PCB) is being developed based on the technique and technology described here. This board is intended to be used in the UCSF Fetal Monitoring system developed at NASA. The board is capable of handling a variety of PPM and PCM signals encoding signals such as ECG, temperature, and pressure. A signal processing program has also been developed to analyze the received ECG signal to determine heart rate. This system provides a base for using digital signal processing in biotelemetry receivers and other similar applications.

An Automated Flying-Insect-Detection System

NASA Technical Reports Server (NTRS)

Vann, Timi; Andrews, Jane C.; Howell, Dane; Ryan, Robert

2005-01-01

An automated flying-insect-detection system (AFIDS) was developed as a proof-of-concept instrument for real-time detection and identification of flying insects. This type of system has use in public health and homeland security decision support, agriculture and military pest management, and/or entomological research. Insects are first lured into the AFIDS integrated sphere by insect attractants. Once inside the sphere, the insect's wing beats cause alterations in light intensity that is detected by a photoelectric sensor. Following detection, the insects are encouraged (with the use of a small fan) to move out of the sphere and into a designated insect trap where they are held for taxonomic identification or serological testing. The acquired electronic wing beat signatures are preprocessed (Fourier transformed) in real-time to display a periodic signal. These signals are sent to the end user where they are graphically displayed. All AFIDS data are pre-processed in the field with the use of a laptop computer equipped with LABVIEW. The AFIDS software can be programmed to run continuously or at specific time intervals when insects are prevalent. A special DC-restored transimpedance amplifier reduces the contributions of low-frequency background light signals, and affords approximately two orders of magnitude greater AC gain than conventional amplifiers. This greatly increases the signal-to-noise ratio and enables the detection of small changes in light intensity. The AFIDS light source consists of high-intensity Al GaInP light-emitting diodes (LEDs). The AFIDS circuitry minimizes brightness fluctuations in the LEDs and when integrated with an integrating sphere, creates a diffuse uniform light field. The insect wing beats isotropically scatter the diffuse light in the sphere and create wing beat signatures that are detected by the sensor. This configuration minimizes variations in signal associated with insect flight orientation.

A coded tracking telemetry system

USGS Publications Warehouse

Howey, P.W.; Seegar, W.S.; Fuller, M.R.; Titus, K.; Amlaner, Charles J.

1989-01-01

We describe the general characteristics of an automated radio telemetry system designed to operate for prolonged periods on a single frequency. Each transmitter sends a unique coded signal to a receiving system that encodes and records only the appropriater, pre-programmed codes. A record of the time of each reception is stored on diskettes in a micro-computer. This system enables continuous monitoring of infrequent signals (e.g. one per minute or one per hour), thus extending operation life or allowing size reduction of the transmitter, compared to conventional wildlife telemetry. Furthermore, when using unique codes transmitted on a single frequency, biologists can monitor many individuals without exceeding the radio frequency allocations for wildlife.

Laser driving and data processing concept for mobile trace gas sensing: Design and implementation

NASA Astrophysics Data System (ADS)

Liu, Chang; Tuzson, Béla; Scheidegger, Philipp; Looser, Herbert; Bereiter, Bernhard; Graf, Manuel; Hundt, Morten; Aseev, Oleg; Maas, Deran; Emmenegger, Lukas

2018-06-01

High precision mobile sensing of multi-species gases is greatly demanded in a wide range of applications. Although quantum cascade laser absorption spectroscopy demonstrates excellent field-deployment capabilities for gas sensing, the implementation of this measurement technique into sensor-like portable instrumentation still remains challenging. In this paper, two crucial elements, the laser driving and data acquisition electronics, are addressed. Therefore, we exploit the benefits of the time-division multiplexed intermittent continuous wave driving concept and the real-time signal pre-processing capabilities of a commercial System-on-Chip (SoC, Red Pitaya). We describe a re-designed current driver that offers a universal solution for operating a wide range of multi-wavelength quantum cascade laser device types and allows stacking for the purpose of multiple laser configurations. Its adaptation to the various driving situations is enabled by numerous field programmable gate array (FPGA) functionalities that were developed on the SoC, such as flexible generation of a large variety of synchronized trigger signals and digital inputs/outputs (DIOs). The same SoC is used to sample the spectroscopic signal at rates up to 125 MS/s with 14-bit resolution. Additional FPGA functionalities were implemented to enable on-board averaging of consecutive spectral scans in real-time, resulting in optimized memory bandwidth and hardware resource utilisation and autonomous system operation. Thus, we demonstrate how a cost-effective, compact, and commercial SoC can successfully be adapted to obtain a fully operational research-grade laser spectrometer. The overall system performance was examined in a spectroscopic setup by analyzing low pressure absorption features of CO2 at 4.3 μm.

Influence of signal intensity non-uniformity on brain volumetry using an atlas-based method.

PubMed

Goto, Masami; Abe, Osamu; Miyati, Tosiaki; Kabasawa, Hiroyuki; Takao, Hidemasa; Hayashi, Naoto; Kurosu, Tomomi; Iwatsubo, Takeshi; Yamashita, Fumio; Matsuda, Hiroshi; Mori, Harushi; Kunimatsu, Akira; Aoki, Shigeki; Ino, Kenji; Yano, Keiichi; Ohtomo, Kuni

2012-01-01

Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 × [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials.

Influence of Signal Intensity Non-Uniformity on Brain Volumetry Using an Atlas-Based Method

PubMed Central

Abe, Osamu; Miyati, Tosiaki; Kabasawa, Hiroyuki; Takao, Hidemasa; Hayashi, Naoto; Kurosu, Tomomi; Iwatsubo, Takeshi; Yamashita, Fumio; Matsuda, Hiroshi; Mori, Harushi; Kunimatsu, Akira; Aoki, Shigeki; Ino, Kenji; Yano, Keiichi; Ohtomo, Kuni

2012-01-01

Objective Many studies have reported pre-processing effects for brain volumetry; however, no study has investigated whether non-parametric non-uniform intensity normalization (N3) correction processing results in reduced system dependency when using an atlas-based method. To address this shortcoming, the present study assessed whether N3 correction processing provides reduced system dependency in atlas-based volumetry. Materials and Methods Contiguous sagittal T1-weighted images of the brain were obtained from 21 healthy participants, by using five magnetic resonance protocols. After image preprocessing using the Statistical Parametric Mapping 5 software, we measured the structural volume of the segmented images with the WFU-PickAtlas software. We applied six different bias-correction levels (Regularization 10, Regularization 0.0001, Regularization 0, Regularization 10 with N3, Regularization 0.0001 with N3, and Regularization 0 with N3) to each set of images. The structural volume change ratio (%) was defined as the change ratio (%) = (100 × [measured volume - mean volume of five magnetic resonance protocols] / mean volume of five magnetic resonance protocols) for each bias-correction level. Results A low change ratio was synonymous with lower system dependency. The results showed that the images with the N3 correction had a lower change ratio compared with those without the N3 correction. Conclusion The present study is the first atlas-based volumetry study to show that the precision of atlas-based volumetry improves when using N3-corrected images. Therefore, correction for signal intensity non-uniformity is strongly advised for multi-scanner or multi-site imaging trials. PMID:22778560

Pre-ischemia melatonin treatment alleviated acute neuronal injury after ischemic stroke by inhibiting endoplasmic reticulum stress-dependent autophagy via PERK and IRE1 signalings.

PubMed

Feng, Dayun; Wang, Bao; Wang, Lei; Abraham, Neeta; Tao, Kai; Huang, Lu; Shi, Wei; Dong, Yushu; Qu, Yan

2017-04-01

Melatonin has demonstrated a potential protective effect in central nervous system. Thus, it is interesting to determine whether pre-ischemia melatonin administration could protect against cerebral ischemia/reperfusion (IR)-related injury and the underlying molecular mechanisms. In this study, we revealed that IR injury significantly activated endoplasmic reticulum (ER) stress and autophagy in a middle cerebral artery occlusion mouse model. Pre-ischemia melatonin treatment was able to attenuate IR-induced ER stress and autophagy. In addition, with tandem RFP-GFP-LC3 adeno-associated virus, we demonstrated pre-ischemic melatonin significantly alleviated IR-induced autophagic flux. Furthermore, we showed that IR induced neuronal apoptosis through ER stress related signalings. Moreover, IR-induced autophagy was significantly blocked by ER stress inhibitor (4-PBA), as well as ER-related signaling inhibitors (PERK inhibitor, GSK; IRE1 inhibitor, 3,5-dibromosalicylaldehyde). Finally, we revealed that melatonin significantly alleviated cerebral infarction, brain edema, neuronal apoptosis, and neurological deficiency, which were remarkably abolished by tunicamycin (ER stress activator) and rapamycin (autophagy activator), respectively. In summary, our study provides strong evidence that pre-ischemia melatonin administration significantly protects against cerebral IR injury through inhibiting ER stress-dependent autophagy. Our findings shed light on the novel preventive and therapeutic strategy of daily administration of melatonin, especially among the population with high risk of cerebral ischemic stroke. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Inactivation of a Single Copy of Crebbp Selectively Alters Pre-mRNA Processing in Mouse Hematopoietic Stem Cells

PubMed Central

Lemieux, Madeleine E.; Cheng, Ziming; Zhou, Qing; White, Ruth; Cornell, John; Kung, Andrew L.; Rebel, Vivienne I.

2011-01-01

Global expression analysis of fetal liver hematopoietic stem cells (FL HSCs) revealed the presence of unspliced pre-mRNA for a number of genes in normal FL HSCs. In a subset of these genes, Crebbp+/− FL HSCs had less unprocessed pre-mRNA without a corresponding reduction in total mRNA levels. Among the genes thus identified were the key regulators of HSC function Itga4, Msi2 and Tcf4. A similar but much weaker effect was apparent in Ep300+/− FL HSCs, indicating that, in this context as in others, the two paralogs are not interchangeable. As a group, the down-regulated intronic probe sets could discriminate adult HSCs from more mature cell types, suggesting that the underlying mechanism is regulated with differentiation stage and is active in both fetal and adult hematopoiesis. Consistent with increased myelopoiesis in Crebbp hemizygous mice, targeted reduction of CREBBP abundance by shRNA in the multipotent EML cell line triggered spontaneous myeloid differentiation in the absence of the normally required inductive signals. In addition, differences in protein levels between phenotypically distinct EML subpopulations were better predicted by taking into account not only the total mRNA signal but also the amount of unspliced message present. CREBBP thus appears to selectively influence the timing and degree of pre-mRNA processing of genes essential for HSC regulation and thereby has the potential to alter subsequent cell fate decisions in HSCs. PMID:21901164

Alternative Pre-mRNA Splicing in Mammals and Teleost Fish: A Effective Strategy for the Regulation of Immune Responses Against Pathogen Infection.

PubMed

Chang, Ming Xian; Zhang, Jie

2017-07-15

Pre-mRNA splicing is the process by which introns are removed and the protein coding elements assembled into mature mRNAs. Alternative pre-mRNA splicing provides an important source of transcriptome and proteome complexity through selectively joining different coding elements to form mRNAs, which encode proteins with similar or distinct functions. In mammals, previous studies have shown the role of alternative splicing in regulating the function of the immune system, especially in the regulation of T-cell activation and function. As lower vertebrates, teleost fish mainly rely on a large family of pattern recognition receptors (PRRs) to recognize pathogen-associated molecular patterns (PAMPs) from various invading pathogens. In this review, we summarize recent advances in our understanding of alternative splicing of piscine PRRs including peptidoglycan recognition proteins (PGRPs), nucleotide binding and oligomerization domain (NOD)-like receptors (NLRs), retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs) and their downstream signaling molecules, compared to splicing in mammals. We also discuss what is known and unknown about the function of splicing isoforms in the innate immune responses against pathogens infection in mammals and teleost fish. Finally, we highlight the consequences of alternative splicing in the innate immune system and give our view of important directions for future studies.

Application of the double relaxation oscillation superconducting quantum interference device sensor to micro-tesla 1H nuclear magnetic resonance experiments

NASA Astrophysics Data System (ADS)

Kang, Chan Seok; Kim, Kiwoong; Lee, Seong-Joo; Hwang, Seong-min; Kim, Jin-Mok; Yu, Kwon Kyu; Kwon, Hyukchan; Lee, Sang Kil; Lee, Yong-Ho

2011-09-01

We developed an ultra-low field (ULF)-nuclear magnetic resonance (NMR) measurement system capable of working with a measurement field (Bm) of several micro-tesla and performed basic NMR studies with a double relaxation oscillation superconducting quantum interference device (DROS) instead of conventional dc-SQUIDs. DROS is a SQUID sensor utilizing a relaxation oscillation between a dc-SQUID and a relaxation circuit; the new unit consists of an inductor and a resistor, and is connected in parallel with the SQUID. DROS has a 10 times larger flux-to-voltage transfer coefficient (˜mV/ϕ0) than that of the dc-SQUID, and this large transfer coefficient enables the acquisition of the SQUID signal with a simple flux-locked-loop (FLL) circuit using room temperature pre-amplifiers. The DROS second-order gradiometer showed average field noise of 9.2 μϕ0/√Hz in a magnetically shielded room (MSR). In addition, a current limiter formed of a Josephson junction array was put in a flux-transformer of DROS to prevent excessive currents that can be generated from the high pre-polarization field (Bp). Using this system, we measured an 1H NMR signal in water under 2.8 μT Bm field and reconstructed a one-dimensional MR image from the 1H NMR signal under a gradient field BG of 4.09 nT/mm. In addition, we confirmed that the ULF-NMR system can measure the NMR signal in the presence of metal without any distortion by measuring the NMR signal of a sample wrapped with metal. Lastly, we have measured the scalar J-coupling of trimethylphosphate and were able to confirm a clear doublet NMR signal with the coupling strength J3[P,H] = 10.4 ± 0.8 Hz. Finally, because the existing ULF-NMR/MRI studies were almost all performed with dc-SQUID based systems, we constructed a dc-SQUID-based ULF-NMR system in addition to the DROS based system and compared the characteristics of the two different systems by operating the two systems under identical experimental conditions.

Investigation of charge coupled device correlation techniques

NASA Technical Reports Server (NTRS)

Lampe, D. R.; Lin, H. C.; Shutt, T. J.

1978-01-01

Analog Charge Transfer Devices (CTD's) offer unique advantages to signal processing systems, which often have large development costs, making it desirable to define those devices which can be developed for general system's use. Such devices are best identified and developed early to give system's designers some interchangeable subsystem blocks, not requiring additional individual development for each new signal processing system. The objective of this work is to describe a discrete analog signal processing device with a reasonably broad system use and to implement its design, fabrication, and testing.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

The modulation transfer function and signal-to-noise ratio of different digital filters: a technical approach.

PubMed

Brüllmann, D D; d'Hoedt, B

2011-05-01

The aim of this study was to illustrate the influence of digital filters on the signal-to-noise ratio (SNR) and modulation transfer function (MTF) of digital images. The article will address image pre-processing that may be beneficial for the production of clinically useful digital radiographs with lower radiation dose. Three filters, an arithmetic mean filter, a median filter and a Gaussian filter (standard deviation (SD) = 0.4), with kernel sizes of 3 × 3 pixels and 5 × 5 pixels were tested. Synthetic images with exactly increasing amounts of Gaussian noise were created to gather linear regression of SNR before and after application of digital filters. Artificial stripe patterns with defined amounts of line pairs per millimetre were used to calculate MTF before and after the application of the digital filters. The Gaussian filter with a 5 × 5 kernel size caused the highest noise suppression (SNR increased from 2.22, measured in the synthetic image, to 11.31 in the filtered image). The smallest noise reduction was found with the 3 × 3 median filter. The application of the median filters resulted in no changes in MTF at the different resolutions but did result in the deletion of smaller structures. The 5 × 5 Gaussian filter and the 5 × 5 arithmetic mean filter showed the strongest changes of MTF. The application of digital filters can improve the SNR of a digital sensor; however, MTF can be adversely affected. As such, imaging systems should not be judged solely on their quoted spatial resolutions because pre-processing may influence image quality.

Fast Sparse Coding for Range Data Denoising with Sparse Ridges Constraint

PubMed Central

Lao, Mingjie; Sang, Yongsheng; Wen, Fei; Zhai, Ruifang

2018-01-01

Light detection and ranging (LiDAR) sensors have been widely deployed on intelligent systems such as unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) to perform localization, obstacle detection, and navigation tasks. Thus, research into range data processing with competitive performance in terms of both accuracy and efficiency has attracted increasing attention. Sparse coding has revolutionized signal processing and led to state-of-the-art performance in a variety of applications. However, dictionary learning, which plays the central role in sparse coding techniques, is computationally demanding, resulting in its limited applicability in real-time systems. In this study, we propose sparse coding algorithms with a fixed pre-learned ridge dictionary to realize range data denoising via leveraging the regularity of laser range measurements in man-made environments. Experiments on both synthesized data and real data demonstrate that our method obtains accuracy comparable to that of sophisticated sparse coding methods, but with much higher computational efficiency. PMID:29734793

Non-Gated Laser Induced Breakdown Spectroscopy Provides a Powerful Segmentation Tool on Concomitant Treatment of Characteristic and Continuum Emission

PubMed Central

Dasari, Ramachandra Rao; Barman, Ishan; Gundawar, Manoj Kumar

2014-01-01

We demonstrate the application of non-gated laser induced breakdown spectroscopy (LIBS) for characterization and classification of organic materials with similar chemical composition. While use of such a system introduces substantive continuum background in the spectral dataset, we show that appropriate treatment of the continuum and characteristic emission results in accurate discrimination of pharmaceutical formulations of similar stoichiometry. Specifically, our results suggest that near-perfect classification can be obtained by employing suitable multivariate analysis on the acquired spectra, without prior removal of the continuum background. Indeed, we conjecture that pre-processing in the form of background removal may introduce spurious features in the signal. Our findings in this report significantly advance the prior results in time-integrated LIBS application and suggest the possibility of a portable, non-gated LIBS system as a process analytical tool, given its simple instrumentation needs, real-time capability and lack of sample preparation requirements. PMID:25084522

Seismic event classification system

DOEpatents

Dowla, F.U.; Jarpe, S.P.; Maurer, W.

1994-12-13

In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities. 21 figures.

Seismic event classification system

DOEpatents

Dowla, Farid U.; Jarpe, Stephen P.; Maurer, William

1994-01-01

In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. Self-organizing neural networks (SONNs) can be used for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs are useful for this purpose. Given the detection of a seismic event and the corresponding signal, computation is made of: the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This pre-processed input is fed into the SONNs. These neural networks are able to group events that look similar. The ART SONN has an advantage in classifying the event because the types of cluster groups do not need to be pre-defined. The results from the SONNs together with an expert seismologist's classification are then used to derive event classification probabilities.

Complex Signal Kurtosis and Independent Component Analysis for Wideband Radio Frequency Interference Detection

NASA Technical Reports Server (NTRS)

Schoenwald, Adam; Mohammed, Priscilla; Bradley, Damon; Piepmeier, Jeffrey; Wong, Englin; Gholian, Armen

2016-01-01

Radio-frequency interference (RFI) has negatively implicated scientific measurements across a wide variation passive remote sensing satellites. This has been observed in the L-band radiometers SMOS, Aquarius and more recently, SMAP [1, 2]. RFI has also been observed at higher frequencies such as K band [3]. Improvements in technology have allowed wider bandwidth digital back ends for passive microwave radiometry. A complex signal kurtosis radio frequency interference detector was developed to help identify corrupted measurements [4]. This work explores the use of ICA (Independent Component Analysis) as a blind source separation technique to pre-process radiometric signals for use with the previously developed real and complex signal kurtosis detectors.

The Reliability and Structure of the Classroom Assessment Scoring System in German Pre-Schools

ERIC Educational Resources Information Center

Stuck, Andrea; Kammermeyer, Gisela; Roux, Susanna

2016-01-01

This study examined the reliability and structure of the Classroom Assessment Scoring System (CLASS; Pianta, R. C., K. M. La Paro, and B. K. Hamre. 2008. "Classroom Assessment Scoring System. Manual Pre-K." Baltimore, MD: Brookes) and the quality of interactional processes in a German pre-school setting, drawing on a sample of 390…

Effects of Teacher Controlled Segmented-Animation Presentation in Facilitating Learning

ERIC Educational Resources Information Center

Mohamad Ali, Ahmad Zamzuri

2010-01-01

The aim of this research was to study the effectiveness of teacher controlled segmented-animation presentation on learning achievement of students with lower level of prior knowledge. Segmented-animation and continuous-animation courseware showing cellular signal transmission process were developed for the research purpose. Pre-test and post-test…

Optical Signal Processing: Poisson Image Restoration and Shearing Interferometry

NASA Technical Reports Server (NTRS)

Hong, Yie-Ming

1973-01-01

Optical signal processing can be performed in either digital or analog systems. Digital computers and coherent optical systems are discussed as they are used in optical signal processing. Topics include: image restoration; phase-object visualization; image contrast reversal; optical computation; image multiplexing; and fabrication of spatial filters. Digital optical data processing deals with restoration of images degraded by signal-dependent noise. When the input data of an image restoration system are the numbers of photoelectrons received from various areas of a photosensitive surface, the data are Poisson distributed with mean values proportional to the illuminance of the incoherently radiating object and background light. Optical signal processing using coherent optical systems is also discussed. Following a brief review of the pertinent details of Ronchi's diffraction grating interferometer, moire effect, carrier-frequency photography, and achromatic holography, two new shearing interferometers based on them are presented. Both interferometers can produce variable shear.

Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

NASA Astrophysics Data System (ADS)

Si, Qian

Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

Method and apparatus for calibrating a tiled display

NASA Technical Reports Server (NTRS)

Chen, Chung-Jen (Inventor); Johnson, Michael J. (Inventor); Chandrasekhar, Rajesh (Inventor)

2001-01-01

A display system that can be calibrated and re-calibrated with a minimal amount of manual intervention. To accomplish this, one or more cameras are provided to capture an image of the display screen. The resulting captured image is processed to identify any non-desirable characteristics, including visible artifacts such as seams, bands, rings, etc. Once the non-desirable characteristics are identified, an appropriate transformation function is determined. The transformation function is used to pre-warp the input video signal that is provided to the display such that the non-desirable characteristics are reduced or eliminated from the display. The transformation function preferably compensates for spatial non-uniformity, color non-uniformity, luminance non-uniformity, and other visible artifacts.

Light-evoked S-nitrosylation in the retina

PubMed Central

Tooker, Ryan E; Vigh, Jozsef

2015-01-01

Nitric oxide (NO) synthesis in the retina is triggered by light stimulation. NO has been shown to modulate visual signal processing at multiple sites in the vertebrate retina, via activation of the most sensitive target of NO signaling, soluble guanylate cyclase. NO can also alter protein structure and function and exert biological effects directly by binding to free thiol groups of cysteine residues in a chemical reaction called S-nitrosylation. However, in the central nervous system, including the retina, this reaction has not been considered to be significant under physiological conditions. Here we provide immunohistochemical evidence for extensive S-nitrosylation that takes place in the goldfish and mouse retinas under physiologically relevant light intensities, in an intensity-dependent manner, with a strikingly similar pattern in both species. Pre-treatment with NEM, which occludes S-nitrosylation, or with TRIM, an inhibitor of neuronal NO synthase, eliminated the light-evoked increase in S-nitrosylated protein immunofluorescence (SNI) in the retinas of both species. Similarly, light did not increase SNI, above basal levels, in retinas of transgenic mice lacking neuronal NO synthase. Qualitative analysis of the light-adapted mouse retina with mass spectrometry revealed more than 300 proteins that were S-nitrosylated upon illumination, many of which are known to participate directly in retinal signal processing. Our data strongly suggest that in the retina, light-evoked NO production leads to extensive S-nitrosylation and that this process is a significant post-translational modification affecting a wide range of proteins under physiological conditions. PMID:25823749

Parallel Signal Processing and System Simulation using aCe

NASA Technical Reports Server (NTRS)

Dorband, John E.; Aburdene, Maurice F.

2003-01-01

Recently, networked and cluster computation have become very popular for both signal processing and system simulation. A new language is ideally suited for parallel signal processing applications and system simulation since it allows the programmer to explicitly express the computations that can be performed concurrently. In addition, the new C based parallel language (ace C) for architecture-adaptive programming allows programmers to implement algorithms and system simulation applications on parallel architectures by providing them with the assurance that future parallel architectures will be able to run their applications with a minimum of modification. In this paper, we will focus on some fundamental features of ace C and present a signal processing application (FFT).

Involvement of SLP-65 and Btk in tumor suppression and malignant transformation of pre-B cells.

PubMed

Hendriks, Rudi W; Kersseboom, Rogier

2006-02-01

Signals from the precursor-B cell receptor (pre-BCR) are essential for selection and clonal expansion of pre-B cells that have performed productive immunoglobulin heavy chain V(D)J recombination. In the mouse, the downstream signaling molecules SLP-65 and Btk cooperate to limit proliferation and induce differentiation of pre-B cells, thereby acting as tumor suppressors to prevent pre-B cell leukemia. In contrast, recent observations in human BCR-ABL1(+) pre-B lymphoblastic leukemia cells demonstrate that Btk is constitutively phosphorylated and activated by the BCR-ABL1 fusion protein. As a result, activated Btk transmits survival signals that are essential for the transforming activity of oncogenic Abl tyrosine kinase.

A nonlinear disturbance-decoupled elevation axis controller for the Multiple Mirror Telescope

NASA Astrophysics Data System (ADS)

Clark, Dusty; Trebisky, Tom; Powell, Keith

2008-07-01

The Multiple Mirror Telescope (MMT), upgraded in 2000 to a monolithic 6.5m primary mirror from its original array of six 1.8m primary mirrors, was commissioned with axis controllers designed early in the upgrade process without regard to structural resonances or the possibility of the need for digital filtering of the control axis signal path. Post-commissioning performance issues led us to investigate replacement of the original control system with a more modern digital controller with full control over the system filters and gain paths. This work, from system identification through controller design iteration by simulation, and pre-deployment hardware-in-the-loop testing, was performed using latest-generation tools with Matlab® and Simulink®. Using Simulink's Real Time Workshop toolbox to automatically generate C source code for the controller from the Simulink diagram and a custom target build script, we were able to deploy the new controller into our existing software infrastructure running Wind River's VxWorks™real-time operating system. This paper describes the process of the controller design, including system identification data collection, with discussion of implementation of non-linear control modes and disturbance decoupling, which became necessary to obtain acceptable wind buffeting rejection.

Ozone Induced Impairment of Systemic Metabolic Processes: Influence of Prior Ozone Exposure and Metformin Pre-treatment on Aged Wistar Kyoto (WKY) Rats.

EPA Science Inventory

SOT2014 Abstract for presentation: March 23-27, 2014; Phoenix, AZ Ozone Induced Impairment of Systemic Metabolic Processes: Influence of Prior Ozone Exposure and Metformin Pre-treatment on Aged Wistar Kyoto (WKY) Rats. V. Bass, D. Andrews, J. Richards, M. Schladweiler, A. Ledb...

Fear processing and social networking in the absence of a functional amygdala.

PubMed

Becker, Benjamin; Mihov, Yoan; Scheele, Dirk; Kendrick, Keith M; Feinstein, Justin S; Matusch, Andreas; Aydin, Merve; Reich, Harald; Urbach, Horst; Oros-Peusquens, Ana-Maria; Shah, Nadim J; Kunz, Wolfram S; Schlaepfer, Thomas E; Zilles, Karl; Maier, Wolfgang; Hurlemann, René

2012-07-01

The human amygdala plays a crucial role in processing social signals, such as face expressions, particularly fearful ones, and facilitates responses to them in face-sensitive cortical regions. This contributes to social competence and individual amygdala size correlates with that of social networks. While rare patients with focal bilateral amygdala lesion typically show impaired recognition of fearful faces, this deficit is variable, and an intriguing possibility is that other brain regions can compensate to support fear and social signal processing. To investigate the brain's functional compensation of selective bilateral amygdala damage, we performed a series of behavioral, psychophysiological, and functional magnetic resonance imaging experiments in two adult female monozygotic twins (patient 1 and patient 2) with equivalent, extensive bilateral amygdala pathology as a sequela of lipoid proteinosis due to Urbach-Wiethe disease. Patient 1, but not patient 2, showed preserved recognition of fearful faces, intact modulation of acoustic startle responses by fear-eliciting scenes, and a normal-sized social network. Functional magnetic resonance imaging revealed that patient 1 showed potentiated responses to fearful faces in her left premotor cortex face area and bilaterally in the inferior parietal lobule. The premotor cortex face area and inferior parietal lobule are both implicated in the cortical mirror-neuron system, which mediates learning of observed actions and may thereby promote both imitation and empathy. Taken together, our findings suggest that despite the pre-eminent role of the amygdala in processing social information, the cortical mirror-neuron system may sometimes adaptively compensate for its pathology. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Elements of an integrated health monitoring framework

NASA Astrophysics Data System (ADS)

Fraser, Michael; Elgamal, Ahmed; Conte, Joel P.; Masri, Sami; Fountain, Tony; Gupta, Amarnath; Trivedi, Mohan; El Zarki, Magda

2003-07-01

Internet technologies are increasingly facilitating real-time monitoring of Bridges and Highways. The advances in wireless communications for instance, are allowing practical deployments for large extended systems. Sensor data, including video signals, can be used for long-term condition assessment, traffic-load regulation, emergency response, and seismic safety applications. Computer-based automated signal-analysis algorithms routinely process the incoming data and determine anomalies based on pre-defined response thresholds and more involved signal analysis techniques. Upon authentication, appropriate action may be authorized for maintenance, early warning, and/or emergency response. In such a strategy, data from thousands of sensors can be analyzed with near real-time and long-term assessment and decision-making implications. Addressing the above, a flexible and scalable (e.g., for an entire Highway system, or portfolio of Networked Civil Infrastructure) software architecture/framework is being developed and implemented. This framework will network and integrate real-time heterogeneous sensor data, database and archiving systems, computer vision, data analysis and interpretation, physics-based numerical simulation of complex structural systems, visualization, reliability & risk analysis, and rational statistical decision-making procedures. Thus, within this framework, data is converted into information, information into knowledge, and knowledge into decision at the end of the pipeline. Such a decision-support system contributes to the vitality of our economy, as rehabilitation, renewal, replacement, and/or maintenance of this infrastructure are estimated to require expenditures in the Trillion-dollar range nationwide, including issues of Homeland security and natural disaster mitigation. A pilot website (http://bridge.ucsd.edu/compositedeck.html) currently depicts some basic elements of the envisioned integrated health monitoring analysis framework.

A quantum inspired model of radar range and range-rate measurements with applications to weak value measurements

NASA Astrophysics Data System (ADS)

Escalante, George

2017-05-01

Weak Value Measurements (WVMs) with pre- and post-selected quantum mechanical ensembles were proposed by Aharonov, Albert, and Vaidman in 1988 and have found numerous applications in both theoretical and applied physics. In the field of precision metrology, WVM techniques have been demonstrated and proven valuable as a means to shift, amplify, and detect signals and to make precise measurements of small effects in both quantum and classical systems, including: particle spin, the Spin-Hall effect of light, optical beam deflections, frequency shifts, field gradients, and many others. In principal, WVM amplification techniques are also possible in radar and could be a valuable tool for precision measurements. However, relatively limited research has been done in this area. This article presents a quantum-inspired model of radar range and range-rate measurements of arbitrary strength, including standard and pre- and post-selected measurements. The model is used to extend WVM amplification theory to radar, with the receive filter performing the post-selection role. It is shown that the description of range and range-rate measurements based on the quantum-mechanical measurement model and formalism produces the same results as the conventional approach used in radar based on signal processing and filtering of the reflected signal at the radar receiver. Numerical simulation results using simple point scatterrer configurations are presented, applying the quantum-inspired model of radar range and range-rate measurements that occur in the weak measurement regime. Potential applications and benefits of the quantum inspired approach to radar measurements are presented, including improved range and Doppler measurement resolution.

Ibrutinib inhibits pre-BCR+ B-cell acute lymphoblastic leukemia progression by targeting BTK and BLK.

PubMed

Kim, Ekaterina; Hurtz, Christian; Koehrer, Stefan; Wang, Zhiqiang; Balasubramanian, Sriram; Chang, Betty Y; Müschen, Markus; Davis, R Eric; Burger, Jan A

2017-03-02

Targeting B-cell receptor (BCR) signaling is a successful therapeutic strategy in mature B-cell malignancies. Precursor BCR (pre-BCR) signaling, which is critical during normal B lymphopoiesis, also plays an important role in pre-BCR + B cell acute lymphoblastic leukemia (B-ALL). Here, we investigated the activity and mechanism of action of the BTK inhibitor ibrutinib in preclinical models of B-ALL. Pre-BCR + ALL cells were exquisitely sensitive to ibrutinib at therapeutically relevant drug concentrations. In pre-BCR + ALL, ibrutinib thwarted autonomous and induced pre-BCR signaling, resulting in deactivation of PI3K/Akt signaling. Ibrutinib modulated the expression of pre-BCR regulators (PTPN6, CD22, CD72, and PKCβ) and substantially reduced BCL6 levels. Ibrutinib inhibited ALL cell migration toward CXCL12 and beneath marrow stromal cells and reduced CD44 expression. CRISPR-Cas9 gene editing revealed that both BTK and B lymphocyte kinase (BLK) are relevant targets of ibrutinib in pre-BCR + ALL. Consequently, in mouse xenograft models of pre-BCR + ALL, ibrutinib treatment significantly prolonged survival. Combination treatment of ibrutinib with dexamethasone or vincristine demonstrated synergistic activity against pre-BCR + ALL. These data corroborate ibrutinib as a promising targeted agent for pre-BCR + ALL and highlight the importance of ibrutinib effects on alternative kinase targets. © 2017 by The American Society of Hematology.

Analysis of thin fractures with GPR: from theory to practice

NASA Astrophysics Data System (ADS)

Arosio, Diego; Zanzi, Luigi; Longoni, Laura; Papini, Monica

2017-04-01

Whenever we perform a GPR survey to investigate a rocky medium, being the ultimate purpose of the survey either to study the stability of a rock slope or to determine the soundness of a quarried rock block, we would like mainly to detect any fracture within the investigated medium and, possibly, to estimate the parameters of the fractures, namely thickness and filling material. In most of the practical cases, rock fracture thicknesses are very small when compared to the wavelength of the electromagnetic radiation generated by the GPR systems. In such cases, fractures are to be considered as thin beds, i.e. two interfaces whose distance is smaller than GPR resolving capability, and the reflected signal is the sum of the electromagnetic reverberation within the bed. According to this, fracture parameters are encoded in the thin bed complex response and in this work we propose a methodology based on deterministic deconvolution to process amplitude and phase information in the frequency domain to estimate fracture parameters. We first present some theoretical aspects related to thin bed response and a sensitivity analysis concerning fracture thickness and filling. Secondly, we deal with GPR datasets collected both during laboratory experiments and in the facilities of quarrying activities. In the lab tests fractures were simulated by placing materials with known electromagnetic parameters and controlled thickness in between two small marble blocks, whereas field GPR surveys were performed on bigger quarried ornamental stone blocks before they were submitted to the cutting process. We show that, with basic pre-processing and the choice of a proper deconvolving signal, results are encouraging although an ambiguity between thickness and filling estimates exists when no a-priori information is available. Results can be improved by performing CMP radar surveys that are able to provide additional information (i.e., variation of thin bed response versus offset) at the expense of acquisition effort and of more complex and tricky pre-processing sequences.

Sensorimotor-Independent Prefrontal Activity During Response Inhibition

PubMed Central

Cai, Weidong; Cannistraci, Christopher J.; Gore, John C.; Leung, Hoi-Chung

2015-01-01

A network of brain regions involving the ventral inferior frontal gyrus/anterior insula (vIFG/AI), presupplementary motor area (pre-SMA) and basal ganglia has been implicated in stopping impulsive, unwanted responses. However, whether this network plays an equal role in response inhibition under different sensorimotor contexts has not been tested systematically. Here, we conducted an fMRI experiment using the stop signal task, a sensorimotor task requiring occasional withholding of the planned response upon the presentation of a stop signal. We manipulated both the sensory modality of the stop signal (visual versus auditory) and the motor response modality (hand versus eye). Results showed that the vIFG/AI and the preSMA along with the right middle frontal gyrus were commonly activated in response inhibition across the various sensorimotor conditions. Our findings provide direct evidence for a common role of these frontal areas, but not striatal areas in response inhibition independent of the sensorimotor contexts. Nevertheless, these three frontal regions exhibited different activation patterns during successful and unsuccessful stopping. Together with the existing evidence, we suggest that the vIFG/AI is involved in the early stages of stopping such as triggering the stop process while the preSMA may play a role in regulating other cortical and subcortical regions involved in stopping. PMID:23798325

VARIATION IN THE PRE-TRANSIT BALMER LINE SIGNAL AROUND THE HOT JUPITER HD 189733B

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

Cauley, P. Wilson; Redfield, Seth; Jensen, Adam G.

As followup to our recent detection of a pre-transit signal around HD 189733 b, we obtained full pre-transit phase coverage of a single planetary transit. The pre-transit signal is again detected in the Balmer lines but with variable strength and timing, suggesting that the bow shock geometry reported in our previous work does not describe the signal from the latest transit. We also demonstrate the use of the Ca ii H and K residual core flux as a proxy for the stellar activity level throughout the transit. A moderate trend is found between the pre-transit absorption signal in the 2013more » data and the Ca ii H flux. This suggests that some of the 2013 pre-transit hydrogen absorption can be attributed to varying stellar activity levels. A very weak correlation is found between the Ca ii H core flux and the Balmer line absorption in the 2015 transit, hinting at a smaller contribution from stellar activity compared to the 2013 transit. We simulate how varying stellar activity levels can produce changes in the Balmer line transmission spectra. These simulations show that the strength of the 2013 and 2015 pre-transit signals can be reproduced by stellar variability. If the pre-transit signature is attributed to circumplanetary material, its evolution in time can be described by accretion clumps spiraling toward the star, although this interpretation has serious limitations. Further high-cadence monitoring at H α is necessary to distinguish between true absorption by transiting material and short-term variations in the stellar activity level.« less

UCMS - A new signal parameter measurement system using digital signal processing techniques. [User Constraint Measurement System

NASA Technical Reports Server (NTRS)

Choi, H. J.; Su, Y. T.

1986-01-01

The User Constraint Measurement System (UCMS) is a hardware/software package developed by NASA Goddard to measure the signal parameter constraints of the user transponder in the TDRSS environment by means of an all-digital signal sampling technique. An account is presently given of the features of UCMS design and of its performance capabilities and applications; attention is given to such important aspects of the system as RF interface parameter definitions, hardware minimization, the emphasis on offline software signal processing, and end-to-end link performance. Applications to the measurement of other signal parameters are also discussed.

Real Time Implementation of an LPC Algorithm. Speech Signal Processing Research at CHI

DTIC Science & Technology

1975-05-01

SIGNAL PROCESSING HARDWARE 2-1 2.1 INTRODUCTION 2-1 2.2 TWO- CHANNEL AUDIO SIGNAL SYSTEM 2-2 2.3 MULTI- CHANNEL AUDIO SIGNAL SYSTEM 2-5 2.3.1... Channel Audio Signal System 2-30 I ii kv^i^ünt«.jfc*. ji .„* ,:-v*. ’.ii. *.. ...... — ■ -,,.,-c-» —ipponp ■^ TOHaBWgBpwiBWgPlpaiPWgW v.«.wN...Messages .... 1-55 1-13. Lost or Out of Order Message 1-56 2-1. Block Diagram of Two- Channel Audio Signal System . . 2-3 2-2. Block Diagram of Audio

Optical fibres in pre-detector signal processing

NASA Astrophysics Data System (ADS)

Flinn, A. R.

The basic form of conventional electro-optic sensors is described. The main drawback of these sensors is their inability to deal with the background radiation which usually accompanies the signal. This 'clutter' limits the sensors performance long before other noise such as 'shot' noise. Pre-detector signal processing using the complex amplitude of the light is introduced as a means to discriminate between the signal and 'clutter'. Further improvements to predetector signal processors can be made by the inclusion of optical fibres allowing radiation to be used with greater efficiency and enabling certain signal processing tasks to be carried out with an ease unequalled by any other method. The theory of optical waveguides and their application in sensors, interferometers, and signal processors is reviewed. Geometrical aspects of the formation of linear and circular interference fringes are described along with temporal and spatial coherence theory and their relationship to Michelson's visibility function. The requirements for efficient coupling of a source into singlemode and multimode fibres are given. We describe interference experiments between beams of light emitted from a few metres of two or more, singlemode or multimode, optical fibres. Fresnel's equation is used to obtain expressions for Fresnel and Fraunhofer diffraction patterns which enable electro-optic (E-0) sensors to be analysed by Fourier optics. Image formation is considered when the aperture plane of an E-0 sensor is illuminated with partially coherent light. This allows sensors to be designed using optical transfer functions which are sensitive to the spatial coherence of the illuminating light. Spatial coherence sensors which use gratings as aperture plane reticles are discussed. By using fibre arrays, spatial coherence processing enables E-0 sensors to discriminate between a spatially coherent source and an incoherent background. The sensors enable the position and wavelength of the source to be determined. Experiments are described which use optical fibre arrays as masks for correlation with spatial distributions of light in image planes of E-0 sensors. Correlations between laser light from different points in a scene is investigated by interfering the light emitted from an array of fibres, placed in the image plane of a sensor, with each other. Temporal signal processing experiments show that the visibility of interference fringes gives information about path differences in a scene or through an optical system. Most E-0 sensors employ wavelength filtering of the detected radiation to improve their discrimination and this is shown to be less selective than temporal coherence filtering which is sensitive to spectral bandwidth. Experiments using fibre interferometers to discriminate between red and blue laser light by their bandwidths are described. In most cases the path difference need only be a few tens of centimetres. We consider spatial and temporal coherence in fibres. We show that high visibility interference fringes can be produced by red and blue laser light transmitted through over 100 metres of singlemode or multimode fibre. The effect of detector size, relative to speckle size, is considered for fringes produced by multimode fibres. The effect of dispersion on the coherence of the light emitted from fibres is considered in terms of correlation and interference between modes. We describe experiments using a spatial light modulator called SIGHT-MOD. The device is used in various systems as a fibre optic switch and as a programmable aperture plane reticle. The contrast of the device is measured using red and green, HeNe, sources. Fourier transform images of patterns on the SIGHT-MOD are obtained and used to demonstrate the geometrical manipulation of images using 2D fibre arrays. Correlation of Fourier transform images of the SIGHT-MOD with 2D fibre arrays is demonstrated.

GLAST Burst Monitor Signal Processing System

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

Bhat, P. Narayana; Briggs, Michael; Connaughton, Valerie

The onboard Data Processing Unit (DPU), designed and built by Southwest Research Institute, performs the high-speed data acquisition for GBM. The analog signals from each of the 14 detectors are digitized by high-speed multichannel analog data acquisition architecture. The streaming digital values resulting from a periodic (period of 104.2 ns) sampling of the analog signal by the individual ADCs are fed to a Field-Programmable Gate Array (FPGA). Real-time Digital Signal Processing (DSP) algorithms within the FPGA implement functions like filtering, thresholding, time delay and pulse height measurement. The spectral data with a 12-bit resolution are formatted according to the commandablemore » look-up-table (LUT) and then sent to the High-Speed Science-Date Bus (HSSDB, speed=1.5 MB/s) to be telemetered to ground. The DSP offers a novel feature of a commandable and constant event deadtime. The ADC non-linearities have been calibrated so that the spectral data can be corrected during analysis. The best temporal resolution is 2 {mu}s for the pre-burst and post-trigger time-tagged events (TTE) data. The time resolution of the binned data types is commandable from 64 msec to 1.024 s for the CTIME data (8 channel spectral resolution) and 1.024 to 32.768 s for the CSPEC data (128 channel spectral resolution). The pulse pile-up effects have been studied by Monte Carlo simulations. For a typical GRB, the possible shift in the Epeak value at high-count rates ({approx}100 kHz) is {approx}1% while the change in the single power-law index could be up to 5%.« less

Characterization and compensation of thermo-elastic instability of SWARM optical bench on micro Advanced Stellar Compass attitude observations

NASA Astrophysics Data System (ADS)

Herceg, M.; Jørgensen, P. S.; Jørgensen, J. L.

2017-08-01

Launched into orbit on November 22, 2013, the Swarm constellation of three satellites precisely measures magnetic signal of the Earth. To ensure the high accuracy of magnetic observation by vector magnetometer (VFM), its inertial attitude is precisely determined by μASC (micro Advanced Stellar Compass). Each of the three Swarm satellites is equipped with three μASC Camera Head Units (CHU) mounted on a common optical bench (OB), which has a purpose of transference of the attitude from the star trackers to the magnetometer measurements. Although substantial pre-launch analyses were made to maximize thermal and mechanical stability of the OB, significant signal with thermal signature is discovered when comparing relative attitude between the three CHU's (Inter Boresight Angle, IBA). These misalignments between CHU's, and consequently geomagnetic reference frame, are found to be correlated with the period of angle between Swarm orbital plane and the Sun (ca. 267 days), which suggests sensitivity of optical bench system on temperature variation. In this paper, we investigate the propagation of thermal effects into the μASC attitude observations and demonstrate how thermally induced attitude variation can be predicted and corrected in the Swarm data processing. The results after applying thermal corrections show decrease in IBA RMS from 6.41 to 2.58″. The model significantly improves attitude determination which, after correction, meets the requirements of Swarm satellite mission. This study demonstrates the importance of the OB pre-launch analysis to ensure minimum thermal gradient on satellite optical system and therefore maximum attitude accuracy.

An IoT-Enabled Stroke Rehabilitation System Based on Smart Wearable Armband and Machine Learning.

PubMed

Yang, Geng; Deng, Jia; Pang, Gaoyang; Zhang, Hao; Li, Jiayi; Deng, Bin; Pang, Zhibo; Xu, Juan; Jiang, Mingzhe; Liljeberg, Pasi; Xie, Haibo; Yang, Huayong

2018-01-01

Surface electromyography signal plays an important role in hand function recovery training. In this paper, an IoT-enabled stroke rehabilitation system was introduced which was based on a smart wearable armband (SWA), machine learning (ML) algorithms, and a 3-D printed dexterous robot hand. User comfort is one of the key issues which should be addressed for wearable devices. The SWA was developed by integrating a low-power and tiny-sized IoT sensing device with textile electrodes, which can measure, pre-process, and wirelessly transmit bio-potential signals. By evenly distributing surface electrodes over user's forearm, drawbacks of classification accuracy poor performance can be mitigated. A new method was put forward to find the optimal feature set. ML algorithms were leveraged to analyze and discriminate features of different hand movements, and their performances were appraised by classification complexity estimating algorithms and principal components analysis. According to the verification results, all nine gestures can be successfully identified with an average accuracy up to 96.20%. In addition, a 3-D printed five-finger robot hand was implemented for hand rehabilitation training purpose. Correspondingly, user's hand movement intentions were extracted and converted into a series of commands which were used to drive motors assembled inside the dexterous robot hand. As a result, the dexterous robot hand can mimic the user's gesture in a real-time manner, which shows the proposed system can be used as a training tool to facilitate rehabilitation process for the patients after stroke.

Technology in rural transportation. Simple solution #11, Emergency vehicle traffic signal pre-emption

DOT National Transportation Integrated Search

1997-01-01

This application was identified as a promising rural Intelligent Transportation Systems (ITS) solution under a project sponsored by the Federal Highway Administration (FHWA) and the ENTERPRISE program. This summary describes the solution as well as o...

An open-loop system design for deep space signal processing applications

NASA Astrophysics Data System (ADS)

Tang, Jifei; Xia, Lanhua; Mahapatra, Rabi

2018-06-01

A novel open-loop system design with high performance is proposed for space positioning and navigation signal processing. Divided by functions, the system has four modules, bandwidth selectable data recorder, narrowband signal analyzer, time-delay difference of arrival estimator and ANFIS supplement processor. A hardware-software co-design approach is made to accelerate computing capability and improve system efficiency. Embedded with the proposed signal processing algorithms, the designed system is capable of handling tasks with high accuracy over long period of continuous measurements. The experiment results show the Doppler frequency tracking root mean square error during 3 h observation is 0.0128 Hz, while the TDOA residue analysis in correlation power spectrum is 0.1166 rad.

Real-Time, General-Purpose, High-Speed Signal Processing Systems for Underwater Research. Proceedings of a Working Level Conference held at Supreme Allied Commander, Atlantic Anti-Submarine Warfare Research Center (SACLANTCEN) on 18-21 September 1979. Part 2. Sessions IV to VI.

DTIC Science & Technology

1979-12-01

ACTIVATED, SYSTEM OPERATION AND TESTING MASCOT PROVIDES: 1. SYSTEM BUILD SOFTWARE COMPILE-TIME CHECKS,a. 2. RUN-TIME SUPERVISOR KERNEL, 3, MONITOR AND...p AD-AOBI 851 SACLANT ASW RESEARCH CENTRE LA SPEZIA 11ITALY) F/B 1711 REAL-TIME, GENERAL-PURPOSE, HIGH-SPEED SIGNAL PROCESSING SYSTEM -- ETC (U) DEC 79...Table of Contents Table of Contents (Cont’d) Page Signal processing language and operating system (w) 23-1 to 23-12 by S. Weinstein A modular signal

The application of digital signal processing techniques to a teleoperator radar system

NASA Technical Reports Server (NTRS)

Pujol, A.

1982-01-01

A digital signal processing system was studied for the determination of the spectral frequency distribution of echo signals from a teleoperator radar system. The system consisted of a sample and hold circuit, an analog to digital converter, a digital filter, and a Fast Fourier Transform. The system is interfaced to a 16 bit microprocessor. The microprocessor is programmed to control the complete digital signal processing. The digital filtering and Fast Fourier Transform functions are implemented by a S2815 digital filter/utility peripheral chip and a S2814A Fast Fourier Transform chip. The S2815 initially simulates a low-pass Butterworth filter with later expansion to complete filter circuit (bandpass and highpass) synthesizing.

Optimal spacing between transmitting and receiving optical fibres in reflectance pulse oximetry

NASA Astrophysics Data System (ADS)

Hickey, M.; Kyriacou, P. A.

2007-10-01

Splanchnic ischaemia can ultimately lead to cellular hypoxia and necrosis, and may well contribute to the development of multiple organ failures and increased mortality. Therefore, it is of utmost importance to monitor abdominal organ blood oxygen saturation (SpO2). Pulse oximetry has been widely accepted as a reliable method for monitoring oxygen saturation of arterial blood. Animal studies have also shown it to be effective in the monitoring of blood oxygen saturation in the splanchnic region. However, commercially available pulse oximeter probes are not suitable for the continuous assessment of SpO2 in the splanchnic region. Therefore, there is a need for a new sensor technology that will allow the continuous measurement of SpO2 in the splanchnic area pre-operatively, operatively and post-operatively. For this purpose, a new fibre optic sensor and processing system utilising the principle of reflectance pulse oximetry has been developed. The accuracy in the estimation of SpO2 in pulse oximetry depends on the quality and amplitude of the photoplethysmographic (PPG) signal and for this reason an experimental procedure was carried out to examine the effect of the source-detector separation distance on the acquired PPG signals, and to ultimately select an optimal separation for the final design of the fibre-optic probe. PPG signals were obtained from the finger for different separation distances between the emitting and detecting fibres. Good quality PPG signals with large amplitudes and high signal-to-noise ratio were detected in the range of 3mm to 6mm. At separation distances between 1mm and 2mm, PPG signals were erratic with no resemblance to a conventional PPG signal. At separation distances greater than 6mm, the amplitudes of PPG signals were very small and not appropriate for processing. This investigation indicates the suitability of optical fibres as a new pulse oximetry sensor for estimating blood oxygen saturation (SpO2) in the splanchnic region.

Real-time holographic surveillance system

DOEpatents

Collins, H. Dale; McMakin, Douglas L.; Hall, Thomas E.; Gribble, R. Parks

1995-01-01

A holographic surveillance system including means for generating electromagnetic waves; means for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; means for receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; means for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and means for displaying the processed information to determine nature of the target. The means for processing the electrical signals includes means for converting analog signals to digital signals followed by a computer means to apply a backward wave algorithm.

Cost-effective TCM-based WDM-PON for highly asymmetric traffic conditions.

PubMed

Lee, Danbi; Kwon, Won-Bae; Chae, Chang-Joon; Park, Chang-Soo

2015-11-16

A time compression multiplexing (TCM)-based wavelength division multiplexing passive optical network (WDM-PON) using a reflective semiconductor optical amplifier (RSOA) is proposed, and its feasibility is experimentally demonstrated. In the proposed system, the RSOA pre-amplifies a 10 Gb/s downstream signal and modulates the RSOA output, wavelength-locked to the downstream signal, with a 1.25 Gb/s upstream signal simultaneously. The sensitivity of the downstream signal is improved by about 3 dB through the RSOA. The downstream and upstream signals have power penalties of about 0.1 dB and 1.1 dB, respectively, at bit error rates (BERs) of 10(-9) after 20 km transmission.

MicroRNA-24 promotes 3T3-L1 adipocyte differentiation by directly targeting the MAPK7 signaling

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

Jin, Min, E-mail: min_jin@zju.edu.cn; Wu, Yutao; Wang, Jing

Over the past years, MicroRNAs (miRNAs) act as a vital role in harmony with gene regulation and maintaining cellular homeostasis. It is well testified that miRNAshave been involved in numerous physiological and pathological processes, including embryogenesis, cell fate decision, and cellular differentiation. Adipogenesis is an organized process of cellular differentiation by which pre-adipocytes differentiate towards mature adipocytes, and it is tightly modulated by a series of transcription factors such as peroxisome proliferator-activated receptor γ (PPAR-γ) and sterol regulatory-element binding proteins 1 (SREBP1). However, the molecular mechanisms underlying the connection between miRNAs and adipogenesis-related transcription factors remain obscure. In this study,more » we unveiled that miR- 24 was remarkably upregulated during 3T3-L1 adipogenesis. Overexpression of miR-24 significantly promoted 3T3-L1 adipogenesis, as evidenced by its ability to increase the expression of PPAR-γ and SREBP1, lipid droplet formation and triglyceride (TG) accumulation. Furthermore, we found that neither ectopic expression of miR-24nor miR-24 inhibitor affect cell proliferation and cell cycle progression. Finally, we demonstrated that miR-24 plays the modulational role by directly repressing MAPK7, a key number in the MAPK signaling pathway. These data indicate that miR-24 is a novel positive regulator of adipocyte differentiation by targeting MAPK7, which provides new insights into the molecular mechanism of miRNA-mediated cellular differentiation. -- Highlights: •We firstly found miR-24 was upregulated in 3T3-L1 pre-adipocytes differentiation. •miR-24 promoted 3T3-L1 pre-adipocytes differentiation while silencing the expression of miR-24 had an opposite function. •miR-24 regulated 3T3-L1 differentiation by directly targeting MAPK7 signaling pathway. •miR-24did not affect 3T3-L1 pre-adipocytes cellular proliferation.« less

Development of wireless brain computer interface with embedded multitask scheduling and its application on real-time driver's drowsiness detection and warning.

PubMed

Lin, Chin-Teng; Chen, Yu-Chieh; Huang, Teng-Yi; Chiu, Tien-Ting; Ko, Li-Wei; Liang, Sheng-Fu; Hsieh, Hung-Yi; Hsu, Shang-Hwa; Duann, Jeng-Ren

2008-05-01

Biomedical signal monitoring systems have been rapidly advanced with electronic and information technologies in recent years. However, most of the existing physiological signal monitoring systems can only record the signals without the capability of automatic analysis. In this paper, we proposed a novel brain-computer interface (BCI) system that can acquire and analyze electroencephalogram (EEG) signals in real-time to monitor human physiological as well as cognitive states, and, in turn, provide warning signals to the users when needed. The BCI system consists of a four-channel biosignal acquisition/amplification module, a wireless transmission module, a dual-core signal processing unit, and a host system for display and storage. The embedded dual-core processing system with multitask scheduling capability was proposed to acquire and process the input EEG signals in real time. In addition, the wireless transmission module, which eliminates the inconvenience of wiring, can be switched between radio frequency (RF) and Bluetooth according to the transmission distance. Finally, the real-time EEG-based drowsiness monitoring and warning algorithms were implemented and integrated into the system to close the loop of the BCI system. The practical online testing demonstrates the feasibility of using the proposed system with the ability of real-time processing, automatic analysis, and online warning feedback in real-world operation and living environments.

Gas turbine engine control system

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

Idelchik, M.S.

1991-02-19

This paper describes a method for controlling a gas turbine engine. It includes receiving an error signal and processing the error signal to form a primary control signal; receiving at least one anticipatory demand signal and processing the signal to form an anticipatory fuel control signal.

Remembered or Forgotten?—An EEG-Based Computational Prediction Approach

PubMed Central

Sun, Xuyun; Qian, Cunle; Chen, Zhongqin; Wu, Zhaohui; Luo, Benyan; Pan, Gang

2016-01-01

Prediction of memory performance (remembered or forgotten) has various potential applications not only for knowledge learning but also for disease diagnosis. Recently, subsequent memory effects (SMEs)—the statistical differences in electroencephalography (EEG) signals before or during learning between subsequently remembered and forgotten events—have been found. This finding indicates that EEG signals convey the information relevant to memory performance. In this paper, based on SMEs we propose a computational approach to predict memory performance of an event from EEG signals. We devise a convolutional neural network for EEG, called ConvEEGNN, to predict subsequently remembered and forgotten events from EEG recorded during memory process. With the ConvEEGNN, prediction of memory performance can be achieved by integrating two main stages: feature extraction and classification. To verify the proposed approach, we employ an auditory memory task to collect EEG signals from scalp electrodes. For ConvEEGNN, the average prediction accuracy was 72.07% by using EEG data from pre-stimulus and during-stimulus periods, outperforming other approaches. It was observed that signals from pre-stimulus period and those from during-stimulus period had comparable contributions to memory performance. Furthermore, the connection weights of ConvEEGNN network can reveal prominent channels, which are consistent with the distribution of SME studied previously. PMID:27973531

Estimation of source location and ground impedance using a hybrid multiple signal classification and Levenberg-Marquardt approach

NASA Astrophysics Data System (ADS)

Tam, Kai-Chung; Lau, Siu-Kit; Tang, Shiu-Keung

2016-07-01

A microphone array signal processing method for locating a stationary point source over a locally reactive ground and for estimating ground impedance is examined in detail in the present study. A non-linear least square approach using the Levenberg-Marquardt method is proposed to overcome the problem of unknown ground impedance. The multiple signal classification method (MUSIC) is used to give the initial estimation of the source location, while the technique of forward backward spatial smoothing is adopted as a pre-processer of the source localization to minimize the effects of source coherence. The accuracy and robustness of the proposed signal processing method are examined. Results show that source localization in the horizontal direction by MUSIC is satisfactory. However, source coherence reduces drastically the accuracy in estimating the source height. The further application of Levenberg-Marquardt method with the results from MUSIC as the initial inputs improves significantly the accuracy of source height estimation. The present proposed method provides effective and robust estimation of the ground surface impedance.

A portable device for rapid nondestructive detection of fresh meat quality

NASA Astrophysics Data System (ADS)

Lin, Wan; Peng, Yankun

2014-05-01

Quality attributes of fresh meat influence nutritional value and consumers' purchasing power. In order to meet the demand of inspection department for portable device, a rapid and nondestructive detection device for fresh meat quality based on ARM (Advanced RISC Machines) processor and VIS/NIR technology was designed. Working principal, hardware composition, software system and functional test were introduced. Hardware system consisted of ARM processing unit, light source unit, detection probe unit, spectral data acquisition unit, LCD (Liquid Crystal Display) touch screen display unit, power unit and the cooling unit. Linux operating system and quality parameters acquisition processing application were designed. This system has realized collecting spectral signal, storing, displaying and processing as integration with the weight of 3.5 kg. 40 pieces of beef were used in experiment to validate the stability and reliability. The results indicated that prediction model developed using PLSR method using SNV as pre-processing method had good performance, with the correlation coefficient of 0.90 and root mean square error of 1.56 for validation set for L*, 0.95 and 1.74 for a*，0.94 and 0.59 for b*, 0.88 and 0.13 for pH, 0.79 and 12.46 for tenderness, 0.89 and 0.91 for water content, respectively. The experimental result shows that this device can be a useful tool for detecting quality of meat.

A Novel Feature Extraction Method for Monitoring (Vehicular) Fuel Storage System Leaks

DTIC Science & Technology

2014-10-02

gives a continuous output of the DPDF with predefined partitions . Resolution a DPDF is dependent on pre-determined signal range and number of... partitions within that range. Conceptually, proposed implementation is identical to the creation of a histogram with a moving data windown given some...window. The crisp partitions within specified signal range act as “competing and possible” scenarios or alternatives where we impose a “winner takes all

Surveillance of Space - Optimal Use of Complementary Sensors for Maximum Efficiency

DTIC Science & Technology

2006-04-01

as track - before - detect [4] have been shown to allow improved sensitivity. This technique employs fast running algorithms and computing power to pre...Multifunction Radar” IEEE Signal Processing Magazine, January 2006. [4] Wallace W R “The Use of Track - Before - Detect in Pulse-Doppler Radar” IEE 490, Radar

Development of automatic pre-tracking system for fillet weld based on laser trigonometry

NASA Astrophysics Data System (ADS)

Shen, Xiaoqin; Yu, Fusheng

2005-01-01

In this paper, an automatic fillet weld pre-tracking system for welding the work piece of lorry back boards with several bend in haul automobile is developed basing on laser trigonometry. The optical measuring head based on laser-PSD trigonometry is used as position sensor. It is placed in front of the traveling direction of welding wire to get the distances from welding wire to the two side boards of the welding lines, upper board and bottom board of the fillet weld respectively. A chip of AT89S52 is used as the micro controller in this system. The AC servomotors, ball-screws and straight guide rails constitute the sliding table to take welding wire move. The laser-PSD sensors pass through the vertical board, upper board and bottom board of the fillet weld when welding wire moves and then get the distance. The laser-PSD sensors output the analog signals. After A/D conversion, the digital signal is input into AT89S52 and calculated. Then the information of the position and lateral deviation of the welding wire when welding a certain position are gotten to control welding wires. So the weld pre-tracking for welding the work piece with long distance and large bend in haul automobile is realized. The position information is input into EEPROM to be saved for short time after handled by AT89S52. The information is as the welding position information as well as the speed adjusting data of the welding wire when it welds the several bend of the work piece. The practice indicates that this system has high pre-tracking precision, good anti-disturb ability, excellent reliability, easy operating ability and good adaptability to the field of production.

Cutting edge: rescue of pre-TCR but not mature TCR signaling in mice expressing membrane-targeted SLP-76.

PubMed

Bezman, Natalie A; Baker, Rebecca G; Lenox, Laurie E; Jordan, Martha S; Koretzky, Gary A

2009-05-01

SLP-76 (Src homology 2 domain-containing leukocyte phosphoprotein of 76 kDa) organizes signaling from immunoreceptors, including the platelet collagen receptor, the pre-TCR, and the TCR, and is required for T cell development. In this study we examine a mouse in which wild-type SLP-76 is replaced with a mutant constitutively targeted to the cell membrane. Membrane-targeted SLP-76 (MTS) supports ITAM signaling in platelets and from the pre-TCR. Signaling from the mature TCR, however, is defective in MTS thymocytes, resulting in failed T cell differentiation. Defective thymic selection by MTS is not rescued by a SLP-76 mutant whose localization is restricted to the cytosol. Thus, fixed localization of SLP-76 reveals differential requirements for the subcellular localization of signaling complexes downstream of the pre-TCR vs mature TCR.

Brain signaling and behavioral responses induced by exposure to (56)Fe-particle radiation

NASA Technical Reports Server (NTRS)

Denisova, N. A.; Shukitt-Hale, B.; Rabin, B. M.; Joseph, J. A.

2002-01-01

Previous experiments have demonstrated that exposure to 56Fe-particle irradiation (1.5 Gy, 1 GeV) produced aging-like accelerations in neuronal and behavioral deficits. Astronauts on long-term space flights will be exposed to similar heavy-particle radiations that might have similar deleterious effects on neuronal signaling and cognitive behavior. Therefore, the present study evaluated whether radiation-induced spatial learning and memory behavioral deficits are associated with region-specific brain signaling deficits by measuring signaling molecules previously found to be essential for behavior [pre-synaptic vesicle proteins, synaptobrevin and synaptophysin, and protein kinases, calcium-dependent PRKCs (also known as PKCs) and PRKA (PRKA RIIbeta)]. The results demonstrated a significant radiation-induced increase in reference memory errors. The increases in reference memory errors were significantly negatively correlated with striatal synaptobrevin and frontal cortical synaptophysin expression. Both synaptophysin and synaptobrevin are synaptic vesicle proteins that are important in cognition. Striatal PRKA, a memory signaling molecule, was also significantly negatively correlated with reference memory errors. Overall, our findings suggest that radiation-induced pre-synaptic facilitation may contribute to some previously reported radiation-induced decrease in striatal dopamine release and for the disruption of the central dopaminergic system integrity and dopamine-mediated behavior.

Brain signaling and behavioral responses induced by exposure to (56)Fe-particle radiation.

PubMed

Denisova, N A; Shukitt-Hale, B; Rabin, B M; Joseph, J A

2002-12-01

Previous experiments have demonstrated that exposure to 56Fe-particle irradiation (1.5 Gy, 1 GeV) produced aging-like accelerations in neuronal and behavioral deficits. Astronauts on long-term space flights will be exposed to similar heavy-particle radiations that might have similar deleterious effects on neuronal signaling and cognitive behavior. Therefore, the present study evaluated whether radiation-induced spatial learning and memory behavioral deficits are associated with region-specific brain signaling deficits by measuring signaling molecules previously found to be essential for behavior [pre-synaptic vesicle proteins, synaptobrevin and synaptophysin, and protein kinases, calcium-dependent PRKCs (also known as PKCs) and PRKA (PRKA RIIbeta)]. The results demonstrated a significant radiation-induced increase in reference memory errors. The increases in reference memory errors were significantly negatively correlated with striatal synaptobrevin and frontal cortical synaptophysin expression. Both synaptophysin and synaptobrevin are synaptic vesicle proteins that are important in cognition. Striatal PRKA, a memory signaling molecule, was also significantly negatively correlated with reference memory errors. Overall, our findings suggest that radiation-induced pre-synaptic facilitation may contribute to some previously reported radiation-induced decrease in striatal dopamine release and for the disruption of the central dopaminergic system integrity and dopamine-mediated behavior.

Frequency domain laser velocimeter signal processor: A new signal processing scheme

NASA Technical Reports Server (NTRS)

Meyers, James F.; Clemmons, James I., Jr.

1987-01-01

A new scheme for processing signals from laser velocimeter systems is described. The technique utilizes the capabilities of advanced digital electronics to yield a smart instrument that is able to configure itself, based on the characteristics of the input signals, for optimum measurement accuracy. The signal processor is composed of a high-speed 2-bit transient recorder for signal capture and a combination of adaptive digital filters with energy and/or zero crossing detection signal processing. The system is designed to accept signals with frequencies up to 100 MHz with standard deviations up to 20 percent of the average signal frequency. Results from comparative simulation studies indicate measurement accuracies 2.5 times better than with a high-speed burst counter, from signals with as few as 150 photons per burst.

Genetically modified whole-cell bioreporters for environmental assessment

PubMed Central

Xu, Tingting; Close, Dan M.; Sayler, Gary S.; Ripp, Steven

2015-01-01

Living whole-cell bioreporters serve as environmental biosentinels that survey their ecosystems for harmful pollutants and chemical toxicants, and in the process act as human and other higher animal proxies to pre-alert for unfavorable, damaging, or toxic conditions. Endowed with bioluminescent, fluorescent, or colorimetric signaling elements, bioreporters can provide a fast, easily measured link to chemical contaminant presence, bioavailability, and toxicity relative to a living system. Though well tested in the confines of the laboratory, real-world applications of bioreporters are limited. In this review, we will consider bioreporter technologies that have evolved from the laboratory towards true environmental applications, and discuss their merits as well as crucial advancements that still require adoption for more widespread utilization. Although the vast majority of environmental monitoring strategies rely upon bioreporters constructed from bacteria, we will also examine environmental biosensing through the use of less conventional eukaryotic-based bioreporters, whose chemical signaling capacity facilitates a more human-relevant link to toxicity and health-related consequences. PMID:26594130

Slit/Robo1 signaling regulates neural tube development by balancing neuroepithelial cell proliferation and differentiation

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

Wang, Guang; Li, Yan; Wang, Xiao-yu

2013-05-01

Formation of the neural tube is the morphological hallmark for development of the embryonic central nervous system (CNS). Therefore, neural tube development is a crucial step in the neurulation process. Slit/Robo signaling was initially identified as a chemo-repellent that regulated axon growth cone elongation, but its role in controlling neural tube development is currently unknown. To address this issue, we investigated Slit/Robo1 signaling in the development of chick neCollege of Life Sciences Biocentre, University of Dundee, Dundee DD1 5EH, UKural tube and transgenic mice over-expressing Slit2. We disrupted Slit/Robo1 signaling by injecting R5 monoclonal antibodies into HH10 neural tubes tomore » block the Robo1 receptor. This inhibited the normal development of the ventral body curvature and caused the spinal cord to curl up into a S-shape. Next, Slit/Robo1 signaling on one half-side of the chick embryo neural tube was disturbed by electroporation in ovo. We found that the morphology of the neural tube was dramatically abnormal after we interfered with Slit/Robo1 signaling. Furthermore, we established that silencing Robo1 inhibited cell proliferation while over-expressing Robo1 enhanced cell proliferation. We also investigated the effects of altering Slit/Robo1 expression on Sonic Hedgehog (Shh) and Pax7 expression in the developing neural tube. We demonstrated that over-expressing Robo1 down-regulated Shh expression in the ventral neural tube and resulted in the production of fewer HNK-1{sup +} migrating neural crest cells (NCCs). In addition, Robo1 over-expression enhanced Pax7 expression in the dorsal neural tube and increased the number of Slug{sup +} pre-migratory NCCs. Conversely, silencing Robo1 expression resulted in an enhanced Shh expression and more HNK-1{sup +} migrating NCCs but reduced Pax7 expression and fewer Slug{sup +} pre-migratory NCCs were observed. In conclusion, we propose that Slit/Robo1 signaling is involved in regulating neural tube development by tightly coordinating cell proliferation and differentiation during neurulation. - Highlights: ► The role of Slit/Robo1 signaling was investigated with chick and mouse models. ► Disturbance of Slit/Robo1 signaling resulted in neural tube defects. ► Slit/Robo1 signaling regulated the proliferation of neural tube cells. ► Slit/Robo1 signaling modulated the differentiation of neural tube cells. ► Slit/Robo1 signaling balanced the proliferation and differentiation of neural tube.« less

An efficient magnetron transmitter for superconducting accelerators

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

Kazakevich, G.; Lebedev, V.; Yakovlev, V.

A concept of a highly-efficient high-power magnetron transmitter allowing wide-band phase and the mid-frequency power control at the frequency of the locking signal is proposed. The proposal is aimed for powering Superconducting RF (SRF) cavities of intensity-frontier accelerators. The transmitter is intended to operate with phase and amplitude control feedback loops allowing suppression of microphonics and beam loading in the SRF cavities. The concept utilizes injectionlocked magnetrons controlled in phase by the locking signal supplied by a feedback system. The injection-locking signal pre-excites the magnetron and allows its operation below the critical voltage. This realizes control of the magnetron powermore » in a wide range by control of the magnetron current. Pre-excitation of the magnetron by the locking signal provides an output power range up to 10 dB. Experimental studies were carried out with 2.45 GHz, 1 kW, CW magnetrons. They demonstrated stable operation of the magnetrons and power control at a low noise level. In conclusion, an analysis of the kinetics of the drifting charge in the drift approximation substantiates the concept and the experimental results.« less

Distributed sensing signal analysis of deformable plate/membrane mirrors

NASA Astrophysics Data System (ADS)

Lu, Yifan; Yue, Honghao; Deng, Zongquan; Tzou, Hornsen

2017-11-01

Deformable optical mirrors usually play key roles in aerospace and optical structural systems applied to space telescopes, radars, solar collectors, communication antennas, etc. Limited by the payload capacity of current launch vehicles, the deformable mirrors should be lightweight and are generally made of ultra-thin plates or even membranes. These plate/membrane mirrors are susceptible to external excitations and this may lead to surface inaccuracy and jeopardize relevant working performance. In order to investigate the modal vibration characteristics of the mirror, a piezoelectric layer is fully laminated on its non-reflective side to serve as sensors. The piezoelectric layer is segmented into infinitesimal elements so that microscopic distributed sensing signals can be explored. In this paper, the deformable mirror is modeled as a pre-tensioned plate and membrane respectively and sensing signal distributions of the two models are compared. Different pre-tensioning forces are also applied to reveal the tension effects on the mode shape and sensing signals of the mirror. Analytical results in this study could be used as guideline of optimal sensor/actuator placement for deformable space mirrors.

An efficient magnetron transmitter for superconducting accelerators

DOE PAGES

Kazakevich, G.; Lebedev, V.; Yakovlev, V.; ...

2016-09-22

A concept of a highly-efficient high-power magnetron transmitter allowing wide-band phase and the mid-frequency power control at the frequency of the locking signal is proposed. The proposal is aimed for powering Superconducting RF (SRF) cavities of intensity-frontier accelerators. The transmitter is intended to operate with phase and amplitude control feedback loops allowing suppression of microphonics and beam loading in the SRF cavities. The concept utilizes injectionlocked magnetrons controlled in phase by the locking signal supplied by a feedback system. The injection-locking signal pre-excites the magnetron and allows its operation below the critical voltage. This realizes control of the magnetron powermore » in a wide range by control of the magnetron current. Pre-excitation of the magnetron by the locking signal provides an output power range up to 10 dB. Experimental studies were carried out with 2.45 GHz, 1 kW, CW magnetrons. They demonstrated stable operation of the magnetrons and power control at a low noise level. In conclusion, an analysis of the kinetics of the drifting charge in the drift approximation substantiates the concept and the experimental results.« less

Signaling Device for the Pre-Emergency State of the Elements of the Rotating Assembly of Steam Compressor of Desalination Plant

NASA Astrophysics Data System (ADS)

Danilin, A. I.; Chernyavskiy, A. Zh; Danilin, S. A.; Blagin, E. V.

2018-01-01

This article deals with non-contact exploitation control method based on the treatment of the radio wave signal reflected from controlled gear teeth and its advantages in comparison with traditional methods of gear teeth control. Justification of necessity to use such control method during multiplier gears condition determination during its exploitation is given. Also this article deals with influence of different types of gear wear on typical information parameters of analyzed signals. Disadvantages of the method which are the impossibility of determination of certain types of wear are also taken into account. Certain stages of the development of mathematical model for interaction of first converter with controlled surface. Suggested mathematical model uses only the laws of geometric optics without taking wave processes into account but considering first converter direction diagram influence during its interaction with controlled surface. Structural scheme of developed experimental system for gears teeth condition control for steam compressor. Operation of the experimental system of gear control is given on the base of structural scheme. Core of the developed device is microcontroller STM32 which treat the information received from the sensors as well as connection with computer. Certain elements of the experimental control system as well as its components are described separately. Photos of experimental unit for control for control method development in laboratory conditions are presented. Design of the first converter is given in short.

A Novel Signal Modeling Approach for Classification of Seizure and Seizure-Free EEG Signals.

PubMed

Gupta, Anubha; Singh, Pushpendra; Karlekar, Mandar

2018-05-01

This paper presents a signal modeling-based new methodology of automatic seizure detection in EEG signals. The proposed method consists of three stages. First, a multirate filterbank structure is proposed that is constructed using the basis vectors of discrete cosine transform. The proposed filterbank decomposes EEG signals into its respective brain rhythms: delta, theta, alpha, beta, and gamma. Second, these brain rhythms are statistically modeled with the class of self-similar Gaussian random processes, namely, fractional Brownian motion and fractional Gaussian noises. The statistics of these processes are modeled using a single parameter called the Hurst exponent. In the last stage, the value of Hurst exponent and autoregressive moving average parameters are used as features to design a binary support vector machine classifier to classify pre-ictal, inter-ictal (epileptic with seizure free interval), and ictal (seizure) EEG segments. The performance of the classifier is assessed via extensive analysis on two widely used data set and is observed to provide good accuracy on both the data set. Thus, this paper proposes a novel signal model for EEG data that best captures the attributes of these signals and hence, allows to boost the classification accuracy of seizure and seizure-free epochs.

Targeting high value metals in lithium-ion battery recycling via shredding and size-based separation.

PubMed

Wang, Xue; Gaustad, Gabrielle; Babbitt, Callie W

2016-05-01

Development of lithium-ion battery recycling systems is a current focus of much research; however, significant research remains to optimize the process. One key area not studied is the utilization of mechanical pre-recycling steps to improve overall yield. This work proposes a pre-recycling process, including mechanical shredding and size-based sorting steps, with the goal of potential future scale-up to the industrial level. This pre-recycling process aims to achieve material segregation with a focus on the metallic portion and provide clear targets for subsequent recycling processes. The results show that contained metallic materials can be segregated into different size fractions at different levels. For example, for lithium cobalt oxide batteries, cobalt content has been improved from 35% by weight in the metallic portion before this pre-recycling process to 82% in the ultrafine (<0.5mm) fraction and to 68% in the fine (0.5-1mm) fraction, and been excluded in the larger pieces (>6mm). However, size fractions across multiple battery chemistries showed significant variability in material concentration. This finding indicates that sorting by cathode before pre-treatment could reduce the uncertainty of input materials and therefore improve the purity of output streams. Thus, battery labeling systems may be an important step towards implementation of any pre-recycling process. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fermilab Recycler Ring BPM Upgrade Based on Digital Receiver Technology

NASA Astrophysics Data System (ADS)

Webber, R.; Crisp, J.; Prieto, P.; Voy, D.; Briegel, C.; McClure, C.; West, R.; Pordes, S.; Mengel, M.

2004-11-01

Electronics for the 237 BPMs in the Fermilab Recycler Ring have been upgraded from a log-amplifier based system to a commercially produced digitizer-digital down converter based system. The hardware consists of a pre-amplifier connected to a split-plate BPM, an analog differential receiver-filter module and an 8-channel 80-MHz digital down converter VME board. The system produces position and intensity with a dynamic range of 30 dB and a resolution of ±10 microns. The position measurements are made on 2.5-MHz bunched beam and barrier buckets of the un-bunched beam. The digital receiver system operates in one of six different signal processing modes that include 2.5-MHz average, 2.5-MHz bunch-by-bunch, 2.5-MHz narrow band, unbunched average, un-bunched head/tail and 89-kHz narrow band. Receiver data is acquired on any of up to sixteen clock events related to Recycler beam transfers and other machine activities. Data from the digital receiver board are transferred to the front-end CPU for position and intensity computation on an on-demand basis through the VME bus. Data buffers are maintained for each of the acquisition events and support flash, closed orbit and turn-by-turn measurements. A calibration system provides evaluation of the BPM signal path and application programs.

CATAVIÑA: new infrared camera for OAN-SPM

NASA Astrophysics Data System (ADS)

Iriarte, Arturo; Cruz-González, Irene; Martínez, Luis A.; Tinoco, Silvio; Lara, Gerardo; Ruiz, Elfego; Sohn, Erika; Bernal, Abel; Angeles, Fernando; Moreno, Arturo; Murillo, Francisco; Langarica, Rosalía; Luna, Esteban; Salas, Luis; Cajero, Vicente

2006-06-01

CATAVIÑA is a near-infrared camera system to be operated in conjunction with the existing multi-purpose nearinfrared optical bench "CAMALEON" in OAN-SPM. Observing modes include direct imaging, spectroscopy, Fabry- Perot interferometry and polarimetry. This contribution focuses on the optomechanics and detector controller description of CATAVIÑA, which is planned to start operating later in 2006. The camera consists of an 8 inch LN2 dewar containing a 10 filter carousel, a radiation baffle and the detector circuit board mount. The system is based on a Rockwell 1024x1024 HgCdTe (HAWAII-I) FPA, operating in the 1 to 2.5 micron window. The detector controller/readout system was designed and developed at UNAM Instituto de Astronomia. It is based on five Texas Instruments DSK digital signal processor (DSP) modules. One module generates the detector and ADC-system control, while the remaining four are in charge of the acquisition of each of the detector's quadrants. Each DSP has a built-in expanded memory module in order to store more than one image. The detector read-out and signal driver subsystems are mounted onto the dewar in a "back-pack" fashion, each containing four independent pre-amplifiers, converters and signal drivers, that communicate through fiber optics with their respective DSPs. This system has the possibility of programming the offset input voltage and converter gain. The controller software architecture is based on a client/server model. The client sends commands through the TCP/IP protocol and acquires the image. The server consists of a microcomputer with an embedded Linux operating system, which runs the main program that receives the user commands and interacts with the timing and acquisition DSPs. The observer's interface allows for several readout and image processing modes.

A miniature electronic nose system based on an MWNT-polymer microsensor array and a low-power signal-processing chip.

PubMed

Chiu, Shih-Wen; Wu, Hsiang-Chiu; Chou, Ting-I; Chen, Hsin; Tang, Kea-Tiong

2014-06-01

This article introduces a power-efficient, miniature electronic nose (e-nose) system. The e-nose system primarily comprises two self-developed chips, a multiple-walled carbon nanotube (MWNT)-polymer based microsensor array, and a low-power signal-processing chip. The microsensor array was fabricated on a silicon wafer by using standard photolithography technology. The microsensor array comprised eight interdigitated electrodes surrounded by SU-8 "walls," which restrained the material-solvent liquid in a defined area of 650 × 760 μm(2). To achieve a reliable sensor-manufacturing process, we used a two-layer deposition method, coating the MWNTs and polymer film as the first and second layers, respectively. The low-power signal-processing chip included array data acquisition circuits and a signal-processing core. The MWNT-polymer microsensor array can directly connect with array data acquisition circuits, which comprise sensor interface circuitry and an analog-to-digital converter; the signal-processing core consists of memory and a microprocessor. The core executes the program, classifying the odor data received from the array data acquisition circuits. The low-power signal-processing chip was designed and fabricated using the Taiwan Semiconductor Manufacturing Company 0.18-μm 1P6M standard complementary metal oxide semiconductor process. The chip consumes only 1.05 mW of power at supply voltages of 1 and 1.8 V for the array data acquisition circuits and the signal-processing core, respectively. The miniature e-nose system, which used a microsensor array, a low-power signal-processing chip, and an embedded k-nearest-neighbor-based pattern recognition algorithm, was developed as a prototype that successfully recognized the complex odors of tincture, sorghum wine, sake, whisky, and vodka.

Compressed sensing: Radar signal detection and parameter measurement for EW applications

NASA Astrophysics Data System (ADS)

Rao, M. Sreenivasa; Naik, K. Krishna; Reddy, K. Maheshwara

2016-09-01

State of the art system development is very much required for UAVs (Unmanned Aerial Vehicle) and other airborne applications, where miniature, lightweight and low-power specifications are essential. Currently, the airborne Electronic Warfare (EW) systems are developed with digital receiver technology using Nyquist sampling. The detection of radar signals and parameter measurement is a necessary requirement in EW digital receivers. The Random Modulator Pre-Integrator (RMPI) can be used for matched detection of signals using smashed filter. RMPI hardware eliminates the high sampling rate analog to digital computer and reduces the number of samples using random sampling and detection of sparse orthonormal basis vectors. RMPI explore the structural and geometrical properties of the signal apart from traditional time and frequency domain analysis for improved detection. The concept has been proved with the help of MATLAB and LabVIEW simulations.

Induction of SA-signaling pathway and ethylene biosynthesis in Trichoderma harzianum-treated tomato plants after infection of the root-knot nematode Meloidogyne incognita.

PubMed

Leonetti, Paola; Zonno, Maria Chiara; Molinari, Sergio; Altomare, Claudio

2017-04-01

Salicylic acid-signaling pathway and ethylene biosynthesis were induced in tomato treated with Trichoderma harzianum when infected by root-knot nematodes and limited the infection by activation of SAR and ethylene production. Soil pre-treatment with Trichoderma harzianum (Th) strains ITEM 908 (T908) and T908-5 decreased susceptibility of tomato to Meloidogyne incognita, as assessed by restriction in nematode reproduction and development. The effect of T. harzianum treatments on plant defense was detected by monitoring the expression of the genes PR-1/PR-5 and JERF3/ACO, markers of the SA- and JA/ET-dependent signaling pathways, respectively. The compatible nematode-plant interaction in absence of fungi caused a marked suppression of PR-1, PR-5, and ACO gene expressions, either locally or systemically, whilst expression of JERF3 gene resulted unaffected. Conversely, when plants were pre-treated with Th-strains, over-expression of PR-1, PR-5, and ACO genes was observed in roots 5 days after nematode inoculation. JERF3 gene expression did not change in Th-colonized plants challenged with nematodes. In the absence of nematodes, Trichoderma-root interaction was characterized by the inhibition of both SA-dependent signaling pathway and ET biosynthesis, and, in the case of PR-1 and ACO genes, this inhibition was systemic. JERF3 gene expression was systemically restricted only at the very early stages of plant-fungi interaction. Data presented indicate that Th-colonization primed roots for Systemic Acquired Resistance (SAR) against root-knot nematodes and reacted to nematode infection more efficiently than untreated plants. Such a response probably involves also activation of ET production, through an augmented transcription of the ACO gene, which encodes for the enzyme catalyzing the last step of ET biosynthesis. JA signaling and Induced Systemic Resistance (ISR) do not seem to be involved in the biocontrol action of the tested Th-strains against RKNs.

Real-time holographic surveillance system

DOEpatents

Collins, H.D.; McMakin, D.L.; Hall, T.E.; Gribble, R.P.

1995-10-03

A holographic surveillance system is disclosed including means for generating electromagnetic waves; means for transmitting the electromagnetic waves toward a target at a plurality of predetermined positions in space; means for receiving and converting electromagnetic waves reflected from the target to electrical signals at a plurality of predetermined positions in space; means for processing the electrical signals to obtain signals corresponding to a holographic reconstruction of the target; and means for displaying the processed information to determine nature of the target. The means for processing the electrical signals includes means for converting analog signals to digital signals followed by a computer means to apply a backward wave algorithm. 21 figs.

Process observation in fiber laser-based selective laser melting

NASA Astrophysics Data System (ADS)

Thombansen, Ulrich; Gatej, Alexander; Pereira, Milton

2015-01-01

The process observation in selective laser melting (SLM) focuses on observing the interaction point where the powder is processed. To provide process relevant information, signals have to be acquired that are resolved in both time and space. Especially in high-power SLM, where more than 1 kW of laser power is used, processing speeds of several meters per second are required for a high-quality processing results. Therefore, an implementation of a suitable process observation system has to acquire a large amount of spatially resolved data at low sampling speeds or it has to restrict the acquisition to a predefined area at a high sampling speed. In any case, it is vitally important to synchronously record the laser beam position and the acquired signal. This is a prerequisite that allows the recorded data become information. Today, most SLM systems employ f-theta lenses to focus the processing laser beam onto the powder bed. This report describes the drawbacks that result for process observation and suggests a variable retro-focus system which solves these issues. The beam quality of fiber lasers delivers the processing laser beam to the powder bed at relevant focus diameters, which is a key prerequisite for this solution to be viable. The optical train we present here couples the processing laser beam and the process observation coaxially, ensuring consistent alignment of interaction zone and observed area. With respect to signal processing, we have developed a solution that synchronously acquires signals from a pyrometer and the position of the laser beam by sampling the data with a field programmable gate array. The relevance of the acquired signals has been validated by the scanning of a sample filament. Experiments with grooved samples show a correlation between different powder thicknesses and the acquired signals at relevant processing parameters. This basic work takes a first step toward self-optimization of the manufacturing process in SLM. It enables the addition of cognitive functions to the manufacturing system to the extent that the system could track its own process. The results are based on analyzing and redesigning the optical train, in combination with a real-time signal acquisition system which provides a solution to certain technological barriers.

Debris Impact Detection Instrument for Crewed Modules

NASA Technical Reports Server (NTRS)

Opiela, J.; Corsaro, R.; Giovanes, F.; Lio, J.-C.

2012-01-01

When micrometeoroid or debris impacts occur on a space habitat, crew members need to be quickly informed of the likely extent of damage, and be directed to the impact location for possible repairs. This is especially important because the outer walls of pressurized volumes are often not easily accessible, blocked by racks or cabinets. The goal of the Habitat Particle Impact Monitoring System (HIMS) is to develop a fully automated, end-to-end particle impact detection system for crewed space exploration modules. The HIMS uses multiple passive, thin film piezo-polymer vibration sensors to detect impacts on a surface, and computer processing of the acoustical signals to characterize the impacts. Development and demonstration of the HIMS is proceeding in concert with NASA's Habitat Demonstration Unit (HDU) Project. The HDU Project is designed to develop and test various technologies, configurations, and operational concepts for exploration habitats. This paper describes the HIMS development, initial testing, and HDU integration efforts. Initial tests of the system on the HDU were conducted at NASA s 2010 and 2011 Desert Research and Technologies Studies (Desert-RATS or D-RATS). The HDU lab module, as seen from above, has an open circular floorplan divided into eight wedge-shaped Segments. The side wall of the module -- the surface used for this technology demonstration -- is a hard fiberglass composite covered with a layer of sprayed-on foam insulation. Four sensor locations were assigned near the corners of a rectangular pattern on the wall of one segment of the HDU lab module. The flat, self-adhesive sensors were applied to the module during its initial outfitting. To study the influence of the wall s construction (thickness and materials), three sets of four sensors were installed at different layer depths: on the interior of the module s wall, on the exterior of the same wall, and on the exterior of the foam insulation. The signal produced when a vibration passes through a sensor is first sent through a pre-amplifier. The amplified signal then is sent to the data acquisition and data processing systems. The vibration data from the sensors are then processed and reduced to a form suitable for presentation to the crew.

The Modular need for the Division Signal Battalion

DTIC Science & Technology

2017-06-09

findings and analyzes them to expand on them. It is with these findings and subsequent analysis that the case studies shape the answer to the three...These case studies focus on the signal leadership development and how it occurred in the pre-modular force structure, during modularity, and the...the comparative case study research. The case studies focus on signal leader development in a pre-modular signal force, a modular signal force, and

Audio feature extraction using probability distribution function

NASA Astrophysics Data System (ADS)

Suhaib, A.; Wan, Khairunizam; Aziz, Azri A.; Hazry, D.; Razlan, Zuradzman M.; Shahriman A., B.

2015-05-01

Voice recognition has been one of the popular applications in robotic field. It is also known to be recently used for biometric and multimedia information retrieval system. This technology is attained from successive research on audio feature extraction analysis. Probability Distribution Function (PDF) is a statistical method which is usually used as one of the processes in complex feature extraction methods such as GMM and PCA. In this paper, a new method for audio feature extraction is proposed which is by using only PDF as a feature extraction method itself for speech analysis purpose. Certain pre-processing techniques are performed in prior to the proposed feature extraction method. Subsequently, the PDF result values for each frame of sampled voice signals obtained from certain numbers of individuals are plotted. From the experimental results obtained, it can be seen visually from the plotted data that each individuals' voice has comparable PDF values and shapes.

Pervasive technology in Neonatal Intensive Care Unit: a prototype for newborns unobtrusive monitoring.

PubMed

Ciani, Oriana; Piccini, Luca; Parini, Sergio; Rullo, Alessia; Bagnoli, Franco; Marti, Patrizia; Andreoni, Giuseppe

2008-01-01

Pervasive computing research is introducing new perspectives in a wide range of applications, including healthcare domain. In this study we explore the possibility to realize a prototype of a system for unobtrusive recording and monitoring of multiple biological parameters on premature newborns hospitalized in the Neonatal Intensive Care Unit (NICU). It consists of three different units: a sensitized belt for Electrocardiogram (ECG) and chest dilatation monitoring, augmented with extrinsic transducers for temperature and respiratory activity measure, a device for signals pre-processing, sampling and transmission through Bluetooth(R) (BT) technology to a remote PC station and a software for data capture and post-processing. Preliminary results obtained by monitoring babies just discharged from the ward demonstrated the feasibility of the unobtrusive monitoring on this kind of subjects and open a new scenario for premature newborns monitoring and developmental cares practice in NICU.

Application of Mathematical Signal Processing Techniques to Mission Systems. (l’Application des techniques mathematiques du traitement du signal aux systemes de conduite des missions)

DTIC Science & Technology

1999-11-01

represents the linear time invariant (LTI) response of the combined analysis /synthesis system while the second repre- sents the aliasing introduced into...effectively to implement voice scrambling systems based on time - frequency permutation . The most general form of such a system is shown in Fig. 22 where...92201 NEUILLY-SUR-SEINE CEDEX, FRANCE RTO LECTURE SERIES 216 Application of Mathematical Signal Processing Techniques to Mission Systems (1

Switching and optimizing control for coal flotation process based on a hybrid model

PubMed Central

Dong, Zhiyong; Wang, Ranfeng; Fan, Minqiang; Fu, Xiang

2017-01-01

Flotation is an important part of coal preparation, and the flotation column is widely applied as efficient flotation equipment. This process is complex and affected by many factors, with the froth depth and reagent dosage being two of the most important and frequently manipulated variables. This paper proposes a new method of switching and optimizing control for the coal flotation process. A hybrid model is built and evaluated using industrial data. First, wavelet analysis and principal component analysis (PCA) are applied for signal pre-processing. Second, a control model for optimizing the set point of the froth depth is constructed based on fuzzy control, and a control model is designed to optimize the reagent dosages based on expert system. Finally, the least squares-support vector machine (LS-SVM) is used to identify the operating conditions of the flotation process and to select one of the two models (froth depth or reagent dosage) for subsequent operation according to the condition parameters. The hybrid model is developed and evaluated on an industrial coal flotation column and exhibits satisfactory performance. PMID:29040305

Ventromedial prefrontal cortex generates pre-stimulus theta coherence desynchronization: A schema instantiation hypothesis.

PubMed

Gilboa, Asaf; Moscovitch, Morris

2017-02-01

The ventral medial prefrontal cortex (vmPFC) has long been implicated in monitoring of memory veracity, and more recently also in memory schema functions. In our model of strategic retrieval the two are related. We have proposed that the vmPFC has two schema-dependent functions: (i) to establish context-relevant templates against which the output of memory systems can be compared; (ii) to mediate automatic decision monitoring processes to ensure that only those responses that meet the criterion are enacted. Electroencephalogram (EEG) data were used to provide evidence that vmPFC supports both functions, and that schema instantiation informs monitoring. Participants viewed pictures of acquaintances, along with those of famous and nonfamous people, and were asked to respond positively only to pictures of individuals they had met (personal familiarity). The Self serves as a super-ordinate cognitive schema, facilitating accurate endorsement of acquaintances and exclusion of non-personal but familiar faces. For the present report we focused on pre-cue tonic oscillatory activity. Controls demonstrated theta coherence desynchronization between medial prefrontal areas, inferotemporal and lateral temporal cortices. These oscillatory coherence patterns were significantly reduced in patients with vmPFC damage, especially in those with clinical histories of spontaneous confabulation. Importantly, these pre-stimulus cortico-cortical desynchronizations predicted post-cue automatic memory activation, as indexed by a familiarity modulation of the face-sensitive posterior cortical N170. Pre-cue desynchronization also predicted early post-cue frontal positive modulation (P230) and response accuracy. The data are consistent with a schema instantiation model that suggests the vmPFC biases posterior neocortical long-term memory representations that enhance automatic memory cue processing and informs frontally-mediated rapid memory monitoring (P230). Damage to these structures can lead to inaccurate, context-irrelevant activation of schemas. These, in turn, impair monitoring signals and can lead to confabulation when memory control processes are also deficient. Copyright © 2016 Elsevier Ltd. All rights reserved.

Symmetric 40-Gb/s TWDM-PON with 51-dB loss budget by using a single SOA as preamplifier, booster and format converter in ONU.

PubMed

Li, Zhengxuan; Yi, Lilin; Hu, Weisheng

2014-10-06

In this paper, we propose to use a semiconductor optical amplifier (SOA) in the optical network unit (ONU) to improve the loss budget in time and wavelength division multiplexed-passive optical network (TWDM-PON) systems. The SOA boosts the upstream signal to increase the output power of the electro-absorption modulated laser (EML) and simultaneously pre-amplifies the downstream signal for sensitivity improvement. The penalty caused by cross gain modulation (XGM) effect is negligible due to the low extinction ratio (ER) of upstream signal and the large wavelength difference between upstream and downstream links. In order to achieve a higher output power, the SOA is driven into its saturation region, where the self-phase modulation (SPM) effect converts the intensity into phase information and realizes on-off-keying (OOK) to phase-shifted-keying (PSK) format conversion. In this way, the pattern effect is eliminated, which releases the requirement of gain-clamping on SOA. To further improve the loss budget of upstream link, an Erbium doped fiber amplifier (EDFA) is used in the optical line terminal (OLT) to pre-amplify the received signal. For the downstream direction, directly modulated laser (DML) is used as the laser source. Taking advantage of its carrier-less characteristic, directly modulated signal shows high tolerance to fiber nonlinearity, which could support a downstream launch power as high as + 16 dBm per channel. In addition, the signal is pre-amplified by the SOA in ONU before being detected, so the sensitivity limitation for downstream link is also removed. As a result, a truly passive symmetric 40-Gb/s TWDM-PON was demonstrated, achieving a link loss budget of 51 dB.

Robust real-time extraction of respiratory signals from PET list-mode data

NASA Astrophysics Data System (ADS)

Salomon, André; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-06-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions’ detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting (‘binning’) of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signals directly from the acquired PET data simplifies the clinical workflow as it avoids handling additional signal measurement equipment. We introduce a new data-driven method ‘combined local motion detection’ (CLMD). It uses the time-of-flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using seven measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4 s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware.

Bayesian Inference for Signal-Based Seismic Monitoring

NASA Astrophysics Data System (ADS)

Moore, D.

2015-12-01

Traditional seismic monitoring systems rely on discrete detections produced by station processing software, discarding significant information present in the original recorded signal. SIG-VISA (Signal-based Vertically Integrated Seismic Analysis) is a system for global seismic monitoring through Bayesian inference on seismic signals. By modeling signals directly, our forward model is able to incorporate a rich representation of the physics underlying the signal generation process, including source mechanisms, wave propagation, and station response. This allows inference in the model to recover the qualitative behavior of recent geophysical methods including waveform matching and double-differencing, all as part of a unified Bayesian monitoring system that simultaneously detects and locates events from a global network of stations. We demonstrate recent progress in scaling up SIG-VISA to efficiently process the data stream of global signals recorded by the International Monitoring System (IMS), including comparisons against existing processing methods that show increased sensitivity from our signal-based model and in particular the ability to locate events (including aftershock sequences that can tax analyst processing) precisely from waveform correlation effects. We also provide a Bayesian analysis of an alleged low-magnitude event near the DPRK test site in May 2010 [1] [2], investigating whether such an event could plausibly be detected through automated processing in a signal-based monitoring system. [1] Zhang, Miao and Wen, Lianxing. "Seismological Evidence for a Low-Yield Nuclear Test on 12 May 2010 in North Korea". Seismological Research Letters, January/February 2015. [2] Richards, Paul. "A Seismic Event in North Korea on 12 May 2010". CTBTO SnT 2015 oral presentation, video at https://video-archive.ctbto.org/index.php/kmc/preview/partner_id/103/uiconf_id/4421629/entry_id/0_ymmtpps0/delivery/http

Application of Advanced Signal Processing Techniques to Angle of Arrival Estimation in ATC Navigation and Surveillance Systems

DTIC Science & Technology

1982-06-23

Administration Systems Research and Development Service 14, Spseq Aese Ce ’ Washington, D.C. 20591 It. SeppkW•aae metm The work reported in this document was...consider sophisticated signal processing techniques as an alternative method of improving system performanceH Some work in this area has already taken place...demands on the frequency spectrum. As noted in Table 1-1, there has been considerable work on advanced signal processing in the MLS context

Compressed sensing system considerations for ECG and EMG wireless biosensors.

PubMed

Dixon, Anna M R; Allstot, Emily G; Gangopadhyay, Daibashish; Allstot, David J

2012-04-01

Compressed sensing (CS) is an emerging signal processing paradigm that enables sub-Nyquist processing of sparse signals such as electrocardiogram (ECG) and electromyogram (EMG) biosignals. Consequently, it can be applied to biosignal acquisition systems to reduce the data rate to realize ultra-low-power performance. CS is compared to conventional and adaptive sampling techniques and several system-level design considerations are presented for CS acquisition systems including sparsity and compression limits, thresholding techniques, encoder bit-precision requirements, and signal recovery algorithms. Simulation studies show that compression factors greater than 16X are achievable for ECG and EMG signals with signal-to-quantization noise ratios greater than 60 dB.

Influence of video compression on the measurement error of the television system

NASA Astrophysics Data System (ADS)

Sotnik, A. V.; Yarishev, S. N.; Korotaev, V. V.

2015-05-01

Video data require a very large memory capacity. Optimal ratio quality / volume video encoding method is one of the most actual problem due to the urgent need to transfer large amounts of video over various networks. The technology of digital TV signal compression reduces the amount of data used for video stream representation. Video compression allows effective reduce the stream required for transmission and storage. It is important to take into account the uncertainties caused by compression of the video signal in the case of television measuring systems using. There are a lot digital compression methods. The aim of proposed work is research of video compression influence on the measurement error in television systems. Measurement error of the object parameter is the main characteristic of television measuring systems. Accuracy characterizes the difference between the measured value abd the actual parameter value. Errors caused by the optical system can be selected as a source of error in the television systems measurements. Method of the received video signal processing is also a source of error. Presence of error leads to large distortions in case of compression with constant data stream rate. Presence of errors increases the amount of data required to transmit or record an image frame in case of constant quality. The purpose of the intra-coding is reducing of the spatial redundancy within a frame (or field) of television image. This redundancy caused by the strong correlation between the elements of the image. It is possible to convert an array of image samples into a matrix of coefficients that are not correlated with each other, if one can find corresponding orthogonal transformation. It is possible to apply entropy coding to these uncorrelated coefficients and achieve a reduction in the digital stream. One can select such transformation that most of the matrix coefficients will be almost zero for typical images . Excluding these zero coefficients also possible reducing of the digital stream. Discrete cosine transformation is most widely used among possible orthogonal transformation. Errors of television measuring systems and data compression protocols analyzed In this paper. The main characteristics of measuring systems and detected sources of their error detected. The most effective methods of video compression are determined. The influence of video compression error on television measuring systems was researched. Obtained results will increase the accuracy of the measuring systems. In television image quality measuring system reduces distortion identical distortion in analog systems and specific distortions resulting from the process of coding / decoding digital video signal and errors in the transmission channel. By the distortions associated with encoding / decoding signal include quantization noise, reducing resolution, mosaic effect, "mosquito" effect edging on sharp drops brightness, blur colors, false patterns, the effect of "dirty window" and other defects. The size of video compression algorithms used in television measuring systems based on the image encoding with intra- and inter prediction individual fragments. The process of encoding / decoding image is non-linear in space and in time, because the quality of the playback of a movie at the reception depends on the pre- and post-history of a random, from the preceding and succeeding tracks, which can lead to distortion of the inadequacy of the sub-picture and a corresponding measuring signal.

SeeSway - A free web-based system for analysing and exploring standing balance data.

PubMed

Clark, Ross A; Pua, Yong-Hao

2018-06-01

Computerised posturography can be used to assess standing balance, and can predict poor functional outcomes in many clinical populations. A key limitation is the disparate signal filtering and analysis techniques, with many methods requiring custom computer programs. This paper discusses the creation of a freely available web-based software program, SeeSway (www.rehabtools.org/seesway), which was designed to provide powerful tools for pre-processing, analysing and visualising standing balance data in an easy to use and platform independent website. SeeSway links an interactive web platform with file upload capability to software systems including LabVIEW, Matlab, Python and R to perform the data filtering, analysis and visualisation of standing balance data. Input data can consist of any signal that comprises an anterior-posterior and medial-lateral coordinate trace such as center of pressure or mass displacement. This allows it to be used with systems including criterion reference commercial force platforms and three dimensional motion analysis, smartphones, accelerometers and low-cost technology such as Nintendo Wii Balance Board and Microsoft Kinect. Filtering options include Butterworth, weighted and unweighted moving average, and discrete wavelet transforms. Analysis methods include standard techniques such as path length, amplitude, and root mean square in addition to less common but potentially promising methods such as sample entropy, detrended fluctuation analysis and multiresolution wavelet analysis. These data are visualised using scalograms, which chart the change in frequency content over time, scatterplots and standard line charts. This provides the user with a detailed understanding of their results, and how their different pre-processing and analysis method selections affect their findings. An example of the data analysis techniques is provided in the paper, with graphical representation of how advanced analysis methods can better discriminate between someone with neurological impairment and a healthy control. The goal of SeeSway is to provide a simple yet powerful educational and research tool to explore how standing balance is affected in aging and clinical populations. Copyright © 2018 Elsevier B.V. All rights reserved.

Non-contact control of the working condition of mechanical units of the steam compressor for desalination plant

NASA Astrophysics Data System (ADS)

Danilin, A. I.; Chernyavsky, A. Zh.; Danilin, S. A.; Neverov, V. V.; Voroh, D. A.; Blagin, E. V.

2018-03-01

New methods and means for monitoring working condition of the rotating elements of steam compressor unit such as blade ring of the impeller and gears of multiplier are considered. Blade control is carried out by the signalling device of pre-emergency deformation of impeller blades. Control of the gears condition is carried out by apparatus system which allows to analyse change of the signal form caused by the gears wear. Influence of the wear types on the typical information parameters of the analysed signals is described. Technical characteristics of the devices and experimental research results are presented. Described control systems allow to detect deviations equal to 1-2% from initial condition. Application of such systems gives the opportunity to improve fault diagnosis and maintenance in 2-3 times.

Integrating SAR and derived products into operational volcano monitoring and decision support systems

NASA Astrophysics Data System (ADS)

Meyer, F. J.; McAlpin, D. B.; Gong, W.; Ajadi, O.; Arko, S.; Webley, P. W.; Dehn, J.

2015-02-01

Remote sensing plays a critical role in operational volcano monitoring due to the often remote locations of volcanic systems and the large spatial extent of potential eruption pre-cursor signals. Despite the all-weather capabilities of radar remote sensing and its high performance in monitoring of change, the contribution of radar data to operational monitoring activities has been limited in the past. This is largely due to: (1) the high costs associated with radar data; (2) traditionally slow data processing and delivery procedures; and (3) the limited temporal sampling provided by spaceborne radars. With this paper, we present new data processing and data integration techniques that mitigate some of these limitations and allow for a meaningful integration of radar data into operational volcano monitoring decision support systems. Specifically, we present fast data access procedures as well as new approaches to multi-track processing that improve near real-time data access and temporal sampling of volcanic systems with SAR data. We introduce phase-based (coherent) and amplitude-based (incoherent) change detection procedures that are able to extract dense time series of hazard information from these data. For a demonstration, we present an integration of our processing system with an operational volcano monitoring system that was developed for use by the Alaska Volcano Observatory (AVO). Through an application to a historic eruption, we show that the integration of SAR into systems such as AVO can significantly improve the ability of operational systems to detect eruptive precursors. Therefore, the developed technology is expected to improve operational hazard detection, alerting, and management capabilities.

An eye movement pre-training fosters the comprehension of processes and functions in technical systems.

PubMed

Skuballa, Irene T; Fortunski, Caroline; Renkl, Alexander

2015-01-01

The main research goal of the present study was to investigate in how far pre-training eye movements can facilitate knowledge acquisition in multimedia (pre-training principle). We combined considerations from research on eye movement modeling and pre-training to design and test a non-verbal eye movement-based pre-training. Participants in the experimental condition watched an animated circle moving in close spatial resemblance to a static visualization of a solar plant accompanied by a narration in a subsequently presented learning environment. This training was expected to foster top-down processes as reflected in gaze behavior during the learning process and enhance knowledge acquisition. We compared two groups (N = 45): participants in the experimental condition received pre-training in a first step and processed the learning material in a second step, whereas the control group underwent the second step without any pre-training. The pre-training group outperformed the control group in their learning outcomes, particularly in knowledge about processes and functions of the solar plant. However, the superior learning outcomes in the pre-training group could not be explained by eye-movement patterns. Furthermore, the pre-training moderated the relationship between experienced stress and learning outcomes. In the control group, high stress levels hindered learning, which was not found for the pre-training group. On a delayed posttest participants were requested to draw a picture of the learning content. Despite a non-significant effect of training on the quality of drawings, the pre-training showed associations between learning outcomes at the first testing time and process-related aspects in the quality of their drawings. Overall, non-verbal pre-training is a successful instructional intervention to promote learning processes in novices although these processes did not directly reflect in learners' eye movement behavior during learning.

Analysis of acoustic emission signals and monitoring of machining processes

PubMed

Govekar; Gradisek; Grabec

2000-03-01

Monitoring of a machining process on the basis of sensor signals requires a selection of informative inputs in order to reliably characterize and model the process. In this article, a system for selection of informative characteristics from signals of multiple sensors is presented. For signal analysis, methods of spectral analysis and methods of nonlinear time series analysis are used. With the aim of modeling relationships between signal characteristics and the corresponding process state, an adaptive empirical modeler is applied. The application of the system is demonstrated by characterization of different parameters defining the states of a turning machining process, such as: chip form, tool wear, and onset of chatter vibration. The results show that, in spite of the complexity of the turning process, the state of the process can be well characterized by just a few proper characteristics extracted from a representative sensor signal. The process characterization can be further improved by joining characteristics from multiple sensors and by application of chaotic characteristics.

A new high dynamic range ROIC with smart light intensity control unit

NASA Astrophysics Data System (ADS)

Yazici, Melik; Ceylan, Omer; Shafique, Atia; Abbasi, Shahbaz; Galioglu, Arman; Gurbuz, Yasar

2017-05-01

This journal presents a new high dynamic range ROIC with smart pixel which consists of two pre-amplifiers that are controlled by a circuit inside the pixel. Each pixel automatically decides which pre-amplifier is used according to the incoming illumination level. Instead of using single pre-amplifier, two input pre-amplifiers, which are optimized for different signal levels, are placed inside each pixel. The smart circuit mechanism, which decides the best input circuit according to the incoming light level, is also designed for each pixel. In short, an individual pixel has the ability to select the best input amplifier circuit that performs the best/highest SNR for the incoming signal level. A 32 × 32 ROIC prototype chip is designed to demonstrate the concept in 0.18 μ m CMOS technology. The prototype is optimized for NIR and SWIR bands. Instead of a detector, process variation optimized current sources are placed inside the ROIC. The chip achieves minimum 8.6 e- input referred noise and 98.9 dB dynamic range. It has the highest dynamic range in the literature in terms of analog ROICs for SWIR band. It is operating in room temperature and power consumption is 2.8 μ W per pixel.

A portable system for acquiring and removing motion artefact from ECG signals

NASA Astrophysics Data System (ADS)

Griffiths, A.; Das, A.; Fernandes, B.; Gaydecki, P.

2007-07-01

A novel electrocardiograph (ECG) signal acquisition and display system is under development. It is designed for patients ranging from the elderly to athletes. The signals are obtained from electrodes integrated into a vest, amplified, digitally processed and transmitted via Bluetooth to a PC with a Labview ® interface. Digital signal processing is performed to remove movement artefact and electromyographic (EMG) noise, which severely distorts signal morphology and complicates clinical diagnosis. Independent component analysis (ICA) is also used to improve the signal quality. The complete system will integrate the electronics into a single module which will be embedded in the vest.

A delivery device for presentation of tactile stimuli during functional magnetic resonance imaging.

PubMed

Dykes, Robert W; Miqueé, Aline; Xerri, Christian; Zennou-Azogui, Yoh'i; Rainville, Constant; Dumoulin, André; Marineau, Daniel

2007-01-30

We describe a novel stimulus delivery system designed to present tactile stimuli to a subject in the tunnel of a magnetic resonance imaging (MRI) system. Using energy from an air-driven piston to turn a wheel, the device advances a conveyor belt with a pre-determined sequence of stimuli that differ in their spatial features into the tunnel of the MRI. The positioning of one or several stimulus objects in a window near the subject's hand is controlled by a photoelectric device that detects periodic openings in the conveyor belt. Using this electric signal to position each presentation avoids cumulative positioning errors and provides a signal related to the progression of the experiment. We used a series of shapes that differed in their spatial features but the device could carry stimuli with a diversity of shapes and textures. This flexibility allows the experimenter to design a wide variety of psychophysical experiments in the haptic world and possibly to compare and contrast these stimuli with the cognitive treatment of similar stimuli delivered to the other senses. Appropriate experimental design allows separation of motor, sensory and memory storage phases of mental processes.

Time-dependent phase error correction using digital waveform synthesis

DOEpatents

Doerry, Armin W.; Buskirk, Stephen

2017-10-10

The various technologies presented herein relate to correcting a time-dependent phase error generated as part of the formation of a radar waveform. A waveform can be pre-distorted to facilitate correction of an error induced into the waveform by a downstream operation/component in a radar system. For example, amplifier power droop effect can engender a time-dependent phase error in a waveform as part of a radar signal generating operation. The error can be quantified and an according complimentary distortion can be applied to the waveform to facilitate negation of the error during the subsequent processing of the waveform. A time domain correction can be applied by a phase error correction look up table incorporated into a waveform phase generator.

An Airborne Ultrasonic Imaging System Based on 16 Elements: 150 kHz Piezopolymer Transducer Arrays—Preliminary Simulated and Experimental Results for Cylindrical Targets Detection

NASA Astrophysics Data System (ADS)

Capineri, L.; Bulletti, A.; Calzolai, M.; Giannelli, P.

2016-12-01

This paper describes the design and fabrication of a 16-element transducer array for airborne ultrasonic imaging operating at 150 kHz, that can operate both at close range (50 mm) in the near field of a synthetic aperture, and up to 250 mm. The proposed imaging technique is based on a modified version of the delay and sum algorithm implemented with a synthetic aperture where each pixel amplitude is determined by the integration of the signal obtained by the coherent summation of the acquired signals over a delayed window with fixed length. The image reconstruction methods using raw data provides the possibility to detect targets with smaller feature size on the order of one wavelength because the coherent signals summation over the selected window length while the image reconstruction methods using the summation of enveloped signals increases the amplitude response at the expenses of a lower spatial resolution. For the implementation of this system it is important to design compact airborne transducers with large field of view and this can be obtained with a new design of hemi-cylindrical polyvinylidene fluoride film transducers directly mounted on a printed circuit board. This new method is low cost and has repeatable transducer characteristics. The complete system is compact, with a modular architecture, in which eight boards with dual ultrasonic channels are mounted on a mother board. Each daughter board hosts a microcontroller unit and can operate with transducers in the bandwidth 40-200 kHz with on-board data acquisition, pre-processing and transfer on a dedicated bus.

System for monitoring an industrial process and determining sensor status

DOEpatents

Gross, K.C.; Hoyer, K.K.; Humenik, K.E.

1995-10-17

A method and system for monitoring an industrial process and a sensor are disclosed. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test. 17 figs.

System for monitoring an industrial process and determining sensor status

DOEpatents

Gross, K.C.; Hoyer, K.K.; Humenik, K.E.

1997-05-13

A method and system are disclosed for monitoring an industrial process and a sensor. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test. 17 figs.

System for monitoring an industrial process and determining sensor status

DOEpatents

Gross, Kenneth C.; Hoyer, Kristin K.; Humenik, Keith E.

1995-01-01

A method and system for monitoring an industrial process and a sensor. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test.

System for monitoring an industrial process and determining sensor status

DOEpatents

Gross, Kenneth C.; Hoyer, Kristin K.; Humenik, Keith E.

1997-01-01

A method and system for monitoring an industrial process and a sensor. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test.

Polymeric waveguide array with 45 degree slopes fabricated by bottom side tilted exposure

NASA Astrophysics Data System (ADS)

Lin, Xiaohui; Dou, Xinyuan; Wang, Alan X.; Chen, Ray T.

2011-01-01

This paper demonstrated a practical fabrication process of polymeric waveguide array (12 channels) with 50μm(W)×50μm(H)×23mm(L) dimension and mirror embedded 45° degree slopes for vertical coupling purpose. The entire process contained three main parts: a SU8 pre-mold with 45° slope, a PDMS mold and the final waveguide array device. The key step of fabricating the pre-mold included a bottom side tilted exposure of SU8 photo resist. By placing the sample upside down, tilting by 58.7° and immersing into DI water, the ultraviolet (UV) beam that shined vertically was directed to go through from the bottom of the glass substrate into top side SU8 resist with 45° angle to form the surface. This method was able to guarantee no-gap contact between the mask pattern and the photo resist when exposing. By comparing the process complexity and achieved structure of the top and bottom side exposure, the later was proved to be a promising method for making high quality tilted structure without any tailing effect. The reversed PDMS mold was then fabricated on the SU8 pre-mold. The PDMS mold was used to imprint the cladding layer of the waveguide array. After metal deposition, core filling and top cladding layer coating, the final polymeric waveguide array device was achieved. For performance evaluation, 850nm laser beam from VCSEL was modulated to 10Gbps signals and vertically coupled into the waveguide array. The eye diagrams revealed high Q factor when transmitting signals along these waveguide array.

AIP1 expression in tumor niche suppresses tumor progression and metastasis

PubMed Central

Ji, Weidong; Li, Yonghao; He, Yun; Yin, Mingzhu; Zhou, Huanjiao Jenny; Boggon, Titus J.; Zhang, Haifeng; Min, Wang

2015-01-01

Studies from tumor cells suggest that tumor suppressor AIP1 inhibits epithelial-mesenchymal transition (EMT). However, the role of AIP1 in the tumor microenvironment has not been examined. We show that a global or vascular endothelial cell (EC)-specific deletion of the AIP1 gene in mice augments tumor growth and metastasis in melanoma and breast cancer models. AIP1-deficient vascular environment not only enhances tumor neovascularization and increases pre-metastatic niche formation, but also secrets tumor EMT-promoting factors. These effects from AIP1 loss are associated with increased VEGFR2 signaling in the vascular EC and could be abrogated by systemic administration of VEGFR2 kinase inhibitors. Mechanistically, AIP1 blocks VEGFR2-dependent signaling by directly binding to the phosphotyrosine residues within the activation loop of VEGFR2. Our data reveal that AIP1, by inhibiting VEGFR2-dependent signaling in tumor niche, suppresses tumor EMT switch, tumor angiogenesis and tumor pre-metastatic niche formation to limit tumor growth and metastasis. PMID:26139244

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.

Design of Flow Systems for Improved Networking and Reduced Noise in Biomolecular Signal Processing in Biocomputing and Biosensing Applications

PubMed Central

Verma, Arjun; Fratto, Brian E.; Privman, Vladimir; Katz, Evgeny

2016-01-01

We consider flow systems that have been utilized for small-scale biomolecular computing and digital signal processing in binary-operating biosensors. Signal measurement is optimized by designing a flow-reversal cuvette and analyzing the experimental data to theoretically extract the pulse shape, as well as reveal the level of noise it possesses. Noise reduction is then carried out numerically. We conclude that this can be accomplished physically via the addition of properly designed well-mixing flow-reversal cell(s) as an integral part of the flow system. This approach should enable improved networking capabilities and potentially not only digital but analog signal-processing in such systems. Possible applications in complex biocomputing networks and various sense-and-act systems are discussed. PMID:27399702

Design of an FMCW radar baseband signal processing system for automotive application.

PubMed

Lin, Jau-Jr; Li, Yuan-Ping; Hsu, Wei-Chiang; Lee, Ta-Sung

2016-01-01

For a typical FMCW automotive radar system, a new design of baseband signal processing architecture and algorithms is proposed to overcome the ghost targets and overlapping problems in the multi-target detection scenario. To satisfy the short measurement time constraint without increasing the RF front-end loading, a three-segment waveform with different slopes is utilized. By introducing a new pairing mechanism and a spatial filter design algorithm, the proposed detection architecture not only provides high accuracy and reliability, but also requires low pairing time and computational loading. This proposed baseband signal processing architecture and algorithms balance the performance and complexity, and are suitable to be implemented in a real automotive radar system. Field measurement results demonstrate that the proposed automotive radar signal processing system can perform well in a realistic application scenario.

Mellin Transform-Based Correction Method for Linear Scale Inconsistency of Intrusion Events Identification in OFPS

NASA Astrophysics Data System (ADS)

Wang, Baocheng; Qu, Dandan; Tian, Qing; Pang, Liping

2018-05-01

For the problem that the linear scale of intrusion signals in the optical fiber pre-warning system (OFPS) is inconsistent, this paper presents a method to correct the scale. Firstly, the intrusion signals are intercepted, and an aggregate of the segments with equal length is obtained. Then, the Mellin transform (MT) is applied to convert them into the same scale. The spectral characteristics are obtained by the Fourier transform. Finally, we adopt back-propagation (BP) neural network to identify intrusion types, which takes the spectral characteristics as input. We carried out the field experiments and collected the optical fiber intrusion signals which contain the picking signal, shoveling signal, and running signal. The experimental results show that the proposed algorithm can effectively improve the recognition accuracy of the intrusion signals.

Reversible Human TGF-β Signal Shifting between Tumor Suppression and Fibro-Carcinogenesis: Implications of Smad Phospho-Isoforms for Hepatic Epithelial-Mesenchymal Transitions.

PubMed

Yoshida, Katsunori; Murata, Miki; Yamaguchi, Takashi; Matsuzaki, Koichi; Okazaki, Kazuichi

2016-01-12

Epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET) are observed during both physiological liver wound healing and the pathological fibrotic/carcinogenic (fibro-carcinogenetic) process. TGF-β and pro-inflammatory cytokine are considered to be the major factors accelerating liver fibrosis and promoting liver carcinogenesis. Smads, consisting of intermediate linker regions connecting Mad homology domains, act as the intracellular mediators of the TGF-β signal transduction pathway. As the TGF-β receptors, c-Jun N-terminal kinase and cyclin-dependent kinase, differentially phosphorylate Smad2/3, we have generated numerous antibodies against linker (L) and C-terminal (C) phosphorylation sites in Smad2/3 and identified four types of phosphorylated forms: cytostatic COOH-terminally-phosphorylated Smad3 (pSmad3C), mitogenic pSmad3L (Ser-213) signaling, fibrogenic pSmad2L (Ser-245/250/255)/C signaling and migratory pSmad2/3L (Thr-220/179)/C signaling. After acute liver injury, TGF-β upregulates pSmad3C signaling and terminates pSmad3L (Ser-213)-mediated hepatocyte proliferation. TGF-β and pro-inflammatory cytokines cooperatively enhance collagen synthesis by upregulating pSmad2L (Thr-220)/C and pSmad3L (Thr-179)/C pathways in activated hepatic stellate cells. During chronic liver injuries, hepatocytes persistently affected by TGF-β and pro-inflammatory cytokines eventually become pre-neoplastic hepatocytes. Both myofibroblasts and pre-neoplastic hepatocyte exhibit the same carcinogenic (mitogenic) pSmad3L (Ser-213) and fibrogenic pSmad2L (Ser-245/250/255)/C signaling, with acquisition of fibro-carcinogenic properties and increasing risk of hepatocellular carcinoma (HCC). Firstly, we review phospho-Smad-isoform signalings in epithelial and mesenchymal cells in physiological and pathological conditions and then consider Smad linker phosphorylation as a potential target for pathological EMT during human fibro-carcinogenesis, because human Smad phospho-isoform signals can reverse from fibro-carcinogenesis to tumor-suppression in a process of MET after therapy.

Automatic inspection system for nuclear fuel pellets or rods

DOEpatents

Miller, Jr., William H.; Sease, John D.; Hamel, William R.; Bradley, Ronnie A.

1978-01-01

An automatic inspection system is provided for determining surface defects on cylindrical objects such as nuclear fuel pellets or rods. The active element of the system is a compound ring having a plurality of pneumatic jet units directed into a central bore. These jet units are connected to provide multiple circuits, each circuit being provided with a pressure sensor. The outputs of the sensors are fed to a comparator circuit whereby a signal is generated when the difference of pressure between pneumatic circuits, caused by a defect, exceeds a pre-set amount. This signal may be used to divert the piece being inspected into a "reject" storage bin or the like.

An adaptable multiple power source for mass spectrometry and other scientific instruments.

PubMed

Lin, T-Y; Anderson, G A; Norheim, R V; Prost, S A; LaMarche, B L; Leach, F E; Auberry, K J; Smith, R D; Koppenaal, D W; Robinson, E W; Paša-Tolić, L

2015-09-01

An Adaptable Multiple Power Source (AMPS) system has been designed and constructed. The AMPS system can provide up to 16 direct current (DC) (±400 V; 5 mA), 4 radio frequency (RF) (two 500 VPP sinusoidal signals each, 0.5-5 MHz) channels, 2 high voltage sources (±6 kV), and one ∼40 W, 250 °C temperature-regulated heater. The system is controlled by a microcontroller, capable of communicating with its front panel or a computer. It can assign not only pre-saved fixed DC and RF signals but also profiled DC voltages. The AMPS system is capable of driving many mass spectrometry components and ancillary devices and can be adapted to other instrumentation/engineering projects.

Pre-Hardware Optimization of Spacecraft Image Processing Software Algorithms and Hardware Implementation

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Flatley, Thomas P.; Hestnes, Phyllis; Jentoft-Nilsen, Marit; Petrick, David J.; Day, John H. (Technical Monitor)

2001-01-01

Spacecraft telemetry rates have steadily increased over the last decade presenting a problem for real-time processing by ground facilities. This paper proposes a solution to a related problem for the Geostationary Operational Environmental Spacecraft (GOES-8) image processing application. Although large super-computer facilities are the obvious heritage solution, they are very costly, making it imperative to seek a feasible alternative engineering solution at a fraction of the cost. The solution is based on a Personal Computer (PC) platform and synergy of optimized software algorithms and re-configurable computing hardware technologies, such as Field Programmable Gate Arrays (FPGA) and Digital Signal Processing (DSP). It has been shown in [1] and [2] that this configuration can provide superior inexpensive performance for a chosen application on the ground station or on-board a spacecraft. However, since this technology is still maturing, intensive pre-hardware steps are necessary to achieve the benefits of hardware implementation. This paper describes these steps for the GOES-8 application, a software project developed using Interactive Data Language (IDL) (Trademark of Research Systems, Inc.) on a Workstation/UNIX platform. The solution involves converting the application to a PC/Windows/RC platform, selected mainly by the availability of low cost, adaptable high-speed RC hardware. In order for the hybrid system to run, the IDL software was modified to account for platform differences. It was interesting to examine the gains and losses in performance on the new platform, as well as unexpected observations before implementing hardware. After substantial pre-hardware optimization steps, the necessity of hardware implementation for bottleneck code in the PC environment became evident and solvable beginning with the methodology described in [1], [2], and implementing a novel methodology for this specific application [6]. The PC-RC interface bandwidth problem for the class of applications with moderate input-output data rates but large intermediate multi-thread data streams has been addressed and mitigated. This opens a new class of satellite image processing applications for bottleneck problems solution using RC technologies. The issue of a science algorithm level of abstraction necessary for RC hardware implementation is also described. Selected Matlab functions already implemented in hardware were investigated for their direct applicability to the GOES-8 application with the intent to create a library of Matlab and IDL RC functions for ongoing work. A complete class of spacecraft image processing applications using embedded re-configurable computing technology to meet real-time requirements, including performance results and comparison with the existing system, is described in this paper.

A new approach to pre-processing digital image for wavelet-based watermark

NASA Astrophysics Data System (ADS)

Agreste, Santa; Andaloro, Guido

2008-11-01

The growth of the Internet has increased the phenomenon of digital piracy, in multimedia objects, like software, image, video, audio and text. Therefore it is strategic to individualize and to develop methods and numerical algorithms, which are stable and have low computational cost, that will allow us to find a solution to these problems. We describe a digital watermarking algorithm for color image protection and authenticity: robust, not blind, and wavelet-based. The use of Discrete Wavelet Transform is motivated by good time-frequency features and a good match with Human Visual System directives. These two combined elements are important for building an invisible and robust watermark. Moreover our algorithm can work with any image, thanks to the step of pre-processing of the image that includes resize techniques that adapt to the size of the original image for Wavelet transform. The watermark signal is calculated in correlation with the image features and statistic properties. In the detection step we apply a re-synchronization between the original and watermarked image according to the Neyman-Pearson statistic criterion. Experimentation on a large set of different images has been shown to be resistant against geometric, filtering, and StirMark attacks with a low rate of false alarm.

Syndromic surveillance using veterinary laboratory data: data pre-processing and algorithm performance evaluation

PubMed Central

Dórea, Fernanda C.; McEwen, Beverly J.; McNab, W. Bruce; Revie, Crawford W.; Sanchez, Javier

2013-01-01

Diagnostic test orders to an animal laboratory were explored as a data source for monitoring trends in the incidence of clinical syndromes in cattle. Four years of real data and over 200 simulated outbreak signals were used to compare pre-processing methods that could remove temporal effects in the data, as well as temporal aberration detection algorithms that provided high sensitivity and specificity. Weekly differencing demonstrated solid performance in removing day-of-week effects, even in series with low daily counts. For aberration detection, the results indicated that no single algorithm showed performance superior to all others across the range of outbreak scenarios simulated. Exponentially weighted moving average charts and Holt–Winters exponential smoothing demonstrated complementary performance, with the latter offering an automated method to adjust to changes in the time series that will likely occur in the future. Shewhart charts provided lower sensitivity but earlier detection in some scenarios. Cumulative sum charts did not appear to add value to the system; however, the poor performance of this algorithm was attributed to characteristics of the data monitored. These findings indicate that automated monitoring aimed at early detection of temporal aberrations will likely be most effective when a range of algorithms are implemented in parallel. PMID:23576782

Syndromic surveillance using veterinary laboratory data: data pre-processing and algorithm performance evaluation.

PubMed

Dórea, Fernanda C; McEwen, Beverly J; McNab, W Bruce; Revie, Crawford W; Sanchez, Javier

2013-06-06

Diagnostic test orders to an animal laboratory were explored as a data source for monitoring trends in the incidence of clinical syndromes in cattle. Four years of real data and over 200 simulated outbreak signals were used to compare pre-processing methods that could remove temporal effects in the data, as well as temporal aberration detection algorithms that provided high sensitivity and specificity. Weekly differencing demonstrated solid performance in removing day-of-week effects, even in series with low daily counts. For aberration detection, the results indicated that no single algorithm showed performance superior to all others across the range of outbreak scenarios simulated. Exponentially weighted moving average charts and Holt-Winters exponential smoothing demonstrated complementary performance, with the latter offering an automated method to adjust to changes in the time series that will likely occur in the future. Shewhart charts provided lower sensitivity but earlier detection in some scenarios. Cumulative sum charts did not appear to add value to the system; however, the poor performance of this algorithm was attributed to characteristics of the data monitored. These findings indicate that automated monitoring aimed at early detection of temporal aberrations will likely be most effective when a range of algorithms are implemented in parallel.

Relationships between digital signal processing and control and estimation theory

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1978-01-01

Research areas associated with digital signal processing and control and estimation theory are identified. Particular attention is given to image processing, system identification problems (parameter identification, linear prediction, least squares, Kalman filtering), stability analyses (the use of the Liapunov theory, frequency domain criteria, passivity), and multiparameter systems, distributed processes, and random fields.

Externalizing proneness and brain response during pre-cuing and viewing of emotional pictures

PubMed Central

Foell, Jens; Brislin, Sarah J.; Strickland, Casey M.; Seo, Dongju; Sabatinelli, Dean

2016-01-01

Externalizing proneness, or trait disinhibition, is a concept relevant to multiple high-impact disorders involving impulsive-aggressive behavior. Its mechanisms remain disputed: major models posit hyperresponsive reward circuitry or heightened threat-system reactivity as sources of disinhibitory tendencies. This study evaluated alternative possibilities by examining relations between trait disinhibition and brain reactivity during preparation for and processing of visual affective stimuli. Forty females participated in a functional neuroimaging procedure with stimuli presented in blocks containing either pleasurable or aversive pictures interspersed with neutral, with each picture preceded by a preparation signal. Preparing to view elicited activation in regions including nucleus accumbens, whereas visual regions and bilateral amygdala were activated during viewing of emotional pictures. High disinhibition predicted reduced nucleus accumbens activation during preparation within pleasant/neutral picture blocks, along with enhanced amygdala reactivity during viewing of pleasant and aversive pictures. Follow-up analyses revealed that the augmented amygdala response was related to reduced preparatory activation. Findings indicate that participants high in disinhibition are less able to process implicit cues and mentally prepare for upcoming stimuli, leading to limbic hyperreactivity during processing of actual stimuli. This outcome is helpful for integrating findings from studies suggesting reward-system hyperreactivity and others suggesting threat-system hyperreactivity as mechanisms for externalizing proneness. PMID:26113614

Laser pulse coded signal frequency measuring device based on DSP and CPLD

NASA Astrophysics Data System (ADS)

Zhang, Hai-bo; Cao, Li-hua; Geng, Ai-hui; Li, Yan; Guo, Ru-hai; Wang, Ting-feng

2011-06-01

Laser pulse code is an anti-jamming measures used in semi-active laser guided weapons. On account of the laser-guided signals adopting pulse coding mode and the weak signal processing, it need complex calculations in the frequency measurement process according to the laser pulse code signal time correlation to meet the request in optoelectronic countermeasures in semi-active laser guided weapons. To ensure accurately completing frequency measurement in a short time, it needed to carry out self-related process with the pulse arrival time series composed of pulse arrival time, calculate the signal repetition period, and then identify the letter type to achieve signal decoding from determining the time value, number and rank number in a signal cycle by Using CPLD and DSP for signal processing chip, designing a laser-guided signal frequency measurement in the pulse frequency measurement device, improving the signal processing capability through the appropriate software algorithms. In this article, we introduced the principle of frequency measurement of the device, described the hardware components of the device, the system works and software, analyzed the impact of some system factors on the accuracy of the measurement. The experimental results indicated that this system improve the accuracy of the measurement under the premise of volume, real-time, anti-interference, low power of the laser pulse frequency measuring device. The practicality of the design, reliability has been demonstrated from the experimental point of view.

Distinct role of IL-1β in instigating disease in Sharpincpdm mice

PubMed Central

Gurung, Prajwal; Sharma, Bhesh Raj; Kanneganti, Thirumala-Devi

2016-01-01

Mice deficient in SHARPIN (Sharpincpdm mice), a member of linear ubiquitin chain assembly complex (LUBAC), develop severe dermatitis associated with systemic inflammation. Previous studies have demonstrated that components of the TNF-signaling pathway, NLRP3 inflammasome and IL-1R signaling are required to provoke skin inflammation in Sharpincpdm mice. However, whether IL-1α or IL-1β, both of which signals through IL-1R, instigates skin inflammation and systemic disease is not known. Here, we have performed extensive cellular analysis of pre-diseased and diseased Sharpincpdm mice and demonstrated that cellular dysregulation precedes skin inflammation. Furthermore, we demonstrate a specific role for IL-1β, but not IL-1α, in instigating dermatitis in Sharpincpdm mice. Our results altogether demonstrate distinct roles of SHARPIN in initiating systemic inflammation and dermatitis. Furthermore, skin inflammation in Sharpincpdm mice is specifically modulated by IL-1β, highlighting the importance of specific targeted therapies in the IL-1 signaling blockade. PMID:27892465

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring.

PubMed

Martinek, Radek; Nedoma, Jan; Fajkus, Marcel; Kahankova, Radana; Konecny, Jaromir; Janku, Petr; Kepak, Stanislav; Bilik, Petr; Nazeran, Homer

2017-04-18

This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio-SNR, Root Mean Square Error-RMSE, Sensitivity-S+, and Positive Predictive Value-PPV.

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring

PubMed Central

Martinek, Radek; Nedoma, Jan; Fajkus, Marcel; Kahankova, Radana; Konecny, Jaromir; Janku, Petr; Kepak, Stanislav; Bilik, Petr; Nazeran, Homer

2017-01-01

This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio—SNR, Root Mean Square Error—RMSE, Sensitivity—S+, and Positive Predictive Value—PPV. PMID:28420215

Conditions for Lorentz-invariant superluminal information transfer without signaling

NASA Astrophysics Data System (ADS)

Grössing, G.; Fussy, S.; Mesa Pascasio, J.; Schwabl, H.

2016-03-01

We understand emergent quantum mechanics in the sense that quantum mechanics describes processes of physical emergence relating an assumed sub-quantum physics to macroscopic boundary conditions. The latter can be shown to entail top-down causation, in addition to usual bottom-up scenarios. With this example it is demonstrated that definitions of “realism” in the literature are simply too restrictive. A prevailing manner to define realism in quantum mechanics is in terms of pre-determination independent of the measurement. With our counter-example, which actually is ubiquitous in emergent, or self-organizing, systems, we argue for realism without pre-determination. We refer to earlier results of our group showing how the guiding equation of the de Broglie-Bohm interpretation can be derived from a theory with classical ingredients only. Essentially, this corresponds to a “quantum mechanics without wave functions” in ordinary 3-space, albeit with nonlocal correlations. This, then, leads to the central question of how to deal with the nonlocality problem in a relativistic setting. We here show that a basic argument discussing the allegedly paradox time ordering of events in EPR-type two-particle experiments falls short of taking into account the contextuality of the experimental setup. Consequently, we then discuss under which circumstances (i.e. physical premises) superluminal information transfer (but not signaling) may be compatible with a Lorentz-invariant theory. Finally, we argue that the impossibility of superluminal signaling - despite the presence of superluminal information transfer - is not the result of some sort of conspiracy (á la “Nature likes to hide”), but the consequence of the impossibility to exactly reproduce in repeated experimental runs a state's preparation, or of the no-cloning theorem, respectively.

Entirely soft dielectric elastomer robots

NASA Astrophysics Data System (ADS)

Henke, E.-F. Markus; Wilson, Katherine E.; Anderson, Iain A.

2017-04-01

Multifunctional Dielectric Elastomer (DE) devices are well established as actuators, sensors and energy har- vesters. Since the invention of the Dielectric Elastomer Switch (DES), a piezoresistive electrode that can directly switch charge on and off, it has become possible to expand the wide functionality of DE structures even more. We show the application of fully soft DE subcomponents in biomimetic robotic structures. It is now possible to couple arrays of actuator/switch units together so that they switch charge between them- selves on and off. One can then build DE devices that operate as self-controlled oscillators. With an oscillator one can produce a periodic signal that controls a soft DE robot - a DE device with its own DE nervous system. DESs were fabricated using a special electrode mixture, and imprinting technology at an exact pre-strain. We have demonstrated six orders of magnitude change in conductivity within the DES over 50% strain. The control signal can either be a mechanical deformation from another DE or an electrical input to a connected dielectric elastomer actuator (DEA). We have demonstrated a variety of fully soft multifunctional subcomponents that enable the design of autonomous soft robots without conventional electronics. The combination of digital logic structures for basic signal processing, data storage in dielectric elastomer flip-flops and digital and analogue clocks with adjustable frequencies, made of dielectric elastomer oscillators (DEOs), enables fully soft, self-controlled and electronics-free robotic structures. DE robotic structures to date include stiff frames to maintain necessary pre-strains enabling sufficient actuation of DEAs. Here we present a design and production technology for a first robotic structure consisting only of soft silicones and carbon black.

Fast, multi-channel real-time processing of signals with microsecond latency using graphics processing units.

PubMed

Rath, N; Kato, S; Levesque, J P; Mauel, M E; Navratil, G A; Peng, Q

2014-04-01

Fast, digital signal processing (DSP) has many applications. Typical hardware options for performing DSP are field-programmable gate arrays (FPGAs), application-specific integrated DSP chips, or general purpose personal computer systems. This paper presents a novel DSP platform that has been developed for feedback control on the HBT-EP tokamak device. The system runs all signal processing exclusively on a Graphics Processing Unit (GPU) to achieve real-time performance with latencies below 8 μs. Signals are transferred into and out of the GPU using PCI Express peer-to-peer direct-memory-access transfers without involvement of the central processing unit or host memory. Tests were performed on the feedback control system of the HBT-EP tokamak using forty 16-bit floating point inputs and outputs each and a sampling rate of up to 250 kHz. Signals were digitized by a D-TACQ ACQ196 module, processing done on an NVIDIA GTX 580 GPU programmed in CUDA, and analog output was generated by D-TACQ AO32CPCI modules.

Device and method to enhance availability of cluster-based processing systems

NASA Technical Reports Server (NTRS)

Lupia, David J. (Inventor); Ramos, Jeremy (Inventor); Samson, Jr., John R. (Inventor)

2010-01-01

An electronic computing device including at least one processing unit that implements a specific fault signal upon experiencing an associated fault, a control unit that generates a specific recovery signal upon receiving the fault signal from the at least one processing unit, and at least one input memory unit. The recovery signal initiates specific recovery processes in the at least one processing unit. The input memory buffers input data signals input to the at least one processing unit that experienced the fault during the recovery period.

Cancer systems biology: signal processing for cancer research

PubMed Central

Yli-Harja, Olli; Ylipää, Antti; Nykter, Matti; Zhang, Wei

2011-01-01

In this editorial we introduce the research paradigms of signal processing in the era of systems biology. Signal processing is a field of science traditionally focused on modeling electronic and communications systems, but recently it has turned to biological applications with astounding results. The essence of signal processing is to describe the natural world by mathematical models and then, based on these models, develop efficient computational tools for solving engineering problems. Here, we underline, with examples, the endless possibilities which arise when the battle-hardened tools of engineering are applied to solve the problems that have tormented cancer researchers. Based on this approach, a new field has emerged, called cancer systems biology. Despite its short history, cancer systems biology has already produced several success stories tackling previously impracticable problems. Perhaps most importantly, it has been accepted as an integral part of the major endeavors of cancer research, such as analyzing the genomic and epigenomic data produced by The Cancer Genome Atlas (TCGA) project. Finally, we show that signal processing and cancer research, two fields that are seemingly distant from each other, have merged into a field that is indeed more than the sum of its parts. PMID:21439242

Cell-Autonomous Control of IL-7 Response Revealed In a Novel Stage of Precursor B Cells

PubMed Central

Sandoval, Gabriel J.; Graham, Daniel B.; Bhattacharya, Deepta; Sleckman, Barry P.; Xavier, Ramnik J.; Swat, Wojciech

2013-01-01

During early stages of B-lineage differentiation in bone marrow, signals emanating from IL-7 receptor and pre-B cell receptor (pre-BCR) are thought to synergistically induce proliferative expansion of progenitor cells. Paradoxically, loss of pre-BCR signaling components is associated with leukemia in both mice and humans. Exactly how progenitor B cells perform the task of balancing proliferative burst dependent on IL-7 with the termination of IL-7 signals and the initiation of LC gene rearrangement remains to be elucidated. In this report, we provide genetic and functional evidence that the cessation of IL-7 response of pre-B cells is controlled via a cell-autonomous mechanism that operates at a discreet developmental transition inside Fraction C’ (Large Pre-BII) marked by transient expression of c-Myc. Our data indicates that pre-BCR cooperates with IL-7R in expanding pre-B cell pool, but it is also critical to control differentiation program shutting off c-Myc gene in large pre-B cells. PMID:23420891

Infrared system for monitoring movement of objects

DOEpatents

Valentine, Kenneth H.; Falter, Diedre D.; Falter, Kelly G.

1991-01-01

A system for monitoring moving objects, such as the flight of honeybees and other insects, using a pulsed laser light source. This system has a self-powered micro-miniaturized transmitting unit powered, in the preferred embodiment, with an array solar cells. This transmitting unit is attached to the object to be monitored. These solar cells provide current to a storage energy capacitor to produce, for example, five volts for the operation of the transmitter. In the simplest embodiment, the voltage on the capacitor operates a pulse generator to provide a pulsed energizing signal to one or more very small laser diodes. The pulsed light is then received at a receiving base station using substantially standard means which converts the light to an electrical signal for processing in a microprocessor to create the information as to the movement of the object. In the case of a unit for monitoring honeybees and other insects, the transmitting unit weighs less than 50 mg, and has a size no larger than 1.times.3.times.5 millimeters. Also, the preferred embodiment provides for the coding of the light to uniquely identify the particular transmitting unit that is being monitored. A "wake-up" circuit is provided in the preferred embodiment whereby there is no transmission until the voltage on the capacitor has exceeded a pre-set threshold. Various other uses of the motion-detection system are described.

Infrared system for monitoring movement of objects

DOEpatents

Valentine, K.H.; Falter, D.D.; Falter, K.G.

1991-04-30

A system is described for monitoring moving objects, such as the flight of honeybees and other insects, using a pulsed laser light source. This system has a self-powered micro-miniaturized transmitting unit powered, in the preferred embodiment, with an array of solar cells. This transmitting unit is attached to the object to be monitored. These solar cells provide current to a storage energy capacitor to produce, for example, five volts for the operation of the transmitter. In the simplest embodiment, the voltage on the capacitor operates a pulse generator to provide a pulsed energizing signal to one or more very small laser diodes. The pulsed light is then received at a receiving base station using substantially standard means which converts the light to an electrical signal for processing in a microprocessor to create the information as to the movement of the object. In the case of a unit for monitoring honeybees and other insects, the transmitting unit weighs less than 50 mg, and has a size no larger than 1[times]3[times]5 millimeters. Also, the preferred embodiment provides for the coding of the light to uniquely identify the particular transmitting unit that is being monitored. A wake-up' circuit is provided in the preferred embodiment whereby there is no transmission until the voltage on the capacitor has exceeded a pre-set threshold. Various other uses of the motion-detection system are described. 4 figures.

SISYPHUS: A high performance seismic inversion factory

NASA Astrophysics Data System (ADS)

Gokhberg, Alexey; Simutė, Saulė; Boehm, Christian; Fichtner, Andreas

2016-04-01

In the recent years the massively parallel high performance computers became the standard instruments for solving the forward and inverse problems in seismology. The respective software packages dedicated to forward and inverse waveform modelling specially designed for such computers (SPECFEM3D, SES3D) became mature and widely available. These packages achieve significant computational performance and provide researchers with an opportunity to solve problems of bigger size at higher resolution within a shorter time. However, a typical seismic inversion process contains various activities that are beyond the common solver functionality. They include management of information on seismic events and stations, 3D models, observed and synthetic seismograms, pre-processing of the observed signals, computation of misfits and adjoint sources, minimization of misfits, and process workflow management. These activities are time consuming, seldom sufficiently automated, and therefore represent a bottleneck that can substantially offset performance benefits provided by even the most powerful modern supercomputers. Furthermore, a typical system architecture of modern supercomputing platforms is oriented towards the maximum computational performance and provides limited standard facilities for automation of the supporting activities. We present a prototype solution that automates all aspects of the seismic inversion process and is tuned for the modern massively parallel high performance computing systems. We address several major aspects of the solution architecture, which include (1) design of an inversion state database for tracing all relevant aspects of the entire solution process, (2) design of an extensible workflow management framework, (3) integration with wave propagation solvers, (4) integration with optimization packages, (5) computation of misfits and adjoint sources, and (6) process monitoring. The inversion state database represents a hierarchical structure with branches for the static process setup, inversion iterations, and solver runs, each branch specifying information at the event, station and channel levels. The workflow management framework is based on an embedded scripting engine that allows definition of various workflow scenarios using a high-level scripting language and provides access to all available inversion components represented as standard library functions. At present the SES3D wave propagation solver is integrated in the solution; the work is in progress for interfacing with SPECFEM3D. A separate framework is designed for interoperability with an optimization module; the workflow manager and optimization process run in parallel and cooperate by exchanging messages according to a specially designed protocol. A library of high-performance modules implementing signal pre-processing, misfit and adjoint computations according to established good practices is included. Monitoring is based on information stored in the inversion state database and at present implements a command line interface; design of a graphical user interface is in progress. The software design fits well into the common massively parallel system architecture featuring a large number of computational nodes running distributed applications under control of batch-oriented resource managers. The solution prototype has been implemented on the "Piz Daint" supercomputer provided by the Swiss Supercomputing Centre (CSCS).

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System.

PubMed

Li, Hongqiang; Yuan, Danyang; Wang, Youxi; Cui, Dianyin; Cao, Lu

2016-10-20

Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System

PubMed Central

Li, Hongqiang; Yuan, Danyang; Wang, Youxi; Cui, Dianyin; Cao, Lu

2016-01-01

Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias. PMID:27775596

Understanding the Key to Targeting the IGF Axis in Cancer: A Biomarker Assessment

PubMed Central

Lodhia, Kunal Amratlal; Tienchaiananda, Piyawan; Haluska, Paul

2015-01-01

Type 1 insulin like growth factor receptor (IGF-1R) targeted therapies showed compelling pre-clinical evidence; however, to date, this has failed to translate into patient benefit in Phase 2/3 trials in unselected patients. This was further complicated by the toxicity, including hyperglycemia, which largely results from the overlap between IGF and insulin signaling systems and associated feedback mechanisms. This has halted the clinical development of inhibitors targeting IGF signaling, which has limited the availability of biopsy samples for correlative studies to understand biomarkers of response. Indeed, a major factor contributing to lack of clinical benefit of IGF targeting agents has been difficulty in identifying patients with tumors driven by IGF signaling due to the lack of predictive biomarkers. In this review, we will describe the IGF system, rationale for targeting IGF signaling, the potential liabilities of targeting strategies, and potential biomarkers that may improve success. PMID:26217584

On the Teneurin track: a new synaptic organization molecule emerges

PubMed Central

Mosca, Timothy J.

2015-01-01

To achieve proper synaptic development and function, coordinated signals must pass between the pre- and postsynaptic membranes. Such transsynaptic signals can be comprised of receptors and secreted ligands, membrane associated receptors, and also pairs of synaptic cell adhesion molecules. A critical open question bridging neuroscience, developmental biology, and cell biology involves identifying those signals and elucidating how they function. Recent work in Drosophila and vertebrate systems has implicated a family of proteins, the Teneurins, as a new transsynaptic signal in both the peripheral and central nervous systems. The Teneurins have established roles in neuronal wiring, but studies now show their involvement in regulating synaptic connections between neurons and bridging the synaptic membrane and the cytoskeleton. This review will examine the Teneurins as synaptic cell adhesion molecules, explore how they regulate synaptic organization, and consider how some consequences of human Teneurin mutations may have synaptopathic origins. PMID:26074772

Methods and Systems for Advanced Spaceport Information Management

NASA Technical Reports Server (NTRS)

Fussell, Ronald M. (Inventor); Ely, Donald W. (Inventor); Meier, Gary M. (Inventor); Halpin, Paul C. (Inventor); Meade, Phillip T. (Inventor); Jacobson, Craig A. (Inventor); Blackwell-Thompson, Charlie (Inventor)

2007-01-01

Advanced spaceport information management methods and systems are disclosed. In one embodiment, a method includes coupling a test system to the payload and transmitting one or more test signals that emulate an anticipated condition from the test system to the payload. One or more responsive signals are received from the payload into the test system and are analyzed to determine whether one or more of the responsive signals comprises an anomalous signal. At least one of the steps of transmitting, receiving, analyzing and determining includes transmitting at least one of the test signals and the responsive signals via a communications link from a payload processing facility to a remotely located facility. In one particular embodiment, the communications link is an Internet link from a payload processing facility to a remotely located facility (e.g. a launch facility, university, etc.).

Methods and systems for advanced spaceport information management

NASA Technical Reports Server (NTRS)

Ely, Donald W. (Inventor); Fussell, Ronald M. (Inventor); Halpin, Paul C. (Inventor); Blackwell-Thompson, Charlie (Inventor); Meier, Gary M. (Inventor); Meade, Phillip T. (Inventor); Jacobson, Craig A. (Inventor)

2007-01-01

Advanced spaceport information management methods and systems are disclosed. In one embodiment, a method includes coupling a test system to the payload and transmitting one or more test signals that emulate an anticipated condition from the test system to the payload. One or more responsive signals are received from the payload into the test system and are analyzed to determine whether one or more of the responsive signals comprises an anomalous signal. At least one of the steps of transmitting, receiving, analyzing and determining includes transmitting at least one of the test signals and the responsive signals via a communications link from a payload processing facility to a remotely located facility. In one particular embodiment, the communications link is an Internet link from a payload processing facility to a remotely located facility (e.g. a launch facility, university, etc.).

Can you hear me yet? An intracranial investigation of speech and non-speech audiovisual interactions in human cortex.

PubMed

Rhone, Ariane E; Nourski, Kirill V; Oya, Hiroyuki; Kawasaki, Hiroto; Howard, Matthew A; McMurray, Bob

In everyday conversation, viewing a talker's face can provide information about the timing and content of an upcoming speech signal, resulting in improved intelligibility. Using electrocorticography, we tested whether human auditory cortex in Heschl's gyrus (HG) and on superior temporal gyrus (STG) and motor cortex on precentral gyrus (PreC) were responsive to visual/gestural information prior to the onset of sound and whether early stages of auditory processing were sensitive to the visual content (speech syllable versus non-speech motion). Event-related band power (ERBP) in the high gamma band was content-specific prior to acoustic onset on STG and PreC, and ERBP in the beta band differed in all three areas. Following sound onset, we found with no evidence for content-specificity in HG, evidence for visual specificity in PreC, and specificity for both modalities in STG. These results support models of audio-visual processing in which sensory information is integrated in non-primary cortical areas.

Controlled membrane translocation provides a mechanism for signal transduction and amplification

NASA Astrophysics Data System (ADS)

Langton, Matthew J.; Keymeulen, Flore; Ciaccia, Maria; Williams, Nicholas H.; Hunter, Christopher A.

2017-05-01

Transmission and amplification of chemical signals across lipid bilayer membranes is of profound significance in many biological processes, from the development of multicellular organisms to information processing in the nervous system. In biology, membrane-spanning proteins are responsible for the transmission of chemical signals across membranes, and signal transduction is often associated with an amplified signalling cascade. The ability to reproduce such processes in artificial systems has potential applications in sensing, controlled drug delivery and communication between compartments in tissue-like constructs of synthetic vesicles. Here we describe a mechanism for transmitting a chemical signal across a membrane based on the controlled translocation of a synthetic molecular transducer from one side of a lipid bilayer membrane to the other. The controlled molecular motion has been coupled to the activation of a catalyst on the inside of a vesicle, which leads to a signal-amplification process analogous to the biological counterpart.

Calibration and compensation method of three-axis geomagnetic sensor based on pre-processing total least square iteration

NASA Astrophysics Data System (ADS)

Zhou, Y.; Zhang, X.; Xiao, W.

2018-04-01

As the geomagnetic sensor is susceptible to interference, a pre-processing total least square iteration method is proposed for calibration compensation. Firstly, the error model of the geomagnetic sensor is analyzed and the correction model is proposed, then the characteristics of the model are analyzed and converted into nine parameters. The geomagnetic data is processed by Hilbert transform (HHT) to improve the signal-to-noise ratio, and the nine parameters are calculated by using the combination of Newton iteration method and the least squares estimation method. The sifter algorithm is used to filter the initial value of the iteration to ensure that the initial error is as small as possible. The experimental results show that this method does not need additional equipment and devices, can continuously update the calibration parameters, and better than the two-step estimation method, it can compensate geomagnetic sensor error well.

Tree-ring width reveals the preparation of the 1974 Mt. Etna eruption

PubMed Central

Seiler, Ruedi; Houlié, Nicolas; Cherubini, Paolo

2017-01-01

Reduced near-infrared reflectance observed in September 1973 in Skylab images of the western flank of Mt. Etna has been interpreted as an eruption precursor of the January 1974 eruption. Until now, it has been unclear when this signal started, whether it was sustained and which process(es) could have caused it. By analyzing tree-ring width time-series, we show that the reduced near-infrared precursory signal cannot be linked to a reduction in annual tree growth in the area. However, comparing the tree-ring width time-series with both remote sensing observations and volcano-seismic activity enables us to discuss the starting date of the pre-eruptive period of the 1974 eruption. PMID:28266610

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.

Rise Time Reduction of Thermal Actuators Operated in Air and Water through Optimized Pre-Shaped Open-Loop Driving.

PubMed

Larsen, T; Doll, J C; Loizeau, F; Hosseini, N; Peng, A W; Fantner, G; Ricci, A J; Pruitt, B L

2017-01-01

Electrothermal actuators have many advantages compared to other actuators used in Micro-Electro-Mechanical Systems (MEMS). They are simple to design, easy to fabricate and provide large displacements at low voltages. Low voltages enable less stringent passivation requirements for operation in liquid. Despite these advantages, thermal actuation is typically limited to a few kHz bandwidth when using step inputs due to its intrinsic thermal time constant. However, the use of pre-shaped input signals offers a route for reducing the rise time of these actuators by orders of magnitude. We started with an electrothermally actuated cantilever having an initial 10-90% rise time of 85 μs in air and 234 μs in water for a standard open-loop step input. We experimentally characterized the linearity and frequency response of the cantilever when operated in air and water, allowing us to obtain transfer functions for the two cases. We used these transfer functions, along with functions describing desired reduced rise-time system responses, to numerically simulate the required input signals. Using these pre-shaped input signals, we improved the open-loop 10-90% rise time from 85 μs to 3 μs in air and from 234 μs to 5 μs in water, an improvement by a factor of 28 and 47, respectively. Using this simple control strategy for MEMS electrothermal actuators makes them an attractive alternative to other high speed micromechanical actuators such as piezoelectric stacks or electrostatic comb structures which are more complex to design, fabricate, or operate.

Hybrid photonic signal processing

NASA Astrophysics Data System (ADS)

Ghauri, Farzan Naseer

This thesis proposes research of novel hybrid photonic signal processing systems in the areas of optical communications, test and measurement, RF signal processing and extreme environment optical sensors. It will be shown that use of innovative hybrid techniques allows design of photonic signal processing systems with superior performance parameters and enhanced capabilities. These applications can be divided into domains of analog-digital hybrid signal processing applications and free-space---fiber-coupled hybrid optical sensors. The analog-digital hybrid signal processing applications include a high-performance analog-digital hybrid MEMS variable optical attenuator that can simultaneously provide high dynamic range as well as high resolution attenuation controls; an analog-digital hybrid MEMS beam profiler that allows high-power watt-level laser beam profiling and also provides both submicron-level high resolution and wide area profiling coverage; and all optical transversal RF filters that operate on the principle of broadband optical spectral control using MEMS and/or Acousto-Optic tunable Filters (AOTF) devices which can provide continuous, digital or hybrid signal time delay and weight selection. The hybrid optical sensors presented in the thesis are extreme environment pressure sensors and dual temperature-pressure sensors. The sensors employ hybrid free-space and fiber-coupled techniques for remotely monitoring a system under simultaneous extremely high temperatures and pressures.

Towards a Standard Mixed-Signal Parallel Processing Architecture for Miniature and Microrobotics.

PubMed

Sadler, Brian M; Hoyos, Sebastian

2014-01-01

The conventional analog-to-digital conversion (ADC) and digital signal processing (DSP) architecture has led to major advances in miniature and micro-systems technology over the past several decades. The outlook for these systems is significantly enhanced by advances in sensing, signal processing, communications and control, and the combination of these technologies enables autonomous robotics on the miniature to micro scales. In this article we look at trends in the combination of analog and digital (mixed-signal) processing, and consider a generalized sampling architecture. Employing a parallel analog basis expansion of the input signal, this scalable approach is adaptable and reconfigurable, and is suitable for a large variety of current and future applications in networking, perception, cognition, and control.

Towards a Standard Mixed-Signal Parallel Processing Architecture for Miniature and Microrobotics

PubMed Central

Sadler, Brian M; Hoyos, Sebastian

2014-01-01

The conventional analog-to-digital conversion (ADC) and digital signal processing (DSP) architecture has led to major advances in miniature and micro-systems technology over the past several decades. The outlook for these systems is significantly enhanced by advances in sensing, signal processing, communications and control, and the combination of these technologies enables autonomous robotics on the miniature to micro scales. In this article we look at trends in the combination of analog and digital (mixed-signal) processing, and consider a generalized sampling architecture. Employing a parallel analog basis expansion of the input signal, this scalable approach is adaptable and reconfigurable, and is suitable for a large variety of current and future applications in networking, perception, cognition, and control. PMID:26601042

N-Channel field-effect transistors with floating gates for extracellular recordings.

PubMed

Meyburg, Sven; Goryll, Michael; Moers, Jürgen; Ingebrandt, Sven; Böcker-Meffert, Simone; Lüth, Hans; Offenhäusser, Andreas

2006-01-15

A field-effect transistor (FET) for recording extracellular signals from electrogenic cells is presented. The so-called floating gate architecture combines a complementary metal oxide semiconductor (CMOS)-type n-channel transistor with an independent sensing area. This concept allows the transistor and sensing area to be optimised separately. The devices are robust and can be reused several times. The noise level of the devices was smaller than of comparable non-metallised gate FETs. In addition to the usual drift of FET devices, we observed a long-term drift that has to be controlled for future long-term measurements. The device performance for extracellular signal recording was tested using embryonic rat cardiac myocytes cultured on fibronectin-coated chips. The extracellular cell signals were recorded before and after the addition of the cardioactive isoproterenol. The signal shapes of the measured action potentials were comparable to the non-metallised gate FETs previously used in similar experiments. The fabrication of the devices involved the process steps of standard CMOS that were necessary to create n-channel transistors. The implementation of a complete CMOS process would facilitate the integration of the logical circuits necessary for signal pre-processing on a chip, which is a prerequisite for a greater number of sensor spots in future layouts.

Chang'E-3 data pre-processing system based on scientific workflow

NASA Astrophysics Data System (ADS)

tan, xu; liu, jianjun; wang, yuanyuan; yan, wei; zhang, xiaoxia; li, chunlai

2016-04-01

The Chang'E-3(CE3) mission have obtained a huge amount of lunar scientific data. Data pre-processing is an important segment of CE3 ground research and application system. With a dramatic increase in the demand of data research and application, Chang'E-3 data pre-processing system(CEDPS) based on scientific workflow is proposed for the purpose of making scientists more flexible and productive by automating data-driven. The system should allow the planning, conduct and control of the data processing procedure with the following possibilities: • describe a data processing task, include:1)define input data/output data, 2)define the data relationship, 3)define the sequence of tasks,4)define the communication between tasks,5)define mathematical formula, 6)define the relationship between task and data. • automatic processing of tasks. Accordingly, Describing a task is the key point whether the system is flexible. We design a workflow designer which is a visual environment for capturing processes as workflows, the three-level model for the workflow designer is discussed:1) The data relationship is established through product tree.2)The process model is constructed based on directed acyclic graph(DAG). Especially, a set of process workflow constructs, including Sequence, Loop, Merge, Fork are compositional one with another.3)To reduce the modeling complexity of the mathematical formulas using DAG, semantic modeling based on MathML is approached. On top of that, we will present how processed the CE3 data with CEDPS.

Biomolecular filters for improved separation of output signals in enzyme logic systems applied to biomedical analysis.

PubMed

Halámek, Jan; Zhou, Jian; Halámková, Lenka; Bocharova, Vera; Privman, Vladimir; Wang, Joseph; Katz, Evgeny

2011-11-15

Biomolecular logic systems processing biochemical input signals and producing "digital" outputs in the form of YES/NO were developed for analysis of physiological conditions characteristic of liver injury, soft tissue injury, and abdominal trauma. Injury biomarkers were used as input signals for activating the logic systems. Their normal physiological concentrations were defined as logic-0 level, while their pathologically elevated concentrations were defined as logic-1 values. Since the input concentrations applied as logic 0 and 1 values were not sufficiently different, the output signals being at low and high values (0, 1 outputs) were separated with a short gap making their discrimination difficult. Coupled enzymatic reactions functioning as a biomolecular signal processing system with a built-in filter property were developed. The filter process involves a partial back-conversion of the optical-output-signal-yielding product, but only at its low concentrations, thus allowing the proper discrimination between 0 and 1 output values.

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.

Modelling a man-portable air-defence (MANPAD) system with a conical scan two-colour infrared (IR) seeker

NASA Astrophysics Data System (ADS)

Jackman, James; Richardson, Mark; Butters, Brian; Walmsley, Roy

2011-11-01

The use of flares of flares against 1st and 2nd generation man-portable air-defence (MANPAD) systems proved to be very effective. This naturally led to the development of counter-countermeasures (CCM) that could be incorporated into the MANPADs infrared (IR) seeker. One possible CCM is two-colour where the seeker detects in two separate IR bands. It is designed to exploit the different spectral characteristics of the target and flare. In this paper we describe the modelling process of a two-colour conical scan (conscan) IR seeker using CounterSim, a missile engagement and countermeasure simulation software tool developed by Chemring Countermeasures Ltd. It starts by explaining the signal processing needed to be able to reject the flare and track the target. The MANPAD model is then used in an engagement with a fast jet model and a transport aircraft model. Flares are first deployed reactively then released throughout an engagement to investigate the effect of flare release time and the viability of pre-emptive countermeasures.

Applying emerging digital video interface standards to airborne avionics sensor and digital map integrations: benefits outweigh the initial costs

NASA Astrophysics Data System (ADS)

Kuehl, C. Stephen

1996-06-01

Video signal system performance can be compromised in a military aircraft cockpit management system (CMS) with the tailoring of vintage Electronics Industries Association (EIA) RS170 and RS343A video interface standards. Video analog interfaces degrade when induced system noise is present. Further signal degradation has been traditionally associated with signal data conversions between avionics sensor outputs and the cockpit display system. If the CMS engineering process is not carefully applied during the avionics video and computing architecture development, extensive and costly redesign will occur when visual sensor technology upgrades are incorporated. Close monitoring and technical involvement in video standards groups provides the knowledge-base necessary for avionic systems engineering organizations to architect adaptable and extendible cockpit management systems. With the Federal Communications Commission (FCC) in the process of adopting the Digital HDTV Grand Alliance System standard proposed by the Advanced Television Systems Committee (ATSC), the entertainment and telecommunications industries are adopting and supporting the emergence of new serial/parallel digital video interfaces and data compression standards that will drastically alter present NTSC-M video processing architectures. The re-engineering of the U.S. Broadcasting system must initially preserve the electronic equipment wiring networks within broadcast facilities to make the transition to HDTV affordable. International committee activities in technical forums like ITU-R (former CCIR), ANSI/SMPTE, IEEE, and ISO/IEC are establishing global consensus on video signal parameterizations that support a smooth transition from existing analog based broadcasting facilities to fully digital computerized systems. An opportunity exists for implementing these new video interface standards over existing video coax/triax cabling in military aircraft cockpit management systems. Reductions in signal conversion processing steps, major improvement in video noise reduction, and an added capability to pass audio/embedded digital data within the digital video signal stream are the significant performance increases associated with the incorporation of digital video interface standards. By analyzing the historical progression of military CMS developments, establishing a systems engineering process for CMS design, tracing the commercial evolution of video signal standardization, adopting commercial video signal terminology/definitions, and comparing/contrasting CMS architecture modifications using digital video interfaces; this paper provides a technical explanation on how a systems engineering process approach to video interface standardization can result in extendible and affordable cockpit management systems.

Frequency-feature based antistrong-disturbance signal processing method and system for vortex flowmeter with single sensor

NASA Astrophysics Data System (ADS)

Xu, Ke-Jun; Luo, Qing-Lin; Wang, Gang; Liu, San-Shan; Kang, Yi-Bo

2010-07-01

Digital signal processing methods have been applied to vortex flowmeter for extracting the useful information from noisy output of the vortex flow sensor. But these approaches are unavailable when the power of the mechanical vibration noise is larger than that of the vortex flow signal. In order to solve this problem, an antistrong-disturbance signal processing method is proposed based on frequency features of the vortex flow signal and mechanical vibration noise for the vortex flowmeter with single sensor. The frequency bandwidth of the vortex flow signal is different from that of the mechanical vibration noise. The autocorrelation function can represent bandwidth features of the signal and noise. The output of the vortex flow sensor is processed by the spectrum analysis, filtered by bandpass filters, and calculated by autocorrelation function at the fixed delaying time and at τ =0 to obtain ratios. The frequency corresponding to the minimal ratio is regarded as the vortex flow frequency. With an ultralow-power microcontroller, a digital signal processing system is developed to implement the antistrong-disturbance algorithm, and at the same time to ensure low-power and two-wire mode for meeting the requirement of process instrumentation. The water flow-rate calibration and vibration test experiments are conducted, and the experimental results show that both the algorithm and system are effective.

Frequency-feature based antistrong-disturbance signal processing method and system for vortex flowmeter with single sensor.

PubMed

Xu, Ke-Jun; Luo, Qing-Lin; Wang, Gang; Liu, San-Shan; Kang, Yi-Bo

2010-07-01

Digital signal processing methods have been applied to vortex flowmeter for extracting the useful information from noisy output of the vortex flow sensor. But these approaches are unavailable when the power of the mechanical vibration noise is larger than that of the vortex flow signal. In order to solve this problem, an antistrong-disturbance signal processing method is proposed based on frequency features of the vortex flow signal and mechanical vibration noise for the vortex flowmeter with single sensor. The frequency bandwidth of the vortex flow signal is different from that of the mechanical vibration noise. The autocorrelation function can represent bandwidth features of the signal and noise. The output of the vortex flow sensor is processed by the spectrum analysis, filtered by bandpass filters, and calculated by autocorrelation function at the fixed delaying time and at tau=0 to obtain ratios. The frequency corresponding to the minimal ratio is regarded as the vortex flow frequency. With an ultralow-power microcontroller, a digital signal processing system is developed to implement the antistrong-disturbance algorithm, and at the same time to ensure low-power and two-wire mode for meeting the requirement of process instrumentation. The water flow-rate calibration and vibration test experiments are conducted, and the experimental results show that both the algorithm and system are effective.

An IoT-Enabled Stroke Rehabilitation System Based on Smart Wearable Armband and Machine Learning

PubMed Central

Yang, Geng; Pang, Gaoyang; Zhang, Hao; Li, Jiayi; Deng, Bin; Pang, Zhibo; Xu, Juan; Jiang, Mingzhe; Liljeberg, Pasi; Xie, Haibo; Yang, Huayong

2018-01-01

Surface electromyography signal plays an important role in hand function recovery training. In this paper, an IoT-enabled stroke rehabilitation system was introduced which was based on a smart wearable armband (SWA), machine learning (ML) algorithms, and a 3-D printed dexterous robot hand. User comfort is one of the key issues which should be addressed for wearable devices. The SWA was developed by integrating a low-power and tiny-sized IoT sensing device with textile electrodes, which can measure, pre-process, and wirelessly transmit bio-potential signals. By evenly distributing surface electrodes over user’s forearm, drawbacks of classification accuracy poor performance can be mitigated. A new method was put forward to find the optimal feature set. ML algorithms were leveraged to analyze and discriminate features of different hand movements, and their performances were appraised by classification complexity estimating algorithms and principal components analysis. According to the verification results, all nine gestures can be successfully identified with an average accuracy up to 96.20%. In addition, a 3-D printed five-finger robot hand was implemented for hand rehabilitation training purpose. Correspondingly, user’s hand movement intentions were extracted and converted into a series of commands which were used to drive motors assembled inside the dexterous robot hand. As a result, the dexterous robot hand can mimic the user’s gesture in a real-time manner, which shows the proposed system can be used as a training tool to facilitate rehabilitation process for the patients after stroke. PMID:29805919

Target-specific expression of presynaptic NMDA receptors in neocortical microcircuits.

PubMed

Buchanan, Katherine A; Blackman, Arne V; Moreau, Alexandre W; Elgar, Dale; Costa, Rui P; Lalanne, Txomin; Tudor Jones, Adam A; Oyrer, Julia; Sjöström, P Jesper

2012-08-09

Traditionally, NMDA receptors are located postsynaptically; yet, putatively presynaptic NMDA receptors (preNMDARs) have been reported. Although implicated in controlling synaptic plasticity, their function is not well understood and their expression patterns are debated. We demonstrate that, in layer 5 of developing mouse visual cortex, preNMDARs specifically control synaptic transmission at pyramidal cell inputs to other pyramidal cells and to Martinotti cells, while leaving those to basket cells unaffected. We also reveal a type of interneuron that mediates ascending inhibition. In agreement with synapse-specific expression, we find preNMDAR-mediated calcium signals in a subset of pyramidal cell terminals. A tuned network model predicts that preNMDARs specifically reroute information flow in local circuits during high-frequency firing, in particular by impacting frequency-dependent disynaptic inhibition mediated by Martinotti cells, a finding that we experimentally verify. We conclude that postsynaptic cell type determines presynaptic terminal molecular identity and that preNMDARs govern information processing in neocortical columns. Copyright © 2012 Elsevier Inc. All rights reserved.

Evaluating the Safety Profile of Non-Active Implantable Medical Devices Compared with Medicines.

PubMed

Pane, Josep; Coloma, Preciosa M; Verhamme, Katia M C; Sturkenboom, Miriam C J M; Rebollo, Irene

2017-01-01

Recent safety issues involving non-active implantable medical devices (NAIMDs) have highlighted the need for better pre-market and post-market evaluation. Some stakeholders have argued that certain features of medicine safety evaluation should also be applied to medical devices. Our objectives were to compare the current processes and methodologies for the assessment of NAIMD safety profiles with those for medicines, identify potential gaps, and make recommendations for the adoption of new methodologies for the ongoing benefit-risk monitoring of these devices throughout their entire life cycle. A literature review served to examine the current tools for the safety evaluation of NAIMDs and those for medicines. We searched MEDLINE using these two categories. We supplemented this search with Google searches using the same key terms used in the MEDLINE search. Using a comparative approach, we summarized the new product design, development cycle (preclinical and clinical phases), and post-market phases for NAIMDs and drugs. We also evaluated and compared the respective processes to integrate and assess safety data during the life cycle of the products, including signal detection, signal management, and subsequent potential regulatory actions. The search identified a gap in NAIMD safety signal generation: no global program exists that collects and analyzes adverse events and product quality issues. Data sources in real-world settings, such as electronic health records, need to be effectively identified and explored as additional sources of safety information, particularly in some areas such as the EU and USA where there are plans to implement the unique device identifier (UDI). The UDI and other initiatives will enable more robust follow-up and assessment of long-term patient outcomes. The safety evaluation system for NAIMDs differs in many ways from those for drugs, but both systems face analogous challenges with respect to monitoring real-world usage. Certain features of the drug safety evaluation process could, if adopted and adapted for NAIMDs, lead to better and more systematic evaluations of the latter.

Transfer Function Control for Biometric Monitoring System

NASA Technical Reports Server (NTRS)

Chmiel, Alan J. (Inventor); Grodinsky, Carlos M. (Inventor); Humphreys, Bradley T. (Inventor)

2015-01-01

A modular apparatus for acquiring biometric data may include circuitry operative to receive an input signal indicative of a biometric condition, the circuitry being configured to process the input signal according to a transfer function thereof and to provide a corresponding processed input signal. A controller is configured to provide at least one control signal to the circuitry to programmatically modify the transfer function of the modular system to facilitate acquisition of the biometric data.

CYCLOPS-3 System Research.

ERIC Educational Resources Information Center

Marill, Thomas; And Others

The aim of the CYCLOPS Project research is the development of techniques for allowing computers to perform visual scene analysis, pre-processing of visual imagery, and perceptual learning. Work on scene analysis and learning has previously been described. The present report deals with research on pre-processing and with further work on scene…

Shuttle orbiter radar cross-sectional analysis

NASA Technical Reports Server (NTRS)

Cooper, D. W.; James, R.

1979-01-01

Theoretical and model simulation studies on signal to noise levels and shuttle radar cross section are described. Pre-mission system calibrations, system configuration, and postmission system calibration of the tracking radars are described. Conversion of target range, azimuth, and elevation into radar centered east north vertical position coordinates are evaluated. The location of the impinging rf energy with respect to the target vehicles body axis triad is calculated. Cross section correlation between the two radars is presented.

Press fluid pre-treatment optimisation of the integrated generation of solid fuel and biogas from biomass (IFBB) process approach.

PubMed

Corton, John; Toop, Trisha; Walker, Jonathan; Donnison, Iain S; Fraser, Mariecia D

2014-10-01

The integrated generation of solid fuel and biogas from biomass (IFBB) system is an innovative approach to maximising energy conversion from low input high diversity (LIHD) biomass. In this system water pre-treated and ensiled LIHD biomass is pressed. The press fluid is anaerobically digested to produce methane that is used to power the process. The fibrous fraction is densified and then sold as a combustion fuel. Two process options designed to concentrate the press fluid were assessed to ascertain their influence on productivity in an IFBB like system: sedimentation and the omission of pre-treatment water. By concentrating press fluid and not adding water during processing, energy production from methane was increased by 75% per unit time and solid fuel productivity increased by 80% per unit of fluid produced. The additional energy requirements for pressing more biomass in order to generate equal volumes of feedstock were accounted for in these calculations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Aberrant approach-avoidance conflict resolution following repeated cocaine pre-exposure.

PubMed

Nguyen, David; Schumacher, Anett; Erb, Suzanne; Ito, Rutsuko

2015-10-01

Addiction is characterized by persistence to seek drug reinforcement despite negative consequences. Drug-induced aberrations in approach and avoidance processing likely facilitate the sustenance of addiction pathology. Currently, the effects of repeated drug exposure on the resolution of conflicting approach and avoidance motivational signals have yet to be thoroughly investigated. The present study sought to investigate the effects of cocaine pre-exposure on conflict resolution using novel approach-avoidance paradigms. We used a novel mixed-valence conditioning paradigm to condition cocaine-pre-exposed rats to associate visuo-tactile cues with either the delivery of sucrose reward or shock punishment in the arms in which the cues were presented. Following training, exploration of an arm containing a superimposition of the cues was assessed as a measure of conflict resolution behavior. We also used a mixed-valence runway paradigm wherein cocaine-pre-exposed rats traversed an alleyway toward a goal compartment to receive a pairing of sucrose reward and shock punishment. Latency to enter the goal compartment across trials was taken as a measure of motivational conflict. Our results reveal that cocaine pre-exposure attenuated learning for the aversive cue association in our conditioning paradigm and enhanced preference for mixed-valence stimuli in both paradigms. Repeated cocaine pre-exposure allows appetitive approach motivations to gain greater influence over behavioral output in the context of motivational conflict, due to aberrant positive and negative incentive motivational processing.

Enabling surface nuclear magnetic resonance at high-noise environments using a pre-polarization pulse

NASA Astrophysics Data System (ADS)

Lin, Tingting; Yang, Yujing; Teng, Fei; Müller-Petke, Mike

2018-02-01

The technique of surface nuclear magnetic resonance (SNMR) has been widely used for hydrological investigations in recent years. Unfortunately, the detected SNMR signals are limited to tens of nanovolts and are thus susceptible to environmental noise. While pre-polarization pulses to enhance the detected signal amplitudes are common in laboratory applications, SNMR field testing has only utilized excitation pulses until now. In conducting measurements in China, we demonstrate that adding a pre-polarization field to the SNMR pulse sequence is feasible and allows for the reliable detection of SNMR signals in noisy scenarios that otherwise prohibit signal detection. We introduce a forward modelling for pre-polarization using SNMR and present a three-layer model obtained from inverse modelling that satisfies the observed data from the field experiment. We expect this development to open up new applications for SNMR technology, especially in high-noise level places, such as active mines.

Remote, non-contacting personnel bio-identification using microwave radiation

NASA Technical Reports Server (NTRS)

McGrath, William R. (Inventor); Talukder, Ashit (Inventor)

2011-01-01

A system to remotely identify a person by utilizing a microwave cardiogram, where some embodiments segment a signal representing cardiac beats into segments, extract features from the segments, and perform pattern identification of the segments and features with a pre-existing data set. Other embodiments are described and claimed.

Biosignals learning and synthesis using deep neural networks.

PubMed

Belo, David; Rodrigues, João; Vaz, João R; Pezarat-Correia, Pedro; Gamboa, Hugo

2017-09-25

Modeling physiological signals is a complex task both for understanding and synthesize biomedical signals. We propose a deep neural network model that learns and synthesizes biosignals, validated by the morphological equivalence of the original ones. This research could lead the creation of novel algorithms for signal reconstruction in heavily noisy data and source detection in biomedical engineering field. The present work explores the gated recurrent units (GRU) employed in the training of respiration (RESP), electromyograms (EMG) and electrocardiograms (ECG). Each signal is pre-processed, segmented and quantized in a specific number of classes, corresponding to the amplitude of each sample and fed to the model, which is composed by an embedded matrix, three GRU blocks and a softmax function. This network is trained by adjusting its internal parameters, acquiring the representation of the abstract notion of the next value based on the previous ones. The simulated signal was generated by forecasting a random value and re-feeding itself. The resulting generated signals are similar with the morphological expression of the originals. During the learning process, after a set of iterations, the model starts to grasp the basic morphological characteristics of the signal and later their cyclic characteristics. After training, these models' prediction are closer to the signals that trained them, specially the RESP and ECG. This synthesis mechanism has shown relevant results that inspire the use to characterize signals from other physiological sources.

Signal processing: opportunities for superconductive circuits

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

Ralston, R.W.

1985-03-01

Prime motivators in the evolution of increasingly sophisticated communication and detection systems are the needs for handling ever wider signal bandwidths and higher data-processing speeds. These same needs drive the development of electronic device technology. Until recently the superconductive community has been tightly focused on digital devices for high speed computers. The purpose of this paper is to describe opportunities and challenges which exist for both analog and digital devices in a less familiar area, that of wideband signal processing. The function and purpose of analog signal-processing components, including matched filters, correlators and Fourier transformers, will be described and examplesmore » of superconductive implementations given. A canonic signal-processing system is then configured using these components and digital output circuits to highlight the important issues of dynamic range, accuracy and equivalent computation rate. (Reprints)« less

Robust real-time extraction of respiratory signals from PET list-mode data.

PubMed

Salomon, Andre; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-05-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions' detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting ("binning") of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signalsdirectly from the acquired PET data simplifies the clinical workflow as it avoids to handle additional signal measurement equipment. We introduce a new data-driven method "Combined Local Motion Detection" (CLMD). It uses the Time-of-Flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using 7 measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware. © 2018 Institute of Physics and Engineering in Medicine.

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.

Acoustic Signal Processing in Photorefractive Optical Systems.

NASA Astrophysics Data System (ADS)

Zhou, Gan

This thesis discusses applications of the photorefractive effect in the context of acoustic signal processing. The devices and systems presented here illustrate the ideas and optical principles involved in holographic processing of acoustic information. The interest in optical processing stems from the similarities between holographic optical systems and contemporary models for massively parallel computation, in particular, neural networks. An initial step in acoustic processing is the transformation of acoustic signals into relevant optical forms. A fiber-optic transducer with photorefractive readout transforms acoustic signals into optical images corresponding to their short-time spectrum. The device analyzes complex sound signals and interfaces them with conventional optical correlators. The transducer consists of 130 multimode optical fibers sampling the spectral range of 100 Hz to 5 kHz logarithmically. A physical model of the human cochlea can help us understand some characteristics of human acoustic transduction and signal representation. We construct a life-sized cochlear model using elastic membranes coupled with two fluid-filled chambers, and use a photorefractive novelty filter to investigate its response. The detection sensitivity is determined to be 0.3 angstroms per root Hz at 2 kHz. Qualitative agreement is found between the model response and physiological data. Delay lines map time-domain signals into space -domain and permit holographic processing of temporal information. A parallel optical delay line using dynamic beam coupling in a rotating photorefractive crystal is presented. We experimentally demonstrate a 64 channel device with 0.5 seconds of time-delay and 167 Hz bandwidth. Acoustic signal recognition is described in a photorefractive system implementing the time-delay neural network model. The system consists of a photorefractive optical delay-line and a holographic correlator programmed in a LiNbO_3 crystal. We demonstrate the recognition of synthesized chirps as well as spoken words. A photorefractive ring resonator containing an optical delay line can learn temporal information through self-organization. We experimentally investigate a system that learns by itself and picks out the most-frequently -presented signals from the input. We also give results demonstrating the separation of two orthogonal temporal signals into two competing ring resonators.

Continuous detection of the self-initiated walking pre-movement state from EEG correlates without session-to-session recalibration

NASA Astrophysics Data System (ADS)

Ioana Sburlea, Andreea; Montesano, Luis; Minguez, Javier

2015-06-01

Objective. Brain-computer interfaces (BCI) as a rehabilitation tool have been used to restore functions in patients with motor impairments by actively involving the central nervous system and triggering prosthetic devices according to the detected pre-movement state. However, since EEG signals are highly variable between subjects and recording sessions, typically a BCI is calibrated at the beginning of each session. This process is inconvenient especially for patients suffering locomotor disabilities in maintaining a bipedal position for a longer time. This paper presents a continuous EEG decoder of a pre-movement state in self-initiated walking and the usage of this decoder from session to session without recalibrating. Approach. Ten healthy subjects performed a self-initiated walking task during three sessions, with an intersession interval of one week. The implementation of our continuous decoder is based on the combination of movement-related cortical potential (MRCP) and event-related desynchronization (ERD) features with sparse classification models. Main results. During intrasession our technique detects the pre-movement state with 70% accuracy. Moreover this decoder can be applied from session to session without recalibration, with a decrease in performance of about 4% on a one- or two-week intersession interval. Significance. Our detection model operates in a continuous manner, which makes it a straightforward asset for rehabilitation scenarios. By using both temporal and spectral information we attained higher detection rates than the ones obtained with the MRCP and ERD detection models, both during the intrasession and intersession conditions.

Geomagnetic signal induced by the M5.7 earthquake occurred on September 24-th, 2016, in the seismic active Vrancea zone, Romania

NASA Astrophysics Data System (ADS)

Stanica, Dumitru; Armand Stanica, Dragos

2017-04-01

In this paper, we used the geomagnetic time series collected in real time by the electromagnetic monitoring system, placed at the Geomagnetic Observatory Provita de Sus, to emphasize possible relationships between the pre-seismic anomalous behavior of the normalized function Bzn and M5.7 earthquake occurrence in Vrancea seismic active zone, on September 24, 2016. It has already been demonstrated (Stanica and Stanica, 2012, Stanica et al., 2015) that for a 2D geoelectric structure, in pre-seismic conditions, the normalized function Bzn has significant changes in magnitudes due to the electrical conductivity changes, possibly associated with the earthquake-induced rupture-processes and high-pressure fluid flow through the faulting systems developed inside the Vrancea seismogenic volume and along the Carpathian electrical conductivity anomaly. In this circumstances, the daily mean distributions of the Bzn = Bz/Bperp (where Bz is vertical component of the geomagnetic field; Bperp is geomagnetic component perpendicular to the geoelectric strike) and its standard deviation (SD) are performed in the ULF frequency range 0.001Hz to 0.0083Hz by using both the FFT band-pass filter analysis and statistical analysis based on a standardized random variable equation. After analyzing the pre-seismic anomalous intervals, a pre-seismic geomagnetic signal greater than 5 SD was identified on September 22, 2016, what means a lead time of 2 days before the M5.7 earthquake occurred on September 24, emphasized in real time on the web site (www.geodin.ro). The final conclusion is that the proposed geomagnetic methodology might be used to provide suitable information for the extreme seismic hazard assessment and risk mitigation. References: Dumitru Stanica and Dragos Armand Stanica, Earthquakes precursors, in "Earthquake Research and Analysis-Statistical Studies, Observations and Planning" Book 5, edited by: Dr. Sebastiano D'Amico, ISBN 978-953-51-0134-5, InTech open access publisher, Chapter 4, 71-100, 2012 Dragos Armand Stanica, Dumitru Stanica, Nicoleta Vladimirescu, Long-range anomalous electromagnetic effect related to M9 Great Tohoku earthquake, Earth Sciences. Vol. 4, No. 1, 2015, pp. 31-38, http://www.sciencepublishinggroup.com/j/earth, doi: 10.11648/j.earth.20150401.13

An Interactive Graphics Program for Investigating Digital Signal Processing.

ERIC Educational Resources Information Center

Miller, Billy K.; And Others

1983-01-01

Describes development of an interactive computer graphics program for use in teaching digital signal processing. The program allows students to interactively configure digital systems on a monitor display and observe their system's performance by means of digital plots on the system's outputs. A sample program run is included. (JN)

The importance of pre-annealing treatment for ESR dating of mollusc shells: A key study for İsmil in Konya closed Basin/Turkey

NASA Astrophysics Data System (ADS)

Ekici, Gamze; Sayin, Ulku; Aydin, Hulya; Isik, Mesut; Kapan, Sevinc; Demir, Ahmet; Engin, Birol; Delikan, Arif; Orhan, Hukmu; Biyik, Recep; Ozmen, Ayhan

2018-02-01

In this study, Electron Spin Resonance (ESR) spectroscopy is used to determine the geological ages of fossil mollusc shells systematically collected from two different geological splitting at İsmil Location (37.72769° N, 33.17781° E) in eastern part of Konya. According to the assessment of obtained ESR ages, the importance of pre-annealing treatment emphasize in the case of g=2.0007 dating signal is overlapped with the other signals arisen from short lived radicals that cause the wrong age calculation. To overcome this problem, the samples are pre-annealed at 180°C for 16 minutes and, in this case ESR ages are re-calculated for g=1.9973 dating signal. Dose response curves are obtained using 1.9973 signals after pre-annealing treatments for each samples. ESR ages of samples are obtained in the range of 138 ± 38 ka and 132 ± 30 ka (Upper Pleistocene) according to the Early Uranium Uptake model and the results are in good agreement with the estimated ages from stratigraphic and paleontological correlation by geologists. Thus, it is suggested that especially in the case of 2.0007 dating signal cannot been used due to superimposition case, the signal with 1.9973 g value can be used for dating after pre-annealing treatment. The results reports the first ESR ages on shells collected from İsmil Location and highlight the importance of pre-annealing treatment. This study is supported by TUBITAK 114Y237 research project.

Weak Defect Identification for Centrifugal Compressor Blade Crack Based on Pressure Sensors and Genetic Algorithm.

PubMed

Li, Hongkun; He, Changbo; Malekian, Reza; Li, Zhixiong

2018-04-19

The Centrifugal compressor is a piece of key equipment for petrochemical factories. As the core component of a compressor, the blades suffer periodic vibration and flow induced excitation mechanism, which will lead to the occurrence of crack defect. Moreover, the induced blade defect usually has a serious impact on the normal operation of compressors and the safety of operators. Therefore, an effective blade crack identification method is particularly important for the reliable operation of compressors. Conventional non-destructive testing and evaluation (NDT&E) methods can detect the blade defect effectively, however, the compressors should shut down during the testing process which is time-consuming and costly. In addition, it can be known these methods are not suitable for the long-term on-line condition monitoring and cannot identify the blade defect in time. Therefore, the effective on-line condition monitoring and weak defect identification method should be further studied and proposed. Considering the blade vibration information is difficult to measure directly, pressure sensors mounted on the casing are used to sample airflow pressure pulsation signal on-line near the rotating impeller for the purpose of monitoring the blade condition indirectly in this paper. A big problem is that the blade abnormal vibration amplitude induced by the crack is always small and this feature information will be much weaker in the pressure signal. Therefore, it is usually difficult to identify blade defect characteristic frequency embedded in pressure pulsation signal by general signal processing methods due to the weakness of the feature information and the interference of strong noise. In this paper, continuous wavelet transform (CWT) is used to pre-process the sampled signal first. Then, the method of bistable stochastic resonance (SR) based on Woods-Saxon and Gaussian (WSG) potential is applied to enhance the weak characteristic frequency contained in the pressure pulsation signal. Genetic algorithm (GA) is used to obtain optimal parameters for this SR system to improve its feature enhancement performance. The analysis result of experimental signal shows the validity of the proposed method for the enhancement and identification of weak defect characteristic. In the end, strain test is carried out to further verify the accuracy and reliability of the analysis result obtained by pressure pulsation signal.

Weak Defect Identification for Centrifugal Compressor Blade Crack Based on Pressure Sensors and Genetic Algorithm

PubMed Central

Li, Hongkun; He, Changbo

2018-01-01

The Centrifugal compressor is a piece of key equipment for petrochemical factories. As the core component of a compressor, the blades suffer periodic vibration and flow induced excitation mechanism, which will lead to the occurrence of crack defect. Moreover, the induced blade defect usually has a serious impact on the normal operation of compressors and the safety of operators. Therefore, an effective blade crack identification method is particularly important for the reliable operation of compressors. Conventional non-destructive testing and evaluation (NDT&E) methods can detect the blade defect effectively, however, the compressors should shut down during the testing process which is time-consuming and costly. In addition, it can be known these methods are not suitable for the long-term on-line condition monitoring and cannot identify the blade defect in time. Therefore, the effective on-line condition monitoring and weak defect identification method should be further studied and proposed. Considering the blade vibration information is difficult to measure directly, pressure sensors mounted on the casing are used to sample airflow pressure pulsation signal on-line near the rotating impeller for the purpose of monitoring the blade condition indirectly in this paper. A big problem is that the blade abnormal vibration amplitude induced by the crack is always small and this feature information will be much weaker in the pressure signal. Therefore, it is usually difficult to identify blade defect characteristic frequency embedded in pressure pulsation signal by general signal processing methods due to the weakness of the feature information and the interference of strong noise. In this paper, continuous wavelet transform (CWT) is used to pre-process the sampled signal first. Then, the method of bistable stochastic resonance (SR) based on Woods-Saxon and Gaussian (WSG) potential is applied to enhance the weak characteristic frequency contained in the pressure pulsation signal. Genetic algorithm (GA) is used to obtain optimal parameters for this SR system to improve its feature enhancement performance. The analysis result of experimental signal shows the validity of the proposed method for the enhancement and identification of weak defect characteristic. In the end, strain test is carried out to further verify the accuracy and reliability of the analysis result obtained by pressure pulsation signal. PMID:29671821

A New Statistics-Based Online Baseline Restorer for a High Count-Rate Fully Digital System.

PubMed

Li, Hongdi; Wang, Chao; Baghaei, Hossain; Zhang, Yuxuan; Ramirez, Rocio; Liu, Shitao; An, Shaohui; Wong, Wai-Hoi

2010-04-01

The goal of this work is to develop a novel, accurate, real-time digital baseline restorer using online statistical processing for a high count-rate digital system such as positron emission tomography (PET). In high count-rate nuclear instrumentation applications, analog signals are DC-coupled for better performance. However, the detectors, pre-amplifiers and other front-end electronics would cause a signal baseline drift in a DC-coupling system, which will degrade the performance of energy resolution and positioning accuracy. Event pileups normally exist in a high-count rate system and the baseline drift will create errors in the event pileup-correction. Hence, a baseline restorer (BLR) is required in a high count-rate system to remove the DC drift ahead of the pileup correction. Many methods have been reported for BLR from classic analog methods to digital filter solutions. However a single channel BLR with analog method can only work under 500 kcps count-rate, and normally an analog front-end application-specific integrated circuits (ASIC) is required for the application involved hundreds BLR such as a PET camera. We have developed a simple statistics-based online baseline restorer (SOBLR) for a high count-rate fully digital system. In this method, we acquire additional samples, excluding the real gamma pulses, from the existing free-running ADC in the digital system, and perform online statistical processing to generate a baseline value. This baseline value will be subtracted from the digitized waveform to retrieve its original pulse with zero-baseline drift. This method can self-track the baseline without a micro-controller involved. The circuit consists of two digital counter/timers, one comparator, one register and one subtraction unit. Simulation shows a single channel works at 30 Mcps count-rate with pileup condition. 336 baseline restorer circuits have been implemented into 12 field-programmable-gate-arrays (FPGA) for our new fully digital PET system.

Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems.

PubMed

Gao, Lei; Bourke, A K; Nelson, John

2014-06-01

Physical activity has a positive impact on people's well-being and it had been shown to decrease the occurrence of chronic diseases in the older adult population. To date, a substantial amount of research studies exist, which focus on activity recognition using inertial sensors. Many of these studies adopt a single sensor approach and focus on proposing novel features combined with complex classifiers to improve the overall recognition accuracy. In addition, the implementation of the advanced feature extraction algorithms and the complex classifiers exceed the computing ability of most current wearable sensor platforms. This paper proposes a method to adopt multiple sensors on distributed body locations to overcome this problem. The objective of the proposed system is to achieve higher recognition accuracy with "light-weight" signal processing algorithms, which run on a distributed computing based sensor system comprised of computationally efficient nodes. For analysing and evaluating the multi-sensor system, eight subjects were recruited to perform eight normal scripted activities in different life scenarios, each repeated three times. Thus a total of 192 activities were recorded resulting in 864 separate annotated activity states. The methods for designing such a multi-sensor system required consideration of the following: signal pre-processing algorithms, sampling rate, feature selection and classifier selection. Each has been investigated and the most appropriate approach is selected to achieve a trade-off between recognition accuracy and computing execution time. A comparison of six different systems, which employ single or multiple sensors, is presented. The experimental results illustrate that the proposed multi-sensor system can achieve an overall recognition accuracy of 96.4% by adopting the mean and variance features, using the Decision Tree classifier. The results demonstrate that elaborate classifiers and feature sets are not required to achieve high recognition accuracies on a multi-sensor system. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Lateral position detection and control for friction stir systems

DOEpatents

Fleming, Paul; Lammlein, David; Cook, George E.; Wilkes, Don Mitchell; Strauss, Alvin M.; Delapp, David; Hartman, Daniel A.

2010-12-14

A friction stir system for processing at least a first workpiece includes a spindle actuator coupled to a rotary tool comprising a rotating member for contacting and processing the first workpiece. A detection system is provided for obtaining information related to a lateral alignment of the rotating member. The detection system comprises at least one sensor for measuring a force experienced by the rotary tool or a parameter related to the force experienced by the rotary tool during processing, wherein the sensor provides sensor signals. A signal processing system is coupled to receive and analyze the sensor signals and determine a lateral alignment of the rotating member relative to a selected lateral position, a selected path, or a direction to decrease a lateral distance relative to the selected lateral position or selected path. In one embodiment, the friction stir system can be embodied as a closed loop tracking system, such as a robot-based tracked friction stir welding (FSW) or friction stir processing (FSP) system.

BPSK Demodulation Using Digital Signal Processing

NASA Technical Reports Server (NTRS)

Garcia, Thomas R.

1996-01-01

A digital communications signal is a sinusoidal waveform that is modified by a binary (digital) information signal. The sinusoidal waveform is called the carrier. The carrier may be modified in amplitude, frequency, phase, or a combination of these. In this project a binary phase shift keyed (BPSK) signal is the communication signal. In a BPSK signal the phase of the carrier is set to one of two states, 180 degrees apart, by a binary (i.e., 1 or 0) information signal. A digital signal is a sampled version of a "real world" time continuous signal. The digital signal is generated by sampling the continuous signal at discrete points in time. The rate at which the signal is sampled is called the sampling rate (f(s)). The device that performs this operation is called an analog-to-digital (A/D) converter or a digitizer. The digital signal is composed of the sequence of individual values of the sampled BPSK signal. Digital signal processing (DSP) is the modification of the digital signal by mathematical operations. A device that performs this processing is called a digital signal processor. After processing, the digital signal may then be converted back to an analog signal using a digital-to-analog (D/A) converter. The goal of this project is to develop a system that will recover the digital information from a BPSK signal using DSP techniques. The project is broken down into the following steps: (1) Development of the algorithms required to demodulate the BPSK signal; (2) Simulation of the system; and (3) Implementation a BPSK receiver using digital signal processing hardware.

Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

NASA Astrophysics Data System (ADS)

Winda, A.; Sofyan; Sthevany; Vincent, R. S.

2017-12-01

Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

78 FR 21930 - Aquenergy Systems, Inc.; Notice of Intent To File License Application, Filing of Pre-Application...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-12

... Systems, Inc.; Notice of Intent To File License Application, Filing of Pre-Application Document, and Approving Use of the Traditional Licensing Process a. Type of Filing: Notice of Intent to File License...: November 11, 2012. d. Submitted by: Aquenergy Systems, Inc., a fully owned subsidiaries of Enel Green Power...

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Zinc oxide nanoflowers make new blood vessels

NASA Astrophysics Data System (ADS)

Barui, Ayan Kumar; Veeriah, Vimal; Mukherjee, Sudip; Manna, Joydeb; Patel, Ajay Kumar; Patra, Sujata; Pal, Krishnendu; Murali, Shruthi; Rana, Rohit K.; Chatterjee, Suvro; Patra, Chitta Ranjan

2012-11-01

It is well established that angiogenesis is the process of formation of new capillaries from pre-existing blood vessels. It is a complex process, involving both pro- and anti-angiogenic factors, and plays a significant role in physiological and pathophysiological processes such as embryonic development, atherosclerosis, post-ischemic vascularization of the myocardium, tumor growth and metastasis, rheumatoid arthritis etc. This is the first report of zinc oxide (ZnO) nanoflowers that show significant pro-angiogenic properties (formation of new capillaries from pre-existing blood vessels), observed by in vitro and in vivo angiogenesis assays. The egg yolk angiogenesis assay using ZnO nanoflowers indicates the presence of matured blood vessels formation. Additionally, it helps to promote endothelial cell (EA.hy926 cells) migration in wound healing assays. Formation of reactive oxygen species (ROS), especially hydrogen peroxide (H2O2)--a redox signaling molecule, might be the plausible mechanism for nanoflower-based angiogenesis. Angiogenesis by nanoflowers may provide the basis for the future development of new alternative therapeutic treatment strategies for cardiovascular and ischemic diseases, where angiogenesis plays a significant role.It is well established that angiogenesis is the process of formation of new capillaries from pre-existing blood vessels. It is a complex process, involving both pro- and anti-angiogenic factors, and plays a significant role in physiological and pathophysiological processes such as embryonic development, atherosclerosis, post-ischemic vascularization of the myocardium, tumor growth and metastasis, rheumatoid arthritis etc. This is the first report of zinc oxide (ZnO) nanoflowers that show significant pro-angiogenic properties (formation of new capillaries from pre-existing blood vessels), observed by in vitro and in vivo angiogenesis assays. The egg yolk angiogenesis assay using ZnO nanoflowers indicates the presence of matured blood vessels formation. Additionally, it helps to promote endothelial cell (EA.hy926 cells) migration in wound healing assays. Formation of reactive oxygen species (ROS), especially hydrogen peroxide (H2O2)--a redox signaling molecule, might be the plausible mechanism for nanoflower-based angiogenesis. Angiogenesis by nanoflowers may provide the basis for the future development of new alternative therapeutic treatment strategies for cardiovascular and ischemic diseases, where angiogenesis plays a significant role. Electronic supplementary information (ESI) available: See DOI: 10.1039/c2nr32369a

The rhythms of predictive coding? Pre-stimulus phase modulates the influence of shape perception on luminance judgments

PubMed Central

Han, Biao; VanRullen, Rufin

2017-01-01

Predictive coding is an influential model emphasizing interactions between feedforward and feedback signals. Here, we investigated the temporal dynamics of these interactions. Two gray disks with different versions of the same stimulus, one enabling predictive feedback (a 3D-shape) and one impeding it (random-lines), were simultaneously presented on the left and right of fixation. Human subjects judged the luminance of the two disks while EEG was recorded. The choice of 3D-shape or random-lines as the brighter disk was used to assess the influence of feedback signals on sensory processing in each trial (i.e., as a measure of post-stimulus predictive coding efficiency). Independently of the spatial response (left/right), we found that this choice fluctuated along with the pre-stimulus phase of two spontaneous oscillations: a ~5 Hz oscillation in contralateral frontal electrodes and a ~16 Hz oscillation in contralateral occipital electrodes. This pattern of results demonstrates that predictive coding is a rhythmic process, and suggests that it could take advantage of faster oscillations in low-level areas and slower oscillations in high-level areas. PMID:28262824

Eye growth and myopia development: Unifying theory and Matlab model.

PubMed

Hung, George K; Mahadas, Kausalendra; Mohammad, Faisal

2016-03-01

The aim of this article is to present an updated unifying theory of the mechanisms underlying eye growth and myopia development. A series of model simulation programs were developed to illustrate the mechanism of eye growth regulation and myopia development. Two fundamental processes are presumed to govern the relationship between physiological optics and eye growth: genetically pre-programmed signaling and blur feedback. Cornea/lens is considered to have only a genetically pre-programmed component, whereas eye growth is considered to have both a genetically pre-programmed and a blur feedback component. Moreover, based on the Incremental Retinal-Defocus Theory (IRDT), the rate of change of blur size provides the direction for blur-driven regulation. The various factors affecting eye growth are shown in 5 simulations: (1 - unregulated eye growth): blur feedback is rendered ineffective, as in the case of form deprivation, so there is only genetically pre-programmed eye growth, generally resulting in myopia; (2 - regulated eye growth): blur feedback regulation demonstrates the emmetropization process, with abnormally excessive or reduced eye growth leading to myopia and hyperopia, respectively; (3 - repeated near-far viewing): simulation of large-to-small change in blur size as seen in the accommodative stimulus/response function, and via IRDT as well as nearwork-induced transient myopia (NITM), leading to the development of myopia; (4 - neurochemical bulk flow and diffusion): release of dopamine from the inner plexiform layer of the retina, and the subsequent diffusion and relay of neurochemical cascade show that a decrease in dopamine results in a reduction of proteoglycan synthesis rate, which leads to myopia; (5 - Simulink model): model of genetically pre-programmed signaling and blur feedback components that allows for different input functions to simulate experimental manipulations that result in hyperopia, emmetropia, and myopia. These model simulation programs (available upon request) can provide a useful tutorial for the general scientist and serve as a quantitative tool for researchers in eye growth and myopia. Copyright © 2016 Elsevier Ltd. All rights reserved.

Non-stationary pre-envelope covariances of non-classically damped systems

NASA Astrophysics Data System (ADS)

Muscolino, G.

1991-08-01

A new formulation is given to evaluate the stationary and non-stationary response of linear non-classically damped systems subjected to multi-correlated non-separable Gaussian input processes. This formulation is based on a new and more suitable definition of the impulse response function matrix for such systems. It is shown that, when using this definition, the stochastic response of non-classically damped systems involves the evaluation of quantities similar to those of classically damped ones. Furthermore, considerations about non-stationary cross-covariances, spectral moments and pre-envelope cross-covariances are presented for a monocorrelated input process.

Design and Performance of the Astro-E/XRS Signal Processing System

NASA Technical Reports Server (NTRS)

Boyce, Kevin R.; Audley, M. D.; Baker, R. G.; Dumonthier, J. J.; Fujimoto, R.; Gendreau, K. C.; Ishisaki, Y.; Kelley, R. L.; Stahle, C. K.; Szymkowiak, A. E.

1999-01-01

We describe the signal processing system of the Astro-E XRS instrument. The Calorimeter Analog Processor (CAP) provides bias and power for the detectors and amplifies the detector signals by a factor of 20,000. The Calorimeter Digital Processor (CDP) performs the digital processing of the calorimeter signals, detecting X-ray pulses and analyzing them by optimal filtering. We describe the operation of pulse detection, Pulse height analysis. and risetime determination. We also discuss performance, including the three event grades (hi-res mid-res, and low-res). anticoincidence detection, counting rate dependence, and noise rejection.

An eye movement pre-training fosters the comprehension of processes and functions in technical systems

PubMed Central

Skuballa, Irene T.; Fortunski, Caroline; Renkl, Alexander

2015-01-01

The main research goal of the present study was to investigate in how far pre-training eye movements can facilitate knowledge acquisition in multimedia (pre-training principle). We combined considerations from research on eye movement modeling and pre-training to design and test a non-verbal eye movement-based pre-training. Participants in the experimental condition watched an animated circle moving in close spatial resemblance to a static visualization of a solar plant accompanied by a narration in a subsequently presented learning environment. This training was expected to foster top-down processes as reflected in gaze behavior during the learning process and enhance knowledge acquisition. We compared two groups (N = 45): participants in the experimental condition received pre-training in a first step and processed the learning material in a second step, whereas the control group underwent the second step without any pre-training. The pre-training group outperformed the control group in their learning outcomes, particularly in knowledge about processes and functions of the solar plant. However, the superior learning outcomes in the pre-training group could not be explained by eye-movement patterns. Furthermore, the pre-training moderated the relationship between experienced stress and learning outcomes. In the control group, high stress levels hindered learning, which was not found for the pre-training group. On a delayed posttest participants were requested to draw a picture of the learning content. Despite a non-significant effect of training on the quality of drawings, the pre-training showed associations between learning outcomes at the first testing time and process-related aspects in the quality of their drawings. Overall, non-verbal pre-training is a successful instructional intervention to promote learning processes in novices although these processes did not directly reflect in learners' eye movement behavior during learning. PMID:26029138

Signal processing in an acousto-optical spectral colorimeter

NASA Astrophysics Data System (ADS)

Emeljanov, Sergey P.; Kludzin, Victor V.; Kochin, Leonid B.; Medvedev, Sergey V.; Polosin, Lev L.; Sokolov, Vladimir K.

2002-02-01

The algorithms of spectrometer signals processing in the acousto-optical spectral colorimeter, proposed earlier are discussed. This processing is directional on distortion elimination of an optical system spectral characteristics and photoelectric transformations, and also for calculation of tristimulus coefficients X,Y,Z in an international colorimetric system of a CIE - 31 and transformation them in coordinates of recommended CIE uniform contrast systems LUV and LAB.

Zero-forcing pre-coding for MIMO WiMAX transceivers: Performance analysis and implementation issues

NASA Astrophysics Data System (ADS)

Cattoni, A. F.; Le Moullec, Y.; Sacchi, C.

Next generation wireless communication networks are expected to achieve ever increasing data rates. Multi-User Multiple-Input-Multiple-Output (MU-MIMO) is a key technique to obtain the expected performance, because such a technique combines the high capacity achievable using MIMO channel with the benefits of space division multiple access. In MU-MIMO systems, the base stations transmit signals to two or more users over the same channel, for this reason every user can experience inter-user interference. This paper provides a capacity analysis of an online, interference-based pre-coding algorithm able to mitigate the multi-user interference of the MU-MIMO systems in the context of a realistic WiMAX application scenario. Simulation results show that pre-coding can significantly increase the channel capacity. Furthermore, the paper presents several feasibility considerations for implementation of the analyzed technique in a possible FPGA-based software defined radio.

Regulation of Bone Metabolism by Serotonin.

PubMed

Lavoie, Brigitte; Lian, Jane B; Mawe, Gary M

2017-01-01

The processes of bone growth and turnover are tightly regulated by the actions of various signaling molecules, including hormones, growth factors, and cytokines. Imbalances in these processes can lead to skeletal disorders such as osteoporosis or high bone mass disease. It is becoming increasingly clear that serotonin can act through a number of mechanisms, and at different locations in the body, to influence the balance between bone formation and resorption. Its actions on bone metabolism can vary, based on its site of synthesis (central or peripheral) as well as the cells and subtypes of receptors that are activated. Within the central nervous system, serotonergic neurons act via the hypothalamus to suppress sympathetic input to the bone. Since sympathetic input inhibits bone formation, brain serotonin has a net positive effect on bone growth. Gut-derived serotonin is thought to inhibit bone growth by attenuating osteoblast proliferation via activation of receptors on pre-osteoblasts. There is also evidence that serotonin can be synthesized within the bone and act to modulate bone metabolism. Osteoblasts, osteoclasts, and osteocytes all have the machinery to synthesize serotonin, and they also express the serotonin-reuptake transporter (SERT). Understanding the roles of serotonin in the tightly balanced system of bone modeling and remodeling is a clinically relevant goal. This knowledge can clarify bone-related side effects of drugs that affect serotonin signaling, including serotonin-specific reuptake inhibitors (SSRIs) and receptor agonists and antagonists, and it can potentially lead to therapeutic approaches for alleviating bone pathologies.

Interactions between pre-processing and classification methods for event-related-potential classification: best-practice guidelines for brain-computer interfacing.

PubMed

Farquhar, J; Hill, N J

2013-04-01

Detecting event related potentials (ERPs) from single trials is critical to the operation of many stimulus-driven brain computer interface (BCI) systems. The low strength of the ERP signal compared to the noise (due to artifacts and BCI irrelevant brain processes) makes this a challenging signal detection problem. Previous work has tended to focus on how best to detect a single ERP type (such as the visual oddball response). However, the underlying ERP detection problem is essentially the same regardless of stimulus modality (e.g., visual or tactile), ERP component (e.g., P300 oddball response, or the error-potential), measurement system or electrode layout. To investigate whether a single ERP detection method might work for a wider range of ERP BCIs we compare detection performance over a large corpus of more than 50 ERP BCI datasets whilst systematically varying the electrode montage, spectral filter, spatial filter and classifier training methods. We identify an interesting interaction between spatial whitening and regularised classification which made detection performance independent of the choice of spectral filter low-pass frequency. Our results show that pipeline consisting of spectral filtering, spatial whitening, and regularised classification gives near maximal performance in all cases. Importantly, this pipeline is simple to implement and completely automatic with no expert feature selection or parameter tuning required. Thus, we recommend this combination as a "best-practice" method for ERP detection problems.