Extraction of the respiratory signal from small-animal CT projections for a retrospective gating method

International Nuclear Information System (INIS)

ChavarrIas, C; Vaquero, J J; Sisniega, A; RodrIguez-Ruano, A; Soto-Montenegro, M L; GarcIa-Barreno, P; Desco, M

2008-01-01

We propose a retrospective respiratory gating algorithm to generate dynamic CT studies. To this end, we compared three different methods of extracting the respiratory signal from the projections of small-animal cone-beam computed tomography (CBCT) scanners. Given a set of frames acquired from a certain axial angle, subtraction of their average image from each individual frame produces a set of difference images. Pixels in these images have positive or negative values (according to the respiratory phase) in those areas where there is lung movement. The respiratory signals were extracted by analysing the shape of the histogram of these difference images: we calculated the first four central and non-central moments. However, only odd-order moments produced the desired breathing signal, as the even-order moments lacked information about the phase. Each of these curves was compared to a reference signal recorded by means of a pneumatic pillow. Given the similar correlation coefficients yielded by all of them, we selected the mean to implement our retrospective protocol. Respiratory phase bins were separated, reconstructed independently and included in a dynamic sequence, suitable for cine playback. We validated our method in five adult rat studies by comparing profiles drawn across the diaphragm dome, with and without retrospective respiratory gating. Results showed a sharper transition in the gated reconstruction, with an average slope improvement of 60.7%

Reference analysis of the signal + background model in counting experiments

Science.gov (United States)

Casadei, D.

2012-01-01

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

Fractal Complexity-Based Feature Extraction Algorithm of Communication Signals

Science.gov (United States)

Wang, Hui; Li, Jingchao; Guo, Lili; Dou, Zheng; Lin, Yun; Zhou, Ruolin

How to analyze and identify the characteristics of radiation sources and estimate the threat level by means of detecting, intercepting and locating has been the central issue of electronic support in the electronic warfare, and communication signal recognition is one of the key points to solve this issue. Aiming at accurately extracting the individual characteristics of the radiation source for the increasingly complex communication electromagnetic environment, a novel feature extraction algorithm for individual characteristics of the communication radiation source based on the fractal complexity of the signal is proposed. According to the complexity of the received signal and the situation of environmental noise, use the fractal dimension characteristics of different complexity to depict the subtle characteristics of the signal to establish the characteristic database, and then identify different broadcasting station by gray relation theory system. The simulation results demonstrate that the algorithm can achieve recognition rate of 94% even in the environment with SNR of -10dB, and this provides an important theoretical basis for the accurate identification of the subtle features of the signal at low SNR in the field of information confrontation.

EXTRACTING PERIODIC TRANSIT SIGNALS FROM NOISY LIGHT CURVES USING FOURIER SERIES

Energy Technology Data Exchange (ETDEWEB)

Samsing, Johan [Department of Astrophysical Sciences, Princeton University, Peyton Hall, 4 Ivy Lane, Princeton, NJ 08544 (United States)

2015-07-01

We present a simple and powerful method for extracting transit signals associated with a known transiting planet from noisy light curves. Assuming the orbital period of the planet is known and the signal is periodic, we illustrate that systematic noise can be removed in Fourier space at all frequencies by only using data within a fixed time frame with a width equal to an integer number of orbital periods. This results in a reconstruction of the full transit signal, which on average is unbiased despite no prior knowledge of either the noise or the transit signal itself being used in the analysis. The method therefore has clear advantages over standard phase folding, which normally requires external input such as nearby stars or noise models for removing systematic components. In addition, we can extract the full orbital transit signal (360°) simultaneously, and Kepler-like data can be analyzed in just a few seconds. We illustrate the performance of our method by applying it to a dataset composed of light curves from Kepler with a fake injected signal emulating a planet with rings. For extracting periodic transit signals, our presented method is in general the optimal and least biased estimator and could therefore lead the way toward the first detections of, e.g., planet rings and exo-trojan asteroids.

An Accurate Integral Method for Vibration Signal Based on Feature Information Extraction

Directory of Open Access Journals (Sweden)

Yong Zhu

2015-01-01

Full Text Available After summarizing the advantages and disadvantages of current integral methods, a novel vibration signal integral method based on feature information extraction was proposed. This method took full advantage of the self-adaptive filter characteristic and waveform correction feature of ensemble empirical mode decomposition in dealing with nonlinear and nonstationary signals. This research merged the superiorities of kurtosis, mean square error, energy, and singular value decomposition on signal feature extraction. The values of the four indexes aforementioned were combined into a feature vector. Then, the connotative characteristic components in vibration signal were accurately extracted by Euclidean distance search, and the desired integral signals were precisely reconstructed. With this method, the interference problem of invalid signal such as trend item and noise which plague traditional methods is commendably solved. The great cumulative error from the traditional time-domain integral is effectively overcome. Moreover, the large low-frequency error from the traditional frequency-domain integral is successfully avoided. Comparing with the traditional integral methods, this method is outstanding at removing noise and retaining useful feature information and shows higher accuracy and superiority.

Research on vibration signal analysis and extraction method of gear local fault

Science.gov (United States)

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

2018-02-01

Gear is the main connection parts and power transmission parts in the mechanical equipment. If the fault occurs, it directly affects the running state of the whole machine and even endangers the personal safety. So it has important theoretical significance and practical value to study on the extraction of the gear fault signal and fault diagnosis of the gear. In this paper, the gear local fault as the research object, set up the vibration model of gear fault vibration mechanism, derive the vibration mechanism of the gear local fault and analyzes the similarities and differences of the vibration signal between the gear non fault and the gears local faults. In the MATLAB environment, the wavelet transform algorithm is used to denoise the fault signal. Hilbert transform is used to demodulate the fault vibration signal. The results show that the method can denoise the strong noise mechanical vibration signal and extract the local fault feature information from the fault vibration signal..

The Influence of Reference Corpus Size on Wordsmith Tools Keywords Extraction

Directory of Open Access Journals (Sweden)

Tony Berber Sardinha

2012-05-01

Full Text Available A KeyWords analysis (using WordSmith Tools enables the discovery of lexical items which reveal the main lexical sets in a text or corpus. Such an analysis requires that a reference corpus be compared to the corpus the researcher intends to describe (the study corpus. This paper presents a mathematical method for finding out the influence of reference corpus size on the number of key words extracted by the program. The results reveal that a reference corpus that is at least five times as large as the study corpus allows for drawing an amount of key words that is statistically equivalent to larger reference corpora, thus suggesting five times (as larger as the study corpora as the minimum order of magnitude for reference corpora.

Global 21 cm Signal Extraction from Foreground and Instrumental Effects. I. Pattern Recognition Framework for Separation Using Training Sets

Science.gov (United States)

Tauscher, Keith; Rapetti, David; Burns, Jack O.; Switzer, Eric

2018-02-01

The sky-averaged (global) highly redshifted 21 cm spectrum from neutral hydrogen is expected to appear in the VHF range of ∼20–200 MHz and its spectral shape and strength are determined by the heating properties of the first stars and black holes, by the nature and duration of reionization, and by the presence or absence of exotic physics. Measurements of the global signal would therefore provide us with a wealth of astrophysical and cosmological knowledge. However, the signal has not yet been detected because it must be seen through strong foregrounds weighted by a large beam, instrumental calibration errors, and ionospheric, ground, and radio-frequency-interference effects, which we collectively refer to as “systematics.” Here, we present a signal extraction method for global signal experiments which uses Singular Value Decomposition of “training sets” to produce systematics basis functions specifically suited to each observation. Instead of requiring precise absolute knowledge of the systematics, our method effectively requires precise knowledge of how the systematics can vary. After calculating eigenmodes for the signal and systematics, we perform a weighted least square fit of the corresponding coefficients and select the number of modes to include by minimizing an information criterion. We compare the performance of the signal extraction when minimizing various information criteria and find that minimizing the Deviance Information Criterion most consistently yields unbiased fits. The methods used here are built into our widely applicable, publicly available Python package, pylinex, which analytically calculates constraints on signals and systematics from given data, errors, and training sets.

Suitability of cerebrospinal fluid as a signal-intensity reference on MRI: evaluation of signal-intensity variations in the lumbosacral dural sac

International Nuclear Information System (INIS)

Luoma, E.K.; Luukkonen, R.; Riihimaeki, H.A.; Raininko, R.; Manninen, H.I.; Nummi, P.J.

1997-01-01

The suitability of the cerebrospinal fluid (CSF) in the lumbosacral dural sac as an internal signal-intensity reference was studied on magnetic resonance imaging (MRI) of the lumbar spine using a surface coil and motion artefact suppression technique. A signal-intensity reference is needed when signal is compared between images, studies or subjects. Homogeneity of the CSF was estimated visually on T2-weighted images of 60 subjects at 1.5 T and of another 60 subjects at 0.1 T. Spines with a severely narrowed dural sac or marked scoliosis were excluded from the study to avoid partial volume effect. CSF was homogeneous in 82% and 73% of the examinations at 1.5 T and 0.1 T, respectively. The type and location of the local inhomogeneities did not relate to local narrowings of the dural sac. The signal intensity of CSF was measured in 108 examinations at 0.1 T after correcting the spatially-dependent signal-intensity nonuniformities with a phantom-based method. The signal-intensity difference between the CSF in the upper and lower lumbar dural sac was less than 10% in 73% of the examinations. The CSF in the lumbosacral dural sac can be a useful signal-intensity reference for estimation of the signal of the adjacent structures in patients without severe narrowing of the dural sac or marked scoliosis. It may contribute to assessing spinal disease processes. (orig.). With 1 fig., 3 tabs

Respiratory Information Extraction from Electrocardiogram Signals

KAUST Repository

Amin, Gamal El Din Fathy

2010-12-01

The Electrocardiogram (ECG) is a tool measuring the electrical activity of the heart, and it is extensively used for diagnosis and monitoring of heart diseases. The ECG signal reflects not only the heart activity but also many other physiological processes. The respiratory activity is a prominent process that affects the ECG signal due to the close proximity of the heart and the lungs. In this thesis, several methods for the extraction of respiratory process information from the ECG signal are presented. These methods allow an estimation of the lung volume and the lung pressure from the ECG signal. The potential benefit of this is to eliminate the corresponding sensors used to measure the respiration activity. A reduction of the number of sensors connected to patients will increase patients’ comfort and reduce the costs associated with healthcare. As a further result, the efficiency of diagnosing respirational disorders will increase since the respiration activity can be monitored with a common, widely available method. The developed methods can also improve the detection of respirational disorders that occur while patients are sleeping. Such disorders are commonly diagnosed in sleeping laboratories where the patients are connected to a number of different sensors. Any reduction of these sensors will result in a more natural sleeping environment for the patients and hence a higher sensitivity of the diagnosis.

Non-stationary component extraction in noisy multicomponent signal using polynomial chirping Fourier transform.

Science.gov (United States)

Lu, Wenlong; Xie, Junwei; Wang, Heming; Sheng, Chuan

2016-01-01

Inspired by track-before-detection technology in radar, a novel time-frequency transform, namely polynomial chirping Fourier transform (PCFT), is exploited to extract components from noisy multicomponent signal. The PCFT combines advantages of Fourier transform and polynomial chirplet transform to accumulate component energy along a polynomial chirping curve in the time-frequency plane. The particle swarm optimization algorithm is employed to search optimal polynomial parameters with which the PCFT will achieve a most concentrated energy ridge in the time-frequency plane for the target component. The component can be well separated in the polynomial chirping Fourier domain with a narrow-band filter and then reconstructed by inverse PCFT. Furthermore, an iterative procedure, involving parameter estimation, PCFT, filtering and recovery, is introduced to extract components from a noisy multicomponent signal successively. The Simulations and experiments show that the proposed method has better performance in component extraction from noisy multicomponent signal as well as provides more time-frequency details about the analyzed signal than conventional methods.

Signaling pathways regulated by Brassicaceae extract inhibit the ...

African Journals Online (AJOL)

Background: The goal of this study was identification signaling molecules mediated the formation of AGEs in brain of rats injected with CdCl2 and the role of camel whey proteins and Brassicaceae extract on formation of AGEs in brain. Methods: Ninety male rats were randomly grouped into five groups; Normal control (GpI) ...

Saw Palmetto Extract Inhibits Metastasis and Antiangiogenesis through STAT3 Signal Pathway in Glioma Cell.

Science.gov (United States)

Ding, Hong; Shen, Jinglian; Yang, Yang; Che, Yuqin

2015-01-01

Signal transducer and activator of transcription factor 3 (STAT3) plays an important role in the proliferation and angiogenesis in human glioma. Previous research indicated that saw palmetto extract markedly inhibited the proliferation of human glioma cells through STAT3 signal pathway. But its effect on tumor metastasis and antiangiogenesis is not clear. This study is to further clear the impact of saw palmetto extract on glioma cell metastasis, antiangiogenesis, and its mechanism. TUNEL assay indicated that the apoptotic cells in the saw palmetto treated group are higher than that in the control group (p saw palmetto extract inhibits the proliferation of human glioma. Meanwhile pSTAT3 is lower in the experimental group and CD34 is also inhibited in the saw palmetto treated group. This means that saw palmetto extract could inhibit the angiogenesis in glioma. We found that saw palmetto extract was an important phytotherapeutic drug against the human glioma through STAT3 signal pathway. Saw palmetto extract may be useful as an adjunctive therapeutic agent for treatment of individuals with glioma and other types of cancer in which STAT3 signaling is activated.

Secrecy extraction from no-signaling correlations

International Nuclear Information System (INIS)

Scarani, Valerio; Gisin, Nicolas; Brunner, Nicolas; Masanes, Lluis; Pino, Sergi; Acin, Antonio

2006-01-01

Quantum cryptography shows that one can guarantee the secrecy of correlation on the sole basis of the laws of physics, that is, without limiting the computational power of the eavesdropper. The usual security proofs suppose that the authorized partners, Alice and Bob, have a perfect knowledge and control of their quantum systems and devices; for instance, they must be sure that the logical bits have been encoded in true qubits and not in higher dimensional systems. In this paper, we present an approach that circumvents this strong assumption. We define protocols, both for the case of bits and for generic d-dimensional outcomes, in which the security is guaranteed by the very structure of the Alice-Bob correlations, under the no-signaling condition. The idea is that if the correlations cannot be produced by shared randomness, then Eve has poor knowledge of Alice's and Bob's symbols. The present study assumes on the one hand that the eavesdropper Eve performs only individual attacks (this is a limitation to be removed in further work), and on the other hand that Eve can distribute any correlation compatible with the no-signaling condition (in this sense her power is greater than what quantum physics allows). Under these assumptions, we prove that the protocols defined here allow extracting secrecy from noisy correlations, when these correlations violate a Bell-type inequality by a sufficiently large amount. The region in which secrecy extraction is possible extends within the region of correlations achievable by measurements on entangled quantum states

Saw Palmetto Extract Inhibits Metastasis and Antiangiogenesis through STAT3 Signal Pathway in Glioma Cell

Directory of Open Access Journals (Sweden)

Hong Ding

2015-01-01

Full Text Available Signal transducer and activator of transcription factor 3 (STAT3 plays an important role in the proliferation and angiogenesis in human glioma. Previous research indicated that saw palmetto extract markedly inhibited the proliferation of human glioma cells through STAT3 signal pathway. But its effect on tumor metastasis and antiangiogenesis is not clear. This study is to further clear the impact of saw palmetto extract on glioma cell metastasis, antiangiogenesis, and its mechanism. TUNEL assay indicated that the apoptotic cells in the saw palmetto treated group are higher than that in the control group (p<0.05. The apoptosis related protein is detected and the results revealed that saw palmetto extract inhibits the proliferation of human glioma. Meanwhile pSTAT3 is lower in the experimental group and CD34 is also inhibited in the saw palmetto treated group. This means that saw palmetto extract could inhibit the angiogenesis in glioma. We found that saw palmetto extract was an important phytotherapeutic drug against the human glioma through STAT3 signal pathway. Saw palmetto extract may be useful as an adjunctive therapeutic agent for treatment of individuals with glioma and other types of cancer in which STAT3 signaling is activated.

Digital mammography: Signal-extraction strategies for computer-aided detection of microcalcifications

International Nuclear Information System (INIS)

Chan, H.P.; Doi, K.; Metz, C.E.; Vyborny, C.J.; Lam, K.L.; Schmidt, R.A.

1987-01-01

The authors found that the structured background of a mammogram can be removed effectively by either a difference-image technique (using a matched filter in combination with a median filter, a contrast-reversal filter, or a box-rim filter) or a visual response filter alone. Locally adaptive gray-level thresholding and region-growing techniques can then be employed to extract microcalcifications from the processed image. Signals are further distinguished from noise or artifacts by their size, contrast, and clustering properties. The authors studied the dependence of the detectability of microcalcifications on the various signal-extraction strategies. Potential application of the computer-aided system to mammography is assessed by its performance on clinical mammograms

A PCA aided cross-covariance scheme for discriminative feature extraction from EEG signals.

Science.gov (United States)

Zarei, Roozbeh; He, Jing; Siuly, Siuly; Zhang, Yanchun

2017-07-01

Feature extraction of EEG signals plays a significant role in Brain-computer interface (BCI) as it can significantly affect the performance and the computational time of the system. The main aim of the current work is to introduce an innovative algorithm for acquiring reliable discriminating features from EEG signals to improve classification performances and to reduce the time complexity. This study develops a robust feature extraction method combining the principal component analysis (PCA) and the cross-covariance technique (CCOV) for the extraction of discriminatory information from the mental states based on EEG signals in BCI applications. We apply the correlation based variable selection method with the best first search on the extracted features to identify the best feature set for characterizing the distribution of mental state signals. To verify the robustness of the proposed feature extraction method, three machine learning techniques: multilayer perceptron neural networks (MLP), least square support vector machine (LS-SVM), and logistic regression (LR) are employed on the obtained features. The proposed methods are evaluated on two publicly available datasets. Furthermore, we evaluate the performance of the proposed methods by comparing it with some recently reported algorithms. The experimental results show that all three classifiers achieve high performance (above 99% overall classification accuracy) for the proposed feature set. Among these classifiers, the MLP and LS-SVM methods yield the best performance for the obtained feature. The average sensitivity, specificity and classification accuracy for these two classifiers are same, which are 99.32%, 100%, and 99.66%, respectively for the BCI competition dataset IVa and 100%, 100%, and 100%, for the BCI competition dataset IVb. The results also indicate the proposed methods outperform the most recently reported methods by at least 0.25% average accuracy improvement in dataset IVa. The execution time

DCTNet and PCANet for acoustic signal feature extraction

OpenAIRE

Xian, Yin; Thompson, Andrew; Sun, Xiaobai; Nowacek, Douglas; Nolte, Loren

2016-01-01

We introduce the use of DCTNet, an efficient approximation and alternative to PCANet, for acoustic signal classification. In PCANet, the eigenfunctions of the local sample covariance matrix (PCA) are used as filterbanks for convolution and feature extraction. When the eigenfunctions are well approximated by the Discrete Cosine Transform (DCT) functions, each layer of of PCANet and DCTNet is essentially a time-frequency representation. We relate DCTNet to spectral feature representation method...

Signal extraction and wave field separation in tunnel seismic prediction by independent component analysis

Science.gov (United States)

Yue, Y.; Jiang, T.; Zhou, Q.

2017-12-01

In order to ensure the rationality and the safety of tunnel excavation, the advanced geological prediction has been become an indispensable step in tunneling. However, the extraction of signal and the separation of P and S waves directly influence the accuracy of geological prediction. Generally, the raw data collected in TSP system is low quality because of the numerous disturb factors in tunnel projects, such as the power interference and machine vibration interference. It's difficult for traditional method (band-pass filtering) to remove interference effectively as well as bring little loss to signal. The power interference, machine vibration interference and the signal are original variables and x, y, z component as observation signals, each component of the representation is a linear combination of the original variables, which satisfy applicable conditions of independent component analysis (ICA). We perform finite-difference simulations of elastic wave propagation to synthetic a tunnel seismic reflection record. The method of ICA was adopted to process the three-component data, and the results show that extract the estimates of signal and the signals are highly correlated (the coefficient correlation is up to more than 0.93). In addition, the estimates of interference that separated from ICA and the interference signals are also highly correlated, and the coefficient correlation is up to more than 0.99. Thus, simulation results showed that the ICA is an ideal method for extracting high quality data from mixed signals. For the separation of P and S waves, the conventional separation techniques are based on physical characteristics of wave propagation, which require knowledge of the near-surface P and S waves velocities and density. Whereas the ICA approach is entirely based on statistical differences between P and S waves, and the statistical technique does not require a priori information. The concrete results of the wave field separation will be presented in

Nonfeedback Distributed Beamforming Using Spatial-Temporal Extraction

Directory of Open Access Journals (Sweden)

Pongnarin Sriploy

2016-01-01

Full Text Available So far, major phase synchronization techniques for distributed beamforming suffer from the problem related to the feedback procedure as a base station has to send the feedback reference signal back to the transmitting nodes. This requires stability of communication channel or a number of retransmissions, introducing a complicated system to both transmitter and receiver. Therefore, this paper proposes an alternative technique, so-called nonfeedback beamforming, employing an operation in both space and time domains. The proposed technique is to extract a combined signal at the base station. The concept of extraction is based on solving a simultaneous linear equation without the requirement of feedback or reference signals from base station. Also, the number of retransmissions is less compared with the ones available in literatures. As a result, the transmitting nodes are of low complexity and also low power consumption. The simulation and experimental results reveal that the proposed technique provides the optimum beamforming gain. Furthermore, it can reduce Bit Error Rate to the systems.

Time-frequency energy density precipitation method for time-of-flight extraction of narrowband Lamb wave detection signals

Energy Technology Data Exchange (ETDEWEB)

Zhang, Y., E-mail: thuzhangyu@foxmail.com; Huang, S. L., E-mail: huangsling@tsinghua.edu.cn; Wang, S.; Zhao, W. [State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084 (China)

2016-05-15

The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert–Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.

Time-frequency energy density precipitation method for time-of-flight extraction of narrowband Lamb wave detection signals

International Nuclear Information System (INIS)

Zhang, Y.; Huang, S. L.; Wang, S.; Zhao, W.

2016-01-01

The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert–Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.

EXPERIMENTAL STUDY OF FIRMWARE FOR INPUT AND EXTRACTION OF USER’S VOICE SIGNAL IN VOICE AUTHENTICATION SYSTEMS

Directory of Open Access Journals (Sweden)

O. N. Faizulaieva

2014-09-01

Full Text Available Scientific task for improving the signal-to-noise ratio for user’s voice signal in computer systems and networks during the process of user’s voice authentication is considered. The object of study is the process of input and extraction of the voice signal of authentication system user in computer systems and networks. Methods and means for input and extraction of the voice signal on the background of external interference signals are investigated. Ways for quality improving of the user’s voice signal in systems of voice authentication are investigated experimentally. Firmware means for experimental unit of input and extraction of the user’s voice signal against external interference influence are considered. As modern computer means, including mobile, have two-channel audio card, two microphones are used in the voice signal input. The distance between sonic-wave sensors is 20 mm and it provides forming one direction pattern lobe of microphone array in a desired area of voice signal registration (from 100 Hz to 8 kHz. According to the results of experimental studies, the usage of directional properties of the proposed microphone array and space-time processing of the recorded signals with implementation of constant and adaptive weighting factors has made it possible to reduce considerably the influence of interference signals. The results of firmware experimental studies for input and extraction of the user’s voice signal against external interference influence are shown. The proposed solutions will give the possibility to improve the value of the signal/noise ratio of the useful signals recorded up to 20 dB under the influence of external interference signals in the frequency range from 4 to 8 kHz. The results may be useful to specialists working in the field of voice recognition and speaker discrimination.

Reference-tracking feedforward control design for linear dynamical systems through signal decomposition

NARCIS (Netherlands)

Kasemsinsup, Y.; Romagnoli, R.; Heertjes, M.F.; Weiland, S.; Butler, H.

2017-01-01

In this work, we study a novel approach towards the reference-tracking feedforward control design for linear dynamical systems. By utilizing the superposition property and exploiting signal decomposition together with a quadratic optimization process, we obtain a feedforward design procedure for

GPR Signal Denoising and Target Extraction With the CEEMD Method

KAUST Repository

Li, Jing

2015-04-17

In this letter, we apply a time and frequency analysis method based on the complete ensemble empirical mode decomposition (CEEMD) method in ground-penetrating radar (GPR) signal processing. It decomposes the GPR signal into a sum of oscillatory components, with guaranteed positive and smoothly varying instantaneous frequencies. The key idea of this method relies on averaging the modes obtained by empirical mode decomposition (EMD) applied to several realizations of Gaussian white noise added to the original signal. It can solve the mode-mixing problem in the EMD method and improve the resolution of ensemble EMD (EEMD) when the signal has a low signal-to-noise ratio. First, we analyze the difference between the basic theory of EMD, EEMD, and CEEMD. Then, we compare the time and frequency analysis with Hilbert-Huang transform to test the results of different methods. The synthetic and real GPR data demonstrate that CEEMD promises higher spectral-spatial resolution than the other two EMD methods in GPR signal denoising and target extraction. Its decomposition is complete, with a numerically negligible error.

A New Synchronous Reference Frame-Based Method for Single-Phase Shunt Active Power Filters

DEFF Research Database (Denmark)

Monfared, Mohammad; Golestan, Saeed; Guerrero, Josep M.

2013-01-01

This paper deals with the design of a novel method in the synchronous reference frame (SRF) to extract the reference compensating current for single-phase shunt active power filters (APFs). Unlike previous works in the SRF, the proposed method has an innovative feature that it does not need...... the fictitious current signal. Frequency-independent operation, accurate reference current extraction and relatively fast transient response are other key features of the presented strategy. The effectiveness of the proposed method is investigated by means of detailed mathematical analysis. The results confirm...

Platelet-rich plasma extract prevents pulmonary edema through angiopoietin-Tie2 signaling.

Science.gov (United States)

Mammoto, Tadanori; Jiang, Amanda; Jiang, Elisabeth; Mammoto, Akiko

2015-01-01

Increased vascular permeability contributes to life-threatening pathological conditions, such as acute respiratory distress syndrome. Current treatments for sepsis-induced pulmonary edema rely on low-tidal volume mechanical ventilation, fluid management, and pharmacological use of a single angiogenic or chemical factor with antipermeability activity. However, it is becoming clear that a combination of multiple angiogenic/chemical factors rather than a single factor is required for maintaining stable and functional blood vessels. We have demonstrated that mouse platelet-rich plasma (PRP) extract contains abundant angiopoietin (Ang) 1 and multiple other factors (e.g., platelet-derived growth factor), which potentially stabilize vascular integrity. Here, we show that PRP extract increases tyrosine phosphorylation levels of Tunica internal endothelial cell kinase (Tie2) and attenuates disruption of cell-cell junctional integrity induced by inflammatory cytokine in cultured human microvascular endothelial cells. Systemic injection of PRP extract also increases Tie2 phosphorylation in mouse lung and prevents endotoxin-induced pulmonary edema and the consequent decreases in lung compliance and exercise intolerance resulting from endotoxin challenge. Soluble Tie2 receptor, which inhibits Ang-Tie2 signaling, suppresses the ability of PRP extract to inhibit pulmonary edema in mouse lung. These results suggest that PRP extract prevents endotoxin-induced pulmonary edema mainly through Ang-Tie2 signaling, and PRP extract could be a potential therapeutic strategy for sepsis-induced pulmonary edema and various lung diseases caused by abnormal vascular permeability.

Time-frequency energy density precipitation method for time-of-flight extraction of narrowband Lamb wave detection signals.

Science.gov (United States)

Zhang, Y; Huang, S L; Wang, S; Zhao, W

2016-05-01

The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert-Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of wave detection signals.

Development of saw palmetto (Serenoa repens) fruit and extract standard reference materials.

Science.gov (United States)

Schantz, Michele M; Bedner, Mary; Long, Stephen E; Molloy, John L; Murphy, Karen E; Porter, Barbara J; Putzbach, Karsten; Rimmer, Catherine A; Sander, Lane C; Sharpless, Katherine E; Thomas, Jeanice B; Wise, Stephen A; Wood, Laura J; Yen, James H; Yarita, Takashi; NguyenPho, Agnes; Sorenson, Wendy R; Betz, Joseph M

2008-10-01

As part of a collaboration with the National Institutes of Health's Office of Dietary Supplements and the Food and Drug Administration's Center for Drug Evaluation and Research, the National Institute of Standards and Technology has developed two standard reference materials (SRMs) representing different forms of saw palmetto (Serenoa repens), SRM 3250 Serenoa repens fruit and SRM 3251 Serenoa repens extract. Both of these SRMs have been characterized for their fatty acid and phytosterol content. The fatty acid concentration values are based on results from gas chromatography with flame ionization detection (GC-FID) and mass spectrometry (GC/MS) analysis while the sterol concentration values are based on results from GC-FID and liquid chromatography with mass spectrometry analysis. In addition, SRM 3250 has been characterized for lead content, and SRM 3251 has been characterized for the content of beta-carotene and tocopherols. SRM 3250 (fruit) has certified concentration values for three phytosterols, 14 fatty acids as triglycerides, and lead along with reference concentration values for four fatty acids as triglycerides and 16 free fatty acids. SRM 3251 (extract) has certified concentration values for three phytosterols, 17 fatty acids as triglycerides, beta-carotene, and gamma-tocopherol along with reference concentration values for three fatty acids as triglycerides, 17 fatty acids as free fatty acids, beta-carotene isomers, and delta-tocopherol and information values for two phytosterols. These SRMs will complement other reference materials currently available with concentrations for similar analytes and are part of a series of SRMs being developed for dietary supplements.

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

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Matsubara, Takamitsu; Morimoto, Jun

2013-08-01

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

Saw Palmetto Extract Inhibits Metastasis and Antiangiogenesis through STAT3 Signal Pathway in Glioma Cell

OpenAIRE

Ding, Hong; Shen, Jinglian; Yang, Yang; Che, Yuqin

2015-01-01

Signal transducer and activator of transcription factor 3 (STAT3) plays an important role in the proliferation and angiogenesis in human glioma. Previous research indicated that saw palmetto extract markedly inhibited the proliferation of human glioma cells through STAT3 signal pathway. But its effect on tumor metastasis and antiangiogenesis is not clear. This study is to further clear the impact of saw palmetto extract on glioma cell metastasis, antiangiogenesis, and its mechanism. TUNEL ass...

Blind Extraction of Chaotic Signals by Using the Fast Independent Component Analysis Algorithm

International Nuclear Information System (INIS)

Hong-Bin, Chen; Jiu-Chao, Feng; Yong, Fang

2008-01-01

We report the results of using the fast independent component analysis (FastICA) algorithm to realize blind extraction of chaotic signals. Two cases are taken into consideration: namely, the mixture is noiseless or contaminated by noise. Pre-whitening is employed to reduce the effect of noise before using the FastICA algorithm. The correlation coefficient criterion is adopted to evaluate the performance, and the success rate is defined as a new criterion to indicate the performance with respect to noise or different mixing matrices. Simulation results show that the FastICA algorithm can extract the chaotic signals effectively. The impact of noise, the length of a signal frame, the number of sources and the number of observed mixtures on the performance is investigated in detail. It is also shown that regarding a noise as an independent source is not always correct

Extracting a shape function for a signal with intra-wave frequency modulation.

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Hou, Thomas Y; Shi, Zuoqiang

2016-04-13

In this paper, we develop an effective and robust adaptive time-frequency analysis method for signals with intra-wave frequency modulation. To handle this kind of signals effectively, we generalize our data-driven time-frequency analysis by using a shape function to describe the intra-wave frequency modulation. The idea of using a shape function in time-frequency analysis was first proposed by Wu (Wu 2013 Appl. Comput. Harmon. Anal. 35, 181-199. (doi:10.1016/j.acha.2012.08.008)). A shape function could be any smooth 2π-periodic function. Based on this model, we propose to solve an optimization problem to extract the shape function. By exploring the fact that the shape function is a periodic function with respect to its phase function, we can identify certain low-rank structure of the signal. This low-rank structure enables us to extract the shape function from the signal. Once the shape function is obtained, the instantaneous frequency with intra-wave modulation can be recovered from the shape function. We demonstrate the robustness and efficiency of our method by applying it to several synthetic and real signals. One important observation is that this approach is very stable to noise perturbation. By using the shape function approach, we can capture the intra-wave frequency modulation very well even for noise-polluted signals. In comparison, existing methods such as empirical mode decomposition/ensemble empirical mode decomposition seem to have difficulty in capturing the intra-wave modulation when the signal is polluted by noise. © 2016 The Author(s).

Kurtosis based blind source extraction of complex noncircular signals with application in EEG artifact removal in real-time

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Soroush eJavidi

2011-10-01

Full Text Available A new class of complex domain blind source extraction (BSE algorithms suitable for the extraction of both circular and noncircular complex signals is proposed. This is achieved through sequential extraction based on the degree of kurtosis and in the presence of noncircular measurement noise. The existence and uniqueness analysis of the solution is followed by a study of fast converging variants of the algorithm. The performance is first assessed through simulations on well understood benchmark signals, followed by a case study on real-time artifact removal from EEG signals, verified using both qualitative and quantitative metrics. The results illustrate the power of the proposed approach in real-time blind extraction of general complex-valued sources.

Consistent Feature Extraction From Vector Fields: Combinatorial Representations and Analysis Under Local Reference Frames

Energy Technology Data Exchange (ETDEWEB)

Bhatia, Harsh [Univ. of Utah, Salt Lake City, UT (United States)

2015-05-01

This dissertation presents research on addressing some of the contemporary challenges in the analysis of vector fields—an important type of scientific data useful for representing a multitude of physical phenomena, such as wind flow and ocean currents. In particular, new theories and computational frameworks to enable consistent feature extraction from vector fields are presented. One of the most fundamental challenges in the analysis of vector fields is that their features are defined with respect to reference frames. Unfortunately, there is no single “correct” reference frame for analysis, and an unsuitable frame may cause features of interest to remain undetected, thus creating serious physical consequences. This work develops new reference frames that enable extraction of localized features that other techniques and frames fail to detect. As a result, these reference frames objectify the notion of “correctness” of features for certain goals by revealing the phenomena of importance from the underlying data. An important consequence of using these local frames is that the analysis of unsteady (time-varying) vector fields can be reduced to the analysis of sequences of steady (timeindependent) vector fields, which can be performed using simpler and scalable techniques that allow better data management by accessing the data on a per-time-step basis. Nevertheless, the state-of-the-art analysis of steady vector fields is not robust, as most techniques are numerical in nature. The residing numerical errors can violate consistency with the underlying theory by breaching important fundamental laws, which may lead to serious physical consequences. This dissertation considers consistency as the most fundamental characteristic of computational analysis that must always be preserved, and presents a new discrete theory that uses combinatorial representations and algorithms to provide consistency guarantees during vector field analysis along with the uncertainty

Alcoholic extraction enables EPR analysis to characterize radiation-induced cellulosic signals in spices.

Science.gov (United States)

Ahn, Jae-Jun; Sanyal, Bhaskar; Akram, Kashif; Kwon, Joong-Ho

2014-11-19

Different spices such as turmeric, oregano, and cinnamon were γ-irradiated at 1 and 10 kGy. The electron paramagnetic resonance (EPR) spectra of the nonirradiated samples were characterized by a single central signal (g = 2.006), the intensity of which was significantly enhanced upon irradiation. The EPR spectra of the irradiated spice samples were characterized by an additional triplet signal at g = 2.006 with a hyperfine coupling constant of 3 mT, associated with the cellulose radical. EPR analysis on various sample pretreatments in the irradiated spice samples demonstrated that the spectral features of the cellulose radical varied on the basis of the pretreatment protocol. Alcoholic extraction pretreatment produced considerable improvements of the EPR signals of the irradiated spice samples relative to the conventional oven and freeze-drying techniques. The alcoholic extraction process is therefore proposed as the most suitable sample pretreatment for unambiguous detection of irradiated spices by EPR spectroscopy.

A novel SNP analysis method to detect copy number alterations with an unbiased reference signal directly from tumor samples

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LaFramboise William A

2011-01-01

Full Text Available Abstract Background Genomic instability in cancer leads to abnormal genome copy number alterations (CNA as a mechanism underlying tumorigenesis. Using microarrays and other technologies, tumor CNA are detected by comparing tumor sample CN to normal reference sample CN. While advances in microarray technology have improved detection of copy number alterations, the increase in the number of measured signals, noise from array probes, variations in signal-to-noise ratio across batches and disparity across laboratories leads to significant limitations for the accurate identification of CNA regions when comparing tumor and normal samples. Methods To address these limitations, we designed a novel "Virtual Normal" algorithm (VN, which allowed for construction of an unbiased reference signal directly from test samples within an experiment using any publicly available normal reference set as a baseline thus eliminating the need for an in-lab normal reference set. Results The algorithm was tested using an optimal, paired tumor/normal data set as well as previously uncharacterized pediatric malignant gliomas for which a normal reference set was not available. Using Affymetrix 250K Sty microarrays, we demonstrated improved signal-to-noise ratio and detected significant copy number alterations using the VN algorithm that were validated by independent PCR analysis of the target CNA regions. Conclusions We developed and validated an algorithm to provide a virtual normal reference signal directly from tumor samples and minimize noise in the derivation of the raw CN signal. The algorithm reduces the variability of assays performed across different reagent and array batches, methods of sample preservation, multiple personnel, and among different laboratories. This approach may be valuable when matched normal samples are unavailable or the paired normal specimens have been subjected to variations in methods of preservation.

Extraction of two tsunamis signals generated by earthquakes around the Pacific rim

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Chu Yonghai

2014-05-01

Full Text Available As one of the ocean sudden natural disasters, the tsunami is not easily to differentiate from the ocean variation in the open ocean due to the tsunami wave amplitude is lees than one meter with hundreds of kilometers wavelength. But the wave height will increases up to tens of meters with enormous energy when the tsunami aarives at the coast. It would not only devastate entire cities near coast, but also kill miilions of people. It is necessary to forecast and make warning before the tsunami aariving for many countries and regions around the Pacific rim. Two kinds of data were used in this study to extract the signals of 2011 Tohoku tsunami and 2014 Iquique tsunami. Wave undulations from DART (Deep-ocean Assessment and Reporting of Tsunamis buoys and SLA from altimetry could extract the tsunami signals generated by this two earthquake. The signals of Tohoku tsunami were stronger than that of Iquique tsunami probably due to the 2011 Tohoku tsunami was generated by a magnitude 9. 0 earthquake and the 2014 Iquique tsunami was triggered by a magnitude 8. 2 earthquake.

New method to extract radial acceleration of target from short-duration signal at low SNR

Institute of Scientific and Technical Information of China (English)

2008-01-01

In order to extract target radial acceleration from radar echo signal at low SNR (signal-to-noise), this paper employed FRFT (fractional Fourier transformation) to analyze short-duration radar echo and studied the relations between signal convergence peaks in matched transformation domain and signal duration and modu- lated frequency of signal. When signal duration is specified, the method of multi- plying sampled signal by the known frequency modulated signal to alter modulated frequency was presented, which generated the new signal with larger convergence peaks than the initial signal in matched transformation domain. Thus, it could successfully estimate the radial acceleration of radar target at low SNR. Simulations were conducted to show the feasibility and effectiveness of the method.

Extracting protein dynamics information from overlapped NMR signals using relaxation dispersion difference NMR spectroscopy.

Science.gov (United States)

Konuma, Tsuyoshi; Harada, Erisa; Sugase, Kenji

2015-12-01

Protein dynamics plays important roles in many biological events, such as ligand binding and enzyme reactions. NMR is mostly used for investigating such protein dynamics in a site-specific manner. Recently, NMR has been actively applied to large proteins and intrinsically disordered proteins, which are attractive research targets. However, signal overlap, which is often observed for such proteins, hampers accurate analysis of NMR data. In this study, we have developed a new methodology called relaxation dispersion difference that can extract conformational exchange parameters from overlapped NMR signals measured using relaxation dispersion spectroscopy. In relaxation dispersion measurements, the signal intensities of fluctuating residues vary according to the Carr-Purcell-Meiboon-Gill pulsing interval, whereas those of non-fluctuating residues are constant. Therefore, subtraction of each relaxation dispersion spectrum from that with the highest signal intensities, measured at the shortest pulsing interval, leaves only the signals of the fluctuating residues. This is the principle of the relaxation dispersion difference method. This new method enabled us to extract exchange parameters from overlapped signals of heme oxygenase-1, which is a relatively large protein. The results indicate that the structural flexibility of a kink in the heme-binding site is important for efficient heme binding. Relaxation dispersion difference requires neither selectively labeled samples nor modification of pulse programs; thus it will have wide applications in protein dynamics analysis.

Extracting protein dynamics information from overlapped NMR signals using relaxation dispersion difference NMR spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Konuma, Tsuyoshi [Icahn School of Medicine at Mount Sinai, Department of Structural and Chemical Biology (United States); Harada, Erisa [Suntory Foundation for Life Sciences, Bioorganic Research Institute (Japan); Sugase, Kenji, E-mail: sugase@sunbor.or.jp, E-mail: sugase@moleng.kyoto-u.ac.jp [Kyoto University, Department of Molecular Engineering, Graduate School of Engineering (Japan)

2015-12-15

Protein dynamics plays important roles in many biological events, such as ligand binding and enzyme reactions. NMR is mostly used for investigating such protein dynamics in a site-specific manner. Recently, NMR has been actively applied to large proteins and intrinsically disordered proteins, which are attractive research targets. However, signal overlap, which is often observed for such proteins, hampers accurate analysis of NMR data. In this study, we have developed a new methodology called relaxation dispersion difference that can extract conformational exchange parameters from overlapped NMR signals measured using relaxation dispersion spectroscopy. In relaxation dispersion measurements, the signal intensities of fluctuating residues vary according to the Carr-Purcell-Meiboon-Gill pulsing interval, whereas those of non-fluctuating residues are constant. Therefore, subtraction of each relaxation dispersion spectrum from that with the highest signal intensities, measured at the shortest pulsing interval, leaves only the signals of the fluctuating residues. This is the principle of the relaxation dispersion difference method. This new method enabled us to extract exchange parameters from overlapped signals of heme oxygenase-1, which is a relatively large protein. The results indicate that the structural flexibility of a kink in the heme-binding site is important for efficient heme binding. Relaxation dispersion difference requires neither selectively labeled samples nor modification of pulse programs; thus it will have wide applications in protein dynamics analysis.

Exploring valid reference genes for quantitative real - time rt - pce studies of hydrogenperoxide signaling in arabidopsis

International Nuclear Information System (INIS)

Zhou, H.; Han, B.; Xie, Y.; Zhang, J.; Shen, W.

2015-01-01

Hydrogen peroxide (H/sub 2/O/sub 2/ ) acts as a signaling molecule modulating the expression of various genes in plants. However, the reference gene(s) used for gene expression analysis of H/sub 2/O/sub 2/ signaling is still arbitrary. A reliable result obtained by quantitative real-time RT-PCR (RT-qPCR) highly depends on accurate transcript normalization using stably expressed reference genes, whereas the inaccurate normalization could easily lead to the false conclusions. In this report, by using geNorm and NormFinder algorithms, 12 candidate reference genes were evaluated and compared in root and shoot tissues of Arabidopsis upon different doses of H/sub 2/O/sub 2/. The results revealed that, in our experimental conditions, three novel reference genes (TIP41-like, UKN, and UBC21) were identified and validated as suitable reference genes for RT-qPCR normalization in both root and shoot tissues under oxidative stress. This conclusion was further confirmed by publicly available microarray data of methyl viologen and drought stress. In comparison with a single reference gene (EF-1a), the expression pattern of ZAT12 modulated by H/sub 2/O/sub 2/, when using TIP41-like, UKN, and UBC21 as multiple reference gene(s), was similar with the previous reports by using northern blotting. Thus, we proposed that these three reference genes might be good candidates for other researchers to include in their reference gene validation in gene expression studies under H/sub 2/O/sub 2/ related oxidative stress. (author)

Solid phase speciation of arsenic by sequential extraction in standard reference materials and industrially contaminated soil samples

International Nuclear Information System (INIS)

Herreweghe, Samuel van; Swennen, Rudy; Vandecasteele, Carlo; Cappuyns, Valerie

2003-01-01

Leaching experiments, a mineralogical survey and larger samples are preferred when arsenic is present as discrete mineral phases. - Availability, mobility, (phyto)toxicity and potential risk of contaminants is strongly affected by the manner of appearance of elements, the so-called speciation. Operational fractionation methods like sequential extractions have been applied for a long time to determine the solid phase speciation of heavy metals since direct determination of specific chemical compounds can not always be easily achieved. The three-step sequential extraction scheme recommended by the BCR and two extraction schemes based on the phosphorus-like protocol proposed by Manful (1992, Occurrence and Ecochemical Behaviours of Arsenic in a Goldsmelter Impacted Area in Ghana, PhD dissertation, at the RUG) were applied to four standard reference materials (SRM) and to a batch of samples from industrially contaminated sites, heavily contaminated with arsenic and heavy metals. The SRM 2710 (Montana soil) was found to be the most useful reference material for metal (Mn, Cu, Zn, As, Cd and Pb) fractionation using the BCR sequential extraction procedure. Two sequential extraction schemes were developed and compared for arsenic with the aim to establish a better fractionation and recovery rate than the BCR-scheme for this element in the SRM samples. The major part of arsenic was released from the heavily contaminated samples after NaOH-extraction. Inferior extraction variability and recovery in the heavily contaminated samples compared to SRMs could be mainly contributed to subsample heterogeneity

On a possible mechanism of the brain for responding to dynamical features extracted from input signals

International Nuclear Information System (INIS)

Liu Zengrong; Chen Guanrong

2003-01-01

Based on the general theory of nonlinear dynamical systems, a possible mechanism for responding to some dynamical features extracted from input signals in brain activities is described and discussed. This mechanism is first converted to a nonlinear dynamical configuration--a generalized synchronization of complex dynamical systems. Then, some general conditions for achieving such synchronizations are derived. It is shown that dynamical systems have potentials of producing different responses for different features extracted from various input signals, which may be used to describe brain activities. For illustration, some numerical examples are given with simulation figures

Effect of saw palmetto extract on PI3K cell signaling transduction in human glioma.

Science.gov (United States)

Yang, Yang; Hui, Lv; Yuqin, Che; Jie, Li; Shuai, Hou; Tiezhu, Zhou; Wei, Wang

2014-08-01

Saw palmetto extract can induce the apoptosis of prostate cancer cells. The aim of the present study was to investigate the effect of saw palmetto extract on the phosphatidylinositol 3-kinase (PI3K)/Akt signaling transduction pathway in human glioma U87 and U251 cell lines. Suspensions of U87 and U251 cells in a logarithmic growth phase were seeded into six-well plates at a density of 10 4 cells/well. In the experimental group, 1 μl/ml saw palmetto extract was added, while the control group was cultured without a drug for 24 h. The expression levels of PI3K, B-cell lymphoma-extra large (Bcl-xL) and p53 were evaluated through western blot analysis. In the experimental group, the U87 and U251 cells exhibited a lower expression level of PI3K protein as compared with the control group (t=6.849; Psaw palmetto extract induces glioma cell growth arrest and apoptosis via decreasing PI3K/Akt signal transduction.

Development of Filtered Bispectrum for EEG Signal Feature Extraction in Automatic Emotion Recognition Using Artificial Neural Networks

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Prima Dewi Purnamasari

2017-05-01

Full Text Available The development of automatic emotion detection systems has recently gained significant attention due to the growing possibility of their implementation in several applications, including affective computing and various fields within biomedical engineering. Use of the electroencephalograph (EEG signal is preferred over facial expression, as people cannot control the EEG signal generated by their brain; the EEG ensures a stronger reliability in the psychological signal. However, because of its uniqueness between individuals and its vulnerability to noise, use of EEG signals can be rather complicated. In this paper, we propose a methodology to conduct EEG-based emotion recognition by using a filtered bispectrum as the feature extraction subsystem and an artificial neural network (ANN as the classifier. The bispectrum is theoretically superior to the power spectrum because it can identify phase coupling between the nonlinear process components of the EEG signal. In the feature extraction process, to extract the information contained in the bispectrum matrices, a 3D pyramid filter is used for sampling and quantifying the bispectrum value. Experiment results show that the mean percentage of the bispectrum value from 5 × 5 non-overlapped 3D pyramid filters produces the highest recognition rate. We found that reducing the number of EEG channels down to only eight in the frontal area of the brain does not significantly affect the recognition rate, and the number of data samples used in the training process is then increased to improve the recognition rate of the system. We have also utilized a probabilistic neural network (PNN as another classifier and compared its recognition rate with that of the back-propagation neural network (BPNN, and the results show that the PNN produces a comparable recognition rate and lower computational costs. Our research shows that the extracted bispectrum values of an EEG signal using 3D filtering as a feature extraction

An EEMD-PCA approach to extract heart rate, respiratory rate and respiratory activity from PPG signal.

Science.gov (United States)

Motin, Mohammod Abdul; Karmakar, Chandan Kumar; Palaniswami, Marimuthu

2016-08-01

The pulse oximeter's photoplethysmographic (PPG) signals, measure the local variations of blood volume in tissues, reflecting the peripheral pulse modulated by cardiac activity, respiration and other physiological effects. Therefore, PPG can be used to extract the vital cardiorespiratory signals like heart rate (HR), respiratory rate (RR) and respiratory activity (RA) and this will reduce the number of sensors connected to the patient's body for recording vital signs. In this paper, we propose an algorithm based on ensemble empirical mode decomposition with principal component analysis (EEMD-PCA) as a novel approach to estimate HR, RR and RA simultaneously from PPG signal. To examine the performance of the proposed algorithm, we used 45 epochs of PPG, electrocardiogram (ECG) and respiratory signal extracted from the MIMIC database (Physionet ATM data bank). The ECG and capnograph based respiratory signal were used as the ground truth and several metrics such as magnitude squared coherence (MSC), correlation coefficients (CC) and root mean square (RMS) error were used to compare the performance of EEMD-PCA algorithm with most of the existing methods in the literature. Results of EEMD-PCA based extraction of HR, RR and RA from PPG signal showed that the median RMS error (quartiles) obtained for RR was 0 (0, 0.89) breaths/min, for HR was 0.62 (0.56, 0.66) beats/min and for RA the average value of MSC and CC was 0.95 and 0.89 respectively. These results illustrated that the proposed EEMD-PCA approach is more accurate in estimating HR, RR and RA than other existing methods.

Morus alba extract modulates blood pressure homeostasis through eNOS signaling.

Science.gov (United States)

Carrizzo, Albino; Ambrosio, Mariateresa; Damato, Antonio; Madonna, Michele; Storto, Marianna; Capocci, Luca; Campiglia, Pietro; Sommella, Eduardo; Trimarco, Valentina; Rozza, Francesco; Izzo, Raffaele; Puca, Annibale A; Vecchione, Carmine

2016-10-01

Morus alba is a promising phytomedicine cultivated in oriental countries that is extensively used to prevent and treat various cardiovascular problems. To date, despite its beneficial effects, the molecular mechanisms involved remain unclear. Thus, we investigate the vascular and haemodynamic effects of Morus alba extract in an experimental model focusing our attention on the molecular mechanisms involved. Through vascular reactivity studies, we demonstrate that Morus alba extract evokes endothelial vasorelaxation through a nitric oxide-dependent pathway. Our molecular analysis highlights an increase in endothelial nitric oxide synthase (eNOS) phosphorylation. In vivo administration of Morus alba extract reduces blood pressure levels exclusively in wild-type mice, whereas it fails to evoke any haemodynamic effects in eNOS-deficient mice. Molecular analyses revealed that its beneficial action on vasculature is mediated by the activation of two important proteins that act as stress sensors and chaperones: PERK and heat shock protein 90. Finally, Morus alba extract exerts antihypertensive action in an experimental model of arterial hypertension. Through its action on eNOS signaling, Morus alba extract could act as a food supplement for the regulation of cardiovascular system, mainly in clinical conditions characterized by eNOS dysfunction, such as arterial hypertension. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hair growth-promoting effect of Aconiti Ciliare Tuber extract mediated by the activation of Wnt/β-catenin signaling.

Science.gov (United States)

Park, Phil-June; Moon, Byoung-San; Lee, Soung-Hoon; Kim, Su-Na; Kim, Ah-Reum; Kim, Hyung-Jun; Park, Won-Seok; Choi, Kang-Yell; Cho, Eun-Gyung; Lee, Tae Ryong

2012-11-02

The activation of Wnt/β-catenin signaling pathway plays an important role in hair follicle morphogenesis by stimulating bulge stem cells. This study was to obtain the activator of Wnt/β-catenin signaling pathway from natural products and to determine whether this activator can induce anagen hair growth in mice. To identify materials that activate Wnt/β-catenin signaling pathway, 800 natural product extracts were screened using pTOPFlash assay and neural progenitor cell (NPC) differentiation assay. A selected extract was further tested for its effects on alkaline phosphatase (ALP) activity in human immortalized dermal papilla cell (iDPC) and the proliferation in iDPC and immortalized rat vibrissa DPC (RvDP). Finally, hair growth-promoting effects were evaluated in the dorsal skin of C57BL/6 mice. Aconiti Ciliare Tuber (ACT) extract was one of the most active materials in both pTOPFlash and NPC differentiation assays. It promoted the differentiation of NPC cells even under proliferation-stimulating conditions (basic fibroblast growth factor: bFGF). It also increased ALP activity and proliferation of iDPC in dose-dependent manners, and it stimulated the induction of the anagen hair growth in C57BL/6 mice. These results suggest that ACT extract activates the Wnt/β-catenin signaling pathway by enhancing β-catenin transcription and has the potential to promote the induction of hair growth via activation of the stem cell activity of the dermal papilla cells. This is the first report indicating benefits of ACT extract in hair loss prevention by triggering the activation of Wnt/β-catenin signaling pathway and induction of the anagen hair growth in mice. Copyright © 2012 Elsevier Inc. All rights reserved.

Research on feature extraction and classification of AE signals of fibers' tensile failure based on HHT and SVM

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Yanding SHEN

2016-10-01

Full Text Available In order to study the feature extraction and recognition method of fibers' tensile failure, AE technology is used to collect AE signals of fiber bundle's tensile fracture of two kinds of fibers of Aramid 1313 and viscose. A transform called wavelet is used to deal with the signals to reduce noise. A method called Hilbert-Huang transform (HHT is used to extract characteristic frequencies of the signals after the noise is reduced. And a classification method called Least Squares support vector machines (LSSVM is used for the classification and recognition of characteristic frequencies of the two kinds of fibers. The results show that wavelet de-noise method can reduce some noise of the signals. Hilbert spectrum can reflect fracture circumstances of the two kinds of fibers in the time dimension to some extent. Characteristic frequencies' extraction can be done from marginal spectrum. The LSSVM can be used for the classification and recognition of characteristic frequencies. The recognition rates of Aramid 1313 and viscose reach 40%, 80% respectively, and the total recognition rate reaches 60%.

Improvements to the extraction of an AlGaN/GaN HEMT small-signal model

International Nuclear Information System (INIS)

Pu Yan; Pang Lei; Wang Liang; Chen Xiaojuan; Li Chengzhan; Liu Xinyu

2009-01-01

The accurate extraction of AlGaN/GaN HEMT small-signal models, which is an important step in large-signal modeling, can exactly reflect the microwave performance of the physical structure of the device. A new method of extracting the parasitic elements is presented, and an open dummy structure is introduced to obtain the parasitic capacitances. With a Schottky resistor in the gate, a new method is developed to extract R g . In order to characterize the changes of the depletion region under various drain voltages, the drain delay factor is involved in the output conductance of the device. Compared to the traditional method, the fitting of S 11 and S 22 is improved, and f T and f max can be better predicted. The validity of the proposed method is verified with excellent correlation between the measured and simulated S-parameters in the range of 0.1 to 26.1 GHz. (semiconductor devices)

Searching for patterns in TJ-II time evolution signals

International Nuclear Information System (INIS)

Farias, G.; Dormido-Canto, S.; Vega, J.; Sanchez, J.; Duro, N.; Dormido, R.; Ochando, M.; Santos, M.; Pajares, G.

2006-01-01

Since fusion plasma experiments generate hundreds of signals, it is important for their analysis to have automatic mechanisms for searching for similarities and retrieving specific data from the signal database. This paper describes a technique for searching in the TJ-II database that combines support vector machines and similarity query methods. Firstly, plasma signals are pre-processed by wavelet transform or discrete Fourier transform to reduce the dimensionality of the problem and to extract their main features. Secondly, support vector machines are used to classify a set of signals by reference to an input signal. Finally, similarity query methods (Euclidean distance and bounding envelope) are used to search the set of signals that best matches the input signal

Reference in human and non-human primate communication: What does it take to refer?

Science.gov (United States)

Sievers, Christine; Gruber, Thibaud

2016-07-01

The concept of functional reference has been used to isolate potentially referential vocal signals in animal communication. However, its relatedness to the phenomenon of reference in human language has recently been brought into question. While some researchers have suggested abandoning the concept of functional reference altogether, others advocate a revision of its definition to include contextual cues that play a role in signal production and perception. Empirical and theoretical work on functional reference has also put much emphasis on how the receiver understands the referential signal. However, reference, as defined in the linguistic literature, is an action of the producer, and therefore, any definition describing reference in non-human animals must also focus on the producer. To successfully determine whether a signal is used to refer, we suggest an approach from the field of pragmatics, taking a closer look at specific situations of signal production, specifically at the factors that influence the production of a signal by an individual. We define the concept of signaller's reference to identify intentional acts of reference produced by a signaller independently of the communicative modality, and illustrate it with a case study of the hoo vocalizations produced by wild chimpanzees during travel. This novel framework introduces an intentional approach to referentiality. It may therefore permit a closer comparison of human and non-human animal referential behaviour and underlying cognitive processes, allowing us to identify what may have emerged solely in the human lineage.

An investigation of two-phase flow instability using wavelet signal extraction technique

International Nuclear Information System (INIS)

Shang Zhi; Yang Ruichang; Cao Xuewu; Yang Yanhua

2004-01-01

When the oscillation periods of the instability of two-phase flow are sought with traditional methods of signal analysis, generally the Fourier transform must be employed and then the oscillation periods will be gotten at the location of the local maximum amplitude of frequency transform. However, Fourier transform will be difficult to clearly analyze the unsteady signals especially when the signals include many peaks and the noise interference is not generated by white noise in many areas of practical engineering like the oscillation of the instability of two-phase flow. The most effective solving method for the difficulty of Fourier transform is to analyze the signals directly in time domain. Wavelet analysis is able to search out the periods from time domain directly. It also has more excellent local characteristics than Fourier analysis in the both of time and frequency domains. In this paper, not only is a direct detecting method of the oscillation periods successfully applied based on the wavelet signal extraction techniques, but also the oscillation of density wave type of TYPE I is found as a kind of oscillations with a high-frequency harmonization

Optimal Elbow Angle for Extracting sEMG Signals During Fatiguing Dynamic Contraction

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Mohamed R. Al-Mulla

2015-09-01

Full Text Available Surface electromyographic (sEMG activity of the biceps muscle was recorded from 13 subjects. Data was recorded while subjects performed dynamic contraction until fatigue and the signals were segmented into two parts (Non-Fatigue and Fatigue. An evolutionary algorithm was used to determine the elbow angles that best separate (using Davies-Bouldin Index, DBI both Non-Fatigue and Fatigue segments of the sEMG signal. Establishing the optimal elbow angle for feature extraction used in the evolutionary process was based on 70% of the conducted sEMG trials. After completing 26 independent evolution runs, the best run containing the optimal elbow angles for separation (Non-Fatigue and Fatigue was selected and then tested on the remaining 30% of the data to measure the classification performance. Testing the performance of the optimal angle was undertaken on nine features extracted from each of the two classes (Non-Fatigue and Fatigue to quantify the performance. Results showed that the optimal elbow angles can be used for fatigue classification, showing 87.90% highest correct classification for one of the features and on average of all eight features (including worst performing features giving 78.45%.

TreeScaper: Visualizing and Extracting Phylogenetic Signal from Sets of Trees.

Science.gov (United States)

Huang, Wen; Zhou, Guifang; Marchand, Melissa; Ash, Jeremy R; Morris, David; Van Dooren, Paul; Brown, Jeremy M; Gallivan, Kyle A; Wilgenbusch, Jim C

2016-12-01

Modern phylogenomic analyses often result in large collections of phylogenetic trees representing uncertainty in individual gene trees, variation across genes, or both. Extracting phylogenetic signal from these tree sets can be challenging, as they are difficult to visualize, explore, and quantify. To overcome some of these challenges, we have developed TreeScaper, an application for tree set visualization as well as the identification of distinct phylogenetic signals. GUI and command-line versions of TreeScaper and a manual with tutorials can be downloaded from https://github.com/whuang08/TreeScaper/releases TreeScaper is distributed under the GNU General Public License. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evaluation of Method-Specific Extraction Variability for the Measurement of Fatty Acids in a Candidate Infant/Adult Nutritional Formula Reference Material.

Science.gov (United States)

Place, Benjamin J

2017-05-01

To address community needs, the National Institute of Standards and Technology has developed a candidate Standard Reference Material (SRM) for infant/adult nutritional formula based on milk and whey protein concentrates with isolated soy protein called SRM 1869 Infant/Adult Nutritional Formula. One major component of this candidate SRM is the fatty acid content. In this study, multiple extraction techniques were evaluated to quantify the fatty acids in this new material. Extraction methods that were based on lipid extraction followed by transesterification resulted in lower mass fraction values for all fatty acids than the values measured by methods utilizing in situ transesterification followed by fatty acid methyl ester extraction (ISTE). An ISTE method, based on the identified optimal parameters, was used to determine the fatty acid content of the new infant/adult nutritional formula reference material.

Evaluation of a Multichannel Non-Contact ECG System and Signal Quality Algorithms for Sleep Apnea Detection and Monitoring

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Ivan D. Castro

2018-02-01

Full Text Available Sleep-related conditions require high-cost and low-comfort diagnosis at the hospital during one night or longer. To overcome this situation, this work aims to evaluate an unobtrusive monitoring technique for sleep apnea. This paper presents, for the first time, the evaluation of contactless capacitively-coupled electrocardiography (ccECG signals for the extraction of sleep apnea features, together with a comparison of different signal quality indicators. A multichannel ccECG system is used to collect signals from 15 subjects in a sleep environment from different positions. Reference quality labels were assigned for every 30-s segment. Quality indicators were calculated, and their signal classification performance was evaluated. Features for the detection of sleep apnea were extracted from capacitive and reference signals. Sleep apnea features related to heart rate and heart rate variability achieved high similarity to the reference values, with p-values of 0.94 and 0.98, which is in line with the more than 95% beat-matching obtained. Features related to signal morphology presented lower similarity with the reference, although signal similarity metrics of correlation and coherence were relatively high. Quality-based automatic classification of the signals had a maximum accuracy of 91%. Best-performing quality indicators were based on template correlation and beat-detection. Results suggest that using unobtrusive cardiac signals for the automatic detection of sleep apnea can achieve similar performance as contact signals, and indicates clinical value of ccECG. Moreover, signal segments can automatically be classified by the proposed quality metrics as a pre-processing step. Including contactless respiration signals is likely to improve the performance and provide a complete unobtrusive cardiorespiratory monitoring solution; this is a promising alternative that will allow the screening of more patients with higher comfort, for a longer time, and at

Unsupervised Symbolization of Signal Time Series for Extraction of the Embedded Information

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Yue Li

2017-03-01

Full Text Available This paper formulates an unsupervised algorithm for symbolization of signal time series to capture the embedded dynamic behavior. The key idea is to convert time series of the digital signal into a string of (spatially discrete symbols from which the embedded dynamic information can be extracted in an unsupervised manner (i.e., no requirement for labeling of time series. The main challenges here are: (1 definition of the symbol assignment for the time series; (2 identification of the partitioning segment locations in the signal space of time series; and (3 construction of probabilistic finite-state automata (PFSA from the symbol strings that contain temporal patterns. The reported work addresses these challenges by maximizing the mutual information measures between symbol strings and PFSA states. The proposed symbolization method has been validated by numerical simulation as well as by experimentation in a laboratory environment. Performance of the proposed algorithm has been compared to that of two commonly used algorithms of time series partitioning.

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

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

2014-05-01

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

Huaier Aqueous Extract Induces Hepatocellular Carcinoma Cells Arrest in S Phase via JNK Signaling Pathway

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Chengshuo Zhang

2015-01-01

Full Text Available Huaier aqueous extract, the main active constituent of Huaier proteoglycan, has antihepatocarcinoma activity in experimental and clinical settings. However, the potential and associated antihepatoma mechanisms of Huaier extract are not yet fully understood. Therefore, in this study, we aimed to elucidate the inhibitory proliferation effect of Huaier extract on apoptosis and cycle of HepG2 and Bel-7402 cells. Our data demonstrated that incubation with Huaier extract resulted in a marked decrease in cell viability dose-dependently. Flow cytometric analysis showed that a 48 h treatment of Huaier extract caused cell apoptosis. Typical apoptotic nucleus alterations were observed with fluorescence microscope after Hoechst staining. Immunoblot analysis further demonstrated that Huaier extract activated caspase 3 and PARP. Additionally, Huaier extract inhibited the activity of p-ERK, p-p38, and p-JNK in terms of MAPK. Furthermore, Huaier extract induced HCC cells arrest in S phase and decreased the cycle related protein expression of β-catenin and cyclin D1. Studies with JNK specific inhibitor, SP600125, showed that Huaier extract induced S phase arrest and decreased β-catenin and cyclin D1 expression via JNK signaling pathway. In conclusion, we verify that Huaier extract causes cell apoptosis and induces hepatocellular carcinoma cells arrest in S phase via JNK pathway, which advances our understanding on the molecular mechanisms of Huaier extract in hepatocarcinoma management.

A Penalized Semialgebraic Deflation ICA Algorithm for the Efficient Extraction of Interictal Epileptic Signals.

Science.gov (United States)

Becker, Hanna; Albera, Laurent; Comon, Pierre; Kachenoura, Amar; Merlet, Isabelle

2017-01-01

As a noninvasive technique, electroencephalography (EEG) is commonly used to monitor the brain signals of patients with epilepsy such as the interictal epileptic spikes. However, the recorded data are often corrupted by artifacts originating, for example, from muscle activities, which may have much higher amplitudes than the interictal epileptic signals of interest. To remove these artifacts, a number of independent component analysis (ICA) techniques were successfully applied. In this paper, we propose a new deflation ICA algorithm, called penalized semialgebraic unitary deflation (P-SAUD) algorithm, that improves upon classical ICA methods by leading to a considerably reduced computational complexity at equivalent performance. This is achieved by employing a penalized semialgebraic extraction scheme, which permits us to identify the epileptic components of interest (interictal spikes) first and obviates the need of extracting subsequent components. The proposed method is evaluated on physiologically plausible simulated EEG data and actual measurements of three patients. The results are compared to those of several popular ICA algorithms as well as second-order blind source separation methods, demonstrating that P-SAUD extracts the epileptic spikes with the same accuracy as the best ICA methods, but reduces the computational complexity by a factor of 10 for 32-channel recordings. This superior computational efficiency is of particular interest considering the increasing use of high-resolution EEG recordings, whose analysis requires algorithms with low computational cost.

The detection of cavitation in hydraulic machines by use of ultrasonic signal analysis

International Nuclear Information System (INIS)

Gruber, P; Odermatt, P; Etterlin, M; Lerch, T; Frei, M; Farhat, M

2014-01-01

This presentation describes an experimental approach for the detection of cavitation in hydraulic machines by use of ultrasonic signal analysis. Instead of using the high frequency pulses (typically 1MHz) only for transit time measurement different other signal characteristics are extracted from the individual signals and its correlation function with reference signals in order to gain knowledge of the water conditions. As the pulse repetition rate is high (typically 100Hz), statistical parameters can be extracted of the signals. The idea is to find patterns in the parameters by a classifier that can distinguish between the different water states. This classification scheme has been applied to different cavitation sections: a sphere in a water flow in circular tube at the HSLU in Lucerne, a NACA profile in a cavitation tunnel and a Francis model test turbine both at LMH in Lausanne. From the signal raw data several statistical parameters in the time and frequency domain as well as from the correlation function with reference signals have been determined. As classifiers two methods were used: neural feed forward networks and decision trees. For both classification methods realizations with lowest complexity as possible are of special interest. It is shown that three signal characteristics, two from the signal itself and one from the correlation function are in many cases sufficient for the detection capability. The final goal is to combine these results with operating point, vibration, acoustic emission and dynamic pressure information such that a distinction between dangerous and not dangerous cavitation is possible

The Effects of Aronia melanocarpa 'Viking' Extracts in Attenuating RANKL-Induced Osteoclastic Differentiation by Inhibiting ROS Generation and c-FOS/NFATc1 Signaling.

Science.gov (United States)

Ghosh, Mithun; Kim, In Sook; Lee, Young Min; Hong, Seong Min; Lee, Taek Hwan; Lim, Ji Hong; Debnath, Trishna; Lim, Beong Ou

2018-03-08

This study aimed to determine the anti-osteoclastogenic effects of extracts from Aronia melanocarpa 'Viking' (AM) and identify the underlying mechanisms in vitro. Reactive oxygen species (ROS) are signal mediators in osteoclast differentiation. AM extracts inhibited ROS production in RAW 264.7 cells in a dose-dependent manner and exhibited strong radical scavenging activity. The extracts also attenuated the number of tartrate-resistant acid phosphatase (TRAP)-positive multinucleated osteoclasts. To attain molecular insights, the effect of the extracts on the signaling pathways induced by receptor activator of nuclear factor kappa B ligand (RANKL) were also investigated. RANKL triggers many transcription factors through the activation of mitogen-activated protein kinase (MAPK) and ROS, leading to the induction of osteoclast-specific genes. The extracts significantly suppressed RANKL-induced activation of MAPKs, such as extracellular signal-regulated kinase (ERK), c-Jun- N -terminal kinase (JNK) and p38 and consequently led to the downregulation of c-Fos and nuclear factor of activated T cells 1 (NFATc1) protein expression which ultimately suppress the activation of the osteoclast-specific genes, cathepsin K, TRAP, calcitonin receptor and integrin β₃. In conclusion, our findings suggest that AM extracts inhibited RANKL-induced osteoclast differentiation by downregulating ROS generation and inactivating JNK/ERK/p38, nuclear factor kappa B (NF-κB)-mediated c-Fos and NFATc1 signaling pathway.

Time Domain Feature Extraction Technique for earth's electric field signal prior to the Earthquake

International Nuclear Information System (INIS)

Astuti, W; Sediono, W; Akmeliawati, R; Salami, M J E

2013-01-01

Earthquake is one of the most destructive of natural disasters that killed many people and destroyed a lot of properties. By considering these catastrophic effects, it is highly important of knowing ahead of earthquakes in order to reduce the number of victims and material losses. Earth's electric field is one of the features that can be used to predict earthquakes (EQs), since it has significant changes in the amplitude of the signal prior to the earthquake. This paper presents a detailed analysis of the earth's electric field due to earthquakes which occurred in Greece, between January 1, 2008 and June 30, 2008. In that period of time, 13 earthquakes had occurred. 6 of them were recorded with magnitudes greater than Ms=5R (5R), while 7 of them were recorded with magnitudes greater than Ms=6R (6R). Time domain feature extraction technique is applied to analyze the 1st significant changes in the earth's electric field prior to the earthquake. Two different time domain feature extraction techniques are applied in this work, namely Simple Square Integral (SSI) and Root Mean Square (RMS). The 1st significant change of the earth's electric field signal in each of monitoring sites is extracted using those two techniques. The feature extraction result can be used as input parameter for an earthquake prediction system

An Enhanced Empirical Wavelet Transform for Features Extraction from Wind Turbine Condition Monitoring Signals

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Pu Shi

2017-07-01

Full Text Available Feature extraction from nonlinear and non-stationary (NNS wind turbine (WT condition monitoring (CM signals is challenging. Previously, much effort has been spent to develop advanced signal processing techniques for dealing with CM signals of this kind. The Empirical Wavelet Transform (EWT is one of the achievements attributed to these efforts. The EWT takes advantage of Empirical Mode Decomposition (EMD in dealing with NNS signals but is superior to the EMD in mode decomposition and robustness against noise. However, the conventional EWT meets difficulty in properly segmenting the frequency spectrum of the signal, especially when lacking pre-knowledge of the signal. The inappropriate segmentation of the signal spectrum will inevitably lower the accuracy of the EWT result and thus raise the difficulty of WT CM. To address this issue, an enhanced EWT is proposed in this paper by developing a feasible and efficient spectrum segmentation method. The effectiveness of the proposed method has been verified by using the bearing and gearbox CM data that are open to the public for the purpose of research. The experiment has shown that, after adopting the proposed method, it becomes much easier and more reliable to segment the frequency spectrum of the signal. Moreover, benefitting from the correct segmentation of the signal spectrum, the fault-related features of the CM signals are presented more explicitly in the time-frequency map of the enhanced EWT, despite the considerable noise contained in the signal and the shortage of pre-knowledge about the machine being investigated.

Windowing of THz time-domain spectroscopy signals: A study based on lactose

Science.gov (United States)

Vázquez-Cabo, José; Chamorro-Posada, Pedro; Fraile-Peláez, Francisco Javier; Rubiños-López, Óscar; López-Santos, José María; Martín-Ramos, Pablo

2016-05-01

Time-domain spectroscopy has established itself as a reference method for determining material parameters in the terahertz spectral range. This procedure requires the processing of the measured time-domain signals in order to estimate the spectral data. In this work, we present a thorough study of the properties of the signal windowing, a step previous to the parameter extraction algorithm, that permits to improve the accuracy of the results. Lactose has been used as sample material in the study.

The Effects of Aronia melanocarpa ‘Viking’ Extracts in Attenuating RANKL-Induced Osteoclastic Differentiation by Inhibiting ROS Generation and c-FOS/NFATc1 Signaling

Directory of Open Access Journals (Sweden)

Mithun Ghosh

2018-03-01

Full Text Available This study aimed to determine the anti-osteoclastogenic effects of extracts from Aronia melanocarpa ‘Viking’ (AM and identify the underlying mechanisms in vitro. Reactive oxygen species (ROS are signal mediators in osteoclast differentiation. AM extracts inhibited ROS production in RAW 264.7 cells in a dose-dependent manner and exhibited strong radical scavenging activity. The extracts also attenuated the number of tartrate-resistant acid phosphatase (TRAP-positive multinucleated osteoclasts. To attain molecular insights, the effect of the extracts on the signaling pathways induced by receptor activator of nuclear factor kappa B ligand (RANKL were also investigated. RANKL triggers many transcription factors through the activation of mitogen-activated protein kinase (MAPK and ROS, leading to the induction of osteoclast-specific genes. The extracts significantly suppressed RANKL-induced activation of MAPKs, such as extracellular signal-regulated kinase (ERK, c-Jun-N-terminal kinase (JNK and p38 and consequently led to the downregulation of c-Fos and nuclear factor of activated T cells 1 (NFATc1 protein expression which ultimately suppress the activation of the osteoclast-specific genes, cathepsin K, TRAP, calcitonin receptor and integrin β3. In conclusion, our findings suggest that AM extracts inhibited RANKL-induced osteoclast differentiation by downregulating ROS generation and inactivating JNK/ERK/p38, nuclear factor kappa B (NF-κB-mediated c-Fos and NFATc1 signaling pathway.

Microwave signal processing with photorefractive dynamic holography

Science.gov (United States)

Fotheringham, Edeline B.

Have you ever found yourself listening to the music playing from the closest stereo rather than to the bromidic (uninspiring) person speaking to you? Your ears receive information from two sources but your brain listens to only one. What if your cell phone could distinguish among signals sharing the same bandwidth too? There would be no "full" channels to stop you from placing or receiving a call. This thesis presents a nonlinear optical circuit capable of distinguishing uncorrelated signals that have overlapping temporal bandwidths. This so called autotuning filter is the size of a U.S. quarter dollar and requires less than 3 mW of optical power to operate. It is basically an oscillator in which the losses are compensated with dynamic holographic gain. The combination of two photorefractive crystals in the resonator governs the filter's winner-take-all dynamics through signal-competition for gain. This physical circuit extracts what is mathematically referred to as the largest principal component of its spatio-temporal input space. The circuit's practicality is demonstrated by its incorporation in an RF-photonic system. An unknown mixture of unknown microwave signals, received by an antenna array, constitutes the input to the system. The output electronically returns one of the original microwave signals. The front-end of the system down converts the 10 GHz microwave signals and amplifies them before the signals phase modulate optical beams. The optical carrier is suppressed from these beams so that it may not be considered as a signal itself to the autotuning filter. The suppression is achieved with two-beam coupling in a single photorefractive crystal. The filter extracts the more intense of the signals present on the carrier-suppressed input beams. The detection of the extracted signal restores the microwave signal to an electronic form. The system, without the receiving antenna array, is packaged in a 13 x 18 x 6″ briefcase. Its power consumption equals that

SOIL VAPOR EXTRACTION TECHNOLOGY: REFERENCE HANDBOOK

Science.gov (United States)

Soil vapor extraction (SVE) systems are being used in Increasing numbers because of the many advantages these systems hold over other soil treatment technologies. SVE systems appear to be simple in design and operation, yet the fundamentals governing subsurface vapor transport ar...

Design Implementation and Testing of a VLSI High Performance ASIC for Extracting the Phase of a Complex Signal

National Research Council Canada - National Science Library

Altmeyer, Ronald

2002-01-01

This thesis documents the research, circuit design, and simulation testing of a VLSI ASIC which extracts phase angle information from a complex sampled signal using the arctangent relationship: (phi=tan/-1 (Q/1...

Automatic Mapping Extraction from Multiecho T2-Star Weighted Magnetic Resonance Images for Improving Morphological Evaluations in Human Brain

Directory of Open Access Journals (Sweden)

Shaode Yu

2013-01-01

Full Text Available Mapping extraction is useful in medical image analysis. Similarity coefficient mapping (SCM replaced signal response to time course in tissue similarity mapping with signal response to TE changes in multiecho T2-star weighted magnetic resonance imaging without contrast agent. Since different tissues are with different sensitivities to reference signals, a new algorithm is proposed by adding a sensitivity index to SCM. It generates two mappings. One measures relative signal strength (SSM and the other depicts fluctuation magnitude (FMM. Meanwhile, the new method is adaptive to generate a proper reference signal by maximizing the sum of contrast index (CI from SSM and FMM without manual delineation. Based on four groups of images from multiecho T2-star weighted magnetic resonance imaging, the capacity of SSM and FMM in enhancing image contrast and morphological evaluation is validated. Average contrast improvement index (CII of SSM is 1.57, 1.38, 1.34, and 1.41. Average CII of FMM is 2.42, 2.30, 2.24, and 2.35. Visual analysis of regions of interest demonstrates that SSM and FMM show better morphological structures than original images, T2-star mapping and SCM. These extracted mappings can be further applied in information fusion, signal investigation, and tissue segmentation.

The signaling cascades of Ganoderma lucidum extracts in stimulating non-amyloidogenic protein secretion in human neuroblastoma SH-SY5Y cell lines.

Science.gov (United States)

Pinweha, Sirinthorn; Wanikiat, Payong; Sanvarinda, Yupin; Supavilai, Porntip

2008-12-19

Ganoderma lucidum (GL) is a medicinal mushroom that possesses various pharmacological properties which are also documented in the ancient reports where GL is praised for its effects on the promotion of health and longevity. In this study, we have investigated the effect of GL mycelia extracts on the non-amyloidogenic protein secretion (sAPPalpha) and the amyloid precursor protein (APP) expression in SH-SY5Y neuroblastoma cells. In order to characterize the signaling pathway which mediates GL-enhanced sAPPalpha secretion, we used inhibitors of nerve growth factor (NGF) signaling pathways, phosphatidylinositol 3 kinase (PI3K), phospholipase Cgamma1 (PLCgamma1), protein kinase C (PKC) and extracellular signal-regulated kinase (ERK1/2), to block GL-mediated sAPPalpha secretion as well as ERK1/2 and PKC activation by using Western blot analysis. Our results provided for the first time evidence that GL mycelia extracts increased APP expression and promoted sAPPalpha secretion. In addition, GL extracts activated ERK1/2 and PKC phosphorylation. The complex signaling cascades of PI3K and ERK may be responsible for GL-mediated sAPPalpha secretion.

Detecting impact signal in mechanical fault diagnosis under chaotic and Gaussian background noise

Science.gov (United States)

Hu, Jinfeng; Duan, Jie; Chen, Zhuo; Li, Huiyong; Xie, Julan; Chen, Hanwen

2018-01-01

In actual fault diagnosis, useful information is often submerged in heavy noise, and the feature information is difficult to extract. Traditional methods, such like stochastic resonance (SR), which using noise to enhance weak signals instead of suppressing noise, failed in chaotic background. Neural network, which use reference sequence to estimate and reconstruct the background noise, failed in white Gaussian noise. To solve these problems, a novel weak signal detection method aimed at the problem of detecting impact signal buried under heavy chaotic and Gaussian background noise is proposed. First, the proposed method obtains the virtual reference sequence by constructing the Hankel data matrix. Then an M-order optimal FIR filter is designed, which can minimize the output power of background noise and pass the weak periodic signal undistorted. Finally, detection and reconstruction of the weak periodic signal are achieved from the output SBNR (signal to background noise ratio). The simulation shows, compared with the stochastic resonance (SR) method, the proposed method can detect the weak periodic signal in chaotic noise background while stochastic resonance (SR) method cannot. Compared with the neural network method, (a) the proposed method does not need a reference sequence while neural network method needs one; (b) the proposed method can detect the weak periodic signal in white Gaussian noise background while the neural network method fails, in chaotic noise background, the proposed method can detect the weak periodic signal under a lower SBNR (about 8-17 dB lower) than the neural network method; (c) the proposed method can reconstruct the weak periodic signal precisely.

Feature Extraction for Track Section Status Classification Based on UGW Signals

Directory of Open Access Journals (Sweden)

Lei Yuan

2018-04-01

Full Text Available Track status classification is essential for the stability and safety of railway operations nowadays, when railway networks are becoming more and more complex and broad. In this situation, monitoring systems are already a key element in applications dedicated to evaluating the status of a certain track section, often determining whether it is free or occupied by a train. Different technologies have already been involved in the design of monitoring systems, including ultrasonic guided waves (UGW. This work proposes the use of the UGW signals captured by a track monitoring system to extract the features that are relevant for determining the corresponding track section status. For that purpose, three features of UGW signals have been considered: the root mean square value, the energy, and the main frequency components. Experimental results successfully validated how these features can be used to classify the track section status into free, occupied and broken. Furthermore, spatial and temporal dependencies among these features were analysed in order to show how they can improve the final classification performance. Finally, a preliminary high-level classification system based on deep learning networks has been envisaged for future works.

A simple iterative independent component analysis algorithm for vibration source signal identification of complex structures

Directory of Open Access Journals (Sweden)

Dong-Sup Lee

2015-01-01

Full Text Available Independent Component Analysis (ICA, one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: insta- bility and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to vali- date the proposed method, numerical analyses have been carried out for a virtual response model and a 30 m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique.

Adaptive Control with Reference Model Modification

Science.gov (United States)

Stepanyan, Vahram; Krishnakumar, Kalmanje

2012-01-01

This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example

Application of a modified BCR sequential extraction (three-step) procedure for the determination of extractable trace metal contents in a sewage sludge amended soil reference material (CRM 483), complemented by a three-year stability study of acetic acid and EDTA extractable metal content.

Science.gov (United States)

Rauret, G; López-Sánchez, J F; Sahuquillo, A; Barahona, E; Lachica, M; Ure, A M; Davidson, C M; Gomez, A; Lück, D; Bacon, J; Yli-Halla, M; Muntau, H; Quevauviller, P

2000-06-01

This paper provides additional data on a sewage sludge amended soil certified reference material, CRM 483, which was certified in 1997 for its EDTA and acetic acid extractable contents of some trace metals, following standardised extraction procedures. The additional work aimed to test the long-term stability of the material and the applicability of an improved version of the BCR three-step sequential extraction procedure on the sewage sludge amended soil (CRM 483). The paper demonstrates the CRM 483 long-term stability for EDTA and acetic acid extractable contents of Cd, Cr, Cu, Ni, Pb and Zn and gives the results (obtained in the framework of an interlaboratory study) for the extractable contents of the same elements in the CRM 483, following the BCR three-step sequential extraction scheme. The aqua regia extractable contents following the ISO 11466 Standard are also given. The data are given as indicative (not certified) values.

Extracted atmospheric impairments on earth-sky signal quality in tropical regions at Ku-band

Science.gov (United States)

Al-Saegh, Ali Mohammed; Sali, Aduwati; Mandeep, J. S.; Ismail, Alyani

2013-11-01

Atmospheric condition variations were shown to have a major effect on the earth sky signal quality at Ku band. Moreover, such variations increased in the tropical regions as compared to temperate areas due to their different weather parameters. With the increase of recent satellite communication technology applications throughout the tropical countries and lack of information regarding the atmospheric impairments analysis, simulation and mitigation techniques, there is an ever increasing need for extracting a unique and accurate performance of the signal quality effects during highly natural tropical weather impairments. This paper presents a new method developed for proper analysis with distinctive and highly realistic performance evaluation for signal quality during the atmospheric conditions variations in 14 tropical areas from the four continents analyzed based on actual measured parameters. The method implementation includes signal attenuation, carrier to noise ratio, symbol energy to noise ratio, and symbol error rate at different areas and different modulation schemes. Furthermore, for improvement in analysis in terms of covering more remarkable regions in tropics, the paper provides new measurements data with analysis for certain region in tropics used as a test bed and to add measurement data of such area to the world's data base for future researchers. The results show a significant investigation and performance observation in terms of weather impairments in tropical regions in general and each region in that area in particular regarding the signal attenuation and error rates accompanied for several transmission schemes.

Porting Gravitational Wave Signal Extraction to Parallel Virtual Machine (PVM)

Science.gov (United States)

Thirumalainambi, Rajkumar; Thompson, David E.; Redmon, Jeffery

2009-01-01

Laser Interferometer Space Antenna (LISA) is a planned NASA-ESA mission to be launched around 2012. The Gravitational Wave detection is fundamentally the determination of frequency, source parameters, and waveform amplitude derived in a specific order from the interferometric time-series of the rotating LISA spacecrafts. The LISA Science Team has developed a Mock LISA Data Challenge intended to promote the testing of complicated nested search algorithms to detect the 100-1 millihertz frequency signals at amplitudes of 10E-21. However, it has become clear that, sequential search of the parameters is very time consuming and ultra-sensitive; hence, a new strategy has been developed. Parallelization of existing sequential search algorithms of Gravitational Wave signal identification consists of decomposing sequential search loops, beginning with outermost loops and working inward. In this process, the main challenge is to detect interdependencies among loops and partitioning the loops so as to preserve concurrency. Existing parallel programs are based upon either shared memory or distributed memory paradigms. In PVM, master and node programs are used to execute parallelization and process spawning. The PVM can handle process management and process addressing schemes using a virtual machine configuration. The task scheduling and the messaging and signaling can be implemented efficiently for the LISA Gravitational Wave search process using a master and 6 nodes. This approach is accomplished using a server that is available at NASA Ames Research Center, and has been dedicated to the LISA Data Challenge Competition. Historically, gravitational wave and source identification parameters have taken around 7 days in this dedicated single thread Linux based server. Using PVM approach, the parameter extraction problem can be reduced to within a day. The low frequency computation and a proxy signal-to-noise ratio are calculated in separate nodes that are controlled by the master

Signal quality measures for unsupervised blood pressure measurement

International Nuclear Information System (INIS)

Abdul Sukor, J; Redmond, S J; Lovell, N H; Chan, G S H

2012-01-01

Accurate systolic and diastolic pressure estimation, using automated blood pressure measurement, is difficult to achieve when the transduced signals are contaminated with noise or interference, such as movement artifact. This study presents an algorithm for automated signal quality assessment in blood pressure measurement by determining the feasibility of accurately detecting systolic and diastolic pressures when corrupted with various levels of movement artifact. The performance of the proposed algorithm is compared to a manually annotated reference scoring (RS). Based on visual representations and audible playback of Korotkoff sounds, the creation of the RS involved two experts identifying sections of the recorded sounds and annotating sections of noise contamination. The experts determined the systolic and diastolic pressure in 100 recorded Korotkoff sound recordings, using a simultaneous electrocardiograph as a reference signal. The recorded Korotkoff sounds were acquired from 25 healthy subjects (16 men and 9 women) with a total of four measurements per subject. Two of these measurements contained purposely induced noise artifact caused by subject movement. Morphological changes in the cuff pressure signal and the width of the Korotkoff pulse were extracted features which were believed to be correlated with the noise presence in the recorded Korotkoff sounds. Verification of reliable Korotkoff pulses was also performed using extracted features from the oscillometric waveform as recorded from the inflatable cuff. The time between an identified noise section and a verified Korotkoff pulse was the key feature used to determine the validity of possible systolic and diastolic pressures in noise contaminated Korotkoff sounds. The performance of the algorithm was assessed based on the ability to: verify if a signal was contaminated with any noise; the accuracy, sensitivity and specificity of this noise classification, and the systolic and diastolic pressure

Multivariate reference technique for quantitative analysis of fiber-optic tissue Raman spectroscopy.

Science.gov (United States)

Bergholt, Mads Sylvest; Duraipandian, Shiyamala; Zheng, Wei; Huang, Zhiwei

2013-12-03

We report a novel method making use of multivariate reference signals of fused silica and sapphire Raman signals generated from a ball-lens fiber-optic Raman probe for quantitative analysis of in vivo tissue Raman measurements in real time. Partial least-squares (PLS) regression modeling is applied to extract the characteristic internal reference Raman signals (e.g., shoulder of the prominent fused silica boson peak (~130 cm(-1)); distinct sapphire ball-lens peaks (380, 417, 646, and 751 cm(-1))) from the ball-lens fiber-optic Raman probe for quantitative analysis of fiber-optic Raman spectroscopy. To evaluate the analytical value of this novel multivariate reference technique, a rapid Raman spectroscopy system coupled with a ball-lens fiber-optic Raman probe is used for in vivo oral tissue Raman measurements (n = 25 subjects) under 785 nm laser excitation powers ranging from 5 to 65 mW. An accurate linear relationship (R(2) = 0.981) with a root-mean-square error of cross validation (RMSECV) of 2.5 mW can be obtained for predicting the laser excitation power changes based on a leave-one-subject-out cross-validation, which is superior to the normal univariate reference method (RMSE = 6.2 mW). A root-mean-square error of prediction (RMSEP) of 2.4 mW (R(2) = 0.985) can also be achieved for laser power prediction in real time when we applied the multivariate method independently on the five new subjects (n = 166 spectra). We further apply the multivariate reference technique for quantitative analysis of gelatin tissue phantoms that gives rise to an RMSEP of ~2.0% (R(2) = 0.998) independent of laser excitation power variations. This work demonstrates that multivariate reference technique can be advantageously used to monitor and correct the variations of laser excitation power and fiber coupling efficiency in situ for standardizing the tissue Raman intensity to realize quantitative analysis of tissue Raman measurements in vivo, which is particularly appealing in

One-Dimensional Signal Extraction Of Paper-Written ECG Image And Its Archiving

Science.gov (United States)

Zhang, Zhi-ni; Zhang, Hong; Zhuang, Tian-ge

1987-10-01

A method for converting paper-written electrocardiograms to one dimensional (1-D) signals for archival storage on floppy disk is presented here. Appropriate image processing techniques were employed to remove the back-ground noise inherent to ECG recorder charts and to reconstruct the ECG waveform. The entire process consists of (1) digitization of paper-written ECGs with an image processing system via a TV camera; (2) image preprocessing, including histogram filtering and binary image generation; (3) ECG feature extraction and ECG wave tracing, and (4) transmission of the processed ECG data to IBM-PC compatible floppy disks for storage and retrieval. The algorithms employed here may also be used in the recognition of paper-written EEG or EMG and may be useful in robotic vision.

Myrcia bella Leaf Extract Presents Hypoglycemic Activity via PI3k/Akt Insulin Signaling Pathway

Directory of Open Access Journals (Sweden)

Priscilla Maria Ponce Vareda

2014-01-01

Full Text Available Species of Myrcia are used by indigenous people and in traditional communities in Brazil for the treatment of Diabetes mellitus. We investigated the hypoglycemic effect of the extract of leaves of Myrcia bella in diabetic mice. The chemical fingerprinting of the 70% EtOH extract characterized as main constituents flavonoid aglycones, flavonoid-O-glycosides, and acylated flavonoid-O-glycosides derivatives of quercetin and myricetin. Mice were treated with saline or extract of M. bella (300 or 600 mg/Kg b.w. for 14 days. Body weight and water and food intake were measured every day. Fasting blood glucose was measured weekly. At the end of the treatment, blood insulin, triglycerides, total cholesterol, and protein were measured. Glycogen content and expression of proteins of the insulin signaling pathway were measured in liver. The treatment with 600 mg/Kg reduced the fasting blood glucose in diabetic mice of the 7th day as water and food intake and increased hepatic glycogen. Total cholesterol and triglycerides were reduced in diabetic treated mice. The treatment increased the expression of IRS-1, PI3-K, and AKT in the livers of diabetic treated mice. The results indicate that the extract of the leaves of Myrcia bella has hypoglycemic properties and possibly acts to regulate glucose uptake by the liver.

ECG signal processing

NARCIS (Netherlands)

2009-01-01

A system extracts an ECG signal from a composite signal (308) representing an electric measurement of a living subject. Identification means (304) identify a plurality of temporal segments (309) of the composite signal corresponding to a plurality of predetermined segments (202,204,206) of an ECG

Wavelet-based ground vehicle recognition using acoustic signals

Science.gov (United States)

Choe, Howard C.; Karlsen, Robert E.; Gerhart, Grant R.; Meitzler, Thomas J.

1996-03-01

We present, in this paper, a wavelet-based acoustic signal analysis to remotely recognize military vehicles using their sound intercepted by acoustic sensors. Since expedited signal recognition is imperative in many military and industrial situations, we developed an algorithm that provides an automated, fast signal recognition once implemented in a real-time hardware system. This algorithm consists of wavelet preprocessing, feature extraction and compact signal representation, and a simple but effective statistical pattern matching. The current status of the algorithm does not require any training. The training is replaced by human selection of reference signals (e.g., squeak or engine exhaust sound) distinctive to each individual vehicle based on human perception. This allows a fast archiving of any new vehicle type in the database once the signal is collected. The wavelet preprocessing provides time-frequency multiresolution analysis using discrete wavelet transform (DWT). Within each resolution level, feature vectors are generated from statistical parameters and energy content of the wavelet coefficients. After applying our algorithm on the intercepted acoustic signals, the resultant feature vectors are compared with the reference vehicle feature vectors in the database using statistical pattern matching to determine the type of vehicle from where the signal originated. Certainly, statistical pattern matching can be replaced by an artificial neural network (ANN); however, the ANN would require training data sets and time to train the net. Unfortunately, this is not always possible for many real world situations, especially collecting data sets from unfriendly ground vehicles to train the ANN. Our methodology using wavelet preprocessing and statistical pattern matching provides robust acoustic signal recognition. We also present an example of vehicle recognition using acoustic signals collected from two different military ground vehicles. In this paper, we will

Advancing Affect Modeling via Preference Learning and Unsupervised Feature Extraction

DEFF Research Database (Denmark)

Martínez, Héctor Pérez

strategies (error functions and training algorithms) for artificial neural networks are examined across synthetic and psycho-physiological datasets, and compared against support vector machines and Cohen’s method. Results reveal the best training strategies for neural networks and suggest their superiority...... difficulties, ordinal reports such as rankings and ratings can yield more reliable affect annotations than alternative tools. This thesis explores preference learning methods to automatically learn computational models from ordinal annotations of affect. In particular, an extensive collection of training...... over the other examined methods. The second challenge addressed in this thesis refers to the extraction of relevant information from physiological modalities. Deep learning is proposed as an automatic approach to extract input features for models of affect from physiological signals. Experiments...

Multiscale Signal Analysis and Modeling

CERN Document Server

Zayed, Ahmed

2013-01-01

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

Variable reflectivity signal mirrors and signal response measurements

International Nuclear Information System (INIS)

Vine, Glenn de; Shaddock, Daniel A; McClelland, David E

2002-01-01

Future gravitational wave detectors will include some form of signal mirror in order to alter the signal response of the device. We introduce interferometer configurations which utilize a variable reflectivity signal mirror allowing a tunable peak frequency and variable signal bandwidth. A detector configured with a Fabry-Perot cavity as the signal mirror is compared theoretically with one using a Michelson interferometer for a signal mirror. A system for the measurement of the interferometer signal responses is introduced. This technique is applied to a power-recycled Michelson interferometer with resonant sideband extraction. We present broadband measurements of the benchtop prototype's signal response for a range of signal cavity detunings. This technique is also applicable to most other gravitational wave detector configurations

Variable reflectivity signal mirrors and signal response measurements

CERN Document Server

Vine, G D; McClelland, D E

2002-01-01

Future gravitational wave detectors will include some form of signal mirror in order to alter the signal response of the device. We introduce interferometer configurations which utilize a variable reflectivity signal mirror allowing a tunable peak frequency and variable signal bandwidth. A detector configured with a Fabry-Perot cavity as the signal mirror is compared theoretically with one using a Michelson interferometer for a signal mirror. A system for the measurement of the interferometer signal responses is introduced. This technique is applied to a power-recycled Michelson interferometer with resonant sideband extraction. We present broadband measurements of the benchtop prototype's signal response for a range of signal cavity detunings. This technique is also applicable to most other gravitational wave detector configurations.

Buck-Boost DC-DC Converter Control by Using the Extracted Model from Signal Flow Graph Method

OpenAIRE

Mohammadian, Leila; Babaei, Ebrahim; Bannae Sharifian, Mohammad Bagher

2015-01-01

In this paper, the signal flow graph technique and Mason gain formula are applied for extracting the model and transfer functions from control to output and from input to output of a buck-boost converter. In order to investigate a controller necessity for the converter of assumed parameters, the frequency and time domain analysis are done and the open loop system characteristics are verified and the needed closed loop controlled system specifications are determined. Finally designing a contro...

Oryza sativa (Rice) Hull Extract Inhibits Lipopolysaccharide-Induced Inflammatory Response in RAW264.7 Macrophages by Suppressing Extracellular Signal-regulated Kinase, c-Jun N-terminal Kinase, and Nuclear Factor-κB Activation.

Science.gov (United States)

Ha, Sang Keun; Sung, Jeehye; Choi, Inwook; Kim, Yoonsook

2016-01-01

Rice ( Oryza sativa ) is a major cereal crop in many Asian countries and an important staple food source. Rice hulls have been reported to possess antioxidant activities. In this study, we evaluated the antiinflammatory effects of rice hull extract and associated signal transduction mechanisms in lipopolysaccharide (LPS)-stimulated RAW 264.7 macrophages. We found that rice hull extract inhibited nitric oxide (NO) and prostaglandin E 2 by suppressing the expression of inducible NO synthase and cyclooxygenase-2, respectively. The release of interleukin-1β and tumor necrosis factor-α was also reduced in a dose-dependent manner. Furthermore, rice hull extract attenuated the activation of nuclear factor-kappa B (NF-κB), as well as the phosphorylation of mitogen-activated protein kinases, extracellular signal-regulated kinase (ERK), and c-Jun N-terminal kinase (JNK), in LPS-stimulated RAW264.7 cells. This suggests that rice hull extract decreases the production of inflammatory mediators by downregulating ERK and JNK and the NF-κB signal pathway in RAW 264.7 cells. Rice hull extract inhibits the lipopolysaccharide-induced inflammatory response in RAW264.7 macrophages.Rice hull extract inhibited nitric oxide and prostaglandin E 2 by suppressing the expression of inducible NO synthase and cyclooxygenase-2, respectively.Rice hull extract exerted anti-inflammatory effect through inhibition of nuclear factor-kappa B, extracellular signal-regulated kinase and c-Jun N-terminal kinase signaling pathways.Rice hull extract may provide a potential therapeutic approach for inflammatory diseases. Abbreviations used: COX-2: cyclooxygenase-2, ERK: extracellular signal-regulated kinase, IκB: inhibitory kappa B, IL-1β: interleukin-1β, iNOS: inducible NO synthase, JNK: c-Jun N-terminal kinase, LPS: lipopolysaccharide, MAPKs: mitogen-activated protein kinases, NF-κB: nuclear factor-κB, NO: nitric oxide, PGE2: prostaglandin E2, RHE: rice hull extract, ROS: reactive oxygen species

Fetal ECG Extraction from Abdominal Signals: A Review on Suppression of Fundamental Power Line Interference Component and Its Harmonics

Directory of Open Access Journals (Sweden)

Dragoş-Daniel Ţarălungă

2014-01-01

Full Text Available Interference of power line (PLI (fundamental frequency and its harmonics is usually present in biopotential measurements. Despite all countermeasures, the PLI still corrupts physiological signals, for example, electromyograms (EMG, electroencephalograms (EEG, and electrocardiograms (ECG. When analyzing the fetal ECG (fECG recorded on the maternal abdomen, the PLI represents a particular strong noise component, being sometimes 10 times greater than the fECG signal, and thus impairing the extraction of any useful information regarding the fetal health state. Many signal processing methods for cancelling the PLI from biopotentials are available in the literature. In this review study, six different principles are analyzed and discussed, and their performance is evaluated on simulated data (three different scenarios, based on five quantitative performance indices.

Fetal ECG extraction from abdominal signals: a review on suppression of fundamental power line interference component and its harmonics.

Science.gov (United States)

Ţarălungă, Dragoş-Daniel; Ungureanu, Georgeta-Mihaela; Gussi, Ilinca; Strungaru, Rodica; Wolf, Werner

2014-01-01

Interference of power line (PLI) (fundamental frequency and its harmonics) is usually present in biopotential measurements. Despite all countermeasures, the PLI still corrupts physiological signals, for example, electromyograms (EMG), electroencephalograms (EEG), and electrocardiograms (ECG). When analyzing the fetal ECG (fECG) recorded on the maternal abdomen, the PLI represents a particular strong noise component, being sometimes 10 times greater than the fECG signal, and thus impairing the extraction of any useful information regarding the fetal health state. Many signal processing methods for cancelling the PLI from biopotentials are available in the literature. In this review study, six different principles are analyzed and discussed, and their performance is evaluated on simulated data (three different scenarios), based on five quantitative performance indices.

Topological signal processing

CERN Document Server

Robinson, Michael

2014-01-01

Signal processing is the discipline of extracting information from collections of measurements. To be effective, the measurements must be organized and then filtered, detected, or transformed to expose the desired information.  Distortions caused by uncertainty, noise, and clutter degrade the performance of practical signal processing systems. In aggressively uncertain situations, the full truth about an underlying signal cannot be known.  This book develops the theory and practice of signal processing systems for these situations that extract useful, qualitative information using the mathematics of topology -- the study of spaces under continuous transformations.  Since the collection of continuous transformations is large and varied, tools which are topologically-motivated are automatically insensitive to substantial distortion. The target audience comprises practitioners as well as researchers, but the book may also be beneficial for graduate students.

Independent component analysis for the extraction of reliable protein signal profiles from MALDI-TOF mass spectra.

Science.gov (United States)

Mantini, Dante; Petrucci, Francesca; Del Boccio, Piero; Pieragostino, Damiana; Di Nicola, Marta; Lugaresi, Alessandra; Federici, Giorgio; Sacchetta, Paolo; Di Ilio, Carmine; Urbani, Andrea

2008-01-01

Independent component analysis (ICA) is a signal processing technique that can be utilized to recover independent signals from a set of their linear mixtures. We propose ICA for the analysis of signals obtained from large proteomics investigations such as clinical multi-subject studies based on MALDI-TOF MS profiling. The method is validated on simulated and experimental data for demonstrating its capability of correctly extracting protein profiles from MALDI-TOF mass spectra. The comparison on peak detection with an open-source and two commercial methods shows its superior reliability in reducing the false discovery rate of protein peak masses. Moreover, the integration of ICA and statistical tests for detecting the differences in peak intensities between experimental groups allows to identify protein peaks that could be indicators of a diseased state. This data-driven approach demonstrates to be a promising tool for biomarker-discovery studies based on MALDI-TOF MS technology. The MATLAB implementation of the method described in the article and both simulated and experimental data are freely available at http://www.unich.it/proteomica/bioinf/.

Cinnamon extract regulates glucose transporter and insulin-signaling gene expression in mouse adipocytes.

Science.gov (United States)

Cao, Heping; Graves, Donald J; Anderson, Richard A

2010-11-01

Cinnamon extracts (CE) are reported to have beneficial effects on people with normal and impaired glucose tolerance, the metabolic syndrome, type 2 diabetes, and insulin resistance. However, clinical results are controversial. Molecular characterization of CE effects is limited. This study investigated the effects of CE on gene expression in cultured mouse adipocytes. Water-soluble CE was prepared from ground cinnamon (Cinnamomum burmannii). Quantitative real-time PCR was used to investigate CE effects on the expression of genes coding for adipokines, glucose transporter (GLUT) family, and insulin-signaling components in mouse 3T3-L1 adipocytes. CE (100 μg/ml) increased GLUT1 mRNA levels 1.91±0.15, 4.39±0.78, and 6.98±2.18-fold of the control after 2-, 4-, and 16-h treatments, respectively. CE decreased the expression of further genes encoding insulin-signaling pathway proteins including GSK3B, IGF1R, IGF2R, and PIK3R1. This study indicates that CE regulates the expression of multiple genes in adipocytes and this regulation could contribute to the potential health benefits of CE. Published by Elsevier GmbH.

Impact of the choice of the precipitation reference data set on climate model selection and the resulting climate change signal

Science.gov (United States)

Gampe, D.; Ludwig, R.

2017-12-01

Regional Climate Models (RCMs) that downscale General Circulation Models (GCMs) are the primary tool to project future climate and serve as input to many impact models to assess the related changes and impacts under such climate conditions. Such RCMs are made available through the Coordinated Regional climate Downscaling Experiment (CORDEX). The ensemble of models provides a range of possible future climate changes around the ensemble mean climate change signal. The model outputs however are prone to biases compared to regional observations. A bias correction of these deviations is a crucial step in the impact modelling chain to allow the reproduction of historic conditions of i.e. river discharge. However, the detection and quantification of model biases are highly dependent on the selected regional reference data set. Additionally, in practice due to computational constraints it is usually not feasible to consider the entire ensembles of climate simulations with all members as input for impact models which provide information to support decision-making. Although more and more studies focus on model selection based on the preservation of the climate model spread, a selection based on validity, i.e. the representation of the historic conditions is still a widely applied approach. In this study, several available reference data sets for precipitation are selected to detect the model bias for the reference period 1989 - 2008 over the alpine catchment of the Adige River located in Northern Italy. The reference data sets originate from various sources, such as station data or reanalysis. These data sets are remapped to the common RCM grid at 0.11° resolution and several indicators, such as dry and wet spells, extreme precipitation and general climatology, are calculate to evaluate the capability of the RCMs to produce the historical conditions. The resulting RCM spread is compared against the spread of the reference data set to determine the related uncertainties and

Sensor-based vibration signal feature extraction using an improved composite dictionary matching pursuit algorithm.

Science.gov (United States)

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-09-09

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm

Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm

Directory of Open Access Journals (Sweden)

Lingli Cui

2014-09-01

Full Text Available This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and

Gelidium elegans Extract Ameliorates Type 2 Diabetes via Regulation of MAPK and PI3K/Akt Signaling.

Science.gov (United States)

Choi, Jia; Kim, Kui-Jin; Koh, Eun-Jeong; Lee, Boo-Yong

2018-01-06

Gelidium elegans , a red alga native to the Asia Pacific region, contains biologically active polyphenols. We conducted a molecular biological study of the anti-diabetic effect of Gelidium elegans extract (GEE) in C57BL/KsJ-db/db mice. Mice that had been administered GEE had significantly lower body mass, water consumption, and fasting blood glucose than db/db controls. Moreover, hemoglobin A1c (HbA1c), an indicator of the glycemic status of people with diabetes, was significantly lower in mice that had been administered GEE. We also found that 200 mg/kg/day GEE upregulates the insulin signaling pathway by activating insulin receptor substrate-1 (IRS-1) and phosphoinositide 3-kinase (PI3K), and increasing the expression of glucose transporter type 4 (GLUT4). In parallel, mitogen-activated protein kinase (MAPK) activity was lower in GEE-treated groups. In summary, these findings indicate that GEE regulates glucose metabolism by activating the insulin signaling pathway and downregulating the MAPK signaling pathway.

Transcriptomic Analysis Reveals Wound Healing of Morus alba Root Extract by Up-Regulating Keratin Filament and CXCL12/CXCR4 Signaling.

Science.gov (United States)

Kim, Kang-Hoon; Chung, Won-Seok; Kim, Yoomi; Kim, Ki-Suk; Lee, In-Seung; Park, Ji Young; Jeong, Hyeon-Soo; Na, Yun-Cheol; Lee, Chang-Hun; Jang, Hyeung-Jin

2015-08-01

Facilitation of the wound healing process is important because a prolonged wound site increases pain and the risk of infection. In oriental medicine, an extract of Morus alba root (MA) has usually been prescribed as traditional treatment for accelerating wound healing, and it has been proven to be safe for centuries. To study the molecular mechanism of MA-mediated skin wound healing, we performed a primary cell culture and a skin explant culture and observed significant difference between the groups with and without MA extract. In the cellular system, a real-time cell analysis and real-time quantitative PCR were performed. It was found that MA extract enhanced proliferation in a dose-dependent manner on Kera-308 cell line, and up-regulated keratin expression including wound-induced Krt6a. In skin explant culture, the mRNA level derived from cell outgrowth displayed a tendency toward more up-regulated mRNA associated keratin filaments and toward a more up-regulated mRNA level of C-X-C motif chemokine 12 (CXCL12) and a chemokine receptor 4 (CXCR4) axis signaling pathway downstream. In this process, we concluded that MA extract had a scientific possibility of wound repair by increasing intracellular and extracellular supports and by inducing a CXCL12/CXCR4 signaling pathway. Copyright © 2015 John Wiley & Sons, Ltd.

PDK1 in NF-κB signaling is a target of Xanthium strumarium methanolic extract-mediated anti-inflammatory activities.

Science.gov (United States)

Hossen, Muhammad Jahangir; Cho, Jae Youl; Kim, Daewon

2016-08-22

Xanthium strumarium L. (Asteraceae) has traditionally been used to treat bacterial infections, nasal sinusitis, urticaria, arthritis, chronic bronchitis and rhinitis, allergic rhinitis, edema, lumbago, and other ailments. However, the molecular mechanisms by which this plant exerts its anti-inflammatory effects are poorly characterized. Here we studied the immunopharmacological activities of the methanolic extract of the aerial parts of this plant (Xs-ME) and validated its pharmacological targets. To evaluate the anti-inflammatory activity of Xs-ME, we employed lipopolysaccharide (LPS)-treated macrophages and an HCl/EtOH-induced mouse model of gastritis. We also used HPLC to identify the potentially active anti-inflammatory components of this extract. The molecular mechanisms of its anti-inflammatory activity were studied by kinase assays, reporter gene assays, immunoprecipitation analysis, and overexpression of target enzymes. The production of nitric oxide (NO) and prostaglandin E2 (PGE2) were both suppressed by Xs-ME. Moreover, orally administered Xs-ME ameliorated HCl/EtOH-induced gastric lesions. Furthermore, this extract downregulated the expression of inducible NO synthase (iNOS) and cyclooxygenase (COX)-2 and reduced the nuclear levels of NF-κB. Signaling events upstream of NF-κB translocation, such as phosphorylation of AKT and the formation of PDK1-AKT signaling complexes, were also inhibited by Xs-ME. Moreover, Xs-ME suppressed the enzymatic activity of PDK1. Additionally, PDK1-induced luciferase activity and Akt phosphorylation were both inhibited by Xs-ME. We also identified the polyphenol resveratrol as a likely active anti-inflammatory component in Xs-ME that targets PDK1. Xs-ME exerts anti-inflammatory activity in vitro and in vivo by inhibiting PDK1 kinase activity and blocking signaling to its downstream transcription factor, NF-κB. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Classification of EEG-P300 Signals Extracted from Brain Activities in BCI Systems Using ν-SVM and BLDA Algorithms

Directory of Open Access Journals (Sweden)

Ali MOMENNEZHAD

2014-06-01

Full Text Available In this paper, a linear predictive coding (LPC model is used to improve classification accuracy, convergent speed to maximum accuracy, and maximum bitrates in brain computer interface (BCI system based on extracting EEG-P300 signals. First, EEG signal is filtered in order to eliminate high frequency noise. Then, the parameters of filtered EEG signal are extracted using LPC model. Finally, the samples are reconstructed by LPC coefficients and two classifiers, a Bayesian Linear discriminant analysis (BLDA, and b the υ-support vector machine (υ-SVM are applied in order to classify. The proposed algorithm performance is compared with fisher linear discriminant analysis (FLDA. Results show that the efficiency of our algorithm in improving classification accuracy and convergent speed to maximum accuracy are much better. As example at the proposed algorithms, respectively BLDA with LPC model and υ-SVM with LPC model with8 electrode configuration for subject S1 the total classification accuracy is improved as 9.4% and 1.7%. And also, subject 7 at BLDA and υ-SVM with LPC model algorithms (LPC+BLDA and LPC+ υ-SVM after block 11th converged to maximum accuracy but Fisher Linear Discriminant Analysis (FLDA algorithm did not converge to maximum accuracy (with the same configuration. So, it can be used as a promising tool in designing BCI systems.

Non-stationary signal analysis based on general parameterized time-frequency transform and its application in the feature extraction of a rotary machine

Science.gov (United States)

Zhou, Peng; Peng, Zhike; Chen, Shiqian; Yang, Yang; Zhang, Wenming

2018-06-01

With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time-frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.

Neural Networks for the Extraction of the ΛC Signal in p-Pb collisions at 
 √sNN = 5.02 TeV

CERN Document Server

Giampaolo, Alberto

2016-01-01

The charmed baryon ΛC is of interest for the characterization of the quark-gluon plasma (QGP) created in Pb-Pb collisions, due to its sensitivity to c-quark thermalization and to the hadronization mechanisms. The measurement in pp an p-Pb collisions is of interest both as a reference for the Pb- Pb result and in the context of recent observations suggesting the possible creation of a QGP in small colliding systems. This project is focused on the study of the extraction of the ΛC signal in p-Pb collisions with the ALICE detector, through the usage of deep learning, a machine learning technique. In a few weeks we were able to reproduce the results of the existing BDT analysis with a simple shallow networks. In the 6 to 8 pT bin, deep networks using low-level variables get close to the performance of the topological variable analysis, but with the architectures tested in this project they do not seem to be able to outperform it.

Herbal Extract SH003 Suppresses Tumor Growth and Metastasis of MDA-MB-231 Breast Cancer Cells by Inhibiting STAT3-IL-6 Signaling

Directory of Open Access Journals (Sweden)

Youn Kyung Choi

2014-01-01

Full Text Available Cancer inflammation promotes cancer progression, resulting in a high risk of cancer. Here, we demonstrate that our new herbal extract, SH003, suppresses both tumor growth and metastasis of MDA-MB-231 breast cancer cells via inhibiting STAT3-IL-6 signaling path. Our new herbal formula, SH003, mixed extract from Astragalus membranaceus, Angelica gigas, and Trichosanthes kirilowii Maximowicz, suppressed MDA-MB-231 tumor growth and lung metastasis in vivo and reduced the viability and metastatic abilities of MDA-MB-231 cells in vitro. Furthermore, SH003 inhibited STAT3 activation, which resulted in a reduction of IL-6 production. Therefore, we conclude that SH003 suppresses highly metastatic breast cancer growth and metastasis by inhibiting STAT3-IL-6 signaling path.

A structural SVM approach for reference parsing.

Science.gov (United States)

Zhang, Xiaoli; Zou, Jie; Le, Daniel X; Thoma, George R

2011-06-09

Automated extraction of bibliographic data, such as article titles, author names, abstracts, and references is essential to the affordable creation of large citation databases. References, typically appearing at the end of journal articles, can also provide valuable information for extracting other bibliographic data. Therefore, parsing individual reference to extract author, title, journal, year, etc. is sometimes a necessary preprocessing step in building citation-indexing systems. The regular structure in references enables us to consider reference parsing a sequence learning problem and to study structural Support Vector Machine (structural SVM), a newly developed structured learning algorithm on parsing references. In this study, we implemented structural SVM and used two types of contextual features to compare structural SVM with conventional SVM. Both methods achieve above 98% token classification accuracy and above 95% overall chunk-level accuracy for reference parsing. We also compared SVM and structural SVM to Conditional Random Field (CRF). The experimental results show that structural SVM and CRF achieve similar accuracies at token- and chunk-levels. When only basic observation features are used for each token, structural SVM achieves higher performance compared to SVM since it utilizes the contextual label features. However, when the contextual observation features from neighboring tokens are combined, SVM performance improves greatly, and is close to that of structural SVM after adding the second order contextual observation features. The comparison of these two methods with CRF using the same set of binary features show that both structural SVM and CRF perform better than SVM, indicating their stronger sequence learning ability in reference parsing.

Reference Proteome Extracts for Mass Spec Instrument Performance Validation and Method Development

Science.gov (United States)

Rosenblatt, Mike; Urh, Marjeta; Saveliev, Sergei

2014-01-01

Biological samples of high complexity are required to test protein mass spec sample preparation procedures and validate mass spec instrument performance. Total cell protein extracts provide the needed sample complexity. However, to be compatible with mass spec applications, such extracts should meet a number of design requirements: compatibility with LC/MS (free of detergents, etc.)high protein integrity (minimal level of protein degradation and non-biological PTMs)compatibility with common sample preparation methods such as proteolysis, PTM enrichment and mass-tag labelingLot-to-lot reproducibility Here we describe total protein extracts from yeast and human cells that meet the above criteria. Two extract formats have been developed: Intact protein extracts with primary use for sample preparation method development and optimizationPre-digested extracts (peptides) with primary use for instrument validation and performance monitoring

Respiratory Information Extraction from Electrocardiogram Signals

KAUST Repository

Amin, Gamal El Din Fathy

2010-01-01

The Electrocardiogram (ECG) is a tool measuring the electrical activity of the heart, and it is extensively used for diagnosis and monitoring of heart diseases. The ECG signal reflects not only the heart activity but also many other physiological

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

Science.gov (United States)

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

2014-09-01

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

EMG signals characterization in three states of contraction by fuzzy network and feature extraction

CERN Document Server

Mokhlesabadifarahani, Bita

2015-01-01

Neuro-muscular and musculoskeletal disorders and injuries highly affect the life style and the motion abilities of an individual. This brief highlights a systematic method for detection of the level of muscle power declining in musculoskeletal and Neuro-muscular disorders. The neuro-fuzzy system is trained with 70 percent of the recorded Electromyography (EMG) cut off window and then used for classification and modeling purposes. The neuro-fuzzy classifier is validated in comparison to some other well-known classifiers in classification of the recorded EMG signals with the three states of contractions corresponding to the extracted features. Different structures of the neuro-fuzzy classifier are also comparatively analyzed to find the optimum structure of the classifier used.

Gelidium elegans Extract Ameliorates Type 2 Diabetes via Regulation of MAPK and PI3K/Akt Signaling

Directory of Open Access Journals (Sweden)

Jia Choi

2018-01-01

Full Text Available Gelidium elegans, a red alga native to the Asia Pacific region, contains biologically active polyphenols. We conducted a molecular biological study of the anti-diabetic effect of Gelidium elegans extract (GEE in C57BL/KsJ-db/db mice. Mice that had been administered GEE had significantly lower body mass, water consumption, and fasting blood glucose than db/db controls. Moreover, hemoglobin A1c (HbA1c, an indicator of the glycemic status of people with diabetes, was significantly lower in mice that had been administered GEE. We also found that 200 mg/kg/day GEE upregulates the insulin signaling pathway by activating insulin receptor substrate-1 (IRS-1 and phosphoinositide 3-kinase (PI3K, and increasing the expression of glucose transporter type 4 (GLUT4. In parallel, mitogen-activated protein kinase (MAPK activity was lower in GEE-treated groups. In summary, these findings indicate that GEE regulates glucose metabolism by activating the insulin signaling pathway and downregulating the MAPK signaling pathway.

Multicomponent quantitative spectroscopic analysis without reference substances based on ICA modelling.

Science.gov (United States)

Monakhova, Yulia B; Mushtakova, Svetlana P

2017-05-01

A fast and reliable spectroscopic method for multicomponent quantitative analysis of targeted compounds with overlapping signals in complex mixtures has been established. The innovative analytical approach is based on the preliminary chemometric extraction of qualitative and quantitative information from UV-vis and IR spectral profiles of a calibration system using independent component analysis (ICA). Using this quantitative model and ICA resolution results of spectral profiling of "unknown" model mixtures, the absolute analyte concentrations in multicomponent mixtures and authentic samples were then calculated without reference solutions. Good recoveries generally between 95% and 105% were obtained. The method can be applied to any spectroscopic data that obey the Beer-Lambert-Bouguer law. The proposed method was tested on analysis of vitamins and caffeine in energy drinks and aromatic hydrocarbons in motor fuel with 10% error. The results demonstrated that the proposed method is a promising tool for rapid simultaneous multicomponent analysis in the case of spectral overlap and the absence/inaccessibility of reference materials.

Extracting the evolutionary signal from genomes.

NARCIS (Netherlands)

Dutilh, B.E.

2007-01-01

Several methods to analyze aspects of evolution are developed, that depend on the availability of complete genomes. While I consistently find a phylogenetic signal using many approaches, a question that is winning concern is how these evolutionary relationships should be interpreted. Since Darwin’s

Polyphenol-Rich Propolis Extracts Strengthen Intestinal Barrier Function by Activating AMPK and ERK Signaling

Directory of Open Access Journals (Sweden)

Kai Wang

2016-05-01

Full Text Available Propolis has abundant polyphenolic constituents and is used widely as a health/functional food. Here, we investigated the effects of polyphenol-rich propolis extracts (PPE on intestinal barrier function in human intestinal epithelial Caco-2 cells, as well as in rats. In Caco-2 cells, PPE increased transepithelial electrical resistance and decreased lucifer yellow flux. PPE-treated cells showed increased expression of the tight junction (TJ loci occludin and zona occludens (ZO-1. Confocal microscopy showed organized expressions in proteins related to TJ assembly, i.e., occludin and ZO-1, in response to PPE. Furthermore, PPE led to the activation of AMPK, ERK1/2, p38, and Akt. Using selective inhibitors, we found that the positive effects of PPE on barrier function were abolished in cells in which AMPK and ERK1/2 signaling were inhibited. Moreover, rats fed a diet supplemented with PPE (0.3% in the diet exhibited increased colonic epithelium ZO-1 expression. Overall, these data suggest that PPE strengthens intestinal barrier function by activating AMPK and ERK signaling and provide novel insights into the potential application of propolis for human gut health.

Evaluation of RNA extraction methods and identification of putative reference genes for real-time quantitative polymerase chain reaction expression studies on olive (Olea europaea L.) fruits.

Science.gov (United States)

Nonis, Alberto; Vezzaro, Alice; Ruperti, Benedetto

2012-07-11

Genome wide transcriptomic surveys together with targeted molecular studies are uncovering an ever increasing number of differentially expressed genes in relation to agriculturally relevant processes in olive (Olea europaea L). These data need to be supported by quantitative approaches enabling the precise estimation of transcript abundance. qPCR being the most widely adopted technique for mRNA quantification, preliminary work needs to be done to set up robust methods for extraction of fully functional RNA and for the identification of the best reference genes to obtain reliable quantification of transcripts. In this work, we have assessed different methods for their suitability for RNA extraction from olive fruits and leaves and we have evaluated thirteen potential candidate reference genes on 21 RNA samples belonging to fruit developmental/ripening series and to leaves subjected to wounding. By using two different algorithms, GAPDH2 and PP2A1 were identified as the best reference genes for olive fruit development and ripening, and their effectiveness for normalization of expression of two ripening marker genes was demonstrated.

NInFEA: an embedded framework for the real-time evaluation of fetal ECG extraction algorithms.

Science.gov (United States)

Pani, Danilo; Barabino, Gianluca; Raffo, Luigi

2013-02-01

Fetal electrocardiogram (ECG) extraction from non-invasive biopotential recordings is a long-standing research topic. Despite the significant number of algorithms presented in the scientific literature, it is difficult to find information about embedded hardware implementations able to provide real-time support for the required features, bridging the gap between theory and practice. This article presents the NInFEA (non-invasive fetal ECG analysis) tool, an embedded hardware/software framework based on the hybrid dual-core OMAP-L137 low-power processor for the real-time evaluation of fetal ECG extraction algorithms. The hybrid platform, including a digital signal processor (DSP) and a general-purpose processor (GPP), allows achieving the best performance compared with single-core architectures. The GPP provides a portable graphical user interface, whereas the DSP is extensively used for advanced signal processing tasks. As a case study, three state-of-the-art fetal ECG extraction algorithms have been ported onto NInFEA, along with some support routines needed to provide the additional information required by the clinicians and supported by the user interface. NInFEA can be regarded both as a reference design for similar applications and as a common embedded low-power testbed for real-time fetal ECG extraction algorithms.

TLC densitometric method for screening of lycopsamine in comfrey root (Symphytum officinale L. extracts using retrorsine as a reference compound

Directory of Open Access Journals (Sweden)

Janeš Damjan

2014-12-01

Full Text Available Due to severe toxicity of pyrrolizidine alkaloids, their quantification in medicinal products is very important. The idea of this research was to use retrorsine as a surrogate reference compound instead of lycopsamine reference or lycopsamine isolated from comfrey. A method for the analysis of lycopsamine in extracts of comfrey roots was developed and validated, employing thin layer chromatography, derivatisation with Dann-Mattocks reagent followed by densitometric analysis. The new method showed linearity within 0.70 to 7.0 μg of lycopsamine per application of 10 μL of a solution. It has also been proven to be specific and precise (repeatability RSD 2-4 % within the plate. The method was successfully employed for quantification of lycopsamine in comfrey root and comfrey root medicinal products such as ointments.

TLC densitometric method for screening of lycopsamine in comfrey root (Symphytum officinale L.) extracts using retrorsine as a reference compound.

Science.gov (United States)

Janeš, Damjan; Kreft, Samo

2014-12-01

Due to severe toxicity of pyrrolizidine alkaloids, their quantification in medicinal products is very important. The idea of this research was to use retrorsine as a surrogate reference compound instead of lycopsamine reference or lycopsamine isolated from comfrey. A method for the analysis of lycopsamine in extracts of comfrey roots was developed and validated, employing thin layer chromatography, derivatisation with Dann-Mattocks reagent followed by densitometric analysis. The new method showed linearity within 0.70 to 7.0 μg of lycopsamine per application of 10 μL of a solution. It has also been proven to be specific and precise (repeatability RSD 2-4 % within the plate). The method was successfully employed for quantification of lycopsamine in comfrey root and comfrey root medicinal products such as ointments.

Performance comparison of six independent components analysis algorithms for fetal signal extraction from real fMCG data

International Nuclear Information System (INIS)

Hild, Kenneth E; Alleva, Giovanna; Nagarajan, Srikantan; Comani, Silvia

2007-01-01

In this study we compare the performance of six independent components analysis (ICA) algorithms on 16 real fetal magnetocardiographic (fMCG) datasets for the application of extracting the fetal cardiac signal. We also compare the extraction results for real data with the results previously obtained for synthetic data. The six ICA algorithms are FastICA, CubICA, JADE, Infomax, MRMI-SIG and TDSEP. The results obtained using real fMCG data indicate that the FastICA method consistently outperforms the others in regard to separation quality and that the performance of an ICA method that uses temporal information suffers in the presence of noise. These two results confirm the previous results obtained using synthetic fMCG data. There were also two notable differences between the studies based on real and synthetic data. The differences are that all six ICA algorithms are independent of gestational age and sensor dimensionality for synthetic data, but depend on gestational age and sensor dimensionality for real data. It is possible to explain these differences by assuming that the number of point sources needed to completely explain the data is larger than the dimensionality used in the ICA extraction

A Signal Processing Module for the Analysis of Heart Sounds and Heart Murmurs

International Nuclear Information System (INIS)

Javed, Faizan; Venkatachalam, P A; H, Ahmad Fadzil M

2006-01-01

In this paper a Signal Processing Module (SPM) for the computer-aided analysis of heart sounds has been developed. The module reveals important information of cardiovascular disorders and can assist general physician to come up with more accurate and reliable diagnosis at early stages. It can overcome the deficiency of expert doctors in rural as well as urban clinics and hospitals. The module has five main blocks: Data Acquisition and Pre-processing, Segmentation, Feature Extraction, Murmur Detection and Murmur Classification. The heart sounds are first acquired using an electronic stethoscope which has the capability of transferring these signals to the near by workstation using wireless media. Then the signals are segmented into individual cycles as well as individual components using the spectral analysis of heart without using any reference signal like ECG. Then the features are extracted from the individual components using Spectrogram and are used as an input to a MLP (Multiple Layer Perceptron) Neural Network that is trained to detect the presence of heart murmurs. Once the murmur is detected they are classified into seven classes depending on their timing within the cardiac cycle using Smoothed Pseudo Wigner-Ville distribution. The module has been tested with real heart sounds from 40 patients and has proved to be quite efficient and robust while dealing with a large variety of pathological conditions

A Signal Processing Module for the Analysis of Heart Sounds and Heart Murmurs

Energy Technology Data Exchange (ETDEWEB)

Javed, Faizan; Venkatachalam, P A; H, Ahmad Fadzil M [Signal and Imaging Processing and Tele-Medicine Technology Research Group, Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, 31750 Tronoh, Perak (Malaysia)

2006-04-01

In this paper a Signal Processing Module (SPM) for the computer-aided analysis of heart sounds has been developed. The module reveals important information of cardiovascular disorders and can assist general physician to come up with more accurate and reliable diagnosis at early stages. It can overcome the deficiency of expert doctors in rural as well as urban clinics and hospitals. The module has five main blocks: Data Acquisition and Pre-processing, Segmentation, Feature Extraction, Murmur Detection and Murmur Classification. The heart sounds are first acquired using an electronic stethoscope which has the capability of transferring these signals to the near by workstation using wireless media. Then the signals are segmented into individual cycles as well as individual components using the spectral analysis of heart without using any reference signal like ECG. Then the features are extracted from the individual components using Spectrogram and are used as an input to a MLP (Multiple Layer Perceptron) Neural Network that is trained to detect the presence of heart murmurs. Once the murmur is detected they are classified into seven classes depending on their timing within the cardiac cycle using Smoothed Pseudo Wigner-Ville distribution. The module has been tested with real heart sounds from 40 patients and has proved to be quite efficient and robust while dealing with a large variety of pathological conditions.

Portulaca oleracea extract can inhibit nodule formation of colon cancer stem cells by regulating gene expression of the Notch signal transduction pathway.

Science.gov (United States)

Jin, Heiying; Chen, Li; Wang, Shuiming; Chao, Deng

2017-07-01

To investigate whether Portulaca oleracea extract affects tumor formation in colon cancer stem cells and its chemotherapy sensitivity. In addition, to analyze associated genetic changes within the Notch signal transduction pathway. Serum-free cultures of colon cancer cells (HT-29) and HT-29 cancer stem cells were treated with the chemotherapeutic drug 5-fluorouracil to assess sensitivity. Injections of the stem cells were also given to BALB/c mice to confirm tumor growth and note its characteristics. In addition, the effect of different concentrations of P. oleracea extract was tested on the growth of HT-29 colon cancer cells and HT-29 cancer stem cells, as determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide method. The effects of P. oleracea extract on the expression of β-catenin, Notch1, and Notch2 in the HT-29 cells were studied using reverse transcription polymerase chain reaction and Western blotting. The tumor volume of the HT29 cells was two times larger than that of HT29 cancer stem cells. Treatment with P. oleracea extract inhibited the proliferation of both HT-29 cancer cells and HT-29 cancer stem cells at doses from 0.07 to 2.25 µg/mL. Apoptosis of HT-29 cancer cells and HT-29 cancer stem cells was assessed by flow cytometry; it was enhanced by the addition of P. oleracea extract. Finally, treatment with P. oleracea extract significantly downregulated the expression of the Notch1 and β-catenin genes in both cell types. The results of this study show that P. oleracea extract inhibits the growth of colon cancer stem cells in a dose-dependent manner. Furthermore, it inhibits the expression of the Notch1 and β-catenin genes. Taken together, this suggests that it may elicit its effects through regulatory and target genes that mediate the Notch signal transduction pathway.

The Spallation Neutron Source RF Reference System

CERN Document Server

Piller, Maurice; Crofford, Mark; Doolittle, Lawrence; Ma, Hengjie

2005-01-01

The Spallation Neutron Source (SNS) RF Reference System includes the master oscillator (MO), local oscillator(LO) distribution, and Reference RF distribution systems. Coherent low noise Reference RF signals provide the ability to control the phase relationships between the fields in the front-end and linear accelerator (linac) RF cavity structures. The SNS RF Reference System requirements, implementation details, and performance are discussed.

Signal recovery in imaging photoplethysmography

International Nuclear Information System (INIS)

Holton, Benjamin D; Mannapperuma, Kavan; Lesniewski, Peter J; Thomas, John C

2013-01-01

Imaging photoplethysmography is an emerging technique for the extraction of biometric information from people using video recordings. The focus is on extracting the cardiac heart rate of the subject by analysing the luminance of the colour video signal and identifying periodic components. Advanced signal processing is needed to recover the information required. In this paper, independent component analysis (ICA), principal component analysis, auto- and cross-correlation are investigated and compared with respect to their effectiveness in extracting the relevant information from video recordings. Results obtained are compared with those recorded by a modern commercial finger pulse oximeter. It is found that ICA produces the most consistent results. (paper)

Signal recovery in imaging photoplethysmography.

Science.gov (United States)

Holton, Benjamin D; Mannapperuma, Kavan; Lesniewski, Peter J; Thomas, John C

2013-11-01

Imaging photoplethysmography is an emerging technique for the extraction of biometric information from people using video recordings. The focus is on extracting the cardiac heart rate of the subject by analysing the luminance of the colour video signal and identifying periodic components. Advanced signal processing is needed to recover the information required. In this paper, independent component analysis (ICA), principal component analysis, auto- and cross-correlation are investigated and compared with respect to their effectiveness in extracting the relevant information from video recordings. Results obtained are compared with those recorded by a modern commercial finger pulse oximeter. It is found that ICA produces the most consistent results.

Reference hearing threshold levels for short duration signals

DEFF Research Database (Denmark)

Poulsen, Torben; Legarth, Søren Vase

2008-01-01

for the determination of reference hearing threshold levels. The results are given as peak-to-peak equivalent threshold sound pressure levels (peETSPL). The results are in good agreement with other sparse results from literature and are part of the basis for the ISO 389-6 standard from 2007....

Biomedical signal and image processing

CERN Document Server

Najarian, Kayvan

2012-01-01

INTRODUCTION TO DIGITAL SIGNAL AND IMAGE PROCESSINGSignals and Biomedical Signal ProcessingIntroduction and OverviewWhat is a ""Signal""?Analog, Discrete, and Digital SignalsProcessing and Transformation of SignalsSignal Processing for Feature ExtractionSome Characteristics of Digital ImagesSummaryProblemsFourier TransformIntroduction and OverviewOne-Dimensional Continuous Fourier TransformSampling and NYQUIST RateOne-Dimensional Discrete Fourier TransformTwo-Dimensional Discrete Fourier TransformFilter DesignSummaryProblemsImage Filtering, Enhancement, and RestorationIntroduction and Overview

Reference-shaping adaptive control by using gradient descent optimizers.

Directory of Open Access Journals (Sweden)

Baris Baykant Alagoz

Full Text Available This study presents a model reference adaptive control scheme based on reference-shaping approach. The proposed adaptive control structure includes two optimizer processes that perform gradient descent optimization. The first process is the control optimizer that generates appropriate control signal for tracking of the controlled system output to a reference model output. The second process is the adaptation optimizer that performs for estimation of a time-varying adaptation gain, and it contributes to improvement of control signal generation. Numerical update equations derived for adaptation gain and control signal perform gradient descent optimization in order to decrease the model mismatch errors. To reduce noise sensitivity of the system, a dead zone rule is applied to the adaptation process. Simulation examples show the performance of the proposed Reference-Shaping Adaptive Control (RSAC method for several test scenarios. An experimental study demonstrates application of method for rotor control.

Signal Separation of Helicopter Radar Returns Using Wavelet-Based Sparse Signal Optimisation

Science.gov (United States)

2016-10-01

helicopter from the composite radar returns. The received signal consists of returns from the rotating main and tail rotor blades, the helicopter body...is used to separate the main and tail rotor blade components of a helicopter from the composite radar returns. The received signal consists of returns...Two algorithms are presented in the report to separately extract main rotor blade returns and tail rotor blade returns from the composite signal

Substoichiometric isotope dilution analysis of arsenic in biological and environmental standard reference materials by solvent extraction using toluene-3,4-dithiol in benzene

International Nuclear Information System (INIS)

Chutke, N.L.; Ambulkar, Ms.M.N.; Weginwar, R.G.; Garg, A.N.

1994-01-01

A radiochemical solvent extraction procedure has been developed for the determination of As(III) using 76 As tracer. It is based on the complexation of As(III) with toluene-3,4-dithiol (TDT) at pH 2 and subsequent extraction in benzene. The effect of various parameters such as pH, time of equilibration, nature of solvent, quantitative character and interferences have been studied. The method has been further developed into substoichiometric isotope dilution analysis for the determination of As at < 1μg level and employed for the analysis of several environmental and biological standard Reference Materials from NIST (USA), IAEA (Vienna) and NIES (Japan). (author) 39 refs.; 4 figs.; 4 tabs

Meteorological information in GPS-RO reflected signals

Directory of Open Access Journals (Sweden)

K. Boniface

2011-07-01

Full Text Available Vertical profiles of the atmosphere can be obtained globally with the radio-occultation technique. However, the lowest layers of the atmosphere are less accurately extracted. A good description of these layers is important for the good performance of Numerical Weather Prediction (NWP systems, and an improvement of the observational data available for the low troposphere would thus be of great interest for data assimilation. We outline here how supplemental meteorological information close to the surface can be extracted whenever reflected signals are available. We separate the reflected signal through a radioholographic filter, and we interpret it with a ray tracing procedure, analyzing the trajectories of the electromagnetic waves over a 3-D field of refractive index. A perturbation approach is then used to perform an inversion, identifying the relevant contribution of the lowest layers of the atmosphere to the properties of the reflected signal, and extracting some supplemental information to the solution of the inversion of the direct propagation signals. It is found that there is a significant amount of useful information in the reflected signal, which is sufficient to extract a stand-alone profile of the low atmosphere, with a precision of approximately 0.1 %. The methodology is applied to one reflection case.

Locating and parsing bibliographic references in HTML medical articles.

Science.gov (United States)

Zou, Jie; Le, Daniel; Thoma, George R

2010-06-01

The set of references that typically appear toward the end of journal articles is sometimes, though not always, a field in bibliographic (citation) databases. But even if references do not constitute such a field, they can be useful as a preprocessing step in the automated extraction of other bibliographic data from articles, as well as in computer-assisted indexing of articles. Automation in data extraction and indexing to minimize human labor is key to the affordable creation and maintenance of large bibliographic databases. Extracting the components of references, such as author names, article title, journal name, publication date and other entities, is therefore a valuable and sometimes necessary task. This paper describes a two-step process using statistical machine learning algorithms, to first locate the references in HTML medical articles and then to parse them. Reference locating identifies the reference section in an article and then decomposes it into individual references. We formulate this step as a two-class classification problem based on text and geometric features. An evaluation conducted on 500 articles drawn from 100 medical journals achieves near-perfect precision and recall rates for locating references. Reference parsing identifies the components of each reference. For this second step, we implement and compare two algorithms. One relies on sequence statistics and trains a Conditional Random Field. The other focuses on local feature statistics and trains a Support Vector Machine to classify each individual word, followed by a search algorithm that systematically corrects low confidence labels if the label sequence violates a set of predefined rules. The overall performance of these two reference-parsing algorithms is about the same: above 99% accuracy at the word level, and over 97% accuracy at the chunk level.

Multi-geodetic characterization of the seasonal signal at the CERGA geodetic reference, France

Science.gov (United States)

Memin, A.; Viswanathan, V.; Fienga, A.; Santamaría-Gómez, A.; Boy, J. P.

2016-12-01

Crustal deformations due to surface-mass loading account for a significant part of the variability in geodetic time series. A perfect understanding of the loading signal observed by geodetic techniques should help in improving terrestrial reference frame (TRF) realizations. Yet, discrepancies between crustal motion estimates from models of surface-mass loading and observations are still too large so that no model is currently recommended by the IERS for reducing the data. We investigate the discrepancy observed in the seasonal variations of the CERGA station, South of France.We characterize the seasonal motions of the reference geodetic station CERGA from GNSS, SLR and LLR. We compare the station motion observed with GNSS and SLR and we estimate changes in the station-to-the-moon distance using an improved processing strategy. We investigate the consistency between these geodetic techniques and compare the observed station motion with that estimated using models of surface-mass change. In that regard, we compute atmospheric loading effects using surface pressure fields from ECMWF, assuming an ocean response according to the classical inverted barometer (IB) assumption, considered to be valid for periods typically exceeding a week. We also used general circulation ocean models (ECCO and GLORYS) forced by wind, heat and fresh water fluxes. The continental water storage is described using GLDAS/Noah and MERRA-land models.Using the surface-mass models, we estimate the amplitude of the seasonal vertical motion of the CERGA station ranging between 5 and 10 mm with a maximum reached in August, mostly due to hydrology. The horizontal seasonal motion of the station may reach up to 3 mm. Such a station motion should induce a change in the distance to the moon reaching up to 10 mm, large enough to be detected in LLR time series and compared to GNSS- and SLR-derived motion.

Method and apparatus for stabilizing signals in radioactive well logging tools

International Nuclear Information System (INIS)

Kampfer, J.G.; Ingram, L.A.

1977-01-01

A method and apparatus are presented for stabilizing signals in radioactive well logging tools. In the tool a main scintillating crystal and photomultiplier tube for detecting radiation induced in the borehole by a source of radiation are provided and a reference crystal, including a source of mono-energetic radiation, for producing continuous reference signals of a predetermined energy level. The signals are monitored and the spectrum is stabilized to correct for drift of the data signals introduced by the photomultiplier tube and the data transmission system. The preferred mono-energetic reference signals are selected to appear in the energy spectrum at a level which minimizes error. An electronic circuit at the surface provides a correction signal for adjusting the gain of a data signal amplifier responsive to changes in the reference signal, thereby correcting for drift in the data signal

Inhibition of AKT signaling by supercritical CO2 extract of mango ginger (Curcuma amada Roxb.) in human glioblastoma cells.

Science.gov (United States)

Ramachandran, Cheppail; Portalatin, Gilda; Quirin, Karl-W; Escalon, Enrique; Khatib, Ziad; Melnick, Steven J

2015-12-01

Mango ginger (Curcuma amada Roxb.) is a less-investigated herb for anticancer properties than other related Curcuma species. AKT (a serine/threonine protein kinase B, originally identified as an oncogene in the transforming retrovirus AKT8) plays a central role in the development and promotion of cancer. In this investigation, we have analyzed the effect of supercritical CO2 extract of mango ginger (CA) on the genetic pathways associated with AKT signaling in human glioblastoma cells. The inhibitory effect of supercritical CO2 extract of mango ginger (Curcuma amada) on AKT signaling was investigated in U-87MG glioblastoma cells. CA was highly cytotoxic to glioblastoma cell line (IC50=4.92±0.81 µg/mL) compared to mHypoE-N1 normal mouse hypothalamus cell line (IC50=40.57±0.06 µg/mL). CA inhibits AKT (protein Kinase B) and adenosine monophophate -activated protein kinase α (AMPKα) phosphorylation significantly in a dose-dependent manner. The cell migration which is necessary for invasion and metastasis was also inhibited by CA treatment, with about 43% reduction at 20 µg/mL concentration. Analysis of mRNA and protein expression of genes associated with apoptosis, cell proliferation and angiogenesis showed that CA modulates expression of genes associated with apoptosis (Bax, Bcl-2, Bcl-X, BNIP3, caspase-3, mutant p53 and p21), cell proliferation (Ki67) and angiogenesis vascular endothelial growth factor (VEGF). Additionally, heat shock protein 90 (HSP90) and AMPKα genes interacting with the AKT signaling pathway were also downregulated by CA treatment. These results indicate the molecular targets and mechanisms underlying the anticancer effect of CA in human glioblastoma cells.

Rapid extraction of PCDD/Fs from soil and fly ash samples. Pressurized fluid extraction (PFE) and microwave-assisted extraction (MAE)

Energy Technology Data Exchange (ETDEWEB)

Sanz, P.; Fabrellas, B. [Centro de Investigaciones Energeticas Medioambientales y Tecnologicas (CIEMAT), Madrid (Spain)

2004-09-15

The main reference extraction method in the analysis of polychlorinated dibenzop- dioxins and dibenzofurans (PCDD/Fs) is still the Soxhlet extraction. But it requires long extraction times (up to 24 hs), large volumes of hazardous organic solvents (100-300 ml) and its automation is limited. Pressurized Fluid Extraction (PFE) and Microwave-Assisted Extraction (MAE) are two relatively new extraction techniques that reduce the time and the volume of solvent required for extraction. However, very different PFE extraction conditions are found for the same enviromental matrices in the literature. MAE is not a extraction technique very applied for the analysis of PCDD/Fs yet, although it is used for the determination of other organic compounds, such as PCBs and PAHs. In this study, PFE and MAE extraction conditions were optimized to determine PCDDs y PCDFs in fly ash and soil/sediment samples. Conventional Soxhlet extraction with toluene was used to compare the extraction efficiency of both techniques.

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

International Nuclear Information System (INIS)

Haghpanahi, Masoumeh; Borkholder, David A

2014-01-01

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

Quantitative measurement of intervertebral disc signal using MRI

International Nuclear Information System (INIS)

Niemelaeinen, R.; Videman, T.; Dhillon, S.S.; Battie, M.C.

2008-01-01

Aim: To investigate the spinal cord as an alternative intra-body reference to cerebrospinal fluid (CSF) in evaluating thoracic disc signal intensity. Materials and methods: T2-weighted magnetic resonance imaging (MRI) images of T6-T12 were obtained using 1.5 T machines for a population-based sample of 523 men aged 35-70 years. Quantitative data on the signal intensities were acquired using an image analysis program (SpEx (copy right) ). A random sample of 30 subjects and intraclass correlation coeffcients (ICC) were used to examine the repeatability of the spinal cord measurements. The validity of using the spinal cord as a reference was examined by correlating cord and CSF samples. Finally, thoracic disc signal was validated by correlating it with age without adjustment and adjusting for either cord or CSF. Pearson's r was used for correlational analyses. Results: The repeatability of the spinal cord signal measurements was extremely high (≥0.99). The correlations between the signals of spinal cord and CSF by level were all above 0.9. The spinal cord-adjusted disc signal and age correlated similarly with CSF-adjusted disc signal and age (r = -0.30 to -0.40 versus r = -0.26 to -0.36). Conclusion: Adjacent spinal cord is a good alternative reference to the current reference standard, CSF, for quantitative measurements of disc signal intensity. Clearly fewer levels were excluded when using spinal cord as compared to CSF due to missing reference samples

Quantitative measurement of intervertebral disc signal using MRI

Energy Technology Data Exchange (ETDEWEB)

Niemelaeinen, R. [Faculty of Rehabilitation Medicine, University of Alberta, Edmonton (Canada)], E-mail: riikka.niemelainen@ualberta.ca; Videman, T. [Faculty of Rehabilitation Medicine, University of Alberta, Edmonton (Canada); Dhillon, S.S. [Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton (Canada); Battie, M.C. [Faculty of Rehabilitation Medicine, University of Alberta, Edmonton (Canada)

2008-03-15

Aim: To investigate the spinal cord as an alternative intra-body reference to cerebrospinal fluid (CSF) in evaluating thoracic disc signal intensity. Materials and methods: T2-weighted magnetic resonance imaging (MRI) images of T6-T12 were obtained using 1.5 T machines for a population-based sample of 523 men aged 35-70 years. Quantitative data on the signal intensities were acquired using an image analysis program (SpEx (copy right) ). A random sample of 30 subjects and intraclass correlation coeffcients (ICC) were used to examine the repeatability of the spinal cord measurements. The validity of using the spinal cord as a reference was examined by correlating cord and CSF samples. Finally, thoracic disc signal was validated by correlating it with age without adjustment and adjusting for either cord or CSF. Pearson's r was used for correlational analyses. Results: The repeatability of the spinal cord signal measurements was extremely high ({>=}0.99). The correlations between the signals of spinal cord and CSF by level were all above 0.9. The spinal cord-adjusted disc signal and age correlated similarly with CSF-adjusted disc signal and age (r = -0.30 to -0.40 versus r = -0.26 to -0.36). Conclusion: Adjacent spinal cord is a good alternative reference to the current reference standard, CSF, for quantitative measurements of disc signal intensity. Clearly fewer levels were excluded when using spinal cord as compared to CSF due to missing reference samples.

Accurate determination of brain metabolite concentrations using ERETIC as external reference.

Science.gov (United States)

Zoelch, Niklaus; Hock, Andreas; Heinzer-Schweizer, Susanne; Avdievitch, Nikolai; Henning, Anke

2017-08-01

Magnetic Resonance Spectroscopy (MRS) can provide in vivo metabolite concentrations in standard concentration units if a reliable reference signal is available. For 1 H MRS in the human brain, typically the signal from the tissue water is used as the (internal) reference signal. However, a concentration determination based on the tissue water signal most often requires a reliable estimate of the water concentration present in the investigated tissue. Especially in clinically interesting cases, this estimation might be difficult. To avoid assumptions about the water in the investigated tissue, the Electric REference To access In vivo Concentrations (ERETIC) method has been proposed. In this approach, the metabolite signal is compared with a reference signal acquired in a phantom and potential coil-loading differences are corrected using a synthetic reference signal. The aim of this study, conducted with a transceiver quadrature head coil, was to increase the accuracy of the ERETIC method by correcting the influence of spatial B 1 inhomogeneities and to simplify the quantification with ERETIC by incorporating an automatic phase correction for the ERETIC signal. Transmit field ( B1+) differences are minimized with a volume-selective power optimization, whereas reception sensitivity changes are corrected using contrast-minimized images of the brain and by adapting the voxel location in the phantom measurement closely to the position measured in vivo. By applying the proposed B 1 correction scheme, the mean metabolite concentrations determined with ERETIC in 21 healthy subjects at three different positions agree with concentrations derived with the tissue water signal as reference. In addition, brain water concentrations determined with ERETIC were in agreement with estimations derived using tissue segmentation and literature values for relative water densities. Based on the results, the ERETIC method presented here is a valid tool to derive in vivo metabolite

Digital signal processing

CERN Document Server

O'Shea, Peter; Hussain, Zahir M

2011-01-01

In three parts, this book contributes to the advancement of engineering education and that serves as a general reference on digital signal processing. Part I presents the basics of analog and digital signals and systems in the time and frequency domain. It covers the core topics: convolution, transforms, filters, and random signal analysis. It also treats important applications including signal detection in noise, radar range estimation for airborne targets, binary communication systems, channel estimation, banking and financial applications, and audio effects production. Part II considers sel

An open-source framework for stress-testing non-invasive foetal ECG extraction algorithms.

Science.gov (United States)

Andreotti, Fernando; Behar, Joachim; Zaunseder, Sebastian; Oster, Julien; Clifford, Gari D

2016-05-01

Over the past decades, many studies have been published on the extraction of non-invasive foetal electrocardiogram (NI-FECG) from abdominal recordings. Most of these contributions claim to obtain excellent results in detecting foetal QRS (FQRS) complexes in terms of location. A small subset of authors have investigated the extraction of morphological features from the NI-FECG. However, due to the shortage of available public databases, the large variety of performance measures employed and the lack of open-source reference algorithms, most contributions cannot be meaningfully assessed. This article attempts to address these issues by presenting a standardised methodology for stress testing NI-FECG algorithms, including absolute data, as well as extraction and evaluation routines. To that end, a large database of realistic artificial signals was created, totaling 145.8 h of multichannel data and over one million FQRS complexes. An important characteristic of this dataset is the inclusion of several non-stationary events (e.g. foetal movements, uterine contractions and heart rate fluctuations) that are critical for evaluating extraction routines. To demonstrate our testing methodology, three classes of NI-FECG extraction algorithms were evaluated: blind source separation (BSS), template subtraction (TS) and adaptive methods (AM). Experiments were conducted to benchmark the performance of eight NI-FECG extraction algorithms on the artificial database focusing on: FQRS detection and morphological analysis (foetal QT and T/QRS ratio). The overall median FQRS detection accuracies (i.e. considering all non-stationary events) for the best performing methods in each group were 99.9% for BSS, 97.9% for AM and 96.0% for TS. Both FQRS detections and morphological parameters were shown to heavily depend on the extraction techniques and signal-to-noise ratio. Particularly, it is shown that their evaluation in the source domain, obtained after using a BSS technique, should be

The organophosphorus extractants

International Nuclear Information System (INIS)

Zaoul, B.; Attou, M.; Azzouz, A.

1989-07-01

This work consists in a bibliographic review dealing with phosphorus and organophosphorus compounds chemistry and especially with the main extracting agents used in uranium ore treatment. In this context, a special interest is devoted to TBP, D 2 EHPA and TOPO. The content of this work is based on a large bibliography including cca. One hundred references related to many aspects concerning as well the nomenclature, the classification and the chemical structures of the organophosphorus compounds as synthesis methods, purification and analysis of the main extracting agents used in uranium extraction

Extraction of temporal information in functional MRI

Science.gov (United States)

Singh, M.; Sungkarat, W.; Jeong, Jeong-Won; Zhou, Yongxia

2002-10-01

The temporal resolution of functional MRI (fMRI) is limited by the shape of the haemodynamic response function (hrf) and the vascular architecture underlying the activated regions. Typically, the temporal resolution of fMRI is on the order of 1 s. We have developed a new data processing approach to extract temporal information on a pixel-by-pixel basis at the level of 100 ms from fMRI data. Instead of correlating or fitting the time-course of each pixel to a single reference function, which is the common practice in fMRI, we correlate each pixel's time-course to a series of reference functions that are shifted with respect to each other by 100 ms. The reference function yielding the highest correlation coefficient for a pixel is then used as a time marker for that pixel. A Monte Carlo simulation and experimental study of this approach were performed to estimate the temporal resolution as a function of signal-to-noise ratio (SNR) in the time-course of a pixel. Assuming a known and stationary hrf, the simulation and experimental studies suggest a lower limit in the temporal resolution of approximately 100 ms at an SNR of 3. The multireference function approach was also applied to extract timing information from an event-related motor movement study where the subjects flexed a finger on cue. The event was repeated 19 times with the event's presentation staggered to yield an approximately 100-ms temporal sampling of the haemodynamic response over the entire presentation cycle. The timing differences among different regions of the brain activated by the motor task were clearly visualized and quantified by this method. The results suggest that it is possible to achieve a temporal resolution of /spl sim/200 ms in practice with this approach.

[An improved algorithm for electrohysterogram envelope extraction].

Science.gov (United States)

Lu, Yaosheng; Pan, Jie; Chen, Zhaoxia; Chen, Zhaoxia

2017-02-01

Extraction uterine contraction signal from abdominal uterine electromyogram(EMG) signal is considered as the most promising method to replace the traditional tocodynamometer(TOCO) for detecting uterine contractions activity. The traditional root mean square(RMS) algorithm has only some limited values in canceling the impulsive noise. In our study, an improved algorithm for uterine EMG envelope extraction was proposed to overcome the problem. Firstly, in our experiment, zero-crossing detection method was used to separate the burst of uterine electrical activity from the raw uterine EMG signal. After processing the separated signals by employing two filtering windows which have different width, we used the traditional RMS algorithm to extract uterus EMG envelope. To assess the performance of the algorithm, the improved algorithm was compared with two existing intensity of uterine electromyogram(IEMG) extraction algorithms. The results showed that the improved algorithm was better than the traditional ones in eliminating impulsive noise present in the uterine EMG signal. The measurement sensitivity and positive predictive value(PPV) of the improved algorithm were 0.952 and 0.922, respectively, which were not only significantly higher than the corresponding values(0.859 and 0.847) of the first comparison algorithm, but also higher than the values(0.928 and 0.877) of the second comparison algorithm. Thus the new method is reliable and effective.

A Novel Technique for Fetal ECG Extraction Using Single-Channel Abdominal Recording

Directory of Open Access Journals (Sweden)

Nannan Zhang

2017-02-01

Full Text Available Non-invasive fetal electrocardiograms (FECGs are an alternative method to standard means of fetal monitoring which permit long-term continual monitoring. However, in abdominal recording, the FECG amplitude is weak in the temporal domain and overlaps with the maternal electrocardiogram (MECG in the spectral domain. Research in the area of non-invasive separations of FECG from abdominal electrocardiograms (AECGs is in its infancy and several studies are currently focusing on this area. An adaptive noise canceller (ANC is commonly used for cancelling interference in cases where the reference signal only correlates with an interference signal, and not with a signal of interest. However, results from some existing studies suggest that propagation of electrocardiogram (ECG signals from the maternal heart to the abdomen is nonlinear, hence the adaptive filter approach may fail if the thoracic and abdominal MECG lack strict waveform similarity. In this study, singular value decomposition (SVD and smooth window (SW techniques are combined to build a reference signal in an ANC. This is to avoid the limitation that thoracic MECGs recorded separately must be similar to abdominal MECGs in waveform. Validation of the proposed method with r01 and r07 signals from a public dataset, and a self-recorded private dataset showed that the proposed method achieved F1 scores of 99.61%, 99.28% and 98.58%, respectively for the detection of fetal QRS. Compared with four other single-channel methods, the proposed method also achieved higher accuracy values of 99.22%, 98.57% and 97.21%, respectively. The findings from this study suggest that the proposed method could potentially aid accurate extraction of FECG from MECG recordings in both clinical and commercial applications.

Reference-free fatigue crack detection using nonlinear ultrasonic modulation under various temperature and loading conditions

Science.gov (United States)

Lim, Hyung Jin; Sohn, Hoon; DeSimio, Martin P.; Brown, Kevin

2014-04-01

This study presents a reference-free fatigue crack detection technique using nonlinear ultrasonic modulation. When low frequency (LF) and high frequency (HF) inputs generated by two surface-mounted lead zirconate titanate (PZT) transducers are applied to a structure, the presence of a fatigue crack can provide a mechanism for nonlinear ultrasonic modulation and create spectral sidebands around the frequency of the HF signal. The crack-induced spectral sidebands are isolated using a combination of linear response subtraction (LRS), synchronous demodulation (SD) and continuous wavelet transform (CWT) filtering. Then, a sequential outlier analysis is performed on the extracted sidebands to identify the crack presence without referring any baseline data obtained from the intact condition of the structure. Finally, the robustness of the proposed technique is demonstrated using actual test data obtained from simple aluminum plate and complex aircraft fitting-lug specimens under varying temperature and loading variations.

Noninvasive extraction of fetal electrocardiogram based on Support Vector Machine

Science.gov (United States)

Fu, Yumei; Xiang, Shihan; Chen, Tianyi; Zhou, Ping; Huang, Weiyan

2015-10-01

The fetal electrocardiogram (FECG) signal has important clinical value for diagnosing the fetal heart diseases and choosing suitable therapeutics schemes to doctors. So, the noninvasive extraction of FECG from electrocardiogram (ECG) signals becomes a hot research point. A new method, the Support Vector Machine (SVM) is utilized for the extraction of FECG with limited size of data. Firstly, the theory of the SVM and the principle of the extraction based on the SVM are studied. Secondly, the transformation of maternal electrocardiogram (MECG) component in abdominal composite signal is verified to be nonlinear and fitted with the SVM. Then, the SVM is trained, and the training results are compared with the real data to ensure the effect of the training. Meanwhile, the parameters of the SVM are optimized to achieve the best performance so that the learning machine can be utilized to fit the unknown samples. Finally, the FECG is extracted by removing the optimal estimation of MECG component from the abdominal composite signal. In order to evaluate the performance of FECG extraction based on the SVM, the Signal-to-Noise Ratio (SNR) and the visual test are used. The experimental results show that the FECG with good quality can be extracted, its SNR ratio is significantly increased as high as 9.2349 dB and the time cost is significantly decreased as short as 0.802 seconds. Compared with the traditional method, the noninvasive extraction method based on the SVM has a simple realization, the shorter treatment time and the better extraction quality under the same conditions.

Classification of Steps on Road Surface Using Acceleration Signals

Directory of Open Access Journals (Sweden)

Junji Takahashi

2015-12-01

Full Text Available In order to reduce a road monitoring cost, we propose a system to monitor extensively road condition by cyclists with a smartphone. In this paper, we propose two methods towards road monitoring. First is to classify road signals to four road conditions. Second is to extract road signal from a smartphone's accelerometer in three positions: pants' side pocket, chest pocket and a bag in a front basket. In pants' side pocket, road signal is extracted by Independent Component Analysis. In chest pocket and bag in a front basket, road signal is extracted by selecting 1-axis affected from gravitational acceleration. In the experiment of the classification method, overall accuracy was 75%. The experimental results of the extraction methods with correlation coefficient showed the overall accuracy were more than 0.7 in pants' side pocket and chest pocket, the overall accuracy was less than 0.3 in bag in a front basket.

Signal Based Mixing Analysis for the magnetohydrodynamic mode reconstruction from homodyne microwave reflectometry

International Nuclear Information System (INIS)

Ejiri, Akira; Sakakibara, Satoru; Kawahata, Kazuo.

1995-03-01

A new method 'Signal Based Mixing Analysis', to extract the components which are coherent to a certain reference signal from a noisy signal, has been developed. The method is applied to homodyne microwave reflectometry to reconstruct the radial structure of a magnetohydrodynamic (MHD) mode in heliotron/torsatron Compact Helical System (CHS) [K. Matsuoka et al. Plasma Phys. Control. Nuclear Fusion Research 1988 Vol. 2, IAEA, Vienna 411 (1989)]. In CHS plasmas, MHD fluctuations measured with magnetic probes show bursts, in which the amplitude and frequency quasi-periodically vary. The signal based mixing analysis uses a set of functions which have the same amplitude and the harmonic frequency as those of the magnetic fluctuations. The product (mixing) of the signal of reflectometer and the functions yields the amplitude and phase of the coherent components. When the plasma density gradually increases, the measuring position moves radially outward. Thus, the radial structure of MHD modes can be obtained by this method. The analysis indicates several peaks and nodes inside the resonance surface of the MHD mode. In addition, the structure does not propagate radially during a burst. (author)

Some techniques to improve time structure of slow extracted beam

International Nuclear Information System (INIS)

Shoji, Y.; Sato, H.; Toyama, T.; Marutsuka, K.; Sueno, T.; Mikawa, K.; Ninomiya, S.; Yoshii, M.

1992-01-01

In order to improve the time structure of slow extracted beam spill for the KEK 12GeV PS, the spill control system has been upgraded by adding feed forward signal to feedback signal. Further, the wake field in the RF cavity has been cancelled by the beam bunch signal to reduce the re-bunch effect during extraction period. (author)

Average combination difference morphological filters for fault feature extraction of bearing

Science.gov (United States)

Lv, Jingxiang; Yu, Jianbo

2018-02-01

In order to extract impulse components from vibration signals with much noise and harmonics, a new morphological filter called average combination difference morphological filter (ACDIF) is proposed in this paper. ACDIF constructs firstly several new combination difference (CDIF) operators, and then integrates the best two CDIFs as the final morphological filter. This design scheme enables ACIDF to extract positive and negative impacts existing in vibration signals to enhance accuracy of bearing fault diagnosis. The length of structure element (SE) that affects the performance of ACDIF is determined adaptively by a new indicator called Teager energy kurtosis (TEK). TEK further improves the effectiveness of ACDIF for fault feature extraction. Experimental results on the simulation and bearing vibration signals demonstrate that ACDIF can effectively suppress noise and extract periodic impulses from bearing vibration signals.

Measurement of oxygen extraction fraction (OEF): An optimized BOLD signal model for use with hypercapnic and hyperoxic calibration.

Science.gov (United States)

Merola, Alberto; Murphy, Kevin; Stone, Alan J; Germuska, Michael A; Griffeth, Valerie E M; Blockley, Nicholas P; Buxton, Richard B; Wise, Richard G

2016-04-01

Several techniques have been proposed to estimate relative changes in cerebral metabolic rate of oxygen consumption (CMRO2) by exploiting combined BOLD fMRI and cerebral blood flow data in conjunction with hypercapnic or hyperoxic respiratory challenges. More recently, methods based on respiratory challenges that include both hypercapnia and hyperoxia have been developed to assess absolute CMRO2, an important parameter for understanding brain energetics. In this paper, we empirically optimize a previously presented "original calibration model" relating BOLD and blood flow signals specifically for the estimation of oxygen extraction fraction (OEF) and absolute CMRO2. To do so, we have created a set of synthetic BOLD signals using a detailed BOLD signal model to reproduce experiments incorporating hypercapnic and hyperoxic respiratory challenges at 3T. A wide range of physiological conditions was simulated by varying input parameter values (baseline cerebral blood volume (CBV0), baseline cerebral blood flow (CBF0), baseline oxygen extraction fraction (OEF0) and hematocrit (Hct)). From the optimization of the calibration model for estimation of OEF and practical considerations of hypercapnic and hyperoxic respiratory challenges, a new "simplified calibration model" is established which reduces the complexity of the original calibration model by substituting the standard parameters α and β with a single parameter θ. The optimal value of θ is determined (θ=0.06) across a range of experimental respiratory challenges. The simplified calibration model gives estimates of OEF0 and absolute CMRO2 closer to the true values used to simulate the experimental data compared to those estimated using the original model incorporating literature values of α and β. Finally, an error propagation analysis demonstrates the susceptibility of the original and simplified calibration models to measurement errors and potential violations in the underlying assumptions of isometabolism

Biological network extraction from scientific literature: state of the art and challenges.

Science.gov (United States)

Li, Chen; Liakata, Maria; Rebholz-Schuhmann, Dietrich

2014-09-01

Networks of molecular interactions explain complex biological processes, and all known information on molecular events is contained in a number of public repositories including the scientific literature. Metabolic and signalling pathways are often viewed separately, even though both types are composed of interactions involving proteins and other chemical entities. It is necessary to be able to combine data from all available resources to judge the functionality, complexity and completeness of any given network overall, but especially the full integration of relevant information from the scientific literature is still an ongoing and complex task. Currently, the text-mining research community is steadily moving towards processing the full body of the scientific literature by making use of rich linguistic features such as full text parsing, to extract biological interactions. The next step will be to combine these with information from scientific databases to support hypothesis generation for the discovery of new knowledge and the extension of biological networks. The generation of comprehensive networks requires technologies such as entity grounding, coordination resolution and co-reference resolution, which are not fully solved and are required to further improve the quality of results. Here, we analyse the state of the art for the extraction of network information from the scientific literature and the evaluation of extraction methods against reference corpora, discuss challenges involved and identify directions for future research. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Noise reduction in Lidar signal using correlation-based EMD combined with soft thresholding and roughness penalty

Science.gov (United States)

Chang, Jianhua; Zhu, Lingyan; Li, Hongxu; Xu, Fan; Liu, Binggang; Yang, Zhenbo

2018-01-01

Empirical mode decomposition (EMD) is widely used to analyze the non-linear and non-stationary signals for noise reduction. In this study, a novel EMD-based denoising method, referred to as EMD with soft thresholding and roughness penalty (EMD-STRP), is proposed for the Lidar signal denoising. With the proposed method, the relevant and irrelevant intrinsic mode functions are first distinguished via a correlation coefficient. Then, the soft thresholding technique is applied to the irrelevant modes, and the roughness penalty technique is applied to the relevant modes to extract as much information as possible. The effectiveness of the proposed method was evaluated using three typical signals contaminated by white Gaussian noise. The denoising performance was then compared to the denoising capabilities of other techniques, such as correlation-based EMD partial reconstruction, correlation-based EMD hard thresholding, and wavelet transform. The use of EMD-STRP on the measured Lidar signal resulted in the noise being efficiently suppressed, with an improved signal to noise ratio of 22.25 dB and an extended detection range of 11 km.

The CEBAF fiber optic phase reference system

International Nuclear Information System (INIS)

Crawford, K.; Simrock, S.; Hovater, C.; Krycuk, A.

1995-01-01

The specified phase stability of the CEBAF RF distribution system is 2.9 degree rms per linac. Stability is achieved through the use of a temperature and pressure regulated coaxial drive line. Purpose of the fiber optic phase reference system is to monitor the relative phase at the beginning and ending of this drive line, between linacs, injector and separator to determine drift due to ambient temperature fluctuations. The system utilizes an Ortel 1310 nm single mode laser driving Sumitumo optical fiber to distribute a reference signal at 1497 MHz. Phase of this reference signal is compared to the 1427 MHz (LO) and the 70 MHz (IF) via a 360 degree phase detector. The detected information is then routed to the CEBAF control system for display with a specified resolution of ±0.2 degree over a 20 degree phase delta

Antiatherosclerotic Effect of Korean Red Ginseng Extract Involves Regulator of G-Protein Signaling 5

Directory of Open Access Journals (Sweden)

Eun Ju Im

2014-01-01

Full Text Available Regulator of G-protein signaling 5 (RGS5, an inhibitor of Gα(q and Gα(i activation, has been reported to have antiatherosclerosis. Previous studies showed antiatherosclerotic effect of Korean red ginseng water extract (KRGE via multiple signaling pathways. However, potential protective effect of KRGE through RGS5 expression has not been elucidated. Here, we investigated the antiatherosclerotic effect of KRGE in vivo and in vitro and its role on RGS5 mRNA expression. Elevated levels of total cholesterol, lactate dehydrogenase (LDH, and triglyceride (TG in western diet groups of low-density lipoprotein receptor deficient LDLr−/− mice were reversed by oral administration of KRGE. KRGE suppressed transcriptional activity of tumor necrotic factor alpha (TNF-α, interleukin-6 (IL-6, and leptin in adipose tissue. It also potently repressed western diet-induced atheroma formation in aortic sinus. While KRGE showed reduced mRNA expression of inducible nitric oxide synthase (iNOS, cyclooxygenase-2 (COX-2, IL-1β, IL-6, and TNF-α in LPS-stimulated RAW264.7 cells, it enhanced mRNA expression of RGS5. Moreover, RGS5 siRNA transfection of microglia cells pretreated with KRGE reversed its inhibitory effect on the expression of iNOS, COX-2, and IL-1β mRNA. In conclusion, KRGE showed antiatherosclerotic and anti-inflammatory effects in western diet fed LDLr−/− mice and this effect could partly be mediated by RGS5 expression.

Shengui Sansheng San extraction is an angiogenic switch via regulations of AKT/mTOR, ERK1/2 and Notch1 signal pathways after ischemic stroke.

Science.gov (United States)

Liu, Bowen; Luo, Cheng; Zheng, Zhaoguang; Xia, Zhenyan; Zhang, Qian; Ke, Chienchih; Liu, Renshyan; Zhao, Yonghua

2018-05-15

As a traditional Chinese herbal formula, Shengui Sansheng San (SSS) has been employed for stroke treatment more than 300 years. We hypothesize that SSS extraction is an angiogenic switch in penumbra post-stroke, and corresponding mechanisms are investigated. In present study, rats were subjected to permanent middle cerebral artery occlusion model (MCAo) and were treated with low, middle and high doses of SSS extraction. We assessed neurological function and survival rate, and measured infarct volume by 2,3,5-triphenyltetrazolium chloride staining on day 7 after ischemia. von Willebrand factor (vWF), stromal cell-derived factor-1 alpha (SDF-1α) /chemokine (C-X-C motif) receptor 4 (CXCR4) axis, vascular endothelial growth factor (VEGF)/VEGF receptor 2 (VEGFR2) as well as protein kinase B (AKT)/mammalian target of rapamycin (mTOR) /hypoxia-inducible factor-1 alpha (HIF-1α), extracellular signal-regulated kinase 1/2 (ERK1/2) and Notch1 signaling pathways were respectively investigated by immunofluorescence assay or western blotting in vivo and oxygen-glucose-deprived (OGD) brain microvascular endothelial cells (BMECs); simultaneously, wound healing of BMECs and tube formation assay were administrated. Compared to MCAo group, SSS extraction could significantly improve neurological functional scores, survival rate and cerebral infarct volume, enhance vWF + vascular density and perimeter, SDF-1α/CXCR4 axis, VEGF expression, as well as activate AKT/mTOR/HIF-1α and ERK1/2 and inhibit Notch1 pathways in penumbra. In vitro, containing SSS extraction serum increased BMEC migration, capillary formation and VEGF expression via up-regulations of AKT/mTOR and ERK1/2 pathways in OGD BMECs, but ERK inhibitor (U0126) reversed the result of VEGF expression in high dose of SSS group. Additionally, VEGFR2 and Notch1 expressions were suppressed by containing SSS extraction serum. All results were in dose dependent manner. Our study firstly demonstrates that SSS extraction is an

Protective Effect of Mulberry (Morus alba L.) Extract against Benzo[a]pyrene Induced Skin Damage through Inhibition of Aryl Hydrocarbon Receptor Signaling.

Science.gov (United States)

Woo, Hyunju; Lee, JungA; Park, Deokhoon; Jung, Eunsun

2017-12-20

Benzo[a]pyrene (B[a]P), a type of polycyclic aromatic hydrocarbon, is present in the atmosphere surrounding our environment. Although B[a]P is a procarcinogen, enzymatically metabolized benzo[a]pyrene-7,8-dihydrodiol-9,10-epoxide (BPDE) could intercalate into DNA to form bulky BPDE-DNA adducts as an ultimate carcinogenic product in human keratinocytes. The aim of this study was to evaluate the protective effect of mulberry extract, purified from the fruit of Morus Alba L., on B[a]P-induced cytotoxicity in human keratinocytes and its mechanisms of action. In this study, we confirmed that B[a]P induced nuclear translocation and the activation of aryl hydrocarbon receptor (AhR) were decreased by pretreatment of mulberry extract. Mulberry extract could decrease DNA damage through the suppression of B[a]P derived DNA adduct formation and restoration of cell cycle retardation at S phase in a dose-dependent manner. Additionally, cyanidin-3-glucoside (C3G), a major active compound of mulberry extract, showed biological activities to protect the cells from B[a]P exposure, similar to the effectivity of the mulberry extract. These results indicated that the inhibitory effect of C3G against B[a]P inducing skin cancer is attributable to repress the AhR signaling pathway.

Efficient feature for classification of eye movements using electrooculography signals

OpenAIRE

Phukpattaranont Pornchai; Aungsakul Siriwadee; Phinyomark Angkoon; Limsakul Chusak

2016-01-01

Electrooculography (EOG) signal is widely and successfully used to detect activities of human eye. The advantages of the EOG-based interface over other conventional interfaces have been presented in the last two decades; however, due to a lot of information in EOG signals, the extraction of useful features should be done before the classification task. In this study, an efficient feature extracted from two directional EOG signals: vertical and horizontal si...

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

NARCIS (Netherlands)

Marchetti, M.

2013-01-01

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

PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction

OpenAIRE

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting ...

An Effective Fault Feature Extraction Method for Gas Turbine Generator System Diagnosis

Directory of Open Access Journals (Sweden)

Jian-Hua Zhong

2016-01-01

Full Text Available Fault diagnosis is very important to maintain the operation of a gas turbine generator system (GTGS in power plants, where any abnormal situations will interrupt the electricity supply. The fault diagnosis of the GTGS faces the main challenge that the acquired data, vibration or sound signals, contain a great deal of redundant information which extends the fault identification time and degrades the diagnostic accuracy. To improve the diagnostic performance in the GTGS, an effective fault feature extraction framework is proposed to solve the problem of the signal disorder and redundant information in the acquired signal. The proposed framework combines feature extraction with a general machine learning method, support vector machine (SVM, to implement an intelligent fault diagnosis. The feature extraction method adopts wavelet packet transform and time-domain statistical features to extract the features of faults from the vibration signal. To further reduce the redundant information in extracted features, kernel principal component analysis is applied in this study. Experimental results indicate that the proposed feature extracted technique is an effective method to extract the useful features of faults, resulting in improvement of the performance of fault diagnosis for the GTGS.

The reduction of background signal in bismuth germanate scintillators

International Nuclear Information System (INIS)

Lewis, T.A.

1986-07-01

Bismuth germanate (BGO) is one of several new scintillator materials developed in recent years. It has similar energy resolution (6-8%) to sodium iodide (NaI) but it is non-hygroscopic, has a much better Peak-to-Compton ratio and a stopping power about 2.3 times greater than NaI. For counting activated foils it represents an improvement on NaI for high efficiency counting where the resolution of a germanium spectrometer is not required. Two scintillators bought for this purpose were found to have a higher than expected background signal between 500 keV and 2 MeV which was traced to Bi207, an active isotope of bismuth with a 38 year half-life and not listed as occurring naturally. Reference to the manufacturer showed all crystals to be similarly contaminated. It is speculated that this active isotope arises from cosmic proton activation of associated lead in the ore from which the bismuth is extracted. Although not confirmed rigorously it has been shown that bismuth extracted from ore with a low lead content does not contain Bi207. Scintillators have been manufactured from uncontaminated material and reductions in the background signal of more than an order of magnitude have been achieved. This reduction will be of immediate benefit for monitoring nickel foils (fast flux monitors) activated in zero-energy reactors and should also permit the exploitation of other low probability reactions previously not thought to be feasible. (author)

PyEEG: an open source Python module for EEG/MEG feature extraction.

Science.gov (United States)

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.

Detection of signals in noise

CERN Document Server

Whalen, Anthony D; Declaris, Nicholas

1971-01-01

Detection of Signals in Noise serves as an introduction to the principles and applications of the statistical theory of signal detection. The book discusses probability and random processes; narrowband signals, their complex representation, and their properties described with the aid of the Hilbert transform; and Gaussian-derived processes. The text also describes the application of hypothesis testing for the detection of signals and the fundamentals required for statistical detection of signals in noise. Problem exercises, references, and a supplementary bibliography are included after each c

Stochastic Modelling as a Tool for Seismic Signals Segmentation

Directory of Open Access Journals (Sweden)

Daniel Kucharczyk

2016-01-01

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

[Evaluation of the total biological activity and allergenic composition of allergenic extracts].

Science.gov (United States)

Lombardero, M; González, R; Duffort, O; Juan, F; Ayuso, R; Ventas, P; Cortés, C; Carreira, J

1986-01-01

In the present study, a complete procedure is presented in order to standardize allergenic extracts, the meaning of which is the measurement of the total allergenic activity and the determination of the allergenic composition. The measurement of the biological activity comprises 2 steps: Preparation of Reference Extracts and determination of their "in vivo" activity. Evaluation of the total allergenic activity of extracts for clinical use. Reference extracts were prepared from the main allergens and their "in vivo" biological activity was determined by a quantitative skin prick test in a sample of at least 30 allergic patients. By definition, the protein concentration of Reference Extract that produces, in the allergic population, a geometric mean wheal of 75 mm.2 has an activity of 100 biological units (BUs). The determination of the biological activity of a problem extract is made by RAST inhibition. The sample is compared with the corresponding Reference Extract by this technique and, from this comparison, it is possible to quantify the activity of the problem extract in biologic units (BUs) with clinical significance. Likewise, different techniques have been used to determine the allergenic composition of extracts. These techniques comprise 2 steps: Separation of the components of the extract. Identification of the components that bind specific human IgE. The separation of the components of the extract has been carried out by isoelectric focusing (IEF) and electrophoresis in the presence of sodium dodecyl sulphate (SDS-PAGE). In order to identify the allergenic components, an immunoblotting technique has been employed. The separated components in the IEF gel or SDS-PAGE gel are transferred to a nitrocellulose sheet and later on, this membrane is overlaid with a serum pool from allergic patients and a mouse monoclonal anti-human IgE, labelled with 125I. Finally, the autoradiography of the nitrocellulose membrane is obtained. In this way it is possible to compare

Spirulina maxima Extract Prevents Neurotoxicity via Promoting Activation of BDNF/CREB Signaling Pathways in Neuronal Cells and Mice.

Science.gov (United States)

Koh, Eun-Jeong; Seo, Young-Jin; Choi, Jia; Lee, Hyeon Yong; Kang, Do-Hyung; Kim, Kui-Jin; Lee, Boo-Yong

2017-08-17

Spirulina maxima is a microalgae which contains flavonoids and other polyphenols. Although Spirulina maxima 70% ethanol extract (SM70EE) has diverse beneficial effects, its effects on neurotoxicity have not been fully understood. In this study, we investigated the neuroprotective effects of SM70EE against trimethyltin (TMT)-induced neurotoxicity in HT-22 cells. SM70EE inhibited the cleavage of poly-ADP ribose polymerase (PARP). Besides, ROS production was decreased by down-regulating oxidative stress-associated enzymes. SM70EE increased the factors of brain-derived neurotrophic factor (BDNF)/cyclic AMPresponsive elementbinding protein (CREB) signalling pathways. Additionally, acetylcholinesterase (AChE) was suppressed by SM70EE. Furthermore, we investigated whether SM70EE prevents cognitive deficits against scopolamine-induced neurotoxicity in mice by applying behavioral tests. SM70EE increased step-through latency time and decreased the escape latency time. Therefore, our data suggest that SM70EE may prevent TMT neurotoxicity through promoting activation of BDNF/CREB neuroprotective signaling pathways in neuronal cells. In vivo study, SM70EE would prevent cognitive deficits against scopolamine-induced neurotoxicity in mice.

Information Thermodynamics of the Cell Signal Transduction as a Szilard Engine

Directory of Open Access Journals (Sweden)

Tatsuaki Tsuruyama

2018-03-01

Full Text Available A cell signaling system is in a non-equilibrium state, and it includes multistep biochemical signaling cascades (BSCs, which involve phosphorylation of signaling molecules, such as mitogen-activated protein kinase (MAPK pathways. In this study, the author considered signal transduction description using information thermodynamic theory. The ideal BSCs can be considered one type of the Szilard engine, and the presumed feedback controller, Maxwell’s demon, can extract the work during signal transduction. In this model, the mutual entropy and chemical potential of the signal molecules can be redefined by the extracted chemical work in a mechanicochemical model, Szilard engine, of BSC. In conclusion, signal transduction is computable using the information thermodynamic method.

Fundamentals of statistical signal processing

CERN Document Server

Kay, Steven M

1993-01-01

A unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms. Covers important approaches to obtaining an optimal estimator and analyzing its performance; and includes numerous examples as well as applications to real- world problems. MARKETS: For practicing engineers and scientists who design and analyze signal processing systems, i.e., to extract information from noisy signals — radar engineer, sonar engineer, geophysicist, oceanographer, biomedical engineer, communications engineer, economist, statistician, physicist, etc.

A Novel Multilayer Correlation Maximization Model for Improving CCA-Based Frequency Recognition in SSVEP Brain-Computer Interface.

Science.gov (United States)

Jiao, Yong; Zhang, Yu; Wang, Yu; Wang, Bei; Jin, Jing; Wang, Xingyu

2018-05-01

Multiset canonical correlation analysis (MsetCCA) has been successfully applied to optimize the reference signals by extracting common features from multiple sets of electroencephalogram (EEG) for steady-state visual evoked potential (SSVEP) recognition in brain-computer interface application. To avoid extracting the possible noise components as common features, this study proposes a sophisticated extension of MsetCCA, called multilayer correlation maximization (MCM) model for further improving SSVEP recognition accuracy. MCM combines advantages of both CCA and MsetCCA by carrying out three layers of correlation maximization processes. The first layer is to extract the stimulus frequency-related information in using CCA between EEG samples and sine-cosine reference signals. The second layer is to learn reference signals by extracting the common features with MsetCCA. The third layer is to re-optimize the reference signals set in using CCA with sine-cosine reference signals again. Experimental study is implemented to validate effectiveness of the proposed MCM model in comparison with the standard CCA and MsetCCA algorithms. Superior performance of MCM demonstrates its promising potential for the development of an improved SSVEP-based brain-computer interface.

Market signals of unsustainable and inequitable forest extraction

DEFF Research Database (Denmark)

Schaafsma, Marije; Burgess, Neil David; Swetnam, Ruth D.

2014-01-01

are largely captured by people whose livelihoods do not directly depend on other EAM ecosystem services. Market data, such as declining plank sizes and shifts to low-quality timber species, contain possible early warning signals of unsustainable hardwood harvesting. Policy recommendations include simplifying...

Extraction of the fetal ECG in noninvasive recordings by signal decompositions

International Nuclear Information System (INIS)

Christov, I; Simova, I; Abächerli, R

2014-01-01

No signal processing technique has been able to reliably deliver an undistorted fetal electrocardiographic (fECG) signal from electrodes placed on the maternal abdomen because of the low signal-to-noise ratio of the fECG recorded from the maternal body surface. As a result, this led to increased rates of Caesarean deliveries of healthy infants. In an attempt to solve the problem, Physionet/Computing in Cardiology announced the 2013 Challenge: noninvasive fetal ECG. We are suggesting a method for cancellation of the maternal ECG consisting of: maternal QRS detection, heart rate dependant P-QRS-T interval selection, location of the fiducial points inside this interval for best matching by cross correlation, superimposition of the intervals, calculation of the mean signal of the P-QRS-T interval, and sequential subtraction of the mean signal from the whole fECG recording. Three signal decomposition methods were further applied in order to enhance the fetal QRSs (fQRS): principal component analysis, root-mean-square and Hotelling’s T-squared. A combined lead of all decompositions was synthesized and fQRS detection was performed on it. The current research differs from the Challenge in that it uses three signal decomposition methods to enhance the fECG. The new results for 97 recordings of test set B are: 305.657 for Event 4: Fetal heart rate (FHR) and 23.062 for Event 5: Fetal RR interval (FRR). (paper)

Bibliography of extraction chromatography, ch. 15

International Nuclear Information System (INIS)

Eschrich, H.; Drent, W.

1975-01-01

A bibliography of reviews, books and publications dealing with laminar extraction chromatography is given. A tabular survey of experimental data on column extraction chromatographic investigations, stationary phases and support materials is presented. An author index and corporative author index are included. This bibliography refers to various publications relevant to nuclear interest

Symposium 'geology, mining and extractive processing of uranium, with special reference to Europe'

International Nuclear Information System (INIS)

Pietsch, H.B.

1977-01-01

This review of the symposium 'Geology, mining and extractive processing of uranium' gives a survey from the point of view of ore processing rather than exploration. A reason for the uranium consumption assumed is given, and uranium deposits and availability, methods of exploration, and interesting facts on uranium extraction from ores are gone into. (HK) [de

Status of the H- extraction program at TRIUMF

International Nuclear Information System (INIS)

Zach, M.; Laxdal, R.E.; Dutto, G.; Fong, K.; MacKenzie, G.H.; Pearson, J.B.; Stanford, G.

1989-05-01

The principle of utilizing the ν r - 3/2 resonance for efficient direct extraction of 100 μA of H - ions at 450 MeV from the TRIUMF cyclotron has been previously demonstrated. The initiation of the KAON Factory Project Definition Study at TRIUMF moves the emphasis of the H - extraction effort from the design of components compatible with short beam tests to equipment suitable for the final extraction configuration and from beam dynamics studies to engineering studies. To this end a reference extraction design has been chosen and will be described. Designs for the magnetic channels, both air core and iron compensated, ranging in strength from 0.1 T to 0.45 T, are progressing. Engineering constraints complicating the implementation of the reference design will be discussed

Quorum Quenching Revisited—From Signal Decays to Signalling Confusion

Directory of Open Access Journals (Sweden)

Kok-Gan Chan

2012-04-01

Full Text Available In a polymicrobial community, while some bacteria are communicating with neighboring cells (quorum sensing, others are interrupting the communication (quorum quenching, thus creating a constant arms race between intercellular communication. In the past decade, numerous quorum quenching enzymes have been found and initially thought to inactivate the signalling molecules. Though this is widely accepted, the actual roles of these quorum quenching enzymes are now being uncovered. Recent evidence extends the role of quorum quenching to detoxification or metabolism of signalling molecules as food and energy source; this includes “signalling confusion”, a term coined in this paper to refer to the phenomenon of non-destructive modification of signalling molecules. While quorum quenching has been explored as a novel anti-infective therapy targeting, quorum sensing evidence begins to show the development of resistance against quorum quenching.

Protective effect of Rhizoma Dioscoreae extract against alveolar bone loss in ovariectomized rats via regulation of IL-6/STAT3 signaling.

Science.gov (United States)

Zhang, Zhi-Guo; Chen, Yan-Jing; Xiang, Li-Hua; Pan, Jing-Hua; Wang, Zhen; Xiao, Gary Guishan; Ju, Da-Hong

2017-11-01

The aim of the present study was to assess the effectiveness of Rhizoma Dioscoreae extract (RDE) on preventing rat alveolar bone loss induced by ovariectomy (OVX), and to determine the role of interleukin-6 (IL-6)/signal transducer and activator of transcription 3 (STAT3) signaling pathway in this effect. Female Wistar rats were subjected to OVX or sham surgery. The rats that had undergone OVX were treated with RDE (RDE group), vehicle (OVX group) or 17β-estradiol subcutaneous injection (E2 group). Subsequently, bone metabolic activity was assessed by analyzing 3-D alveolar bone construction, bone mineral density, as well as the plasma biomarkers of bone turnover. The gene expression of alveolar bone in the OVX and RDE groups was evaluated by IL-6/STAT3 signaling pathway polymerase chain reaction (PCR) arrays, and differentially expressed genes were determined through reverse transcription-quantitative PCR. The inhibitory effect of RDE on alveolar bone loss in the OVX group was demonstrated in the study. In comparison with the OVX group, the RDE group exhibited 19 downregulated genes and 1 upregulated gene associated with the IL-6/STAT3 signaling pathway in alveolar bone. Thus, RDE was shown to relieve OVX-induced alveolar bone loss in rats, an effect which was likely associated with decreased abnormal bone remodeling via regulation of the IL-6/STAT3 signaling pathway.

Si-Wu-tang extract stimulates bone formation through PI3K/Akt/NF-κB signaling pathways in osteoblasts.

Science.gov (United States)

Wu, Chi-Ming; Chen, Po-Chun; Li, Te-Mao; Fong, Yi-Chin; Tang, Chih-Hsin

2013-10-24

Si-Wu-Tang (SWT), a Traditional Chinese Medicine (TCM) formula, is widely used for the treatment of gynopathies diseases such as menstrual discomfort, climacteric syndrome, dysmenorrhea, and other estrogen-related diseases. Recent studies have shown that SWT can treat primary dysmenorrhea, have anti-pruritic anti-inflammatory effects, and protect against radiation-induced bone marrow damage in an animal model. It has been reported that anti-inflammatory and anti-oxidant agents have the potential to treat osteoporosis by increasing bone formation and/or suppressing bone resorption. However, the effect of SWT on bone cell function has not yet been reported. Alkaline phosphatase (ALP), bone morphogenetic proteins (BMP)-2, and osteopontin (OPN) mRNA expression was analyzed by qPCR. The mechanism of action of SWT extract was investigated using western blotting. The in vivo anti-osteoporotic effect of SWT extract was assessed in ovariectomized mice. Here, we report that SWT increases ALP, BMP-2, and OPN expression as well as bone mineralization. In addition, we show that the PI3K, Akt, and NF-κB signaling pathways may be involved in the SWT-mediated increase in gene expression and bone mineralization. Notably, treatment of mice with SWT extract prevented bone loss induced by ovariectomy in vivo. SWT may be used to stimulate bone formation for the treatment of osteoporosis.

Detection test of wireless network signal strength and GPS positioning signal in underground pipeline

Science.gov (United States)

Li, Li; Zhang, Yunwei; Chen, Ling

2018-03-01

In order to solve the problem of selecting positioning technology for inspection robot in underground pipeline environment, the wireless network signal strength and GPS positioning signal testing are carried out in the actual underground pipeline environment. Firstly, the strength variation of the 3G wireless network signal and Wi-Fi wireless signal provided by China Telecom and China Unicom ground base stations are tested, and the attenuation law of these wireless signals along the pipeline is analyzed quantitatively and described. Then, the receiving data of the GPS satellite signal in the pipeline are tested, and the attenuation of GPS satellite signal under underground pipeline is analyzed. The testing results may be reference for other related research which need to consider positioning in pipeline.

Modified DCTNet for audio signals classification

Science.gov (United States)

Xian, Yin; Pu, Yunchen; Gan, Zhe; Lu, Liang; Thompson, Andrew

2016-10-01

In this paper, we investigate DCTNet for audio signal classification. Its output feature is related to Cohen's class of time-frequency distributions. We introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature extraction. The A-DCTNet applies the idea of constant-Q transform, with its center frequencies of filterbanks geometrically spaced. The A-DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to human audio perception than features such as Mel-frequency spectral coefficients (MFSC). We use features extracted by the A-DCTNet as input for classifiers. Experimental results show that the A-DCTNet and Recurrent Neural Networks (RNN) achieve state-of-the-art performance in bird song classification rate, and improve artist identification accuracy in music data. They demonstrate A-DCTNet's applicability to signal processing problems.

Eucalyptus globulus extract protects against UVB-induced photoaging by enhancing collagen synthesis via regulation of TGF-β/Smad signals and attenuation of AP-1.

Science.gov (United States)

Park, Bom; Hwang, Eunson; Seo, Seul A; Cho, Jin-Gyeong; Yang, Jung-Eun; Yi, Tae-Hoo

2018-01-01

UV irradiation triggers the overproduction of matrix metalloproteinases and collagen degradation, which in turn causes increased pigmentation, dryness, and deep wrinkling of the skin. These chronic symptoms are collectively referred to as photoaging. Eucalyptus globulus is an evergreen tree that is widely used in cosmetics because of its antimicrobial activity. In this study, we investigated the protective effect of 50% ethanol extracts of Eucalyptus globulus on UV-induced photoaging in vitro and in vivo. Normal human dermal fibroblasts were treated with Eucalyptus globulus at concentrations ranging from 1 to 100 μg/mL after UVB or non-UVB irradiation. We found that Eucalyptus globulus suppressed the expression of MMPs and IL-6, but increased the expression of TGF-β1 and procollagen type 1. In addition, Eucalyptus globulus inhibited activation of the AP-1 transcription factor, an inducer of MMPs. Eucalyptus globulus was also found to regulate TGF-β/Smad signaling by reversing the activity of negative Smad regulators. Lastly, in vivo studies showed that topical application of Eucalyptus globulus on UVB-irradiated hairless mice reduced wrinkle formation and dryness by down-regulating MMP-1 and up-regulating expression of elastin, TGF-β1, and procollagen type 1. Taken together, these data suggest that Eucalyptus globulus may be a useful agent in cosmetic products. Copyright © 2017 Elsevier Inc. All rights reserved.

Review on calixarene-type macrocycles and metal extraction data

International Nuclear Information System (INIS)

Ludwig, R.

1995-12-01

This paper gives an overview on the current state of solvent extraction studies with derivatized [1.n]-metacyclophanes and related compounds. 122 References from the last ten years are discussed and data on extractability, extraction equilibria, and complex formation are presented in graphical form. (author) 122 refs

Review on calixarene-type macrocycles and metal extraction data

Energy Technology Data Exchange (ETDEWEB)

Ludwig, R [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

1995-12-01

This paper gives an overview on the current state of solvent extraction studies with derivatized [1.n]-metacyclophanes and related compounds. 122 References from the last ten years are discussed and data on extractability, extraction equilibria, and complex formation are presented in graphical form. (author) 122 refs.

Comparison of extraction and clean-up techniques for the ...

African Journals Online (AJOL)

user

Six different extraction solvents: acetone, cyclohexane, 2- propanol, methanol, acetonitrile and dichloromethane, were tested to select the most suitable solvent for the extraction of the 16 PAHs from the certified soil reference material. The results were compared to determine the method with the highest extraction efficiency.

Parameter-free extraction of EMCD from an energy-filtered diffraction datacube using multivariate curve resolution

International Nuclear Information System (INIS)

Muto, S.; Tatsumi, K.; Rusz, J.

2013-01-01

We present a parameter-free method of extraction of the electron magnetic circular dichroism spectra from energy-filtered diffraction patterns measured on a crystalline specimen. The method is based on a multivariate curve resolution technique. The main advantage of the proposed method is that it allows extraction of the magnetic signal regardless of the symmetry and orientation of the crystal, as long as there is a sufficiently strong magnetic component of the signal in the diffraction plane. This method essentially overcomes difficulties in extraction of the EMCD signal caused by complexity of dynamical diffraction effects. - Highlights: ► New method of extraction of EMCD signal using statistical methods (multivariate curve resolution). ► EMCD can be extracted quantitatively regardless of symmetry of crystal or its orientation. ► First principles simulation of EFDIF datacube, including dynamical diffraction effects

Fetal ECG extraction via Type-2 adaptive neuro-fuzzy inference systems.

Science.gov (United States)

Ahmadieh, Hajar; Asl, Babak Mohammadzadeh

2017-04-01

We proposed a noninvasive method for separating the fetal ECG (FECG) from maternal ECG (MECG) by using Type-2 adaptive neuro-fuzzy inference systems. The method can extract FECG components from abdominal signal by using one abdominal channel, including maternal and fetal cardiac signals and other environmental noise signals, and one chest channel. The proposed algorithm detects the nonlinear dynamics of the mother's body. So, the components of the MECG are estimated from the abdominal signal. By subtracting estimated mother cardiac signal from abdominal signal, fetal cardiac signal can be extracted. This algorithm was applied on synthetic ECG signals generated based on the models developed by McSharry et al. and Behar et al. and also on DaISy real database. In environments with high uncertainty, our method performs better than the Type-1 fuzzy method. Specifically, in evaluation of the algorithm with the synthetic data based on McSharry model, for input signals with SNR of -5dB, the SNR of the extracted FECG was improved by 38.38% in comparison with the Type-1 fuzzy method. Also, the results show that increasing the uncertainty or decreasing the input SNR leads to increasing the percentage of the improvement in SNR of the extracted FECG. For instance, when the SNR of the input signal decreases to -30dB, our proposed algorithm improves the SNR of the extracted FECG by 71.06% with respect to the Type-1 fuzzy method. The same results were obtained on synthetic data based on Behar model. Our results on real database reflect the success of the proposed method to separate the maternal and fetal heart signals even if their waves overlap in time. Moreover, the proposed algorithm was applied to the simulated fetal ECG with ectopic beats and achieved good results in separating FECG from MECG. The results show the superiority of the proposed Type-2 neuro-fuzzy inference method over the Type-1 neuro-fuzzy inference and the polynomial networks methods, which is due to its

Large-signal modeling method for power FETs and diodes

Energy Technology Data Exchange (ETDEWEB)

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

2009-06-01

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

Large-signal modeling method for power FETs and diodes

International Nuclear Information System (INIS)

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

2009-01-01

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

Non-linear Analysis of Scalp EEG by Using Bispectra: The Effect of the Reference Choice

Directory of Open Access Journals (Sweden)

Federico Chella

2017-05-01

Full Text Available Bispectral analysis is a signal processing technique that makes it possible to capture the non-linear and non-Gaussian properties of the EEG signals. It has found various applications in EEG research and clinical practice, including the assessment of anesthetic depth, the identification of epileptic seizures, and more recently, the evaluation of non-linear cross-frequency brain functional connectivity. However, the validity and reliability of the indices drawn from bispectral analysis of EEG signals are potentially biased by the use of a non-neutral EEG reference. The present study aims at investigating the effects of the reference choice on the analysis of the non-linear features of EEG signals through bicoherence, as well as on the estimation of cross-frequency EEG connectivity through two different non-linear measures, i.e., the cross-bicoherence and the antisymmetric cross-bicoherence. To this end, four commonly used reference schemes were considered: the vertex electrode (Cz, the digitally linked mastoids, the average reference, and the Reference Electrode Standardization Technique (REST. The reference effects were assessed both in simulations and in a real EEG experiment. The simulations allowed to investigated: (i the effects of the electrode density on the performance of the above references in the estimation of bispectral measures; and (ii the effects of the head model accuracy in the performance of the REST. For real data, the EEG signals recorded from 10 subjects during eyes open resting state were examined, and the distortions induced by the reference choice in the patterns of alpha-beta bicoherence, cross-bicoherence, and antisymmetric cross-bicoherence were assessed. The results showed significant differences in the findings depending on the chosen reference, with the REST providing superior performance than all the other references in approximating the ideal neutral reference. In conclusion, this study highlights the importance of

Noise cancellation in magnetoencephalography and electroencephalography with isolated reference sensors

Science.gov (United States)

Kraus, Jr., Robert H.; Espy, Michelle A.; Matlachov, Andrei; Volegov, Petr

2010-06-01

An apparatus measures electromagnetic signals from a weak signal source. A plurality of primary sensors is placed in functional proximity to the weak signal source with an electromagnetic field isolation surface arranged adjacent the primary sensors and between the weak signal source and sources of ambient noise. A plurality of reference sensors is placed adjacent the electromagnetic field isolation surface and arranged between the electromagnetic isolation surface and sources of ambient noise.

Tevatron extraction microcomputer

International Nuclear Information System (INIS)

Chapman, L.; Finley, D.A.; Harrison, M.; Merz, W.

1985-06-01

Extraction in the Fermilab Tevatron is controlled by a multi-processor Multibus microcomputer system called QXR (Quad eXtraction Regulator). QXR monitors several analog beam signals and controls three sets of power supplies: the ''bucker'' and ''pulse'' magnets at a rate of 5760 Hz, and the ''QXR'' magnets at 720 Hz. QXR supports multiple slow spills (up to a total of 35 seconds) with multiple fast pulses intermixed. It linearizes the slow spill and bucks out the high frequency components. Fast extraction is done by outputting a variable pulse waveform. Closed loop learning techniques are used to improve performance from cycle to cycle for both slow and fast extraction. The system is connected to the Tevatron clock system so that it can track the machine cycle. QXR is also connected to the rest of the Fermilab control system, ACNET. Through ACNET, human operators and central computers can monitor and control extraction through communications with QXR. The controls hardware and software both employ some standard and some specialized components. This paper gives an overview of QXR as a control system; another paper summarizes performance

Use of multiple singular value decompositions to analyze complex intracellular calcium ion signals

KAUST Repository

Martinez, Josue G.

2009-12-01

We compare calcium ion signaling (Ca(2+)) between two exposures; the data are present as movies, or, more prosaically, time series of images. This paper describes novel uses of singular value decompositions (SVD) and weighted versions of them (WSVD) to extract the signals from such movies, in a way that is semi-automatic and tuned closely to the actual data and their many complexities. These complexities include the following. First, the images themselves are of no interest: all interest focuses on the behavior of individual cells across time, and thus, the cells need to be segmented in an automated manner. Second, the cells themselves have 100+ pixels, so that they form 100+ curves measured over time, so that data compression is required to extract the features of these curves. Third, some of the pixels in some of the cells are subject to image saturation due to bit depth limits, and this saturation needs to be accounted for if one is to normalize the images in a reasonably un-biased manner. Finally, the Ca(2+) signals have oscillations or waves that vary with time and these signals need to be extracted. Thus, our aim is to show how to use multiple weighted and standard singular value decompositions to detect, extract and clarify the Ca(2+) signals. Our signal extraction methods then lead to simple although finely focused statistical methods to compare Ca(2+) signals across experimental conditions.

X-ray holography with a customizable reference.

Science.gov (United States)

Martin, Andrew V; D'Alfonso, Adrian J; Wang, Fenglin; Bean, Richard; Capotondi, Flavio; Kirian, Richard A; Pedersoli, Emanuele; Pedersoli, Emmanuele; Raimondi, Lorenzo; Stellato, Francesco; Yoon, Chun Hong; Chapman, Henry N

2014-08-22

In X-ray Fourier-transform holography, images are formed by exploiting the interference pattern between the X-rays scattered from the sample and a known reference wave. To date, this technique has only been possible with a limited set of special reference waves. We demonstrate X-ray Fourier-transform holography with an almost unrestricted choice for the reference wave, permitting experimental geometries to be designed according to the needs of each experiment and opening up new avenues to optimize signal-to-noise and resolution. The optimization of holographic references can aid the development of holographic techniques to meet the demands of resolution and fidelity required for single-shot imaging applications with X-ray lasers.

Research on Weak Fault Extraction Method for Alleviating the Mode Mixing of LMD

Directory of Open Access Journals (Sweden)

Lin Zhang

2018-05-01

Full Text Available Compared with the strong background noise, the energy entropy of early fault signals of bearings are weak under actual working conditions. Therefore, extracting the bearings’ early fault features has always been a major difficulty in fault diagnosis of rotating machinery. Based on the above problems, the masking method is introduced into the Local Mean Decomposition (LMD decomposition process, and a weak fault extraction method based on LMD and mask signal (MS is proposed. Due to the mode mixing of the product function (PF components decomposed by LMD in the noisy background, it is difficult to distinguish the authenticity of the fault frequency. Therefore, the MS method is introduced to deal with the PF components that are decomposed by the LMD and have strong correlation with the original signal, so as to suppress the modal aliasing phenomenon and extract the fault frequencies. In this paper, the actual fault signal of the rolling bearing is analyzed. By combining the MS method with the LMD method, the fault signal mixed with the noise is processed. The kurtosis value at the fault frequency is increased by eight-fold, and the signal-to-noise ratio (SNR is increased by 19.1%. The fault signal is successfully extracted by the proposed composite method.

The neural correlates of reference to the past

Directory of Open Access Journals (Sweden)

Laura S. Bos

2014-04-01

Analysis (see Figure 1 showed greater BOLD signal change for both types of past over non-past time-reference bilaterally frontal—the SMA and frontal superior medial gyrus. We ascribe this to increased difficulty in selecting past time-reference inflection, hence, discourse linking. We found significantly increased LIFG activation for simple past over simple present, but not for periphrastic past over future (see Figure 1C. LIFG might be taxed for past tense inflection, but not past time-reference specifically. Although periphrastic past and future differ in time-reference, both verb clusters have a present tense auxiliary. Our results align with a fundamental difference between past and non-past time-reference, and are in accordance with past time-reference processing difficulties of aphasic individuals.

Biological signals classification and analysis

CERN Document Server

Kiasaleh, Kamran

2015-01-01

This authored monograph presents key aspects of signal processing analysis in the biomedical arena. Unlike wireless communication systems, biological entities produce signals with underlying nonlinear, chaotic nature that elude classification using the standard signal processing techniques, which have been developed over the past several decades for dealing primarily with standard communication systems. This book separates what is random from that which appears to be random, and yet is truly deterministic with random appearance. At its core, this work gives the reader a perspective on biomedical signals and the means to classify and process such signals. In particular, a review of random processes along with means to assess the behavior of random signals is also provided. The book also includes a general discussion of biological signals in order to demonstrate the inefficacy of the well-known techniques to correctly extract meaningful information from such signals. Finally, a thorough discussion of recently ...

A Transform-Based Feature Extraction Approach for Motor Imagery Tasks Classification

Science.gov (United States)

Khorshidtalab, Aida; Mesbah, Mostefa; Salami, Momoh J. E.

2015-01-01

In this paper, we present a new motor imagery classification method in the context of electroencephalography (EEG)-based brain–computer interface (BCI). This method uses a signal-dependent orthogonal transform, referred to as linear prediction singular value decomposition (LP-SVD), for feature extraction. The transform defines the mapping as the left singular vectors of the LP coefficient filter impulse response matrix. Using a logistic tree-based model classifier; the extracted features are classified into one of four motor imagery movements. The proposed approach was first benchmarked against two related state-of-the-art feature extraction approaches, namely, discrete cosine transform (DCT) and adaptive autoregressive (AAR)-based methods. By achieving an accuracy of 67.35%, the LP-SVD approach outperformed the other approaches by large margins (25% compared with DCT and 6 % compared with AAR-based methods). To further improve the discriminatory capability of the extracted features and reduce the computational complexity, we enlarged the extracted feature subset by incorporating two extra features, namely, Q- and the Hotelling’s \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$T^{2}$ \\end{document} statistics of the transformed EEG and introduced a new EEG channel selection method. The performance of the EEG classification based on the expanded feature set and channel selection method was compared with that of a number of the state-of-the-art classification methods previously reported with the BCI IIIa competition data set. Our method came second with an average accuracy of 81.38%. PMID:27170898

EEG Signal Classification With Super-Dirichlet Mixture Model

DEFF Research Database (Denmark)

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

2012-01-01

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

Fetal source extraction from magnetocardiographic recordings by dependent component analysis

Energy Technology Data Exchange (ETDEWEB)

Araujo, Draulio B de [Department of Physics and Mathematics, FFCLRP, University of Sao Paulo, Ribeirao Preto, SP (Brazil); Barros, Allan Kardec [Department of Electrical Engineering, Federal University of Maranhao, Sao Luis, Maranhao (Brazil); Estombelo-Montesco, Carlos [Department of Physics and Mathematics, FFCLRP, University of Sao Paulo, Ribeirao Preto, SP (Brazil); Zhao, Hui [Department of Medical Physics, University of Wisconsin, Madison, WI (United States); Filho, A C Roque da Silva [Department of Physics and Mathematics, FFCLRP, University of Sao Paulo, Ribeirao Preto, SP (Brazil); Baffa, Oswaldo [Department of Physics and Mathematics, FFCLRP, University of Sao Paulo, Ribeirao Preto, SP (Brazil); Wakai, Ronald [Department of Medical Physics, University of Wisconsin, Madison, WI (United States); Ohnishi, Noboru [Department of Information Engineering, Nagoya University (Japan)

2005-10-07

Fetal magnetocardiography (fMCG) has been extensively reported in the literature as a non-invasive, prenatal technique that can be used to monitor various functions of the fetal heart. However, fMCG signals often have low signal-to-noise ratio (SNR) and are contaminated by strong interference from the mother's magnetocardiogram signal. A promising, efficient tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). Herein we propose an algorithm based on a variation of ICA, where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We model the system using autoregression, and identify the signal component of interest from the poles of the autocorrelation function. We show that the method is effective in removing the maternal signal, and is computationally efficient. We also compare our results to more established ICA methods, such as FastICA.

Aqueous extract of Tribulus terrestris Linn induces cell growth arrest and apoptosis by down-regulating NF-κB signaling in liver cancer cells.

Science.gov (United States)

Kim, Hye Jin; Kim, Jin Chul; Min, Jung Sun; Kim, Mi-Jee; Kim, Ji Ae; Kor, Myung Ho; Yoo, Hwa Seung; Ahn, Jeong Keun

2011-06-14

A medicinal herb Tribulus terrestris Linn has been used to treat various diseases including hepatocellular carcinoma. The aim of the present study was to investigate the anticancer activity of Tribulus terrestris Linn (TT) in liver cancer cells. The antitumor activity of aqueous TT extract was analyzed by testing the cytotoxicity and the effect on clonogenecity in HepG2 cells. Apoptosis and cell cycle arrest induced by TT were dissected by flow cytometry and its inhibitory effect on NF-κB activity was determined by analyzing the expression levels of NF-κB/IκB subunit proteins. The suppression of NF-κB-regulated gene expression by TT was assessed by RT-PCR. TT extract repressed clonogenecity and proliferation, induced apoptosis, and enhanced accumulation in the G0/G1 phase of liver cancer cells. It also turned out that TT extract inhibited NF-κB-dependent reporter gene expression and NF-κB subunit p50 expression, while it enhanced the cellular level of IκBα by inhibiting the phosphorylation and degradation of IκBα. In addition, IKK activity was inhibited in a dose-dependent manner. Furthermore, TT extract suppressed the transcription of genes associated with cell cycle regulation, anti-apoptosis, and invasion. These data showed that TT extract blocks proliferation and induces apoptosis in human liver cancer cells through the inhibition of NF-κB signaling. Aqueous TT extract can be used as an anticancer drug for hepatocellular carcinoma patients. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Extracting messages masked by chaos

International Nuclear Information System (INIS)

Perez, G.; Cerdeira, H.A.

1995-01-01

We show how to extract messages that are masked by a chaotic signal in a system of two Lorenz oscillators. This mask removal is done for two different modes of transmission, a digital one where a parameter of the sender is switched between two values, and an analog mode, where a small amplitude message is added to the carrier signal. We achieve this without using a second Lorenz oscillator as receiver, and without doing a full reconstruction of the dynamics. This method is robust with respect to transformations that impede the unmasking using a Lorenz receiver, and is not affected by the broad-band noise that is inherent to the synchronization process. We also discuss the limitations of this way of extraction for messages in high frequency bands. (author). 12 refs, 4 figs

Sensory integration of a light touch reference in human standing balance

Science.gov (United States)

Smith, Craig P.; Reynolds, Raymond F.

2018-01-01

In upright stance, light touch of a space-stationary touch reference reduces spontaneous sway. Moving the reference evokes sway responses which exhibit non-linear behavior that has been attributed to sensory reweighting. Reweighting refers to a change in the relative contribution of sensory cues signaling body sway in space and light touch cues signaling finger position with respect to the body. Here we test the hypothesis that the sensory fusion process involves a transformation of light touch signals into the same reference frame as other sensory inputs encoding body sway in space, or vice versa. Eight subjects lightly gripped a robotic manipulandum which moved in a circular arc around the ankle joint. A pseudo-randomized motion sequence with broad spectral characteristics was applied at three amplitudes. The stimulus was presented at two different heights and therefore different radial distances, which were matched in terms of angular motion. However, the higher stimulus evoked a significantly larger sway response, indicating that the response was not matched to stimulus angular motion. Instead, the body sway response was strongly related to the horizontal translation of the manipulandum. The results suggest that light touch is integrated as the horizontal distance between body COM and the finger. The data were well explained by a model with one feedback loop minimizing changes in horizontal COM-finger distance. The model further includes a second feedback loop estimating the horizontal finger motion and correcting the first loop when the touch reference is moving. The second loop includes the predicted transformation of sensory signals into the same reference frame and a non-linear threshold element that reproduces the non-linear sway responses, thus providing a mechanism that can explain reweighting. PMID:29874252

Comparison of continuously acquired resting state and extracted analogues from active tasks.

Science.gov (United States)

Ganger, Sebastian; Hahn, Andreas; Küblböck, Martin; Kranz, Georg S; Spies, Marie; Vanicek, Thomas; Seiger, René; Sladky, Ronald; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

2015-10-01

Functional connectivity analysis of brain networks has become an important tool for investigation of human brain function. Although functional connectivity computations are usually based on resting-state data, the application to task-specific fMRI has received growing attention. Three major methods for extraction of resting-state data from task-related signal have been proposed (1) usage of unmanipulated task data for functional connectivity; (2) regression against task effects, subsequently using the residuals; and (3) concatenation of baseline blocks located in-between task blocks. Despite widespread application in current research, consensus on which method best resembles resting-state seems to be missing. We, therefore, evaluated these techniques in a sample of 26 healthy controls measured at 7 Tesla. In addition to continuous resting-state, two different task paradigms were assessed (emotion discrimination and right finger-tapping) and five well-described networks were analyzed (default mode, thalamus, cuneus, sensorimotor, and auditory). Investigating the similarity to continuous resting-state (Dice, Intraclass correlation coefficient (ICC), R(2) ) showed that regression against task effects yields functional connectivity networks most alike to resting-state. However, all methods exhibited significant differences when compared to continuous resting-state and similarity metrics were lower than test-retest of two resting-state scans. Omitting global signal regression did not change these findings. Visually, the networks are highly similar, but through further investigation marked differences can be found. Therefore, our data does not support referring to resting-state when extracting signals from task designs, although functional connectivity computed from task-specific data may indeed yield interesting information. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Extracting natural dyes from wool--an evaluation of extraction methods.

Science.gov (United States)

Manhita, Ana; Ferreira, Teresa; Candeias, António; Dias, Cristina Barrocas

2011-05-01

The efficiency of eight different procedures used for the extraction of natural dyes was evaluated using contemporary wool samples dyed with cochineal, madder, woad, weld, brazilwood and logwood. Comparison was made based on the LC-DAD peak areas of the natural dye's main components which had been extracted from the wool samples. Among the tested methods, an extraction procedure with Na(2)EDTA in water/DMF (1:1, v/v) proved to be the most suitable for the extraction of the studied dyes, which presented a wide range of chemical structures. The identification of the natural dyes used in the making of an eighteenth century Arraiolos carpet was possible using the Na(2)EDTA/DMF extraction of the wool embroidery samples and an LC-DAD-MS methodology. The effectiveness of the Na(2)EDTA/DMF extraction method was particularly observed in the extraction of weld dye components. Nine flavone derivatives previously identified in weld extracts could be identified in a single historical sample, confirming the use of this natural dye in the making of Arraiolos carpets. Indigo and brazilwood were also identified in the samples, and despite the fact that these natural dyes were referred in the historical recipes of Arraiolos dyeing, it is the first time that the use of brazilwood is confirmed. Mordant analysis by ICP-MS identified the widespread use of alum in the dyeing process, but in some samples with darker hues, high amounts of iron were found instead.

Electronic signal conditioning

CERN Document Server

NEWBY, BRUCE

1994-01-01

At technician level, brief references to signal conditioning crop up in a fragmented way in various textbooks, but there has been no single textbook, until now!More advanced texts do exist but they are more mathematical and presuppose a higher level of understanding of electronics and statistics. Electronic Signal Conditioning is designed for HNC/D students and City & Guilds Electronics Servicing 2240 Parts 2 & 3. It will also be useful for BTEC National, Advanced GNVQ, A-level electronics and introductory courses at degree level.

Tamarind Seed Xyloglucans Promote Proliferation and Migration of Human Skin Cells through Internalization via Stimulation of Proproliferative Signal Transduction Pathways

Directory of Open Access Journals (Sweden)

W. Nie

2013-01-01

Full Text Available Xyloglucans (XGs of Tamarindus indica L. Fabaceae are used as drug vehicles or as ingredients of cosmetics. Two xyloglucans were extracted from T. indica seed with cold water (TSw and copper complex precipitation (TSc. Both were analyzed in regard to composition and influence on cell viability, proliferation, cell cycle progression, migration, MAPK phosphorylation, and gene expression of human skin keratinocytes (NHEK and HaCaT and fibroblasts (NHDF in vitro. TSw and TSc differed in molecular weight, rhamnose content, and ratios of xylose, arabinose, galactose, and glucose. Both XGs improved keratinocytes and fibroblast proliferation, promoted the cell cycle, and stimulated migration and intracellular enzyme activity of NHDF after endosomal uptake. Only TSw significantly enhanced HaCaT migration and extracellular enzyme activity of NHDF and HaCaT. TSw and TSc predominantly enhanced the phosphorylation of molecules that referred to Erk signaling in NHEK. In NHDF parts of the integrin signaling and SAPK/JNK pathway were affected. Independent of cell type TSw marginally regulated the expression of genes, which referred to membrane proteins, cytoskeleton, cytokine signaling, and ECM as well as to processes of metabolism and transcription. Results show that T. indica xyloglucans promote skin regeneration by a direct influence on cell proliferation and migration.

Deep Learning Methods for Underwater Target Feature Extraction and Recognition

Directory of Open Access Journals (Sweden)

Gang Hu

2018-01-01

Full Text Available The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert-Huang transform, and Mel frequency cepstral coefficients are used as a method of underwater acoustic signal feature extraction. In this paper, a method for feature extraction and identification of underwater noise data based on CNN and ELM is proposed. An automatic feature extraction method of underwater acoustic signals is proposed using depth convolution network. An underwater target recognition classifier is based on extreme learning machine. Although convolution neural networks can execute both feature extraction and classification, their function mainly relies on a full connection layer, which is trained by gradient descent-based; the generalization ability is limited and suboptimal, so an extreme learning machine (ELM was used in classification stage. Firstly, CNN learns deep and robust features, followed by the removing of the fully connected layers. Then ELM fed with the CNN features is used as the classifier to conduct an excellent classification. Experiments on the actual data set of civil ships obtained 93.04% recognition rate; compared to the traditional Mel frequency cepstral coefficients and Hilbert-Huang feature, recognition rate greatly improved.

High-Q Bandpass Comb Filter for Mains Interference Extraction

Directory of Open Access Journals (Sweden)

Neycheva T.

2009-12-01

Full Text Available This paper presents a simple digital high-Q bandpass comb filter for power-line (PL or other periodical interference extraction. The filter concept relies on a correlated signal average resulting in alternating constructive and destructive spectrum interference i.e. the so-called comb frequency response. The presented filter is evaluated by Matlab simulations with real ECG signal contaminated with low amplitude PL interference. The made simulations show that this filter accurately extract the PL interference. It has high-Q notches only at PL odd harmonics and is appropriate for extraction of any kind of odd harmonic interference including rectangular shape. The filter is suitable for real-time operation with popular low-cost microcontrollers.

Evaluation of Masimo signal extraction technology pulse oximetry in anaesthetized pregnant sheep.

Science.gov (United States)

Quinn, Christopher T; Raisis, Anthea L; Musk, Gabrielle C

2013-03-01

Evaluation of the accuracy of Masimo signal extraction technology (SET) pulse oximetry in anaesthetized late gestational pregnant sheep. Prospective experimental study. Seventeen pregnant Merino ewes. Animals included in study were late gestation ewes undergoing general anaesthesia for Caesarean delivery or foetal surgery in a medical research laboratory. Masimo Radical-7 pulse oximetry (SpO(2) ) measurements were compared to co-oximetry (SaO(2) ) measurements from arterial blood gas analyses. The failure rate of the pulse oximeter was calculated. Accuracy was assessed by Bland & Altman's (2007) limits of agreement method. The effect of mean arterial blood pressure (MAP), perfusion index (PI) and haemoglobin (Hb) concentration on accuracy were assessed by regression analysis. Forty arterial blood samples paired with SpO(2) and blood pressure measurements were obtained. SpO(2) ranged from 42 to 99% and SaO(2) from 43.7 to 99.9%. MAP ranged from 24 to 82 mmHg, PI from 0.1 to 1.56 and Hb concentration from 71 to 114 g L(-1) . Masimo pulse oximetry measurements tended to underestimate oxyhaemoglobin saturation compared to co-oximetry with a bias (mean difference) of -2% and precision (standard deviation of the differences) of 6%. Accuracy appeared to decrease when SpO(2) was oximeter function during extreme hypotension and hypoxaemia. © 2012 The Authors. Veterinary Anaesthesia and Analgesia. © 2012 Association of Veterinary Anaesthetists and the American College of Veterinary Anesthesiologists.

Principle study on the signal connection at transabdominal fetal pulse oximetry

Directory of Open Access Journals (Sweden)

Böttrich Marcel

2016-09-01

Full Text Available Transabdominal fetal pulse oximetry is an approach to measure oxygen saturation of the unborn child non-invasively. The principle of pulse oximetry is applied to the abdomen of a pregnant woman, such that the measured signal includes both, the maternal and the fetal pulse curve. One of the major challenges is to extract the shape of the fetal pulse curve from the mixed signal for computation of the oxygen saturation. In this paper we analyze the principle kind of connection of the fetal and maternal pulse curves in the measured signal. A time varying finite element model is used to rebuild the basic measurement environment, including a bulk tissue and two independently pulsing arteries to model the fetal and maternal blood circuit. The distribution of the light fluence rate in the model is computed by applying diffusion equation. From the detectors we extracted the time dependent fluence rate and analyzed the signal regarding its components. The frequency spectra of the signals show peaks at the fetal and maternal basic frequencies. Additional signal components are visible in the spectra, indicating multiplicative coupling of the fetal and maternal pulse curves. We conclude that the underlying signal model of algorithms for robust extraction of the shape of the fetal pulse curve, have to consider additive and multiplicative signal coupling.

rf reference line for PEP

International Nuclear Information System (INIS)

Schwarz, H.D.; Weaver, J.N.

1979-03-01

A rf phase reference line in 6 segments around the 2200 meter circumference PEP storage ring is described. Each segment of the reference line is phase stabilized by its own independent feedback system, which uses an amplitude modulated reflection from the end of each line. The modulation is kept small and decoupled from the next segment to avoid crosstalk and significant modulation of the rf drive signal. An error evaluation of the system is made. The technical implementation and prototype performance are described. Prototype tests indicate that the phase error around the ring can be held below 1 degree with this relatively simple system

rf reference line for PEP

Energy Technology Data Exchange (ETDEWEB)

Schwarz, H.D.; Weaver, J.N.

1979-03-01

A rf phase reference line in 6 segments around the 2200 meter circumference PEP storage ring is described. Each segment of the reference line is phase stabilized by its own independent feedback system, which uses an amplitude modulated reflection from the end of each line. The modulation is kept small and decoupled from the next segment to avoid crosstalk and significant modulation of the rf drive signal. An error evaluation of the system is made. The technical implementation and prototype performance are described. Prototype tests indicate that the phase error around the ring can be held below 1 degree with this relatively simple system.

Production of acyl-homoserine lactone quorum-sensing signals is widespread in gram-negative Methylobacterium.

Science.gov (United States)

Poonguzhali, Selvaraj; Madhaiyan, Munusamy; Sa, Tongmin

2007-02-01

Members of Methylobacterium, referred as pink-pigmented facultative methylotrophic bacteria, are frequently associated with terrestrial and aquatic plants, tending to form aggregates on the phyllosphere. We report here that the production of autoinducer molecules involved in the cell-to-cell signaling process, which is known as quorum sensing, is common among Methylobacterium species. Several strains of Methylobacterium were tested for their ability to produce N-acyl-homoserine lactone (AHL) signal molecules using different indicators. Most strains of Methylobacterium tested could elicit a positive response in Agrobacterium tumefaciens harboring lacZ fused to a gene that is regulated by autoinduction. The synthesis of these compounds was cell-density dependent, and the maximal activity was reached during the late exponential to stationary phases. The bacterial extracts were separated by thin-layer chromatography and bioassayed with A. tumefaciens NT1 (traR, tra::lacZ749). They revealed the production of various patterns of the signal molecules, which are strain dependent. At least two signal molecules could be detected in most of the strains tested, and comparison of their relative mobilities suggested that they are homologs of N-octanoyl-DL-homoserine lactone (C8-HSL) and N-decanoyl-DL-homoserine lactone (C10-HSL).

Mechanomyographic Parameter Extraction Methods: An Appraisal for Clinical Applications

Directory of Open Access Journals (Sweden)

Morufu Olusola Ibitoye

2014-12-01

Full Text Available The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity.

Optimized Feature Extraction for Temperature-Modulated Gas Sensors

Directory of Open Access Journals (Sweden)

Alexander Vergara

2009-01-01

Full Text Available One of the most serious limitations to the practical utilization of solid-state gas sensors is the drift of their signal. Even if drift is rooted in the chemical and physical processes occurring in the sensor, improved signal processing is generally considered as a methodology to increase sensors stability. Several studies evidenced the augmented stability of time variable signals elicited by the modulation of either the gas concentration or the operating temperature. Furthermore, when time-variable signals are used, the extraction of features can be accomplished in shorter time with respect to the time necessary to calculate the usual features defined in steady-state conditions. In this paper, we discuss the stability properties of distinct dynamic features using an array of metal oxide semiconductors gas sensors whose working temperature is modulated with optimized multisinusoidal signals. Experiments were aimed at measuring the dispersion of sensors features in repeated sequences of a limited number of experimental conditions. Results evidenced that the features extracted during the temperature modulation reduce the multidimensional data dispersion among repeated measurements. In particular, the Energy Signal Vector provided an almost constant classification rate along the time with respect to the temperature modulation.

Social signal processing for studying parent-infant interaction

Directory of Open Access Journals (Sweden)

Marie eAvril

2014-12-01

Full Text Available Studying early interactions is a core issue of infant development and psychopathology. Automatic social signal processing theoretically offers the possibility to extract and analyse communication by taking an integrative perspective, considering the multimodal nature and dynamics of behaviours (including synchrony. This paper proposes an explorative method to acquire and extract relevant social signals from a naturalistic early parent-infant interaction. An experimental setup is proposed based on both clinical and technical requirements. We extracted various cues from body postures and speech productions of partners using the IMI2S (Interaction, Multimodal Integration, and Social Signal Framework. Preliminary clinical and computational results are reported for two dyads (one pathological in a situation of severe emotional neglect and one normal control as an illustration of our cross-disciplinary protocol. The results from both clinical and computational analyses highlight similar differences: the pathological dyad shows dyssynchronic interaction led by the infant whereas the control dyad shows synchronic interaction and a smooth interactive dialog. The results suggest that the current method might be promising for future studies.

A review of signals used in sleep analysis

International Nuclear Information System (INIS)

Roebuck, A; Monasterio, V; Gederi, E; Osipov, M; Behar, J; Clifford, G D; Malhotra, A; Penzel, T

2014-01-01

This article presents a review of signals used for measuring physiology and activity during sleep and techniques for extracting information from these signals. We examine both clinical needs and biomedical signal processing approaches across a range of sensor types. Issues with recording and analysing the signals are discussed, together with their applicability to various clinical disorders. Both univariate and data fusion (exploiting the diverse characteristics of the primary recorded signals) approaches are discussed, together with a comparison of automated methods for analysing sleep. (topical review)

Separable Reversible Data Hiding in Encrypted Signals with Public Key Cryptography

Directory of Open Access Journals (Sweden)

Wei-Liang Tai

2018-01-01

Full Text Available We propose separable reversible data hiding in an encrypted signal with public key cryptography. In our separable framework, the image owner encrypts the original image by using a public key. On receipt of the encrypted signal, the data-hider embeds data in it by using a data-hiding key. The image decryption and data extraction are independent and separable at the receiver side. Even though the receiver, who has only the data-hiding key, does not learn about the decrypted content, he can extract data from the received marked encrypted signal. However, the receiver who has only the private key cannot extract the embedded data, but he can directly decrypt the received marked encrypted signal to obtain the original image without any error. Compared with other schemes using a cipher stream to encrypt the image, the proposed scheme is more appropriate for cloud services without degrading the security level.

Extractability of Thevetia peruviana glycosides with alcohol mixture

African Journals Online (AJOL)

SERVER

2007-09-19

Sep 19, 2007 ... Nitrogen extraction of defatted rapeseed with particular reference to United Kingdom rapeseed meal. J. Sci. Food Agric. 36: 520–530. Finnigan TJA, Lewis MJ (1988). Ethanolic Extraction of Commercial. Rapeseed Meal in the Production of Protein Concentrate of Reduced. Glucosinolate Content. J. Sci.

Extracts of Porphyra tenera (Nori Seaweed) Activate the Immune Response in Mouse RAW264.7 Macrophages via NF-κB Signaling.

Science.gov (United States)

Song, Ji-Hye; Kang, Hee-Bum; Park, Seung-Ho; Jeong, Ji-Hoon; Park, Jeongjin; You, Yanghee; Lee, Yoo-Hyun; Lee, Jeongmin; Kim, Eungpil; Choi, Kyung-Chul; Jun, Woojin

2017-12-01

Porphyra tenera, also known as nori, is a red algal species of seaweed. It is cultivated in Asia for culinary purposes. We report that P. tenera extract (PTE) enhances the immune response in mouse macrophages. We found that P. tenera extract regulates the NF-κB IκB kinase (IKK) signaling pathway, and we assessed the expression and translocation of p65, a subunit of NF-κB, in RAW264.7 mouse macrophage cells after treatment with PTE. We also investigated the effects of 10% ethanol PTE (PTE10) in RAW264.7 cells. The production of IL-10, IL-6, TNF-α, and IFN-γ was induced by PTE treatment of the macrophages, and PTE also enhanced p-IκB and p-AKT. PTE10 showed no cytotoxicity at 10-20 μg/mL in RAW264.7 cells. PTE10, in fact, increased cell viability at 24 h, stimulated macrophage cells, and induced the phosphorylation of Akt. Akt stimulates IKK activity through the phosphorylation of IKKα and enhances immune activity through the activation of NF-κB. In this study, NF-κB activation was induced by increasing p-NF-κB and p-IKK. A subunit of NF-κB, p65, was located in the nucleus and increased the expression of various cytokines. PTE thus enhanced the immune response through IκB-α immunostimulation signaling in RAW264.7 cells. PTE10 has potential therefore for development of future treatments requiring immune system stimulation.

Tevatron extraction microcomputer

International Nuclear Information System (INIS)

Chapman, L.; Finley, D.A.; Harrison, M.; Merz, W.; Batavia, IL)

1985-01-01

Extraction in the Fermilab Tevatron is controlled by a multi-processor Multibus microcomputer system called QXR (Quad eXtraction Regulator). QXR monitors several analog beam signals and controls three sets of power supplies: the ''bucker'' and ''pulse'' magnets at a rate of 5760 Hz, and the ''QXR'' magnets at 720 Hz. QXR supports multiple slow spills (up to a total of 35 seconds) with multiple fast pulses intermixed. It linearizes the slow spill and bucks out the high frequency components. Fast extraction is done by outputting a variable pulse waveform. Closed loop learning techniques are used to improve performance from cycle to cycle for both slow and fast extraction. The system is connected to the Tevatron clock system so that it can track the machine cycle. QXR is also connected to the rest of the Fermilab control system, ACNET. Through ACNET, human operators and central computers can monitor and control extraction through communications with QXR. The controls hardware and software both employ some standard and some specialized components. This paper gives an overview of QXR as a control system; another paper (1) summarizes performance

Highly Simple Deep Eutectic Solvent Extraction of Manganese in Vegetable Samples Prior to Its ICP-OES Analysis.

Science.gov (United States)

Bağda, Esra; Altundağ, Hüseyin; Soylak, Mustafa

2017-10-01

In the present work, simple and sensitive extraction methods for selective determination of manganese have been successfully developed. The methods were based on solubilization of manganese in deep eutectic solvent medium. Three deep eutectic solvents with choline chloride (vitamin B4) and tartaric/oxalic/citric acids have been prepared. Extraction parameters were optimized with using standard reference material (1573a tomato leaves). The quantitative recovery values were obtained with 1.25 g/L sample to deep eutectic solvent (DES) volume, at 95 °C for 2 h. The limit of detection was found as 0.50, 0.34, and 1.23 μg/L for DES/tartaric, DES/oxalic, and DES/citric acid, respectively. At optimum conditions, the analytical signal was linear for the range of 10-3000 μg/L for all studied DESs with the correlation coefficient >0.99. The extraction methods were applied to different real samples such as basil herb, spinach, dill, and cucumber barks. The known amount of manganese was spiked to samples, and good recovery results were obtained.

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

Science.gov (United States)

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

2016-01-01

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

A novel strategy with standardized reference extract qualification and single compound quantitative evaluation for quality control of Panax notoginseng used as a functional food.

Science.gov (United States)

Li, S P; Qiao, C F; Chen, Y W; Zhao, J; Cui, X M; Zhang, Q W; Liu, X M; Hu, D J

2013-10-25

Root of Panax notoginseng (Burk.) F.H. Chen (Sanqi in Chinese) is one of traditional Chinese medicines (TCMs) based functional food. Saponins are the major bioactive components. The shortage of reference compounds or chemical standards is one of the main bottlenecks for quality control of TCMs. A novel strategy, i.e. standardized reference extract based qualification and single calibrated components directly quantitative estimation of multiple analytes, was proposed to easily and effectively control the quality of natural functional foods such as Sanqi. The feasibility and credibility of this methodology were also assessed with a developed fast HPLC method. Five saponins, including ginsenoside Rg1, Re, Rb1, Rd and notoginsenoside R1 were rapidly separated using a conventional HPLC in 20 min. The quantification method was also compared with individual calibration curve method. The strategy is feasible and credible, which is easily and effectively adapted for improving the quality control of natural functional foods such as Sanqi. Copyright © 2013 Elsevier B.V. All rights reserved.

Reference Device-Assisted Adaptive Location Fingerprinting

Directory of Open Access Journals (Sweden)

Dongjin Wu

2016-06-01

Full Text Available Location fingerprinting suffers in dynamic environments and needs recalibration from time to time to maintain system performance. This paper proposes an adaptive approach for location fingerprinting. Based on real-time received signal strength indicator (RSSI samples measured by a group of reference devices, the approach applies a modified Universal Kriging (UK interpolant to estimate adaptive temporal and environmental radio maps. The modified UK can take the spatial distribution characteristics of RSSI into account. In addition, the issue of device heterogeneity caused by multiple reference devices is further addressed. To compensate the measuring differences of heterogeneous reference devices, differential RSSI metric is employed. Extensive experiments were conducted in an indoor field and the results demonstrate that the proposed approach not only adapts to dynamic environments and the situation of changing APs’ positions, but it is also robust toward measuring differences of heterogeneous reference devices.

Towards a full reference library of MS(n) spectra. II: A perspective from the library of pesticide spectra extracted from the literature/Internet.

Science.gov (United States)

Milman, Boris L; Zhurkovich, Inna K

2011-12-30

To gain perspective on building full transferable libraries of MS(n) spectra from their diverse/numerous collections, a new library was built from 1723 MS(>1) spectra (mainly MS² spectra) of 490 pesticides and related compounds. Spectra acquired on different types of tandem instruments in various experimental conditions were extracted from 168 literature articles and Internet sites. Testing of the library was based on searches where 'unknown' and reference spectra originated from different sources (mainly from different laboratories) were cross-compared. The NIST 05 MS² library was added to the reference spectra. The library searches were performed with all the test spectra or were divided into different subsamples containing (a) various numbers of replicate spectra of test compounds or (b) spectra acquired from different instrument types. Thus, the dependence of true/false search (identification) result rates on different factors was explored. The percentage of 1st rank correct identifications (true positives) for the only 'unknown' mass spectrum and two and more reference spectra and matching precursor ion m/z values was 89%. For qualified matches, above the cut-off match factor, that rate decreased to 80%. The corresponding rates based on the best match for two and more 'unknown' and reference spectral replicates were 89-94%. For quadrupole instruments, the rates were even higher: 91-95% (one 'unknown' spectrum) and 90-100% (two and more such spectra). This study shows that MS² spectral libraries generated from the numerous literature/Internet sources are not less efficient for the goal of identification of unknown compounds including pesticides than very common EI-MS¹ libraries and are almost as efficient as the most productive from current MS² spectral databases. Such libraries may be used as individual reference databases or supplements to large experimental spectral collections covering many groups of abundant compounds and different types of tandem

Bioelectric Signal Measuring System

Science.gov (United States)

Guadarrama-Santana, A.; Pólo-Parada, L.; García-Valenzuela, A.

2015-01-01

We describe a low noise measuring system based on interdigitated electrodes for sensing bioelectrical signals. The system registers differential voltage measurements in order of microvolts. The base noise during measurements was in nanovolts and thus, the sensing signals presented a very good signal to noise ratio. An excitation voltage of 1Vrms with 10 KHz frequency was applied to an interdigitated capacitive sensor without a material under test and to a mirror device simultaneously. The output signals of both devices was then subtracted in order to obtain an initial reference value near cero volts and reduce parasitic capacitances due to the electronics, wiring and system hardware as well. The response of the measuring system was characterized by monitoring temporal bioelectrical signals in real time of biological materials such as embryo chicken heart cells and bovine suprarenal gland cells.

Contact-Free Heartbeat Signal for Human Identification and Forensics

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Haque, Mohammad Ahsanul; Irani, Ramin

2017-01-01

The heartbeat signal, which is one of the physiological signals, is of great importance in many real-world applications, for example, in patient monitoring and biometric recognition. The traditional methods for measuring such this signal use contact-based sensors that need to be installed...... been developed for contact-free extraction of the heartbeat signal. We have recently used the contact-free measured heartbeat signal, for bio- metric recognition, and have obtained promising results, indicating the importance of these signals for biometrics recognition and also for forensics...

Cellular semiotics and signal transduction

DEFF Research Database (Denmark)

Bruni, Luis Emilio

2007-01-01

Semiosis, the processes of production, communication and interpretation of signs - coding and de-coding - takes place within and between organisms. The term "endosemiosis" refers to the processes of interpretation and sign transmission inside an organism (as opposed to "exosemiosis", which refers...... to the processes of sign interpretation and transmission between organisms of the same or different species). In Biosemiotics it is customary to recognise the cell as the most elementary integration unit for semiosis. Therefore intra and intercellular communication constitute the departure point for the study...... considering semiotic logic in order to construct our understanding of living phenomena. Given the central integrating role of signal transduction in physiological and ecological studies, this chapter outlines its semiotic implications. The multi-modality and modularity of signal molecules and relative...

Extraction of Pn seismic signals from air-gun shots recorded by the Cascadia Amphibious seismic experiment

Science.gov (United States)

Rathnayaka, S.; Gao, H.

2017-12-01

The goal of this study is to extract Pn (head wave) seismic waveforms recorded by both offshore and onshore (broadband and short period) seismic stations and evaluate the data quality. Two offshore active-source seismic experiments, MGL 1211 and MGL 1212, were conducted from 13th June to 24th July 2012, during the first year deployment of the Cascadia Initiative Amphibious Array. In total, we choose 110 ocean bottom seismometers and 209 inland stations that are located along the entire Cascadia subduction zone. We first remove the instrument response, and then explore the potential frequency ranges and the diurnal effect. We make the common receiver gathering for each seismic station and filter the seismic waveforms at multiple frequency bands, ranging from 3-5 Hz, 5-10 Hz, 10-20 Hz, to 20-40 Hz, respectively. To quantitatively evaluate the data quality, we calculate the signal-to-noise ratio (SNR) of the waveforms for usable stations that record clear Pn arrivals at multiple frequency bands. Our results show that most offshore stations located at deep water (>1.5 km) record clear air-gun shot signals at frequencies higher than 3 Hz and up to 550 km away from the source. For most stations located on the shallow continental shelf, the seismic recordings appear much noisier at all the frequencies compared to stations at deep water. Three general trends are observed for the SNR distribution; First, the SNR ratio increases from lower to higher frequency bands; Second, the ratio decreases with the increasing source-to-receiver distance; And third, the ratio increases from shallow to deep water. We also observe a rough negative relationship of the signal-to-noise ratio with the thickness of the marine sediment. Only 5 inland stations record clear air-gun shot arrivals up to 200 km away from the source. More detailed data quality analysis with more results will also be present.

Extracting time-frequency feature of single-channel vastus medialis EMG signals for knee exercise pattern recognition.

Directory of Open Access Journals (Sweden)

Yi Zhang

Full Text Available The EMG signal indicates the electrophysiological response to daily living of activities, particularly to lower-limb knee exercises. Literature reports have shown numerous benefits of the Wavelet analysis in EMG feature extraction for pattern recognition. However, its application to typical knee exercises when using only a single EMG channel is limited. In this study, three types of knee exercises, i.e., flexion of the leg up (standing, hip extension from a sitting position (sitting and gait (walking are investigated from 14 healthy untrained subjects, while EMG signals from the muscle group of vastus medialis and the goniometer on the knee joint of the detected leg are synchronously monitored and recorded. Four types of lower-limb motions including standing, sitting, stance phase of walking, and swing phase of walking, are segmented. The Wavelet Transform (WT based Singular Value Decomposition (SVD approach is proposed for the classification of four lower-limb motions using a single-channel EMG signal from the muscle group of vastus medialis. Based on lower-limb motions from all subjects, the combination of five-level wavelet decomposition and SVD is used to comprise the feature vector. The Support Vector Machine (SVM is then configured to build a multiple-subject classifier for which the subject independent accuracy will be given across all subjects for the classification of four types of lower-limb motions. In order to effectively indicate the classification performance, EMG features from time-domain (e.g., Mean Absolute Value (MAV, Root-Mean-Square (RMS, integrated EMG (iEMG, Zero Crossing (ZC and frequency-domain (e.g., Mean Frequency (MNF and Median Frequency (MDF are also used to classify lower-limb motions. The five-fold cross validation is performed and it repeats fifty times in order to acquire the robust subject independent accuracy. Results show that the proposed WT-based SVD approach has the classification accuracy of 91.85%±0

A Novel Feature Extraction Approach Using Window Function Capturing and QPSO-SVM for Enhancing Electronic Nose Performance

Directory of Open Access Journals (Sweden)

Xiuzhen Guo

2015-06-01

Full Text Available In this paper, a novel feature extraction approach which can be referred to as moving window function capturing (MWFC has been proposed to analyze signals of an electronic nose (E-nose used for detecting types of infectious pathogens in rat wounds. Meanwhile, a quantum-behaved particle swarm optimization (QPSO algorithm is implemented in conjunction with support vector machine (SVM for realizing a synchronization optimization of the sensor array and SVM model parameters. The results prove the efficacy of the proposed method for E-nose feature extraction, which can lead to a higher classification accuracy rate compared to other established techniques. Meanwhile it is interesting to note that different classification results can be obtained by changing the types, widths or positions of windows. By selecting the optimum window function for the sensor response, the performance of an E-nose can be enhanced.

Advances in biomedical signal and image processing – A systematic review

Directory of Open Access Journals (Sweden)

J. Rajeswari

Full Text Available Biomedical signal and image processing establish a dynamic area of specialization in both academic as well as research aspects of biomedical engineering. The concepts of signal and image processing have been widely used for extracting the physiological information in implementing many clinical procedures for sophisticated medical practices and applications. In this paper, the relationship between electrophysiological signals, i.e., electrocardiogram (ECG, electromyogram (EMG, electroencephalogram (EEG and functional image processing and their derived interactions have been discussed. Examples have been investigated in various case studies such as neurosciences, functional imaging, and cardiovascular system, by using different algorithms and methods. The interaction between the extracted information obtained from multiple signals and modalities seems to be very promising. The advanced algorithms and methods in the area of information retrieval based on time-frequency representation have been investigated. Finally, some examples of algorithms have been discussed in which the electrophysiological signals and functional images have been properly extracted and have a significant impact on various biomedical applications. Keywords: Biomedical signals and images, Processing, Analysis

A Comparative Study of Different EEG Reference Choices for Diagnosing Unipolar Depression.

Science.gov (United States)

Mumtaz, Wajid; Malik, Aamir Saeed

2018-06-02

The choice of an electroencephalogram (EEG) reference has fundamental importance and could be critical during clinical decision-making because an impure EEG reference could falsify the clinical measurements and subsequent inferences. In this research, the suitability of three EEG references was compared while classifying depressed and healthy brains using a machine-learning (ML)-based validation method. In this research, the EEG data of 30 unipolar depressed subjects and 30 age-matched healthy controls were recorded. The EEG data were analyzed in three different EEG references, the link-ear reference (LE), average reference (AR), and reference electrode standardization technique (REST). The EEG-based functional connectivity (FC) was computed. Also, the graph-based measures, such as the distances between nodes, minimum spanning tree, and maximum flow between the nodes for each channel pair, were calculated. An ML scheme provided a mechanism to compare the performances of the extracted features that involved a general framework such as the feature extraction (graph-based theoretic measures), feature selection, classification, and validation. For comparison purposes, the performance metrics such as the classification accuracies, sensitivities, specificities, and F scores were computed. When comparing the three references, the diagnostic accuracy showed better performances during the REST, while the LE and AR showed less discrimination between the two groups. Based on the results, it can be concluded that the choice of appropriate reference is critical during the clinical scenario. The REST reference is recommended for future applications of EEG-based diagnosis of mental illnesses.

Validation of an HPLC method for quantification of total quercetin in Calendula officinalis extracts

International Nuclear Information System (INIS)

Muñoz Muñoz, John Alexander; Morgan Machado, Jorge Enrique; Trujillo González, Mary

2015-01-01

Introduction: calendula officinalis extracts are used as natural raw material in a wide range of pharmaceutical and cosmetic preparations; however, there are no official methods for quality control of these extracts. Objective: to validate an HPLC-based analytical method for quantification total quercetin in glycolic and hydroalcoholic extracts of Calendula officinalis. Methods: to quantify total quercetin content in the matrices, it was necessary to hydrolyze flavonoid glycosides under optimal conditions. The chromatographic separation was performed on a C-18 SiliaChrom 4.6x150 mm 5 µm column, adapted to a SiliaChrom 5 um C-18 4.6x10 mm precolumn, with UV detection at 370 nm. The gradient elution was performed with a mobile phase consisting of methanol (MeOH) and phosphoric acid (H 3 PO 4 ) (0.08 % w/v). The quantification was performed through the external standard method and comparison with quercetin reference standard. Results: the studied method selectivity against extract components and degradation products under acid/basic hydrolysis, oxidation and light exposure conditions showed no signals that interfere with the quercetin quantification. It was statistically proved that the method is linear from 1.0 to 5.0 mg/mL. Intermediate precision expressed as a variation coefficient was 1.8 and 1.74 % and the recovery percentage was 102.15 and 101.32 %, for glycolic and hydroalcoholic extracts, respectively. Conclusions: the suggested methodology meets the quality parameters required for quantifying total quercetin, which makes it a useful tool for quality control of C. officinalis extracts. (author)

Spectral feature extraction of EEG signals and pattern recognition during mental tasks of 2-D cursor movements for BCI using SVM and ANN.

Science.gov (United States)

Bascil, M Serdar; Tesneli, Ahmet Y; Temurtas, Feyzullah

2016-09-01

Brain computer interface (BCI) is a new communication way between man and machine. It identifies mental task patterns stored in electroencephalogram (EEG). So, it extracts brain electrical activities recorded by EEG and transforms them machine control commands. The main goal of BCI is to make available assistive environmental devices for paralyzed people such as computers and makes their life easier. This study deals with feature extraction and mental task pattern recognition on 2-D cursor control from EEG as offline analysis approach. The hemispherical power density changes are computed and compared on alpha-beta frequency bands with only mental imagination of cursor movements. First of all, power spectral density (PSD) features of EEG signals are extracted and high dimensional data reduced by principle component analysis (PCA) and independent component analysis (ICA) which are statistical algorithms. In the last stage, all features are classified with two types of support vector machine (SVM) which are linear and least squares (LS-SVM) and three different artificial neural network (ANN) structures which are learning vector quantization (LVQ), multilayer neural network (MLNN) and probabilistic neural network (PNN) and mental task patterns are successfully identified via k-fold cross validation technique.

Data-driven haemodynamic response function extraction using Fourier-wavelet regularised deconvolution

Directory of Open Access Journals (Sweden)

Roerdink Jos BTM

2008-04-01

Full Text Available Abstract Background We present a simple, data-driven method to extract haemodynamic response functions (HRF from functional magnetic resonance imaging (fMRI time series, based on the Fourier-wavelet regularised deconvolution (ForWaRD technique. HRF data are required for many fMRI applications, such as defining region-specific HRFs, effciently representing a general HRF, or comparing subject-specific HRFs. Results ForWaRD is applied to fMRI time signals, after removing low-frequency trends by a wavelet-based method, and the output of ForWaRD is a time series of volumes, containing the HRF in each voxel. Compared to more complex methods, this extraction algorithm requires few assumptions (separability of signal and noise in the frequency and wavelet domains and the general linear model and it is fast (HRF extraction from a single fMRI data set takes about the same time as spatial resampling. The extraction method is tested on simulated event-related activation signals, contaminated with noise from a time series of real MRI images. An application for HRF data is demonstrated in a simple event-related experiment: data are extracted from a region with significant effects of interest in a first time series. A continuous-time HRF is obtained by fitting a nonlinear function to the discrete HRF coeffcients, and is then used to analyse a later time series. Conclusion With the parameters used in this paper, the extraction method presented here is very robust to changes in signal properties. Comparison of analyses with fitted HRFs and with a canonical HRF shows that a subject-specific, regional HRF significantly improves detection power. Sensitivity and specificity increase not only in the region from which the HRFs are extracted, but also in other regions of interest.

Algorithmic processing of intrinsic signals in affixed transmission speckle analysis (ATSA) (Conference Presentation)

Science.gov (United States)

Ghijsen, Michael T.; Tromberg, Bruce J.

2017-03-01

Affixed Transmission Speckle Analysis (ATSA) is a method recently developed to measure blood flow that is based on laser speckle imaging miniaturized into a clip-on form factor the size of a pulse-oximeter. Measuring at a rate of 250 Hz, ATSA is capable or obtaining the cardiac waveform in blood flow data, referred to as the Speckle-Plethysmogram (SPG). ATSA is also capable of simultaneously measuring the Photoplethysmogram (PPG), a more conventional signal related to light intensity. In this work we present several novel algorithms for extracting physiologically relevant information from the combined SPG-PPG waveform data. First we show that there is a slight time-delay between the SPG and PPG that can be extracted computationally. Second, we present a set of frequency domain algorithms that measure harmonic content on pulse-by-pulse basis for both the SPG and PPG. Finally, we apply these algorithms to data obtained from a set of subjects including healthy controls and individuals with heightened cardiovascular risk. We hypothesize that the time-delay and frequency content are correlated with cardiovascular health; specifically with vascular stiffening.

Methanol Extract of Myelophycus caespitosus Inhibits the ...

African Journals Online (AJOL)

Methanol Extract of Myelophycus caespitosus Inhibits the Inflammatory Response in Lipopolysaccharidestimulated BV2 Microglial Cells by Downregulating NF-kB via Inhibition of the Akt Signaling Pathway.

Signal classification for acoustic neutrino detection

International Nuclear Information System (INIS)

Neff, M.; Anton, G.; Enzenhöfer, A.; Graf, K.; Hößl, J.; Katz, U.; Lahmann, R.; Richardt, C.

2012-01-01

This article focuses on signal classification for deep-sea acoustic neutrino detection. In the deep sea, the background of transient signals is very diverse. Approaches like matched filtering are not sufficient to distinguish between neutrino-like signals and other transient signals with similar signature, which are forming the acoustic background for neutrino detection in the deep-sea environment. A classification system based on machine learning algorithms is analysed with the goal to find a robust and effective way to perform this task. For a well-trained model, a testing error on the level of 1% is achieved for strong classifiers like Random Forest and Boosting Trees using the extracted features of the signal as input and utilising dense clusters of sensors instead of single sensors.

Phase Locking of a 2.7 THz Quantum Cascade Laser to a Microwave Reference

Science.gov (United States)

Khosropanah, P.; Baryshev, A.; Zhang, W.; Jellema, W.; Hovenier, J. N.; Gao, J. R.; Klapwijk, T. M.; Paveliev, D. G.; Williams, B. S.; Hu, Q.;

Medicaid Analytic eXtract (MAX) Chartbooks

Data.gov (United States)

U.S. Department of Health & Human Services — The Medicaid Analytic eXtract Chartbooks are research tools and reference guides on Medicaid enrollees and their Medicaid experience in 2002 and 2004. Developed for...

Universal Reference RNA as a standard for microarray experiments

Directory of Open Access Journals (Sweden)

Fero Michael

2004-03-01

Full Text Available Abstract Background Obtaining reliable and reproducible two-color microarray gene expression data is critically important for understanding the biological significance of perturbations made on a cellular system. Microarray design, RNA preparation and labeling, hybridization conditions and data acquisition and analysis are variables difficult to simultaneously control. A useful tool for monitoring and controlling intra- and inter-experimental variation is Universal Reference RNA (URR, developed with the goal of providing hybridization signal at each microarray probe location (spot. Measuring signal at each spot as the ratio of experimental RNA to reference RNA targets, rather than relying on absolute signal intensity, decreases variability by normalizing signal output in any two-color hybridization experiment. Results Human, mouse and rat URR (UHRR, UMRR and URRR, respectively were prepared from pools of RNA derived from individual cell lines representing different tissues. A variety of microarrays were used to determine percentage of spots hybridizing with URR and producing signal above a user defined threshold (microarray coverage. Microarray coverage was consistently greater than 80% for all arrays tested. We confirmed that individual cell lines contribute their own unique set of genes to URR, arguing for a pool of RNA from several cell lines as a better configuration for URR as opposed to a single cell line source for URR. Microarray coverage comparing two separately prepared batches each of UHRR, UMRR and URRR were highly correlated (Pearson's correlation coefficients of 0.97. Conclusion Results of this study demonstrate that large quantities of pooled RNA from individual cell lines are reproducibly prepared and possess diverse gene representation. This type of reference provides a standard for reducing variation in microarray experiments and allows more reliable comparison of gene expression data within and between experiments and

A Hybrid Approach to Proving Memory Reference Monotonicity

KAUST Repository

Oancea, Cosmin E.

2013-01-01

Array references indexed by non-linear expressions or subscript arrays represent a major obstacle to compiler analysis and to automatic parallelization. Most previous proposed solutions either enhance the static analysis repertoire to recognize more patterns, to infer array-value properties, and to refine the mathematical support, or apply expensive run time analysis of memory reference traces to disambiguate these accesses. This paper presents an automated solution based on static construction of access summaries, in which the reference non-linearity problem can be solved for a large number of reference patterns by extracting arbitrarily-shaped predicates that can (in)validate the reference monotonicity property and thus (dis)prove loop independence. Experiments on six benchmarks show that our general technique for dynamic validation of the monotonicity property can cover a large class of codes, incurs minimal run-time overhead and obtains good speedups. © 2013 Springer-Verlag.

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

Directory of Open Access Journals (Sweden)

Hau-Tieng Wu

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

Preparation and certification of reference materials for the nuclear industry

International Nuclear Information System (INIS)

Wagner, J.F.

1994-01-01

CETAMA (Commission for the Establishment of Analytical Methods) of the Cea group is producing and certifying uranium and plutonium reference materials to meet the requirements of analytical laboratories in the nuclear industry. Reference materials are required at all stages in the fuel cycle: from extraction of uranium, purification, conversion, uranium enrichment, fuel fabrication until reprocessing of spent fuel, management and storage of waste. 3 tabs

Anxiogenic Like activity of Sarcocephalus latifolius Fruit Extract in Mice

Directory of Open Access Journals (Sweden)

David Arome

2014-01-01

Full Text Available The use of pharmacological agents in the treatment of anxiety disorders have fallen out of favour as their unwanted side effects have become evident. The present challenges call for an inward look into harnessing the full potential of medicinal plants that abound around us. The present study evaluates the anxiogenic activity of ethanolic fruit extract of Sarcocephalus latifolius in mice. The prepared extract at 200, 400, and 600 mg/kg as well as 2.5 mg/kg of diazepam, the reference standard was administered orally. The anxiogenic activity of the extract was evaluated using elevated plus maze and open field models. In the elevated plus maze, the extract showed an anxiogenic effect in all the experimental dosage levels by decreasing the time spent and number within the open arms. Animals in the extract and physiological saline groups spent more time in the enclosed arms to avoid the open arms, probably to avoid falling off. The reference standard showed a significant (P

Aliasing-free wideband beamforming using sparse signal representation

NARCIS (Netherlands)

Tang, Z.; Blacquière, G.; Leus, G.

2011-01-01

Sparse signal representation (SSR) is considered to be an appealing alternative to classical beamforming for direction-of-arrival (DOA) estimation. For wideband signals, the SSR-based approach constructs steering matrices, referred to as dictionaries in this paper, corresponding to different

Noise Reduction, Atmospheric Pressure Admittance Estimation and Long-Period Component Extraction in Time-Varying Gravity Signals Using Ensemble Empirical Mode Decomposition

Directory of Open Access Journals (Sweden)

Linsong Wang

2015-01-01

Full Text Available Time-varying gravity signals, with their nonlinear, non-stationary and multi-scale characteristics, record the physical responses of various geodynamic processes and consist of a blend of signals with various periods and amplitudes, corresponding to numerous phenomena. Superconducting gravimeter (SG records are processed in this study using a multi-scale analytical method and corrected for known effects to reduce noise, to study geodynamic phenomena using their gravimetric signatures. Continuous SG (GWR-C032 gravity and barometric data are decomposed into a series of intrinsic mode functions (IMFs using the ensemble empirical mode decomposition (EEMD method, which is proposed to alleviate some unresolved issues (the mode mixing problem and the end effect of the empirical mode decomposition (EMD. Further analysis of the variously scaled signals is based on a dyadic filter bank of the IMFs. The results indicate that removing the high-frequency IMFs can reduce the natural and man-made noise in the data, which are caused by electronic device noise, Earth background noise and the residual effects of pre-processing. The atmospheric admittances based on frequency changes are estimated from the gravity and the atmospheric pressure IMFs in various frequency bands. These time- and frequency-dependent admittance values can be used effectively to improve the atmospheric correction. Using the EEMD method as a filter, the long-period IMFs are extracted from the SG time-varying gravity signals spanning 7 years. The resulting gravity residuals are well correlated with the gravity effect caused by the _ polar motion after correcting for atmospheric effects.

Heartbeat Signal from Facial Video for Biometric Recognition

DEFF Research Database (Denmark)

Haque, Mohammad Ahsanul; Nasrollahi, Kamal; Moeslund, Thomas B.

2015-01-01

Different biometric traits such as face appearance and heartbeat signal from Electrocardiogram (ECG)/Phonocardiogram (PCG) are widely used in the human identity recognition. Recent advances in facial video based measurement of cardio-physiological parameters such as heartbeat rate, respiratory rate......, and blood volume pressure provide the possibility of extracting heartbeat signal from facial video instead of using obtrusive ECG or PCG sensors in the body. This paper proposes the Heartbeat Signal from Facial Video (HSFV) as a new biometric trait for human identity recognition, for the first time...... to the best of our knowledge. Feature extraction from the HSFV is accomplished by employing Radon transform on a waterfall model of the replicated HSFV. The pairwise Minkowski distances are obtained from the Radon image as the features. The authentication is accomplished by a decision tree based supervised...

Processing Electromyographic Signals to Recognize Words

Science.gov (United States)

Jorgensen, C. C.; Lee, D. D.

2009-01-01

A recently invented speech-recognition method applies to words that are articulated by means of the tongue and throat muscles but are otherwise not voiced or, at most, are spoken sotto voce. This method could satisfy a need for speech recognition under circumstances in which normal audible speech is difficult, poses a hazard, is disturbing to listeners, or compromises privacy. The method could also be used to augment traditional speech recognition by providing an additional source of information about articulator activity. The method can be characterized as intermediate between (1) conventional speech recognition through processing of voice sounds and (2) a method, not yet developed, of processing electroencephalographic signals to extract unspoken words directly from thoughts. This method involves computational processing of digitized electromyographic (EMG) signals from muscle innervation acquired by surface electrodes under a subject's chin near the tongue and on the side of the subject s throat near the larynx. After preprocessing, digitization, and feature extraction, EMG signals are processed by a neural-network pattern classifier, implemented in software, that performs the bulk of the recognition task as described.

Serenoa repens extracts promote hair regeneration and repair of hair loss mouse models by activating TGF-β and mitochondrial signaling pathway.

Science.gov (United States)

Zhu, H-L; Gao, Y-H; Yang, J-Q; Li, J-B; Gao, J

2018-06-01

Plenty of plant extracts have been used for treating hair loss. This study aims to investigate the effects of liposterolic extracts of Serenoa repens (LSESr) on hair cell growth and regeneration of hair, and clarify the associated mechanisms. Human keratinocyte cells (HACAT) were cultured, incubated with dihydrotestosterone (DHT) and treated with LSESr. Cell viability was examined by using 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H- tetrazolium bromide (MTT) assay. Hair loss C57BL/6 mouse model was established by inducing with DHT. Hair growth, density, and thickness were evaluated. Back skin samples were collected and stained with hematoxylin and eosin (HE) assay. B-cell lymphoma-2 (Bcl-2), Bcl-2 associated protein X (Bax), cleaved caspase 3 and transforming growth factor β2 (TGF-β2) were examined using Western blot assay. LSESr treatment significantly increased HACAT cell viabilities compared to DHT-only treated cells (p<0.05). LSESr treatment post injection of DHT significantly converted skin color from pink to gray and increased hair density, weight and thickness compared to DHT-only treated mice (p<0.05). LSESr treatment significantly triggered follicle growth and decreased inflammatory response. LSESr treatment significantly decreased TGF-β2 and cleaved caspase 3 expression of hair loss mouse models compared to that of DHT treated mice (p<0.05). LSESr treatment significantly enhanced Bcl-2 expression and reduced Bax expression compared to that of DHT treated mice (p<0.05). Meanwhile, effects of LSESr were substantial even achieving to the potential of finasteride. LSESr promoted the hair regeneration and repair of hair loss mouse models by activating TGF-β signaling and mitochondrial signaling pathway.

Signal processing methods for MFE plasma diagnostics

International Nuclear Information System (INIS)

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

1985-02-01

The application of various signal processing methods to extract energy storage information from plasma diamagnetism sensors occurring during physics experiments on the Tandom Mirror Experiment-Upgrade (TMX-U) is discussed. We show how these processing techniques can be used to decrease the uncertainty in the corresponding sensor measurements. The algorithms suggested are implemented using SIG, an interactive signal processing package developed at LLNL

Selective killing of cancer cells by leaf extract of Ashwagandha: components, activity and pathway analyses.

Science.gov (United States)

Widodo, Nashi; Takagi, Yasuomi; Shrestha, Bhupal G; Ishii, Tetsuro; Kaul, Sunil C; Wadhwa, Renu

2008-04-08

Ashwagandha, also called as "Queen of Ayurveda" and "Indian ginseng", is a commonly used plant in Indian traditional medicine, Ayurveda. Its roots have been used as herb remedy to treat a variety of ailments and to promote general wellness. However, scientific evidence to its effects is limited to only a small number of studies. We had previously identified anti-cancer activity in the leaf extract (i-Extract) of Ashwagandha and demonstrated withanone as a cancer inhibitory factor (i-Factor). In the present study, we fractionated the i-Extract to its components by silica gel column chromatography and subjected them to cell based activity analyses. We found that the cancer inhibitory leaf extract (i-Extract) has, at least, seven components that could cause cancer cell killing; i-Factor showed the highest selectivity for cancer cells and i-Factor rich Ashwagandha leaf powder was non-toxic and anti-tumorigenic in mice assays. We undertook a gene silencing and pathway analysis approach and found that i-Extract and its components kill cancer cells by at least five different pathways, viz. p53 signaling, GM-CFS signaling, death receptor signaling, apoptosis signaling and G2-M DNA damage regulation pathway. p53 signaling was most common. Visual analysis of p53 and mortalin staining pattern further revealed that i-Extract, fraction F1, fraction F4 and i-Factor caused an abrogation of mortalin-p53 interactions and reactivation of p53 function while the fractions F2, F3, F5 work through other mechanisms.

Ginkgo biloba extract mitigates liver fibrosis and apoptosis by regulating p38 MAPK, NF-κB/IκBα, and Bcl-2/Bax signaling

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Wang YY

2015-12-01

Full Text Available Yuanyuan Wang, Rong Wang, Yujie Wang, Ruqin Peng, Yan Wu, Yongfang Yuan Department of Pharmacy, Shanghai 9th People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China Background: Liver fibrosis is the consequence of diverse liver injuries and can eventually develop into liver cirrhosis. Ginkgo biloba extract (GBE is an extract from dried ginkgo leaves that has many pharmacological effects because of its various ingredients and has been shown to be hepatoprotective. Purpose and methods: Aimed to investigate the underlying protective mechanisms of GBE on carbon tetrachloride (CCl4-induced liver fibrosis in rats. Male Sprague Dawley rats were randomly divided into four groups: control group (C, model group (M, low-dose group (L, and high-dose group (H. Liver fibrosis was induced by CCl4 groups M, L, and H: group C was administered saline. In addition, GBE at different doses was used to treat groups L and H. Results: The results of hematoxylin and eosin staining, Masson’s trichrome staining, a liver function index, and a liver fibrosis index showed that GBE application noticeably mitigated fibrosis and improved the function of the liver. The western blotting and immunohistochemistry analyses indicated that GBE reduced liver fibrosis not only by inhibiting p38 MAPK and NF-κBp65 via inhibition of IκBα degradation but also by inhibiting hepatocyte apoptosis via downregulation of Bax, upregulation of Bcl-2, and subsequent inhibition of caspase-3 activation. Inflammation-associated factors and hepatic stellate cell (HSC-activation markers further demonstrated that GBE could effectively inhibit HSC activation and inflammation as a result of its regulation of p38 MAPK and nuclear factor-kappa B/IκBα signaling. Conclusion: Our findings indicated a novel role for GBE in the treatment of liver fibrosis. The potential mechanisms may be associated with the following signaling pathways: 1 the p38 MAPK

Generation and coherent detection of QPSK signal using a novel method of digital signal processing

Science.gov (United States)

Zhao, Yuan; Hu, Bingliang; He, Zhen-An; Xie, Wenjia; Gao, Xiaohui

2018-02-01

We demonstrate an optical quadrature phase-shift keying (QPSK) signal transmitter and an optical receiver for demodulating optical QPSK signal with homodyne detection and digital signal processing (DSP). DSP on the homodyne detection scheme is employed without locking the phase of the local oscillator (LO). In this paper, we present an extracting one-dimensional array of down-sampling method for reducing unwanted samples of constellation diagram measurement. Such a novel scheme embodies the following major advantages over the other conventional optical QPSK signal detection methods. First, this homodyne detection scheme does not need strict requirement on LO in comparison with linear optical sampling, such as having a flat spectral density and phase over the spectral support of the source under test. Second, the LabVIEW software is directly used for recovering the QPSK signal constellation without employing complex DSP circuit. Third, this scheme is applicable to multilevel modulation formats such as M-ary PSK and quadrature amplitude modulation (QAM) or higher speed signals by making minor changes.

Looking at 3,000,000 References Without Growing Grey Hair

Science.gov (United States)

Demleitner, M.; Accomazzi, A.; Eichhorn, G.; Grant, C. S.; Kurtz, M. J.; Murray, S. S.

1999-12-01

The article service of the Astrophysics Data System (ADS, http://adswww.harvard.edu) currently holds about 500,000 pages scanned from astronomical journals and conference proceedings. This data set not only facilitates an easy and convenient access to the majority of the astronomical literature from anywhere on the Internet but also allows highly automatized extraction of the information contained in the articles. As first steps towards processing and indexing the full texts of the articles, the ADS has been extracting abstracts and references from the bitmap images of the articles since May 1999. In this poster we describe the procedures and strategies to (a) automatically identify the regions within a paper containing the abstract or the references, (b) spot and correct errors in the data base or the identification of the regions, (c) resolve references obtained by optical character recognition (OCR) with its inherent uncertainties to parsed references (i.e., bibcodes) and (d) incorporate the data collected in this way into the ADS abstract service. We also give an overview of the extent of additional bibliographical material from this source. We estimate that by January 2000, these procedures will have yielded about 14,000 abstracts and 1,000,000 citation pairs (out of a total of 3,000,000 references) not previously present in the ADS.

Extracting volatility signal using maximum a posteriori estimation

Science.gov (United States)

Neto, David

2016-11-01

This paper outlines a methodology to estimate a denoised volatility signal for foreign exchange rates using a hidden Markov model (HMM). For this purpose a maximum a posteriori (MAP) estimation is performed. A double exponential prior is used for the state variable (the log-volatility) in order to allow sharp jumps in realizations and then log-returns marginal distributions with heavy tails. We consider two routes to choose the regularization and we compare our MAP estimate to realized volatility measure for three exchange rates.

Selection of the signal synchronization method in software GPS receivers

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Vlada S. Sokolović

2011-04-01

Full Text Available Introduction This paper presents a critical analysis of the signal processing flow carried out in a software GPS receiver and a critical comparison of different architectures for signal processing within the GPS receiver. A model of software receivers is shown. Based on the displayed model, a receiver has been realized in the MATLAB software package, in which the simulations of signal processing were carried out. The aim of this paper is to demonstrate the advantages and disadvantages of different methods of the synchronization of signals in the receiver, and to propose a solution acceptable for possible implementation. The signal processing flow was observed from the input circuit to the extraction of the bits of the navigation message. The entire signal processing was performed on the L1 signal and the data collected by the input circuit SE4110. A radio signal from the satellite was accepted with the input circuit, filtered and translated into a digital form. The input circuit ends with the hardware of the receiver. A digital signal from the input circuit is brought into the PC Pentium 4 (AMD 3000 + where the receiver is realized in Matlab. Model of software GPS receiver The first level of processing is signal acquisition. Signal acquisition was realized using the cyclic convolution. The acquisition process was carried out by measuring signals from satellites, and these parameters are passed to the next level of processing. The next level was done by monitoring the synchronization signal and extracting the navigation message bits. On the basis of the detection of the navigation message the receiver calculates the position of a satellite and then, based on the position of the satellite, its own position. Tracking of GPS signal synchronization In order to select the most acceptable method of signal synchronization in the receiver, different methods of signal synchronization are compared. The early-late-DLL (Delay Lock Loop, TDL (Tau Dither Loop

Applying advanced digital signal processing techniques in industrial radioisotopes applications

International Nuclear Information System (INIS)

Mahmoud, H.K.A.E.

2012-01-01

Radioisotopes can be used to obtain signals or images in order to recognize the information inside the industrial systems. The main problems of using these techniques are the difficulty of identification of the obtained signals or images and the requirement of skilled experts for the interpretation process of the output data of these applications. Now, the interpretation of the output data from these applications is performed mainly manually, depending heavily on the skills and the experience of trained operators. This process is time consuming and the results typically suffer from inconsistency and errors. The objective of the thesis is to apply the advanced digital signal processing techniques for improving the treatment and the interpretation of the output data from the different Industrial Radioisotopes Applications (IRA). This thesis focuses on two IRA; the Residence Time Distribution (RTD) measurement and the defect inspection of welded pipes using a gamma source (gamma radiography). In RTD measurement application, this thesis presents methods for signal pre-processing and modeling of the RTD signals. Simulation results have been presented for two case studies. The first case study is a laboratory experiment for measuring the RTD in a water flow rig. The second case study is an experiment for measuring the RTD in a phosphate production unit. The thesis proposes an approach for RTD signal identification in the presence of noise. In this approach, after signal processing, the Mel Frequency Cepstral Coefficients (MFCCs) and polynomial coefficients are extracted from the processed signal or from one of its transforms. The Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), and Discrete Sine Transform (DST) have been tested and compared for efficient feature extraction. Neural networks have been used for matching of the extracted features. Furthermore, the Power Density Spectrum (PDS) of the RTD signal has been also used instead of the discrete

Boehmenan, a lignan from Hibiscus ficulneus, showed Wnt signal inhibitory activity.

Science.gov (United States)

Shono, Takumi; Ishikawa, Naoki; Toume, Kazufumi; Arai, Midori A; Ahmed, Firoj; Sadhu, Samir K; Ishibashi, Masami

2015-07-15

The Wnt signal pathway modulates numerous biological processes, and its aberrant activation is related to various diseases. Therefore, inhibition of the Wnt signal may provide an effective (or efficient) strategy for these diseases. Cell-based luciferase assay targeting the Wnt signal (TOP assay) revealed that Hibiscus ficulneus extract inhibited the Wnt signal. The activity-guided isolation of the MeOH extract of H. ficulneus stems yielded four known (1-4) lignans along with myriceric acid (5). Compounds 1-4 potently inhibited the Wnt signal with TOPflash IC50 values of 1.0, 4.5, 6.3, and 1.9 μM, respectively. Compound 1 exhibited cytotoxicity against both Wnt-dependent (HCT116) and Wnt-independent (RKO) cells. Western blot analysis showed that 1 decreased the expression of full, cytosolic and nuclear β-catenin along with c-myc in STF/293 cells. Our results suggested that 1 may have inhibited the Wnt signal by decreasing β-catenin levels. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multipath ultrasonic gas flow-meter based on multiple reference waves.

Science.gov (United States)

Zhou, Hongliang; Ji, Tao; Wang, Ruichen; Ge, Xiaocheng; Tang, Xiaoyu; Tang, Shizhen

2018-01-01

Several technologies can be used in ultrasonic gas flow-meters, such as transit-time, Doppler, cross-correlation and etc. In applications, the approach based on measuring transit-time has demonstrated its advantages and become more popular. Among those techniques which can be applied to determine time-of-flight (TOF) of ultrasonic waves, including threshold detection, cross correlation algorithm and other digital signal processing algorithms, cross correlation algorithm has more advantages when the received ultrasonic signal is severely disturbed by the noise. However, the reference wave for cross correlation computation has great influence on the precise measurement of TOF. In the applications of the multipath flow-meters, selection of the reference wave becomes even more complicated. Based on the analysis of the impact factors that will introduce noise and waveform distortion of ultrasonic waves, an averaging method is proposed to determine the reference wave in this paper. In the multipath ultrasonic gas flow-meter, the analysis of each path of ultrasound needs its own reference wave. In case study, a six-path ultrasonic gas flow-meter has been designed and tested with air flow through the pipeline. The results demonstrate that the flow rate accuracy and the repeatability of the TOF are significantly improved by using averaging reference wave, compared with that using random reference wave. Copyright © 2017 Elsevier B.V. All rights reserved.

Performance of unbalanced QPSK in the presence of noisy reference and crosstalk

Science.gov (United States)

Divsalar, D.; Yuen, J. H.

1979-01-01

The problem of transmitting two telemetry data streams having different rates and different powers using unbalanced quadriphase shift keying (UQPSK) signaling is considered. It is noted that the presence of a noisy carrier phase reference causes a degradation in detection performance in coherent communications systems and that imperfect carrier synchronization not only attenuates the main demodulated signal voltage in UQPSK but also produces interchannel interference (crosstalk) which degrades the performance still further. Exact analytical expressions for symbol error probability of UQPSK in the presence of noise phase reference are derived.

Estimating Transmitted-Signal Phase Variations for Uplink Array Antennas

Science.gov (United States)

Paal, Leslie; Mukai, Ryan; Vilntrotter, Victor; Cornish, Timothy; Lee, Dennis

2009-01-01

A method of estimating phase drifts of microwave signals distributed to, and transmitted by, antennas in an array involves the use of the signals themselves as phase references. The method was conceived as part of the solution of the problem of maintaining precise phase calibration required for proper operation of an array of Deep Space Network (DSN) antennas on Earth used for communicating with distant spacecraft at frequencies between 7 and 8 GHz. The method could also be applied to purely terrestrial phased-array radar and other radio antenna array systems. In the DSN application, the electrical lengths (effective signal-propagation path lengths) of the various branches of the system for distributing the transmitted signals to the antennas are not precisely known, and they vary with time. The variations are attributable mostly to thermal expansion and contraction of fiber-optic and electrical signal cables and to a variety of causes associated with aging of signal-handling components. The variations are large enough to introduce large phase drifts at the signal frequency. It is necessary to measure and correct for these phase drifts in order to maintain phase calibration of the antennas. A prior method of measuring phase drifts involves the use of reference-frequency signals separate from the transmitted signals. A major impediment to accurate measurement of phase drifts over time by the prior method is the fact that although DSN reference-frequency sources separate from the transmitting signal sources are stable and accurate enough for most DSN purposes, they are not stable enough for use in maintaining phase calibrations, as required, to within a few degrees over times as long as days or possibly even weeks. By eliminating reliance on the reference-frequency subsystem, the present method overcomes this impediment. In a DSN array to which the present method applies (see figure), the microwave signals to be transmitted are generated by exciters in a signal

Sub-Audible Speech Recognition Based upon Electromyographic Signals

Science.gov (United States)

Jorgensen, Charles C. (Inventor); Lee, Diana D. (Inventor); Agabon, Shane T. (Inventor)

2012-01-01

Method and system for processing and identifying a sub-audible signal formed by a source of sub-audible sounds. Sequences of samples of sub-audible sound patterns ("SASPs") for known words/phrases in a selected database are received for overlapping time intervals, and Signal Processing Transforms ("SPTs") are formed for each sample, as part of a matrix of entry values. The matrix is decomposed into contiguous, non-overlapping two-dimensional cells of entries, and neural net analysis is applied to estimate reference sets of weight coefficients that provide sums with optimal matches to reference sets of values. The reference sets of weight coefficients are used to determine a correspondence between a new (unknown) word/phrase and a word/phrase in the database.

A Standardized Chemically Modified Curcuma longa Extract Modulates IRAK-MAPK Signaling in Inflammation and Potentiates Cytotoxicity

Directory of Open Access Journals (Sweden)

Minakshi Rana

2016-07-01

Full Text Available The TLR/IL-1R pathway is a critical signaling module that is misregulated in pathologies like inflammation and cancer. Extracts from turmeric (Curcuma longa L. enriched in curcumin and carbonyls like turmerones have been shown to exert potent anti-inflammatory effects. The present study evaluated the anti-inflammatory activity, cytotoxic effect and the underlying mechanism of a novel chemically modified, non-carbonyl compound enriched Curcuma longa L. (C. longa extract (CMCE. CMCE (1 or 10 µg/mL; 14 h significantly decreased LPS (50-100 ng/mL induced TNF-α and IL-1β production in THP-1 cells, human, and mouse whole blood as measured by ELISA. LPS-induced IRAK1, MAPK activation, TLR4 expression, TLR4-MyD88 interaction and IκBα degradation were significantly reduced in CMCE pre-treated THP-1 cells as assessed by Western blotting. CMCE (30, 100 and 300 mg/kg; 10 days p.o. pre-treated and LPS (10 mg/kg challenged Swiss mice exhibited attenuated plasma TNF-α, IL-1β, nitrite, aortic iNOS expression and vascular dysfunction. In a PI permeability assay, cell lines derived from acute myeloid leukemia were most sensitive to the cytotoxic effects of CMCE. Analysis of Sub-G1 phase, Annexin V-PI positivity, loss of mitochondrial membrane potential, increased caspase-3 and PARP-1 activation confirmed CMCE induced apoptosis in HL-60 cells. IRAK inhibition also sensitized HL-60 cells to CMCE induced cytotoxicity. The present study defines the mechanism underlying the action of CMCE and suggests a therapeutic potential for its use in sepsis and leukemia.

Exploiting Sequential Injection on-line Solvent Extraction/Back Extraction with Detection by ETAAS or ICPMS

DEFF Research Database (Denmark)

Wang, Jianhua; Hansen, Elo Harald

presents an on-line SI-solvent extraction/back extraction procedure used in connection with detection by either ETAAS or ICPMS. Incorporating two newly designed dual-conical gravitational phase separators, its performance is demonstrated for the determination of various metals in reference materials.......Electrothermal atomic absorption spectrometry (ETAAS) and inductively coupled plasma mass spectrometry (ICPMS) are highly sensitive techniques for trace metal analyses. Nevertheless, separation/preconcentration procedures are often called for in order to overcome their inherent low matrix...... tolerances. With detection by ETAAS, separation/preconcentration by solvent extraction has enjoyed much use. However, this approach is not necessarily the optimal one since introduction of organic eluates directly into the graphite tube might lead to deteriorated reproducibility and lower sensitivity...

Feature Extraction Using Discrete Wavelet Transform for Gear Fault Diagnosis of Wind Turbine Gearbox

DEFF Research Database (Denmark)

Bajric, Rusmir; Zuber, Ninoslav; Skrimpas, Georgios Alexandros

2016-01-01

, the vibration signals are decomposed into a series of subbands signals with the use of amultiresolution analytical property of the discrete wavelet transform.Then, 22 condition indicators are extracted fromthe TSA signal, residual signal, and difference signal.Through the case study analysis, a new approach...

ANTIOXIDANT ACTIVITY, TOTAL PHENOLIC AND FLAVONOID CONTENT OF MORINDA CITRIFOLIA FRUIT EXTRACTS FROM VARIOUS EXTRACTION PROCESSES

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PRAVEEN K. RAMAMOORTHY

2007-04-01

Full Text Available Soxhlet, Ultrasonic extract of Morinda citrifolia L. fruit and four extracts from high pressure extraction at 10 MPa using ethanol, ethyl acetate as solvent and dried by vacuum oven and spray dryer were analyzed for their antioxidant activity by peroxide value method and diphenylpicrylhydrazyl radical scavenging method. The five extracts along with the reference samples, butylated hydroxyl toluene and tannic acid were further analyzed to determine their total phenolic content by Folin-Ciocalteau method and total flavonoid content by Dowd method. The M. citrifolia extract by high pressure extraction with ethyl acetate as solvent and spray dried was found to exhibit highest antioxidant activity and total flavonoid content. High total phenolic content was determined in the high pressure extract using ethyl acetate as solvent and vacuum dried. It was interesting to note that ultrasonic extract exhibited significant antioxidant activity, total phenolic and flavonoid content. High pressure extracted M. citrifolia in ethanol was found to express lesser values comparatively. The significant difference in activity among the high pressure extracts was found to be due to the polarity of the solvents used for extraction as M. citrifolia fruit contains relatively larger quantity of non-polar antioxidant compounds. It was also found that the drying methods had significant impact on the antioxidant activity, total phenolic and flavonoid content of the extracts.

Design and implementation of a multiband digital filter using FPGA to extract the ECG signal in the presence of different interference signals.

Science.gov (United States)

Aboutabikh, Kamal; Aboukerdah, Nader

2015-07-01

In this paper, we propose a practical way to synthesize and filter an ECG signal in the presence of four types of interference signals: (1) those arising from power networks with a fundamental frequency of 50Hz, (2) those arising from respiration, having a frequency range from 0.05 to 0.5Hz, (3) muscle signals with a frequency of 25Hz, and (4) white noise present within the ECG signal band. This was done by implementing a multiband digital filter (seven bands) of type FIR Multiband Least Squares using a digital programmable device (Cyclone II EP2C70F896C6 FPGA, Altera), which was placed on an education and development board (DE2-70, Terasic). This filter was designed using the VHDL language in the Quartus II 9.1 design environment. The proposed method depends on Direct Digital Frequency Synthesizers (DDFS) designed to synthesize the ECG signal and various interference signals. So that the synthetic ECG specifications would be closer to actual ECG signals after filtering, we designed in a single multiband digital filter instead of using three separate digital filters LPF, HPF, BSF. Thus all interference signals were removed with a single digital filter. The multiband digital filter results were studied using a digital oscilloscope to characterize input and output signals in the presence of differing sinusoidal interference signals and white noise. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Antidepressant Effect of Angelica sinensis Extracts on Chronic Unpredictable Mild Stress-Induced Depression Is Mediated via the Upregulation of the BDNF Signaling Pathway in Rats

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Jun Shen

2016-01-01

Full Text Available Angelica sinensis (AS, a traditional Chinese herbal medicine, has pharmaceutical effects on menstrual illness, cerebrovascular diseases, cardiovascular diseases, and cognitive impairments. However, until recently, few studies had explored its antidepressant effect. The current study attempts to investigate the effect of AS extracts on chronic unpredictable mild stress- (CUMS- induced depression in rats. Male SD rats were exposed to a CUMS-inducing procedure for 5 weeks, resulting in rodent depressive behaviors that included reduced sucrose consumption and lessened sucrose preference ratios in sucrose preference test, prolonged immobility times and decreased struggling time in force swim test, and decreased locomotor activity in open field test. Moreover, the expression of brain derived neurotrophic factor (BDNF and the phosphorylation of cAMP-response element binding protein (CREB and extracellular signal-regulated protein kinase (ERK 1/2 were markedly decreased in the hippocampus in depressed rats. However, chronically treating the depressed rats with AS (1 g/kg normalized their depression-related behaviors and molecular profiles. In conclusion, in the present study, we show that AS extracts exerted antidepressant effects that were mediated by the BDNF signaling pathway: in AS-treated depressed rats, the expression of the BDNF protein and the phosphorylation of its downstream targets (ERK 1/2, CREB were upregulated in the hippocampus.

Mitigation of the voltage fluctuations using an efficient disturbance extraction technique

Energy Technology Data Exchange (ETDEWEB)

Elnady, Amr; Salama, M.M.A. [University of Waterloo, Electrical and Computer Engineering, 200 University Ave. West, Waterloo, Ont. (Canada N2L3G1)

2007-03-15

This paper introduces an efficient technique for extracting the disturbance signal of the voltage flicker. The proposed technique depends on the supervised state estimation that is controlled by the Widrow-Hoff delta rule. The extracted disturbance signal is employed for mitigating the cyclic voltage flicker by using series and parallel mitigating devices. The speed and accuracy of the proposed technique are verified by simulation results with EMTDC/PSCAD. In addition, experimental results are presented to prove the validity of the proposed algorithm. (author)

A novel approach for SEMG signal classification with adaptive local binary patterns.

Science.gov (United States)

Ertuğrul, Ömer Faruk; Kaya, Yılmaz; Tekin, Ramazan

2016-07-01

Feature extraction plays a major role in the pattern recognition process, and this paper presents a novel feature extraction approach, adaptive local binary pattern (aLBP). aLBP is built on the local binary pattern (LBP), which is an image processing method, and one-dimensional local binary pattern (1D-LBP). In LBP, each pixel is compared with its neighbors. Similarly, in 1D-LBP, each data in the raw is judged against its neighbors. 1D-LBP extracts feature based on local changes in the signal. Therefore, it has high a potential to be employed in medical purposes. Since, each action or abnormality, which is recorded in SEMG signals, has its own pattern, and via the 1D-LBP these (hidden) patterns may be detected. But, the positions of the neighbors in 1D-LBP are constant depending on the position of the data in the raw. Also, both LBP and 1D-LBP are very sensitive to noise. Therefore, its capacity in detecting hidden patterns is limited. To overcome these drawbacks, aLBP was proposed. In aLBP, the positions of the neighbors and their values can be assigned adaptively via the down-sampling and the smoothing coefficients. Therefore, the potential to detect (hidden) patterns, which may express an illness or an action, is really increased. To validate the proposed feature extraction approach, two different datasets were employed. Achieved accuracies by the proposed approach were higher than obtained results by employed popular feature extraction approaches and the reported results in the literature. Obtained accuracy results were brought out that the proposed method can be employed to investigate SEMG signals. In summary, this work attempts to develop an adaptive feature extraction scheme that can be utilized for extracting features from local changes in different categories of time-varying signals.

Automatic modulation recognition of communication signals

CERN Document Server

Azzouz, Elsayed Elsayed

1996-01-01

Automatic modulation recognition is a rapidly evolving area of signal analysis. In recent years, interest from the academic and military research institutes has focused around the research and development of modulation recognition algorithms. Any communication intelligence (COMINT) system comprises three main blocks: receiver front-end, modulation recogniser and output stage. Considerable work has been done in the area of receiver front-ends. The work at the output stage is concerned with information extraction, recording and exploitation and begins with signal demodulation, that requires accurate knowledge about the signal modulation type. There are, however, two main reasons for knowing the current modulation type of a signal; to preserve the signal information content and to decide upon the suitable counter action, such as jamming. Automatic Modulation Recognition of Communications Signals describes in depth this modulation recognition process. Drawing on several years of research, the authors provide a cr...

Radar signal processing and its applications

CERN Document Server

Hummel, Robert; Stoica, Petre; Zelnio, Edmund

2003-01-01

Radar Signal Processing and Its Applications brings together in one place important contributions and up-to-date research results in this fast-moving area. In twelve selected chapters, it describes the latest advances in architectures, design methods, and applications of radar signal processing. The contributors to this work were selected from the leading researchers and practitioners in the field. This work, originally published as Volume 14, Numbers 1-3 of the journal, Multidimensional Systems and Signal Processing, will be valuable to anyone working or researching in the field of radar signal processing. It serves as an excellent reference, providing insight into some of the most challenging issues being examined today.

Antidiuretic Activity of the Methanol Extract of Aporusa lindleyana ...

African Journals Online (AJOL)

Methods: Three doses (500, 1000 and 1500 mg/kg) of the methanol extract (ME) of Aporusa lindleyana (Leaf and bark in 5:1 ratio) were orally administered to female, adult Sprague Dawley rats. Furosemide, vasopressin (antidiuretic hormone) and distilled water were used as diuretic reference, antidiuretic reference and ...

Three-Dimensional Imaging by Self-Reference Single-Channel Digital Incoherent Holography

Science.gov (United States)

Rosen, Joseph; Kelner, Roy

2016-01-01

Digital holography offers a reliable and fast method to image a three-dimensional scene from a single perspective. This article reviews recent developments of self-reference single-channel incoherent hologram recorders. Hologram recorders in which both interfering beams, commonly referred to as the signal and the reference beams, originate from the same observed objects are considered as self-reference systems. Moreover, the hologram recorders reviewed herein are configured in a setup of a single channel interferometer. This unique configuration is achieved through the use of one or more spatial light modulators. PMID:28757811

Signal processing for radiation detectors

CERN Document Server

Nakhostin, Mohammad

2018-01-01

This book provides a clear understanding of the principles of signal processing of radiation detectors. It puts great emphasis on the characteristics of pulses from various types of detectors and offers a full overview on the basic concepts required to understand detector signal processing systems and pulse processing techniques. Signal Processing for Radiation Detectors covers all of the important aspects of signal processing, including energy spectroscopy, timing measurements, position-sensing, pulse-shape discrimination, and radiation intensity measurement. The book encompasses a wide range of applications so that readers from different disciplines can benefit from all of the information. In addition, this resource: * Describes both analog and digital techniques of signal processing * Presents a complete compilation of digital pulse processing algorithms * Extrapolates content from more than 700 references covering classic papers as well as those of today * Demonstrates concepts with more than 340 origin...

Adaptive DCTNet for Audio Signal Classification

OpenAIRE

Xian, Yin; Pu, Yunchen; Gan, Zhe; Lu, Liang; Thompson, Andrew

2016-01-01

In this paper, we investigate DCTNet for audio signal classification. Its output feature is related to Cohen's class of time-frequency distributions. We introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature extraction. The A-DCTNet applies the idea of constant-Q transform, with its center frequencies of filterbanks geometrically spaced. The A-DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to h...

An Improved Second-Order Generalized Integrator Based Quadrature Signal Generator

DEFF Research Database (Denmark)

Xin, Zhen; Wang, Xiongfei; Qin, Zian

2016-01-01

The second-order generalized integrator based quadrature signal generator (SOGI-QSG) is able to produce in-quadrature signals for many applications, such as frequency estimation, grid synchronization, and harmonic extraction. However, the SOGI-QSG is sensitive to input dc and harmonic components...

Selection of Mother Wavelet Functions for Multi-Channel EEG Signal Analysis during a Working Memory Task

Directory of Open Access Journals (Sweden)

Noor Kamal Al-Qazzaz

2015-11-01

Full Text Available We performed a comparative study to select the efficient mother wavelet (MWT basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM task recorded through electro-encephalography (EEG. Nineteen EEG electrodes were placed on the scalp following the 10–20 system. These electrodes were then grouped into five recording regions corresponding to the scalp area of the cerebral cortex. Sixty-second WM task data were recorded from ten control subjects. Forty-five MWT basis functions from orthogonal families were investigated. These functions included Daubechies (db1–db20, Symlets (sym1–sym20, and Coiflets (coif1–coif5. Using ANOVA, we determined the MWT basis functions with the most significant differences in the ability of the five scalp regions to maximize their cross-correlation with the EEG signals. The best results were obtained using “sym9” across the five scalp regions. Therefore, the most compatible MWT with the EEG signals should be selected to achieve wavelet denoising, decomposition, reconstruction, and sub-band feature extraction. This study provides a reference of the selection of efficient MWT basis functions.

Generating Human-Like Velocity-Adapted Jumping Gait from sEMG Signals for Bionic Leg’s Control

Directory of Open Access Journals (Sweden)

Weiwei Yu

2017-01-01

Full Text Available In the case of dynamic motion such as jumping, an important fact in sEMG (surface Electromyogram signal based control on exoskeletons, myoelectric prostheses, and rehabilitation gait is that multichannel sEMG signals contain mass data and vary greatly with time, which makes it difficult to generate compliant gait. Inspired by the fact that muscle synergies leading to dimensionality reduction may simplify motor control and learning, this paper proposes a new approach to generate flexible gait based on muscle synergies extracted from sEMG signal. Two questions were discussed and solved, the first one concerning whether the same set of muscle synergies can explain the different phases of hopping movement with various velocities. The second one is about how to generate self-adapted gait with muscle synergies while alleviating model sensitivity to sEMG transient changes. From the experimental results, the proposed method shows good performance both in accuracy and in robustness for producing velocity-adapted vertical jumping gait. The method discussed in this paper provides a valuable reference for the sEMG-based control of bionic robot leg to generate human-like dynamic gait.

In vitro time kill assessment of crude methanol extract of ...

African Journals Online (AJOL)

The in vitro antibacterial activities and time kill regimes of crude methanol extract of Helichrysum pedunculatum was assessed using standard microbiological procedures. The experiment was conducted against a panel of bacterial species made up of clinical, environmental and reference strains. The extract was active ...

Handbook of Signal Processing in Acoustics

CERN Document Server

Havelock, David; Vorländer, Michael

2009-01-01

The Handbook of Signal Processing in Acoustics presents signal processing as it is practiced in the field of acoustics. The Handbook is organized by areas of acoustics, with recognized leaders coordinating the self-contained chapters of each section. It brings together a wide range of perspectives from over 100 authors to reveal the interdisciplinary nature of signal processing in acoustics. Success in acoustic applications often requires juggling both the acoustic and the signal processing parameters of the problem. This handbook brings the key issues from both into perspective and is complementary to other reference material on the two subjects. It is a unique resource for experts and practitioners alike to find new ideas and techniques within the diversity of signal processing in acoustics.

Engagement Assessment Using EEG Signals

Science.gov (United States)

Li, Feng; Li, Jiang; McKenzie, Frederic; Zhang, Guangfan; Wang, Wei; Pepe, Aaron; Xu, Roger; Schnell, Thomas; Anderson, Nick; Heitkamp, Dean

2012-01-01

In this paper, we present methods to analyze and improve an EEG-based engagement assessment approach, consisting of data preprocessing, feature extraction and engagement state classification. During data preprocessing, spikes, baseline drift and saturation caused by recording devices in EEG signals are identified and eliminated, and a wavelet based method is utilized to remove ocular and muscular artifacts in the EEG recordings. In feature extraction, power spectrum densities with 1 Hz bin are calculated as features, and these features are analyzed using the Fisher score and the one way ANOVA method. In the classification step, a committee classifier is trained based on the extracted features to assess engagement status. Finally, experiment results showed that there exist significant differences in the extracted features among different subjects, and we have implemented a feature normalization procedure to mitigate the differences and significantly improved the engagement assessment performance.

Signal shape registration in the JINR synchrophasotron slowly extracted beam parameter control system

International Nuclear Information System (INIS)

Volkov, V.I.; Kulikov, I.I.; Romanov, S.V.

1982-01-01

Signal shape registration in the JINR synchrophasotron slowly estracted beam parameter control system on-line with the ES-1010 computer is described. 32 input signals can be connected to the registrator. The maximum measurement rate of signal shape registration is about 38 kHz. The registrator consists of 32-channel analog multiplexer, 10-bit analog-to-digital converter, 1024-word buffer memory and control circuits. For information representation the colour TV monitor is used

Fast digitizing and digital signal processing of detector signals

International Nuclear Information System (INIS)

Hannaske, Roland

2008-01-01

A fast-digitizer data acquisition system recently installed at the neutron time-of-flight experiment nELBE, which is located at the superconducting electron accelerator ELBE of Forschungszentrum Dresden-Rossendorf, is tested with two different detector types. Preamplifier signals from a high-purity germanium detector are digitized, stored and finally processed. For a precise determination of the energy of the detected radiation, the moving-window deconvolution algorithm is used to compensate the ballistic deficit and different shaping algorithms are applied. The energy resolution is determined in an experiment with γ-rays from a 22 Na source and is compared to the energy resolution achieved with analogously processed signals. On the other hand, signals from the photomultipliers of barium fluoride and plastic scintillation detectors are digitized. These signals have risetimes of a few nanoseconds only. The moment of interaction of the radiation with the detector is determined by methods of digital signal processing. Therefore, different timing algorithms are implemented and tested with data from an experiment at nELBE. The time resolutions achieved with these algorithms are compared to each other as well as to reference values coming from analog signal processing. In addition to these experiments, some properties of the digitizing hardware are measured and a program for the analysis of stored, digitized data is developed. The analysis of the signals shows that the energy resolution achieved with the 10-bit digitizer system used here is not competitive to a 14-bit peak-sensing ADC, although the ballistic deficit can be fully corrected. However, digital methods give better result in sub-ns timing than analog signal processing. (orig.)

Optimization of microwave-assisted extraction of hydrocarbons in marine sediments: comparison with the Soxhlet extraction method.

Science.gov (United States)

Vázquez Blanco, E; López Mahía, P; Muniategui Lorenzo, S; Prada Rodríguez, D; Fernández Fernández, E

2000-02-01

Microwave energy was applied to extract polycyclic aromatic hydrocarbons (PAHs) and linear aliphatic hydrocarbons (LAHs) from marine sediments. The influence of experimental conditions, such as different extracting solvents and mixtures, microwave power, irradiation time and number of samples extracted per run has been tested using real marine sediment samples; volume of the solvent, sample quantity and matrix effects were also evaluated. The yield of extracted compounds obtained by microwave irradiation was compared with that obtained using the traditional Soxhlet extraction. The best results were achieved with a mixture of acetone and hexane (1:1), and recoveries ranged from 92 to 106%. The extraction time is dependent on the irradiation power and the number of samples extracted per run, so when the irradiation power was set to 500 W, the extraction times varied from 6 min for 1 sample to 18 min for 8 samples. Analytical determinations were carried out by high-performance liquid chromatography (HPLC) with an ultraviolet-visible photodiode-array detector for PAHs and gas chromatography (GC) using a FID detector for LAHs. To test the accuracy of the microwave-assisted extraction (MAE) technique, optimized methodology was applied to the analysis of standard reference material (SRM 1941), obtaining acceptable results.

An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification.

Science.gov (United States)

Li, Fangmin; Yang, Chao; Xia, Yuqing; Ma, Xiaolin; Zhang, Tao; Zhou, Zhou

2017-11-29

In this paper, we propose the multiwindow Adaptive S-method (AS-method) distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM) trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference.

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

Science.gov (United States)

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

2007-10-01

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

Exploiting sequential injection on-line solvent extraction/back extraction with detection by ETAAS and ICPMS

DEFF Research Database (Denmark)

Wang, Jianhua; Hansen, Elo Harald

presents an on-line SI-solvent extraction/back extraction procedure used in connection with detection by either ETAAS or ICPMS. Incorporating two newly designed dual-conical gravitational phase separators, its performance is demonstrated for the determination of various metals in reference materials.......Electrothermal atomic absorption spectrometry (ETAAS) and inductively coupled plasma mass spectrometry (ICPMS) are highly sensitive techniques for trace metal analyses. Nevertheless, separation/preconcentration procedures are often called for in order to overcome their inherent low matrix tolerance....... With detection by ETAAS, separation/preconcentration by solvent extraction has enjoyed much use. However, this approach is not necessarily the optimal one since introduction of organic eluates directly into the graphite tube might lead to deteriorated reproducibility and lower sensitivity. And for ICPMS...

Characterization of EEG Signals Using Wavelet Packet and Fuzzy Entropy in Motor Imagination Tasks

Directory of Open Access Journals (Sweden)

Boris Alexander Medina

2017-05-01

Full Text Available Context:  Clinical rhythm analysis on advanced signal processing methods is very important in medical areas such as brain disorder diagnostic, epilepsy, sleep analysis, anesthesia analysis, and more recently in brain-computer interfaces (BCI. Method: Wavelet transform package is used on this work to extract brain rhythms of electroencephalographic signals (EEG related to motor imagination tasks. We used the Competition BCI 2008 database for this characterization. Using statistical functions we obtained features that characterizes brain rhythms, which are discriminated using different classifiers; they were evaluated using a 10-fold cross validation criteria. Results: The classification accuracy achieved 81.11% on average, with a degree of agreement of 61%, indicating a "suitable" concordance, as it has been reported in the literature. An analysis of relevance showed the concentration of characteristics provided in the nodes as a result of Wavelet decomposition, as well as the characteristics that more information content contribute to improve the separability decision region for the classification task. Conclusions: The proposed method can be used as a reference to support future studies focusing on characterizing EEG signals oriented to the imagination of left and right hand movement, considering that our results proved to compared favourably to those reported in the literature. Language: Spanish.

Comparison of various extraction techniques for the determination of polycyclic aromatic hydrocarbons in worms.

Science.gov (United States)

Mooibroek, D; Hoogerbrugge, R; Stoffelsen, B H G; Dijkman, E; Berkhoff, C J; Hogendoorn, E A

2002-10-25

Two less laborious extraction methods, viz. (i) a simplified liquid extraction using light petroleum or (ii) microwave-assisted solvent extraction (MASE), for the analysis of polycyclic aromatic hydrocarbons (PAHs) in samples of the compost worm Eisenia andrei, were compared with a reference method. After extraction and concentration, analytical methodology consisted of a cleanup of (part) of the extract with high-performance gel permeation chromatography (HPGPC) and instrumental analysis of 15 PAHs with reversed-phase liquid chromatography with fluorescence detection (RPLC-FLD). Comparison of the methods was done by analysing samples with incurred residues (n=15, each method) originating from an experiment in which worms were exposed to a soil contaminated with PAHs. Simultaneously, the performance of the total lipid determination of each method was established. Evaluation of the data by means of principal component analysis (PCA) and analysis of variance (ANOVA) revealed that the performance of the light petroleum method for both the extraction of PAHs (concentration range 1-30 ng/g) and lipid content corresponds very well with the reference method. Compared to the reference method, the MASE method yielded somewhat lower concentrations for the less volatile PAHs, e.g., dibenzo[ah]anthracene and benzo[ghi]perylene and provided a significant higher amount of co-extracted material.

Phase extracting algorithms analysis in the white-light spectral interferometry

Science.gov (United States)

Guo, Tong; Li, Bingtong; Li, Minghui; Chen, Jinping; Fu, Xing; Hu, Xiaotang

2018-01-01

As an optical testing method, white-light spectral interferometry has the characteristics of non-contact, high precision. The phase information can be obtained by analyzing the spectral interference signal of the tested sample, and then the absolute distance is calculated. Fourier transform method, temporal phase-shifting method, spatial phase-shifting method and envelope method can be used to extract the phase information of the spectral interference signal. In this paper, the performance of four methods to extract phase information is simulated and analyzed by using the ideal spectral interference signal. It turns out that temporal phase-shifting method has the performance of high precision, the results of Fourier transform method and envelop method are distorted at the edge of the signal, and spatial phase-shifting method has the worst precision. Adding different levels of white noise to the ideal signal, temporal phase-shifting method is most accurate, while Fourier transform method and envelope method are relatively poor. Finally, the absolute distance measurement experiment is carried out on the constructed test system, and the results are consistent with the simulation ones.

Signal processing for the profoundly deaf.

Science.gov (United States)

Boothyroyd, A

1990-01-01

Profound deafness, defined here as a hearing loss in excess of 90 dB, is characterized by high thresholds, reduced hearing range in the intensity and frequency domains, and poor resolution in the frequency and time domains. The high thresholds call for hearing aids with unusually high gains or remote microphones that can be placed close to the signal source. The former option creates acoustic feedback problems for which digital signal processing may yet offer solutions. The latter option calls for carrier wave technology that is already available. The reduced frequency and intensity ranges would appear to call for frequency and/or amplitude compression. It might also be argued, however, that any attempts to compress the acoustic signal into the limited hearing range of the profoundly deaf will be counterproductive because of poor frequency and time resolution, especially when the signal is present in noise. In experiments with a 2-channel compression system, only 1 of 9 subjects showed an improvement of perception with the introduction of fast-release (20 ms) compression. The other 8 experienced no benefit or a slight deterioration of performance. These results support the concept of providing the profoundly deaf with simpler, rather than more complex, patterns, perhaps through the use of feature extraction hearing aids. Data from users of cochlear implants already employing feature extraction techniques also support this concept.

The Curvelet Transform in the analysis of 2-D GPR data: Signal enhancement and extraction of orientation-and-scale-dependent information

Science.gov (United States)

Tzanis, Andreas

2013-04-01

wavelet transform: whereas discrete wavelets are designed to provide sparse representations of functions with point singularities, curvelets are designed to provide sparse representations of functions with singularities on curves. This work investigates the utility of the CT in processing noisy GPR data from geotechnical and archaeometric surveys. The analysis has been performed with the Fast Discrete CT (FDCT - Candès et al., 2006) available from http://www.curvelet.org/ and adapted for use by the matGPR software (Tzanis, 2010). The adaptation comprises a set of driver functions that compute and display the curvelet decomposition of the input GPR section and then allow for the interactive exclusion/inclusion of data (wavefront) components at different scales and angles by cancelation/restoration of the corresponding curvelet coefficients. In this way it is possible to selectively reconstruct the data so as to abstract/retain information of given scales and orientations. It is demonstrated that the CT can be used to: (a) Enhance the S/N ratio by cancelling directional noise wavefronts of any angle of emergence, with particular reference to clutter. (b) Extract geometric information for further scrutiny, e.g. distinguish signals from small and large aperture fractures, faults, bedding etc. (c) Investigate the characteristics of signal propagation (hence material properties), albeit indirectly. This is possible because signal attenuation and temporal localization are closely associated, so that scale and spatio-temporal localization are also closely related. Thus, interfaces embedded in low attenuation domains will tend to produce sharp reflections rich in high frequencies and fine-scale localization. Conversely, interfaces in high attenuation domains will tend to produce dull reflections rich in low frequencies and broad localization. At a single scale and with respect to points (a) and (b) above, the results of the CT processor are comparable to those of the tuneable

Selected bibliography for the extraction of uranium from seawater: chemical process and plant design feasibility study

Energy Technology Data Exchange (ETDEWEB)

Binney, S.E.; Polkinghorne, S.T.; Jante, R.R.; Rodman, M.R.; Chen, A.C.T.; Gordon, L.I.

1979-02-01

A selected annotated bibliography of 521 references was prepared as a part of a feasibility study of the extraction of uranium from seawater. For the most part, these references are related to the chemical processes whereby the uranium is removed from the seawater. A companion docment contains a similar bibliography of 471 references related to oceanographic and uranium extraction plant siting considerations, although some of the references are in common. The bibliography was prepared by computer retrieval from Chemical Abstracts, Nuclear Science Abstracts, Energy Data Base, NTIS, and Oceanic Abstracts. References are listed by author, country of author, and selected keywords.

Selected bibliography for the extraction of uranium from seawater: chemical process and plant design feasibility study

International Nuclear Information System (INIS)

Binney, S.E.; Polkinghorne, S.T.; Jante, R.R.; Rodman, M.R.; Chen, A.C.T.; Gordon, L.I.

1979-02-01

A selected annotated bibliography of 521 references was prepared as a part of a feasibility study of the extraction of uranium from seawater. For the most part, these references are related to the chemical processes whereby the uranium is removed from the seawater. A companion docment contains a similar bibliography of 471 references related to oceanographic and uranium extraction plant siting considerations, although some of the references are in common. The bibliography was prepared by computer retrieval from Chemical Abstracts, Nuclear Science Abstracts, Energy Data Base, NTIS, and Oceanic Abstracts. References are listed by author, country of author, and selected keywords

Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering

Directory of Open Access Journals (Sweden)

Chin-Teng Lin

2018-01-01

Full Text Available Electroencephalogram (EEG signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA, feature extraction, and the Gaussian mixture model (GMM to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research.

Acoustic Green's function extraction in the ocean

Science.gov (United States)

Zang, Xiaoqin

The acoustic Green's function (GF) is the key to understanding the acoustic properties of ocean environments. With knowledge of the acoustic GF, the physics of sound propagation, such as dispersion, can be analyzed; underwater communication over thousands of miles can be understood; physical properties of the ocean, including ocean temperature, ocean current speed, as well as seafloor bathymetry, can be investigated. Experimental methods of acoustic GF extraction can be categorized as active methods and passive methods. Active methods are based on employment of man-made sound sources. These active methods require less computational complexity and time, but may cause harm to marine mammals. Passive methods cost much less and do not harm marine mammals, but require more theoretical and computational work. Both methods have advantages and disadvantages that should be carefully tailored to fit the need of each specific environment and application. In this dissertation, we study one passive method, the noise interferometry method, and one active method, the inverse filter processing method, to achieve acoustic GF extraction in the ocean. The passive method of noise interferometry makes use of ambient noise to extract an approximation to the acoustic GF. In an environment with a diffusive distribution of sound sources, sound waves that pass through two hydrophones at two locations carry the information of the acoustic GF between these two locations; by listening to the long-term ambient noise signals and cross-correlating the noise data recorded at two locations, the acoustic GF emerges from the noise cross-correlation function (NCF); a coherent stack of many realizations of NCFs yields a good approximation to the acoustic GF between these two locations, with all the deterministic structures clearly exhibited in the waveform. To test the performance of noise interferometry in different types of ocean environments, two field experiments were performed and ambient noise

Signal transforms in dynamic measurements

CERN Document Server

Layer, Edward

2015-01-01

This book is devoted to the analysis of measurement signals which requires specific mathematical operations like Convolution, Deconvolution, Laplace, Fourier, Hilbert, Wavelet or Z transform which are all presented in the present book. The different problems refer to the modulation of signals, filtration of disturbance as well as to the orthogonal signals and their use in digital form for the measurement of current, voltage, power and frequency are also widely discussed. All the topics covered in this book are presented in detail and illustrated by means of examples in MathCad and LabVIEW. This book provides a useful source for researchers, scientists and engineers who in their daily work are required to deal with problems of measurement and signal processing and can also be helpful to undergraduate students of electrical engineering.    

Antidiarrhoeal activity of leaf methanolic extract of Rauwolfia serpentina

OpenAIRE

II Ezeigbo; MI Ezeja; KG Madubuike; DC Ifenkwe; IA Ukweni; NE Udeh; SC Akomas

2012-01-01

Objective: To evaluate the antidiarrhoeal property of methanol extract of the leaves of Rauwolfia serpentina (R. serpentina) in experimental diarrhoea induced by castor oil in mice. Methods: Doses of 100, 200 and 400 mg/kg R. serpentina leaf methanol extracts were administered to castor oil induced diarrhoea mice to determine its antidiarrhoeal activity. Results: All doses of the extract and the reference drug atropine sulphate (3 mg/kg, i.p.) produced a dose-dependent reduction in inte...

PETCO2 measurement and feature extraction of capnogram signals for extubation outcomes from mechanical ventilation

International Nuclear Information System (INIS)

Rasera, Carmen C; Gewehr, Pedro M; Domingues, Adriana Maria T

2015-01-01

Capnography is a continuous and noninvasive method for carbon dioxide (CO 2 ) measurement, and it has become the standard of care for basic respiratory monitoring for intubated patients in the intensive care unit. In addition, it has been used to adjust ventilatory parameters during mechanical ventilation (MV). However, a substantial debate remains as to whether capnography is useful during the process of weaning and extubation from MV during the postoperative period. Thus, the main objective of this study was to present a new use for time-based capnography data by measuring the end-tidal CO 2 pressure (PET CO 2 ), partial pressure of arterial CO 2 (Pa CO 2 ) and feature extraction of capnogram signals before extubation from MV to evaluate the capnography as a predictor of outcome extubation in infants after cardiac surgery. Altogether, 82 measurements were analysed, 71.9% patients were successfully extubated, and 28.1% met the criteria for extubation failure within 48 h. The ROC-AUC analysis for quantitative measure of the capnogram showed significant differences (p < 0.001) for: expiratory time (0.873), slope of phase III (0.866), slope ratio (0.923) and ascending angle (0.897). In addition, the analysis of PET CO 2 (0.895) and Pa CO 2   (0.924) obtained 30 min before extubation showed significant differences between groups. The PET CO 2 mean value for success and failure extubation group was 39.04 mmHg and 46.27 mmHg, respectively. It was also observed that high CO 2 values in patients who had returned MV was 82.8  ±  21 mmHg at the time of extubation failure. Thus, PET CO 2 measurements and analysis of features extracted from a capnogram can differentiate extubation outcomes in infant patients under MV, thereby reducing the physiologic instability caused by failure in this process. (paper)

Surface EMG signals based motion intent recognition using multi-layer ELM

Science.gov (United States)

Wang, Jianhui; Qi, Lin; Wang, Xiao

2017-11-01

The upper-limb rehabilitation robot is regard as a useful tool to help patients with hemiplegic to do repetitive exercise. The surface electromyography (sEMG) contains motion information as the electric signals are generated and related to nerve-muscle motion. These sEMG signals, representing human's intentions of active motions, are introduced into the rehabilitation robot system to recognize upper-limb movements. Traditionally, the feature extraction is an indispensable part of drawing significant information from original signals, which is a tedious task requiring rich and related experience. This paper employs a deep learning scheme to extract the internal features of the sEMG signals using an advanced Extreme Learning Machine based auto-encoder (ELMAE). The mathematical information contained in the multi-layer structure of the ELM-AE is used as the high-level representation of the internal features of the sEMG signals, and thus a simple ELM can post-process the extracted features, formulating the entire multi-layer ELM (ML-ELM) algorithm. The method is employed for the sEMG based neural intentions recognition afterwards. The case studies show the adopted deep learning algorithm (ELM-AE) is capable of yielding higher classification accuracy compared to the Principle Component Analysis (PCA) scheme in 5 different types of upper-limb motions. This indicates the effectiveness and the learning capability of the ML-ELM in such motion intent recognition applications.

A review of intelligent systems for heart sound signal analysis.

Science.gov (United States)

Nabih-Ali, Mohammed; El-Dahshan, El-Sayed A; Yahia, Ashraf S

2017-10-01

Intelligent computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of physicians and reduce the time required for accurate diagnosis. CAD systems could provide physicians with a suggestion about the diagnostic of heart diseases. The objective of this paper is to review the recent published preprocessing, feature extraction and classification techniques and their state of the art of phonocardiogram (PCG) signal analysis. Published literature reviewed in this paper shows the potential of machine learning techniques as a design tool in PCG CAD systems and reveals that the CAD systems for PCG signal analysis are still an open problem. Related studies are compared to their datasets, feature extraction techniques and the classifiers they used. Current achievements and limitations in developing CAD systems for PCG signal analysis using machine learning techniques are presented and discussed. In the light of this review, a number of future research directions for PCG signal analysis are provided.

Developing a reference of normal lung sounds in healthy Peruvian children.

Science.gov (United States)

Ellington, Laura E; Emmanouilidou, Dimitra; Elhilali, Mounya; Gilman, Robert H; Tielsch, James M; Chavez, Miguel A; Marin-Concha, Julio; Figueroa, Dante; West, James; Checkley, William

2014-10-01

Lung auscultation has long been a standard of care for the diagnosis of respiratory diseases. Recent advances in electronic auscultation and signal processing have yet to find clinical acceptance; however, computerized lung sound analysis may be ideal for pediatric populations in settings, where skilled healthcare providers are commonly unavailable. We described features of normal lung sounds in young children using a novel signal processing approach to lay a foundation for identifying pathologic respiratory sounds. 186 healthy children with normal pulmonary exams and without respiratory complaints were enrolled at a tertiary care hospital in Lima, Peru. Lung sounds were recorded at eight thoracic sites using a digital stethoscope. 151 (81%) of the recordings were eligible for further analysis. Heavy-crying segments were automatically rejected and features extracted from spectral and temporal signal representations contributed to profiling of lung sounds. Mean age, height, and weight among study participants were 2.2 years (SD 1.4), 84.7 cm (SD 13.2), and 12.0 kg (SD 3.6), respectively; and, 47% were boys. We identified ten distinct spectral and spectro-temporal signal parameters and most demonstrated linear relationships with age, height, and weight, while no differences with genders were noted. Older children had a faster decaying spectrum than younger ones. Features like spectral peak width, lower-frequency Mel-frequency cepstral coefficients, and spectro-temporal modulations also showed variations with recording site. Lung sound extracted features varied significantly with child characteristics and lung site. A comparison with adult studies revealed differences in the extracted features for children. While sound-reduction techniques will improve analysis, we offer a novel, reproducible tool for sound analysis in real-world environments.

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

Directory of Open Access Journals (Sweden)

Abhishek Jain

2016-01-01

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

Aqueous extract of Allium sativum L bulbs offer nephroprotection by attenuating vascular endothelial growth factor and extracellular signal-regulated kinase-1 expression in diabetic rats.

Science.gov (United States)

Shiju, T M; Rajkumar, R; Rajesh, N G; Viswanathan, Pragasam

2013-02-01

To investigate the nephroprotective effect of garlic and elucidate the mechanism by which it prevents the progression of diabetic nephropathy in diabetic rats, diabetes was induced by a single ip injection of streptozotocin (45 mg/kg body weight). Garlic extract (500 mg/kg body weight) and aminoguanidine (1 g/L) were supplemented in the treatment groups. Histopathological examination using H&E, PAS staining and the immunohistochemical analysis of vascular endothelial growth factor (VEGF) and extracellular signal-regulated kinase-1 (ERK-1) expression were performed on kidney sections at the end of 12 weeks. Significant change in both, the urine and serum biochemistry confirmed kidney damage in diabetic animals which was further confirmed by the histological changes such as mesangial expansion, glomerular basement membrane thickening, glycosuria and proteinuria. However, the diabetic animals treated with garlic extract showed a significant change in urine and serum biochemical parameters such as albumin, urea nitrogen and creatinine compared to that of diabetic rats. Further, the garlic supplemented diabetic rats showed a significant decrease in the expression of VEGF and ERK-1 compared to diabetic rats, attenuating mesangial expansion and glomerulosclerosis. Thus, garlic extract rendered nephroprotection in diabetic rats.

[PREPARATION OF HUMAN TISSUE PROTEIN EXTRACTS ENRICHED WITH THE SPHINGOMYELIN SYNTHASE 1].

Science.gov (United States)

Sudarkina, O Yu; Dergunova, L V

2015-01-01

Sphingomyelin synthase 1 (SMS 1) catalyzes sphingomyelin biosynthesis in eukaryotic cells. We previously studied the structure of the human SGMS1 gene, which encodes the enzyme and its numerous transcripts. The tissue-specific expression of the transcripts was also described. Analysis of the SMS1 protein expression in human tissues using immunoblotting of tissue extracts prepared in the RIPA (Radio Immuno-Precipitation Assay) buffer revealed a weak signal in renal cortex, testis, lung, and no signal in placenta and lymphatic node. In this work, a new method of preparation of the tissue protein extracts enriched with SMS1 was suggested. The method based on the consecutive extraction with a buffer containing 0.05 and 1 mg/ml of the Quillaja saponaria saponin allowed SMS1 to be detected in all tissues tested. The SMS1 content in the saponin extract of kidney cortex is about 12-fold higher compared to the RIPA extraction procedure.

An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification

Directory of Open Access Journals (Sweden)

Fangmin Li

2017-11-01

Full Text Available In this paper, we propose the multiwindow Adaptive S-method (AS-method distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference.

Detection of cardiovascular risk from a photoplethysmographic signal using a matching pursuit algorithm.

Science.gov (United States)

Sommermeyer, Dirk; Zou, Ding; Ficker, Joachim H; Randerath, Winfried; Fischer, Christoph; Penzel, Thomas; Sanner, Bernd; Hedner, Jan; Grote, Ludger

2016-07-01

Cardiovascular disease is the main cause of death in Europe, and early detection of increased cardiovascular risk (CR) is of clinical importance. Pulse wave analysis based on pulse oximetry has proven useful for the recognition of increased CR. The current study provides a detailed description of the pulse wave analysis technology and its clinical application. A novel matching pursuit-based feature extraction algorithm was applied for signal decomposition of the overnight photoplethysmographic pulse wave signals obtained by a single-pulse oximeter sensor. The algorithm computes nine parameters (pulse index, SpO2 index, pulse wave amplitude index, respiratory-related pulse oscillations, pulse propagation time, periodic and symmetric desaturations, time under 90 % SpO2, difference between pulse and SpO2 index, and arrhythmia). The technology was applied in 631 patients referred for a sleep study with suspected sleep apnea. The technical failure rate was 1.4 %. Anthropometric data like age and BMI correlated significantly with measures of vascular stiffness and pulse rate variability (PPT and age r = -0.54, p < 0.001, PR and age r = -0.36, p < 0.01). The composite biosignal risk score showed a dose-response relationship with the number of CR factors (p < 0.001) and was further elevated in patients with sleep apnea (AHI ≥ 15n/h; p < 0.001). The developed algorithm extracts meaningful parameters indicative of cardiorespiratory and autonomic nervous system function and dysfunction in patients suspected of SDB.

Vibration Feature Extraction and Analysis for Fault Diagnosis of Rotating Machinery-A Literature Survey

Directory of Open Access Journals (Sweden)

Saleem Riaz

2017-02-01

Full Text Available Safety, reliability, efficiency and performance of rotating machinery in all industrial applications are the main concerns. Rotating machines are widely used in various industrial applications. Condition monitoring and fault diagnosis of rotating machinery faults are very important and often complex and labor-intensive. Feature extraction techniques play a vital role for a reliable, effective and efficient feature extraction for the diagnosis of rotating machinery. Therefore, developing effective bearing fault diagnostic method using different fault features at different steps becomes more attractive. Bearings are widely used in medical applications, food processing industries, semi-conductor industries, paper making industries and aircraft components. This paper review has demonstrated that the latest reviews applied to rotating machinery on the available a variety of vibration feature extraction. Generally literature is classified into two main groups: frequency domain, time frequency analysis. However, fault detection and diagnosis of rotating machine vibration signal processing methods to present their own limitations. In practice, most healthy ingredients faulty vibration signal from background noise and mechanical vibration signals are buried. This paper also reviews that how the advanced signal processing methods, empirical mode decomposition and interference cancellation algorithm has been investigated and developed. The condition for rotating machines based rehabilitation, prevent failures increase the availability and reduce the cost of maintenance is becoming necessary too. Rotating machine fault detection and diagnostics in developing algorithms signal processing based on a key problem is the fault feature extraction or quantification. Currently, vibration signal, fault detection and diagnosis of rotating machinery based techniques most widely used techniques. Furthermore, the researchers are widely interested to make automatic

Signal processing for cognitive radios

CERN Document Server

Jayaweera, Sudharman K

2014-01-01

This book covers power electronics, in depth, by presenting the basic principles and application details, and it can be used both as a textbook and reference book.  Introduces the specific type of CR that has gained the most research attention in recent years: the CR for Dynamic Spectrum Access (DSA). Provides signal processing solutions to each task by relating the tasks to materials covered in Part II. Specialized chapters then discuss specific signal processing algorithms required for DSA and DSS cognitive radios  

EEMD Independent Extraction for Mixing Features of Rotating Machinery Reconstructed in Phase Space

Directory of Open Access Journals (Sweden)

Zaichao Ma

2015-04-01

Full Text Available Empirical Mode Decomposition (EMD, due to its adaptive decomposition property for the non-linear and non-stationary signals, has been widely used in vibration analyses for rotating machinery. However, EMD suffers from mode mixing, which is difficult to extract features independently. Although the improved EMD, well known as the ensemble EMD (EEMD, has been proposed, mode mixing is alleviated only to a certain degree. Moreover, EEMD needs to determine the amplitude of added noise. In this paper, we propose Phase Space Ensemble Empirical Mode Decomposition (PSEEMD integrating Phase Space Reconstruction (PSR and Manifold Learning (ML for modifying EEMD. We also provide the principle and detailed procedure of PSEEMD, and the analyses on a simulation signal and an actual vibration signal derived from a rubbing rotor are performed. The results show that PSEEMD is more efficient and convenient than EEMD in extracting the mixing features from the investigated signal and in optimizing the amplitude of the necessary added noise. Additionally PSEEMD can extract the weak features interfered with a certain amount of noise.

MODELLING SLOW EXTRACTION INDUCED RADIOACTIVITY IN SPS LSS2

CERN Document Server

Araujo Martinez, Aurora Cecilia; CERN. Geneva. TE Department

2017-01-01

The Accelerator and Beam Transfer (ABT) group is investigating the impact of recent proposals to extract higher proton intensities to Fixed Target experiments at the SPS. The 400 GeV high-energy proton beam is typically extracted over a few seconds using a resonant slow-extraction technique that induces small but unavoidable beam losses on the extraction equipment in SPS LSS2. In this report, the induced radioactivity for 2016-2017 is used to predict future activation levels and cool-down times, using a past intervention as a reference to predict dose to the personnel carrying-out maintenance of the accelerator.

Stir Bar Sorptive Extraction (SBSE), a novel extraction technique for aqueous samples: theory and principles

NARCIS (Netherlands)

Baltussen, H.A.; Sandra, P.J.F.; David, F.; Cramers, C.A.M.G.

1999-01-01

The theory and practice of a novel approach for sample enrichment, namely the application of stir bars coated with the sorbent polydimethylsiloxane (PDMS) and referred to as stir bar sorptive extraction (SBSE) are presented. Stir bars with a length of 10 and 40 mm coated with 55 and 219 L of PDMS

Supercritical Fluid Extract of Spent Coffee Grounds Attenuates Melanogenesis through Downregulation of the PKA, PI3K/Akt, and MAPK Signaling Pathways

Directory of Open Access Journals (Sweden)

Huey-Chun Huang

2016-01-01

Full Text Available The mode of action of spent coffee grounds supercritical fluid CO2 extract (SFE in melanogenesis has never been reported. In the study, the spent coffee grounds were extracted by the supercritical fluid CO2 extraction method; the chemical constituents of the SFE were investigated by gas chromatography-mass spectrometry (GC-MS. The effects of the SFE and its major fatty acid components on melanogenesis were evaluated by mushroom tyrosinase activity assay and determination of intracellular tyrosinase activity and melanin content. The expression level of melanogenesis-related proteins was analyzed by western blotting assay. The results revealed that the SFE of spent coffee grounds (1–10 mg/mL and its major fatty acids such as linoleic acid and oleic acid (6.25–50 μM effectively suppressed melanogenesis in the B16F10 murine melanoma cells. Furthermore, the SFE decreased the expression of melanocortin 1 receptor (MC1R, microphthalmia-associated transcription factor (MITF, tyrosinase, tyrosinase-related protein-1 (TRP-1, and tyrosinase-related protein-2 (TRP-2. The SFE also decreased the protein expression levels of p-JNK, p-p38, p-ERK, and p-CREB. Our results revealed that the SFE of spent coffee grounds attenuated melanogenesis in B16F10 cells by downregulation of protein kinase A (PKA, phosphatidylinositol-3-kinase (PI3K/Akt, and mitogen-activated protein kinases (MAPK signaling pathways, which may be due to linoleic acid and oleic acid.

The Fault Feature Extraction of Rolling Bearing Based on EMD and Difference Spectrum of Singular Value

Directory of Open Access Journals (Sweden)

Te Han

2016-01-01

Full Text Available Nowadays, the fault diagnosis of rolling bearing in aeroengines is based on the vibration signal measured on casing, instead of bearing block. However, the vibration signal of the bearing is often covered by a series of complex components caused by other structures (rotor, gears. Therefore, when bearings cause failure, it is still not certain that the fault feature can be extracted from the vibration signal on casing. In order to solve this problem, a novel fault feature extraction method for rolling bearing based on empirical mode decomposition (EMD and the difference spectrum of singular value is proposed in this paper. Firstly, the vibration signal is decomposed by EMD. Next, the difference spectrum of singular value method is applied. The study finds that each peak on the difference spectrum corresponds to each component in the original signal. According to the peaks on the difference spectrum, the component signal of the bearing fault can be reconstructed. To validate the proposed method, the bearing fault data collected on the casing are analyzed. The results indicate that the proposed rolling bearing diagnosis method can accurately extract the fault feature that is submerged in other component signals and noise.

Device and Method for Gathering Ensemble Data Sets

Science.gov (United States)

Racette, Paul E. (Inventor)

2014-01-01

An ensemble detector uses calibrated noise references to produce ensemble sets of data from which properties of non-stationary processes may be extracted. The ensemble detector comprising: a receiver; a switching device coupled to the receiver, the switching device configured to selectively connect each of a plurality of reference noise signals to the receiver; and a gain modulation circuit coupled to the receiver and configured to vary a gain of the receiver based on a forcing signal; whereby the switching device selectively connects each of the plurality of reference noise signals to the receiver to produce an output signal derived from the plurality of reference noise signals and the forcing signal.

Ultrasound assisted extraction of polyphenols from Punica granatum (Grenada) fruit

International Nuclear Information System (INIS)

Rodriguez Chanfrau, Jorge Enrique; Lopez Armas, Marilyn

2014-01-01

Extraction of bioactive compounds from vegetable materials is a classical operation applied in many industrial processes. Few studies have made reference to processes to obtain extracts from Punica granatum. This fruit is generally consumed as such or as fermented juices. In Cuba, it is known as grenade and numerous studies have shown antiviral, antioxidant and antimicrobial properties. Maceration process is the main used technology in the preparation of extracts from Punica granatum fruit, being this a long and expensive process. Ultrasound-assisted extractions have been proven to significantly decreased extraction time and increased extraction yields in many vegetable materials. However, few papers report the use of this methodology in the extraction processes of Punica granatum. To evaluate an ultrasound-assisted extraction process to extract polyphenols from Punica granatum fruit

Vehicle Reference Generator for Collision-Free Trajectories in Hazardous Maneuvers

Directory of Open Access Journals (Sweden)

Cuauhtémoc Acosta Lúa

2018-01-01

Full Text Available This paper presents a reference generator for ground vehicles, based on potential fields adapted to the case of vehicular dynamics. The reference generator generates signals to be tracked by the vehicle, corresponding to a trajectory avoiding collisions with obstacles. This generator integrates artificial forces of potential fields of the object surrounding the vehicle. The reference generator is used with a controller to ensure the tracking of the accident-free reference. This approach can be used for vehicle autonomous driving or for active control of manned vehicles. Simulation results, presented for the autonomous driving, consider a scenario inspired by the so-called moose (or elk test, with the presence of other collaborative vehicles.

Extracting a respiratory signal from raw dynamic PET data that contain tracer kinetics.

Science.gov (United States)

Schleyer, P J; Thielemans, K; Marsden, P K

2014-08-07

Data driven gating (DDG) methods provide an alternative to hardware based respiratory gating for PET imaging. Several existing DDG approaches obtain a respiratory signal by observing the change in PET-counts within specific regions of acquired PET data. Currently, these methods do not allow for tracer kinetics which can interfere with the respiratory signal and introduce error. In this work, we produced a DDG method for dynamic PET studies that exhibit tracer kinetics. Our method is based on an existing approach that uses frequency-domain analysis to locate regions within raw PET data that are subject to respiratory motion. In the new approach, an optimised non-stationary short-time Fourier transform was used to create a time-varying 4D map of motion affected regions. Additional processing was required to ensure that the relationship between the sign of the respiratory signal and the physical direction of movement remained consistent for each temporal segment of the 4D map. The change in PET-counts within the 4D map during the PET acquisition was then used to generate a respiratory curve. Using 26 min dynamic cardiac NH3 PET acquisitions which included a hardware derived respiratory measurement, we show that tracer kinetics can severely degrade the respiratory signal generated by the original DDG method. In some cases, the transition of tracer from the liver to the lungs caused the respiratory signal to invert. The new approach successfully compensated for tracer kinetics and improved the correlation between the data-driven and hardware based signals. On average, good correlation was maintained throughout the PET acquisitions.

CMOS bandgap references and temperature sensors and their applications

NARCIS (Netherlands)

Wang, G.

2005-01-01

Two main parts have been presented in this thesis: device characterization and circuit. In integrated bandgap references and temperature sensors, the IC(VBE, characteristics of bipolar transistors are used to generate the basic signals with high accuracy. To investigate the possibilities to

INAA and PIXE for the determination of the contents of extractable sediment

International Nuclear Information System (INIS)

Freitas, M.C.; Hipolito, C.S.

2007-01-01

The three-stage BCR sequential step reference extraction procedure was applied to the reference material BCR CRM 601, especially developed for fractionation studies. Extracted fractions were analyzed for Cr, Ni, Zn, Cd, and Pb, by k 0 -standardized instrumental neutron activation (k 0 INAA) and proton induced X-ray emission (PIXE), and flame atomic absorption spectrometry (FAAS). Sample preparation procedures were developed for both k 0 INAA and PIXE techniques, related to the evaporation of the solutions in order to get solid samples for neutron and proton irradiation. Quality control was assessed by intercomparison of the analytical results obtained by the applied techniques, which included results for a few certified reference materials. In the extracted fractions, chromium concentration was not determined accurately by both nuclear techniques. Concerning Cd, Ni, Pb, and Zn, the results were in general in good agreement with the certified values and FAAS. Some incomplete separation of the residue might have occurred. (author)

Nootropic effect of meadowsweet (Filipendula vulgaris) extracts.

Science.gov (United States)

Shilova, I V; Suslov, N I

2015-03-01

The effects of the extracts of the aboveground parts of Filipendula vulgaris Moench on the behavior and memory of mice after hypoxic injury and their physical performance in the open-field test were studied using the models of hypoxia in a sealed volume, conditioned passive avoidance response (CPAR), and forced swimming with a load. The extracts improved animal resistance to hypoxia, normalized orientation and exploration activities, promoted CPAR retention after hypoxic injury, and increased physical performance. Aqueous extract of meadowsweet had the most pronounced effect that corresponded to the effect of the reference drug piracetam. These effects were probably caused by modulation of hippocampal activity.

Using LabVIEW for the design and control of digital signal processing systems. Simulation of the ultra slow extraction at COSY

International Nuclear Information System (INIS)

Heinrichs, G.; Rongen, H.; Jamal, R.

1994-01-01

For the ultraslow extraction system of the COler SYnchrotron COSY a direct digital synthesis system is being developed. LabVIEW from National Instruments has been chosen as a tool for the simulation of the digital signal processing algorithms as well as the generation of test sequences. In order to generate adjustable band-limited noise centered at a carrier frequency, alternative algorithms have been studied. LabVIEW permits the interactive variation of relevant system parameters by means of a graphical language in order to study the quality of the frequency band limitation as a function of noise parameters, digital accuracy and frequency range and to generate test sequences by means of a real-time function generator. Advantages and limitations of LabVIEW for such applications are discussed. ((orig.))

Driver drowsiness classification using fuzzy wavelet-packet-based feature-extraction algorithm.

Science.gov (United States)

Khushaba, Rami N; Kodagoda, Sarath; Lal, Sara; Dissanayake, Gamini

2011-01-01

Driver drowsiness and loss of vigilance are a major cause of road accidents. Monitoring physiological signals while driving provides the possibility of detecting and warning of drowsiness and fatigue. The aim of this paper is to maximize the amount of drowsiness-related information extracted from a set of electroencephalogram (EEG), electrooculogram (EOG), and electrocardiogram (ECG) signals during a simulation driving test. Specifically, we develop an efficient fuzzy mutual-information (MI)- based wavelet packet transform (FMIWPT) feature-extraction method for classifying the driver drowsiness state into one of predefined drowsiness levels. The proposed method estimates the required MI using a novel approach based on fuzzy memberships providing an accurate-information content-estimation measure. The quality of the extracted features was assessed on datasets collected from 31 drivers on a simulation test. The experimental results proved the significance of FMIWPT in extracting features that highly correlate with the different drowsiness levels achieving a classification accuracy of 95%-- 97% on an average across all subjects.

Effect of endogenous reference genes on digital PCR assessment of genetically engineered canola events

Directory of Open Access Journals (Sweden)

Tigst Demeke

2018-05-01

Full Text Available Droplet digital PCR (ddPCR has been used for absolute quantification of genetically engineered (GE events. Absolute quantification of GE events by duplex ddPCR requires the use of appropriate primers and probes for target and reference gene sequences in order to accurately determine the amount of GE materials. Single copy reference genes are generally preferred for absolute quantification of GE events by ddPCR. Study has not been conducted on a comparison of reference genes for absolute quantification of GE canola events by ddPCR. The suitability of four endogenous reference sequences (HMG-I/Y, FatA(A, CruA and Ccf for absolute quantification of GE canola events by ddPCR was investigated. The effect of DNA extraction methods and DNA quality on the assessment of reference gene copy numbers was also investigated. ddPCR results were affected by the use of single vs. two copy reference genes. The single copy, FatA(A, reference gene was found to be stable and suitable for absolute quantification of GE canola events by ddPCR. For the copy numbers measured, the HMG-I/Y reference gene was less consistent than FatA(A reference gene. The expected ddPCR values were underestimated when CruA and Ccf (two copy endogenous Cruciferin sequences were used because of high number of copies. It is important to make an adjustment if two copy reference genes are used for ddPCR in order to obtain accurate results. On the other hand, real-time quantitative PCR results were not affected by the use of single vs. two copy reference genes. Keywords: Canola, Digital PCR, DNA extraction, GMO, Reference genes

Application of adaptive digital signal processing to speech enhancement for the hearing impaired.

Science.gov (United States)

Chabries, D M; Christiansen, R W; Brey, R H; Robinette, M S; Harris, R W

1987-01-01

A major complaint of individuals with normal hearing and hearing impairments is a reduced ability to understand speech in a noisy environment. This paper describes the concept of adaptive noise cancelling for removing noise from corrupted speech signals. Application of adaptive digital signal processing has long been known and is described from a historical as well as technical perspective. The Widrow-Hoff LMS (least mean square) algorithm developed in 1959 forms the introduction to modern adaptive signal processing. This method uses a "primary" input which consists of the desired speech signal corrupted with noise and a second "reference" signal which is used to estimate the primary noise signal. By subtracting the adaptively filtered estimate of the noise, the desired speech signal is obtained. Recent developments in the field as they relate to noise cancellation are described. These developments include more computationally efficient algorithms as well as algorithms that exhibit improved learning performance. A second method for removing noise from speech, for use when no independent reference for the noise exists, is referred to as single channel noise suppression. Both adaptive and spectral subtraction techniques have been applied to this problem--often with the result of decreased speech intelligibility. Current techniques applied to this problem are described, including signal processing techniques that offer promise in the noise suppression application.

Simultaneous extraction and clean-up of polychlorinated biphenyls and their metabolites from small tissue samples using pressurized liquid extraction

Science.gov (United States)

Kania-Korwel, Izabela; Zhao, Hongxia; Norstrom, Karin; Li, Xueshu; Hornbuckle, Keri C.; Lehmler, Hans-Joachim

2008-01-01

A pressurized liquid extraction-based method for the simultaneous extraction and in situ clean-up of polychlorinated biphenyls (PCBs), hydroxylated (OH)-PCBs and methylsulfonyl (MeSO2)-PCBs from small (< 0.5 gram) tissue samples was developed and validated. Extraction of a laboratory reference material with hexane:dichloromethane:methanol (48:43:9, v/v) and Florisil as fat retainer allowed an efficient recovery of PCBs (78–112%; RSD: 13–37%), OH-PCBs (46±2%; RSD: 4%) and MeSO2-PCBs (89±21%; RSD: 24%). Comparable results were obtained with an established analysis method for PCBs, OH-PCBs and MeSO2-PCBs. PMID:19019378

A no-reference metric for perceived ringing artifacts in images

NARCIS (Netherlands)

Liu, H.; Klomp, N.; Heynderickx, I.E.J.

2010-01-01

A novel no-reference metric that can automatically quantify ringing annoyance in compressed images is presented. In the first step a recently proposed ringing region detection method extracts the regions which are likely to be impaired by ringing artifacts. To quantify ringing annoyance in these

Efficient feature for classification of eye movements using electrooculography signals

Directory of Open Access Journals (Sweden)

Phukpattaranont Pornchai

2016-01-01

Full Text Available Electrooculography (EOG signal is widely and successfully used to detect activities of human eye. The advantages of the EOG-based interface over other conventional interfaces have been presented in the last two decades; however, due to a lot of information in EOG signals, the extraction of useful features should be done before the classification task. In this study, an efficient feature extracted from two directional EOG signals: vertical and horizontal signals has been presented and evaluated. There are the maximum peak and valley amplitude values, the maximum peak and valley position values, and slope, which are derived from both vertical and horizontal signals. In the experiments, EOG signals obtained from five healthy subjects with ten directional eye movements were employed: up, down, right, left, up-right, up-left, down-right down-left clockwise and counterclockwise. The mean feature values and their standard deviations have been reported. The difference between the mean values of the proposed feature from different eye movements can be clearly seen. Using the scatter plot, the differences in features can be also clearly observed. Results show that classification accuracy can approach 100% with a simple distinction feature rule. The proposed features can be useful for various advanced human-computer interface applications in future researches.

Determination of sub-microgram amounts of selenium in geological materials by atomic-absorption spectrophotometry with electrothermal atomisation after solvent extraction

Science.gov (United States)

Sanzolone, R.F.; Chao, T.T.

1981-01-01

An atomic-absorption spectrophotometric method with electrothermal atomisation has been developed for the determination of selenium in geological materials. The sample is decomposed with a mixture of nitric, perchloric and hydrofluoric acids and heated with hydrochloric acid to reduce selenium to selenium (IV). Selenium is then extracted into toluene from a hydrochloric acid - hydrobromic acid medium containing iron. A few microlitres of the toluene extract are injected into a carbon rod atomiser, using a nickel solution as a matrix modifier. The limits of determination are 0.2-200 p.p.m. of selenium in a geological sample. For concentrations between 0.05 and 0.2 p.p.m., back-extraction of the selenium into dilute hydrochloric acid is employed before atomisation. Selenium values for reference samples obtained by replicate analysis are in general agreement with those reported by other workers, with relative standard deviations ranging from 4.1 to 8.8%. Recoveries of selenium spiked at two levels were 98-108%. Major and trace elements commonly encountered in geological materials do not interfere. Arsenic has a suppressing effect on the selenium signals, but only when its concentration is greater than 1000 p.p.m. Nitric acid interferes seriously with the extraction of selenium and must be removed by evaporation in the sample-digestion step.

Extracting a respiratory signal from raw dynamic PET data that contain tracer kinetics

International Nuclear Information System (INIS)

Schleyer, P J; Thielemans, K; Marsden, P K

2014-01-01

Data driven gating (DDG) methods provide an alternative to hardware based respiratory gating for PET imaging. Several existing DDG approaches obtain a respiratory signal by observing the change in PET-counts within specific regions of acquired PET data. Currently, these methods do not allow for tracer kinetics which can interfere with the respiratory signal and introduce error. In this work, we produced a DDG method for dynamic PET studies that exhibit tracer kinetics. Our method is based on an existing approach that uses frequency-domain analysis to locate regions within raw PET data that are subject to respiratory motion. In the new approach, an optimised non-stationary short-time Fourier transform was used to create a time-varying 4D map of motion affected regions. Additional processing was required to ensure that the relationship between the sign of the respiratory signal and the physical direction of movement remained consistent for each temporal segment of the 4D map. The change in PET-counts within the 4D map during the PET acquisition was then used to generate a respiratory curve. Using 26 min dynamic cardiac NH 3 PET acquisitions which included a hardware derived respiratory measurement, we show that tracer kinetics can severely degrade the respiratory signal generated by the original DDG method. In some cases, the transition of tracer from the liver to the lungs caused the respiratory signal to invert. The new approach successfully compensated for tracer kinetics and improved the correlation between the data-driven and hardware based signals. On average, good correlation was maintained throughout the PET acquisitions. (paper)

Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal.

Science.gov (United States)

Xu, Shanzhi; Hu, Hai; Ji, Linhong; Wang, Peng

2018-02-26

The recorded electroencephalography (EEG) signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA) is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC) and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA) EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal

Directory of Open Access Journals (Sweden)

Shanzhi Xu

2018-02-01

Full Text Available The recorded electroencephalography (EEG signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

A New Method for Weak Fault Feature Extraction Based on Improved MED

Directory of Open Access Journals (Sweden)

Junlin Li

2018-01-01

Full Text Available Because of the characteristics of weak signal and strong noise, the low-speed vibration signal fault feature extraction has been a hot spot and difficult problem in the field of equipment fault diagnosis. Moreover, the traditional minimum entropy deconvolution (MED method has been proved to be used to detect such fault signals. The MED uses objective function method to design the filter coefficient, and the appropriate threshold value should be set in the calculation process to achieve the optimal iteration effect. It should be pointed out that the improper setting of the threshold will cause the target function to be recalculated, and the resulting error will eventually affect the distortion of the target function in the background of strong noise. This paper presents an improved MED based method of fault feature extraction from rolling bearing vibration signals that originate in high noise environments. The method uses the shuffled frog leaping algorithm (SFLA, finds the set of optimal filter coefficients, and eventually avoids the artificial error influence of selecting threshold parameter. Therefore, the fault bearing under the two rotating speeds of 60 rpm and 70 rpm is selected for verification with typical low-speed fault bearing as the research object; the results show that SFLA-MED extracts more obvious bearings and has a higher signal-to-noise ratio than the prior MED method.

Signal processing techniques for damage detection with piezoelectric wafer active sensors and embedded ultrasonic structural radar

Science.gov (United States)

Yu, Lingyu; Bao, Jingjing; Giurgiutiu, Victor

2004-07-01

Embedded ultrasonic structural radar (EUSR) algorithm is developed for using piezoelectric wafer active sensor (PWAS) array to detect defects within a large area of a thin-plate specimen. Signal processing techniques are used to extract the time of flight of the wave packages, and thereby to determine the location of the defects with the EUSR algorithm. In our research, the transient tone-burst wave propagation signals are generated and collected by the embedded PWAS. Then, with signal processing, the frequency contents of the signals and the time of flight of individual frequencies are determined. This paper starts with an introduction of embedded ultrasonic structural radar algorithm. Then we will describe the signal processing methods used to extract the time of flight of the wave packages. The signal processing methods being used include the wavelet denoising, the cross correlation, and Hilbert transform. Though hardware device can provide averaging function to eliminate the noise coming from the signal collection process, wavelet denoising is included to ensure better signal quality for the application in real severe environment. For better recognition of time of flight, cross correlation method is used. Hilbert transform is applied to the signals after cross correlation in order to extract the envelope of the signals. Signal processing and EUSR are both implemented by developing a graphical user-friendly interface program in LabView. We conclude with a description of our vision for applying EUSR signal analysis to structural health monitoring and embedded nondestructive evaluation. To this end, we envisage an automatic damage detection application utilizing embedded PWAS, EUSR, and advanced signal processing.

Developing a Reference of Normal Lung Sounds in Healthy Peruvian Children

Science.gov (United States)

Ellington, Laura E.; Emmanouilidou, Dimitra; Elhilali, Mounya; Gilman, Robert H.; Tielsch, James M.; Chavez, Miguel A.; Marin-Concha, Julio; Figueroa, Dante; West, James

2018-01-01

Purpose Lung auscultation has long been a standard of care for the diagnosis of respiratory diseases. Recent advances in electronic auscultation and signal processing have yet to find clinical acceptance; however, computerized lung sound analysis may be ideal for pediatric populations in settings, where skilled healthcare providers are commonly unavailable. We described features of normal lung sounds in young children using a novel signal processing approach to lay a foundation for identifying pathologic respiratory sounds. Methods 186 healthy children with normal pulmonary exams and without respiratory complaints were enrolled at a tertiary care hospital in Lima, Peru. Lung sounds were recorded at eight thoracic sites using a digital stethoscope. 151 (81 %) of the recordings were eligible for further analysis. Heavy-crying segments were automatically rejected and features extracted from spectral and temporal signal representations contributed to profiling of lung sounds. Results Mean age, height, and weight among study participants were 2.2 years (SD 1.4), 84.7 cm (SD 13.2), and 12.0 kg (SD 3.6), respectively; and, 47 % were boys. We identified ten distinct spectral and spectro-temporal signal parameters and most demonstrated linear relationships with age, height, and weight, while no differences with genders were noted. Older children had a faster decaying spectrum than younger ones. Features like spectral peak width, lower-frequency Mel-frequency cepstral coefficients, and spectro-temporal modulations also showed variations with recording site. Conclusions Lung sound extracted features varied significantly with child characteristics and lung site. A comparison with adult studies revealed differences in the extracted features for children. While sound-reduction techniques will improve analysis, we offer a novel, reproducible tool for sound analysis in real-world environments. PMID:24943262

Rate phenomena in uranium extraction by amines

International Nuclear Information System (INIS)

Coleman, C.F.; McDowell, W.J.

1979-01-01

Kinetics studies and other rate measurements are reviewed in the amine extraction of uranium and of some other related and associated metal ions. Equilibration is relatively fast in the uranium sulfate systems most important to uranium hydrometallurgy. Significantly slow equilibration has been encountered in some other systems. Most of the recorded rate information, both qualitative and quantitative, has come from exploratory and process-development work, while some kinetics studies have been directed specifically toward elucidation of extraction mechanisms. 71 references

A Hybrid Wavelet-Based Method for the Peak Detection of Photoplethysmography Signals

Directory of Open Access Journals (Sweden)

Suyi Li

2017-01-01

Full Text Available The noninvasive peripheral oxygen saturation (SpO2 and the pulse rate can be extracted from photoplethysmography (PPG signals. However, the accuracy of the extraction is directly affected by the quality of the signal obtained and the peak of the signal identified; therefore, a hybrid wavelet-based method is proposed in this study. Firstly, we suppressed the partial motion artifacts and corrected the baseline drift by using a wavelet method based on the principle of wavelet multiresolution. And then, we designed a quadratic spline wavelet modulus maximum algorithm to identify the PPG peaks automatically. To evaluate this hybrid method, a reflective pulse oximeter was used to acquire ten subjects’ PPG signals under sitting, raising hand, and gently walking postures, and the peak recognition results on the raw signal and on the corrected signal were compared, respectively. The results showed that the hybrid method not only corrected the morphologies of the signal well but also optimized the peaks identification quality, subsequently elevating the measurement accuracy of SpO2 and the pulse rate. As a result, our hybrid wavelet-based method profoundly optimized the evaluation of respiratory function and heart rate variability analysis.

A Hybrid Wavelet-Based Method for the Peak Detection of Photoplethysmography Signals.

Science.gov (United States)

Li, Suyi; Jiang, Shanqing; Jiang, Shan; Wu, Jiang; Xiong, Wenji; Diao, Shu

2017-01-01

The noninvasive peripheral oxygen saturation (SpO 2 ) and the pulse rate can be extracted from photoplethysmography (PPG) signals. However, the accuracy of the extraction is directly affected by the quality of the signal obtained and the peak of the signal identified; therefore, a hybrid wavelet-based method is proposed in this study. Firstly, we suppressed the partial motion artifacts and corrected the baseline drift by using a wavelet method based on the principle of wavelet multiresolution. And then, we designed a quadratic spline wavelet modulus maximum algorithm to identify the PPG peaks automatically. To evaluate this hybrid method, a reflective pulse oximeter was used to acquire ten subjects' PPG signals under sitting, raising hand, and gently walking postures, and the peak recognition results on the raw signal and on the corrected signal were compared, respectively. The results showed that the hybrid method not only corrected the morphologies of the signal well but also optimized the peaks identification quality, subsequently elevating the measurement accuracy of SpO 2 and the pulse rate. As a result, our hybrid wavelet-based method profoundly optimized the evaluation of respiratory function and heart rate variability analysis.

A Hybrid Wavelet-Based Method for the Peak Detection of Photoplethysmography Signals

Science.gov (United States)

Jiang, Shanqing; Jiang, Shan; Wu, Jiang; Xiong, Wenji

2017-01-01

The noninvasive peripheral oxygen saturation (SpO2) and the pulse rate can be extracted from photoplethysmography (PPG) signals. However, the accuracy of the extraction is directly affected by the quality of the signal obtained and the peak of the signal identified; therefore, a hybrid wavelet-based method is proposed in this study. Firstly, we suppressed the partial motion artifacts and corrected the baseline drift by using a wavelet method based on the principle of wavelet multiresolution. And then, we designed a quadratic spline wavelet modulus maximum algorithm to identify the PPG peaks automatically. To evaluate this hybrid method, a reflective pulse oximeter was used to acquire ten subjects' PPG signals under sitting, raising hand, and gently walking postures, and the peak recognition results on the raw signal and on the corrected signal were compared, respectively. The results showed that the hybrid method not only corrected the morphologies of the signal well but also optimized the peaks identification quality, subsequently elevating the measurement accuracy of SpO2 and the pulse rate. As a result, our hybrid wavelet-based method profoundly optimized the evaluation of respiratory function and heart rate variability analysis. PMID:29250135

A Comparative Study of Standardized Infinity Reference and Average Reference for EEG of Three Typical Brain States

Directory of Open Access Journals (Sweden)

Gaoxing Zheng

2018-03-01

Full Text Available The choice of different reference electrodes plays an important role in deciphering the functional meaning of electroencephalography (EEG signals. In recent years, the infinity zero reference using the reference electrode standard technique (REST has been increasingly applied, while the average reference (AR was generally advocated as the best available reference option in previous classical EEG studies. Here, we designed EEG experiments and performed a direct comparison between the influences of REST and AR on EEG-revealed brain activity features for three typical brain behavior states (eyes-closed, eyes-open and music-listening. The analysis results revealed the following observations: (1 there is no significant difference in the alpha-wave-blocking effect during the eyes-open state compared with the eyes-closed state for both REST and AR references; (2 there was clear frontal EEG asymmetry during the resting state, and the degree of lateralization under REST was higher than that under AR; (3 the global brain functional connectivity density (FCD and local FCD have higher values for REST than for AR under different behavior states; and (4 the value of the small-world network characteristic in the eyes-closed state is significantly (in full, alpha, beta and gamma frequency bands higher than that in the eyes-open state, and the small-world effect under the REST reference is higher than that under AR. In addition, the music-listening state has a higher small-world network effect than the eyes-closed state. The above results suggest that typical EEG features might be more clearly presented by applying the REST reference than by applying AR when using a 64-channel recording.

New method for extracting tumors in PET/CT images based on the probability distribution

International Nuclear Information System (INIS)

Nitta, Shuhei; Hontani, Hidekata; Hukami, Tadanori

2006-01-01

In this report, we propose a method for extracting tumors from PET/CT images by referring to the probability distribution of pixel values in the PET image. In the proposed method, first, the organs that normally take up fluorodeoxyglucose (FDG) (e.g., the liver, kidneys, and brain) are extracted. Then, the tumors are extracted from the images. The distribution of pixel values in PET images differs in each region of the body. Therefore, the threshold for detecting tumors is adaptively determined by referring to the distribution. We applied the proposed method to 37 cases and evaluated its performance. This report also presents the results of experiments comparing the proposed method and another method in which the pixel values are normalized for extracting tumors. (author)

Automatic removal of eye-movement and blink artifacts from EEG signals.

Science.gov (United States)

Gao, Jun Feng; Yang, Yong; Lin, Pan; Wang, Pei; Zheng, Chong Xun

2010-03-01

Frequent occurrence of electrooculography (EOG) artifacts leads to serious problems in interpreting and analyzing the electroencephalogram (EEG). In this paper, a robust method is presented to automatically eliminate eye-movement and eye-blink artifacts from EEG signals. Independent Component Analysis (ICA) is used to decompose EEG signals into independent components. Moreover, the features of topographies and power spectral densities of those components are extracted to identify eye-movement artifact components, and a support vector machine (SVM) classifier is adopted because it has higher performance than several other classifiers. The classification results show that feature-extraction methods are unsuitable for identifying eye-blink artifact components, and then a novel peak detection algorithm of independent component (PDAIC) is proposed to identify eye-blink artifact components. Finally, the artifact removal method proposed here is evaluated by the comparisons of EEG data before and after artifact removal. The results indicate that the method proposed could remove EOG artifacts effectively from EEG signals with little distortion of the underlying brain signals.

Evaluation of diagnostic thresholds dependability for tribologic signals received in the environment disturbed by vibroacoustic and functional signals

Directory of Open Access Journals (Sweden)

Lindstedt Paweł

2015-12-01

Full Text Available Determination of dependable diagnostic thresholds for tribologic signals received e.g. from antifriction bearings (in particular for insufficient number of measurements, only 4÷5 is a really difficult task due to complexity of working environment where such bearings are operated. Typical working environment for such objects must take account for operation time under various working conditions and accompanying (and disturbing signals, e.g. vibroacoustic ones. The sought assessment of the relationship between diagnostic signals and environmental noise can be determined from convolution of both diagnostic and environments signals that make up the complete set of received information. The convolution of these two series of signals can be obtained from an algorithm based on the Cauchy product. Then one has to find the coherence factor and the square of amplitude gain for the set of diagnostic signals with reference to various sets of signals received from environment, which makes it possible to evaluate cohesion of the investigated series of signals, thus their suitability to determine diagnostic threshold for tribologic signals intended for the analysis.

A novel murmur-based heart sound feature extraction technique using envelope-morphological analysis

Science.gov (United States)

Yao, Hao-Dong; Ma, Jia-Li; Fu, Bin-Bin; Wang, Hai-Yang; Dong, Ming-Chui

2015-07-01

Auscultation of heart sound (HS) signals serves as an important primary approach to diagnose cardiovascular diseases (CVDs) for centuries. Confronting the intrinsic drawbacks of traditional HS auscultation, computer-aided automatic HS auscultation based on feature extraction technique has witnessed explosive development. Yet, most existing HS feature extraction methods adopt acoustic or time-frequency features which exhibit poor relationship with diagnostic information, thus restricting the performance of further interpretation and analysis. Tackling such a bottleneck problem, this paper innovatively proposes a novel murmur-based HS feature extraction method since murmurs contain massive pathological information and are regarded as the first indications of pathological occurrences of heart valves. Adapting discrete wavelet transform (DWT) and Shannon envelope, the envelope-morphological characteristics of murmurs are obtained and three features are extracted accordingly. Validated by discriminating normal HS and 5 various abnormal HS signals with extracted features, the proposed method provides an attractive candidate in automatic HS auscultation.

A parametric framework for modelling of bioelectrical signals

CERN Document Server

Mughal, Yar Muhammad

2016-01-01

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

Nonstationary signals phase-energy approach-theory and simulations

CERN Document Server

Klein, R; Braun, S; 10.1006/mssp.2001.1398

2001-01-01

Modern time-frequency methods are intended to deal with a variety of nonstationary signals. One specific class, prevalent in the area of rotating machines, is that of harmonic signals of varying frequencies and amplitude. This paper presents a new adaptive phase-energy (APE) approach for time-frequency representation of varying harmonic signals. It is based on the concept of phase (frequency) paths and the instantaneous power spectral density (PSD). It is this path which represents the dynamic behaviour of the system generating the observed signal. The proposed method utilises dynamic filters based on an extended Nyquist theorem, enabling extraction of signal components with optimal signal-to-noise ratio. The APE detects the most energetic harmonic components (frequency paths) in the analysed signal. Tests on simulated signals show the superiority of the APE in resolution and resolving power as compared to STFT and wavelets wave- packet decomposition. The dynamic filters also enable the reconstruction of the ...

Reliability analysis for Atucha II reactor protection system signals

International Nuclear Information System (INIS)

Roca, Jose Luis

1996-01-01

Atucha II is a 745 MW Argentine Power Nuclear Reactor constructed by ENACE SA, Nuclear Argentine Company for Electrical Power Generation and SIEMENS AG KWU, Erlangen, Germany. A preliminary modular logic analysis of RPS (Reactor Protection System) signals was performed by means of the well known Swedish professional risk and reliability software named Risk-Spectrum taking as a basis a reference signal coded as JR17ER003 which command the two moderator loops valves. From the reliability and behavior knowledge for this reference signal follows an estimation of the reliability for the other 97 RPS signals. Because the preliminary character of this analysis Main Important Measures are not performed at this stage. Reliability is by the statistic value named unavailability predicted. The scope of this analysis is restricted from the measurement elements to the RPS buffer outputs. In the present context only one redundancy is analyzed so in the Instrumentation and Control area there no CCF (Common Cause Failures) present for signals. Finally those unavailability values could be introduced in the failure domain for the posterior complete Atucha II reliability analysis which includes all mechanical and electromechanical features. Also an estimation of the spurious frequency of RPS signals defined as faulty by no trip is performed

Reliability analysis for Atucha II reactor protection system signals

International Nuclear Information System (INIS)

Roca, Jose L.

2000-01-01

Atucha II is a 745 MW Argentine power nuclear reactor constructed by Nuclear Argentine Company for Electric Power Generation S.A. (ENACE S.A.) and SIEMENS AG KWU, Erlangen, Germany. A preliminary modular logic analysis of RPS (Reactor Protection System) signals was performed by means of the well known Swedish professional risk and reliability software named Risk-Spectrum taking as a basis a reference signal coded as JR17ER003 which command the two moderator loops valves. From the reliability and behavior knowledge for this reference signal follows an estimation of the reliability for the other 97 RPS signals. Because the preliminary character of this analysis Main Important Measures are not performed at this stage. Reliability is by the statistic value named unavailability predicted. The scope of this analysis is restricted from the measurement elements to the RPS buffer outputs. In the present context only one redundancy is analyzed so in the Instrumentation and Control area there no CCF (Common Cause Failures) present for signals. Finally those unavailability values could be introduced in the failure domain for the posterior complete Atucha II reliability analysis which includes all mechanical and electromechanical features. Also an estimation of the spurious frequency of RPS signals defined as faulty by no trip is performed. (author)

Anthelmintic activity of ethanolic leaf extract of Jasminum mesnyi

Directory of Open Access Journals (Sweden)

Vibhuti Dullu

2014-02-01

Full Text Available Objective: To evaluate the anthelmintic activity of ethanolic extract of leaves of Jasminum mesnyi. Methods: Anthelmintic activity was carried out on adult Indian earthworm Eisenia fetida. In this study, 20 mg/mL and 40 mg/mL concentrations of plant extract were tested which involved the time of paralysis and time of death of worm. Albendazole (10 mg/mL was taken as reference standard drug whereas distilled water was used as control. Results: The extract exhibited significant anthelmintic acitivity which was more in higher concentration extract. Conclusions: It was concluded from the present study that the plant exhibited significant anthelmintic activity.

Frequency tracking and variable bandwidth for line noise filtering without a reference.

Science.gov (United States)

Kelly, John W; Collinger, Jennifer L; Degenhart, Alan D; Siewiorek, Daniel P; Smailagic, Asim; Wang, Wei

2011-01-01

This paper presents a method for filtering line noise using an adaptive noise canceling (ANC) technique. This method effectively eliminates the sinusoidal contamination while achieving a narrower bandwidth than typical notch filters and without relying on the availability of a noise reference signal as ANC methods normally do. A sinusoidal reference is instead digitally generated and the filter efficiently tracks the power line frequency, which drifts around a known value. The filter's learning rate is also automatically adjusted to achieve faster and more accurate convergence and to control the filter's bandwidth. In this paper the focus of the discussion and the data will be electrocorticographic (ECoG) neural signals, but the presented technique is applicable to other recordings.

Trichilia monadelpha Bark Extracts Inhibit Carrageenan-Induced ...

African Journals Online (AJOL)

The present study was undertaken to evaluate the anti-inflammatory properties of aqueous (TWE), alcoholic (TAE) and petroleum ether extract (TPEE) of T. ... The reference anti-inflammatory drugs (diclofenac and dexamethasone) inhibited the chick-carrageenan-induced footpad oedema, with maximal inhibitions of ...

Microwave assisted extraction for trace element analysis of plant materials by ICP-AES

Energy Technology Data Exchange (ETDEWEB)

Borkowska-Burnecka, J. [Wroclaw Univ. (Poland). Inst. Chemii

2000-11-01

Application of microwave assisted extraction for the decomposition and dissolution of plant samples for trace metal determination by ICP-AES was examined. Dried onion, leaves of spinach beet and three reference materials CTA-OTL-1, CTA-VTL-2 and CL-1 were analyzed. Water, EDTA and hydrochloric acid (0.01, 0.10 and 1.0 M, respectively) were used as leaching solutions. The extraction efficiency was investigated by comparison of the results with those obtained after microwave wet digestion. HCl was found to be very suitable for quantitative extraction of B, Ba, Cd, Cu, Mn, Ni, Pb, Sr and Zn from the samples. For reference materials, the measured concentrations are well consistent with the certified values. The use of EDTA led to a complete extraction of B, Cd, Ni, Pb, Sr and Zn. Water was found to be a good leaching solution for boron. For extraction with HCl and EDTA, the RSD values for the concentrations measured were below 8% for most of the elements. (orig.)

Microwave assisted extraction for trace element analysis of plant materials by ICP-AES.

Science.gov (United States)

Borkowska-Burnecka, J

2000-11-01

Application of microwave assisted extraction for the decomposition and dissolution of plant samples for trace metal determination by ICP-AES was examined. Dried onion, leaves of spinach beet and three reference materials CTA-OTL-1, CTA-VTL-2 and CL-1 were analyzed. Water, EDTA and hydrochloric acid (0.01, 0.10 and 1.0 M, respectively) were used as leaching solutions. The extraction efficiency was investigated by comparison of the results with those obtained after microwave wet digestion. HCl was found to be very suitable for quantitative extraction of B, Ba, Cd, Cu, Mn, Ni, Pb, Sr and Zn from the samples. For reference materials, the measured concentrations are well consistent with the certified values. The use of EDTA led to a complete extraction of B, Cd, Ni, Pb, Sr and Zn. Water was found to be a good leaching solution for boron. For extraction with HCl and EDTA, the RSD values for the concentrations measured were below 8% for most of the elements.

Blackberry extract inhibits UVB-induced oxidative damage and inflammation through MAP kinases and NF-κB signaling pathways in SKH-1 mice skin

International Nuclear Information System (INIS)

Divya, Sasidharan Padmaja; Wang, Xin; Pratheeshkumar, Poyil; Son, Young-Ok; Roy, Ram Vinod; Kim, Donghern; Dai, Jin; Hitron, John Andrew; Wang, Lei; Asha, Padmaja; Shi, Xianglin; Zhang, Zhuo

2015-01-01

Extensive exposure of solar ultraviolet-B (UVB) radiation to skin induces oxidative stress and inflammation that play a crucial role in the induction of skin cancer. Photochemoprevention with natural products represents a simple but very effective strategy for the management of cutaneous neoplasia. In this study, we investigated whether blackberry extract (BBE) reduces chronic inflammatory responses induced by UVB irradiation in SKH-1 hairless mice skin. Mice were exposed to UVB radiation (100 mJ/cm 2 ) on alternate days for 10 weeks, and BBE (10% and 20%) was applied topically a day before UVB exposure. Our results show that BBE suppressed UVB-induced hyperplasia and reduced infiltration of inflammatory cells in the SKH-1 hairless mice skin. BBE treatment reduced glutathione (GSH) depletion, lipid peroxidation (LPO), and myeloperoxidase (MPO) in mouse skin by chronic UVB exposure. BBE significantly decreased the level of pro-inflammatory cytokines IL-6 and TNF-α in UVB-exposed skin. Likewise, UVB-induced inflammatory responses were diminished by BBE as observed by a remarkable reduction in the levels of phosphorylated MAP Kinases, Erk1/2, p38, JNK1/2 and MKK4. Furthermore, BBE also reduced inflammatory mediators such as cyclooxygenase-2 (COX-2), prostaglandin E 2 (PGE 2 ), and inducible nitric oxide synthase (iNOS) levels in UVB-exposed skin. Treatment with BBE inhibited UVB-induced nuclear translocation of NF-κB and degradation of IκBα in mouse skin. Immunohistochemistry analysis revealed that topical application of BBE inhibited the expression of 8-oxo-7, 8-dihydro-2′-deoxyguanosine (8-oxodG), cyclobutane pyrimidine dimers (CPD), proliferating cell nuclear antigen (PCNA), and cyclin D1 in UVB-exposed skin. Collectively, these data indicate that BBE protects from UVB-induced oxidative damage and inflammation by modulating MAP kinase and NF-κB signaling pathways. - Highlights: • Blackberry extract inhibits UVB-induced glutathione depletion. • Blackberry

Blackberry extract inhibits UVB-induced oxidative damage and inflammation through MAP kinases and NF-κB signaling pathways in SKH-1 mice skin

Energy Technology Data Exchange (ETDEWEB)

Divya, Sasidharan Padmaja; Wang, Xin; Pratheeshkumar, Poyil; Son, Young-Ok; Roy, Ram Vinod [Center for Research on Environmental Disease, University of Kentucky, 1095 VA Drive, Lexington, KY 40536 (United States); Department of Toxicology and Cancer Biology, University of Kentucky, 1095 VA Drive, Lexington, KY 40536 (United States); Kim, Donghern; Dai, Jin [Department of Toxicology and Cancer Biology, University of Kentucky, 1095 VA Drive, Lexington, KY 40536 (United States); Hitron, John Andrew; Wang, Lei [Center for Research on Environmental Disease, University of Kentucky, 1095 VA Drive, Lexington, KY 40536 (United States); Department of Toxicology and Cancer Biology, University of Kentucky, 1095 VA Drive, Lexington, KY 40536 (United States); Asha, Padmaja [National Centre for Aquatic Animal Health, Cochin University of Science and Technology, Cochin (India); Shi, Xianglin [Center for Research on Environmental Disease, University of Kentucky, 1095 VA Drive, Lexington, KY 40536 (United States); Department of Toxicology and Cancer Biology, University of Kentucky, 1095 VA Drive, Lexington, KY 40536 (United States); Zhang, Zhuo, E-mail: zhuo.zhang@uky.edu [Department of Toxicology and Cancer Biology, University of Kentucky, 1095 VA Drive, Lexington, KY 40536 (United States)

2015-04-01

Extensive exposure of solar ultraviolet-B (UVB) radiation to skin induces oxidative stress and inflammation that play a crucial role in the induction of skin cancer. Photochemoprevention with natural products represents a simple but very effective strategy for the management of cutaneous neoplasia. In this study, we investigated whether blackberry extract (BBE) reduces chronic inflammatory responses induced by UVB irradiation in SKH-1 hairless mice skin. Mice were exposed to UVB radiation (100 mJ/cm{sup 2}) on alternate days for 10 weeks, and BBE (10% and 20%) was applied topically a day before UVB exposure. Our results show that BBE suppressed UVB-induced hyperplasia and reduced infiltration of inflammatory cells in the SKH-1 hairless mice skin. BBE treatment reduced glutathione (GSH) depletion, lipid peroxidation (LPO), and myeloperoxidase (MPO) in mouse skin by chronic UVB exposure. BBE significantly decreased the level of pro-inflammatory cytokines IL-6 and TNF-α in UVB-exposed skin. Likewise, UVB-induced inflammatory responses were diminished by BBE as observed by a remarkable reduction in the levels of phosphorylated MAP Kinases, Erk1/2, p38, JNK1/2 and MKK4. Furthermore, BBE also reduced inflammatory mediators such as cyclooxygenase-2 (COX-2), prostaglandin E{sub 2} (PGE{sub 2}), and inducible nitric oxide synthase (iNOS) levels in UVB-exposed skin. Treatment with BBE inhibited UVB-induced nuclear translocation of NF-κB and degradation of IκBα in mouse skin. Immunohistochemistry analysis revealed that topical application of BBE inhibited the expression of 8-oxo-7, 8-dihydro-2′-deoxyguanosine (8-oxodG), cyclobutane pyrimidine dimers (CPD), proliferating cell nuclear antigen (PCNA), and cyclin D1 in UVB-exposed skin. Collectively, these data indicate that BBE protects from UVB-induced oxidative damage and inflammation by modulating MAP kinase and NF-κB signaling pathways. - Highlights: • Blackberry extract inhibits UVB-induced glutathione depletion. �

In vitro V(D)J recombination: signal joint formation.

Science.gov (United States)

Cortes, P; Weis-Garcia, F; Misulovin, Z; Nussenzweig, A; Lai, J S; Li, G; Nussenzweig, M C; Baltimore, D

1996-11-26

The first step of V(D)J recombination, specific cleavage at the recombination signal sequence (RSS), can be carried out by the recombination activating proteins RAG1 and RAG2. In vivo, the cleaved coding and signal ends must be rejoined to generate functional antigen receptors and maintain chromosomal integrity. We have investigated signal joint formation using deletion and inversion substrates in a cell free system. RAG1 and RAG2 alone or in combination were unable to generate signal joints. However, RAG1 and RAG2 complemented with nuclear extracts were able to recombine an extrachromosomal substrate and form precise signal joints. The in vitro reaction resembled authentic V(D)J recombination in being Ku-antigen-dependent.

Video Synchronization With Bit-Rate Signals and Correntropy Function

Directory of Open Access Journals (Sweden)

Igor Pereira

2017-09-01

Full Text Available We propose an approach for the synchronization of video streams using correntropy. Essentially, the time offset is calculated on the basis of the instantaneous transfer rates of the video streams that are extracted in the form of a univariate signal known as variable bit-rate (VBR. The state-of-the-art approach uses a window segmentation strategy that is based on consensual zero-mean normalized cross-correlation (ZNCC. This strategy has an elevated computational complexity, making its application to synchronizing online data streaming difficult. Hence, our proposal uses a different window strategy that, together with the correntropy function, allows the synchronization to be performed for online applications. This provides equivalent synchronization scores with a rapid offset determination as the streams come into the system. The efficiency of our approach has been verified through experiments that demonstrate its viability with values that are as precise as those obtained by ZNCC. The proposed approach scored 81 % in time reference classification against the equivalent 81 % of the state-of-the-art approach, requiring much less computational power.

Audio feature extraction using probability distribution function

Science.gov (United States)

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.

Antidiarrhoeal activity of leaf methanolic extract of Rauwolfia serpentina.

Science.gov (United States)

Ezeigbo, I I; Ezeja, M I; Madubuike, K G; Ifenkwe, D C; Ukweni, I A; Udeh, N E; Akomas, S C

2012-06-01

To evaluate the antidiarrhoeal property of methanol extract of the leaves of Rauwolfia serpentina (R. serpentina) in experimental diarrhoea induced by castor oil in mice. Doses of 100, 200 and 400 mg/kg R. serpentina leaf methanol extracts were administered to castor oil induced diarrhoea mice to determine its antidiarrhoeal activity. All doses of the extract and the reference drug atropine sulphate (3 mg/kg, i.p.) produced a dose-dependent reduction in intestinal weight and fluid volume. The extracts also significantly reduced the intestinal transit in charcoal meal test when compared to diphenoxylate Hcl (5 mg/kg, p.o.). The results show that the extract of R. serpentina leaves has a significant antidiarrhoeal activity and supports its traditional uses in herbal medicine.

Neutron activation analysis of medicinal plant extracts

International Nuclear Information System (INIS)

Vaz, S.M.; Saiki, M.; Vasconcellos, M.B.A.; Sertie, J.A.A.

1995-01-01

Instrumental neutron activation analysis was applied to the determination of the elements Br, Ca, Cl, Cs, Fe, K, La, Mg, Mn, Na, Rb and Zn in medicinal extracts obtained from Centella asiatica, Citrus aurantium L., Achyrolcline satureoides DC, Casearia sylvestris, Solano lycocarpum, Zingiber officinale Roscoe, Solidago microglossa and Stryphnondedron barbatiman plants. The elements Hg and Se were determined using radiochemical separation by means of retention of Se in HMD inorganic exchanger and solvent extraction of Hg by bismuth diethyldithiocarbamate solution. Precision and accuracy of the results were evaluated by analyzing biological reference materials. The therapeutic action of some elements found in plant extracts analyzed is briefly discussed. (author). 15 refs., 5 tabs

2-D DOA Estimation of LFM Signals Based on Dechirping Algorithm and Uniform Circle Array

Directory of Open Access Journals (Sweden)

K. B. Cui

2017-04-01

Full Text Available Based on Dechirping algorithm and uniform circle array(UCA, a new 2-D direction of arrival (DOA estimation algorithm of linear frequency modulation (LFM signals is proposed in this paper. The algorithm uses the thought of Dechirping and regards the signal to be estimated which is received by the reference sensor as the reference signal and proceeds the difference frequency treatment with the signal received by each sensor. So the signal to be estimated becomes a single-frequency signal in each sensor. Then we transform the single-frequency signal to an isolated impulse through Fourier transform (FFT and construct a new array data model based on the prominent parts of the impulse. Finally, we respectively use multiple signal classification (MUSIC algorithm and rotational invariance technique (ESPRIT algorithm to realize 2-D DOA estimation of LFM signals. The simulation results verify the effectiveness of the algorithm proposed.

Recognizing the degree of human attention using EEG signals from mobile sensors.

Science.gov (United States)

Liu, Ning-Han; Chiang, Cheng-Yu; Chu, Hsuan-Chin

2013-08-09

During the learning process, whether students remain attentive throughout instruction generally influences their learning efficacy. If teachers can instantly identify whether students are attentive they can be suitably reminded to remain focused, thereby improving their learning effects. Traditional teaching methods generally require that teachers observe students' expressions to determine whether they are attentively learning. However, this method is often inaccurate and increases the burden on teachers. With the development of electroencephalography (EEG) detection tools, mobile brainwave sensors have become mature and affordable equipment. Therefore, in this study, whether students are attentive or inattentive during instruction is determined by observing their EEG signals. Because distinguishing between attentiveness and inattentiveness is challenging, two scenarios were developed for this study to measure the subjects' EEG signals when attentive and inattentive. After collecting EEG data using mobile sensors, various common features were extracted from the raw data. A support vector machine (SVM) classifier was used to calculate and analyze these features to identify the combination of features that best indicates whether students are attentive. Based on the experiment results, the method proposed in this study provides a classification accuracy of up to 76.82%. The study results can be used as a reference for learning system designs in the future.

Adaptive Reference Levels in a Level-Crossing Analog-to-Digital Converter

Directory of Open Access Journals (Sweden)

Andrew C. Singer

2008-11-01

Full Text Available Level-crossing analog-to-digital converters (LC ADCs have been considered in the literature and have been shown to efficiently sample certain classes of signals. One important aspect of their implementation is the placement of reference levels in the converter. The levels need to be appropriately located within the input dynamic range, in order to obtain samples efficiently. In this paper, we study optimization of the performance of such an LC ADC by providing several sequential algorithms that adaptively update the ADC reference levels. The accompanying performance analysis and simulation results show that as the signal length grows, the performance of the sequential algorithms asymptotically approaches that of the best choice that could only have been chosen in hindsight within a family of possible schemes.

Plate performance in liquid-liquid extraction

International Nuclear Information System (INIS)

Wadkins, R.P.

1984-01-01

The relative effectiveness of perforated, nozzle, and burred plates from a capacity and extraction standpoint were studied in a pulsed liquid-liquid extraction system. The experiments were conducted in a 3.8 x 10 -2 m diameter column using a mixture of aluminum nitrate, nitric acid, and uranyl nitrate as the aqueous phase, and tributyl phosphate dissolved in AMSCO 125-90 W as the organic phase. The uranium was extracted from the aqueous phase to the organic phase. A standard cartridge was made for each type of plate and consisted of an assembly of plates spaced 5.08 x 10 -2 m apart. Each plate had 3.2 x 10 -3 m holes spaced on 6.1 x 10 -3 -m centers, and contained 23% free area. 16 references, 4 figures, 1 table

Optimum detection for extracting maximum information from symmetric qubit sets

International Nuclear Information System (INIS)

Mizuno, Jun; Fujiwara, Mikio; Sasaki, Masahide; Akiba, Makoto; Kawanishi, Tetsuya; Barnett, Stephen M.

2002-01-01

We demonstrate a class of optimum detection strategies for extracting the maximum information from sets of equiprobable real symmetric qubit states of a single photon. These optimum strategies have been predicted by Sasaki et al. [Phys. Rev. A 59, 3325 (1999)]. The peculiar aspect is that the detections with at least three outputs suffice for optimum extraction of information regardless of the number of signal elements. The cases of ternary (or trine), quinary, and septenary polarization signals are studied where a standard von Neumann detection (a projection onto a binary orthogonal basis) fails to access the maximum information. Our experiments demonstrate that it is possible with present technologies to attain about 96% of the theoretical limit

Fuel characteristics and pyrolysis studies of solvent extractables and residues from the evergreen shrub Calotropis procera

Energy Technology Data Exchange (ETDEWEB)

Erdman, M.D.; Gregorski, K.S.; Pavlath, A.E.

1984-01-01

Solvent extractables and residues from milkweed were evaluated as sources of liquid and solid fuels. Selected chemical, physical and pyrolytic determinations of the extractables and residues indicated that hexane extract is a potentially valuable, high density fuel resource. Methanol extract was shown to be a lower energy, highly toxic extract. Extracted residues were demonstrated to be valuable as solid fuel energy resources. 31 references.

Remote reference processing in MT survey using GPS clock; MT ho ni okeru GPS wo mochiita jikoku doki system

Energy Technology Data Exchange (ETDEWEB)

Yamane, K; Inoue, J; Takasugi, S [Geothermal Energy Research and Development Co. Ltd., Tokyo (Japan); Kosuge, S [DRICO Co. Ltd., Tokyo (Japan)

1996-05-01

A report is given about the application of a synchronizing system using clock signals from GPS satellites to a remote reference method which is a technique to reject noise from the MT method. This system uses the C/A code out of the L1 band waves from NAVSTAR/GPS satellites. The new system was operated in MT method-using investigations conducted at China Peninsula, Aichi Prefecture, and Izu Peninsula, Shizuoka Prefecture, with the reference points placed several 100km away in Iwate Prefecture on both occasions. It was found as the result that it is basically possible to catch signals from the GPS at any place, that the signals are accurate enough to be applied to time synchronization for the MT method, and that the signals assure a far remote reference method with a separation of several 100km between the sites involved. The referencing process at high frequencies whose feasibility had been doubted proved a success when highly correlated signals were exchanged between two stations over a distance of several 100km. 5 refs., 9 figs.

Digital signal processing for NDT

International Nuclear Information System (INIS)

Georgel, B.

1994-01-01

NDT begins to adapt and use the most recent developments of digital signal and image processing. We briefly sum up the main characteristics of NDT situations (particularly noise and inverse problem formulation) and comment on techniques already used or just emerging (SAFT, split spectrum, adaptive learning network, noise reference filtering, stochastic models, neural networks). This survey is focused on ultrasonics, eddy currents and X-ray radiography. The final objective of end users (availability of automatic diagnosis systems) cannot be achieved only by signal processing algorithms. A close cooperation with other techniques such as artificial intelligence has therefore to be implemented. (author). 20 refs

About the identification of signals at LHC

CERN Document Server

Mansoulié, Bruno

2015-01-01

This chapter describes the main ingredients and steps of the analysis used in the search for the Standard Model Higgs boson decaying into WW (l‎, l‎, νν‎) in the ATLAS experiment. It presents a short guide through a “modern” analysis, typical of the analyses performed on LHC data. The main ingredients are reviewed: irreducible and reducible backgrounds, background estimates from Monte Carlo or data-driven, signal and control regions, global fit, extraction of limits and signal, and the look-elsewhere effect.

The in vitro antimicrobial activity of fruit and leaf crude extracts of ...

African Journals Online (AJOL)

Objective: To evaluate the antimicrobial activity of Momordica charantia extracts on reference strains and microorganisms isolated from clinical specimens. Method: Petroleum ether and methanolic crude extracts of fruits and leaves of the plant were evaluated for antimicrobial activity using the disk diffusion method on four ...

Fixed kernel regression for voltammogram feature extraction

International Nuclear Information System (INIS)

Acevedo Rodriguez, F J; López-Sastre, R J; Gil-Jiménez, P; Maldonado Bascón, S; Ruiz-Reyes, N

2009-01-01

Cyclic voltammetry is an electroanalytical technique for obtaining information about substances under analysis without the need for complex flow systems. However, classifying the information in voltammograms obtained using this technique is difficult. In this paper, we propose the use of fixed kernel regression as a method for extracting features from these voltammograms, reducing the information to a few coefficients. The proposed approach has been applied to a wine classification problem with accuracy rates of over 98%. Although the method is described here for extracting voltammogram information, it can be used for other types of signals

Sources of inspiration? Making sense of scientific references in patents

NARCIS (Netherlands)

Callaert, Julie; Pellens, Maikel; van Looy, Bart

2013-01-01

Scientific references in patent documents can be used as indicators signaling science-technology interactions. Whether they reflect a direct ‘knowledge flow’ from science to technology is subject of debate. Based on 33 interviews with inventors at Belgian firms and knowledge-generating institutes

Toward multimodal signal detection of adverse drug reactions.

Science.gov (United States)

Harpaz, Rave; DuMouchel, William; Schuemie, Martijn; Bodenreider, Olivier; Friedman, Carol; Horvitz, Eric; Ripple, Anna; Sorbello, Alfred; White, Ryen W; Winnenburg, Rainer; Shah, Nigam H

2017-12-01

Improving mechanisms to detect adverse drug reactions (ADRs) is key to strengthening post-marketing drug safety surveillance. Signal detection is presently unimodal, relying on a single information source. Multimodal signal detection is based on jointly analyzing multiple information sources. Building on, and expanding the work done in prior studies, the aim of the article is to further research on multimodal signal detection, explore its potential benefits, and propose methods for its construction and evaluation. Four data sources are investigated; FDA's adverse event reporting system, insurance claims, the MEDLINE citation database, and the logs of major Web search engines. Published methods are used to generate and combine signals from each data source. Two distinct reference benchmarks corresponding to well-established and recently labeled ADRs respectively are used to evaluate the performance of multimodal signal detection in terms of area under the ROC curve (AUC) and lead-time-to-detection, with the latter relative to labeling revision dates. Limited to our reference benchmarks, multimodal signal detection provides AUC improvements ranging from 0.04 to 0.09 based on a widely used evaluation benchmark, and a comparative added lead-time of 7-22 months relative to labeling revision dates from a time-indexed benchmark. The results support the notion that utilizing and jointly analyzing multiple data sources may lead to improved signal detection. Given certain data and benchmark limitations, the early stage of development, and the complexity of ADRs, it is currently not possible to make definitive statements about the ultimate utility of the concept. Continued development of multimodal signal detection requires a deeper understanding the data sources used, additional benchmarks, and further research on methods to generate and synthesize signals. Copyright © 2017 Elsevier Inc. All rights reserved.

Novel determination of the total phenolic content in crude plant extracts by the use of 1H NMR of the -OH spectral region

International Nuclear Information System (INIS)

Nerantzaki, A.A.; Tsiafoulis, C.G.; Charisiadis, P.; Kontogianni, V.G.; Gerothanassis, I.P.

2011-01-01

A novel method for the determination of the total phenolic content using 1 H NMR spectroscopy in the -OH spectral region is presented. The use of DMSO-d 6 , which is an aprotic and strongly hydrogen bonding solvent, allows the 'appearance' of the relative sharp resonances of phenolic hydroxyl protons in the region of 8-14 ppm. The determination of the total phenolic -OH content requires three steps: (i) a 1D 1 H NMR spectrum is obtained in DMSO-d 6 ; (ii) a subsequent 1D 1 H NMR spectrum is recorded with irradiation of the residual water signal which results in the elimination or reduction of the phenolic -OH groups, due to proton exchange; and (iii) 1D 1 H NMR spectra are recorded with the addition of a progressively increased amount of salt, NaHCO 3 , which results in extensive linebroadening of the COOH resonances thus allowing the discrimination of the phenolic from the carboxylic acid signals. Integration, with respect to the internal standard TSP-d 4 , of the signal resonances between 14 and 8 ppm in spectrum (i) which are either eliminated or reduced in intensity in steps (ii) and (iii) allows the quantitation of the total phenolic content. The method was applied to model compounds, a mixture of them and several extracts of natural products. The results of the proposed 1 H NMR method were compared to the Folin-Ciocalteu (FC) reagent method. Additionally, since 1 H NMR refers to the total phenolic hydroxyl protons, a reaction factor, A e , is proposed that corresponds to the hydroxyl reactivity. The 1 H NMR method is rapid and accurate bearing the inherent advantages of the NMR spectroscopy and can be applied directly in complex extracts. Furthermore, it can be applied in a wide range of matrixes from crude plant extracts and food products to biological samples.

Xenopus egg extract: A powerful tool to study genome maintenance mechanisms.

Science.gov (United States)

Hoogenboom, Wouter S; Klein Douwel, Daisy; Knipscheer, Puck

2017-08-15

DNA repair pathways are crucial to maintain the integrity of our genome and prevent genetic diseases such as cancer. There are many different types of DNA damage and specific DNA repair mechanisms have evolved to deal with these lesions. In addition to these repair pathways there is an extensive signaling network that regulates processes important for repair, such as cell cycle control and transcription. Despite extensive research, DNA damage repair and signaling are not fully understood. In vitro systems such as the Xenopus egg extract system, have played, and still play, an important role in deciphering the molecular details of these processes. Xenopus laevis egg extracts contain all factors required to efficiently perform DNA repair outside a cell, using mechanisms conserved in humans. These extracts have been used to study several genome maintenance pathways, including mismatch repair, non-homologous end joining, ICL repair, DNA damage checkpoint activation, and replication fork stability. Here we describe how the Xenopus egg extract system, in combination with specifically designed DNA templates, contributed to our detailed understanding of these pathways. Copyright © 2017. Published by Elsevier Inc.

FEATURE EXTRACTION FOR EMG BASED PROSTHESES CONTROL

Directory of Open Access Journals (Sweden)

R. Aishwarya

2013-01-01

Full Text Available The control of prosthetic limb would be more effective if it is based on Surface Electromyogram (SEMG signals from remnant muscles. The analysis of SEMG signals depend on a number of factors, such as amplitude as well as time- and frequency-domain properties. Time series analysis using Auto Regressive (AR model and Mean frequency which is tolerant to white Gaussian noise are used as feature extraction techniques. EMG Histogram is used as another feature vector that was seen to give more distinct classification. The work was done with SEMG dataset obtained from the NINAPRO DATABASE, a resource for bio robotics community. Eight classes of hand movements hand open, hand close, Wrist extension, Wrist flexion, Pointing index, Ulnar deviation, Thumbs up, Thumb opposite to little finger are taken into consideration and feature vectors are extracted. The feature vectors can be given to an artificial neural network for further classification in controlling the prosthetic arm which is not dealt in this paper.

Selection of References in Wind Turbine Model Predictive Control Design

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Hovgaard, Tobias

2015-01-01

a model predictive controller for a wind turbine. One of the important aspects for a tracking control problem is how to setup the optimal reference tracking problem, as it might be relevant to track, e.g., the three concurrent references: optimal pitch angle, optimal rotational speed, and optimal power......Lowering the cost of energy is one of the major focus areas in the wind turbine industry. Recent research has indicated that wind turbine controllers based on model predictive control methods can be useful in obtaining this objective. A number of design considerations have to be made when designing....... The importance if the individual references differ depending in particular on the wind speed. In this paper we investigate the performance of a reference tracking model predictive controller with two different setups of the used optimal reference signals. The controllers are evaluated using an industrial high...

Phase locking of a 2.7 THz quantum cascade laser to a microwave reference

NARCIS (Netherlands)

Khosropanah, P.; Baryshev, A.; Zhang, W.; Jellema, W.; Hovenier, J.N.; Gao, J.R.; Klapwijk, T.M.; Paveliev, D.G.; Williams, B.S.; Kumar, S.; Hu, Q.; Reno, J.L.; Klein, B.; Hesler, J.L.

2009-01-01

We demonstrate the phase locking of a 2.7 THz metal–metal waveguide quantum cascade laser (QCL) to an external microwave signal. The reference is the 15th harmonic, generated by a semiconductor superlattice nonlinear device, of a signal at 182 GHz, which itself is generated by a multiplier chain

Phase locking of a 2.7 THz quantum cascade laser to a microwave reference

NARCIS (Netherlands)

Khosropanah, P.; Baryshev, A.; Zhang, W.; Jellema, W.; Hovenier, J. N.; Gao, J. R.; Klapwijk, T. M.; Paveliev, D. G.; Williams, B. S.; Kumar, S.; Hu, Q.; Reno, J. L.; Klein, B.; Hesler, J. L.

2009-01-01

We demonstrate the phase locking of a 2.7 THz metal-metal waveguide quantum cascade laser (QCL) to an external microwave signal. The reference is the 15th harmonic, generated by a semiconductor superlattice nonlinear device, of a signal at 182 GHz, which itself is generated by a multiplier chain

The anti-aging and anti-oxidation effects of tea water extract in Caenorhabditis elegans.

Science.gov (United States)

Fei, Tianyi; Fei, Jian; Huang, Fang; Xie, Tianpei; Xu, Jifeng; Zhou, Yi; Yang, Ping

2017-10-15

Tea includes puer tea, black tea, green tea and many others. By using model organism Caenorhabditis elegans, the anti-aging and anti-oxidation effects of tea water extract were systemically examined in this study. We found that water extract of puer tea, black tea and green tea all increased the lifespan of worms, postponed Aβ-induced progressive paralysis in Alzheimer's disease transgenic worms, and improved the tolerance of worms to the oxidative stress induced by heavy metal Cr 6+ . Moreover, the anti-oxidation effects of tea water extract at low concentration were different among 4 kinds of brands of green tea. The underlying mechanisms were further explored using genetically manipulated-mutant worms. The anti-oxidative stress effects of green tea water extract depend on the dietary restriction and germline signaling pathways, but not the FOXO and mitochondrial respiratory chain signals. Therefore, tea water extract provides benefits of anti-aging, anti-AD and anti-oxidation. Copyright © 2017. Published by Elsevier Inc.

Extraction of airways from CT (EXACT’09)

DEFF Research Database (Denmark)

Lo, Pechin Chien Pau; Ginneken, Bram van; Reinhardt, Joseph M.

2012-01-01

or not it is a correctly segmented part of the airway tree. Finally, the reference airway trees are constructed by taking the union of all correctly extracted branch segments. Fifteen airway tree extraction algorithms from different research groups are evaluated on a diverse set of 20 chest computed tomography (CT) scans...... of subjects ranging from healthy volunteers to patients with severe pathologies, scanned at different sites, with different CT scanner brands, models, and scanning protocols. Three performance measures covering different aspects of segmentation quality were computed for all participating algorithms. Results...

Determination of Cd in urine by cloud point extraction-tungsten coil atomic absorption spectrometry.

Science.gov (United States)

Donati, George L; Pharr, Kathryn E; Calloway, Clifton P; Nóbrega, Joaquim A; Jones, Bradley T

2008-09-15

Cadmium concentrations in human urine are typically at or below the 1 microgL(-1) level, so only a handful of techniques may be appropriate for this application. These include sophisticated methods such as graphite furnace atomic absorption spectrometry and inductively coupled plasma mass spectrometry. While tungsten coil atomic absorption spectrometry is a simpler and less expensive technique, its practical detection limits often prohibit the detection of Cd in normal urine samples. In addition, the nature of the urine matrix often necessitates accurate background correction techniques, which would add expense and complexity to the tungsten coil instrument. This manuscript describes a cloud point extraction method that reduces matrix interference while preconcentrating Cd by a factor of 15. Ammonium pyrrolidinedithiocarbamate and Triton X-114 are used as complexing agent and surfactant, respectively, in the extraction procedure. Triton X-114 forms an extractant coacervate surfactant-rich phase that is denser than water, so the aqueous supernatant is easily removed leaving the metal-containing surfactant layer intact. A 25 microL aliquot of this preconcentrated sample is placed directly onto the tungsten coil for analysis. The cloud point extraction procedure allows for simple background correction based either on the measurement of absorption at a nearby wavelength, or measurement of absorption at a time in the atomization step immediately prior to the onset of the Cd signal. Seven human urine samples are analyzed by this technique and the results are compared to those found by the inductively coupled plasma mass spectrometry analysis of the same samples performed at a different institution. The limit of detection for Cd in urine is 5 ngL(-1) for cloud point extraction tungsten coil atomic absorption spectrometry. The accuracy of the method is determined with a standard reference material (toxic metals in freeze-dried urine) and the determined values agree with

Extra virgin olive oil polyphenolic extracts downregulate inflammatory responses in LPS-activated murine peritoneal macrophages suppressing NFκB and MAPK signalling pathways.

Science.gov (United States)

Cárdeno, A; Sánchez-Hidalgo, M; Aparicio-Soto, M; Sánchez-Fidalgo, S; Alarcón-de-la-Lastra, C

2014-06-01

Extra virgin olive oil (EVOO) is obtained from the fruit of the olive tree Olea europaea L. Phenolic compounds present in EVOO have recognized anti-oxidant and anti-inflammatory properties. However, the activity of the total phenolic fraction extracted from EVOO and the action mechanisms involved are not well defined. The present study was designed to evaluate the potential anti-inflammatory mechanisms of the polyphenolic extract (PE) from EVOO on LPS-stimulated peritoneal murine macrophages. Nitric oxide (NO) production was analyzed by the Griess method and intracellular reactive oxygen species (ROS) by fluorescence analysis. Moreover, changes in the protein expression of the pro-inflammatory enzymes, inducible nitric oxide synthase (iNOS), cyclooxygenase (COX)-2 and microsomal prostaglandin E synthase-1 (mPGES-1), as well as the role of nuclear transcription factor kappa B (NFκB) and mitogen-activated protein kinase (MAPK) signalling pathways, were analyzed by Western blot. PE from EVOO reduced LPS-induced oxidative stress and inflammatory responses through decreasing NO and ROS generation. In addition, PE induced a significant down-regulation of iNOS, COX-2 and mPGES-1 protein expressions, reduced MAPK phosphorylation and prevented the nuclear NFκB translocation. This study establishes that PE from EVOO possesses anti-inflammatory activities on LPS-stimulated murine macrophages.

Automatic recognition of smoke-plume signatures in lidar signal

Science.gov (United States)

Utkin, Andrei B.; Lavrov, Alexander; Vilar, Rui

2008-10-01

A simple and robust algorithm for lidar-signal classification based on the fast extraction of sufficiently pronounced peaks and their recognition with a perceptron, whose efficiency is enhanced by a fast nonlinear preprocessing that increases the signal dimension, is reported. The method allows smoke-plume recognition with an error rate as small as 0.31% (19 misdetections and 4 false alarms in analyzing a test set of 7409 peaks).

Multiple Signal Classification for Gravitational Wave Burst Search

Science.gov (United States)

Cao, Junwei; He, Zhengqi

2013-01-01

This work is mainly focused on the application of the multiple signal classification (MUSIC) algorithm for gravitational wave burst search. This algorithm extracts important gravitational wave characteristics from signals coming from detectors with arbitrary position, orientation and noise covariance. In this paper, the MUSIC algorithm is described in detail along with the necessary adjustments required for gravitational wave burst search. The algorithm's performance is measured using simulated signals and noise. MUSIC is compared with the Q-transform for signal triggering and with Bayesian analysis for direction of arrival (DOA) estimation, using the Ω-pipeline. Experimental results show that MUSIC has a lower resolution but is faster. MUSIC is a promising tool for real-time gravitational wave search for multi-messenger astronomy.

Experiments on Classification of Electroencephalography (EEG Signals in Imagination of Direction using Stacked Autoencoder

Directory of Open Access Journals (Sweden)

Kenta Tomonaga

2017-08-01

Full Text Available This paper presents classification methods for electroencephalography (EEG signals in imagination of direction measured by a portable EEG headset. In the authorsr previous studies, principal component analysis extracted significant features from EEG signals to construct neural network classifiers. To improve the performance, the authors have implemented a Stacked Autoencoder (SAE for the classification. The SAE carries out feature extraction and classification in a form of multi-layered neural network. Experimental results showed that the SAE outperformed the previous classifiers.

Conditional Random Fields for Morphological Analysis of Wireless ECG Signals

Science.gov (United States)

Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin

2015-01-01

Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel approach to the problem of extracting the morphological structure of ECG signals based on the use of dynamically structured conditional random field (CRF) models. We apply this framework to the problem of extracting morphological structure from wireless ECG sensor data collected in a lab-based study of habituated cocaine users. Our results show that the proposed CRF-based approach significantly out-performs independent prediction models using the same features, as well as a widely cited open source toolkit. PMID:26726321

Corn Silk Extract and Its Bioactive Peptide Ameliorated Lipopolysaccharide-Induced Inflammation in Mice via the Nuclear Factor-κB Signaling Pathway.

Science.gov (United States)

Ho, Tin-Yun; Li, Chia-Cheng; Lo, Hsin-Yi; Chen, Feng-Yuan; Hsiang, Chien-Yun

2017-02-01

Bioactive peptides derived from foods have shown beneficial anti-inflammatory potential. Inhibitory κB kinase-β (IKKβ) plays a crucial role in the activation of nuclear factor-κB (NF-κB), a transcription factor involved in inflammation. Here we applied proteomic and bioinformatics approaches to identify anti-inflammatory peptides that target IKKβ from corn silk. Corn silk extract significantly suppressed lipopolysaccharide (LPS)-induced NF-κB activities [(1.7 ± 0.2)-fold vs (3.0 ± 0.6)-fold, p corn silk also suppressed LPS-induced NF-κB activities [(1.1 ± 0.3)-fold vs 3.3 ± 0.5 fold, p corn silk extract and trypsin hydrolysate significantly inhibited LPS-induced interleukin-1β (IL-1β) production by 58.3 ± 4.5 and 55.1 ± 7.4%, respectively. A novel peptide, FK2, docked into the ATP-binding pocket of IKKβ, was further identified from trypsin hydrolysis of corn silk. FK2 inhibited IKKβ activities, IκB phosphorylation, and subsequent NF-κB activation [(2.3 ± 0.4)-fold vs (5.5 ± 0.4)-fold, p corn silk displayed anti-inflammatory abilities. In addition, we first identified an anti-inflammatory peptide FK2 from corn silk. Moreover, the anti-inflammatory effect of FK2 might be through IKKβ-NF-κB signaling pathways.

Microfluidic extraction and microarray detection of biomarkers from cancer tissue slides

Science.gov (United States)

Nguyen, H. T.; Dupont, L. N.; Jean, A. M.; Géhin, T.; Chevolot, Y.; Laurenceau, E.; Gijs, M. A. M.

2018-03-01

We report here a new microfluidic method allowing for the quantification of human epidermal growth factor receptor 2 (HER2) expression levels from formalin-fixed breast cancer tissues. After partial extraction of proteins from the tissue slide, the extract is routed to an antibody (Ab) microarray for HER2 titration by fluorescence. Then the HER2-expressing cell area is evaluated by immunofluorescence (IF) staining of the tissue slide and used to normalize the fluorescent HER2 signal measured from the Ab microarray. The number of HER2 gene copies measured by fluorescence in situ hybridization (FISH) on an adjacent tissue slide is concordant with the normalized HER2 expression signal. This work is the first study implementing biomarker extraction and detection from cancer tissue slides using microfluidics in combination with a microarray system, paving the way for further developments towards multiplex and precise quantification of cancer biomarkers.

Microfabricated Reference Electrodes and their Biosensing Applications

Directory of Open Access Journals (Sweden)

M. Jamal Deen

2010-03-01

Full Text Available Over the past two decades, there has been an increasing trend towards miniaturization of both biological and chemical sensors and their integration with miniaturized sample pre-processing and analysis systems. These miniaturized lab-on-chip devices have several functional advantages including low cost, their ability to analyze smaller samples, faster analysis time, suitability for automation, and increased reliability and repeatability. Electrical based sensing methods that transduce biological or chemical signals into the electrical domain are a dominant part of the lab-on-chip devices. A vital part of any electrochemical sensing system is the reference electrode, which is a probe that is capable of measuring the potential on the solution side of an electrochemical interface. Research on miniaturization of this crucial component and analysis of the parameters that affect its performance, stability and lifetime, is sparse. In this paper, we present the basic electrochemistry and thermodynamics of these reference electrodes and illustrate the uses of reference electrodes in electrochemical and biological measurements. Different electrochemical systems that are used as reference electrodes will be presented, and an overview of some contemporary advances in electrode miniaturization and their performance will be provided.

Unconventional shale gas extraction: present and future affects

OpenAIRE

Mohajan, Haradhan

2012-01-01

In the 1990s the extraction of unconventional shale gas extraction increases in the USA due to national and global demand of energy. The expansion of shale gas production will provide low carbon economy, therefore it is a positive side of low greenhouse gas emissions in the atmosphere and considering the benefit sides it has been referred to as a bridging fuel. Horizontal drilling and hydraulic fracturing are the two technologies by the combination with one another; provide the potential to ...

Hearing the Sound in the Brain: Influences of Different EEG References

Directory of Open Access Journals (Sweden)

Dan Wu

2018-03-01

Full Text Available If the scalp potential signals, the electroencephalogram (EEG, are due to neural “singers” in the brain, how could we listen to them with less distortion? One crucial point is that the data recording on the scalp should be faithful and accurate, thus the choice of reference electrode is a vital factor determining the faithfulness of the data. In this study, music on the scalp derived from data in the brain using three different reference electrodes were compared, including approximate zero reference—reference electrode standardization technique (REST, average reference (AR, and linked mastoids reference (LM. The classic music pieces in waveform format were used as simulated sources inside a head model, and they were forward calculated to scalp as standard potential recordings, i.e., waveform format music from the brain with true zero reference. Then these scalp music was re-referenced into REST, AR, and LM based data, and compared with the original forward data (true zero reference. For real data, the EEG recorded in an orthodontic pain control experiment were utilized for music generation with the three references, and the scale free index (SFI of these music pieces were compared. The results showed that in the simulation for only one source, different references do not change the music/waveform; for two sources or more, REST provide the most faithful music/waveform to the original ones inside the brain, and the distortions caused by AR and LM were spatial locations of both source and scalp electrode dependent. The brainwave music from the real EEG data showed that REST and AR make the differences of SFI between two states more recognized and found the frontal is the main region that producing the music. In conclusion, REST can reconstruct the true signals approximately, and it can be used to help to listen to the true voice of the neural singers in the brain.