Artificial Signals Research Articles

The Removal of Artificially Generated Polarization in SHARP Maps

ABSTRACTWe characterize the problem of artificial polarization for the Submillimeter High Angular Resolution Polarimeter (SHARP) through the use of simulated data and observations made at the Caltech Submillimeter Observatory (CSO). These erroneous, artificial polarization signals are introduced into the data through misalignments in the bolometer subarrays and by pointing drifts present during the data-taking procedure. An algorithm is outlined here to address this problem and correct for it, provided that one can measure the degree of the subarray misalignments and telescope pointing drifts. Tests involving simulated sources of Gaussian intensity profile indicate that the level of introduced artificial polarization is highly dependent on the angular size of the source. Despite this, the correction algorithm is effective at removing up to 60% of the artificial polarization during these tests. The analysis of Jupiter data taken in 2006 January and 2007 February indicates a mean polarization of 1.44% ± 0.04% and 0.95% ± 0.09%, respectively. The application of the correction algorithm yields mean reductions in the polarization of approximately 0.15% and 0.03% for the 2006 and 2007 data sets, respectively.

Optimal Design of a Molecular Recognizer: Molecular Recognition as a Bayesian Signal Detection Problem

Numerous biological functions-such as enzymatic catalysis, the immune response system, and the DNA-protein regulatory network-rely on the ability of molecules to specifically recognize target molecules within a large pool of similar competitors in a noisy biochemical environment. Using the basic framework of signal detection theory, we treat the molecular recognition process as a signal detection problem and examine its overall performance. Thus, we evaluate the optimal properties of a molecular recognizer in the presence of competition and noise. Our analysis reveals that the optimal design undergoes a "phase transition" as the structural properties of the molecules and interaction energies between them vary. In one phase, the recognizer should be complementary in structure to its target (like a lock and a key), while in the other, conformational changes upon binding, which often accompany molecular recognition, enhance recognition quality. Using this framework, the abundance of conformational changes may be explained as a result of increasing the fitness of the recognizer. Furthermore, this analysis may be used in future design of artificial signal processing devices based on biomolecules.

Synthetic signal injection using inductive coupling

Conversion of MR signals into units of metabolite concentration requires a very high level of diligence to account for the numerous parameters and transformations that affect the proportionality between the quantity of excited nuclei in the acquisition volume and the integrated area of the corresponding peak in the spectrum. We describe a method that eases this burden with respect to the transformations that occur during and following data acquisition. The conceptual approach is similar to the ERETIC method, which uses a pre-calibrated, artificial reference signal as a calibration factor to accomplish the conversion. The distinguishing feature of our method is that the artificial signal is introduced strictly via induction, rather than radiation. We tested a prototype probe that includes a second RF coil rigidly positioned close to the receive coil so that there was constant mutual inductance between them. The artificial signal was transmitted through the second RF coil and acquired by the receive coil in parallel with the real signal. Our results demonstrate that the calibration factor is immune to changes in sample resistance. This is a key advantage because it removes the cumbersome requirement that coil loading conditions be the same for the calibration sample as for experimental samples. The method should be adaptable to human studies and could allow more practical and accurate quantification of metabolite content.

Data-based forecasting of beach volumes on monthly to yearly timescales

Data-based methods for forecasting beach volumes are tested using ground-measured bathymetry from Duck, North Carolina, comprising 26 profiles, 20 year duration and one-month resolution. Derived beach volume time series show weak seasonal and strong event signals. The forecasting methods used are: Holt–Winters (standard and modified), three types of linear regression, and a default forecast in which the latest measurement persists unchanged into the future. Improved forecast accuracies are obtained by two modifications to Holt–Winters, involving an autocorrelation correction and long-term trend-damping, and by smoothing the fitting data using running medians or wavelet approximations. Beach volume forecasts are tested mainly at monthly intervals up to 12 months ahead, with further tests at up to 36 months ahead. Overall, modified Holt–Winters performs best and the default forecast second-best. With an added artificial seasonal signal, modified Holt–Winters outperforms the other methods more substantially.

Blind estimation method of reverberation time based on concept of modulation transfer function

This paper proposes a method for blindly estimating the reverberation time based on the concept of the modulation transfer function (MTF). This method estimates the reverberation time from the reverberant signal without measuring room acoustics. In the MTF-based speech dereverberation method, proposed by the authors, a process for estimating a parameter related to the reverberation time was incorporated. In this paper, we investigate whether the estimation process, previously presented by authors, works as a blind estimation method and point out a problem with their method. We then propose a new method for blindly estimating the reverberation time to resolve the problem. In the proposed method, the reverberation time is correctly estimated by inverse-MTF filtering in the modulation frequency domain. We evaluated the proposed method with their method using both artificial MTF-based signals and speech signals to show how well the proposed method correctly estimates the reverberation time in artificial reverberant environments. Results suggested that the proposed method correctly estimates reverberation times from the observed reverberant signals. [Work supported by a Grant-in-Aid for Science Research from the Japanese Ministry of Education (No. 18680017).]

Sound insulation of artificial and natural sound signals in reeds habitats

From the point of view of acoustical communication, dense fields of reeds are strong acoustical filtre which distorts original sound signal. In this research the rate of sound signals sound insulation in massives of reeds was estimated. As a models were used artificially synthesized, modulated by frequency signals of three frequency lines: 1‐2 kHz, 2‐4 kHz, and 4‐8 kHz with duration of 0.1 and 0.25 msec. For comparison were also used elements of bird songs. The least damping was noted in signals with descending frequency modulation in 8 ‐ 4 kHz range in the upper level of reeds (6 db on 10 m). The most damping were noted in signals with descending frequency modulation in 2 ‐ 1 kHz in the middle level of juncaceous massive(18 db to 10 m). The signals with frequency modulation of 4‐2 kHz were extending better in the upper level of reeds (7‐8 db), whereas in the lower and upper levels were noted dependence of damping rate on duration of sound impulse ‐ the signals with duration of 0.25 mec were damping less than signals with duration of 0.1 msec . The elements of bird songs during their emission in the middle level of juncaceous massive were damping by 15‐20 db on 10 m.

Periplasmic expression and recovery of human interferon gamma in Escherichia coli

A synthetic human interferon gamma (hIFN-γ) gene was fused to SP1 and SP3, two Sec-dependent artificial signal peptides to transport the hIFN-γ to the periplasm of Escherichia coli BL21-SI. The processing efficiency of both SP1-hIFN-γ and SP3-hIFN-γ was dependent on the culture medium as well as the post-induction temperature. Both precursors were processed completely when cells were cultured using minimal medium and a post-induction temperature of 32.5°C, and only the processed hIFN-γ was detected. The SP3 signal peptide was more efficient than SP1 for the secretion of hIFN-γ. Sixty percent of the total hIFN-γ was secreted to the periplasm using the SP3 signal peptide and a post-induction temperature of 20°C. Using Tris–sucrose–dithiothreitol (TSD) hypertonic buffer, the periplasmic soluble hINF-γ was recovered with a purity of 85%.

High-Level Secretion of a Chimeric Thermostable Lichenase from Bacillus subtilis by Screening of Site-Mutated Signal Peptides with Structural Alterations

A chimeric gene mHG (669 bp) was constructed by substitution of Clostridium thermocellum ZJL4 lichenase (CG) N-terminal fragment (except its signal sequence) for the counterpart of Bacillus sp. A3 lichenase (BG). To acquire high-level secretion of the chimeric lichenase (mHG) in Bacillus subtilis, a series of site-mutated signal peptides were designed. The activity of mHG, which was directed by an artificial hydrophobic signal peptide H1 (MMARKIAGMATSLLVIFSSSAVA) from cytoplasm into growth medium, reached 80.56 U/ml after 22-h incubation, indicating that signal peptide hydrophobicity appears to be critical for early stages in mHG export. By purification of the mHG (approximately 25.3 kDa) from cultures of B. subtilis (pBSG-H1), enzymatic property assays showed that the common optima for mHG were 70 degrees C and pH 5.0. The residual activity of mHG at 90 degrees C for 10 min was 83.45% of its maximum activity, which was almost similar to that of CG (90 degrees C, 10 min, 84.33%). This constructed shuttle expression vector with a novel signal peptide exhibited its applicability for high-level production of heterologous proteins from B. subtilis. Moreover, the high-level secreted mHG with relatively high thermostability could be a potential candidate for feed industrial applications.

Self-Repairing and Adaptive Tracking for MIMO Systems with Sensor Failures

This paper presents a new self-repairing control system (SRCS) for unknown stable multiple-input-multiple-output (MIMO) plants with sensor failures. The proposed method can automatically switch from the faulty sensors to the healthy ones if the sensor failures occur. Only the artificial test signals and the integrators are utilized to detect the sensor failures. Hence, the SRCS requires no mathematical model of the plant. Furthermore, the adaptive λ-tracker is introduced not only to cope with uncertainties in parameters but also to eliminate the bias effects of the injected test signals.

Two-dimensional signal reconstruction: The correlation sampling method

An accurate approach for reconstructing a time-dependent two-dimensional signal from non-synchronized time series recorded at points located on a grid is discussed. The method, denoted as correlation sampling, improves the standard conditional sampling approach commonly employed in the study of turbulence in magnetoplasma devices. Its implementation is illustrated in the case of an artificial time-dependent signal constructed using a fractal algorithm that simulates a fluctuating surface. A statistical method is also discussed for distinguishing coherent (i.e., collective) from purely random (noisy) behavior for such two-dimensional fluctuating phenomena.

Duration learning for analysis of nanopore ionic current blockades

BackgroundIonic current blockade signal processing, for use in nanopore detection, offers a promising new way to analyze single molecule properties, with potential implications for DNA sequencing. The alpha-Hemolysin transmembrane channel interacts with a translocating molecule in a nontrivial way, frequently evidenced by a complex ionic flow blockade pattern. Typically, recorded current blockade signals have several levels of blockade, with various durations, all obeying a fixed statistical profile for a given molecule. Hidden Markov Model (HMM) based duration learning experiments on artificial two-level Gaussian blockade signals helped us to identify proper modeling framework. We then apply our framework to the real multi-level DNA hairpin blockade signal.ResultsThe identified upper level blockade state is observed with durations that are geometrically distributed (consistent with an a physical decay process for remaining in any given state). We show that mixture of convolution chains of geometrically distributed states is better for presenting multimodal long-tailed duration phenomena. Based on learned HMM profiles we are able to classify 9 base-pair DNA hairpins with accuracy up to 99.5% on signals from same-day experiments.ConclusionWe have demonstrated several implementations for de novo estimation of duration distribution probability density function with HMM framework and applied our model topology to the real data. The proposed design could be handy in molecular analysis based on nanopore current blockade signal.

Learning the Language of Bacteria

Bacteria "talk" with each other by using small molecules that enable individuals in a population to coordinate their behavior. This language is termed quorum sensing. Bacterial pathogens may use this language to decide when to attack a host organism; therefore, the development of artificial signals to interfere with this signal process has become an area of intense chemical research.

Escape performance decreases during ontogeny in wild crickets

Increasing the ecological relevance of studies relating to the performance of organisms has been a central issue for functional biologists over the last few years. Of particular concern are changes in performance throughout the life cycle as selective forces act differently on various life stages. We addressed this issue experimentally by following ontogenic variations in the escape performance of crickets threatened by artificial predatory signals. We measured their performance under natural settings, which is a necessary approach yet one that is undocumented in insects. We analysed numeric film sequences obtained using a high-speed video camera at 1000 frames s(-1) to quantify wild cricket performance and behaviour in the field. We detected significant differences in cricket escape performance throughout ontogeny. Escape performances were higher in juvenile crickets than older instars. Complementary behavioural measurements for escaping crickets suggest that these variations may be related to the lower predatory risk perceived by large adults than by juveniles. We expect that our analysis of size-refuge will also improve our understanding in the development of performance, given its importance in community and population ecology theories.

Markov and Semi-Markov Switching of Source Appearances for Nonstationary Independent Component Analysis

Independent component analysis (ICA) is currently the most popularly used approach to blind source separation (BSS), the problem of recovering unknown source signals when their mixtures are observed but the actual mixing process is unknown. Many ICA algorithms assume that a fixed set of source signals consistently exists in mixtures throughout the time-series to be examined. However, real-world signals often have such difficult nonstationarity that each source signal abruptly appears or disappears, thus the set of active sources dynamically changes with time. In this paper, we propose switching ICA (SwICA), which focuses on such situations. The proposed approach is based on the noisy ICA formulated as a generative model. We employ a special type of hidden Markov model (HMM) to represent such prior knowledge that the source may abruptly appear or disappear with time. The special HMM setting t hen provides an effect ofvariable selection in a dynamic way. We use the variational Bayes (VB) method to derive an effective approximation of Bayesian inference for this model. In simulation experiments using artificial and realistic source signals, the proposed method exhibited performance superior to existing methods, especially in the presence of noise. The compared methods include the natural-gradient ICA with a nonholonomic constraint, and the existing ICA method incorporating an HMM source model, which aims to deal with general nonstationarities that may exist in source signals. In addition, the proposed method could successfully recover the source signals even when the total number of true sources was overestimated or was larger than that of mixtures. We also propose a modification of the basic Markov model into a semi-Markov model, and show that the semi-Markov one is more effective for robust estimation of the source appearance.

In vitro evaluation of coronary stents and in-stent stenosis using a dynamic cardiac phantom and a 64-detector row CT scanner

The aim of the study was to examine the ability of a 64-slice MDCT to detect in-stent stenoses in an ex vivo model of coronary stents. Five different stents (Liberté, Boston Scientific; Driver, Medtronic; Multi-Link Vision, Guidant; Taxus Express, Boston Scientific; Cypher, Cordis) were examined using a dynamic cardiac phantom. The stents were pulled over a vessel model that consists of a polymer tube with diameters of 3.0, 3.5, and 4.0 mm and four different degrees of stenoses (0%; 30%; 50%; 70-80%). This model was moved with a rate of 60 bpm to mimic cardiac motion. To assess the degree of artificial signal reduction (artificial reduction of attenuation (ARA)) by the different stents, attenuation values were measured in the vessel outside the stent, and in the non-stenotic vessel inside the stent. Furthermore the grade of stenosis was assessed by two clinical observers. Highest ARA was found for the Cypher Stent (35 HU), whereas the Liberté Stent presented the lowest ARA (16 HU). Depending on the stent and the vessel diameter, up to 87.5% of the stenoses were correctly diagnosed. In the 3.0 and 3.5 mm vessels, a nonstenotic or low-grade stenotic vessel was diagnosed as intermediate or high-grade stenosis in 22.5%, whereas in the 4.0 mm vessels, this kind of overestimation did not occur. A 50% stenosis was diagnosed as a 30% stenosis in 30%. On the other hand, high-grade stenoses were underestimated in only 10%. On a four-point scale, the average deviation from the real grade of stenosis was 0.21 for the Liberté stent, 0.54 for the Taxus Express stent, 0.29 for Driver stent, 0.62 for the Multi-Link Vision stent, and 0.37 for the Cypher stent. In a dynamic cardiac phantom model, high grade stenoses in vessels with a diameter of 4 mm could be reliably detected irrespective of the stent type used in this study. Vice versa, high grade stenoses (> or = 50%) could only be ruled out with certainty in vessels with a diameter of 4 mm. In smaller vessels, the ability to correctly diagnose high-grade stenoses was dependent on the type of stent and the imaging artifacts associated with it.

PERFORMANCE EVALUATION OF PULSED RADAR IDENTIFICATION USING HIDDEN MARKOV MODEL

Due to the increasing complexity in modern radar systems, it has become apparent that new ways of classify received signals are required. In this paper, the performance of a proposed method for radar system identification using hidden Markov model (HMM) is evaluated. In this method, a given radar system is modeled as a finite state automaton. In so, doing, it is possible to uncover the underlying system processes in a probabilistic fashion using hidden Markov models. Artificial deterministic signals are used to show that HMMs can provide adequate signal recognition. It will be shown that a perfect exists that is directly related to the number of symbols per period. A slightly adjusted version of this perfect model provides low false recognition rates in a threat library consisting of three models so long as the observation errors do not become too frequent. The simulation results show that if the observation errors are introduced, then, it becomes necessary to retrain the HMM with an error corrupted version of the original training sequence in order to improve the model's robustness.

주요성분분석과 상호정보 추정에 의한 입력변수선택

This paper presents an efficient input variable selection method using both principal component analysis(PCA) and adaptive partition mutual information(AP-MI) estimation. PCA which is based on 2nd order statistics, is applied to prevent a overestimation by quickly removing the dependence between input variables. AP-MI estimation is also applied to estimate an accurate dependence information by equally partitioning the samples of input variable for calculating the probability density function. The proposed method has been applied to 2 problems for selecting the input variables, which are the 7 artificial signals of 500 samples and the 24 environmental pollution signals of 55 samples, respectively. The experimental results show that the proposed methods has a fast and accurate selection performance. The proposed method has also respectively better performance than AP-MI estimation without the PCA and regular partition MI estimation.

Generation and functional characterization of fluorescent, N-terminally tagged CB 1 receptor chimeras for live-cell imaging

N-terminally tagged CB 1 receptor fusion proteins, incorporating enhanced green fluorescent protein (GFP) or super-ecliptic pHluorin (SEP), were generated to study CB 1 receptor trafficking and cell surface receptor expression in live COS7 and HEK293 cells and hippocampal neurons. An artificial signal sequence (SS) was required for efficient surface expression of CB 1 receptor chimeras, which behaved like wild-type CB 1 receptors in functional assays. Treatment with cannabinoid ligands led to a rapid down-regulation of SS-GFP-CB 1 from the plasma membrane in COS7 and HEK293 cells, associated with trafficking into cytosolic vesicles. Activation of CB 1 receptors was also linked with a time-dependent reduction in cell surface SEP-CB 1 fluorescence and incorporation of the construct into acidic endosomes, revealed following exposure to NH 4Cl. In live hippocampal neurons, SEP-CB 1 fluorescence was largely restricted to the axon, consistent with its polarised surface expression. Thus, these new molecular tools are well suited for studying CB 1 receptor trafficking and a new generation of GPCR chimeras incorporating SEP at the N-terminus will be especially useful for monitoring dynamic changes in cell surface receptor expression in living cells.

Detrending moving average algorithm: A closed-form approximation of the scaling law

The Hurst exponent H of long range correlated series can be estimated by means of the detrending moving average ( DMA) method. The computational tool, on which the algorithm is based, is the generalized variance σ DMA 2 = 1 / ( N - n ) ∑ i = n N [ y ( i ) - y ˜ n ( i ) ] 2 , with y ˜ n ( i ) = 1 / n ∑ k = 0 n y ( i - k ) being the average over the moving window n and N the dimension of the stochastic series y ( i ) . The ability to yield H relies on the property of σ DMA 2 to vary as n 2 H over a wide range of scales [E. Alessio, A. Carbone, G. Castelli, V. Frappietro, Eur. J. Phys. B 27 (2002) 197]. Here, we give a closed form proof that σ DMA 2 is equivalent to C H n 2 H and provide an explicit expression for C H . We furthermore compare the values of C H with those obtained by applying the DMA algorithm to artificial self-similar signals.

Control of virulence factor expression in opportunistic pathogens using cyclodextrin immobilized gel

Cyclodextrins (CDs) could intercept a quorum sensing (QS) in Pseudomonas aeruginosa by trapping signal molecules for bacterial cell-to-cell communication systems. The QS in human pathogens is the cell density dependent system that regulates the expression of virulence determinants. The cellulose ether hydrogel immobilized with 2-hydroxypropyl-β-CD (HP-β-CD) was synthesized as an artificial QS signal receptor to develop a novel system for controlling the expression of virulence determinants in P. aeruginosa. Since the α- and β-CD could form inclusion complex with N-acyl-l-homoserinelactone (AHL) as the gram-negative bacterial QS signal in the culture solution, both AHL-mediated rhl and las quorum-sensing systems could be intercepted by CD. Inhibitory control of the rhlA transcription could cause to produce less pyocyanin in the presence of 5 mM soluble α- or β-CD in the liquid medium. Furthermore, production of the reporter enzyme β-galactosidase was meaningfully decreased in P. aeruginosa PAO1 (pQF50-lasB) containing lasB-lacZ transcriptional fusion when HP-β-CD immobilized gel was immersed in the culture solution to trap AHLs from the liquid medium. By adding the artificial AHL receptors to the culture medium, the expression of the QS-controlled genes could be remotely controlled from the outside of cells.